ASSESSING THE ROLE OF ATTENTIONAL ENGAGEMENT

AND ATTENTIONAL DISENGAGEMENT

IN ANXIETY-LINKED ATTENTIONAL BIAS

Patrick Clarke

BSc. (Hons)

MA

This thesis is presented for the degree of Doctor of Philosophy

School of Psychology

The University of Western Australia

2009

ii

ABSTRACT

It has consistently been found that individuals who are more highly vulnerable to

anxious mood selectively attend to emotionally negative stimuli as compared to those

lower in anxiety vulnerability, suggesting that such anxiety-prone individuals possess an

attentional bias favouring negative information. Two of the most consistent tasks used to

reveal this bias have been the attentional probe and emotional Stroop tasks. It has been

noted, however, that these tasks have not been capable of differentiating the relative role of

attentional engagement with, and attentional disengagement from emotionally valenced

stimuli, suggesting that either of these attentional processes could account for the

attentional bias observed in individuals with high levels of anxiety vulnerability on the

attentional probe and emotional Stroop tasks. A number of resent studies have claimed

support for the operation of biased attentional disengagement in anxiety using a modified

attentional cueing paradigm, concluding that individuals more vulnerable to anxious mood

have a selective difficulty disengaging attention from emotionally negative stimuli. The

current thesis highlights the possibility, however, that the structure of the modified cueing

paradigm could allow individual differences in initial attentional engagement with

differentially valenced stimuli to be interpreted as a selective disengagement bias. The goal

of research reported in this dissertation was to develop modified variants of attentional

probe and emotional Stroop tasks which would discriminate the role of biased attentional

engagement with and biased attentional disengagement from emotionally valenced stimuli

for individuals who differ in vulnerability to anxious mood. Results of experiments

employing modified variants of the attentional probe task did not reveal anxiety-linked

differences in spatially orienting attention to engage with the locus of differentially

valenced stimuli, or, anxiety-linked differences in spatially orienting attention to disengage

iii

attention from the locus of differentially valenced stimuli. These studies therefore provided

no evidence to support either the presence of an anxiety-linked bias in attentional

engagement or attentional disengagement. The modified emotional Stroop task employed

in the current research measured participant‟s ability to engage with the emotional content

of differentially valenced stimuli having initially processed non-emotional information

(stimulus colour), and measured their relative ability to disengage attention from such

emotional content to process non-emotional stimulus information. Results using this

modified Stroop task suggested that those with high vulnerability to anxious mood were

disproportionately fast to engage with the content of negative as compared to non-negative

stimuli whereas those with low vulnerability to anxious mood did not display this pattern.

The results provided no support for presence of an anxiety-linked bias in attentional

disengagement from the content of differentially valenced stimuli. Results derived from the

modified emotional Stroop task therefore provided support for the presence of an anxiety-

linked bias in attentional engagement with the content of emotionally negative stimuli, but

no support for a bias in attentional disengagement from the content of such material. The

final study in the present series of experiments was designed to address the novel

possibility that a bias in attentional disengagement could result in ongoing semantic

activation of negatively valenced stimuli which would not necessarily be indexed by

previous tasks assessing biased attentional disengagement. The results of this final study,

however, provided no evidence to suggest the presence of anxiety-linked differences in

ongoing semantic activation of differentially valenced stimuli. The present series of studies

therefore provide support for the presence of an anxiety-linked bias in attentional

engagement with the content of emotionally negative stimuli, while providing no support

iv

for the presence of an anxiety-linked bias in attentional disengagement from negative

stimuli.

v

ACKNOWLEDGEMENTS

I am deeply grateful to my supervisor Colin MacLeod for his perpetual, infectious,

and seemingly boundless enthusiasm which has sustained my motivation over these years.

For his patience and helpful guidance in developing my capabilities as a researcher, and

honing my skills in communication, I am eternally indebted and without this support I

would have struggled to reach this point.

My sincere thanks to Mike Anderson who was kind enough to read a draft of this

document and provide valuable feedback prior to its submission.

My gratitude goes to my office mates both past and present, Shane, Stewart, Dave

and Johnson, for providing the distraction and humor when it was necessary and being the

sounding board and filter for many ideas, with varying degrees of rationality, that occurred

during the completion of this dissertation.

To all the members of the Cognition and Emotion Lab that have come and gone

over the years, Russsel, Sian, David, Nicole, Helen and particularly Ed Wilson, for the

support they provided and the comfort gained from sharing this ride, and observing that

some do come out the other end.

I am eternally grateful to both my parents, Nigel and Sue Clarke, who have

nurtured my enquiry into the workings of the world from an early age and have always

encouraged me in my pursuit of education. I thank you both for you contribution to this.

And finally, to my partner, and soon to be wife, Kim Shirras, for her gentle

tolerance of my constant enquiry into the workings of the world, for her strength,

emotional support and encouragement in times of need, and for her patience over this long

journey, I am forever grateful.

vi

TABLE OF CONTENTS

ABSTRACT ....................................................................................................................... ii

ACKNOWLEDGEMENTS .............................................................................................. v

CHAPTER 1

INTRODUCTION .............................................................................................................. 1

Overview ..................................................................................................................... 1

Individual Differences in Anxiety Vulnerability ........................................................ 1

Cognitive Models of Anxiety Vulnerability ............................................................... 5

Experimental Support of the Association Between Attentional Bias to Negative

Stimuli and Anxiety Vulnerability ............................................................................ 10

Emotional Stroop Task and Attentional Bias ........................................................... 10

Attentional Probe Task and Attentional Bias ........................................................... 16

Does Biased Attentional Engagement or Biased Attentional Disengagement

Underpin Attentional Bias in Anxiety? ..................................................................... 21

Overview of Current Research Program ................................................................... 30

Summary ................................................................................................................... 32

CHAPTER 2

EXPERIMENT 1 ............................................................................................................. 34

Method ...................................................................................................................... 37

Overview .................................................................................................................. 37

Participants .............................................................................................................. 39

Materials .................................................................................................................. 40

Procedure ................................................................................................................. 44

Results ....................................................................................................................... 46

vii

Discussion ................................................................................................................. 53

CHAPTER 3

EXPERIMENT 2 ............................................................................................................. 65

Method ...................................................................................................................... 69

Overview .................................................................................................................. 69

Participants .............................................................................................................. 70

Materials .................................................................................................................. 71

Emotional Assessment Measure ............................................................................... 71

Procedure ................................................................................................................. 74

Results ....................................................................................................................... 75

Discussion ................................................................................................................. 79

CHAPTER 4

EXPERIMENT 3 ............................................................................................................. 84

Method ...................................................................................................................... 86

Overview .................................................................................................................. 86

Participants .............................................................................................................. 88

Materials .................................................................................................................. 89

Procedure ................................................................................................................. 92

Results ....................................................................................................................... 93

Discussion ............................................................................................................... 100

CHAPTER 5

EXPERIMENT 4 ........................................................................................................... 112

Method .................................................................................................................... 117

Overview ................................................................................................................ 117

viii

Participants ............................................................................................................ 119

Materials ................................................................................................................ 120

Procedure ............................................................................................................... 124

Results ..................................................................................................................... 124

Assessment of Biased Attentional Disengagement from Semantic Content ........... 126

Assessment of Biased Attentional Engagement with Emotional Content ............... 129

Discussion ............................................................................................................... 131

CHAPTER 6

EXPERIMENT 5 ........................................................................................................... 135

Method .................................................................................................................... 138

Overview ................................................................................................................ 138

Participants ............................................................................................................ 139

Materials ................................................................................................................ 140

Procedure ............................................................................................................... 143

Results ..................................................................................................................... 144

Assessment of Biased Attentional Disengagement from Semantic Content ........... 146

Assessment of Biased Attentional Engagement with Semantic Content ................. 148

Discussion ............................................................................................................... 152

CHAPTER 7

EXPERIMENT 6 ........................................................................................................... 162

Method .................................................................................................................... 168

Overview ................................................................................................................ 168

Participants ............................................................................................................ 169

Materials ................................................................................................................ 170

ix

Procedure ............................................................................................................... 173

Results ..................................................................................................................... 174

Analysis of Lexical Decision Latency Data ........................................................... 175

Analysis of Word-Naming Latency Data ................................................................ 177

Discussion ............................................................................................................... 181

CHAPTER 8

GENERAL DISCUSSION ............................................................................................. 189

Review of Research Findings .................................................................................. 189

Evidence for the Biased Attentional Disengagement account of anxiety-linked

attentional bias ....................................................................................................... 190

Evidence for the Biased Attentional Engagement account of anxiety-linked

attentional bias ....................................................................................................... 194

Theoretical Implications and Future Theoretical Research Directions ................... 196

Applied Implications and Future Applied Research Directions ............................. 211

Limitations of Present Research and Future Research Directions to Overcome

These ....................................................................................................................... 213

Concluding Comments ............................................................................................ 223

REFERENCES ............................................................................................................... 225

APPENDIX A ................................................................................................................ 240

APPENDIX B ................................................................................................................ 244

APPENDIX C ................................................................................................................ 246

APPENDIX D ................................................................................................................ 248

1

CHAPTER 1

INTRODUCTION

Overview

In this chapter the constructs of anxiety and anxiety vulnerability are first defined.

Recent causal theories of individual differences in anxiety vulnerability next are

discussed, with specific attention devoted to models implicating cognitive processing

biases in the development and maintenance of anxiety vulnerability. Research findings

from studies which have identified a link between vulnerability to anxious mood and an

attentional bias favoring the processing of negatively valenced material are then

reviewed, along with common methodological approaches used to assess this attentional

bias. The relatively new theoretical question which forms the basis of this thesis is then

considered: whether the observed attentional bias favouring negative stimuli reflects

biased attentional engagement with or biased attentional disengagement from negatively

valenced stimuli. Recent studies attempting to address this question are reviewed, along

with discussion of the methodological flaws inherent in the majority of these

experiments. Finally, an overview of the current research program is described.

Individual Differences in Anxiety Vulnerability

At any given moment we are likely to experience different levels of anxious mood

state depending on the situation we find ourselves in. It is also readily observable,

however, that some people display a more intense anxiety response to the same stressful

situation than do others. The level of anxious mood at any one time, and the propensity to

become anxious in response to a given situation, form the basis of a key distinction made

in anxiety research between state anxiety and trait anxiety (Endler, Edwards, Vitelli, &

2

Parker, 1989). State anxiety describes an individual‟s immediate level of anxious mood,

which can fluctuate from moment to moment in response to environmental stressors

(Spielberger, 1985). Trait anxiety on the other hand refers to a more stable dispositional

characteristic reflecting the degree to which an individual will elevate anxious mood in

response to environmental stressors (Endler, 1997; Jorm, 1989). Anxiety vulnerability

therefore corresponds to individual differences in trait anxiety while anxious mood refers

to an individual‟s current state anxiety. As the construct of trait anxiety is said to be

predictive of the frequency and intensity of an individual‟s state anxiety response to

stressful events, a strong association should exist between these two dimensions. Indeed,

research has consistently demonstrated that measures of state and trait anxiety are

commonly quite highly correlated (Bleiker, Pouwer, van der Ploeg, Leer, & Ader, 2000;

Czarnocka & Slade, 2000; Giacobbi & Weinberg, 2000). In examining long and short-

term factors associated with anxiety vulnerability, research has estimated that around

44% of the variance in state anxiety symptoms over the period of a year can be accounted

for by a measure of trait anxiety (Duncan-Jones, 1987).

Individuals with high trait anxiety are distinguished from those with lower trait

anxiety by the frequency and intensity with which they experience elevations in state

anxiety. Symptoms of state anxiety are commonly grouped according to their affective,

somatic and cognitive features. Affective characteristics of state anxiety commonly

include irritability and apprehension. Somatic features of state anxiety can include

general physiological arousal (increased heart rate and respiration), muscle tension,

exaggerated startle response and motor restlessness (Barlow, 2002). At its most extreme,

as in a panic response, individuals can experience nausea, chest pain, the sensation of

choking, sweating and trembling (American Psychiatric Association, 1994). Chronic

3

elevation of state anxiety, as observed in some anxiety disorders, can be associated with

symptoms such as sleep disturbance and tiring easily (Resick & Calhoun, 2001). The

cognitive features of state anxiety may consist of difficulty concentrating and biases in

cognitive processing such as selective attention favouring more negative/threatening

information. Cognitive characteristics associated with more extreme state anxiety

responses can include derealisation (feelings of unreality) and/or depersonalisation (being

detached from oneself; Resick & Calhoun, 2001).

The adaptive value of state anxiety responses to stress could broadly be

considered to reflect enhanced successful avoidance of potential dangers (Barlow, 2002).

Increasing state anxiety in response to an imminent threat is likely to motivate a

behavioural response that will eliminate or reduce the prospect of the threat negatively

affecting an individual. Adaptive anxiety could therefore be considered to serve an

anticipatory function in identifying and reducing the occurrence or impact of potentially

adverse events. Alternatively, maladaptive anxiety occurs when the anxiety response is

disproportionately high in relation to the potential threat, or when it is based on

misappraisal of the potential danger posed by a situation or stimulus. When these

distortions of anxious reactivity and/or perceived danger significantly impair an

individuals everyday functioning, such a condition will often attract diagnosis of a

clinical anxiety disorder.

Individuals who are higher in trait anxiety by definition experience more intense

and frequent elevations in anxious mood than do their low trait anxious counterparts. It is

unsurprising therefore that individuals with greater vulnerability to anxious mood have a

substantially increased risk of developing a clinical anxiety disorder (Eysenck, 1992).

Indeed elevated trait anxiety is a common feature of many anxiety disorders including

4

Generalised Anxiety Disorder (MacLeod & Mathews, 1991; Rapee, 1991), Panic

Disorder (Borden & Turner, 1989), Social Phobia (Chambers, Power, & Durham, 2004),

Post Traumatic Stress Disorder (Shalev, Freedman, Peri, Brandes, & Sahar, 1997; Sutker,

Bugg, & Allain, 1991), and Obsessive Compulsive Disorder (Apter, et al., 2003;

Scarrabelotti, Duck, & Dickerson, 1995). Long-term follow up of anxiety disorder

patients has also demonstrated that those individuals with higher levels of trait anxiety

pre-treatment have a poorer prognosis of recovery from such conditions (Chambers, et

al., 2004). While higher trait anxiety clearly acts as a risk factor for the development of

anxiety disorders, is has also been demonstrated that successful treatment of anxiety

disorders is associated with a decline in measures of trait anxiety (Chambers, et al., 2004;

Fisher & Durham, 1999).

While considerable differences exist between the presentation of various anxiety

disorders, the strong association between vulnerability to anxious mood and anxiety

pathology suggest that those who develop anxiety disorders commonly lie at the upper

end of the trait anxiety continuum. Research on the contribution of genetics to the

development of anxiety disorders provides further support for this assertion. Studies

examining the concordance rates of anxiety disorders and symptoms among first degree

relatives have consistently demonstrated that variance in the distinctive symptoms of

anxiety pathology is not strongly related to genetic factors (Tambs, 1991). What does

appear to be inherited, however, is a general vulnerability to anxious mood rather than a

specific susceptibility to developing a particular anxiety disorder (Kendler, Kessler,

Walters, MacLean, & et al., 1995). Therefore, despite variation in their symptomatology,

it is reasonable to suggest that a common variable in the development of anxiety

disorders is the dispositional characteristic of high trait anxiety. Therefore, a sound

5

understanding of factors associated with the maintenance of high trait anxiety is likely to

improve knowledge regarding appropriate preventative and treatment strategies, both for

individuals who suffer from anxiety disorders and those at risk of developing them.

Cognitive Models of Anxiety Vulnerability

Conceptions of anxiety vulnerability have evolved considerably in the last

century. Past theories often have strongly reflected the dominant explanatory models of

the time. In the late 19th

and early 20th

century, for example, Freudian theories were

commonly embraced as ways of understanding anxiety vulnerability. Freud proposed that

anxiety is the product of conflict between impulses arising from urges to satisfy physical

drives, and the desire to conform to internally embraced social expectation. These

theories were largely based on Freud‟s interpretations of clinical observations

(Rachmann, 1998). Later researchers criticised such psychodynamic accounts for their

lack of empirical basis, their loose evidence and their lack of methodological rigor

(Wolpe & Rachman, 1960). These theories gave way to behavioural models of human

functioning, which emphasised the role of learning experiences in the acquisition of

anxiety symptoms (e.g. Estes & Skinner, 1941; Pavlov, 1934; Wolpe, 1958). The

exclusive focus on observable behaviour became a point of criticism for behavioural

accounts of anxiety by the 1970‟s, with researchers challenging the capacity of

behavioural models to completely account for the range of anxiety symptoms and their

modes of acquisition (e.g. Ohman, 1979; Rachman, 1977). A number of influential

cognitive models of anxiety have since been proposed to account for the range of

symptoms observed in normal and pathological anxiety. These models emphasise the role

of information processing systems in the development and maintenance of anxiety

6

vulnerability. Three influential cognitive models of anxiety vulnerability are reviewed

below.

One cognitive account that has guided theoretical investigation into anxiety and

other dysphoric mood states is Bower‟s associative network model (Bower, 1981; Bower,

1987; Bower, et al., 1994). Bower‟s model conceptualises emotions such as anxiety as

being represented as „nodes‟ that are embedded within a cluster of related concepts

within long-term memory. Any particular emotion node is said to be connected to

emotionally congruent semantic information within this memory system via an

associative network. When an emotion is aroused, its node becomes activated; this

activation spreads from the emotion node to associated cognitive structures making

information contained in these structures more accessible to current cognitive operations.

Experiencing a particular emotional state will therefore partially activate, or prime,

emotion-congruent information in the cognitive system. This means that such information

will be more accessible for subsequent cognitive operations due to this sub-threshold

excitation.

While Bower‟s model focuses principally on the cognitive characteristics of state

anxiety, individual differences in trait anxiety can also be represented within this model.

The nature of the information connected to the anxiety node within the memory system,

and the relative strength of the connections between the anxiety node and this anxiety-

congruent information in the cognitive system will be dependent on the frequency and

intensity with which anxiety is experienced, and so the anxiety node is activated. More

frequent state anxiety responses will result in stronger connections between the anxiety

node and other anxiety-congruent information. This in turn will render those individuals

more prone to display anxiety-congruent biases in information processing when state

7

anxiety is elevated. One specific characteristic of elevated anxiety vulnerability that this

model predicts is a bias in attention, whereby a mild increase in state anxiety will cause

anxiety-prone individuals to disproportionately favour attending to anxiety-congruent

(negative/ threatening) information.

Another highly influential cognitive model of anxiety vulnerability is that of Beck

(1976; Beck & Clark, 1988; Beck, Emery, & Greenberg, 1985). While Beck‟s model was

constructed to specifically account for anxiety pathology, this theory is also readily

applicable to general anxiety vulnerability. Beck suggests that information processing in

anxiety is affected by schemata. Schemata are hypothetical cognitive structures that

represent exemplars of early life events stored in long-term memory. When in a given

situation, the particular schema relevant to the characteristics of that event is activated.

This schema is then used to interpret, classify and assign meaning to the event. Beck

suggests that individuals vulnerable to anxious mood possess maladaptive „danger

schemata‟, which developed during the processing of past events involving high levels of

personal danger. When activated, these schemata act to bias information processing in a

threat-congruent manner and will directly influence the content of an individual‟s

perceptions, interpretations, and associations in a ways that favour the processing of

negative stimuli and so exacerbate anxiety responses to stressful events or stimuli.

Therefore, according to this account, anxiety vulnerability is associated with

idiosyncrasies in high level cognitive structures that influence lower level cognitive

processes, such as attention. Like Bower‟s model, however, Beck‟s schema model also

predicts that individuals vulnerable to anxious mood will display a selective attentional

bias favouring the processing of emotionally negative stimuli.

8

A more recent cognitive model of emotional vulnerability which specifically

focuses on information processing has been proposed by Williams, Watts, MacLeod, &

Mathews (1988; 1997). This model makes a key distinction between the processes of

integration and elaboration, which operate on mental representations. Integration is said

to occur automatically and acts to strengthen the internal structure of a representation

such that the elements of that structure become more closely associated with one another.

Activation of any feature within a highly integrated structure will therefore result in

activation of the entire representation due to the close association between the features.

Highly integrated representations will therefore be more accessible to cognitive

processes. Being more accessible in this respect refers to mental representations coming

to mind more readily. Highly integrated representations will therefore be accessed more

rapidly and will have a lower threshold for activation because stronger internal

representation will lead to partial matches in the environment activating the entire

representation. Alternatively, elaborative processing is said to strengthen the associative

connections between different representations in memory. Increased strength in the

connections between distinct structures will increase the likelihood that activation of one

structure will also prime the recall of a linked structure making this information more

retrievable. Being more retrievable in this sense therefore refers to the relative ability to

recall information from long-term memory. As such recall is believed to occur through

associative pathways, highly elaborated representations will be more retrievable.

Williams et al. (1988; 1997) propose that anxiety vulnerability reflects the

increased integrative but not elaborative processing of anxiety-related representations.

Thus, high trait anxiety will be associated with enhanced accessibility, but not

retrievability, of anxiety-related representations, given that individuals more vulnerable

9

to anxious mood have more highly integrated representations for anxiety-related

information. The model predicts that the highly integrated representations of anxiety-

related stimuli for high trait anxious individuals will result in these individuals displaying

an attentional bias favouring the processing of more negative stimuli.

Despite differences in the mechanisms they implicate, each cognitive model

reviewed above makes the common prediction that vulnerability to anxious mood will be

associated with a bias in attention selectively favouring the processing of negative as

compared to non-negative stimuli. There now exists a considerable body of literature to

support the existence of an association between anxiety vulnerability and an attentional

bias favouring negative material, and this will be reviewed in detail below. Recently,

experimental investigations have questioned whether the attentional bias associated with

heightened anxiety vulnerability is characterised by enhanced engagement of attention

with negative stimuli, or, by impaired disengagement of attention from negative stimuli.

These alternative hypotheses will be referred to as the Biased Attentional Engagement

account, and the Biased Attentional Disengagement account respectively. The question of

which account best explains the pattern of attentional bias associated with elevated trait

anxiety forms the basis the current thesis. The following review of research that has

demonstrated a relationship between attentional bias to negative stimuli and elevated trait

anxiety highlights how these presently available findings are equally amenable to either

the Biased Attentional Engagement account, or Biased Attentional Disengagement

account, of anxiety-linked attentional bias.

10

Experimental Support of the Association Between Attentional Bias to Negative Stimuli

and Anxiety Vulnerability

A number of experimental approaches have been employed in research examining

the link between attentional bias to negative stimuli and anxiety vulnerability. Two of the

most common tasks employed in such research, which have consistently revealed an

association between attentional bias and anxiety vulnerability, have been emotional

Stroop task and attentional probe task. The majority of research using such tasks has

contrasted patterns of attention for high trait anxious or clinically anxious individuals,

with low trait anxious controls, to reveal differences in the degree of attention paid to

stimuli which vary in emotional tone. In addition to these group comparison studies,

research has also examined the capacity of attentional bias measures to predict

subsequent emotional reactions to stressful life events and, has explored the causal nature

of the relationship between attentional bias and anxiety vulnerability by investigating

whether the direct manipulation of attentional bias can serve to modify emotional

reactivity to stressful events. These experimental approaches, which have employed both

the emotional Stroop and the attentional probe task, will be reviewed in turn below.

Emotional Stroop Task and Attentional Bias

The emotional Stroop task is a widely used method of examining attentional

responses to negative stimuli in anxiety. This task is based on the original Stroop colour-

naming task (Stroop, 1935; 1938) in which the colour names were printed in different ink

colours. In this original task, participants were required to name the ink colour of words

while ignoring the word meanings. Stroop revealed that participants were consistently

slower to colour-name the ink of colour words when the word itself spelled a different

colour name than when the word spelled the same colour name, or than they were to

11

colour-name the same colours printed in squares. This effect was attributed to the

interference produced from having read the incongruous colour words in text. In a simple

adaptation of this task, Mathews and MacLeod (1985) replaced the colour words with

words that were negative or non-negative in emotional tone. As with the original task,

participants were required to name the ink colour on each trial while ignoring word

content. The relative colour-naming interference for negative as compared to non-

negative words was taken as a measure of the degree to which participants differentially

processed the semantic content of these stimulus words. Slowing to colour-name words

of a particular emotional valence would therefore suggest selective attention favouring

the content of these stimuli.

Using this emotional Stroop task, Mathews and MacLeod (1985) compared the

performance of individuals with a clinical anxiety disorder (Generalised Anxiety

Disorder - GAD) to that of non-anxious controls. They found that the GAD patients,

unlike control participants, were disproportionately slow to colour-name negative as

compared to non-negative stimulus words, suggesting that these individuals preferentially

attended to the content of the more negative stimuli. Subsequent research has produced

support for these findings, consistently demonstrating that patients with GAD are

disproportionately slow to colour-name negative words as compared to controls (Martin,

Williams, & Clark, 1991; Mogg, Mathews, & Weinman, 1989).

Experimental findings using the emotional Stroop task have not been limited to

populations with generalised anxiety disorder. A considerable body of literature has

amassed to indicate that clinically anxious individuals are disproportionately slow to

colour-name emotionally negative words, especially when relevant to their specific

domains of concern, as compared to non-anxious individuals. For example, individuals

12

who suffer from Panic Disorder show significantly longer latencies to colour-name

negative words concerning separation, physical harm or social embarrassment, relative to

normal controls (Ehlers, Margraf, Davies, & Roth, 1988). A similar effect has also been

observed for those who suffer from Post-traumatic Stress Disorder (PTSD). For example,

in a study comparing groups of individuals who were involved in a motor vehicle

accident (MVA) and either had, or had not developed PTSD, Bryant and Harvey (1995)

found that those who had developed PTSD demonstrated greater colour-naming

interference for strongly negative MVA related words as compared to those who had not

developed PTSD.

Patients who suffer from specific phobias also display greater colour-naming

interference on negative words relating to their feared situation or object. When

compared to controls, individuals with Social Phobia have been found to display greater

colour-naming interference on socially negative words (e.g. criticise) and negative words

describing physical responses to embarrassment (e.g. blushing; Spector, Pecknold, &

Libman, 2003). Those who suffer specific object-related phobias also show

disproportionately slow colour-naming for words relating to these stimuli. For example,

Watts, McKenna, Sharrock and Treize (1986) found spider phobics to be specifically

slowed to colour-name spider-related words relative to non-negative words. Furthermore,

their study also revealed that, following a desensitisation procedure, spider phobics

showed a marked selective decrease in colour-naming latencies for spider-related words,

suggesting that this bias is attenuated with successful treatment of the anxiety disorder.

The anxiety-linked interference effect observed on the emotional Stroop task is

not limited to clinical populations. Research using this same task confirms the presence

of biased attention favouring negative stimuli among high trait anxious members of the

13

general population. For example, MacLeod and Rutherford, (1992) demonstrated that

high relative to low trait anxious students displayed greater slowing to colour-name

exam-related negative words. Subsequent research using the emotional Stroop has

consistently produced support for an attentional bias which favors the selective

processing of emotionally negative material in high trait anxious individuals (e.g.

Eysenck & Byrne, 1992; Mogg, Kentish, & Bradley, 1993; Richards, French, Johnson,

Naparstek, & Williams, 1992; Rutherford, MacLeod, & Campbell, 2004).

Therefore results obtained from studies using the emotional Stroop task have

consistently supported the hypothesis that selective attention to negative stimuli is a

cognitive characteristic of high trait anxiety. There also is evidence to suggest that this

bias may mediate anxiety reactivity to stressful events. In a study designed to assess

whether this attentional bias is predictive of dysphoric responses to a subsequent stressful

life event, MacLeod and Hagen (1992) first assessed patients awaiting investigation for

potential cervical pathology using a number of traditional questionnaire measures and the

emotional Stroop task. They then assessed emotional reactions to a subsequent diagnosis

of such cervical pathology in those participants who later received such a diagnosis. They

found that the best predictor of the intensity of emotional distress elicited by this negative

life event was the degree of attentional selectivity to negative stimuli previously

evidenced by the emotional Stroop task. This was taken to suggest that the attentional

processing bias observed on this task may moderate emotional reactions to stressful

events.

As outlined above, there exists considerable empirical support for an anxiety-

linked attentional bias favouring the processing of negative material, as indexed by

slowing to colour name negative stimuli on the emotional Stroop task. It is unknown,

14

however, whether this bias reflects biased attentional engagement with the content of

negative stimuli or, biased attentional disengagement from the content of such stimuli. A

bias in either of these attentional processes can provide an equally plausible account of

the findings observed using this task. The attentional processes involved in performing

the emotional Stroop task could be considered in terms of distinct phases which allow for

individual differences in attentional engagement and disengagement to emerge at

different times. When a coloured word is first presented it is assumed that there is an

initial phase where some degree of stimulus processing occurs prior to any differential

processing of the stimulus content or colour. The second phase could then be considered

the point at which an individual has the opportunity to increase processing of the

emotional content of the stimulus by engaging attention with this stimulus dimension.

According to the Biased Attentional Engagement account, it is at this point that high trait

anxious individuals will demonstrate enhanced engagement with the content of negative

stimuli and the resulting increase in engagement will contribute to longer latencies to

colour-name negatively valenced words. The Biased Attentional Disengagement account,

however, suggests that high trait anxious individuals will not necessarily demonstrate

such preferential engagement at this point. Rather, this account predicts that it is after this

second phase, when an individual then has the opportunity to disengage from processing

the stimulus content to process stimulus colour that anxiety related differences will

emerge. The Biased Attentional Disengagement account suggests that during this third

phase high trait anxious individuals will have disproportionate difficulty disengage

attention from the emotional content of negative stimuli, resulting in slower colour-

naming latencies. The biased attentional engagement account, however, suggests that

there would be no anxiety-linked differences during this phase. Figure 1.1 summarises

15

the proposed amount of attention devoted to processing the content of negative and non-

negative words (indicated by the thickness of the line) implicated by the Biased

Attentional Engagement and Biased Attentional Disengagement accounts of anxiety-

linked attentional bias for high trait anxious individuals the at different stages of the

emotional Stroop task.

As can be observed, both accounts suggest equivalent low level initial processing

of negative and non-negative stimuli during the first phase. It is during the second phase

that the Biased Attentional Engagement account predicts differences will emerge with

high trait anxious individuals selectively engaging with the content of negative material

Biased

Attentional

Engagement

Account

Negative

Word

Non-negative

Word

1. Initial stimulus

processing

2. Opportunity to

engage

3. Requirement to

disengage

Negative

Word Biased

Attentional

Disengagement

Account Non-negative

Word

Figure 1.1. Pattern of attention implicated by the Biased Attentional Engagement and Biased Attentional

Disengagement accounts for high trait anxious individuals completing the emotional Stroop task. Line

thickness represents the amount of attention devoted to processing the stimulus at a given point.

16

while the Biased Attentional Engagement account predicts no differential engagement

during this phase. During the third phase the Biased Attentional Engagement account

predicts high trait anxious individuals will show equivalent disengagement from

processing negative and non-negative stimuli while the Biased Attentional

Disengagement account predicts that these individuals will have difficulty disengaging

attention from negative words in particular. It is evident therefore that results obtained for

the emotional Stroop task are amenable to either enhanced attentional engagement with

stimulus content or impaired disengagement from such stimuli for high trait anxious

individuals.

Attentional Probe Task and Attentional Bias

In the attentional probe task, developed by MacLeod Mathews & Tata (1986),

negative and non-negative words are presented simultaneously on a computer screen for a

short duration. On critical trials, a small probe is presented in one of the two locations

vacated by the previously presented words, and participants are required to process the

probe as quickly as possible. The latency to identify probes appearing in the vicinity of

negative or non-negative words provides an indication of attentional distribution in

relation to these stimuli. MacLeod et al. (1986) used this task to examine attentional

distribution in a group of GAD patients and matched normal controls. They found that

the GAD patients were significantly faster to discriminate probes presented in the vicinity

of negative words as compared to neutral words, while control participants showed the

reverse pattern, being slower to discriminate probes in the vicinity of negative words as

compared to neutral words. Subsequent findings consistent with this result have served to

substantiate the conclusions drawn by MacLeod et al. (1986), that clinically anxious

17

individuals selectively attend to the spatial locus of anxiety-related stimuli (Mogg,

Bradley, & Williams, 1995; Mogg, Mathews, & Eysenck, 1992).

Researchers employing this probe task methodology have revealed findings

consistent with an attentional bias favouring negative stimuli in other clinically anxious

groups. In a study examining patterns of attention on this task shown by patients with

social phobia and non-anxious controls, Musa, Lepine, Clark, Mansell, & Ehlers (2003)

found results consistent with the hypothesis that patients with social phobia selectively

attend to socially-negative words while controls attend away from such words. Research

using the probe methodology have also revealed patterns of probe discrimination

latencies suggesting an attentional bias for negative stimuli for individuals with PTSD (R.

A. Bryant & Harvey, 1997), Panic Disorder (Kroeze & van den Hout, 2000), and

Obsessive-Compulsive disorder (Tata, Leibowitz, Prunty, Cameron, & Pickering, 1996).

Attentional probe task support for an anxiety-linked attentional bias favouring

negative stimuli have not been restricted to individuals with clinical anxiety disorders and

studies consistently have revealed similar results for high trait anxious members of the

normal population. MacLeod & Mathews (1988) administered the attentional probe task

to a group of first year medical students selected on the basis that their trait anxiety scores

were either high or low. They revealed that individuals high in trait anxiety displayed a

heightened tendency to attend to negative material, while low trait anxious individuals

showed attentional avoidance of this material. Such findings have been well replicated,

with other investigations confirming on probe task variants, that high relative to low trait

anxious individuals selectively attend to the locus of emotionally negative as compared to

non-negative stimuli (Broadbent & Broadbent, 1988; Fox, 1993; Mogg, Bradley, &

Hallowell, 1994).

18

Recent research using a modified version of the attentional probe task has

provided direct evidence that attentional bias may causally contribute to trait anxiety

vulnerability. MacLeod, Rutherford, Campbell, Ebsworthy, and Holker (2002) were able

to demonstrate this by showing that the direct manipulation of attentional bias, achieved

using a training variant of the attentional probe task, served to modify the intensity of

anxiety reactions to a subsequent stressful event. This training variant of the probe task

was designed to encourage an attentional bias favouring either negative or non-negative

stimuli, by establishing a contingency between the position of the negative word and the

position of the probe. To train attention to negative stimuli, the contingency was such

that, across many trials, the probe always appeared in the vicinity of the negative word.

Conversely, to train attention to non-negative stimuli, the probe always appeared in the

vicinity of a non-negative word. After extended exposure to these training contingencies,

MacLeod et al. (2002) found that participants‟ came to consistently shift attention in the

direction encouraged by the training contingency. Furthermore, participants‟ affective

response to a subsequent stressor task revealed that the induction of these different

attentional biases served to modify the intensity of the emotional reaction, such that those

participants trained to attend to negative stimuli experienced a more intense emotional

reaction to the stressor than did those trained to attend to non-negative stimuli. The

observation that the manipulation of attentional bias using the probe task methodology

resulted in the modification of emotional reactivity to a stressful event provides

compelling support for the causal role of attentional bias in mediating anxiety

vulnerability.

The association between anxiety vulnerability and the allocation of spatial

attention observed in studies using the attentional probe task clearly supports the notion

19

that high trait anxious and clinically anxious individuals selectively attend to negatively

valenced stimuli. The observation that manipulation of attentional bias can causally

modify anxiety response to a stressful event further suggests that this attentional bias may

functionally mediate anxiety vulnerability. Nevertheless, despite this consistency of

findings using the probe task, the precise attentional process which gives rise to the

attentional bias favouring negative stimuli remains unknown. It is plausible that findings

using the attentional probe task can be accommodated either by the Biased Attentional

Disengagement account or the Biased Attentional Engagement account of anxiety-linked

attentional bias.

As with the emotional Stroop task, the dot probe task could be considered to

involve distinct phases where individual differences in attentional engagement and

disengagement can potentially emerge. When negative and non-negative words are

initially displayed in the dot probe task it is assumed that there is some initial degree of

equivalent pre-attentive processing of both stimuli. Following this, an individual may

then deploy attentional resources to one of the two stimulus words and therefore increase

attentional engagement with this attended stimulus. The Biased attentional engagement

account suggests that high trait anxious individuals will preferentially engage with

negative as compared to non-negative stimuli during this phase, thus decreasing the

latencies to identify probes appearing in this location and increasing latencies to identify

probes in the opposite location. The Biased Attentional Disengagement account predicts

that high trait anxious individuals will not preferentially attend to either negative or non-

negative material during this phase. This account instead suggests that it is during the

third phase, when the presence of the dot probe requires attentional disengagement from

the attended stimuli, that differences will emerge for high trait anxious individuals. It

20

should be noted that the need to disengage will only occur on half the trials. The Biased

Attentional Engagement account predicts that on those trials where the probe appears

opposite an attended negative word, high trait anxious individuals will be

disproportionately slow to respond due to their difficulty disengaging from this material,

while they will be faster to identify probes in the locus of negative material, due to the

absence of the requirement to disengage.

The predictions of the Biased Attentional Engagement and Biased Attentional

Disengagement accounts regarding the allocation of attention on the dot probe task also

map onto the pattern of attention depicted for high trait anxious individuals in Figure 1.1.

Thus, during initial processing in the first phase neither accounts predict differences in

allocation of attention across negative and non-negative material. When the opportunity

to selectively engage occurs in the second phase however, the Biased Attentional

Engagement account predicts enhanced engagement with negative stimuli while the

Biased Attentional Disengagement account predicts no difference in the allocation of

attention. When probe stimuli require attentional disengagement in the third phase, the

Biased Attentional Engagement account predicts equivalent disengagement for negative

and non-negative stimuli while the Biased Attentional Disengagement account predicts

greater ongoing processing of negative stimuli for high trait anxious individuals. The

observation that high trait anxious individuals are faster to identify probes appearing in

the locus of negative relative to non-negative words on the dot probe task could therefore

be either due to these individuals‟ tendency to rapidly orient attention to preferentially

engage with such stimuli, or, disproportionate difficulty disengaging from such stimuli.

The results of studies reviewed above demonstrating an anxiety-linked attentional bias on

21

the dot probe task can therefore be readily explained by either the Biased Attentional

Engagement or Biased Attentional Disengagement accounts.

Thus, while the emotional Stroop and attentional probe tasks have produced

considerable evidence for an attentional bias in anxiety, neither task is capable of

revealing whether this bias is associated with enhanced engagement with, or, impaired

disengagement from negative stimuli. The following section considers this relatively new

question regarding the role of attentional engagement and disengagement in anxiety-

linked attentional bias, and critically evaluates attempts to empirically resolve this issue.

Does Biased Attentional Engagement or Biased Attentional Disengagement

Underpin Attentional Bias in Anxiety?

Posner (1980; Posner, Inhoff, Friedrich, & Cohen, 1987) proposed that visual

attention can be decomposed into a number of critical component processes. Whenever a

shift in attention occurs, the first action is to disengage from the current focus of

attention. It has been suggested that degree of difficulty in performing this operation

relates to the processing demands occurring at the time of attentional disengagement

(Kerr, 1973; LaBerge, 1973). The second and third actions involve movement of

attention, before finally engaging with a new target respectively. Posner developed a

paradigm to assess these components of visual attention. In this task, attention was

initially directed to a locus by the presentation of a cue, such as the brightening of one

area of a screen. On the majority of trials (80%) the cue would accurately predict the

location of a to-be-identified target (valid trials) while on the remaining trials the target

would appear in the location opposite the initial cue (invalid trials). Posner et al. (1987)

found that targets were detected faster on valid trials as compared to invalid trials.

22

Slowing on invalid trials was attributed to costs of having to disengage from the cued

location, and engage with the target appearing in the opposite location.

In considering the discrete components which contribute to a shift in attention as

described by Posner, it is readily apparent that biased attention to negative material could

readily be affected by selectivity operating within either the engagement or

disengagement process. It is curious therefore, that relatively little research to date has

been devoted to determining which component of attention is implicated in the

processing of negative stimuli. An appreciation for the precise contributions of

engagement and disengagement in attentional bias could be considered fundamental to

understanding the nature of this bias and hence clearly identifying the crucial target of

curative change for interventions designed to remediate dysfunctional anxiety through the

manipulation of attentional bias. Thus, there are both theoretical and applied reasons for

investigating whether attentional bias in anxiety is characterised by enhanced engagement

with or impaired disengagement from negative stimuli.

In considering the theoretical implications of Biased Attentional Engagement and

Biased Attentional Disengagement accounts of anxiety-linked attentional bias, it worth

reflecting on the cognitive models of anxiety vulnerability previously outlined. Both

Beck‟s (1976) schema model and Bower‟s (1981) associative network model predict that

a number of processing biases will be associated with anxiety, including selective

attention to negative stimuli. While these models do not explicitly differentiate between

attentional engagement and disengagement in their predictions, the generality with which

they predict anxiety-congruent processing of negative information by high trait anxious

individuals suggests that they would anticipate both anxiety-linked enhancement of

attentional engagement with, and anxiety-linked impaired disengagement from, negative

23

stimuli. Williams et al.‟s (1988) integrative processing model, however, more specifically

predicts the enhanced detection of potentially negative information in high trait anxious

individuals. This model therefore implicates biased attentional engagement with negative

stimuli as underlying the pattern of attentional selectivity displayed by high trait anxious

individuals.

Identifying the specific attentional process which underpins anxiety-linked

attentional bias also has number of potential applied implications. As reviewed earlier,

research has demonstrated that measures of selective attention to negative stimuli have

proven to be the most accurate predictors of emotional reactions to later stressful life

events (MacLeod & Hagen, 1992). By resolving whether such anxiety-linked selective

attention reflects biased attentional engagement with or biased attentional disengagement

from negative stimuli, it would become possible to improve their assessment by

developing tasks specifically sensitive to that particular dimension of attentional

selectivity, thereby enhancing prediction of anxiety reactivity in ways that lead to

improved methods of preempting distress to adverse events by providing appropriate

support based on the accurate prediction of needs.

A thorough understanding of the processes which underlie attentional bias in

anxiety could also lead to the development of improved methods for therapeutically

modifying such attentional biases in individuals with anxiety pathology. Recent success

in experimentally modifying attentional bias, and consequently influencing anxiety

responses to a stressor (MacLeod et al., 2002), suggests that developing means to directly

alter attentional bias may have direct therapeutic implications in reducing anxiety

vulnerability. It could be anticipated that a task which acts to specifically modify the

precise attentional mechanism that directly underpins the attentional bias associated with

24

anxiety vulnerability would be most effective in reducing such anxiety vulnerability.

Clearly, therefore, revealing whether anxiety-linked attentional bias is characterised by

selective attentional engagement with or disengagement from negative stimuli is likely to

maximise the effectiveness of interventions designed to modify anxiety vulnerability

through the manipulation of attentional bias.

Despite the importance of this issue, few empirical studies have been devoted to

differentiating the roles of attentional engagement with and disengagement from

differentially valenced stimuli in the pattern of attentional selectivity evidenced by

anxious individuals. Furthermore, the limited existing work has been compromised by

methodological flaws in the tasks employed which raise concerns about their ability

employ the resulting findings to resolve the matter. One such study, which has attempted

to identify whether anxiety-linked attentional bias is characterised by biased attentional

engagement with, or biased attentional disengagement from, negative information, was

conducted by Fox, Russo, Bowles, and Dutton (2001). These researchers adopted a

modified version of Posner et al.‟s (1987) cueing paradigm to assess these processes. The

structure of this modified task was such that, on each trial, a negative or non-negative

word, acting as a directional cue, was presented to the right or left of a central fixation

point for a brief duration. The display was then cleared for a brief period and a target

probe was presented to the right or left of the fixation point for a brief duration. On the

majority of trials (75%) the word cue predicted the location of the target probe while on

the remainder, the target appeared in the opposite location to the word stimuli.

Participants were required to identify whether the target probe appeared in the right or

left screen location. On trials where the target appeared opposite the negative or non-

negative stimulus, participants who were higher in anxiety were slower to identify targets

25

when the cue was negatively valenced. The authors drew the conclusion that that the

presence of negative information influences the disengage process in anxious individuals.

A subsequent study using the same cueing paradigm also revealed a similar effect, in

another sample of high trait anxious participants (Fox, Russo, & Dutton, 2002). Based on

the results of these tasks Fox et al. (2001, 2002) have suggested that past research which

has demonstrated anxiety-linked attentional bias may have wrongly attributed this bias to

differential engagement and these past findings may instead be due to biased attentional

disengagement from negative stimuli.

When considering the results of this research it is worth pausing to reflect on the

structure of the task as employed in its original form, and how this was modified for use

in the studies described above. In adapting Posner et al‟s (1987) cueing task, Fox et al.

(2001, 2002) replaced a neutral cue, designed to direct attention to a particular locus, with

an emotionally valenced cue. In doing this, however, they potentially compromised

Posner‟s experimental manipulation designed to secure initial attention to this locus, as

the emotional valence of the stimuli could differentially influence the degree of initial

attention to this locus across individuals. The key problem is that the task is insensitive to

the possibility that the securing of initial attention varied across participants as a function

of the emotional valence of a cue. It is known that anxious individuals will exhibit

selective processing of negative stimuli, even when such stimuli are presented in a

manner that precludes conscious awareness (MacLeod & Rutherford, 1992). Therefore,

employing a stimulus known to elicit differences in attentional processing in a task

format where this cue is supposed to equivalently orient initial attention could be

considered incompatible.

26

While Fox et al.‟s modification of Posner‟s cueing task would seem a logical

means of assessing individual differences in attentional disengagement from valenced

stimuli, the problem with replacing Posner‟s neutral cue with an emotionally valenced

stimulus becomes evident when considering the possibility that an attentional bias may be

characterised by individual differences in attentional engagement with negative stimuli.

As discussed by Posner et al. (1987), any shift in attention involves disengagement from

the attended stimulus and engagement with a subsequent stimulus. In Fox et al.‟s

modified version of the cueing task, speed to respond to a target appearing in the uncued

location will be affected by individual differences in initial attentional engagement with

the cue, subsequent disengagement from the cue, and engagement with the probe target.

The measure of speed to process uncued targets will therefore be influenced by individual

differences in each of these stages. It is plausible that the degree to which participants

initially engaged with the cue stimuli, or indeed the probability that they engaged at all,

may depend on differences in anxiety vulnerability. As a result, it is possible that high

trait anxious participants‟ slowing to detect probes in the opposite location to negative

stimuli, which has been construed as evidence for an anxiety-linked impairment in

attentional disengagement from negative information, instead could have reflected

increased initial attentional engagement with the negative information by these

participants. The valenced cue in the modified version of Posner‟s task is therefore

performing the two incompatible functions of securing attention and differentiating

attentional response to an emotional stimulus. Thus, a key problem with using emotional

material to secure initial attention is that it compromises the conclusions that can be

drawn about attentional disengagement from emotionally valenced material.

27

Another problem with the modified Posner task becomes evident if you consider

the possibility that individuals who differ in vulnerability to anxious mood may also

differ in response times when negative and non-negative stimuli are present. It is entirely

plausible that anxious individuals may be slower to respond when negative as compared

to non-negative stimuli are presented. The emotional Stroop task is also susceptible to the

effect of general slowing in the presence of threat. MacLeod et al., (1986) highlighted

that the different pattern of responses observed across high and low trait anxious

individuals on the emotional Stroop task could simply reflect individual differences in

slowing in the presence of negative stimuli. The attentional probe task developed by

MacLeod et al., (1986) was designed to overcome this problem by always having both

negative and non-negative stimuli on the screen at the same time, thus controlling for any

general slowing in the presence of negative stimuli. By presenting only a single stimulus

at any one time, the modified version of the Posner task has reintroduced a potential

confound that had been overcome by the dot probe task.

In considering the pattern of effects observed using the modified attentional

cueing paradigm (Fox et al. 2001, 2002), it is quite possible that, when the potential

influence of slowing in the presence of negative stimuli is taken into consideration, the

pattern of effects could be due to differences in attentional engagement rather than

attentional disengagement. If anxious individuals do selectively engage with negative

stimuli on valid trials (where the negative cue appears in the same location as the

subsequent probe), the relative speeding to attend to such stimuli could be offset by

slowing to respond in the presence of negative stimuli, thereby negating any relative

differences in relative speeding to attend to these versus non-negative stimuli. Slowing in

the presence of threat for anxious individuals could also account for longer response

28

times of these individuals on invalid trials (where the negative cue appears in the opposite

location to the subsequent probe). Anxious individuals may be slower to respond to

probes in the opposite screen position, not because of a difficulty disengaging from

negative words but from a slowing to respond when such words are present. Indeed, a

recent study by Mogg, Holmes, Gardiner and Bradley (2008) directly assessed this

possibility. They employed a similar task design to Fox et al. (2001, 2002) but included a

baseline condition where participants did not relocate attention from an initial central

fixation where a negative or non-negative stimulus was presented prior to a probe being

presented in the same location. This condition was designed to measure any differences

in slowing in the presence of emotional stimuli in the absence of any shift in attention.

They found that when the relative slowing on these control trials was accounted for, high

trait anxious individuals were observed to be relatively faster to discriminate probes

appearing in the position of negative as compared to non-negative words. This study

clearly highlights that measures of both attentional engagement and disengagement on

the modified Posner task may be compromised by general effects of slowing in the

presence of threat.

A number of studies have been conducted using the same attentional cueing

paradigm employed by Fox et al (2001, 2002) and have consistently revealed that high

trait anxious individuals are slower to respond to probes appearing in the screen position

opposite negative as compared to non-negative words (Koster, Crombez, Verschuere,

Van Damme, & Wiersema, 2006; Yiend & Mathews, 2001). This effect has also been

observed for individuals with social phobia who are disproportionately slow to respond to

probes that appear opposite initially exposed socially negative words as compared to non-

negative words (Amir, Elias, Klumpp, & Przeworski, 2003). All these studies, however,

29

are compromised in the same way, by employing emotionally valenced stimuli as the

stimuli supposed to secure initial attentional engagement and by not controlling for

individual differences in slowing in the presence of differentially valenced stimuli. The

results of all of these therefore remain amenable to either the Biased Attentional

Engagement account or the Biased Attentional Disengagement account of anxiety-linked

attentional bias.

One study has used an alternative probe task variant to draw the same conclusion

as researchers using variants of the Posner task. Koster, Crombez, Verschuere, and De

Houwer (2004) presented participants with a number of trials each containing pairs of

words that could both be non-negative or comprised of negative and non-negative

members. On trials containing negative and non-negative words probes could appear with

equal frequency in the location of either the negative or the non-negative word. The study

found that on trials containing negative and non-negative words, participants were faster

to identify probes in the vicinity of negative words and slower to identify probes in the

vicinity of non-negative words. It was also observed that on trials containing both

negative and non-negative words, responding to probes in the vicinity of neutral words

was slower overall than when compared to response times to probes on trials containing

both neutral words. The authors attributed this effect to difficulty disengaging attention

from negative words on negative/non-negative word trials where probes appear in the

vicinity of non-negative words. The problem with this claim however is that it assumes

that, on trials containing negative and non-negative words, slowing to identify probes in

the vicinity of non-negative words is directly attributable to difficulty disengaging from

negative material. A number of equally plausible possibilities could also account for this

pattern of findings. For example, it is possible that this pattern of slowing to respond to

30

probes in the vicinity of non-negative words on trials also containing negative words,

may be due to selective attentional engagement with negative stimuli, resulting in slower

responses to process probes in the locus of neutral material, not because of a greater

difficulty disengaging attention from the negative information, but because of the

necessity to disengage more often as a result of their engagement bias favouring such

information. Therefore, as with prior attentional probe tasks, the results of this study are

amenable to either the Biased Attentional Engagement or Biased Attentional

Disengagement accounts of this attentional bias.

The existing research designed to differentiate the role of attentional engagement

and disengagement in anxiety-linked attentional bias has been compromised by a number

of methodological flaws. As has been highlighted, studies claiming to reveal biased

attentional disengagement from negative stimuli in anxious participants have employed

experimental tasks which permit the observed effects to be readily attributed to enhanced

attentional engagement with negative stimuli. Thus, the effects observed in past research

using attentional probe and emotional Stroop methodologies, and in more recent studies

seeking to specifically examine attentional engagement and disengagement, remain

equally amenable to either the Biased Attentional Engagement or Biased Attentional

Disengagement accounts of attentional bias in anxiety.

Overview of Current Research Program

The principal goal of the present research program was to employ experimental

tasks that will overcome the limitations of past approaches, in order to successfully

differentiate the contribution of attentional engagement and disengagement processes to

anxiety-linked attentional bias. As has been argued, to date no strong empirical evidence

31

has been presented to clearly favour one of these hypothetical accounts of selective

attention in anxiety over the other. The aim of the present series of experiments was to

investigate the Biased Attentional Engagement and Biased Attentional Disengagement

accounts of attentional bias in anxiety, using modified versions of tasks which have

consistently been successful in revealing attentional biases in anxiety in the past.

In order to accurately measure attentional engagement and disengagement, a

number of critical criteria must be fulfilled by an experimental task. First, it is necessary

for a task to provide a means of securing initial attention to an emotionally neutral cue.

Ideally, a measure of whether attention has been secured would also be included to verify

that attention was indeed directed towards this emotionally neutral cue at the start of each

trial. Secondly, the task must require participants to then shift their attention in relation to

emotionally valenced stimuli, and must provide a means of assessing the relative ease

with which these shifts occur. To reliably index attentional engagement, a task should

therefore secure initial attention with a consistently non-emotional stimulus, before

requiring an attentional shift to engage with a negative or non-negative stimulus,

providing a measure of the speed with which this shift occurs. Baseline trials where

negative or non-negative stimuli are presented with no requirement to shift attention

should also be included to control for any possible influence of general slowing in the

presence of differentially valenced stimuli. According to the Biased Attentional

Engagement account of anxiety-linked attentional bias, high trait anxious individuals will

be disproportionately fast as compared to low trait anxious individuals to shift attention

to negative stimuli, having initially been engaged with a non-emotional stimulus. In

contrast, to reliably index attentional disengagement, a task should equivalently secure

initial attention with negative or non-negative stimuli and then require attentional

32

disengagement from this stimulus to an alternative non-emotional stimulus. Again,

baseline trials where negative or non-negative stimuli are presented in the attended

location and no shift in attention is required will control for any general slowing in the

presence of differentially valenced stimuli. According to the Biased Attentional

Disengagement account of anxiety-linked attentional bias, high trait anxious individuals

will be disproportionately slow to shift attention to the non-emotional stimulus having

been initially engaged with a negative, as compared to non-negative stimulus.

The present series of studies fulfill these criteria, by developing novel variants of

both the dot probe and emotional Stroop tasks, and so meet the requirements necessary to

differentiate and accurately measure anxiety-linked biases in attentional engagement

with, and disengagement from, emotionally negative and non-negative stimuli.

Experiments 1, 2 and 3 were devoted to examining Biased Attentional Engagement and

Biased Attentional Disengagement accounts of anxiety-linked attentional bias in spatial

attention, using attentional probe task variants. Experiments 4 and 5 then proceed to do

the same with respect to non spatial aspects of attention by employing modified variants

of the emotional Stroop task to examine these engagement and disengagement processes.

The final experiment was designed to answer remaining questions regarding the nature of

attentional disengagement, arising from consideration of preceding task structure and

results of Experiment 5.

Summary

Cognitive models of anxiety have proposed that vulnerability anxiety is

characterised by a number of processing biases, including an attentional bias that favors

anxiety-related stimuli. A considerably body of literature has amassed to support the

33

presence of such an attentional bias in clinically anxious and high trait anxious

individuals. Resent research also indicates that this attentional bias may predict, and

make a causal contribution to, anxiety vulnerability. However, the tasks commonly used

to demonstrate anxiety-linked attentional bias have not been able to differentiate whether

this bias is characterised by enhanced engagement with, or impaired disengagement from,

negative stimuli. Recent research attempting to differentiate these alternative accounts of

anxiety-linked attentional bias has claimed support for the Biased Attentional

Disengagement account over the Biased Attentional Engagement account. However,

these studies have consistently employed assessment tasks that preclude the differential

assessment of these two hypothetical classes of attentional bias, and their findings can be

equally well accommodated by either the Biased Attentional Engagement or Biased

Attentional Disengagement hypotheses. The aim of the current series of studies was

therefore to overcome the methodological flaws present in past research, and to

discriminate the validity of the Biased Attentional Engagement and Biased Attentional

Disengagement accounts of anxiety-linked attentional bias using modified variants of

tasks which have successfully revealed an attentional bias in past research.

34

CHAPTER 2

EXPERIMENT 1

Both engagement and disengagement process are constantly in operation in day-

to-day attentional functioning. Therefore, the question posed by the current research is

not whether individuals who differ in anxiety vulnerability can engage with or disengage

from the locus of negatively valenced material, it is whether the attentional bias in

anxiety selectively affects the engage or disengage component of attention when

processing differentially valenced stimuli. The principal purpose of the first experiment

was therefore to determine whether anxiety vulnerability is characterised by enhanced

attentional engagement with or impaired attentional disengagement from differentially

valenced stimuli. These attentional processes were examined using an attentional probe

task variant.

As outlined in the general introduction, previous attempts to measure attentional

engagement and disengagement processes have used cueing paradigms supposed to direct

initial attention to negative and non-negative stimuli and have then measured the relative

ease with which participants can relocate their attention to a different spatial locus (e.g.

Fox et al., 2001; Fox et al., 2002; Yiend & Mathews, 2001). As previously highlighted, a

limitation associated with these tasks is that they have been premised on the assumption

that differentially valenced material would initially secure attention in a given locus to

the same degree for both high and low trait anxious participants. If we entertain the

possibility that individuals who differ in anxiety vulnerability also vary in their tendency

to initially engage with negative material, then the ability of these task to measure and

isolate attentional engagement and attentional disengagement processes is seriously

compromised.

35

In order to eliminate the reliance on this assumption of equivalent engagement

with differentially valenced stimuli that has formed the basis of previous tasks, two key

requirements were considered crucial in developing a probe task capable of measuring

attentional engagement and disengagement. The first was that the task should require all

participants to attend equally to the locus of differentially valenced stimuli, thus

controlling for potential individual differences in the tendency to spatially attend to such

stimuli on subsequent measures of engagement and disengagement. The second

requirement was that the task should include a performance measure capable of

confirming that attention indeed was secured in the initial location as required. By

including these additional requirements this new task should allow the isolation and

measurement of attentional engagement with and disengagement from negative and non-

negative stimuli.

The probe task variant used in the first experiment was conceptually similar in

format to MacLeod et al.‟s (1986) probe task. A critical difference between this task and

previous modified versions of Posner‟s (1987) cueing task (e.g. Fox et al. 2001, 2002),

was that a neutral cue acted to reliably secure attention to an initial locus. Furthermore,

the task did not rely on the probability of to-be-presented material appearing in a cued

location to secure attention. Initial attention was instead secured by requiring participants

to attend to a particular location in order to obtain information essential to the successful

completion of the task. This was achieved by briefly replacing an initial fixation cross,

indicating the locus that participants must initially attend to, with a stimulus cue that

participants must note the structure of (i.e. noting the structure of one of two different

arrows), and use to make their final decision on the trial. The presentation of this cue was

sufficiently brief to ensure that participants must be attending to the fixation location in

36

order to correctly identify the structure of the stimulus. The cue presentation was then

immediately replaced by a differentially valenced word (either negative or non-negative)

paired with a non-word, one appearing in the location vacated by the briefly exposed cue

and the other appearing in the other half of the screen. This display remained for a brief

duration before one of these letter strings was replaced with a probe stimulus that was

either structurally identical to, or different from, the initial cue stimulus. On half the

trials, the probe required participants to relocate their attention to the opposite screen

position to process its content while in the remainder, the probe was presented in the

initially attended locus. Participants were required to decide whether this probe was a

structural match or mismatch to the initial cue stimulus. Probe response accuracy

therefore provided a measure of whether participants were attending to the locus of the

probe and also confirmed that attention was initially secured in the locus of the stimulus

cue as required.

Critical trials on this task were those where the probe appears in the opposite

screen location to the initial cue requiring participants to relocate attention either toward

differentially valenced material (providing a measure of engagement) or away from such

material (providing a measure of disengagement). Trials on which the cue position and

probe position were the same therefore acted as a baseline measure for the trials where

cue position did not predict probe position. The Biased Attentional Engagement and

Biased Attentional Disengagement accounts both make different predictions about the

likely pattern of results. The Biased Attentional Disengagement account predicts that

high trait anxious participants will evidence greater slowing, as compared to low trait

anxious participants, when they are required to relocate attention away from the locus of

negative as compared to non-negative material to identify probes. Conversely the Biased

37

Attentional Engagement account predicts that high trait anxious participants will be faster

than low trait anxious participants to relocate attention to probes appearing in the vicinity

of negative as compared to non-negative words.

In summary, the aim of the first experiment was to determine whether differences

exist in attentional engagement with, and disengagement from, the locus of negative and

non-negative stimuli, for individuals who differ in vulnerability to anxious mood.

Introducing the requirement that participants must process the structure of the initial cue,

and a means of testing whether this cue has been processed, will allow the task to control

and verify the position of the participant‟s initial attentional fixation. By varying the

position of the initial cue, the subsequent probe, and the intervening lexical stimuli

presented in each location, the task will be able to measure anxiety-linked differences in

attentional engagement with and disengagement from negative and non-negative material

without the confounding influence of an emotionally valenced attentional cue. It was

therefore the goal of this first experiment to employ this new task to determine whether

the attentional bias, favoring the locus of more negative material for high trait anxious

individuals, represents enhanced engagement with, or impaired disengagement from the

locus of such material.

Method

Overview

The principal focus of the current study was to permit the measurement of the

relative speeding or slowing to attentionally engage with and attentionally disengage

from the locus of emotionally valenced words, in high and low trait anxious individuals.

To achieve this, a computer task was developed which required participants sometimes to

38

initially focus attention in the location of a word that varied in emotional valence (a

negative or non-negative word), and then to keep attention in the same locus, or shift

attention to where a non-word had appeared, in order to identify a probe presented in that

locus. At other times the task required participants to initially focus attention in the

location of a non-word and then to keep attention in the same locus or instead to shift

attention to the locus where an emotionally valenced word appeared in order to identify a

probe presented in that locus. The former type or trials yield information about the

relative difficulty disengaging attention from the locus of differentially valenced words

by comparing response latency across trials where participants are required to keep

attention in the same locus as such words, and trials where they instead are required to

move attention away from such words. In contrast the latter type of trials can yield

information about the relative ease with which attention can engage with the locus of

differentially valenced words by comparing response latencies across trials where

participants are required to keep attention in the locus opposite such words, and trials

where they instead are required to move attention toward such words.

The Biased Attentional Engagement hypothesis predicts that when probe

presentation requires that participants relocate attention to the position of these

differentially valenced stimuli, high trait anxious individuals will demonstrate

disproportionate speeding to identify probes appearing in the location of negative stimuli.

Alternatively, the Biased Attentional Disengagement hypothesis predicts that when

differentially valenced stimuli are presented in the initially attended locus, high trait

anxious individuals will show a disproportionately slow response to the probes that then

appear in the opposite location to negative words.

39

Participants

As the present series of studies wished to assess anxiety-linked differences in the

allocation of attention, it was desirable to select participants on the basis of differences in

vulnerability to anxious mood. Many previous studies examining individual differences

in anxiety vulnerability have employed median splits on anxiety measures as a means of

differentiating high and low trait anxious groups for comparison (e.g. Karch et al., 2008;

Rutherford, MacLeod, & Campbell, 2004; Hubert & de Jong-Meyer, 1992). An obvious

problem with using such a criterion, however, is that it involves the classification of

individuals in the mid-range of trait anxiety measures into high or low anxious groups.

Such classification will be dubious, however, due to the considerable role of

measurement error in determining whether an individual is allocated to a high or a low

anxious group. A better criterion, and one employed throughout the current thesis, is to

select individuals whose trait anxiety scores fall within the upper or lower band (e.g.

thirds) of a distribution of scores obtained from individuals belonging to a larger

population screened on measures of trait anxiety. This decreases the possibility of overlap

between groups and increases the likelihood that differences on measures of interest can

be attributed to true differences in anxiety vulnerability between groups. Many studies

which have successfully demonstrated anxiety-linked differences in attention have used

pre-screened distributions of non-disordered populations to guide sample selection of

individuals who differ in emotional vulnerability (e.g. Wilson & MacLeod, 2003; Mogg,

Mathews, Bird, & Macgregor-Morris, 1990). Such sample selection could be considered

more methodologically rigorous due to its reference to a larger screened population and is

the method adopted in the present series of studies.

40

To ensure participants differed in trait anxiety as required in the current study,

selection of participants was guided by the screening of 449 students using the trait

version of the Spielberger State-Trait Anxiety Inventory (STAI-T; Spielberger, Gorsuch,

Luchene, Vagg & Jacobs, 1983) in an earlier session prior to the commencement of the

study. Those individuals whose trait anxiety scores fell in either the upper third (at or

above 43) or lower third (at or below 36) of the distribution were considered eligible to

participate. Of the 48 participants who were recruited for this study, 24 were from the

lower third of the distribution and were designated the low trait anxious group, while the

remaining 24 were from the upper third of the distribution and were designated the high

trait anxious group. Of those in the high trait anxious group, six were male and 18 were

female (mean age 18.79 years) while the low trait anxious group consisted of, 10 males

and 14 females (mean age 19.00 years). The high and low trait anxious groups did not

differ significantly in terms of age, t(46) = 0.20, ns, and chi square analysis revealed that

the two groups did not differ significantly in terms of gender ratio, ²(1,47) = 1.50, ns.

Materials

Emotional Assessment Measure

Anxiety vulnerability was assessed using the trait version of the Spielberger State

Trait Anxiety Inventory (STAI-T), and participants also completed the state version of

this questionnaire (STAI-S; Spielberger et al., 1983) to reveal their level of anxious mood

state. The STAI is considered the most widely used questionnaire assessing trait and state

anxiety in the area of anxiety research (Keedwell & Snaith, 1996; Marteau & Bekker,

1992; Reiss, 1997). It also has well established reliability (Abdel-Khalek, 1989; L. L.

Barnes, Harp, & Jung, 2002) and validity (Dupuis, Perrault, Kennedy, & Lambany, 1991;

Sutker et al., 1991). The state section of the questionnaire is comprised of 20 items

41

designed to measure an individual‟s current anxious mood state (state anxiety). Total

scores on the STAI-S scales can range from 20 through to 80 with norms showing a mean

of around 40 with a standard deviation of 10. The trait section of the questionnaire is also

comprised of 20 items and is designed to measure the frequency and intensity with which

an individual experiences symptoms of anxiety to determine their general vulnerability to

anxious mood (trait anxiety). Total scores on the STAI-T can range from 20 through to

80 with norms similarly showing a mean of around 40 with a standard deviation of 10.

Stimulus Words

The task required differentially valenced stimulus words that would be perceived

by participants as either negative or non-negative in emotional tone. It was believed that

negative words would be considered most salient when of relevance to the type of

worries and concerns experienced by the participant population. To obtain a stimulus

sample, an initial pool of 182 candidate negative and 182 candidate non-negative words

was generated. These 364 words were compiled into a questionnaire to be rated according

to valence and relevance. A group of 14 undergraduates, drawn from the same population

as the experimental population, rated all words on a 7-point scale according to how

positive or negative they thought the word was (ranging from -3 “very negative” to 3

“very positive”) and rated negative words on an 11 point scale as to how relevant the

word was to their worries (ranging from 0 “not relevant at all” to 10 “very relevant”).

Negative words were first selected according to how relevant they were to

participant worries. Candidate words were deemed to be irrelevant if they were not rated

at least 5 on the relevance scale by multiple raters. From the surviving pool of candidate

negative words, the 48 which had the most negative rating were selected for use in the

study. To ensure that the non-negative words were indeed non-negative in tone, those that

42

had a valence rating of less than 0 were omitted. All non-negative words therefore had a

valence rating of equal to, or greater than 0. Such non-negative words were selected for

inclusion in a manner that ensured equivalency with the negative stimuli in terms of letter

length and frequency of usage (according to Kucera & Francis, 1967). The design of the

current study required that each negative and non-negative word be paired with a

stimulus that was structurally similar yet without meaning. A set of 96 length matched

non-words consisting of random letter strings was therefore created to serve this function.

The final stimulus set therefore comprised 96 words (48 negative and 48 non-negative),

each paired with a length-matched non-word (see Appendix A for stimulus words and

mean judge ratings of negativity and relevance). An addition set of 96 pairs of non-words

was also constructed for the exclusive use during practice trials.

Experimental Hardware

An Acorn Archimedes 5000 computer, with two-button response box and high

resolution monitor was used to present stimuli and record participants‟ probe

discrimination responses.

Experimental Task

The basic trial format was consistent across each trial presentation. A fixation cue

was first presented for a total duration of 450ms in either of two possible screen

locations. This cue consisted of a cross presented in either the upper or lower screen

location. This was then replaced for 150ms by the stimulus cue in the same screen

location (a stationary arrow facing either right or left). Immediately after the offset of the

stimulus cue, a word (negative or non-negative) and non-word pair was presented. These

two letter strings were presented vertically aligned in one of two screen locations

separated by 3cm on the vertical axis of the display which, at a viewing distance of

43

approximately 75cm, subtends around 2 of visual angle separation. This is consistent

with spatial parameters utilised in previous attentional probe tasks (e.g. C. MacLeod et

al., 1986). On half the trials the word was presented in the location vacated by the cue

while on the remaining trials the non-word appeared in this location. This verbal stimulus

display remained on the screen for 300ms. Following this, a visual probe (a stationary

arrow facing either right or left) was presented in either screen location, replacing the

letter string that occupied that space. The visual probe remained on the screen until the

participant made a response. The participant was required to determine whether the probe

stimulus exactly matched the cue stimulus in form (i.e. faced in the same direction) or not

(faced in the opposite direction), and their latency to make this response was recorded

together with accuracy. A “match” response required a right mouse click while a

“mismatch” response required a left mouse click. The participants‟ response terminated

the trial and the next trial began 1000ms later.

The entire task consisted of 768 experimental trials. During the task each stimulus

pair was presented once before any were repeated and across the 768 trials each

word/non-word pair appeared once in each of the 8 unique conditions resulting from the

nested combination of the three two-level factors of cue locus (cue word or cue non-

word), word valence (negative or non-negative word) and probe position (probe word or

probe non-word). The order in which the stimuli were presented was randomised within

these constraints. The eight different trial conditions generated by the combination of

these experimental factors are summarized in Figure 2.1. Cue position (top or bottom

screen location), cue stimulus (left or right facing arrow) and probe type (match or

mismatch with cue stimulus) was determined randomly within the constraint that each

occurred an equal number of times across the 768 trials. Three equally spaced, self-paced

44

rest periods were included in the task which occurred after the completion of every 192

trials.

Procedure

All participants were tested individually in a sound-attenuated cubicle. Upon arrival

participants first completed state and trait versions of the STAI questionnaire prior to the

commencement of the computer task. A brief description of the trial presentation was

provided to participants and they were informed that their aim in the task was to discern

as quickly as possible, without inaccuracy, whether the probe stimulus presented at the

end of each trial was a match or mismatch to the initially presented stimulus cue. The

importance of attending to the initial fixation cue was impressed upon participants,

highlighting that it was necessary in order to note the structure of the briefly presented

stimulus cue and therefore, to correctly complete the task of identifying a match or

mismatch between this and the probe stimulus. Prior to beginning the experimental trials,

each participant completed 96 practice trials where the letter strings presented were

comprised of only non-words generated for the use in practice trials alone. On these

practice trials, the fixation cue appeared with equal frequency in the top or bottom screen

location and the probe stimuli appeared in the same and opposite location to the cue with

equal frequency. Once the practice trials were completed and any additional questions

answered participants began the experimental task.

45

asdfasef

Figure 2.1. Eight trial combinations resulting from the experimental variables of word valence (negative or

non-negative) cue locus (word or non-word) and probe position (word or non-word), including stimulus

exposure durations. Initial cue position and match/mismatch between cue and probe shown randomly.

+

+

ONION

XHDVM

XHDVM

+

IVFKLZJID

CRITICISE

CRITICISE

+

EARS

RQBW

EARS

+

RQBW

EARS

EARS

+

LFGPQ

CRUEL

LFGPQ

+

XHDVM

ONION

XHDVM

Cue non-word

Negative word

Probe non-word

Engagement trial baseline

Cue non-word

Negative word

Probe word

Engagement trial

Cue non-word

Non-Negative word

Probe non-word

Engagement trial baseline

Cue non-word

Non-Negative word

Probe word

Engagement trial

+

CRUEL

LFGPQ

CRUEL

IVFKLZJID

CRITICISE

NONWORD

IVFKLZJID

NONWORD

Cue word

Negative word

Probe word locus

Disengagement trial baseline

Cue word

Negative word

Probe non-word locus

Disengagement trial

Cue word

Non-Negative word

Probe word

Disengagement trial baseline

Cue word

Non-Negative word

Probe non-word

Disengagement trial

Fixation Cue Stimulus Cue Word Stimuli Probe

450ms 150ms 300ms Remain until response

46

Results

A summary of participant characteristics taken at the time of testing, including

measures of state anxiety are provided in Table 2.1. In accordance with expected

requirements, the high trait anxious group scored significantly higher than the low trait

anxious group on the STAI-T at the time of testing t(46) = 13.23, p < .01. These scores

ranged between a minimum of 37 and a maximum of 63 with a mean of 50.71 (SD =

6.72) in the high trait anxious group, and from 23 to 38 with a mean of 29.54 (SD = 4.03)

in the low trait anxious group. It was also revealed that high and low trait anxious groups

differed according to state anxiety scores t(46) = 6.77, p < .01. While this is not

unexpected, given the close association between state and trait anxiety, it also means that

any differences observed between these groups could also be due to differences in state

anxiety. Correlational analyses are also conducted with measures derived from the

experimental task to assess the degree of association between these and state and trait

anxiety.

Table 2.1

Characteristics of participants in Experiment 1. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F

High Trait Anxious 50.71 (6.72) 42.54 (9.91) 18.97 (3.16) 6:18

Low Trait Anxious 29.54 (4.03) 27.50 (4.49) 19.00 (4.02) 10:14

All Participants 40.12 (10.02) 35.02 (10.75) 18.90 (3.58) 16:22

Eight different trial types were generated by the combination of the three

experimental factors of word type (negative or non-negative) cue locus (cue word or cue

47

non-word) and probe locus (probe word or probe non-word). Those trials where the initial

cue appeared in the locus of a word provide information regarding participants‟ ability to

disengage attention from differing word types by revealing the extent of slowing to

respond when the subsequent probe appeared in the opposite (non-word) location,

compared to when this subsequent probe appeared in the same (word) location. These

will therefore be referred to as attentional disengagement trials. Trials where the cue

appears in the locus of the non-word will instead yield information regarding speed to

engage attention with differing word types, again by revealing speed to respond when the

subsequent probe appears in the opposite location, which now will be the locus of the

word, compared to when this subsequent probe instead appears in the same (non-word)

location. These trials are therefore referred to as attentional engagement trials.

Overall accuracy on the probe discrimination latencies was high with participants

averaging 93.80% (SD = 6.51) across all trials. To minimise the influence of outlying

data points, median discrimination latencies for correct responses were calculated for

each experimental condition for each participant. As high numbers of incorrect responses

would suggest noncompliance with task instructions, it was inappropriate to include

participants with very low accuracy rates. Therefore, participants who failed to obtain

greater than 80% accuracy were excluded. This resulted in two exclusions, one each from

the high and low trait anxious groups. For the remaining participants, no overall

difference in incorrect responses were observed for the high and low trait anxious

individuals, F(1, 44) = 0.97, ns, and similarly, no group differences in incorrect responses

were observed across different trial types in the interactions described below. The probe

discrimination latencies in each experimental condition across the high and low trait

anxious participants are provided in Table 2.2.

48

Table 2.2

Mean probe discrimination latencies in milliseconds across experimental conditions and trait

anxiety groups. Standard deviations given in parenthesis.

Cue Locus Word Valence Probe Locus High Trait Group Low Trait Group

Word

(Attentional engage

trials)

Negative Word 622.82 (135.88) 661.30 (115.14)

Non-Word 628.70 (106.19) 690.65 (137.93)

Non-negative Word 600.43 (92.66) 659.78 (103.27)

Non-Word 636.30 (123.81) 686.74 (118.79)

Non-Word

(Attentional disengage

trials)

Negative Word 633.48 (109.00) 673.70 (115.19)

Non-Word 597.17 (116.72) 660.43 (107.90)

Non-negative Word 624.56 (109.42) 695.65 (121.56)

Non-Word 605.43 (112.52) 605.65 (119.81)

These data were subjected to a 2 x 2 x 2 x 2 mixed design ANOVA consisting of

one between group factor and three within group factors. The between group factor was

trait anxiety (high or low) and the three within group factors were cue locus (cue word or

cue non-word), word valence (negative or non-negative), and probe locus (probe word or

probe non-word). Both accounts under experimental test predict a significant four-way

interaction, however, each account differs in the predictions it would make about the

pattern of component three-way interactions across trials where the cue acts to secure

initial attention in the locus of words (attentional disengagement trials) versus trials

where the cue acts to secure initial attention in the locus of non-words (attentional

engagement trials) that will give rise to this four-way effect. Specifically, the Biased

Attentional Disengagement account predicts that the simple three-way interaction will be

49

restricted to attentional disengagement trials, where the initial cue acts to secure attention

in the location of words, whereby high trait anxious participants will show

disproportionate slowing to respond to probes in the opposite (non-word) location when

the initially fixated word is negative rather than non-negative in valence. The Biased

Attentional Engagement account, however, predicts that a three-way interaction will be

restricted to attentional engagement trials only, where the initial cue acts to secure

attention in the location of non-words, whereby high trait anxious participants will show

disproportionate speeding to identify probes appearing in the opposite (word) location

when the word appearing in that locus is negative in valence.

The analysis revealed a significant main effect of cue locus, F(1, 44) = 4.88, p

<.05, whereby all participants were faster to identify probes when the cue initially

secured attention in the locus of non-words (M = 642.34, SD = 16.22) and slower to

identify probes when the cue secured attention in the locus of words (M = 648.34, SD =

16.68). A significant 2-way interaction between cue locus and probe locus was also found

F(1, 44) = 46.73, p <.01. This interaction essentially reflects the fact that trials requiring

participants to relocate attention to the opposite screen position from the initially attended

cue locus resulted in longer latencies to identify probes. This was specifically

demonstrated in that all participants were faster to identify probes appearing in the

location of the word rather, than the non-word, if the initial cue had also been in the locus

of the word (M = 636.09, SD = 16.12) than if the initial cue had been the locus of the

non-word (M = 656.85, SD = 16.35); while they were faster to identify a probe in the

locus of the non-word if the initial cue had also been in the locus of the non-word (M =

628.42, SD = 16.32) than if the initial cue had been in the locus of a word (M = 660.60,

SD = 17.55).

50

The only other interaction to emerge from the four-way ANOVA was a

significant three-way between trait anxiety, word valence and probe locus F(1, 44) =

11.47, p <.01. This three-way interaction was observed to be comprised of a simple two-

way interaction for the high trait anxious group, who showed disproportionate speeding1

to process probes on trials where the word valence was negative and probes were

presented in the non-word (M = 612.93, SD = 22.70) as compared to the word locus (M =

628.15, SD = 25.09) while they showed disproportionate slowing on trials where word

valence was non-negative and probes were presented in the non-word (M = 620.87, SD =

23.54) as compared to the word locus (M = 612.50, SD = 20.02), F(1, 22) = 10.71, p

<.01. While this pattern of results was reversed for the equivalent two-way interaction

involving low trait anxious participants, who showed disproportionate slowing on trials

where the word valence was negative and probes were presented in the non-word (M =

675.54, SD = 24.72) as compared to the word locus (M = 660.54, SD = 22.47) while they

showed disproportionate speeding on trials where word valence was non-negative and

probes were presented in the non-word (M = 655.54, SD = 23.05) as compared to the

word locus (M = 684.67, SD = 23.89), this interaction did not reach significance (F(1, 22)

= 3.16, ns). The three-way interaction between trait anxiety, word valence and probe

locus is summarised in Figure 2.2.

The expected four-way interaction between trait anxiety, cue locus, word valence

and probe locus predicted by both the Biased Attentional Disengagement and Biased

Attentional Engagement accounts was not observed to be significant F(1, 44) = 0.11, ns.

Similarly, neither of the simple three-way interactions predicted by the Biased

1 Throughout this thesis focus will be on relative rather than absolute speeding. This is because it is

possible that absolute speeding may be affected by extraneous variables other than attentional bias. For

example, a general slowing for high trait anxious participants may be the result of a factor unrelated to

attentional bias, such as arousal which would not be of focal interest in the current research.

51

Attentional Disengagement and Biased Attentional Engagement accounts between trait

anxiety, word valence and probe locus for either the attentional engage trials (cue word

trials) and attentional disengage trials (cue non-word trials) were observed to be

significant (F(1, 44) = 1.38, ns and F(1, 44) = 3.13, ns respectively).

Figure 2.2. Three-way interaction between trait anxiety group (low or high), word

valence (negative or non-negative) and probe locus (probe word or probe non-word).

Although the expected group differences did not emerge for either the attentional

engage or attentional disengage trials it remains possible that associations may exist

between engagement and/or disengagement measures and state and trait anxiety scores.

Correlational analyses were therefore conducted to determine if such relationships were

present. Two indices were therefore computed, one each for attentional engage trials and

attentional disengage trials. For the attentional engage trials it was necessary to first

compute an index of speeding to process probes in the vicinity of words for negative and

Low Trait Anxious

660

664

668

672

676

680

Negative Non-Negative

Word Valence

Re

sp

on

se

La

ten

cy

(m

s)

High Trait Anxious

610

614

618

622

626

630

Negative Non-Negative

Word Valence

Resp

on

se L

ate

ncy (

ms)

Probe Word

Probe Non-Word

52

non-negative word trials. This was achieved by subtracting latencies to identify probes in

the vicinity of words from latencies to identify probes in the vicinity of non-words for

both negative and non-negative word trials. This resulted in two measures of speeding to

process words, one each for negative and non-negative word trials where higher scores

represent shorter response latencies to process probes in the vicinity of words as

compared to non-words. A single index of enhanced engagement with the locus of

negative relative to non-negative words was then computed by subtracting the measure of

speed to engage with negative words from the measure of speed to engage with non-

negative words. Higher scores on this enhanced engagement index therefore represented

disproportionate speeding to process probes in the vicinity of negative as compared to

non-negative words. The equivalent index was also calculated for attentional disengage

trials. This involved first calculating two measures of speed to disengage from the locus

of words, one each for negative and non-negative word trials. Latencies to identify probes

in the same locus of words were therefore taken from latencies to identify probes in the

opposite locus to words (non-words locus) to yield a measure of relative slowing to

disengage from the locus of words for both negative and non-negative word trials. A

single index of impaired disengagement from the locus of negative words was then

computed by subtracting the measure of slowing to disengage from the locus of non-

negative words, from the measure of slowing to disengage from the locus of non-negative

words. Higher scores on this index of impaired disengagement from negative words

represented disproportionate slowing to identify probes in the vicinity of non-words

having processed negative as compared to non-negative stimuli. Pearson‟s correlations

between the index representing impaired disengagement from negative words was not

observed to be significantly correlated with either state anxiety scores (r(46) = .12, ns), or

53

trait anxiety scores (r(46) = .18, ns). Similarly, correlations between the index of

enhanced engagement with negative words was not significantly correlated with either

state anxiety scores (r(46) = .28, ns), or trait anxiety scores (r(46) = .23, ns).

Discussion

The accuracy data in the current study provide encouragement that participants

were performing the task in accordance to expectations in securing attention in the

initially attended locus. As task performance accuracy could only be attained by noting

the structure of the initially attended stimulus cue, the high level of participant‟s accuracy

in matching cue and probe stimuli allows confidence that the stimulus cue provided an

effective means of securing attention to the initial locus. The main effect of cue position

also highlighted that securing participants‟ attention in the locus of words, as compared to

non-words, resulted in longer response latencies to process subsequent probes appearing

in either the same or opposite screen location. This result suggest that there was some

selective processing of word as compared to non-word stimuli with participants showing

a pattern of slowing to process probes after having attended to the locus of words. The

significant 2-way interaction between cue locus and probe locus, demonstrating that

probe discrimination latencies were slower when participants were required to relocate

attention to the opposite screen location to identify probes, as compared when probes

were presented in the cued location, also suggest that the requirement to process the

stimulus cue was a reliable means of securing initial attention. These results therefore

provide confidence that the task used in the current study reliably secured participants‟

initial attention in the desired location and having done this, should provide a measure of

54

the relative ease or difficulty relocating attention in relation to differentially valenced

stimuli to the locus of a subsequently presented probe.

Despite assurances that the task was functioning according to its designed purpose

of securing attention to an initial location and requiring participants to relocate attention

from or toward the locus of negative or non-negative stimuli, the results of the first study

provide little support for either the Biased Attentional Engagement or Biased Attentional

Disengagement accounts of attentional bias in anxiety. That is, results from the four-way

ANOVA provided no evidence that high trait anxious participants were

disproportionately fast, as compared to low trait anxious participants, to relocate attention

from the cue locus toward negative stimuli or, having been initially secured in the locus

of negative stimuli, being disproportionately slow to relocate attention away from this

spatial locus to identify a probe in the opposite screen location.

The current results would clearly run counter to the Biased Attentional

Disengagement account espoused by the research of Yiend and Mathews (2001) amongst

others (e.g. Fox et al., 2001; 2002). Their findings, demonstrating that anxious

participants were disproportionately slow to identifying probes appearing in the screen

location opposite initially presented negative material, appear inconsistent with the

current study‟s finding, that no significant differences in probe discrimination latencies

emerged across high and low trait anxious participants when relocating attention from the

locus of differentially valenced stimuli. The most direct implication of the current results

for the Biased Attentional Disengagement account therefore is that, when care is taken to

ensure that participants engage attention equally with the locus of an initially exposed

word, high and low trait anxious individuals do not evidence differences in the speed

with which they can relocate attention away from this material. The failure to

55

demonstrate a selective difficulty for high trait anxious individuals to disengage attention

from the locus of negative material under the current task conditions, therefore presents

as inconsistent with the predictions of the Biased Attentional Disengagement account of

anxiety-linked attentional bias. It must, however, be recognised that it is not possible to

dismiss the existence of such a bias based on the absence of findings in favour of this

hypothesis. Thus, while the current results provide no support for the Biased Attentional

Disengagement account it would be premature to rule out the existence of an anxiety-

linked disengagement bias based on the present findings.

Given that the current task allows us to be confident that participants‟ attention is

equivalently secured in an initial locus and, there is no evidence that high and low trait

anxious participants are differentially slow to disengage attention from the spatial locus

of negative or non-negative material, then this absence of a biased attentional

disengagement effect might implicate biased attentional engagement as the likely

mechanism underpinning the anxiety-linked attentional bias favouring negative stimuli.

The results of the current study however, also failed to demonstrate a pattern of biased

attentional engagement with the locus of negative stimuli for high trait anxious

participants. It was predicted that, if the group difference in trait anxiety is characterised

by biased engagement with negative material then, an interaction would emerge on trials

where attention is initially secured in the location of non-words and participants are either

required to remain in that locus or relocate attention to negative or non-negative words

appearing in the opposite screen location. No such interaction was demonstrated

however, suggesting that, having been secured in an initial locus, high and low trait

anxious participants did not significantly differ in the speed with which they then were

able to engage attention with the spatially removed locus of negative or non-negative

56

material. While the absence of support for the Biased Attentional Engagement account

could lead us to question the validity of this hypothesis, the absence of evidence for both

this and the Biased Attentional Disengagement account would suggest the possibility that

the present task may be in fact be insensitive to individual differences in attentional

engagement and disengagement. Therefore, as with the Biased Attentional

Disengagement account, while the present findings provide no support for the Biased

Attentional Engagement account they do not allow us to rule out the possibility that such

a bias exists.

The only higher-order interaction observed in the current study which involved

differences in probe discrimination latencies across trait anxiety groups, was the three-

way interaction between trait anxiety (high or low trait anxious), word valence (negative

or non-negative) and probe locus (word or non-word). While it did not involve cue locus,

and is therefore not informative in relation to attentional engagement and disengagement,

this interaction demonstrated valence-related differences in probe discrimination latencies

between high and low trait anxious participants. When considering that the removal of

the cue locus factor from the current task results in a close resemblance to original

versions of the probe task, with the simple presentation of two stimuli followed by a

probe appearing in the spatial locus of one of these two stimuli, the presence of such a

three-way interaction would seem fairly unsurprising. A three-way interaction between

trait anxiety group, valence and probe locus demonstrating that high trait anxious

individuals more rapidly processed probes appearing in the vicinity of negative as

compared to non-negative words would therefore be very consistent with findings of

previous probe tasks. However, the direction of the three-way interaction observed in the

current study was the opposite of this and runs counter to the expectations of traditional

57

probe tasks. This three-way interaction demonstrated that high trait anxious participants

were disproportionately slow to identify probes in the vicinity of negative as compared to

non-negative words and disproportionately fast to identify probes appearing opposite

negative as compared to non-negative words, while low trait anxious participants showed

the reverse pattern. The simple two-way interaction for the high trait anxious group was

independently significant while the two-way interaction for the low trait anxious group

was not. The most direct implication of this interaction for the high trait anxious group

suggests that these individuals preferentially attended away from the locus of negative

words while being more inclined to attend to the locus of non-negative words.

The three-way interaction observed in the current experiment clearly contradicts

past findings regarding attentional bias and anxiety. Prior research employing probe tasks

has consistently demonstrated that individuals more vulnerable to anxious mood evidence

an attentional bias favouring the locus of negative material as demonstrated by shorter

latencies to identify probes appearing in the locus of negative stimuli as compared to non-

negative stimuli (e.g. Broadbent & Broadbent, 1988; MacLeod et al., 1986; Mogg et al.,

1994). The results of the current study however highlight that high trait anxious

individuals were slower to process probes presented in the vicinity of negative words.

Such a pattern of findings would beg the question as to why the current task produced a

result which so starkly contrasts those obtained in previous probe tasks.

An obvious difference between the current and previous probe tasks is that

original versions of the probe task involved the simultaneous presentation of both a

negative and non-negative word on the screen at the same time. In considering how this

change could potentially affect participant responses, it will be recalled that the purpose

of presenting both negative and non-negative stimuli in the original probe task was to

58

yield a directional measure of attentional bias in relation to differentially valenced

stimuli. One reason for wishing to include both negative and non-negative words

simultaneously was that this that would control for any interference effects potentially

resulting from general slowing in the presence of negative material. While interference

effects have been relied upon to infer selective processing of negative material for high

trait anxious individuals in tasks such as the emotional Stroop (e.g. Mathews &

MacLeod, 1985), the presence of these effects in probe tasks compromise the ability of

such tasks to attribute differences in reaction times to selective attention to a given locus,

as discrimination latencies could also be influenced by general slowing in the presence of

negative words. Traditional probe tasks have been able to control for interference effects

by always presenting negative stimuli. In the current task however, it is possible that the

necessary inclusion of only a single, differentially valenced, stimulus word on each trial

has exposed the task to the potential influence of interference effects in response to the

presence of specific stimulus types.

In considering how the presence of interference effects could account for the

apparently contradictory finding in the current study, which suggest that high trait

anxious individuals selectively attend away from, rather than toward negative stimuli, it

is necessary to distinguish potential differences in types of interference. Interference

paradigms, such as the traditional Stroop and emotional Stroop involve semantic

interference where individuals are distracted by the meaning of the stimulus causing a

slowing in task performance. An alternative type of interference can also arise when the

presence of particular salient stimuli causes an individual to become emotionally aroused

or anxious and this in turn impairs or enhances task performance (depending on the

difficulty of the task and the level of arousal experienced). In considering how

59

interference effects may have influenced the pattern of findings in the current study, it is

possible that the presence of negative words appearing in the same spatial locus as probes

resulted in greater interference for high trait anxious participants in the current study due

to their tendency to selectively process word content rather than probe information, thus

contributing to longer latencies to perform the task of matching probe and cue stimuli.

The possibility that individuals may have been differentially processing material in an

attended locus also highlights an issue salient to the current research that will be returned

to later in the discussion. This interference effect of slowing in the presence of negative

material would not however account for the fact that high trait anxious individuals also

evidenced speeding to process probes appearing in the screen location opposite negative

stimuli. It is possible that an arousal-mediated interference effect could account for such a

pattern of findings if the presence of negative stimuli increased arousal such that the

processing of negative stimuli interfered with performing the task of probe discrimination

in the same spatial as this material however, the heightened arousal resulting from the

presence of negative stimuli resulted in speeded processing of stimuli in the opposite

screen location. While such an arousal-mediated interference would appear possible,

results of past attentional probe studies would tend to refute the presence of a locus-

specific interference effect where the presence of negative material acts to slow

processing of probes in the same spatial locus as negative stimuli while speeding the

processing of probes appearing in the location opposite negative stimuli. Therefore, while

the task structure in the current study would potentially allow interference effects to

emerge, it would appear unlikely that simple interference effects or arousal-mediated

interference effects could account for the pattern of findings observed.

60

An alternative possibility which could go some way to accounting for the pattern

of findings observed in the present study is that the temporal characteristics of the task

allowed for unmeasured shifts in attention. It is possible that the 300ms presentation of

differentially valenced and non-word stimuli, following presentation of the stimulus cue

and prior to the probe being revealed, could have allowed sufficient time for participants

attention to relocate. It is possible therefore that unmeasured shifts in attention occurring

within this window could have contributed to the present unexpected findings. This

underscores the potential problem of assumptions regarding stimulus presentation times.

Specifically, for a task wishing to assess individual differences in the allocation of

attention, fixed intervals of stimulus presentation could allow such individual differences

in attentional deployment during such fixed intervals to go unnoticed, or interact with

task parameters to produce results which are not representative of the true pattern of

attention. This issue is addressed in later studies by including in tasks the requirement

that participants respond to stimuli presented at various stages rather than any

assumptions about attentional deployment within specific exposure durations.

Having earlier highlighted the possibility that individuals may differentially

processing the meaning of valenced material, it is worth pausing and reflecting on the

implication of this for conclusions that can be drawn regarding allocating attention to a

spatial location, as distinct from the issue of attending to the content of stimuli appearing

in that location. In the current study, as with prior probe tasks, we have been primarily

interested in examining the orientation of attention to the spatial locus of negative and

non-negative stimuli. The suggestion that individuals may differ in the degree to which

they process the meaning of a given stimulus highlights the possibility that attending to

the spatial locus of a particular word does not necessarily involve attending to the content

61

of that word. Both the current and previous probe tasks allow conclusions to be drawn

only about the spatial locus of attention, though such conclusions have previously always

been premised on the assumption that attending to a spatial locus implies attending to the

content of the information appearing in that locus. If we entertain the alternative

possibility, that making decisions about probes in a spatial locus may not require

attention to the content of verbal material in that locus, then this carries implications for

both the current and previous probe tasks. In relation to the current study, the task

allowed confidence only that participants were initially attending to specific spatial loci

but still permitted the possibility that participants differentially processed the content of

the stimulus presented in these spatial loci. When processing cues or probes, we can be

certain that participants were attending to their spatial location and to the probe or cue

information in order to correctly discriminate these stimulus types but cannot be certain

they were attending to the content of stimuli occupying these locations.

The main effect of cue locus observed in the current task would, however, suggest

that there may have been some processing of stimulus word content. This main effect

demonstrated that all participants were faster to discriminate probes when the cue secured

initial attention in the locus of words as compared to non-words. The presence of this

effect could counter the suggestion that participants were potentially not processing word

content. It is possible, however, that participants may have engaged in some level of

processing that was sufficient to discriminate between words and non-words but may not

have been sufficiently deep, or consistent, to reliably produce processing of word content.

Participants may therefore have processed some, more salient words during the task but

may not have been reliably processing word content. An alternative possibility is that the

main effect observed in the current study between words and non-words was not due to

62

differences in processing meaning but instead because word stimuli formed

graphemically legitimate letter strings while non-words did not. Indeed it is possible that

that participants could discriminate words form non-words on the basis of graphemic

legitimacy without having to process word meaning at all. For example, people presented

with an unfamiliar word, such as „vellum‟, and a graphemically illegitimate letter string,

such as „uxhdvm‟, are likely to perform well above chance in deciding which of these

two strings are real words despite the fact that few would be readily able to identify the

meaning of the former word (being a parchment written on animal skin). It is therefore

possible that participants may not have been processing word content in the current study

but instead responding to the difference in graphemic legitimacy between words and non-

words.

Based on the rationale outlined above, the results of the present study allow us to

conclude that, when attention is initially secured in the spatial location of differentially

valenced stimuli, high and low trait anxious individuals do not differ in the speed with

which they can relocate attention to a spatially removed location. Similarly, we can

conclude that, when attention is initially secured in the spatial locus of non-words, high

and low trait anxious participants do not evidence differences in the speed with which

they can relocate attention to the spatial loci of negative and non-negative words. Based

on the distinction identified between attending to a given locus and processing the

content of material presented in that locus however, the current task does not allow us to

draw conclusions about attentional disengagement from the locus of semantically

processed negative and non-negative words, or attentional engagement with the semantic

content of spatially removed negative and non-negative words. In the current task, the

method of ensuring equivalent processing of initially attended material in order to assess

63

biased attentional disengagement or, of requiring subsequent engagement with word

content to examine differences in attentional engagement with such material may not

have met the objective of ensuring equivalent processing of stimulus content.

This raises the possibility that the current task may be insensitive to individual

differences in disengagement due the fact that, having been secured in the same spatial

locus, high and low trait anxious individuals either did not process the semantic content

of the differentially valenced stimulus in that location, or differences in the degree of

initial engagement with the stimulus content negate differences in the speed to identify

spatially removed probes such that no overall differences in probe discrimination

latencies emerge. Similarly, with attentional engagement, it is possible that relocating

attention to the locus of negative and non-negative stimuli did not involve the processing

of these stimuli, or, that differences across high and low trait anxious individuals in

speeding to the locus of differentially valenced stimuli is negated by differences in

processing the content of these stimuli.

To provide greater assurance that individuals are equivalently processing the

content of an initially presented stimulus, or are relocating attention and processing the

meaning of a stimulus in a spatially removed locus, a refinement of the current

methodology is required. In order to measure the ease with which individuals can

spatially disengage from attending to differentially valenced semantic information, it

would be necessary to provide them with an initial task which provides assurance that

they are indeed attending to the semantic content of the word stimuli presented.

Similarly, in order to measure the speed with which individuals engage attention with

differentially valenced semantic information, it is necessary to employ a task that

measures the speed of moving to process the semantic content of the word stimuli. These

64

requirements will be met across the next two experiments, of which the first (Experiment

2) examines relative speed to disengage attention from the locus of material that

participants are processing the semantic content of, while the second study (Experiment

3) examines speed to engage attention with the semantic content of material presented in

a locus participants are not initially attending to.

In summary, while the task employed in the current study demonstrated its

capacity to secure attention in an initial locus and measure the speed of shifts in spatial

attention toward or away from the locus of differentially valenced stimuli, it has revealed

no evidence of anxiety-linked differences in biased attentional engagement or biased

attentional disengagement from the content of differentially valenced stimuli. A potential

reason for this has been identified in the limitations of using a probe methodology to

secure engagement with the semantic content of initially presented stimuli or to measure

the speed with which attention can move to engage with the semantic content of spatially

removed stimuli. The possibility that participants may differentially process the content

of stimuli in an equally attended locus highlights the need to ensure equivalent processing

of such information when measuring biased attentional engagement with and

disengagement from negative and non-negative words. Studies two and three therefore

include these necessary task requirements to measure biased attentional disengagement

from the locus of semantically processed stimuli and biased attentional engagement with

the locus of semantically processed stimuli respectively.

65

CHAPTER 3

EXPERIMENT 2

Traditionally, research into attentional bias in anxiety using probe task

methodologies has not drawn the distinction between attending to a specific locus and

processing the content of information in that locus, tending to assume equivalence

between these two factors. Such a distinction becomes important however when

attempting to isolate and measure engagement and disengagement components of

attention. In relation to the measurement of disengagement, differences in, or the

potential lack of, processing of information in an attended locus can compromise

conclusions about the relative difficulty with which individuals can subsequently

disengage their attention from such information. In principal, it is possible that

differential processing, or a lack of processing, material presented in an initially attended

spatial locus could give rise to apparent disengagement effects when none in fact exist or,

alternatively, could obscure disengagement effects that do actually exist.

If individuals were to differentially engage with the semantic content of material

in an attended spatial locus, it is possible that measures of speed to disengage from such

material would reveal the cumulative effects of slowing resulting from variations in

initial engagement with the content of the material. Any subsequent slowing resulting

from selective difficulty disengaging attention from that stimulus to a spatially removed

locus would therefore also be influenced by individual differences in greater levels of

initial engagement with the content of the stimulus. Alternatively, it is possible that an

individual may possess a selective difficulty disengaging attention from stimuli of a

particular valence, but such a bias does not manifest when performing a task where there

is no advantage to initially process such material. A selective difficulty to spatially

66

disengage attention may therefore not manifest if a task does not require participants to

process the content of information presented in an initially attended locus. Conceptually,

the same issues arise in the measurement of biased attentional engagement when

considering potential discordance between engaging with a spatial locus and engaging

with the content of the material presented in that locus. This issue will be returned to in

Experiment 3.

The task employed in Experiment 1 provided a means of ensuring that

participants were equivalently attending to an initial locus and demonstrated that when

this is controlled, no anxiety-linked differences in attentional disengagement are

apparent. This result would suggest that past findings which have demonstrated

disproportionate slowing of high anxious individuals to relocate attention away from the

locus of negative stimuli (e.g. Fox et al., 2001; 2002; Yiend & Mathews, 2001), may not

be due to impaired disengagement from such stimuli. While the results of the first study

demonstrated that controlling the initially attended locus eliminates biased attentional

disengagement effects, the possibility remains however, that differences in attentional

disengagement could emerge when a task involves equivalent semantic processing of

negative and non-negative information before requiring participants to relocate attention

to a spatially removed locus. The key aim of the present study was therefore to examine

whether anxiety-linked differences in biased attentional disengagement from the locus of

negative and non-negative stimuli will emerge when equivalent processing of the

semantic content of such stimuli is ensured.

While the task used in the first study was able to provide certainty only that

participants were initially attending to a predetermined spatial locus, the aim of the

current study required that the task ensure participants equivalently engage with the

67

semantic content of the stimuli in the predetermined initial spatial locus. Ideally, the task

would require that individuals engage with the word‟s meaning and having done so,

provide a measure to verify that this has occurred. A number of methods have been used

in the past to ensure individuals process the semantic content of stimulus words including

word-naming, lexical classification (classifying a target letter string as a word or non-

word) or grammatical judgment (classifying a word according to its part of speech). It has

been demonstrated however that word-naming does not necessarily require an individual

to process the meaning of named words and this can occur through the execution of

simple grapheme to phoneme conversions (Joubert & Lecours, 2000). Word-naming

would not therefore be considered an appropriate means of ensuring participants attempt

to access the meaning of a stimulus. While the process of grammatically judging a word

necessarily involves first identifying its semantic meaning, the process of classifying the

word according to its part of speech (e.g. verb, noun, adjective) may involve post-lexical

processing beyond simply accessing meaning. Alternatively, a lexical decision task can

be performed more easily. However, past theories have suggested that identifying the

lexical status of a word may not necessarily require that an individual access its meaning

(Meyer & Schvaneveldt, 1971). It has subsequently been argued however that a lexical

decision task can only be performed by accessing the representation of a word, which in

turn includes its associated semantic meaning (James, 1975; Schvaneveldt, Meyer, &

Becker, 1976). The current task therefore employed a lexical decision component to

ensure participants accessed the semantic meaning of word stimuli.

A lexical decision task will only ensure that participants attempt to access the

semantic meaning of words when the difference between these word stimuli and non-

word foils is limited to the meaningfulness of the word stimuli. That is, participants may

68

not attempt to access the semantic representation to decide if a particular stimulus is a

word if they are able to make such a decision based on another difference between the

stimuli, such as graphemic legitimacy. It is necessary therefore for non-word stimuli to

also be graphemically legitimate, thus eliminating this as criteria on which to base lexical

decisions. The current study therefore included a lexical decision component to ensure

equivalent semantic processing of target stimuli across participants. Including the

requirement that participants initially determine the lexical status of word stimuli ensures

that they must attend to the word or letter string, access the semantic representation

attached to it, and respond accordingly. Performance of the task thus ensures that a string

has been processed for meaning, while accuracy provides reassurance that an individual

has successfully attempted this.

A modified version of the task used in the first study was therefore constructed

with the added inclusion of an initial lexical decision component. The current task

therefore directed attention to the locus of one of two letter strings by presenting a cue (a

small cross) in one of two locations. The cue was then replaced by a valenced word

(negative and non-negative word) paired with a non-word, one appearing in the location

previously occupied by the cue and the other appearing in the other screen location.

Participants were required to determine the lexical status of the string appearing in the

same locus as the initial cue. Immediately following this response participants were then

required to determine the identity of a simple probe stimulus, which appeared with equal

frequency in either the same or opposite location to the lexical decision string. Critical

trials on the current task were those where the lexical decision target was a negative or

non-negative word and probes were presented in the opposite screen position to the initial

fixation. These trials therefore required participants to process the semantic content of a

69

negative or non-negative word before then being required to spatially relocate attention

away from this stimulus in order to identify the probe. Trials on which the lexical

decision target was a negative or non-negative word and participants remained in the

initially attended locus therefore acted as a baseline for these trials. If attentional bias in

anxiety is characterised by impaired disengagement from the locus of semantically

processed negative stimuli, then it follows that high trait anxious participants should be

disproportionately slow to relocate attention away from the locus of negative, as

compared to non-negative stimuli, to identify probes appearing in the opposite screen

location.

Method

Overview

To meet the additional requirements of the second experiment, a modified version

of the probe task used in the first study was employed. This modified task again directed

attention to an initial locus with a briefly presented cue. The function of this cue,

however, was slightly different from the first study, as it instead signaled the location of

the subsequently presented letter string that participants were required to determine the

lexical status of. As with the first study, a differentially valenced word (negative or non-

negative) paired with a non-word was always presented simultaneously, one appearing in

the location of the cue and one in the opposite screen location. Participants were required

to make a lexical decision about the letter string appearing in the location of the cue,

classifying it as either a word or non-word, and were then required to identify a probe

that subsequently appeared either in the same locus, or in the alternative locus. Critical

trials were those on which participants were first required to determine the lexical status

70

of negative or non-negative words. On half of these trials participants were then required

to relocate attention to the opposite screen position (move locus trials), providing a

measure of difficulty disengaging attention from the locus of such stimuli, while the trials

where they processed words and remained in the same screen locus (stay locus trials)

acted as a baseline for these trials. Trials where participants initially determined the

lexical status of non-words were a necessary feature of the current task in order to

maintain the expectation that a word or non-word could be presented with equal

probability on each trial. The trials of focal interest were therefore those where

participants initially processed the content of words before either remaining in the same

locus or relocating attention away from the locus of the initially processed word. The

Biased Attentional Disengagement hypothesis predicts that when individuals have been

required to determine the lexical status of differentially valenced words in the initially

attended locus, high trait anxious individuals will be disproportionately slow to then

spatially shift attention to identify probes appearing in the opposite location, when this

initially processed word was negative as compared to non-negative.

Participants

Participant selection was again guided by the screening of undergraduate students

on the trait version of the Spielberger State-Trait Anxiety Inventory (STAI-T;

Spielberger, et al., 1983) in an earlier session prior to the commencement of the study.

From a pool of 509 individuals, potential participants were those whose STAI-T score

fell within the upper third (at or above 45) or lower third (at or below 37) of the

distribution. Of those who were recruited for the study, 24 were from the lower third of

the distribution (low trait anxious group) and 24 were from the upper third of the

distribution (high trait anxious group). The low trait anxious group was comprised of 9

71

male and 16 female participants with a mean age of 18.75 years (SD = 1.39) while the

high trait anxious group consisted of 4 male and 20 female participants with a mean age

of 20.96 years (SD = 6.59). The high and low trait anxious groups did not differ

significantly in terms of age, t(47) = 1.67, ns, or gender ratio gender ratio, ²(1,47) =

1.77, ns.

Materials

Emotional Assessment Measure

The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger, et al., 1983)

was again employed as the emotional assessment measure in the current study.

Stimulus Words

The same 48 negative and 48 non-negative words used in the first study were

employed in the Experiment 2. As previously highlighted in Chapter 2, the possibility

that participants could differentiate stimulus words and non-words based on graphemic

legitimacy alone was identified as an issue of potential concern in Experiment 1. The

inclusion of lexical decisions in the current task also means that it is critical for all non-

words to be graphemically legitimate to ensure that participants attempt semantic access

for all stimuli, rather than being able to determine lexical status based on graphemically

legitimacy alone. All non-words used in the study were therefore constructed to be

graphemically legitimate, thus requiring participants to process the stimuli for potential

meaning. A new set of length-matched, graphemically legitimate non-words was

therefore created and paired with negative and non-negative words (see Appendix B). As

the current study involved lexical decisions, it was also necessary to use both word and

non-word stimuli in practice trials, as compared to non-word stimuli alone, as in

72

Experiment 1. A set of 96 non-negative words, paired with length matched non-words,

was therefore created for use in the practice trials alone.

Experimental Hardware

Delivery of the experimental task was managed by an Acorn Archimedes 5000

computer, with stimuli presented on a high resolution monitor.

Experimental Task

Each trial began with the words “next trial” appearing in the centre of the screen

for 500ms to signal the beginning of the trial. A small cue consisting of a cross was then

presented for 200ms in either the upper or lower screen location. The purpose of this was

to indicate to participants the location of the letter string they were required to determine

the lexical status of. Following the cue presentation, two vertically aligned letter strings

were presented, one in the location vacated by the cue and one in the opposite screen

location. The spatial parameters of the stimulus display were identical to the first study

with letter strings presented vertically aligned in one of two screen locations separated by

3cm. Participants were required to determine the lexical status of the letter string

appearing in the locus of the initially presented cue by pressing a key labeled “non-word”

if the string was a non-word, and pressing a key labeled “word” if the string was a word,

using their left hand. Immediately following this response, a probe was presented either

in the same locus as the lexical decision string or the opposite location. Probes were

presented superimposed on the letter string, thus leaving both stimuli present on the

screen until participants responded. The probe again consisted of an arrow facing either

left or right and participants were asked to indicate the direction of the arrow by pressing

the left mouse key for a left facing arrow, and pressing a right mouse key for a right

73

facing arrow, using their right hand. Latencies to correctly identify the probe were taken

as the dependent measure.

Inter-trial interval Cue Lexical Decision Probe Discrimination

500ms 200ms Remain Until Response Remain Until Response

Figure 3.1. Four possible trial types resulting from the task factors of word valence (negative or

non-negative) and probe position (word or non-word), including exposure durations. Initial cue

position and probe type are shown randomly.

The entire task consisted of 768 trials with each of the 96 word/non-word

stimulus pairs being presented once before being repeated again. Across the 768 trials,

each stimulus pair was presented once in each of the four trial types where the initial

lexical decision was performed on a negative or non-negative word, resulting from the

combination of the two, two-level factors of word valence (negative or non-negative) and

probe position (stay locus or move locus). Stimulus presentation order was randomised

+

CRUEL

ERLUC

NONWORD

CRUEL

ERLUC

NONWORD

NEXT TRIAL

Negative Stimulus

Stay locus

Disengage from

negative baseline

+

AGULEE

LEAGUE

AGULEE

LEAGUE

TAFLA

FATAL

TAFLA

FATAL

CAMPUS

PUCSAM

CAMPUS

PUCSAM

+

+

NEXT TRIAL

NEXT TRIAL

NEXT TRIAL

Negative Stimulus

Move locus

Disengage from

negative

Non-Negative Stimulus

Stay locus

Disengage from

non-negative baseline

Non-Negative Stimulus

Move locus

Disengage from

non-negative

74

within these constraints. The four conditions generated by the combination of the two

task variables are provided in Figure 3.1. As the probe position factor determines whether

attention is required to shift from the initially attended locus or not, trials where the probe

appears in the same position as the initial word will be referred to as „stay locus trials‟

while trials where probes appear opposite the initial word will be referred to as „move

locus trials‟. Cue position (upper or lower screen location) and probe type (left or right

arrow) were determined randomly on each trial with the restriction that each was

presented an equal number of times across the 768 trials. Participants were given the

opportunity to have two brief, self-paced rest periods after the completion of every 256

trials.

Procedure

Participants were first administered the Spielberger State-Trait Anxiety Inventory

(STAI; Spielberger et al., 1983) questionnaire upon arrival before completing the

computer task individually in a sound attenuated cubicle. A brief description of the task

presentation structure was provided and participants were informed that they were

required to make two responses, the first being the decision regarding the lexical status of

a letter string, and the second to determine the orientation of the probe stimulus by

pressing the corresponding mouse key. Participants were instructed to attend to the locus

of the initial cue as this signaled the location of the to-be-decided letter string.

Participants were directed to be as fast as possible in their responses without

compromising accuracy. Before commencing the experimental trials participants

completed 96 practice trials consisting of the 96 non-negative words with their non-word

partners.

75

Results

A summary of participant characteristics taken at the time of testing, including

measures of state anxiety are provided in Table 3.1. STAI-T scores taken at the time of

experimental testing confirmed that the high trait anxious participants (M = 48.12, SD =

7.14) continued to score significantly higher than the low trait anxious group (M = 29.95

(SD = 5.17) as required, t(47) = 10.09, p < .01. The high and low trait anxious groups

also differed according to state anxiety scores, t(47) = 4.41, p < .01. As any differences

across trait anxiety groups may also be attributed to this difference in state anxiety,

correlational analyses are conducted to determine the relative association of experimental

measures with state and trait anxiety.

Table 3.1

Characteristics of participants in Experiment 2. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (Years) Gender Ratio M:F

High Trait Anxious 48.12 (7.14) 39.78 (8.42) 18.75 (1.39) 4:20

Low Trait Anxious 29.95 (5.17) 29.95 (6.77) 21.08 (6.70) 8:16

Total 38.80 (11.80) 34.60 (9.00) 19.88 (4.89) 12:36

The dependent measure of interest for examining biased attentional

disengagement from the locus of semantically processed negative and non-negative

material was derived from trials where the initial lexical decision target was a word. This

is because it was these trials that provide information about participants‟ relative ability

to disengage from the locus of semantically processed information, by revealing the

76

extent of slowing across trials where the probe appears in the opposite location to the

initially processed word (move locus trials) location as compared to trials where the

probe appears in the same location as the initially processed word (stay locus trials).

There were four such trial types given by the combination of the two two-level factors of

word valence (negative or non-negative) and probe locus (move locus or stay locus).

Overall accuracy was high for both the lexical decision and probe discrimination

responses with participants averaging 93.28% (SD = 8.21) and 92.05% (SD = 7.25) for

these two measures respectively. Median discrimination latencies were again used as a

means of minimising the influence of outlying data points. As incorrect responses in the

lexical decision component of the task would suggest insufficient processing of word

content, while incorrect probe discrimination responses would suggest insufficient

engagement with the probe locus, it was inappropriate to include participants with very

low accuracy rates. Therefore, participants who failed to obtain greater than 80%

accuracy on either lexical decision, or probe discrimination components of the task, were

excluded from the final analysis. This resulted in five exclusions, three from the high trait

anxious group and two from the low trait anxious group. As the current task was designed

to ensure that participants were equivalently engaging with the semantic content of the

presented material, it was necessary to verify that the trait anxious groups did not differ in

their rates of accuracy in correctly identifying the lexical status of negative and non

negative words. In accordance with this, it was demonstrated that high and low trait

anxious groups did not differ in terms of accuracy rates for identifying negative, F(1, 42)

= 0.57, ns, or non-negative words, F(1, 42) = 0.78, ns, and the interaction between

valence of lexical decision targets (negative and non-negative words) and trait anxiety

group (high and low trait anxious) for accuracy rates, did not approach significance, F(1,

77

42) = 0.01, ns. To determine if participants differed in their speed to identify initial

lexical decision targets, response latencies to determine the lexical status of negative and

non-negative words were analysed. A trend suggesting that all participants were faster to

identify negative as compared to non-negative words was evident, F(1, 42) = 3.76, p =

0.06, however, this was not modified by trait anxiety group F(1, 42) = 1.78, ns.

The probe discrimination latencies for the critical trials measuring biased

attentional disengagement from the locus of semantically processed words for high and

low trait anxious participants are provided in Table 3.2. These data were subjected to a 2

x 2 x 2 mixed design ANOVA, consisting of one between group factor, and two within

group factors. The between group factor was trait anxiety (high or low) and the two

within group factors were word valence (negative or non-negative) and probe locus

(move locus or stay locus). The Biased Attentional Disengagement account would predict

a significant three-way interaction. Specifically, this account predicts that on trials where

the lexical target acts to ensure initial attentional processing of words, high trait anxious

participants will show disproportionate slowing to shift attention to identify the probe in

the opposite location, when the initially processed word is negative, rather than non-

negative in valence.

The three-way ANOVA revealed a significant main effect of probe locus F(1, 42)

= 510.49, p <.01. This main effects reflects the fact that trials requiring participants to

relocate attention to the opposite screen location result in longer latencies to identify

probes. This was specifically demonstrated in longer latencies to identify probes on move

locus trials (M = 662.18, SD = 11.33) and relatively shorter latencies to identify probes

on stay locus trials (M = 516.56, SD = 8.66). The only other significant effect to emerge

was a two-way interaction between probe locus and trait anxiety group F(1, 42) = 5.25, p

78

<.05. This interaction demonstrated that, while both high and low trait anxious

individuals were slower to identify probes on move locus trials, as compared to stay locus

trials, the difference in latencies across these two trial types was greater for the high trait

anxious participants (move locus M = 681.31, SD = 16.39; stay locus M = 520.95, SD =

12.53; difference = 160.72ms) as compared to the low trait anxious participants (move

locus M = 643.04, SD = 15.66; stay locus M = 512.17, SD = 11.97; difference =

130.87ms). The three-way interaction between trait anxiety, word valence and probe

locus predicted by the Biased Attentional Disengage account did not approach

significance F(1, 42) = 0.00, ns.

Table 3.2

Mean probe discrimination latencies in milliseconds across critical experimental

conditions and trait anxiety groups. Standard deviations given in parenthesis.

Word Valence Probe Locus High Trait Group Low Trait Group

Negative Stay locus 519.76 (57.76) 510.87 (56.07)

Move locus 680.47 (90.17) 642.17 (68.74)

Non-negative Stay locus 522.14 (54.42) 513.48 (63.02)

Move locus 682.14 (75.51) 643.91 (70.69)

In order to examine the relationship between measures of attentional

disengagement from negative and non-negative words and measures of state and trait

anxiety, it was necessary to compute an index of impaired attentional disengagement. A

measure of slowing to disengage from negative words was first generated by subtracting

participant‟s response latencies on move locus trials from response latencies on stay locus

79

trials, for trials containing negative words. The equivalent measure was also calculated

for impaired disengagement from non-negative stimuli by subtracting latencies on move

locus trials from latencies on stay locus trials for trials containing non-negative words.

An overall index representing impaired disengagement from negative words was then

computed by subtracting the measure of slowing to disengage from non-negative words,

from the measure of slowing to disengage from negative words. Higher scores on this

index therefore represent greater difficulty disengaging from negative as compared to

non-negative words. This index of impaired disengagement from negative words was not

observed to be significantly correlated with either STAI-T scores, r(43) = 0.05, ns, or and

STAI-S scores, r(43) = 0.01, ns. This result contradicts the predictions of the Biased

Attentional Disengagement account of anxiety-linked attentional bias which suggest that

increased difficulty disengaging from negative stimuli should be associated with higher

levels of anxiety vulnerability.

Discussion

The high overall accuracy rates on both the lexical decision and probe

discrimination components of the task provide reassurance that participants were

processing the semantic content of initially attended words and non-words, and were also

attending to the spatial locus of the subsequent probe. The fact that no differences were

observed across trait anxiety groups on the lexical decision component of the task, either

in terms of accuracy, or lexical decision response latencies to negative and non-negative

stimuli, also provides confidence that trait anxiety groups did not differ in assessing the

lexical status of these initially attended stimuli. The main effect of probe locus

demonstrated that relocating attention to the opposite screen location from the locus of

80

initial attention, in order to identify a probe, resulted in longer response latencies than

keeping attention in the same screen locus to identify a probe, consistent with results of

Experiment 1. The task therefore appeared to function in accordance with its designed

purpose of not only securing attention to an initial spatial locus but also ensuring that the

semantic content of the material in that locus was processed before either requiring

participants to relocate attention to a spatially removed locus, or remain in the same

locus.

Despite assurances that the task was able to ensure equivalent semantic

processing of the differentially valenced words presented initially, the results clearly

failed to support the hypothesis that attentional bias in anxiety is characterised by greater

difficulty disengaging attention from the locus of semantically processed negative

stimuli. This was demonstrated by the absence of a significant three-way interaction

between trait anxiety group, word valence and probe locus factors. Similarly, no

significant correlations were observed between indices of impaired attentional

disengagement and measures of state and trait anxiety suggesting little association

between such measures and current anxious mood or more general susceptibility to

anxious mood. The most direct implication of these results is that, even when equivalent

initial semantic processing of negative and non-negative stimuli is ensured, no anxiety-

linked differences emerge in subsequent speed to disengage attention from the spatial

locus of these stimuli.

Having highlighted the possibility that not controlling the initial locus of spatial

attention could potentially compromise measures of attentional disengagement,

Experiment 1 sought to examine whether a bias in attentional disengagement would

emerge when the task included a means of spatially securing initial attention. The results

81

of the first experiment demonstrated that, having initially secured attention in the spatial

locus of differentially valenced stimuli, high and low trait anxious individuals did not

then differ in the speed with which they were able to relocate attention to a spatially

removed location. This second study was designed to address the additional possibility

highlighted in the conclusion of Experiment 1, that despite the absence of a

disengagement effect, when equivalent engagement with a locus is ensured, it is possible

that biased attentional disengagement from negative material may only emerge when

both high and low trait anxious individuals are required to equivalently process the

semantic content of stimuli presented in an attended locus. The results of the second

study therefore expand the finding of the first study to highlight that when this additional

requirement is met, whereby participants were compelled to process the semantic content

of the material in the initially attended locus, no anxiety-linked differences in capacity to

then relocate attention to a spatially removed locus was evident. Such a lack of support

does not preclude the possibility that an attentional disengagement bias could manifest

under alternative task conditions. The present results, however, do not provide support

for the existence of anxiety-linked attentional disengagement bias when relocating

attention from the locus of semantically processed negative and non-negative words.

Together with the findings of Experiment 1, the results of the current study have

therefore failed to support the hypothesis that Biased Attentional Disengagement

underpins attentional bias favouring the locus of negative stimuli observed in high trait

anxious individuals.

The logical alternative to the Biased Attentional Disengagement hypothesis that

could also account for previous findings demonstrating that high trait anxious individuals

selectively attend to the locus of negative stimuli, is the Biased Attentional Engagement

82

account. The results of Experiment 1 failed to demonstrate an anxiety-linked difference

in attentional engagement, however, the potential reason that the task in the first study did

not demonstrate an anxiety-linked attentional disengagement effect, which was addressed

in the current study, also applies to the Biased Attentional Engagement account.

Specifically, the observation that ensuring equivalent engagement with a particular locus

does not necessarily equate with equivalent engagement with the content of the stimulus

in that locus. In relation to the measurement of attentional engagement, it is possible that

having secured individuals in an initially attended locus, the requirement to then

discriminate a probe appearing in the locus of a spatially removed negative of non-

negative word either allows for the potential influence of differential processing of the

content of these stimuli, or an absence of processing these stimuli at all. The measure of

biased attentional engagement derived from the task in the first study therefore allowed

conclusions to be drawn about relative speeding to attend to a given locus, but not about

potential differences to process the content of information in that locus. In order to

achieve this it would be necessary to develop a measure of speeding to process the

content of words appearing in a spatially removed locus. Such a task would allow the

assessment of the speed with which individuals engage with the semantic content of

differentially valenced material, and not simply the speed to allocate attention to the

spatial locus of such information. Assessing anxiety-linked differences in relative

speeding to engage with the semantic content of negative and non-negative stimuli was

therefore the principal aim of Experiment 3.

In summary, the current study was designed to examine whether attentional bias

in anxiety is characterised by Biased Attentional Disengagement from the locus of

semantically processed negative and non-negative words. While the task ensured

83

equivalent semantic processing of initially attended information for both high and low

trait anxious individuals, the results provided no support for the hypothesis that anxiety-

linked differences exist in Biased Attentional Disengagement from differentially

valenced stimuli. The results of Experiments 1 and 2 therefore provide no support for the

Biased Attentional Disengagement hypothesis. Examining whether anxiety-linked

differences exist in biased attentional engagement with the content of differentially

valenced stimuli presented in a spatially removed locus is therefore the focus of

Experiment 3.

84

CHAPTER 4

EXPERIMENT 3

The principal aim of Experiment 3 was to measure anxiety-linked differences in

the speed with which spatial attention can move to the locus of negative and non-negative

words when individuals are required to semantically process this information. The

rationale for the current study is similar to that underpinning Experiment 2, but with the

present focus placed on attentional engagement rather than attentional disengagement.

The argument previously highlighted in Chapter 2 regarding the measurement of

attentional disengagement applies equally to the measurement of attentional engagement.

That is, by not including a task which required participants to process the semantic

content of negative and non-negative stimuli, Experiment 1 was limited to drawing

conclusions regarding selective attention to spatial loci rather than to different types of

semantic information. Therefore, Experiment 1 was unable to establish whether attention

to a spatial locus involved processing the content of the stimulus appearing in that locus.

The current study seeks to address the possibility that high trait anxious individuals

selectively process the content of negative material appearing in an unattended location.

The Biased Attentional Engagement account of anxiety-linked attentional bias predicts

that the presence of negative material in an unattended locus will result in a level of

semantic activation that will facilitate the processing of the content of this information for

high trait anxious individuals. If this account is correct then we would expect that such

activation would result in high trait anxious individuals being disproportionately fast to

process the content of negative, as compared to non-negative, stimuli when required to

spatially relocate attention to process these stimuli.

85

The aim of the current study was to examine whether attentional bias in anxiety is

characterised by disproportionate speeding to selectively orient spatial attention to the

locus where the semantic content of negative material is processed. In order to measure

this it was necessary for the experimental task to first secure attention in a given location

where no semantic information is present, before requiring participants to process the

semantic content of a subsequently presented negative or non-negative word appearing

either in the same initially attended locus, or in a spatially removed location. The relative

speed with which participants are able to process the semantic content of differentially

valenced stimuli appearing in the initially attended location, versus the opposite location,

will provide a measure of the speed with which participants can relocate spatial attention

to the new position and engagement with the semantic content of the negative or non-

negative stimulus presented in that location.

As in the second experiment, the task in the current study used lexical decisions to

ensure that participants were processing the semantic content of negative and non-

negative words, and a probe task to ensure attention was located in the desired position.

The order in which the probe and lexical decision tasks were performed was reversed

from the order employed in Experiment 2. In the present study, participants were first

required to discriminate the identity of a probe presented in one of two locations on the

screen, before then being required to determine the lexical status of one of two

subsequently presented letter strings, one of which appeared in the same screen location

as the initial probe and the other in the opposite screen location. The task therefore started

with an initial cue which signaled the position where the probe would appear, followed

by the probe which remained on the screen until participants responded. Two letter

strings were then presented on the screen at the same time that a tone was sounded which

86

signaled to participants which of these two strings they were required to determine the

lexical status of. On experimental trials, letter strings consisted of a negative or non-

negative word paired with a graphemically legitimate non-word and participants were

required to determine the lexical status of the word, which on half the trials was presented

in the opposite position to the probe, requiring participants to relocate spatial attention in

order to engage with the semantic information, and on the remaining trials was presented

in the same position as the probe, requiring no such spatial shift in attention. Trials that

involved a spatial shift in attention were those where the lexical decision target was a

negative or non-negative word appearing in the opposite screen position to the initial

probe. These trials therefore required participants to process the probe before relocating

spatial attention to process the semantic content of this negative or non-negative word.

Trials that did not involve a spatial shift in attention were those on which the lexical

decision target was a negative or non-negative word appearing in the same locus as the

initially presented probe. If attentional bias in anxiety is characterised by biased

attentional engagement then high trait anxious participants will be disproportionately fast

to determine the lexical status of negative as compared to non-negative stimuli. Such an

effect would be represented by shorter latencies for high trait anxious individuals to

identify negative as compared to non-negative lexical decision targets on trials where

participants are required to shift attention to the opposite screen position.

Method

Overview

The aim of the current experiment was to assess anxiety-linked differences in

biased attentional engagement with spatially distal, differentially valenced words. In

87

order to measure this it was necessary to secure participants‟ attention in an initial locus

before then requiring them to engage with the semantic content of stimuli appearing in

either the same, or opposite, screen location. It is important to note that the current task

requires participants to make a lexical decision on a negative or non-negative word either

in the initially attended locus, requiring no spatial shift in attention, or in the opposite

screen position, requiring a spatial shift in attention. Although effects relating to word

valence in either location may yield information about the ease with which participants

can access the content of the stimuli, given that the processing of these stimuli will be

equivalent, the key measure of concern in the current task is whether the requirement that

participants spatially relocate attention results in anxiety-linked differences in speed to

process the content of stimuli, as compared to when participants are not required to

relocate attention from the initially attended locus. Speed to stay versus speed to move

attention to the locus of differentially valenced words that participants semantically

process, therefore form the dependent measure in the current task. Participants were

required to initially identify a probe which acted to secure attention in either the locus

where a word or non-word then appeared before they either kept spatial attention in the

same locus or relocated attention to the opposite screen location to process the semantic

content of the material appearing in this locus.

The relevant trials which allowed the current task to measure differences in speed

to move spatial attention to process the semantic content of differentially valenced

stimuli, were those on which participants were required to determine the lexical status of

a negative or non-negative word. On half these trials, initial probe presentation acted to

secure attention in the opposite screen location to where the word was subsequently

presented, requiring participants to relocate spatial attention to a negative or non-negative

88

word in the other screen location thus providing a measure of speeding to engage with the

content of these spatially removed stimuli. As it is these trials that require a spatial shift

in attention, they are referred to as „move locus trials‟. On the remaining trials, the probe

acted to secure participant‟s initial attention in the same locus as the subsequently

presented negative or non-negative words before requiring that they determine the lexical

status of these stimuli in the same location, therefore providing a baseline for the move

locus trials. As these trials do not require a spatial shift in attention, they are referred to as

„stay locus trials‟. The Biased Attentional Engagement account predicts that high trait

anxious individuals will be disproportionately fast to identify the lexical status of

negative as compared to non-negative words on the move locus trials, when a shift in

spatial attention is required, relative to stay locus trials, where no spatial shift in attention

is required. Trials where participants made lexical decisions on non-words were a

necessary task feature in order to maintain the expectation that the lexical target could

equally be a word or non-word, but these trials were not informative in terms of biased

attentional engagement with word content.

Participants

To compare measures of attentional engagement across individuals who differ in

anxiety vulnerability, recruitment of potential participants was guided by the screening of

undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory

(STAI-T; Spielberger, et al., 1983) which took place in a session prior to the

commencement of the study. Of the 426 participants screened, potential participants were

those whose STAI-T score fell in the upper third (at or above 46) or lower third (at or

below 39) of the distribution. Of those recruited for the study, 24 were from the upper

third of the distribution (high trait anxious group) and 24 were from the lower third of the

89

distribution (low trait anxious group). The low trait anxious group comprised four male

and 20 female participants with an average age of 18.29 years (SD =1.45) while the high

trait anxious group comprised five male and 18 female participants with an average age

of 19.25 (SD = 2.86). The high and low trait anxious groups did not differ significantly in

terms of age, t(46) = 1.46, ns, or gender ratio, ²(1,46) = 1.21, ns.

Materials

Emotional Assessment Measure

The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)

was again employed as the emotional assessment measure.

Stimulus Words

The same 48 negative and non-negative words, along with their non-word

partners that were used in Experiment 2 were again employed in the current study. The

key purpose of the move locus trials in the current task was to require participants to shift

attention to the locus of the word in the opposite screen location to identify its lexical

status. The possibility that participants could determine the lexical status of words

appearing in the opposite screen location without attending to them would obviously

undermine the purpose of the current task. If all trials contained word/non-word pairs,

participants could accurately infer the lexical status of the word in the unattended locus

simply by determining the lexical status of a word in the initially attended locus. To

eliminate this possibility, an equal number of foil trials containing either non-word/non-

word pairs or word/word pairs were included to ensure that participants always needed to

attend to the appropriate lexical target to process its content. Therefore, an additional set

of 48 non-word/non-word stimulus pairs and 48 word/word stimulus pairs (comprising

only non-negative words) was therefore constructed for this purpose (see Appendix C).

90

An appropriate stimulus set was also constructed for use in the practice trials comprising

48 word/non-word pairs, 24 word/word pairs and 24 non-word/non-word pairs. All words

used in the practice trials were non-negative in emotional tone.

Experimental Hardware

An Acorn Archimedes 5000 computer, with high resolution monitor, was used to

deliver the experimental task.

Experimental Task

The task used in the current study was similar in structure to the previous

modified probe task used in the Experiment 2, however, the lexical decision was now the

second decision in each trial, and latency to determine the lexical status of these words

was the dependent measure. Each trial began with the words “next trial” appearing in the

centre of the screen for 500ms. A small cue consisting of a cross was then presented in

either the upper or lower screen location for 200ms. This cue informed participants where

the probe was to appear and they were instructed to attend to this locus. The probe

stimulus was then presented, which again consisted of a right or left facing arrow, and

participants were required to indicate the direction of the arrow by pressing the left

mouse key for a left facing arrow and a right mouse key for a right facing arrow using

their right hand. Immediately following registration of this response, two vertically

aligned letter strings were presented, one in the location just vacated by the probe and one

in the opposite screen location. At the onset of this stimulus display a tone

simultaneously sounded to signal which of the two letter strings participants were

required to determine the lexical status of. A high pitched tone indicated that participants

were to make a lexical decision on the top letter string and a low pitched tone indicated

that they were to make a lexical decision on the bottom letter string. Participants were

91

required to respond by pressing a key labeled “non-word” if the string was a non-word

and pressing a key labeled “word” if the string was a word using their left hand.

Latencies to correctly identify the lexical status of the letter string were taken as the

dependent measure. Participants‟ lexical decision response cleared the screen and the

next trial began 500ms later.

The task consisted of 768 experimental trials in total, with each letter string pair

(word/non-word pair, non-word/non-word pair and word/word pair) being presented once

before any were repeated. The presentation of the 96 word/non-word, 48 word/word and

48 non-word/non-word letter string pairs was randomised within each presentation

sequence of 192 trials, with each pair appearing four times throughout the task. Initial cue

position (upper or lower screen location) and probe type (left or right facing arrow) were

determined randomly on each trial within the constraint that each was presented an equal

number of times across the 768 trials. On the trials that provided the dependent measure

of interest (trials where the lexical decision target was a negative or non-negative word)

there were four possible trial types given by the combination the two experimental factors

of word valence (negative or non-negative) and word position (stay locus or move locus).

Across the 768 trials, each experimental letter string pair (96 negative/non-word and 96

non-negative/non-word pairs) was presented in half of these four possible trial conditions.

This stimulus presentation was therefore counter-balanced across participants such that

after two participants had been tested, each stimulus had appeared once in each of these

task conditions. The four conditions providing the dependent measure of interest are

provided in Figure 4.1. During the task, participants had two brief, self-paced rest periods

after the completion of every 256 trials.

92

Inter-trial interval Cue Probe Discrimination Lexical Decision

500ms 200ms Remain until response Remain until response

Figure 4.1. Four trial combinations resulting from the task factors of word valence (negative or

non-negative) and word position (stay locus or move locus) including temporal parameters.

Probe type and position shown randomly. High and low tones indicated in brackets.

Procedure

Upon arrival participants were first administered the state and trait forms of the

Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) questionnaire,

before completing the computer task in a sound attenuated cubicle. The task structure was

then described and participants were informed that they would be required to make two

responses on each trial, the first being to determine the orientation of the probe, and the

second being to determine the lexical decision of the signaled letter string. Participants

were instructed to attend to the location of the initial cue as this signaled the location

NON-NEG (High Tone)

NONWORD

NEGATIVE (High Tone)

NONWORD

NON-NEG (High Tone)

NONWORD

NEXT TRIAL

NEXT TRIAL

NEXT TRIAL

Negative Stimulus

Stay locus

Engage with negative

baseline

Non-negative Stimulus

Stay locus

Engage with non-negative

baseline

NEGATIVE (High Tone)

NONWORD

NONWORD

NEXT TRIAL

Negative Stimulus

Move locus

Engage with negative

Non-negative stimulus

Move locus

Engage with non-negative

+

+

+

+

93

where the probe would appear. The importance of noting the pitch of the signal tone was

also impressed upon participants as this directed their attention to the appropriate letter

string upon which to perform the lexical decision. Participants were directed to be as fast

in their responses as possible without compromising accuracy. The 96 practice trials were

first completed before participants began the experimental task.

Results

A summary of participant characteristics, including measures of state and trait

anxiety taken at the time of testing, is provided in Table 4.1. STAI-T scores taken at the

time of testing confirmed that the high trait anxious group (M = 45.71, SD = 6.82)

continued to score significantly higher than the low trait anxious group (M = 33.50, SD =

4.16) as required, t(46) = 7.48, p < .01. The high and low trait anxious groups were also

observed to differ in terms of STAI-S scores, t(46) = 4.01, p < .01. While this is not

unexpected, it would also potentially allow for group differences to be attributed to

differences in state anxiety rather than trait anxiety. Therefore, as with the previous

attentional probe tasks, correlational analyses w performed to determine whether

observed effects are associated to a greater degree with measures of either state or trait

anxiety.

Information regarding speed to move spatial attention towards the locus of

differentially valenced stimuli was derived from trials where the second trial decision

involved the lexical decision of a word. This is because it was these trials that required

participants to process the content of negative or non-negative words appearing in either

same locus as the initial probe, or the opposite screen location to the initial probe. Biased

attentional engagement with spatially removed negative and non-negative words would

94

therefore be revealed by relative speeding to identify the lexical status of differentially

valenced words in the opposite screen location as compared to the speed to identify these

words in the same screen locus. If a general tendency to shift spatial attention to process

the semantic meaning of one specific stimulus valence exists, this would be revealed by a

significant two-way interaction between word valence and word position. The Biased

Attentional Engagement account would predict that such an interaction would be further

modified by trait anxiety, whereby, across stay locus and move locus trials, low trait

anxious individuals would not show a significant difference in relative speeding to

identify negative versus non negative words, while for the high trait anxious individuals

the time taken to identify words on move locus as compared to stay locus trials will be

less for negative as compared to non-negative stimuli.

Table 4.1

Characteristics of participants in Experiment 3. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F

High Trait Anxious 45.71 (6.82) 38.29 (7.95) 19.25 (2.86) 5:18

Low Trait Anxious 33.50 (4.16) 30.33 (5.61) 18.29 (1.46) 4:20

All Participants 39.74 (8.31) 34.39 (8.15) 18.80 (2.29) 9:38

Accuracy for the probe discrimination and lexical decision responses was again

high overall with participants averaging 98.54% (SD = 2.18) and 89.6% (SD = 10.72)

accuracy for these two measures respectively. As with the previous studies, a high rate of

incorrect probe discrimination responses would suggest insufficient engagement with the

probe locus and similarly, a high rate of incorrect lexical decision responses would

95

suggest an individual was not semantically processing these letter strings. In keeping with

the exclusion criteria applied in the previous experiments, it was deemed inappropriate to

include participants who failed to obtain greater than 80% accuracy on either of these

tasks. This resulted in three exclusions, two from the low trait anxious group, and one

from the high trait anxious group. No significant differences for high and low trait

anxious groups were observed in the pattern of incorrect responses for lexical decisions,

F(1, 44) = 0.03, ns, or probe decisions, F(1, 44) = 0.43. Similarly, no anxiety group

differences in incorrect responses were observed across different trial types included in

analyses below. As with the previous studies, median lexical decision latencies were used

to minimise the influence of outlying data. The latencies for the critical trials where the

lexical decision target was a word, across the high and low trait anxious participants are

provided in Table 4.2.

Table 4.2

Mean lexical decision latencies in milliseconds across critical experimental trials and

trait anxiety groups. Standard deviations given in parenthesis.

Word Valence Word Position High Trait Group Low Trait Group

Negative Stay locus 1084.56 (317.07) 1012.27 (180.61)

Move locus 1215.65 (395.44) 1061.36 (167.83)

Non-negative Stay locus 1135.00 (336.51) 1010.45 (187.57)

Move locus 1158.91 (290.03) 1050.23 (195.32)

The above lexical decision response data were subjected to a 2 x 2 x 2 mixed

design ANOVA consisting of one between group factor and two within group factors.

96

The between group factor being trait anxiety group (high or low) and the two within

group factors being word valence (negative or non-negative) and word position (stay

locus or move locus). As previously outlined, the Biased Attentional Engagement

account predicts a significant three-way interaction on this analysis, whereby the relative

speed for high trait anxious individuals to process the content of words on move locus, as

compared to stay locus trials, will be disproportionately fast for negative as compared to

non-negative words.

The three-way ANOVA revealed a significant main effect of word position, F(1,

44) = 26.53, p < .01, demonstrating that participants were faster to make a lexical

decision of a word appearing in the same position as initial fixation (stay locus trials; M =

1060.57, SD = 38.85) than to make a lexical decision of a word appearing in the opposite

position to initial fixation (move locus trials; M = 1121.54, SD = 40.43). Consistent with

both the first and second studies, this main effect reflects the relative slowing resulting

from participants relocating spatial attention to the opposite screen location to make the

critical decision, in this case a lexical decision. More importantly for the interest of the

current study, this main effect highlights the task achieved the requirement of detecting

the speed of this spatial shift in attention, and therefore has the potential to reveal

valence-linked and anxiety-linked differences that may exist in this spatial shift in

attention. A two-way interaction between word valence (negative or non-negative) and

word position (move locus or stay locus) also emerged from this analysis F(1, 44) = 6.22,

p < .05. The nature of this interaction was such that, on move locus trials participants

lexical decisions were faster for non-negative words (M = 1104.57, SD = 37.05) and

slower for negative words (M = 1138.51, SD = 45.66), while on stay locus trials lexical

decisions were faster for negative words (M = 1048.42 , SD = 38.70) and slower for non-

97

negative words (M = 1072.73, SD = 40.87). This interaction indicates that in general,

participants were slower to move spatial attention to the locus of a negative word than to

move spatial attention toward the locus of a non-negative word on this task. The Biased

Attentional Engagement hypothesis suggests that this effect would be attenuated for the

high trait anxious group, such that these individuals would be disproportionately fast to

identify the lexical status of negative words appearing in the opposite as compared to the

same screen position in relation to low trait anxious individuals. Indeed this two-way

interaction was observed to be further modified by trait anxiety as demonstrated in a

significant a three-way interaction between trait anxiety group, word valence and probe

locus F(1, 44) = 4.39, p < .05. As can be observed from Figure 4.2 however, the pattern

of this interaction was the opposite of what would be predicted by the Biased Attentional

Engagement account. This can be seen most specifically across the component two-way

interactions for the high and low trait anxious individuals. Whereas the low trait anxious

group showed no relative slowing to identify the lexical status of negative or non-

negative stimuli across move locus and stay locus trials F(1, 21) = 0.08, ns, high trait

anxious individuals showed disproportionate slowing for negative as compared to non-

negative words on the move locus trials, as compared to the stay locus trials F(1, 22) =

10.38, p < .01. This two-way interaction for the high trait anxious group suggests that

these individuals are in fact relatively slower to shift spatial attention to semantically

process negative material and relatively faster to shift spatial attention to semantically

process the content of non-negative material. This runs counter to the expectations of the

Biased Attentional Engagement account which would instead predict that the relative

speed for high trait anxious individuals to spatially shift attention would be faster for

negative material as compared to non-negative material.

98

Figure 4.2. Three-way interaction between trait anxiety group (low or high), word

valence (negative or non-negative) and word position (stay locus or move locus).

This observed interaction for the high trait anxious group would suggest that these

individuals have greater difficulty spatially relocating attention to the locus of negative

relative to non-negative words. It is possible, however, that this effect may not simply be

attributable to the speed to process negative and non-negative material on move locus

trials, but instead may be due to differences in the speed to process such differentially

valenced material in the initially attended location on the stay locus trials. If this was the

case, we would predict a main effect to be present on the stay locus trials that would be

absent on the move locus trials. Consistent with this, simple main effects analysis on the

attentional move locus trials for the high trait anxious participants only, revealed that

when participants were required to move spatial attention, no relative speeding to identify

negative (M = 1215.65, SD = 82.46) as compared to non-negative words (M = 1158.91,

Low Trait Anxious

980

1020

1060

1100

1140

Negative Non-Negative

Word Valence

Re

sp

on

se

La

ten

cy

(m

s)

High Trait Anxious

1080

1120

1160

1200

1240

Negative Non-Negative

Word Valence

Resp

on

se L

ate

ncy (

ms)

Stay locus

Move locus

99

SD = 60.52), F(1, 22) = 2.06, ns. Analysis of the stay locus trials however revealed that

there was a strong trend showing high trait anxious individuals were faster to

semantically process negative (M = 1084.57, SD = 66.11) as compared to non-negative

stimuli (M = 1135.00, SD = 70.17) when no shift in spatial attention was required F(1,

22) = 4.01, p = .06. Clearly this pattern of results cannot reflect a differential spatial shift

in attention as no such spatial shift is present on stay locus trials. The breakdown of this

interaction for high trait anxious individuals therefore suggests that the observed pattern

of speeding to identify the semantic content of negative words was present on stay locus

trials but was lost on move locus trials. What these data may therefore be showing is a

non-spatial engagement bias, whereby high trait anxious individuals show greater

tendency to engage with the semantic content of negative words, as compared to non-

negative words, appearing in the focus of spatial attention, which is eliminated by a shift

in spatial attention. Such a conception of attentional engagement is obviously a departure

from that considered in both Experiment 1 and the current study. The possibility that the

current data demonstrate an attentional engagement bias operating in the absence of a

spatial shift in attention will be returned to in the discussion.

As with the first and second studies, the degree of association between measures

of attentional engagement and measures of state and trait anxiety were assessed. An index

of biased attentional engagement was generated by first computing a measure of speeding

to process negative words by subtracting participant response latencies on stay locus

trials containing negative words from latencies on move locus trials containing negative

words. This resulted in a measure whereby higher scores represent greater speeding to

process the content of spatially removed negative words. The equivalent measure of

speeding to process non-negative words was also created by subtracting response

100

latencies on stay locus trials containing non-negative words from latencies on move locus

trials containing non-negative words. Higher scores on the resulting measure represent

greater speeding to process the content of non-negative stimuli appearing in a spatially

removed locus. A single index of biased attentional engagement with spatially removed

negative words was created by subtracting the measure of speeding to process non-

negative words from the measure of speeding to process negative words. Higher scores

on this index therefore represent greater speeding to spatially shift attention to process

negative, as compared to, non-negative words. Correlations between this biased

attentional engagement index and STAI-T, r(45) = .05, ns, and STAI-S, r(45) = -.03, ns,

scores did not prove to be significant. The absence of a correlation between this biased

attentional engagement index and measures of state and trait anxiety would suggest that

there is little association between the relative speeding to spatially shift attention to the

locus of negative or non-negative material and either current anxious mood or more

general anxiety vulnerability.

Discussion

The high overall accuracy of participants‟ responses provided assurance that the

task was being performed as instructed with participants attending to the locus of the

probe before processing the word or non-word stimuli for semantic content. The

significant main effect of probe locus, further suggests that the task was capable of

indexing the speed of the attentional shift from the first attended locus to the

subsequently attended locus. A significant three-way interaction between trait anxiety

group, word valence and word position demonstrated that differences in speeding to

spatially shift attention to process the semantic content of negative and non-negative

101

material did indeed emerge across trait anxiety groups. However, the pattern of this

interaction clearly disconfirmed the prediction generated by the Biased Attentional

Engagement account concerning differences in speeding to spatially shift attention to

process the semantic content of negative and non-negative words. Specifically this

interaction demonstrated that, while low trait anxious participants did not differ in their

pattern of responding to identify negative and non-negative stimuli, high trait anxious

participants showed disproportionate slowing to relocate spatial attention to semantically

process negative material appearing in the opposite screen location and disproportionate

speeding to semantically process non-negative material appearing in the opposite screen

location. This clearly contradicts the predictions of the Biased Attentional Engagement

account which instead state that high trait anxious individuals should demonstrated

disproportionate speeding to spatially shift attention to the process the content of negative

material appearing in the opposite screen location. Correlational analyses failed to

provide any support for the association between speed to spatially shift attention, to

process negative, as opposed to non-negative, material and measures of either state or

trait anxiety.

The Biased Attentional Engagement account of anxiety-linked attentional bias

predicted that high trait anxious individuals would demonstrate disproportionate speeding

to spatially shift attention to process the content of negative as compared to non-negative

words. According to this account, differences in speeding to spatially shift attention

would be demonstrated when participants were required to move attention from the

position of a neutral probe to engage with the semantic content of a spatially removed

negative or non-negative word. It was expected that such differences would emerge

against hypothesised baseline trials where no anxiety-linked differences were necessarily

102

expected as participants did not spatially disengage attention from the neutral probe to

engage with the semantic meaning of a spatially removed negative or non-negative word.

The results of the current study did indeed demonstrate anxiety-linked differences in

speeding to spatially shift attention to engage with the semantic content of negative and

non-negative material across trials where participants were required to remain in the

initially attended locus, versus trials where they were required to relocate to a spatially

removed locus to identify the word. The specific prediction that high trait anxious

participants would evidence disproportionate speeding to process the semantic content of

negative words when they were presented in a spatially removed locus was not met

however. This is clearly inconsistent with the biased attentional engagement account of

anxiety-linked attentional bias which predicts that high trait anxious individuals will

show disproportionate speeding to engage with the content of spatially removed negative,

as compared to non-negative words.

The effect showing that high trait anxious individuals were disproportionately

slow to shift spatial attention to process the semantic content of negative material was

based on the comparison of latencies to semantically process negative and non-negative

words across move locus and stay locus trials. When considered together, the

comparative speeding observed across these two trial types clearly contradicts the

prediction of the Biased Attentional Engagement account that high trait anxious

individuals will be disproportionately fast to spatially shift attention to process the

semantic content of negative material. However, analysis of the component effects for

these individual trial types for the high trait anxious group highlights the possibility that

what appeared to reflect a slowness to move spatial attention to the locus of negative as

compared to non-negative words, resulted instead from a disproportionate speeding to

103

process the content of material appearing in the initially attended location. This was

demonstrated in the main effects analysis of the stay locus trials where the high trait

anxious individuals demonstrated disproportionate speeding to semantically process the

content of negative words appearing in the same attended location. The equivalent

analysis of the move locus trials, however, failed to approach significance. These results

suggest that the effect of disproportionate slowing to spatially shift attention to process

the semantic content of negative material observed across move locus and stay locus trial

types for the high trait anxious individuals, is actually due to the relative speeding of

these individuals to process negative material in the stay locus trials that is absent in the

move locus trials.

As the previous three experiments have principally be concerned with examining

spatial engagement and disengagement, trials where no spatial shift in attention occurs

were considered to be „baseline‟ trials. This assumption was premised on the interest in

examining the properties of attentional engagement and disengagement in the allocation

of attention to negative material when a spatial shift in attention does occur. It was

therefore assumed that these baseline trials would not yield information about biased

attentional engagement and disengagement as there was no requirement that participants

spatially relocate attention from one stimulus to another. The observation in the current

task that high trait anxious participants were disproportionately fast to process the

semantic content of negative material on trials where no attentional shift was required,

highlights the very real possibility of a attentional engagement bias operating in the

absence of a spatial shift in attention. Such an engagement bias would represent relative

speeding from processing a non-emotional aspect of a stimulus presented in a spatially

attended locus, to processing a different aspect of this stimulus that conveys negative as

104

compared to non-negative information. It is equally possible that such a bias could exist

in attentional disengagement also. This bias would be represented by relative speeding to

orient attention from processing an emotional aspect of a negative or non-negative

stimulus to processing a non-emotional aspect of the same stimulus.

In the current study, the faster response latencies for high trait anxious

participants to identify negative words presented in the same locus as initial attention

could represent such biased attentional engagement within a single locus. That is, this

result may be due to an effect of switching from the task of discerning the identity of a

probe, to the alternative task of processing the content of the material presented in the

attended locus. The absence of this effect when the subsequent lexical target is presented

in the opposite screen position would further suggest that this effect is limited to

switching of attention between different aspects of a stimulus in the same attended locus

and requiring participants to relocate attention to a different spatial locus eliminates this

effect.

An equally plausible alternative to the operation of a within-locus attentional

engagement process for the effect observed in the current task could be that high trait

anxious individuals merely exhibit a tendency to rapidly process the semantic content of

negative material presented to the locus of spatial attention. If this result does simply

represent such a general tendency for high trait anxious individuals to rapidly process the

meaning of negative material in the attended spatial locus, then we would also predicted

that high trait anxious individuals will demonstrate shorter latencies to semantically

process negative as compared to non-negative words when they have not previously been

processing an alternative aspect of a stimulus in the same spatial locus. In considering

this possibility, it is noted that such a condition was present in Experiment 2 where

105

participants were initially required to identify the lexical status of negative or non-

negative word before responding to a probe appearing in either the same or opposite

screen location. As the task in this experiment required participants to first make a lexical

decision on each trial prior to any other response, no switch from initially processing a

different dimension of stimulus information in this spatial locus had occurred. If high trait

anxious individuals do simply process the content of negative material more rapidly, then

we would have expected an anxiety-linked difference in response latencies also to emerge

on this initial lexical decision component of the task. Consistent with a non-spatial

attentional engagement account, the results of Experiment 2 clearly demonstrated that no

differences in response latencies for negative and non-negative words on the initial

lexical decision task were present across trait anxiety groups, F(1, 42) = 1.78, ns. Taken

together with the result in the current experiment, suggesting that high trait anxious

individuals are disproportionately fast to determine the lexical status of negative words

following probe discrimination in the same location, these findings would point to the

possibility that attentional bias in anxiety may be characterised by biased attentional

engagement with the semantic content of negative material presented in an attended

locus.

This hypothesis that anxiety may be characterised by an enhanced speed to switch

attention from processing non-emotional stimulus information to instead engage with

processing a different stimulus dimension communicating negative, as opposed to non-

negative meaning, may be thought of as implicating a bias in „set shifting‟ rather than the

shifting of spatial attention. A set shift task typically requires individuals to initially focus

on using one dimension of stimuli which vary in several dimensions (e.g. form, and

colour; Wolff, 1967). A set shift is said to occur when a participant is then required to

106

change the dimension of the stimuli used to make their responses. Slamecka (1968)

describes an extradimensional set shift as involving a switch that renders a previously

irrelevant stimulus dimension relevant to task performance. Hence, in the current task the

set shift on each trial involves participants shifting from processing structural information

(the probe discrimination) to processing semantic information (lexical decision) and this

set shift occurs even when no spatial shift is required.

In the present study, the stay locus trials were initially considered a condition that

did not require an attentional shift, as participants did not need to relocate spatial

attention to a different screen position to perform the lexical decision. Applying the

concept of a set shift outlined above however, it can be seen that these trials nevertheless

always required an attentional shift, moving from one aspect of a presented stimulus, in

this case the structural form of the probe, to an alternative dimension in the same locus,

this being the semantic content of the word. Having entertained the possibility that

differences may exist in shifting of attention between alternative dimensions of stimulus

information in a spatially attended locus, it becomes necessary to distinguish between

two distinct types of attentional shifting; attentional shifting that occurs between

dimensions of information within a given spatial locus and attentional shifting that occurs

between stimuli appearing in alternative spatial loci. In principle, anxiety-linked bias in

attentional engagement and disengagement could be evidenced for either, or both, of

these types of attentional shifting.

These first three modified attentional probe experiments have principally been

concerned with attentional engagement and disengagement during spatial shifting of

attention. The results of the current study however have underscored the possibility of

anxiety-liked differences in non-spatial attentional engagement and disengagement

107

evidenced when participants make set shifts from one dimension to another dimension of

stimuli occurring within the same spatial locus. The prospect of an anxiety-linked bias in

attention operating within a single locus would not be without empirical basis. Indeed one

of the most reliable measures to consistently demonstrate selective attentional bias

favouring negative stimuli involves the presentation of only a single stimulus. As

discussed in the general introduction, the emotional Stroop task developed by Mathews

and MacLeod (1985) utilised an adapted version of the traditional Stroop task (Stroop,

1938) in which participants are required to name the text colour of negative and non-

negative words while ignoring the content, with response latencies taken to indicated the

degree to which individuals have been able to avoid processing the semantic content of

these words. Mathews and MacLeod (1985) demonstrated that clinically anxious

individuals in this study exhibited significantly longer colour-naming latencies for

negative as compared to non-negative stimuli. Such effects have been repeated a number

of times with high trait anxious members of the general population (e.g. MacLeod &

Rutherford, 1992). The observation of such effects using the emotional Stroop task

strongly suggest that an anxiety-linked attentional bias can be demonstrated in a task

involving a single stimulus with two salient dimensions.

The results of the current study suggest that high trait anxious individuals may be

disproportionately fast to switch from processing neutral stimulus information to negative

stimulus information, when task conditions do not require that they relocate spatial

attention. However, as the current task was specifically designed to assess relative

speeding to spatially shift attention, conclusions regarding the existence of an anxiety-

linked attentional engagement bias operating within a single locus based on results of the

current task are tentative, though worthy of further enquiry. To assess whether anxiety-

108

linked attentional bias is characterised by enhanced attentional engagement with, or

impaired attentional disengagement from, the content of negative material presented

within a single spatial location, it would be necessary to construct a task requiring

participants to process either of two dimensions of simple stimuli, only one of which is

semantic content. In order to measure biased attentional engagement it would be

necessary to first require participants process the non-emotional dimension of the

stimulus (e.g. form) before requiring that they process an emotional dimension of the

stimulus (e.g. semantic meaning). The relative speed to process the emotional dimension

of a negative or non-negative stimulus, after having processed the non-emotional

dimension, would therefore provide an index of attentional engagement. By reversing the

order in which the stimulus dimensions are processed by first requiring the emotional

dimension to be processed before the non-emotional dimension, the task could also yield

a measure of attentional disengagement. Such a condition would provide an index of the

speed with which an individual could disengage from processing the emotional content of

a negative or non-negative stimulus to process a non-emotional dimension of the same

stimulus.

An adapted version of the emotional Stroop task could provide the conditions

necessary to yield measures of both non-spatial attentional engagement and

disengagement. The negative and non-negative words presented in coloured text in the

emotional Stroop task provide the necessary stimuli in that it contains both a non-

emotional dimension, in the text colour, and an emotional dimension, in the word

content. Requiring participants to switch between these different stimulus dimensions

could therefore yield a measure of both non-spatial attentional engagement and

disengagement. By consecutively revealing structural and conceptual elements of a single

109

stimulus that participants are required to process, such a „decoupled‟ Stroop task could

act to clarify whether the current findings suggesting that high trait anxious individuals

selectively engage with the semantic content of negative words in an attended locus are in

fact reliable. The principal focus of Experiment 4 therefore was to measure whether

attentional bias in anxiety is characterised by biased attentional engagement with or

disengagement from the emotional dimension of negative and non-negative words.

While the results of the present experiment implicate the possibility of an

attentional engagement bias operating within a spatial locus, it should be noted that the

variants of the attentional probe task used in Experiments 1, 2 and 3 have not produced

evidence to support the presence of either an anxiety-linked attentional engagement bias,

or attentional disengagement bias operating in the preferential allocation of spatial

attention to negative stimuli. The absence of either an anxiety-linked engagement or

disengagement bias in spatial attention would clearly oppose predictions derived from

past results using the original attentional probe task. These past experiments (e.g.

MacLeod et al., 1986) have consistently revealed that high trait anxious individuals

preferentially attend to the locus of negative as compared to non-negative stimuli. Such

finding would implicate the role of either enhanced attentional engagement with, or

impaired disengagement from negative stimuli in the spatial allocation of attention for

these high trait anxious individuals. The past findings regarding anxiety-linked

attentional bias and the spatial allocation of attention therefore stand in contrast to the

present results which have not demonstrated an anxiety-inked attentional engagement or

disengagement effect favouring negative stimuli in the spatial allocation of attention.

The inconsistency between past and present findings in relation to selective

allocation of spatial attention may plausibly be attributed to subtle, but possibly important

110

differences between the specific formats of the tasks used. While this possibility will be

considered more fully in the final discussion, it can be noted here that a necessary

innovation in the present task has been the introduction of a requirement for attention to

be initially assigned to a prescribed location, followed by the requirement for attention

either to disengage from this locus or not. If anxiety-linked attentional bias reflects

individual differences in the tendency to allocate attention to a particular region, rather

than individual differences in the ability to fulfill a requirement to do so then this may

explain the differential sensitivity of previously employed attentional probe tasks, which

do not include such a requirement, as compared to the current experimental tasks. This is

an issue that will be returned to and expanded upon in the general discussion.

In summary, the aim of the current study was to assess anxiety-linked differences

in relative speeding to spatially shift attention to engage with the semantic content of

negative and non-negative words. Contrary to the predictions of the Biased Attentional

Engagement hypothesis, high trait anxious individuals evidenced disproportionate

slowing to shift spatial attention to process the semantic content of negative words as

compared to remaining in the same locus to semantically process these stimuli.

Subsequent analyses of the component effects suggest that what appeared to be slowing

to spatially shift attention the opposite screen position in fact may be due to

disproportionate speeding to process the content of negative material on trials where no

spatial shift in attention is required. This result highlighted the possibility that biases in

attentional engagement and disengagement could occur in the absence of a spatial shift

between different stimuli and instead occur within an attended spatial locus between

different dimensions of the same stimulus. Based on these results, the aim of the

111

Experiment 4 was to further examine anxiety-linked differences in attentional

engagement with, or disengagement from, emotional dimensions of a single stimulus.

112

CHAPTER 5

EXPERIMENT 4

The results of Experiment 3 highlighted the possibility that attentional bias in

anxiety may be characterised by a tendency to selectively engage attention with the

semantic content of a negatively valenced word, after having processed non-emotional

information occupying the same spatial location (i.e. probe structure). It is equally

possible that the equivalent process could also operate for attentional disengagement,

where individuals more vulnerable to anxious mood may have greater difficulty

disengaging attention from the emotional content of a negatively valenced word to non-

emotional information occupying the same spatial location.

As distinct from the assumption that attention stays or moves depending on

whether a stimulus appears in the same or different location, the results of Experiment 3

highlight that attention can move between different stimulus information within a single

locus. Entertaining the possibility that attentional shifts, and indeed attentional biases, can

occur within a single locus moves from the preconception of the past studies that it is

necessary to cause spatial shifts in attention to elicit and measure individual differences

in attentional engagement and disengagement. While the presence of an attentional

engagement or attentional disengagement bias occurring within a single locus would not

eliminate the need to account for the absence of findings in relation to spatial engagement

and disengagement, it is nevertheless important to establish the pattern of attentional bias

that may be present for shifts in attention occurring within a single locus. A clear

implication of attentional shifts occurring within a single locus is that when two pieces of

information are processed in sequence, there is always an attentional shift from one to the

other, regardless of whether a spatial shift in attention is required. Thus, attention must

113

always disengage from one initially attended piece of information and engage with the

subsequently attended piece of information. Therefore, rather than attempting to

experimentally control whether an attentional shift occurs or not, it becomes more useful

to control the emotionality of the stimulus being shifted from, or the emotionality of the

stimulus being shifted towards, in order to differentiate processing biases in attentional

disengagement and attentional engagement. Having individuals initially process

emotional content of a stimulus before then requiring that they process a non-emotional

dimension of this stimulus would provide a measure of biased attentional disengagement

from differentially valenced semantic content. Conversely, requiring an individual to first

process a non-emotional dimension of a stimulus before engaging with the semantic

content of the stimulus would provide a measure of biased attentional engagement with

the semantic content. A key purpose of the current study was to move from the previous

focus on whether attention stays within, or moves from, differing spatial loci, to instead

develop and employ a methodology capable of measuring biased attentional engagement

with and disengagement from emotional content occurring within a single locus.

One of the most commonly used tasks for assessing attentional bias already

provides a methodology capable of measuring biased attention within a single locus.

Specifically, the emotional Stroop task has been a frequently used and reliable means of

measuring attentional bias. Research conducted using this task has consistently

demonstrated that individuals with clinical levels of anxiety, relative to low anxious

controls, are significantly slower to colour-name negative as compared to non-negative

words (e.g. Mathews & MacLeod, 1985; Mogg, et al., 1989), suggesting selective

processing of negative stimulus content, as opposed to stimulus colour, by those with

higher anxiety vulnerability. It has further been demonstrated that this pattern of effects

114

generalises to high trait anxious members of the general population including

undergraduate university students (e.g. MacLeod & Rutherford, 1992). As reviewed in

the introduction, studies have also shown that the attentional preference for negative

content revealed by performance on the emotional Stroop task reduces with improvement

in anxious mood resulting from psychological treatment (Mathews, Mogg, Kentish, &

Eysenck, 1995), and also is predictive of the severity of emotional response to a future

stressful life event (MacLeod & Hagen, 1992). The original emotional Stroop task

therefore provides a reliable and robust measure of anxiety-linked attentional bias to

negative and non-negative dimensions of stimuli presented in a single spatial locus.

However, the anxiety-linked attentional bias observed using the emotional Stroop

task could readily be accounted for by either biased attentional engagement with, or

biased disengagement from, negative semantic content. The Biased Attentional

Engagement account of anxiety-linked attentional bias suggests that high trait anxious

individuals may preferentially engage with the semantic content of negative words which

in turn results in longer latencies to perform the task of colour-naming the text of such

stimuli, as the colour information has received less attention. Alternatively, the Biased

Attentional Disengagement account suggests that both high and low trait anxious

individuals have an equal tendency to attend initially to the semantic content of negative

or neutral words, but high trait anxious individuals have greater difficulty then

disengaging attention from this semantic information when it is negatively valenced, as is

required to efficiently perform the task of colour-naming the text.

The great majority of studies using the emotional Stroop task have instructed

participants to ignore the semantic content of the stimulus while naming the colour and

have inferred enhanced processing of negative material by slowing to colour-name the

115

text. On occasion however, researchers have employed assessment versions of this task

where participants have been directed to ignore the colour and process the content. Here,

increased processing of negative material would instead be revealed by speeding to

register the semantic content of the stimulus. Campbell (2001) used such a version of the

emotional Stroop to assess attentional bias in a group of individuals exposed to a

manipulation designed to induce an attentional bias to negative words. Her study found

that, on trials where these participants were instructed to ignore the word content, they

were slow to colour-name the text of negative, as compared to non-negative words,

whereas on trials where they were required to process semantic content by performing a

grammatical judgment decision, they were relatively faster to make this decision for

negative as compared to non-negative words.

Campbell‟s version of the emotional Stroop demonstrates how assessing either the

speed to process a word‟s colour, or assessing speed to process that word‟s semantic

content, can reveal selective attention favoring information of a particular valence. A

modified version of the emotional Stroop used by Campbell (2001) could readily fulfill

the task requirements associated with the present goal of distinguishing biased attentional

engagement with and biased attentional disengagement from emotional information.

Rather than requiring participants to either process semantic content or colour on a given

trial, they could instead be required to process both colour and semantic content on each

trial, in either of the two possible orders in which these two decisions could be made. In

these trials, latencies to perform the second decision can reveal the biases of relevance.

Specifically, on trials where participants initially process colour information before

processing semantic content, the second decision latency will reveal the time taken to

switch attention from processing colour to engage with the semantic content. Conversely,

116

on trials where the decision order is reversed and participants first process semantic

content before colour information, latency to perform the second decision will reveal the

time taken to disengage attention from the semantic content and switch attention to

process colour information. A measure of biased attentional engagement with

differentially valenced word content would be provided by requiring participants to

initially identify the colour of the stimulus before then requiring them to semantically

process the content of a negative or non-negative word by making a grammatical

classification decision. The speed of this second decision would provide an indication of

individual differences in biased attentional engagement with the semantic content of

these words as participants move attention to this information after first processing the

text colour. A measure of biased attentional disengagement from differentially valenced

word content would instead be obtained by first requiring participants to process the

semantic content of the negative or non-negative word, by making a grammatical

classification judgment, before then identifying the text colour. Now, this second decision

latency (to identify text colour) would provide a measure of biased attentional

disengagement from the initially processed semantic information, as participants would

need to move attention from this emotional information to instead process the non-

emotional colour information to make the second decision.

A modified version of the emotional Stroop task was therefore constructed to

enable the measurement of biased attentional engagement with and disengagement from

semantic content of negative and non-negative words. It should be noted that this variant

the emotional Stroop was modified to a task switching variant, with attention orienting

between colour and content dimensions of the stimulus which become available for

processing at different stages. Because the biased attentional engagement and

117

disengagement accounts of the emotional Stroop effect are in essence competing task-

switching based accounts, it was necessary to modify the task in a way that could

discriminate these task switching accounts. Therefore while the modified variant involves

task switching, it is still referred to as a modified emotional Stroop, albeit one that is

modified to test alternative task switching (biased attentional engagement or

disengagement) accounts of the emotional Stroop effect.

The Biased Attentional Engagement and Biased Attentional Disengagement

accounts of attentional bias both make different predictions about the pattern of effects

that are expected to emerge in the current study. Specifically, the Biased Attentional

Disengagement hypothesis predicts that high trait anxious individuals will exhibit greater

difficulty disengaging attention from the semantic content of negative words as revealed

by disproportionate slowing to colour-name negative words on the second trial decision,

after having processed their semantic meaning on the first trial decision. The biased

attentional engagement hypothesis however predicts that high trait anxious individuals

will be disproportionately fast to grammatically classify negative as compared to non-

negative stimulus words, after having identified the stimulus text colour as the first trial

decision, thereby demonstrating enhanced attentional engagement with the semantic

content of these words on the second trial decision.

Method

Overview

To achieve measures of biased attentional engagement with, and disengagement

from, emotional content, the task used in the current study utilised two distinct trial types

involving a different sequence of stimulus processing requirements. These two trial types

118

will be referred to as Semantic Engagement Trials and Semantic Disengagement Trials

for those assessing biased attentional engagement with, and biased attentional

disengagement from, the semantic content of differentially valenced words respectively.

An instruction was given at the beginning of each trial to indicate whether the trial would

first require the processing of colour, followed by the semantic processing of word

content, or the semantic processing of word content, followed by the processing of

colour. As in Campbell‟s (2001) version of the emotional Stroop, grammatical judgment

was used to ensure participants semantically processed the word. The measures of

attentional engagement and disengagement were provided by the latency to make the

critical second decision on each trial. On this second decision, participants were always

looking at a coloured word. The difference across the two trial types was that, for

Semantic Engagement Trials, participants were switching to process the word meaning

having previously been exposed to the colour information, while for Semantic

Disengagement Trials, participants were switching to process the colour information

having processed the stimulus meaning. To ensure that these measures of attentional

engagement and disengagement were not compromised by the premature processing of

the stimulus information needed to make the second decision, this stimulus information

did not become available until participants made their first decision in the trial.

Therefore, on Semantic Engagement Trials, participants were initially presented with the

colour information, delivered in the form of a coloured string of random letters. As soon

as their colour-naming response was detected, the letter string transformed into the word

that participants were required to make a grammatical classification of. If anxiety is

characterised by biased attentional engagement with emotional content then high trait

119

anxious individuals should be disproportionately fast to grammatically judge the negative

as compared to the non-negative words on these trials.

For Semantic Disengagement Trials, the sequence in which stimulus information

became available was reversed. A negative or non-negative word in white text first was

presented and participants were required to grammatically classify this word. As soon as

this response was detected, colour information was added to the stimulus and participants

were required to verbally name this colour aloud. If anxiety is characterised by difficulty

disengaging attention from the semantic content of a negative stimulus, then high trait

anxious individuals will be disproportionately slow to make this colour naming-response

when they had initially been required to grammatically classify negative as compared to

non-negative word content.

Participants

To ensure that participants differed in trait anxiety as required at the time of

testing, selection of potential participants was again guided by the screening of

undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory

(STAI-T; Spielberger et al., 1983) prior to the commencement of the study. Six hundred

and one participants were screened, with those obtaining scores on the STAI-T which fell

in the upper third (at or above 42) or the lower third (at or below 35) of the distribution

being considered eligible for the study. Of those recruited, 20 were from the upper third

of the distribution (high trait anxious group) and 20 were from the lower third of the

distribution (low trait anxious group). The low trait anxious group comprised five male

and 14 female participants with an average age of 18.35 years (SD = 1.66), while the high

trait anxious group consisted of five male and 15 female participants with a mean age of

120

19.95 years (SD = 6.30). The high and low trait anxious groups did not differ

significantly in terms of age, t(38) = 1.10, ns, or gender ratio ²(1,38) = 0.12, ns.

Materials

Emotional Assessment Measure

The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)

was again employed as the emotional assessment measure.

Stimulus Words

The same 48 negative and 48 non-negative words used in each of the previous

studies were again used in the current task. An additional stimulus set consisting of 20

non-negative words was also created for use in practice trials.

Experimental Hardware

Experimental task delivery was again controlled by an Acorn Archimedes 5000

computer, with high resolution monitor. A microphone and voice key were also attached

for detection of colour-naming responses.

Experimental Task

Each trial began with an instruction string presented in text 10mm in height in the

centre of a blank screen which informed participants of the order in which they would

have to perform the two decisions of colour-naming and grammatical classification. The

task contained two distinct trial types measuring either biased attentional engagement

with (Semantic Engagement Trials) or disengagement from (Semantic Disengagement

Trials) the semantic content of negative and non-negative words. For the Semantic

Disengage Trials, the initial instruction string was either the word VERB, NOUN or

ADJECTIVE paired with the word COLOUR (e.g. “NOUN/COLOUR”). This signaled to

participants that they were first required to make a grammatical classification, as to

121

whether the stimulus word belonged to the stated grammatical category, then to make a

colour naming decision. This initial instruction remained on the screen until participants

pressed the spacebar to begin the trial. A negative or non-negative word in white text was

then presented and participants were required to decide as to whether the word belonged

to the grammatical category presented in the instruction string, and respond by pressing

mouse key labeled “yes” or “no”. Response latency and accuracy were recorded for this

decision. Immediately following the registration of this response, the letter string changed

from white to one of four colours (red, blue green or yellow). Participants were required

to name this colour aloud and their latency to colour name the text, taken as the interval

between the onset of the colour and the detection of the colour naming response by a

voice activated microphone, was recorded. This response terminated the trial and the

instruction for the next trial appeared 1000ms later. Figure 5.1a provides an example

illustration of these trials assessing biased attentional disengagement, when either

negative or non-negative words were employed.

On Semantic Engagement Trials, the instruction string consisted of the word

COLOUR paired with either the word VERB, NOUN or ADJECTIVE (e.g.

“COLOUR/VERB”) indicating that participants were required to make a colour naming

decision before a grammatical judgment. Once participants had registered this instruction

and pressed the spacebar to proceed, a random letter string, automatically generated on

these trials, was first presented in one of four colours (red, blue, green or yellow) and

participants were required to name aloud the colour of the letter string. When this

response was detected, the colour information remained, but the random letter string

transformed into a negative or non-negative word of equal length, and participants were

required to determine whether this word belonged to the grammatical category presented

122

in the instruction string by pressing the corresponding “yes” or “no” mouse key.

Response latency and accuracy for this grammatical judgment was recorded on these

trials. Figure 5.1b provides an example of Semantic Disengage Trials, using a negative

and a non-negative word.

5.1 a) Semantic Disengagement Trials

Instruction Grammatical Judgment Colour Name

5.1 b) Semantic Engagement Trials

Instruction Colour Name Grammatical Judgment

Figure 5.1. Trials assessing biased attentional engagement with and disengagement from

negative and non-negative word content. Colour type and grammatical class shown

randomly.

Grammatical Judgment/

Colour name trial

Using Negative Word

Grammatical Judgment/

Colour name trial

Using Non-Negative Word

NOUN/COLOUR

FEAR

FEAR

VERB/COLOUR

SOFTENER

SOFTENER

Colour Name/

Grammatical Judgment Trial

Using Negative Word

COLOUR/NOUN

DBSLMWQI

RIDICULE

COLOUR/VERB

KCYMSQAILK

WATERPROOF

Colour Name/

Grammatical Judgment Trial

Using Non-Negative Word

123

The task consisted of 384 experimental trials in total. Each of the 48 negative and

48 non-negative words was presented once within each presentation sequence of 96 trials

before any were repeated again. An equal number of Semantic Disengagement Trials and

Semantic Engagement Trials were included within a presentation sequence of 96 trials

with the presentation order of trial type being randomised within these 96 trials. Text

colour was also randomised within each sequence of 96 trials, with the constraint that

each colour (red, blue, green, yellow) was presented an equal number of times. Thus

across all 348 trials each stimulus was presented four times, two times in the Semantic

Disengagement Trials and two times in the Semantic Engagement Trials. To minimise

potential practice effects resulting from repeating the required grammatical classification

for the same words, the grammatical class specified in the instruction string was changed

when a given word was presented for a second time. Therefore, if participants had been

required to determine if the word “powerless” was a verb at an early point in the task,

they would decide whether it was an adjective when it again appeared later in the task.

The correct response to a grammatical classification was balanced across the stimuli such

that correct performance of the task required an equal number of “yes” and “no”

responses across the 348 trials. Across participants, the allocation of stimuli to each trial

type was counterbalanced such that after two participants had been tested, each stimulus

word had appeared in each possible condition once. Word stimuli, the part of speech

category used to classify each word on first and second presentations and correct

responses to these are provided in Appendix D. Participants were given the opportunity

of a brief self-paced rest period after the completion of 192 trials.

124

Procedure

All participants were tested individually in a sound attenuated cubicle. On arrival

participants first completed both state and trait sections of the Spielberger State-Trait

Anxiety Inventory (STAI; Spielberger et al., 1983) before beginning the experimental

task. Prior to commencing the experimental task participants were provided instructions

highlighting that the task would require them to make two responses on each trial, a

grammatical judgment response and a colour naming response, and that the order in

which they were required to make these responses would be specified at the start of each

trial. The nature of the initial instruction string, and the method of responding was then

described to participants. They were informed that colour-naming responses would be

detected by a microphone, and directed to respond verbally to name the text colour. They

were told that their grammatical judgment responses were to be made by pressing the

corresponding mouse key labeled “yes” or “no” according to whether or not the word

could belong to the part of speech specified in the instruction string. Participants were

directed to be as fast as possible in responding without compromising accuracy. Practice

trials were then completed before participants commenced the experimental task. These

trials used the neutral words created for this purpose and presented 10 Semantic

Disengage Trials and 10 Semantic Engagement Trials in random sequence.

Results

Participant characteristics at the time of testing are provided in Table 5.1.

Measures of trait anxiety using the STAI-T taken at the time of testing confirmed that

high and low trait anxious groups continued to differ in terms of trait anxiety, t(38) =

125

9.50, p < .01, with the high trait anxious group displaying a mean score of 49.80 (SD =

8.37) and the low trait anxious group with a mean of 30.50 (3.53).

Table 5.1

Characteristics of participants in Experiment 4. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F

High Trait Anxious 49.80 (8.37) 43.05 (7.96) 19.95 (6.30) 5:15

Low Trait Anxious 30.50 (3.53) 29.90 (3.53) 18.35 (1.66) 6:14

All Participants 40.15 (11.65) 36.02 (9.58) 19.15 (4.62) 11:29

Not surprisingly, high and low trait anxious individuals were also observed to

differ in terms state anxiety as measured by the STAI-S score t(38) = 6.83, p < .01. The

presence of this group difference in state anxiety means that any observed group

differences in task performance in this study could be attributable to state, rather than

trait anxiety. For this reason, correlational analyses will be conducted to determine

whether observed effects are associated to a greater extent with either state or trait

anxiety.

As high rates of inaccuracy for grammatical judgment responses could signal that

participants were not processing the semantic content of stimulus words as required, it

was necessary to exclude those participants with high rates of error. Accuracy of

grammatical judgments proved to be rather low with participants averaging only 81.64%

correct responses for the grammatical judgment component of the task. This higher rate

of error carries important implications that will be returned to in the discussion section

and will bear upon the design of the next experiment. For the present, however, it should

126

be noted that application of the inclusion criteria used in the previous three studies of

minimum 80% accuracy resulted in 16 participants being excluded from the final

analysis, which significantly reduced statistical power in the current study. Although an

argument might be made to be more liberal with respect to acceptable error rate to

increase power, this too would compromise comparisons by including those participants

with a larger error rate. Given that chance responding would have secured an accuracy of

50%, the predetermined inclusion criterion of 80% accuracy was retained. However, the

analyses were also performed with the inclusion of all participants. As will be reported in

footnotes, no difference in the pattern of obtained effects was observed when all

participants were included in the analysis. Of the 16 participants excluded on the basis of

low accuracy, nine came from the high trait anxious group and seven came from the low

trait anxious group. A significant differences was observed between high and low trait

anxious groups in rates of accuracy for those not excluded, F(1, 22) = 6.72, p < .05,

whereby the high trait anxious individuals obtained significantly fewer incorrect

responses (M = 51.81, SD = 7.61) than the low trait anxious individuals (M = 61.46, SD =

51.82). This difference was not significant, however, when all participants were included

in the analysis F(1, 38) = 0.24, ns. Analyses for trials assessing biased attentional

disengagement from, and biased attentional engagement with emotional content are

considered separately in consecutive analyses below.

Assessment of Biased Attentional Disengagement from Semantic Content

Semantic Disengagement Trials assessing biased attentional disengagement from

semantic content were those requiring participants to first make a grammatical judgment

of negative or non-negative words before switching to then colour-name the text of these

stimuli. Latencies to colour name the text, reflecting the speed of this second decision,

127

were recorded as the dependent measure on these trials with longer latencies taken to

indicate greater difficulty disengaging from the semantic content of the word. As

disengagement from this initially presented semantic material can only be assessed when

participants did initially engage with this semantic content, the colour-naming latencies

were included only from trials on which participants had recorded correct grammatical

judgments as their first decision. To minimise the influence of outlying colour-naming

latencies, median response latencies were computed, and these latencies are provided in

Table 5.2.

Table 5.2

Latencies for second trial responses (colour-naming) in milliseconds on Semantic

Disengage Trials, across negative and non-negative word stimuli for high and low trait

anxiety groups. Standard deviations given in parenthesis.

Word Valence High Trait Group Low Trait Group

Negative Word Trials 625.00 (141.01) 594.61 (123.27)

Non-Negative Word Trials 622.27 (148.87) 600.77 (117.08)

These data were subjected to a 2 x 2 mixed design ANOVA with word valence

(negative or non-negative) as the within group factor and trait anxiety group (high or low)

as the between group factor. According to the Biased Disengagement account of

attentional bias in anxiety, on Semantic Disengagement Trials high trait anxious

individuals should exhibit disproportionately slow colour-naming responses after having

grammatically classified negative as compared to non-negative words, resulting in a two

way interaction between word valence and trait anxiety group. The two-way interaction

128

predicted by the biased attentional disengagement account did not approach significance

F(1, 22) = 0.04, ns2, and no other significant effects emerged from the interaction. This

result is inconsistent with the hypothesis that anxiety-linked attentional bias is associated

with biased attentional disengagement from emotional content. It is not however

inconsistent with the Biased Attentional Engagement account of anxiety-linked

attentional bias.

While no group differences were observed to suggest biased attentional

disengagement from emotional content, potential associations between this measure and

either state or trait anxiety could potentially still exist. Correlational analyses were

therefore conducted to establish if this was the case. A single index of impaired

attentional disengagement from negative content was therefore computed. This was

achieved by subtracting colour-naming response latencies following grammatical

judgment on non-negative words from colour-naming response latencies following

grammatical judgment on negative words on Semantic Disengagement Trials. The

resulting index represented a measure of impaired attentional disengagement from

negative word content, with higher scores indicating greater slowing to disengage

attention from negative as compared to non-negative words. Pearson‟s correlations

between this index of impaired attentional disengagement from negative content and

STAI-T scores, r(24) = .08, ns, and STAI-S scores, r(24) = .06, ns, did not prove to be

significant3. Again the absence of such associations is inconsistent with the Biased

2 This two-way interaction remained non-significant when the analysis was conducted including all

participants regardless of accuracy levels F(1, 38) = 0.41, ns. 3 These correlations between the index of biased attentional disengagement and STAI-T scores, r(40) = .00,

ns, and biased attentional disengagement STAI-S scores, r(40) = -.05, ns, remained non-significant when

all participants were included in the analysis, regardless of accuracy levels.

129

Attentional Disengagement account of attentional bias, but is not inconsistent with the

Biased Attentional Engagement account.

Assessment of Biased Attentional Engagement with Emotional Content

The trials assessing biased attentional engagement with emotional content were

those where participants first made a colour-naming decision before switching to make a

grammatical decision of a negative or non-negative word. Speeding to make grammatical

decisions for negative, as compared to non-negative words on these trials would suggest

enhanced attentional engagement with the semantic content of these stimuli. The

grammatical decision latencies comprised dependent measure on these trials. Only trials

on which participants made correct grammatical decisions were include in the analysis,

and median grammatical decision response latencies were again used to minimise the

influence of outlying data. The average of these grammatical decision latencies for

negative and non-negative words across high and low trait anxious individuals are

provided in Table 5.3.

Data from these trials assessing biased attentional engagement with emotional

content were subjected to a 2 x 2 repeated measures ANOVA with one between group

factor, being trait anxiety group (high or low) and one within group factor, being word

valence (negative or non-negative). The Biased Attentional Engagement account of

anxiety-linked attentional bias predicts that on Semantic Engagement Trials, high trait

anxious individuals will be faster to make grammatical decisions for negative as

compared to non-negative words, resulting in a two-way interaction between word

valence and trait anxiety group. No significant effects emerged from this analysis, with

130

the interaction between trait anxiety group and word valence predicted by the biased

attentional engagement account not approaching significance, F(1, 22) = 0.69, ns4.

Table 5.3

Latencies for second trial responses (grammatical decision) in milliseconds on Semantic

Engage Trials, across negative and non-negative word stimuli for high and low trait

anxiety groups. Standard deviations given in parenthesis.

Word Valence High Trait Group Low Trait Group

Negative Word Trials 1795.91 (364.70) 1632.31 (710.08)

Non-Negative Word Trials 1622.73 (283.15) 1569.23 (675.03)

As before, correlational analyses were also conducted to determine if any

relationships could be observed between an index of this attentional bias and state or trait

anxiety. An index of enhanced attentional engagement with negative information was

therefore computed by subtracting grammatical judgment latencies for negative words

from grammatical judgment latencies for non-negative words. Higher scores on the

resulting index therefore represent speeding to switch from processing word colour to

process the content of negative as compared to non-negative words. Neither of the

correlations between this index of enhanced attentional engagement with negative

information and STAI-T scores, r(24) = -.16, ns, or STAI-S scores, r(24) = -.14, ns,

proved to be significant5.

4 This two-way interaction remained non-significant when the analysis was conducted including all

participants regardless of accuracy levels F(1, 38) = 2.65, ns. 5 The correlation between the index of biased attentional engagement and STAI-T scores, r(40) = -.28, ns,

and the index of biased attentional engagement and STAI-S scores, r(40) = -.21, ns, remained non-

significant when all participants were included in the analysis, regardless of accuracy level.

131

Discussion

The aim of the present study was to develop a task capable of measuring biased

attentional engagement with and disengagement from emotional content when orienting

attention between emotional and non-emotional information contained within the same

stimulus. The current task was designed to measure biased attentional engagement with

emotional content by examining the speed with which participants could switch from

processing colour to instead semantically process the content of negative and non-

negative words. Biased attentional disengagement was measured by examining how

rapidly participants were able to switch from processing the content of negative and non-

negative words to instead process the colour of such stimuli. The results of the present

study provided no support for either the Biased Engagement or Biased Disengagement

accounts of anxiety-linked attentional bias. Correlational analyses similarly revealed no

evidence for associations between measures of biased attentional engagement with and

disengagement from emotional content and measures of state or trait anxiety.

While the current experiment failed to provide support for either Biased

Attentional Engagement or Biased Attentional Disengagement accounts of anxiety-linked

attentional bias, the high rate of inaccuracy on the grammatical judgment component of

the task would suggest caution against prematurely dismissing either account based on

the present findings. The purpose of including a grammatical judgment response in the

current experiment was twofold; to ensure participants engaged with the semantic

meaning of stimulus words before assessing their ability to disengage from this

information and, to provide a measure of the speed with which participants could switch

from processing colour to instead engage with emotionally valenced content of the

132

stimuli. The low rate of accuracy observed in the current task could have been due to

participants not reliably processing word content when required to do so or, may have

been due to their difficulty determining the grammatical class of stimulus words even

after accessing their meaning. Indeed, it was noted when conducting testing that a

number of participants requested clarification as to the definition of the part of speech

categories included in the task (verb, noun and adjective) suggesting that there may have

been some confusion in making grammatical judgments.

The results derived from the current task do not allow us to discriminate whether

the high error rate was due to unreliable processing of word content or difficulty with

making grammatical judgments. Either of these possibilities would be problematic for

measuring biased attentional engagement and disengagement however. Indeed, if the

error rate was principally due to participants not having processed the content of the

stimuli, it would mean that the task was not indexing engagement with or disengagement

from such stimulus content. However, even if we assume that participants were

processing the stimuli, and the high error rate reflects greater difficulty making

grammatical judgments, this raises concerns as to whether the latency to make this

decision provides an accurate indication of speed to access the semantic content of the

stimulus.

It is possible that determining the grammatical class of a word involves

considerable post-lexical processing after the semantic content of the word has been

identified. If this were the case, the variance in such post-lexical processing may obscure

individual differences in the tendency to process negative and non-negative word content

across individuals who vary in anxiety vulnerability. The observed difference in average

latency to perform a grammatical judgment responses on the current task (M = 1650.52)

133

as compared to the average latency to perform lexical decision responses on the task used

in Experiment 3 (M = 1127.61) further reinforces the notion that performing grammatical

judgments may involve extensive post-lexical processing of stimulus words as compared

to performing a lexical decision. If we accept that a lexical decision results in participants

accessing a words meaning and responding in around 1100ms in Experiment 3, then the

longer latencies when performing grammatical judgment in the current task would

suggest that participants are doing considerably more post-lexical processing of the

stimulus. The degree of variance observed in grammatical decision latencies in the

current study (SD = 524.11) as compared to lexical decision latencies in Experiment 3

(SD = 272.86) would further suggest that any post-lexical processing that occurs when

making grammatical judgments is likely to be highly variable. The longer decision

latencies and greater variance in performing a grammatical decision could therefore be

obscuring the speed to access semantic content of the stimuli and any effects relating to

biases in engagement with or disengagement from the content of such stimuli.

Based on these concerns it was decided to modify the task used in the current

study by employing a better means of ensuring that participants process semantic

information, and measuring the speed with which this occurs. The key purpose of

Experiment 5 was therefore to modify the current task by adopting an improved means of

securing lexical access, which would minimise post-lexical processing and allow the high

levels of accuracy necessary to permit confidence that stimulus meaning was accessed. It

was anticipated that using lexical decision as a means of assessing lexical access would

instead minimise additional time and variance associated with performing a grammatical

judgment decision and will provide a more consistent response time that is more

representative of speed to access word meaning. Such a decision is also likely to permit

134

the high levels of accuracy necessary to allow confidence that stimulus meaning has

indeed been accessed.

In summary, this present experiment adopted a novel means of assessing whether

anxiety-linked attentional bias is characterised by enhanced attentional engagement with

or impaired disengagement from negatively valenced information. This was achieved by

requiring participants to switch to processing the colour of negative and non-negative

stimuli after first processing their emotional content to assess biased attentional

disengagement, and by requiring participants to switch to process semantic content of

negative and non-negative words after first processing the colour of these words to assess

biased attentional engagement. The results provided no support for either the Biased

Engagement or Biased Disengagement accounts of anxiety-linked attentional bias, but

high rates of error, slow response times and high variance in response latencies in the

grammatical judgment component of the task highlight the possibility that participants

may have experienced difficulty performing this grammatical judgment decision. This

may be due to greater post-lexical processing involved in performing this decision, which

would obscure anxiety-linked differences of interest. Experiment 5 therefore aimed to

modify the task used in this study to include a decision that would ensure participants

processed word content, and enable the precise measurement of speed with which

semantic access occurred. The use of lexical decisions was therefore adopted in place of

grammatical judgment in Experiment 5.

135

CHAPTER 6

EXPERIMENT 5

The principal purpose of Experiment 5 was identical that of the previous study in

that the aim was to measure anxiety-linked differences in biased attentional engagement

with and disengagement from negative and non-negative word content of single stimuli.

The approach taken in the current experiment was to refine the task employed in the

previous study, to provide a better measure of these attentional processes. As highlighted

in the discussion of Chapter 5, the use of grammatical judgment as a means of assessing

participants‟ speed to access the semantic representation of a word may in fact implicate

variable and time consuming cognitive processes beyond those required to simply access

the semantic meaning of a word. If this is the case then measures of speed to make such

grammatical judgments will not necessarily provide an accurate measure of time taken to

process the semantic content of a stimulus and therefore are unlikely to be sensitive to

anxiety-linked differences in accessing the semantic representation of a word due to the

effects of these post-lexical processes. The grammatical classification component of this

process may therefore obscure anxiety-linked differences in attentional engagement or

disengagement that are present at the point where participants are simply accessing the

meaning of the word. In the present study it was therefore desirable to include a simple

measure of access to semantic meaning that minimises the need for any post-lexical

processing. Such a response would ideally require a participant only to identify the

content of the word by acknowledging that the presented stimulus word has an analogous

stored representation in memory. A lexical decision can only be performed by accessing

the representation of a word, including its associated semantic meaning (James, 1975;

Schvaneveldt et al., 1976). Such a decision also has the benefit of requiring only a simple

136

decision with minimal post-lexical processing, in that the task of determining the lexical

status of a real word is complete once the representation of that word has been accessed.

To include a measure of semantic access that would be less affected by post-lexical

processes it was therefore deemed suitable to include a lexical decision response in the

current task in place of the grammatical classification response used previously by

Campbell (2001) and adopted in Experiment 4.

As with the previous study, the methodology employed in the current experiment

acknowledges that it is not possible to measure attentional engagement and

disengagement processes in isolation as attention is always moving from one piece of

information to another. Instead, the current study aims to control the emotionality of the

information that is either being shifted from or towards. The current variant of the

emotional Stroop task manipulates whether participants process the emotional content of

a stimulus as either the first or second decision on the task. By requiring participants to

first process the non-emotional (colour) stimulus information before then processing the

emotional content of negative and non-negative stimuli, the task is able to yield a

measure of the relative speed with which individuals switch attention to process such

differentially valenced information. Conversely, by requiring participants to first process

the semantic content of differentially valenced words before then processing the non-

emotional stimulus information (text colour), the task is able to provide a measure of the

relative difficulty to switch attention away from the emotional content of negative and

non-negative information. The modified emotional Stroop developed in the current study

was therefore similar in format to that used in the previous experiment. The key

modification in the current task was that the means of ensuring that semantic access took

place was achieved by requiring a lexical decision rather than grammatical judgment.

137

Each trial again began with an instruction signaling to participants the order in

which they were required to perform the tasks of colour-naming and semantic processing

of word content. The instruction “COLOUR/WORD” therefore signaled that participants

were required to colour-name the presented text before determining the lexical status of

the word or non-word letter string while a “WORD/COLOUR” instruction signaled that

participants were first required to determine the lexical status of a letter string before

colour-naming the text. As in the emotional Stroop task used in Experiment 4, the

information required for the second decision was not added to the stimulus until

participants had made their first decision. Therefore, on trials assessing biased attentional

engagement with emotional content, the information on which participants performed the

lexical decision was not revealed until participants colour-named the text, while on trials

assessing biased attentional disengagement from emotional content, the text colour was

not revealed until participants recorded a lexical decision response to the initially

presented letter string. The purpose of revealing only one stimulus dimension at a time

was to ensure that participants did not have access to the stimulus dimension processed

second, which allowed confidence that the second decision was not contaminated by

premature processing of this information.

If, in accordance with the Biased Attentional Engagement account, attentional

bias in anxiety is characterised by selective attentional engagement with the semantic

content of negative stimuli, then we would predict that effects on the task would be

limited to trials where participants are required to switch attention to process the semantic

meaning of negative and non-negative stimuli having processed the colour information of

these stimuli, whereby high trait anxious individuals will be faster to determine the

lexical status of negative as compared to non-negative words. The Biased Attentional

138

Disengagement account however predicts that anxiety-linked differences will only

emerge in the current task on trials where participants switch to process non-emotional

stimulus information having previously determined the semantic content of negative and

non-negative words, whereby high trait anxious individuals will be disproportionately

slow to colour-name the text of negative as compared to non-negative words.

Method

Overview

The principal purpose of the present study was to produce a modified variant of

the decoupled emotional Stroop task used in the previous experiment capable of

measuring biased attentional engagement with, and disengagement from, the semantic

content of negative and non-negative stimuli. The task delivered two different trial types,

one designed to specifically measure the speed with which high and low trait anxious

individuals could engage attention with the semantic content of a negative or non-

negative stimulus (Semantic Engagement Trials) the other designed to measure the speed

with which these individuals could disengage attention from the semantic content of a

negative or non-negative stimulus (Semantic Disengagement Trials).

In Semantic Disengagement Trials the semantic meaning of a letter string was

first revealed before the colour dimension was added to this stimulus. Participants were

therefore required first process the material for semantic content by performing a lexical

decision before disengaging attention from this to colour-name the letter string. On the

trials of interest, this letter string was a negative or non-negative word that was initially

presented in white text. Immediately following the lexical decision response the letter

string acquired the hue of one of four colours and the latency to name this colour was

139

recorded. If anxiety is characterised by difficulty disengaging attention from the semantic

content of a negative stimulus then colour-naming responses will be disproportionately

slow for high trait anxious individuals when they are first required to lexically classify a

negative as compared to a non-negative word.

In the Semantic Engagement Trials the colour dimension of the stimulus was first

made available to participants while the semantic content of this stimulus was only

revealed subsequent to participants recording a colour-naming response. Latencies to

identify the lexical status of the semantic content were taken as a measure of the speed to

engage with the semantic meaning. On trials of interest the letter string revealed was

either a negative or non-negative word. If anxiety is associated with biased attentional

engagement with the semantic content of negative stimuli then the lexical decision

response will be disproportionately fast for high trait anxious participants on trials when

the string is a negative word.

Participants

To ensure that participants differed at test time in trait anxiety as required,

participant selection was again guided by the screening of undergraduates on the STAI-T

prior to the commencement of the study. Of the 601 participants screened, those who

obtained scores on the STAI-T which fell in the upper third (at or above 42) or the lower

third (at or below 35) of the distribution were considered eligible for the study. Of those

recruited for the study, 20 were from the upper third of the distribution (high trait anxious

group) and 20 were from the lower third of the distribution (low trait anxious group). The

low trait anxious group comprised eight male and 12 female participants with an average

age of 18.40 years (SD = 1.76) while the high trait anxious group consisted of five male

and 15 female participants with a mean age of 17.70 years (SD = 1.21). The high and low

140

trait anxious groups did not differ significantly in terms of age, t(38) = 1.46, ns, or gender

ratio ²(1,38) = 1.21, ns.

Materials

Emotional Assessment Measure

The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)

was again employed as the emotional assessment measure.

Stimulus Words

As lexical decisions were required in the current task it was necessary to include

an equal number of non-word lexical decision targets to supplement word stimuli to

ensure participants attempted lexical access for all words. As discussed in Chapter 3, it is

necessary for non-words used in a lexical decision task to be graphemically legitimate to

ensure that participants process stimuli for potential meaning rather than being able to

make a judgment of lexical status based on graphemic legitimacy alone. Lexical stimuli

was therefore identical to those used in Experiments 2 and 3 with the same 48 negative

and 48 non-negative words, along with 96 length-matched, graphemically legitimate non-

words again being employed in the current study. While trials containing non-words were

not informative in assessing biased attentional engagement with, or disengagement from

semantic content, they were a necessary task feature in order to maintain the expectation

that a lexical decision response could be a word or non-word with equal frequency. An

additional stimulus set consisting of 20 non-negative words and 20 graphemically

legitimate non-words was also created for use in practice trials.

141

Experimental Hardware

Experimental hardware was identical to that used in Experiment 4, comprising an

Acorn Archimedes 5000 computer, with high resolution monitor and attached

microphone and voice key for detection of colour-naming responses.

Experimental Task

The structure of the current task was similar to that used in Experiment 4 with the

principal difference being that the lexical decision responses replaced the grammatical

classification response. The task again consisted of two distinct trial types. On Semantic

Disengagement Trials the instruction string “WORD/COLOUR” was presented in upper

case letters, 10mm in height, in the centre of the screen signaling to participants that they

were first required to make a lexical decision followed by a colour-naming decision. This

instruction string remained on the screen until participants pressed the spacebar to begin

the trial. A word or non-word in white text was then presented in the same location and

participants were required to indicate its lexical status by pressing the corresponding

“word” or “non-word” mouse key. Response latency and accuracy to make this decision

was recorded. Immediately following the registration of this response the letter string

changed from white to one of four colours (red, blue green or yellow). Participant‟s

latency to name this colour was detected by a voice activated microphone and was

recorded as the interval between the onset of the colour and the detection of the colour-

naming response. This response terminated the trial and the instruction for the next trial

appeared 1000ms later. Figure 6.1a provides a summary of experimental trials assessing

biased attentional disengagement from negative and non-negative words.

142

6.1 a) Semantic Disengagement Trials

Instruction Lexical Decision Colour Name

6.1 b) Semantic Engagement Trials

Instruction Colour Name Lexical Decision

Figure 5.1. Semantic Disengagement Trials and Semantic Engagement Trials

with negative and non-negative stimulus words. Colour type shown randomly.

On Semantic Engagement Trials, the initial instruction consisted of the text

“COLOUR/WORD” which informed participants that they would be required to make a

colour-naming decision before a lexical decision. After pressing the spacebar, this

instruction display was terminated and replaced by the stimulus which was presented

devoid of content permitting lexical classification, but containing colour. Immediately

following participants recording a verbal colour-naming response, colour information

Colour Name/

Lexical Decision

Negative Word

COLOUR/WORD

XXXXXXXX

RIDICULE

COLOUR/WORD

XXXXXXXXXX

WATERPROOF

Colour Name/

Lexical Decision

Non-Negative Word

Lexical Decision/

Colour name trial

Negative Word

Lexical Decision/

Colour name trial

Non-Negative Word

WORD/COLOUR

FEAR

FEAR

WORD/COLOUR

SOFTENER

SOFTENER

143

remained, however, the letter content was added such that it now spelled a negative word,

a non-negative word, or a graphemically legitimate non-word. Participants were then

required to determine the lexical status of this string by pressing the corresponding

“word” or “non-word” mouse key. Response latency and accuracy to make this decision

was recorded on these trials. Figure 6.1b provides a summary of experimental trials

assessing biased attentional engagement with negative and non-negative words.

The task consisted of 384 trials in total. Each of the 48 negative, 48 non-negative

and 96 non-words was presented once before any were repeated and the order of the type

of trial presented (Semantic Disengagement Trials or Semantic Engagement Trials) was

randomised within each presentation sequence of 192 trials. Each stimulus was presented

twice, once in Semantic Disengagement Trials and once Semantic Engagement Trials.

Those stimuli which appeared in the Semantic Disengagement Trials in the first

presentation sequence appeared in the Semantic Engagement Trials in the second

sequence and vice versa. The allocation of each stimulus to each trial type across the two

presentation repetitions was counterbalanced such that after every two participants had

been tested, each stimulus had appeared in each trial type once within each of the first

and second repetition sequences. Text colour presented on each trial was random within

the constraint that each of the four colours appeared an equal number of times across all

trials. During the task participants were given the opportunity of a brief self-paced rest

period after the completion of 192 trials.

Procedure

Participants were tested individually in a sound attenuated cubicle. Upon arrival

they first completed the Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et

al., 1983) before beginning the experimental task. Prior to commencing the task

144

participants were informed that each trial would require two different decisions, each

requiring a different response, and the order in which they would perform these would be

provided at the beginning of each trial. They were instructed that one decision involved

colour-naming, and they should respond verbally, while the other decision involving

determining lexical status of a letter string, and they should respond by pressing one of

two alternately labeled “word” and “non-word” buttons on the computer mouse.

Participants were directed to be as fast as possible without compromising accuracy. Forty

practice trials were then completed before participants began the experimental task.

These trials contained an equal number of Semantic Engagement Trials and Semantic

Disengagement Trials using both non-negative words and graphemically legitimate non-

words not used in the experimental task.

Results

Participant STAI-T scores taken at the time of testing confirmed that the high and

low trait anxious groups continued to differ on measures of trait anxiety when completing

the experiment, t(38) = 7.26, p < .01, with the high trait anxious group displaying a mean

score of 45.80 (SD = 8.60) and the low trait anxious group with a mean of 30.80 (3.38).

A summary of participant characteristics taken at the time of testing are provided in Table

6.1. The high and low trait anxious groups were also observed to differ according to

STAI-S score t(38) = 6.14, p < .01. While unsurprising, this difference also allows for the

possibility that any effects which discriminate high and low trait anxious groups could

also potentially relate to state anxiety. Subsequent correlational analyses are therefore

employed to determine whether observed effects were associated to a greater extent with

measures of either state or trait anxiety.

145

Table 6.1

Characteristics of participants in Experiment 5. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F

High Trait Anxious 45.80 (8.60) 40.10 (8.07) 17.70 (1.21) 5:15

Low Trait Anxious 30.80 (3.38) 26.90 (5.32) 18.40 (1.76) 8:12

All Participants 38.30 (9.96) 33.50 (9.47) 18.05 (1.53) 13:27

As high rates of inaccuracy for lexical decision responses could signal that a

participant was not semantically processing letter strings, it was desirable to exclude

participants with high rates of error. Therefore, participant accuracy in performing the

lexical decision component of the task was first examined. Overall accuracy for this

measure was high with participants averaging 96.41% (SD = 3.39). In keeping with the

exclusion criteria applied in previous experiments, it was deemed inappropriate to include

participants who failed to achieve 80% accuracy on this task. No participants in the

current study recorded over 20% incorrect responses however, and therefore none were

excluded from the final analysis. The consistent high accuracy in the current experiment

contrasts sharply with the low rates of accuracy and high number of exclusions for the

emotional Stroop task used in Experiment 4. This contrast would tend to vindicate the use

of lexical decision as a means of ensuring participants process word content over the use

of grammatical judgment. No significant difference between high and low trait anxious

groups were observed in the rates of incorrect lexical decision responses, F(1, 38) = 0.00,

ns.

146

Assessment of Biased Attentional Disengagement from Semantic Content

Semantic Disengagement Trials consisted of those where participants were first

required to determine the lexical status of negative or non-negative words before

switching to then colour-name the text of the stimuli. Latencies to colour-name the text

was therefore taken as the dependent measure on these trials whereby longer latencies

would suggest greater difficulty disengaging attention from the semantic content of the

word. As semantic processing of the negative and non-negative words was essential to

the measurement of the relative ease with which participants could subsequently

disengage attention from this stimulus dimension, only trials where participants correctly

identified the word on the first response were included in the analysis. To minimise the

influence of outlying data, median colour-naming response latencies for each condition

were used in analyses. The average of these median colour-naming latencies for negative

and non-negative words across high and low trait anxious groups are provided in Table

6.2.

Table 6.2

Latencies in milliseconds for second trial responses (colour-naming) on Semantic

Disengagement Trials, across negative and non-negative word stimuli for high and low

trait anxiety groups. Standard deviations given in parenthesis.

Word Valence High Trait Group Low Trait Group

Negative Word Trials 546.50 (116.87) 501.50 (135.37)

Non-Negative Word Trials 547.75 (117.03) 497.75 (141.45)

147

Data were subjected to a 2 x 2 mixed design ANOVA with word valence

(negative or non-negative) as the within subject factor and trait anxiety group (high or

low) as the between subject factor. According to the Biased Attentional Disengagement

account of anxiety-linked attentional bias, on Semantic Disengagement Trials, high trait

anxious individuals should exhibit disproportionately slow colour-naming responses after

semantically processing negative words on the preceding lexical decision response

compared to low trait anxious individuals, resulting in a two-way interaction between

word valence and trait anxiety group. No significant effects emerged from this analysis.

Of particular note was the absence of a two-way interaction between word valence and

trait anxiety, F(1, 38) = 0.33, ns, which is clearly inconsistent with the prediction that

anxiety-linked attentional bias is associated with biased attentional disengagement from

emotional content.

Although no group differences were observed in biased attentional disengagement

from emotional content it remains possible that associations may exist between measures

of this and state and trait anxiety. Correlational analyses were therefore conducted to

determine if such relationships were present. A single index of impaired attentional

disengagement from negative content was first computed. This was achieved by

subtracting colour-naming response latencies following lexical decision of non-negative

words from colour-naming response latencies following lexical decision of negative

words. This resulted in an index of impaired disengagement where higher scores

represent slowing to disengage attention from negative as compared to non-negative

words. Pearson‟s correlations between this index and STAI-T and STAI-S scores did not

prove to be significant (r(40) = -.14, ns and r(40) = -.20, ns, respectively), providing no

148

support for the association between biased attentional disengagement with either state or

trait anxiety.

Assessment of Biased Attentional Engagement with Semantic Content

Semantic Engagement Trials consisted of those on which participants made a

colour-naming decision before determining the lexical status of a negative or non-

negative word. More rapid discrimination of negative over non-negative words would

suggest enhanced attentional engagement with the content of these stimuli. Latencies to

determine the word‟s lexical status was therefore taken as the dependent measure on

these trials. As with trials assessing biased attentional disengagement from word content,

semantic processing of word stimuli was essential in measuring the speed with which

participants processed the content of these words. Therefore, only trials where

participants recorded a correct response to discriminating the lexical decision target were

included in the analysis. Median lexical decision response latencies were used to

minimise the influence of outlying data. The average of these lexical decision response

latencies for negative and non-negative stimuli across high and low trait anxious groups

are provided in Table 6.3.

Table 6.3

Latencies in milliseconds for second trial responses (lexical decision) on Semantic

Engagement Trials, across negative and non-negative word stimuli for high and low trait

anxiety groups. Standard deviations given in parenthesis.

Word Valence High Trait Group Low Trait Group

Negative Word Trials 1313.88 (186.76) 1302.25 (206.23)

Non-Negative Word Trials 1341.62 (187.63) 1291.00 (205.85)

149

Data from the Semantic Engagement Trials were subjected to a 2 x 2 repeated

measures ANOVA with one between group factor of trait anxiety (high or low) and one

within group factor of word valence (negative or non-negative). The Biased Attentional

Engagement account of attentional bias in anxiety predicts that on these trials, high trait

anxious individuals will be faster to determine the lexical status of negative words

relative to non-negative words after having processed the text colour of these stimuli,

resulting in a two-way interaction between word valence and trait anxiety group. This

analysis revealed a significant two way interaction between trait anxiety and word

valence, F(1, 38) = 5.64, p < .05. As illustrated in Figure 6.2 the nature of this interaction

is precisely the pattern predicted by the Biased Attentional Engagement account. That is,

following colour-naming, high trait anxious individuals were disproportionately fast, in

relation to low trait anxious participants, to determine the lexical status of negative as

compared to non-negative words. Simple main effects analysis revealed that high trait

anxious individuals were faster to discriminate negative as compared to non-negative

words, F(1, 19) = 5.41, p < .05). Low trait anxious individuals in contrast showed a non-

significant effect in the opposite direction, F(1, 19) = .99, ns.

150

1280

1290

1300

1310

1320

1330

1340

1350

Negative Non-Negative

Word Valence

Resp

on

se L

ate

ncy (

ms)

High trait anxious

Low trait anxious

While an anxiety-linked group difference was observed in biased attentional

engagement with semantic content, it is possible that this effect may not be linear in

nature. It was therefore deemed suitable to examine correlational analyses to determine if

any linear component of this effect can be detected and if so, whether this is more a

function of trait or state anxiety. To assess the degree of association between biased

attentional engagement with semantic content and state and trait anxiety, an index of

enhanced attentional engagement with negative stimuli was first computed. This was

achieved by subtracting lexical decision latencies for negative words from lexical

decision latencies for non-negative words on Semantic Engagement Trials. Higher scores

on this index represent speeding to switch attention to process the semantic content of

negative words having previously performed a colour-naming decision. This index was

Figure 6.2. Two-way interaction showing lexical decision response latencies across trait

anxiety groups and word valence for Semantic Engagement Trials.

151

observed to be significantly correlated with measures of trait anxiety, r(40) = .27, p < .05,

but not with measures of state anxiety, r(40) = .19, ns. This correlation with STAI-T

scores supports the contention that relative speeding to switch attention to engage with

the emotional dimension of a negative, as compared to non-negative stimulus, is more

associated with vulnerability to anxious mood rather than current anxious state and is

consistent with the Biased Attentional Engagement account of attentional bias.

While the above results provide support for the hypothesis that anxiety is

characterised by biased attentional engagement with the content of negative material, an

alternative possibility could also provide an equally plausible account of these findings.

Rather than the observed interaction being specifically attributable to a bias in orienting

attention from a non-emotional to an emotional dimension of the same stimulus, it is

possible that high trait anxious individuals are simply faster to discriminate the lexical

status of negative over non-negative material. As lexical decision responses were

recorded as the first decision on Semantic Disengagement Trials, the current task permits

the examination of this alternative account. If high trait anxious individuals are simply

faster to process the content of negative over non-negative words then it is expected that

high trait anxious individuals will also demonstrate disproportionately fast lexical

decision response times for negative words when required to discriminate the lexical

status of letter strings as the first trial decision. It is worthy to note that overall lexical

decision response latencies which occurred as the first decision on a trial (M = 770.81,

SD = 150.12) were substantially faster than those lexical decision response latencies

which occurred as the second decision on a trial (M = 1312.19 SD = 193.25), t(38) =

33.37, p < .01. This slowing on the second decision is consistent with what would be

expected if participants were required to disengage attention from the initially attended

152

information before discriminating the lexical status of the subsequently attended letter

string6. This pattern alone does not however address the possibility that the interaction

observed for Semantic Engagement Trials is specific to trials where attention is required

to switch from one stimulus dimension to another. To address this, lexical decision

responses on trials where this decision occurred as the first response (Semantic

Disengagement Trials) were subjected to a 2 x 2 ANOVA with one within group factor of

word valence (negative and non-negative) and one between group factor of trait anxiety

(high or low). As with the previous analyses, median lexical decision response latencies

were used and only correct responses were included to ensure that participants had indeed

processed the semantic content of the stimuli. The results of this analysis provided no

support for the possibility that high trait anxious individuals are simply faster to process

the content of negative material with the analysis failing to reveal a significant interaction

between trait anxiety group and word valence, F(1, 38) = .90, ns.

Discussion

The key aim of the current study was to refine the version of the decoupled

emotional Stroop task used in Experiment 4 to provide an improved measure of biased

attentional engagement with and disengagement from semantic content of negative and

non-negative stimuli. The high overall accuracy rate for lexical decision responses allows

confidence that participants who performed the task were semantically processing the

negative and non-negative material when required to do so. The most striking finding of

the current study was the clear support for Biased Attentional Engagement account of

6 Similarly it should be noted that colour naming responses were also slower when they occurred as the

second decision (M = 585.06, SD = 109.47) as compared to the first decision (M = 523.38, SD = 128.04),

t(38) = 4.24, p < .01, as would be expected if the process of colour-naming in influenced by disengaging

from the content of the information processed in the first decision.

153

anxiety-linked attentional bias and the absence of support for the Biased Attentional

Disengagement hypothesis.

It was assumed that trials where participants colour-named the text of negative

and non-negative words after having semantically processed their content would provide

an indication of relative difficulty disengaging attention from the semantic content of

differentially valenced stimuli in order to process the non-emotional dimension of the

stimulus. The results revealed no difference between high and low trait anxious

participants in the relative speed to switch attention away from the content of negative as

compared to non-negative words. Nor was there any evidence found of an association

between relative speeding to orient attention away from the semantic content of negative

and non-negative words with measures of either state or trait anxiety. These null effects

stand in stark contrast to the pattern of findings observed for the trials assessing biased

attentional engagement with emotional content. The biased engagement account of

anxiety-linked attentional bias predicted that high trait anxious individuals would be

disproportionately fast to switch attention to discriminate the identity of negative over

non-negative words after initially colour-naming this stimulus. The results obtained on

Semantic Engagement Trials were entirely consistent with these predictions. It was

observed that high trait anxious individuals were significantly faster to switch attention to

successfully access the semantic content of negative as compared to non-negative words,

having initially processing colour information. This difference was not observed for the

low trait anxious group. Correlational analyses also revealed that an index of enhanced

engagement with negative as compared to non-negative semantic content was a

significant predictor of current trait anxiety (STAI-T) but was not significantly associated

with current state anxiety (STAI-S).

154

The current results also addressed an alternative possibility which could account

for the observed findings. In order to examine the possibility that this effect may be due

to a more general pattern of speeding to process the semantic content of negative words,

an analysis was conducted on lexical decision response latencies for trials where the

lexical decision occurred as the first, rather than the second response, thus requiring no

attentional shift. The results demonstrated that when participants were required to

semantically process word content as the first response, no anxiety-linked differences

were observed. This provides further support for the specific prediction that it is only

when participants are required to make an attentional shift from one stimulus dimension

to another, that biased attentional engagement will be evident. It should be noted,

however, that while this pattern of effects is consistent with predictions of the differential

engagement account of attentional bias, the overall three-way interaction involving

lexical decision time (first or second decision), word valence (negative or non-negative)

and trait anxiety group (high or low) did not prove to be significant, F(1, 38) = 0.13, ns.

The present experimental findings also provide converging support for the pattern

of findings observed across Experiments 2 and 3. In Experiment 3 it was demonstrated

that on trials where participants were first required to process a probe before making a

lexical decision on a negative or non-negative word appearing subsequently in the same

spatial position, high trait anxious individuals were faster to identify negative as

compared to non-negative words. Additionally, this pattern of speeding to determine the

lexical status of negative compared to non-negative words was absent in Experiment 2

when participant‟s first response on each trial was a lexical decision. This pattern of

effects is consistent with the observations in the current study which demonstrated that

high trait anxious individuals are only faster to semantically process the content of

155

negative material when orienting attention from a non-emotional dimension of a stimulus

to an emotional dimension of a stimulus occupying that same location. Furthermore, as

with the current study, Experiment 2 also failed to find evidence for biased attentional

disengagement when orienting attention away from an emotional dimension of a stimulus

to a non-emotional dimension of a stimulus presented in the same locus. This was

demonstrated in Experiment 2 by the absence of anxiety-linked differences in probe

detection latencies on trials where participants first processed the semantic content of

negative and non-negative words, before then orienting attention to process the non-

emotional information that appeared in this same spatial locus. The current results are

therefore consistent with the effects observed across Experiments 2 and 3, and together

provide support for the hypothesis that attentional bias in anxiety is characterised by

enhanced attentional engagement with the emotional dimension of negative stimuli, while

providing no support for the biased attentional disengagement hypothesis.

The results obtained using the present emotional Stroop task variant shed light

upon the attentional mechanism likely to underpin the anxiety-linked bias evident in the

traditional emotional Stroop task. The separating of emotional (semantic) and non-

emotional (text colour) dimensions of the stimuli allowed the current task to reveal

anxiety-linked differences when participants shifted between these two dimensions of the

stimulus. The most direct implication of this pattern of effects for the emotional Stroop is

that the consistently observed slowing of high trait anxious individuals to colour-name

negative as compared to non-negative words is likely to reflect their enhanced attentional

engagement with the semantic meaning of negative material, which interferes with the

task of colour-naming the stimulus text. This stands in contrast to the alternative

explanation of the traditional emotional Stroop effect, that high trait anxious individual‟s

156

slower colour-naming latencies on negative words reflect their greater difficulty

switching attention to the non-emotional dimension of the word‟s text colour, whenever

the content has initially been attended to.

The results of the present experiment clearly demonstrated that, while high trait

anxious individuals show disproportionate speeding to determine the lexical status of

negative words when orienting attention from an alternative stimulus dimension, when a

lexical decision is made as a first response, no anxiety-linked differences in response

latency are observed. While this result is consistent with the Biased Attentional

Engagement account of attentional bias, it could also be considered somewhat

counterintuitive. That is, it would tend to pose the question as to why high trait anxious

individuals do not always show more rapid processing of negative stimuli, regardless of

whether they are orienting attention from an alternative stimulus dimension. A potential

answer to this can be found in research examining how the allocation of processing

priorities among competing alternatives affects attentional bias in anxiety. In a modified

lexical decision task, MacLeod and Mathews (1991) presented letter strings to individuals

who differed in vulnerability to anxious mood. Their findings indicated that when a

single letter string was presented, no anxiety-linked differences in processing negative

and non-negative material emerged. However, the study demonstrated that high trait

anxious individuals did evidence selective processing of negative material under

conditions where competing negative and non-negative information was introduced at the

same time. These results were taken to suggest that the facilitated processing of negative

words in anxiety reflects the allocation of processing priorities when competing

alternatives are present, rather than a more general tendency to selectively process the

semantic meaning of negative information. These results could be considered consistent

157

with the results of the present study. As with MacLeod and Mathews (1991), the present

study found no evidence of selective processing of negative material for high trait

anxious individuals when negative material was presented initially in the absence of other

stimulus information (i.e. without competing stimulus dimensions). The implications of

this previous study for the current experiment would suggest that, it is the introduction of

competing stimulus information (i.e. both semantic content and colour information

present simultaneously) at the point where participants have made the first task decision

that results in the selective allocation of processing priorities between these competing

alternatives. The present study acts to further clarify these past findings to highlight that

it is not simply the introduction of competing alternatives which is sufficient to elicit

selective processing of negative material. Rather, by controlling the order in which this

information becomes available in the current study, it was possible to demonstrate that an

anxiety-linked attentional bias favoring the processing of negative content is only evident

when moving attention from non-emotional information to emotional information and not

when moving attention from emotional information to non-emotional information.

Therefore while it appears that the introduction of competing information is necessary to

elicit anxiety-linked selective processing of negative content, the current research

suggests that this will only occur when orienting attention toward emotional content

(engaging attention) and not when orienting attentional away from such material

(disengaging attention).

The fact that the results of the present study failed to demonstrate evidence for an

anxiety-linked bias in attentional disengagement from the semantic content of negative

and non-negative words is inconsistent with the predictions of this hypothesis. Indeed, the

results of all studies conducted in the current research program have not produced

158

evidence of a bias in attentional disengagement. The relative absence of evidence for

anxiety-linked impaired disengagement, along with the pattern of results observed in the

present study suggesting the operation of biased attentional engagement, could be

considered to implicate the role of enhanced attentional engagement with the content of

negative material over impaired attentional disengagement from this negative

information.

One aspect of the task used in the present study however, would suggest the

possibility that the means of assessing attentional disengagement may not have been

adequately sensitive to measure individual differences in this attentional process. The

recording of lexical decision accuracy and response latency allowed confidence that on

Semantic Engagement Trials, participants did indeed engage with the semantic content of

the stimuli after they recorded their initial colour-naming response. Thus the speed to

orient attention from processing colour information to instead semantically process the

word was reliably indexed by the final lexical decision latency, providing a measure of

participant‟s ability to engage with the content of such words when required to do so.

With the trials assessing biased attentional disengagement from negative and non-

negative semantic content, it was similarly believed that having participants colour-name

text after processing the semantic meaning of a stimulus would provide a measure of the

relative difficulty disengaging attention from the word‟s semantic meaning to process its

colour. It is entirely plausible, however, that a participant may be able to colour-name a

stimulus while still processing its meaning. That is, naming the text colour of a word does

not necessarily occur at the exclusion of maintaining the representation of its semantic

meaning in current cognitive operations. This therefore highlights a possible

incongruence between trials assessing biased attentional engagement; where correct

159

performance of the lexical decision provides confidence that participants have indeed

engaged with the content of this stimuli, and trials assessing biased attentional

disengagement; where correct performance of the colour-naming decision does not

necessarily confirm attentional disengagement from the content of the previously

processed word.

The possibility that participants continue to processing stimulus content while

performing an alternate response is an issue relevant to all prior studies examining biased

attentional disengagement from differentially valenced stimuli including those in the

current research program. The results of both Experiments 1 and 2 revealed no evidence

for anxiety-linked differences in the selective disengagement of attention from negative

and non-negative words. The possibility remains however, that participants were able to

orient attention to a spatially removed locus while still processing the content of the

initially attended stimulus. If such ongoing semantic activation of negative material was

occurring for high trait anxious individuals, this would suggest that these individuals

have greater difficulty disengaging from the emotional content of negative stimuli.

The issue of whether biased attentional disengagement is characterised by

ongoing activation of negative stimuli in current cognitive operations also relates more

generally to research on working memory. Recent research has suggested that the ability

to maintain information in current cognitive operations is associated with individual

differences in self-regulatory behaviour such as consumption of tempting food

(Hofmann, Gschwendner, Friese, Wiers, & Schmitt, 2008) and drug use (Grenard, et al.,

2008; Thush et al., 2008). It is entirely possible therefore, that individual differences in

the way negative and non-negative information is maintained in current cognitive

160

operations could hold implications for the way in which people differ in their emotional

reactions to such stimuli.

The structure of the current and previous tasks has not provided a means of

assessing whether anxiety is characterised by the ongoing semantic activation of

negatively valenced stimuli. To address the possibility that such a manifestation of biased

attentional disengagement may operate in those more prone to anxious mood, two related

task modifications could be pursued. The first of these would involve changing the nature

of the second decision on a trial such that it becomes less plausible that the continued

processing of the initial stimulus could be sustained while making the second decision.

Selective difficulty disengaging from negatively valenced stimuli would therefore be

demonstrated by a slower response to perform the second trial decision which would

recruit the same decision making processes used in the first. Another approach, not

inconsistent with that mentioned above, would be to take a measure of the degree to

which a word‟s semantic representation remains active after having performed the second

trial decision. By examining the decline in stimulus activation when required to perform a

subsequent decision, it would become possible to infer the degree to which participants

have disengaged from its content. In the final experiment of this thesis, both of the

methodological approaches outlined above will be adopted to yield a task variant which;

a) reduces the probability of ongoing semantic activation of the stimulus representation

on the second trial decision and, b) reveals whether the decline in activation of negative

and non-negative stimulus representations occurs differentially for high and low trait

anxious individuals.

In summarising the key finding of the present study, a refined task variant of the

emotional Stroop task used in Experiment 4 was employed to assess whether elevated

161

trait anxiety is characterised by biased attentional engagement with the semantic content

of negative words or biased attentional disengagement from the semantic content of

negative words. The results support the former position with high trait anxious

individuals showing speeded engagement with the semantic content of negative words

after processing the non-emotional information of the stimulus. The results provided no

support for presence of an anxiety-linked bias in attentional disengagement from the

semantic content of differentially valenced stimuli. The possibility that measures of

biased attentional disengagement used in the current and previous studies may not be

sensitive to the ongoing semantic activation of a stimulus representation was discussed. It

was therefore the aim of the final study to examine the possibility that high and low trait

anxious individuals differ in the degree to which the semantic representation of negative

and non-negative stimuli remain active in current cognitive processes.

162

CHAPTER 7

EXPERIMENT 6

None of the experiments conducted as part of the current research program have

found support for the hypothesis that individuals vulnerable to anxious mood have

selective difficulty disengaging attention from the emotional content of negatively

valenced material. However, as highlighted in the discussion of Experiment 5, none of

the tasks employed to date have been sensitive to the possibility that anxious individuals

may continue to process the content of more negative material while making a

subsequent, unrelated decision about another stimulus or different stimulus dimension.

The key aim of this final experiment was to specifically examine this possibility by

including a task modification which will increase the likelihood that participants will

disengage from the semantic content of the initially attended stimulus and also include a

measure of representational activation of stimulus content to assess whether this has

occurred.

In assessing biased attentional disengagement the tasks employed in the current

research program (with the exception of Experiment 1) have included the requirement

that participants initially process the semantic content of negative or non-negative

information before assessing the relative ease with which they can then switch to perform

a second, unrelated decision, such as identifying the structure of a probe or colour-

naming stimulus text. It has been assumed that bias reflecting impaired attentional

disengagement from negative information would be revealed by slowing to perform this

second decision after having first processed the semantic content of a negative rather than

a non-negative word, with such longer latencies on this second decision reflecting

difficulty disengaging from the content of the initially processed word. However, because

163

the second task decisions have consistently involved processing, and responding to,

structural rather than semantic information, it is possible ongoing semantic activation of

the original stimulus content may continue with minimal disruption. That is, making a

decision regarding stimulus form or colour need not preclude the ongoing processing of

the previously encoded semantic meaning. If this is the case, then the latency to make this

second decision would not represent an index of the speed with which disengagement

from processing this meaning occurs.

The possibility that minimal disruption to the ongoing processing of

verbal/semantic information may be produced by the processing of visual-spatial

information is consistent with Baddeley‟s (1992; 2001) model of working memory. This

model proposes that there are separate cognitive subsystems devoted to maintaining

visual-spatial information and verbal information within current cognitive operations.

Research has provided support for the existence of these separate subsystems, and

yielded evidence that when a secondary or distracter task differs in the processing

demands from a primary task (i.e. visual-spatial primary task with verbal secondary task

or vice versa) no major reduction in task performance is observed (Robbins et al., 1996).

In contrast, it has also been observed that performance on visual-spatial tasks is disrupted

when new visual-spatial information must be processed during the task completion

(Logie, 1986; Quinn & McConnell, 1996). Similarly, and most importantly for current

considerations, performance on tasks involving the processing of verbal information is

adversely affected when new verbal information is included in the task (Salame &

Baddeley, 1982).

The implication of Baddley‟s (1992; 2001) model of working memory is that the

continued processing of negative or non-negative verbal information could be maintained

164

while subsequently processing the structure of a visual probe or the colour of text. In

order to maximise the likelihood of disengagement from processing verbal information

presented in the first decision, the second task decision should require the processing of

different verbal information. A simple modification to previous tasks which could be

implemented to assess biased attentional disengagement would involve having

participants first make a lexical decision on a negative or non-negative word, as before,

but then go on to make another new semantic decision on a second stimulus string. By

requiring participants to again process the second stimulus for semantic meaning the

same cognitive subsystem would be recruited and so disengagement from the previous

semantic processing would be required. A measure of biased disengagement from the

processing of differential emotional content would therefore be obtained when

participants first determine the lexical status of a negative or non-negative word and are

subsequently required to determine the lexical status of a non-word. Longer latencies to

determine the lexical status of this subsequently presented non-word would indicate

greater difficulty disengaging from the content of the initially processed stimulus word.

While this approach seems likely to discourage continued processing of initial

word content in ways that make the second decision latency a better index of

disengagement from such processing, it remains possible that participants may sometimes

continue to process the initially presented stimulus information to some degree across the

entire trial. Therefore, an additional aim of the present experiment was to include a

measure of ongoing activation of this initial stimulus representation to assess the degree

to which participants continued to process the initial stimulus word after performing the

second task decision. If the second task decision is successful in limiting ongoing

processing of initial negative and non-negative word content then we would expect little

165

evidence for anxiety-linked differences in the continued processing of negative over non-

negative words. If however, anxiety-linked attentional bias results in impaired

disengagement from negative stimuli in spite of this second trial decision, then any

ongoing processing of initially presented negative words is likely to be greater for high as

compared to low trait anxious individuals. By including a measure of ongoing semantic

activation the current task would therefore have the capacity to reveal if high trait anxious

individuals do experience greater ongoing activation of initially processed negative words

as compared to low trait anxious individuals.

The well established „repetition priming effect‟ would seem to offer an

appropriate measure of ongoing activation of initially processed stimulus words. It has

been consistently demonstrated that the presentation of a word facilitates its later

identification in word-naming tasks (Fowler, Napps, & Feldman, 1985; Scarborough,

Cortese, & Scarborough, 1977). This priming effect is thought to result from the

continued activation of this word‟s representation in long-term memory. Following its

initial activation, Besner and Swan (1982) theorise that the cognitive representation of a

word returns to baseline activation slowly, meaning that it remains partially active for

some time following recognition. They suggest that when a word is presented subsequent

to its first exposure, the duration required for its representation to meet the critical level

of activation for it to be recognised, and hence available as a word-naming response, will

be less due to its ongoing partial activation from having been previously identified.

Latencies to name previously presented words, or „repetition priming‟, therefore provides

a measure of the degree to which a word‟s semantic representation remains active in

current cognitive operations (Feldman & Moskovljevic, 1987).

166

Correctly discriminating the lexical status of an initially presented word requires

its representation to become active. Presumably the continued processing of this word

will sustain this activation whereas disengagement from such processing will permit this

activation to subside. If anxiety-linked attentional bias is characterised by impaired

disengagement from the processing of negative words, then it follows that individuals

more vulnerable to anxious mood will demonstrate slower decline in the activation of

initially processed negative as compared to non-negative words. By including at the end

of each trial a priming measure capable of revealing the level of sustained activation of

the initial word representation, it should be possible to reveal anxiety-linked differences

in disengagement from processing these initially presented negative and non-negative

words. Hence, each trial on the current task included such a repetition priming

component. This involved participants naming aloud a final word, presented immediately

after the second lexical decision. This final word was „primed‟ if it had appeared as either

the first or second lexical decision target earlier in the trial and „unprimed‟ if it had not.

The relative speeding to name primed as compared to unprimed words provided a

measure of the ongoing semantic activation of these previously presented negative and

non-negative words. Thus, primed words should be named faster than unprimed words.

The Biased Attentional Disengagement account of attentional bias suggests that high trait

anxious individuals will demonstrate less disengagement from processing negative words

than non-negative words when performing the second task decision. If so, then after

activating the representation of a stimulus word on the first lexical decision, high trait

anxious individuals should evidence less decline in subsequent activation of the word‟s

representation following the second trial decision, when these words are negative rather

167

than non-negative. This will be evidenced by disproportionately large priming effects for

initially processed negative words for high as compared to low trait anxious individuals.

The current study aimed to examine the possibility that previous tasks assessing

biased attentional disengagement have not found evidence for such a bias because it is

characterised by high trait anxious individuals continuing to process negative material

while performing subsequent, unrelated task decisions. Two key task features were

included to address this possibility. The first involved the inclusion of a second trial

decision that recruited the same decision-making processes as the first. This was intended

to increase the likelihood that participants would have to disengage from processing the

content of the initially attended stimulus to performing the second task decision. Biased

attentional disengagement from the content of the initially processed word would be

revealed in longer latencies to identify the lexical status of the non-word target on the

second trial decision. The Biased Attentional Disengagement account of attentional bias

predicts that high trait anxious individuals should be slower to determine the lexical

status of non-words after having processed negative as compared to non-negative words

on the first task decision. The second inclusion in the current task was designed to

measure differences in ongoing activation of initially processed words using a repetition

priming task. If the inclusion of a lexical decision on the second trial decision is

successful in ensuring that participants equivalently disengage from the content of the

initial negative or non-negative word then we would expect no anxiety-linked differences

in ongoing activation of negative and non-negative words. If the second lexical decision

is not able to prevent ongoing processing of word content then priming measures will

reveal whether anxiety linked differences are present in the continued processing of

negative and non-negative words. If, as predicted by the Biased Attentional

168

Disengagement account of attentional bias, high trait anxious individuals do maintain the

representation of negative words in current cognitive operations longer than low trait

anxious individuals, then these individuals will show greater priming for negative as

compared to non-negative words at the end of the trial, after having identified these on

the lexical decision at the beginning of the trial.

Method

Overview

The purpose of the current experiment was to assess anxiety-linked differences in

biased attentional disengagement from the content of negative and non-negative words

and, to measure differences in the degree of ongoing activation of such stimulus words

for high and low trait anxious individuals. These objectives were achieved by including

measures of attentional disengagement from word content and ongoing semantic

activation of a stimulus word within a single trial. On each trial a single letter string

consisting of a negative word, non-negative word or a non-word was initially presented,

and participants were required to make a lexical decision on this string. Following this

decision a second letter string was presented in the same spatial locus, again consisting of

either a negative word, non-negative word or a non-word, and participants performed a

second lexical decision. Critical trials measuring biased attentional disengagement from

word content were those where participants first performed a lexical decision on a

negative or non-negative word before then making a lexical decision of a non-word.

Latencies to correctly make this second decision, classifying the second string as a non-

word, were taken as an indication of relative difficulty disengaging from the processing

of the initially attended negative or non-negative word.

169

Immediately following the second lexical decision a word-naming response was

required to a final word appearing in the locus vacated by the second lexical decision

string. Participants were instructed to verbally name the word as quickly as possible. On

half the trials a new word, not previously presented on that trial as a lexical decision

target, was shown for this word-naming (unprimed words) while on the remaining trials

the word was identical to a negative or non-negative lexical decision target word that had

been presented on that same trial (primed words). It was expected that latencies would be

shorter to name primed versus unprimed words, and the magnitude of this priming effect

provided a measure of the ongoing processing of negative and non-negative words

previously presented as the as the first lexical decision target.

Participants

Selection of high and low trait anxious participants was again guided by screening

of undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory

(STAI-T; Spielberger et al., 1983) to ensure participants differed in trait anxiety as

required. Five hundred and sixty seven undergraduates were screened on this measure

and those who obtained scores on the STAI-T which fell in the upper third (at or above

46) or the lower third (at or below 37) of the distribution were considered eligible to

participate. Of those who participated in the study, 24 fell in the upper third of the

distribution (high trait anxious group) and 24 fell in the lower third of the distribution

(low trait anxious group). The high trait anxious group consisted of 6 males and 18

females while the low trait anxious group comprised 7 males and 17 females. Chi-square

analyses revealed that these groups did not differ significantly in terms of gender ratio,

²(1,46) = 0.11, ns. Similarly, high and low trait anxious groups did not differ

significantly in terms of age, t(46) = 0.13, ns.

170

Materials

Emotional Assessment Measure

As in previous studies, the Spielberger State Trait Anxiety Inventory (STAI;

Spielberger et al., 1983) was again employed as the emotional assessment measure.

Word Stimuli

The same 48 negative, 48 non-negative and 96 length matched non-words as used

in Experiment 5 were used in the current experiment. These stimuli were divided into two

subsets for use in the task, subset A and subset B, each consisting of 24 negative and 24

non-negative words along with their length-matched non-words. An additional stimulus

set consisting of 48 non-negative words and 48 graphemically legitimate non-words was

also created for use in practice trials.

Experimental Hardware

An Acorn Archimedes 5000 computer was used to deliver the experimental task

and record participant responses. A microphone and voice key was also attached for

detecting word-naming responses.

Experimental Task

Each trial began with a row of white crosses presented for 500ms in the centre of

the screen. A single letter string then replaced this, presented in block letters 10mm in

height. This was either a negative word, a non-negative word or a non-word. Participants

were required to determine the lexical status of this string by pressing one of two keys,

with response latency and accuracy being recorded. Once this response was detected a

second letter string immediately replaced the first, appearing in the same location, with

the same size font and also in white text. This letter string was either another negative or

non-negative word or a non-word and participants were again required to determine its

171

lexical status in the same manner as the first string. Immediately following this response,

a word in yellow text was presented in the same location. Participants were required to

verbally name this word aloud. Latency to make this response was recorded via a

microphone. Detection of the participant‟s utterance signaled the end of the trial and the

next trial began 1000ms later.

Thus, from participants perspective, there was an equal probability that either of

the first two stimuli would be a word or a non-word, an equal probability that any word

would be negative or non-negative, and an equal probability that the final yellow word

would repeat any previous word presented on a given trial or not. However, the critical

trials for assessing biased attentional disengagement from emotional content were only

those where the first lexical decision target was a negative or non-negative word, the

second lexical decision target was a non-word, with the final word being either primed or

unprimed. The latency of the second decision on these trials to correctly discriminate the

non-word was taken as a measure of the relative difficulty disengaging from the content

of the initially presented word. The relative latency to name the final primed versus

unprimed word in yellow, provided a measure of ongoing activation of the initially

presented word. Shorter latencies to name primed words would signal greater ongoing

activation of that stimulus word in current cognitive operations.

The entire task consisted of 192 trials, of which 48 were critical trials where

participants first determined the lexical status of a negative or non-negative word before

then identifying a non-word lexical target. The remaining filler trials were a necessity to

maintain the expectation that each lexical decision target could be either a word or non-

word with equal frequency. Therefore, of these filler trials, 48 were delivered in which

the first lexical decision target was a word and the second was a non-word, 48 in which

172

both the first and second lexical decision targets were words, and 48 in which both the

first and second lexical decision targets were non-words. Each of the critical and filler

trial types occurred 12 times during the task. For the 48 critical trials there were 4 unique

conditions given by the combination of the two, two level task factors of stimulus valence

(negative or non-negative word), and prime condition (final word primed or unprimed).

Figure 7.1 provides a summary of these critical trials.

Lexical Decision 1 Lexical Decision 2 Word Naming Response

Figure 7.1. Critical trials for Experiment 6 where negative and non-negative words are

presented as the first lexical decision target, and named words are either primed or unprimed.

Allocation of stimuli was such that, for each participant, either stimulus subset A

or subset B was allocated to those trials where one lexical decision was performed on a

Lexical Decision 1: Negative word

Lexical Decision 2: Non-Word

Word Naming Response: Primed

FEAR

ERAF

FEAR

SOFTENER

ROSFNETE

SOFTENER

Lexical Decision 1: Non-Negative word

Lexical Decision 2: Non-Word

Word Naming Response: Primed

SOFTENER

ROSFNETE

QUANTITY

Lexical Decision 1: Non-Negative word

Lexical Decision 2: Non-Word

Word Naming Response: Unprimed

Lexical Decision 1: Negative word

Lexical Decision 2: Non-Word

Word Naming Response: Unprimed

FEAR

ERAF

NOTE

173

word and one lexical decision was performed on a non-word (i.e. word – non-word or

non-word – word trials). The remaining stimulus subset was allocated to trials where both

lexical decisions were performed on a word (word – word trials), or both lexical

decisions were performed on a non-word (non-word – non-word trials). Within trials

where one lexical decision was performed on a word and the other performed on a non-

word, half of the stimulus subset was assigned to trials where the word appeared as the

first lexical decision target while the remainder were assigned to trials where the word

appeared as the second lexical decision target. The allocation of stimuli for the verbal

naming task was such that, in trials where the word was primed, the named word was

identical to the word that had appeared earlier in the trial. When the named word was

unprimed, a valenced-matched word belonging to the stimulus subset assigned to trials

where both lexical decisions were performed on a word (word – word trials) was used.

Stimulus allocations were counterbalanced such that after eight people had been tested,

each stimulus had appeared once in each of the unique conditions possible for that

stimulus type.

Procedure

As with prior studies, all participants completed the experimental task

individually in a sound attenuated room. Both state and trait versions of the Spielberger

State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) questionnaire were first

completed before participants began the computer task. Participants were informed that

the task would require them to perform three responses on each trial, a lexical decision

followed by another lexical decision followed by a verbal word-naming response. They

were instructed to indicate the lexical status of the first and second letter strings by

pressing one of two keys alternately labeled “word” or “non-word” as quickly as possible

174

without sacrificing accuracy. Participants were told that following the second lexical

decision response, a word in yellow would appear and they should verbally name this

word aloud as rapidly as possible. Participants then completed 48 practice trials using the

stimuli created for this purpose to ensure they were familiar with the task before

beginning the experiment. These practice trials were balanced in a similar manner as

experimental trials such that there was an equal probability that the first or second lexical

decision would be a word or non-word, and an equal probability that the final named

word was primed or unprimed.

Results

A summary of participant characteristics taken at the time of testing is provided in

Table 7.1. STAI-T scores taken at the time of testing revealed the high trait anxious

group demonstrated a mean score of 51.58 (SD = 6.49) on this measure while the low

trait anxious group had a mean of 32.75 (SD = 5.50). The difference between these two

groups on this measure of trait anxiety was significant as required, t(46) = 10.84, p < .01.

As with all previous studies, the two groups also differed in terms of STAI-S score, t(46)

= 3.67, p < .01. Correlational analyses will therefore be needed to determine if any

observed group differences in task performance are more strongly associated with state or

trait anxiety.

High rates of error in performing lexical decisions would preclude confidence that

a participant was performing the task according to instructions. Accuracy in performing

both the first and second lexical decision responses was therefore examined first. Lexical

decision accuracy was high, with participants averaging 93.86% correct responses (SD =

4.58). As with all prior studies, a minimum of 80% accuracy was deemed a requirement

175

for inclusion in the final analysis, and so as before, any participant recording over 20%

incorrect responses were therefore excluded from further analysis. This resulted in one

participant being excluded, from the high trait anxious group. No significant difference

between high and low trait anxious groups were observed in the rates of incorrect lexical

decision responses, F(1, 37) = 0.71, ns. Median latencies were again used as the response

time measure for lexical decisions and for word naming, to minimise the influence of

outlying data. Lexical decision and word-naming data examining biased attentional

disengagement from emotional content are reported in turn below.

Table 7.1

Characteristics of participants in Experiment 6. Standard deviations given in parentheses.

Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F

High Trait Anxious 51.58 (6.49) 41.70 (7.94) 20.91 (7.92) 6:18

Low Trait Anxious 32.75 (5.50) 33.04 (8.42) 20.67 (5.40) 7:17

All Participants 42.17 (11.22) 37.37 (9.20) 20.79 (6.71) 13:35

Analysis of Lexical Decision Latency Data

Critical trials assessing biased attentional disengagement from emotional content

were those where participants were first required to determine the lexical status of

negative and non-negative stimulus words before then determining the lexical status of a

subsequently presented non-word. Latencies to correctly classify non-words as the

second decision on these trials were taken as the dependent measure with longer latencies

suggesting greater difficulty disengaging attention from the content of the first lexical

decision target. Only trials where the first and second lexical decisions were preformed

176

correctly were included in the analysis. The average of these latencies across trials where

the first lexical decision had been a negative or non-negative word, for high and low trait

anxious individuals, is given in Table 7.2.

A 2 x 2 ANOVA was performed on this data with word valence (negative or non-

negative) as the within subject factor and trait anxiety group (high or low) as the between

subject factor. If high trait anxiety is characterised by biased attentional disengagement

from the content of the initially presented negative material, then we would predict that

high as compared to low trait anxious individuals will be disproportionately slow to

determine the lexical status of the subsequent non-word after having first processed the

content of negative as compared to non-negative words on the preceding lexical decision.

This would result in a two-way interaction between valence of the lexical decision target

word and trait anxiety group. The two-way interaction between trait anxiety group and

word valence did not approach significance, F(1, 45) = 0.96, ns, contradicting the pattern

of effects predicted by the biased disengagement account. No other significant effects

emerged from this analysis.

Table 7.2

Latencies in milliseconds for the second (non-word) lexical decision on trials where

negative and non-negative word stimuli was presented as the first lexical decision target

for high and low trait anxiety groups. Standard deviations given in parenthesis.

Word Valence High Trait Group Low Trait Group

Negative Words as First Lexical Decision 745.43 (220.34) 729.17 (224.71)

Non-Negative Words as First Lexical Decision 711.30 (160.15) 721.67 (172.14)

177

While no group differences were observed to suggest differential biased

attentional disengagement from negative information across trait anxiety groups, the

possibility remains that a measure of such bias may co-vary with state or trait anxiety. To

address this possibility correlational analyses were conducted. It was first necessary to

calculate an index of the effect that would represent biased attentional disengagement

from emotional content. This was computed by subtracting second word lexical decision

latencies for non-words on trials where the first lexical decision target had been a non-

negative word from second word lexical decision latencies for non-words on trials where

the first lexical decision target had been a negative word. The result was an index of

impaired attentional disengagement from emotional content, where higher scores

represent disproportionate slowing to identify non-word targets after having processed

negative as compared to non-negative stimuli. Pearson‟s correlations between this index

and STAI-T and STAI-S scores did not approach significance (r(47) = .08, ns and r(40) =

-.15, ns, respectively). The absence of significant correlations between these measures

provides no support for the existence of associations between biased attentional

disengagement from emotional content and either state or trait anxiety.

Analysis of Word-Naming Latency Data

The inclusion of word naming responses in the current task was intended to

provide a measure of ongoing activation of initially processed word content by assessing

the relative priming for negative and non-negative stimuli after participants had

performed the second (non-word) lexical decision. The absence of the effect on lexical

decision data that would be indicative of anxiety-linked biased attentional disengagement

suggests one of two possibilities for the word-naming latency data. If the absence of such

effects was due to the current task‟s inability to ensure that participants disengaged from

178

the content of the initially processed word, then it is possible that anxiety-linked

differences in ongoing activation of negative and non-negative words will emerge in

word-naming latency data. However, if the task was successful in ensuring that

participants disengage from word content and high and low trait anxious participants did

not differ in the degree to which they could disengage from such stimuli, no anxiety-

linked differences in ongoing activation of negative and non-negative words would be

expected to emerge from word-naming latency data.

In order to assess whether any such differences in ongoing activation of

differentially valenced stimulus content was present, word-naming latency data were

examined. These data were the latencies to name the word presented last on each trial

across conditions where the word had appeared earlier in the same trial as a lexical

decision target (primed words) and trials where the word had not previously been

presented as a lexical decision target (unprimed words). As with prior analyses, median

naming latencies were used to minimise the influence of outlying data and only trials

where both prior lexical decision responses were correct were included. The average of

these naming latencies across the task conditions of stimulus valence (negative and non-

negative), and prime condition (primed or unprimed) for high and low trait anxious

individuals is provided in Table 7.3.

These data were subjected to a mixed design 2 x 2 x 2 ANOVA with two within

subject factors of stimulus valence (negative and non-negative) and prime condition

(primed or unprimed) and the between subject factor of trait anxiety group (high and low

trait anxious). The Biased Attentional Disengagement account of attentional bias predicts

that individuals more vulnerable to anxious mood will continue to process the content of

negative as compared to non-negative stimuli and that differences in such ongoing

179

processing will be demonstrated by greater priming effects for negative words as

compared to non-negative words for high trait anxious participants.

Table 7.3

Word-naming latencies in milliseconds for trials where negative and non-negative

stimulus words are presented as the first lexical decision target, and named words are

either primed or unprimed for high and low trait anxiety groups. Standard deviations

given in parenthesis.

Word Valence Prime Condition High Trait Group Low Trait Group

Negative Primed 590.65 (99.68) 537.50 (81.52)

Unprimed 610.87 (112.50) 569.37 (115.22)

Non-negative Primed 581.30 (109.84) 538.12 (80.43)

Unprimed 631.09 (97.72) 572.71 (113.32)

The analysis revealed a main effect of prime condition, revealing the fact that all

participants were faster to name primed words (M = 561.90, SD = 12.92) as compared to

unprimed words (M = 596.01, SD = 15.76), F (1, 45) = 19.98, p < .01. This demonstrated

that when named words were identical to the first lexical decision target there was indeed

a priming effect for these stimuli. This suggests that participants were continuing to

process the content of these initially presented words to some degree. This was the only

significant effect to emerge from this analysis however. Of particular note was the

absence of a significant three-way interaction between stimulus valence, prime condition

and trait anxiety group predicted by the Biased Attentional Disengagement account of

attentional bias, F (1, 45) = 1.51, ns. Thus, word-naming latency data provided no

180

support for the existence of an anxiety-linked difference in priming for negative and non-

negative stimulus words.

As with the lexical decision data, correlation analyses also were conducted with

word-naming data, to assess whether an index reflecting increased ongoing activation of

negative word representations were associated with measures of state or trait anxiety. To

compute this index, priming effects for both negative word trials and non-negative word

trials were first calculated for critical trials where these words appeared as the first lexical

decision target. These two measures were calculated in the same manner with trials where

the named word was primed being taken from trials where the named word was

unprimed. This resulted in two measures of priming, one for negative word trials and one

for non-negative word trials where higher scores represented shorter latencies to name

primed negative or non-negative words as compared to unprimed negative or non-

negative words. The measure of priming for non-negative word trials were then taken

from the measure of priming for the negative word trials to produce one overall index of

ongoing activation of stimulus content whereby higher scores represent greater ongoing

activation of negative as compared to non-negative words. If anxiety-linked attentional

bias is associated with a disengage bias characterised by ongoing semantic activation of

emotionally negative stimuli, then we would predict a positive correlation between this

index and measures of anxiety vulnerability. However, correlations conducted with this

index of ongoing semantic activation of negative content did not reveal any significant

association with either STAI-T, r(47) = -.21, ns, or STAI-S scores, r(47) = -.11, ns. The

absence of a significant effect does not provide support for an association between

ongoing activation of negative words and either current anxious mood or general anxiety

vulnerability.

181

Discussion

The current study introduced two key task modifications designed to test the

possibility that biased attentional disengagement from negative material in high trait

anxiety will result in continued processing of initially attended negative words. The first

was the inclusion of consecutive lexical decisions on each trial. It was believed that the

inclusion of a second trial decision which recruited the same decision making process as

the first decision may discourage continued processing of initial word content and

provide an index of disengagement from such processing. If the task was successful in

requiring participants to disengage from processing the content of negative and non-

negative words then the Biased Attentional Disengagement account of anxiety-linked

attentional bias predicts differences to emerge across stimulus valence and trait anxiety

groups. Specifically, it predicts that high trait anxious individuals will be slower to

determine the lexical status of non-words having initially processed negative as compared

to non-negative words, thereby demonstrating greater difficulty disengaging from the

emotional content of these negative words. This pattern of results did not emerge

however with no significant interaction being observed between trait anxiety group and

word valence. Correlational analyses conducted with lexical decision data similarly

provided no support for an association between biased attentional disengagement from

negative words and state or trait anxiety. Given that no anxiety-linked differences were

observed in disengagement from negative and non-negative words, it is possible that

either no anxiety-linked differences in ongoing processing of negative and non-negative

words was present or, that the task was not successful in requiring participants to

disengage from word content. Indeed, it was acknowledged that the inclusion of two task

decisions which recruited the same decision-making process could not preclude the

182

possibility that participants may continue to process word content to a different degree

while identifying a subsequent non-word target. Examination of priming data allows

conclusions to be drawn regarding this.

The second key task inclusion was designed to assess the degree of ongoing

activation of initially processed stimulus words. This permitted the examination of

whether the task was successful in requiring disengagement from word content and if the

task did not achieve this, allowed us to assess potential anxiety-linked differences in

continued processing of negative and non-negative words. The presence of a priming

effect for words presented as the first lexical decision target indicated that performing the

second lexical decision on a non-word did not require participants to disengage from the

representation of initially processed word. This suggested that participants instead

continued to process the content of these words after the second lexical decision,

allowing potential differences to emerge in ongoing processing of negative and non-

negative words. As the task was not successful in requiring complete disengagement

when performing the second task decision, the Biased Attentional Disengagement

account of anxiety-linked attentional bias predicts that high, relative to low trait anxious

individuals, would exhibit greater ongoing processing of negative stimulus words as

represented by greater priming for these words when processed as the first lexical

decision target. No anxiety-linked differences in priming effects for negative and non-

negative word targets were observed in the current task however, providing no support

for the Biased Attentional Disengagement hypothesis.

As repetition priming has been demonstrated to be a reliable and robust means of

assessing the representational activation of a stimulus word (cf. Besner & Swan, 1982)

priming data obtained in the current study perhaps provide the most compelling evidence

183

for the absence of a bias in attentional disengagement from emotional content. If we

accept that priming provides a reliable means of indexing the activation of a stimulus

word, then the results of the present experiment clearly suggest that the degree to which

participants can disengaging from the content of such stimuli it is not affected by the

emotional valence of the word or by the relative vulnerability to anxious mood of the

individual. Correlational analyses conducted using priming data similarly provided no

support for an association between measures ongoing activation of word content with

vulnerability to anxious mood. These results are clearly problematic for the Biased

Attentional Disengagement account of anxiety-linked attentional bias.

One possibility that could account for the absence of differences in ongoing

semantic activation is that no disengagement occurred for any participants on each trial in

the current task, with ceiling levels of engagement with word content obscuring evidence

of any individual differences in differential disengagement from the content of such

words. It is plausible that the intervening lexical decision response was either not

adequate to elicit natural differences in ongoing processing of differentially valenced

word content or, the brief duration between stimulus activation (when performing the

first lexical decision) and the final word-naming response may not have been sufficient

for any such differences to emerge. Indeed, the strong priming effect observed for

initially presented negative and non-negative words could suggest that the subsequent

processing of the non-word lexical target did not require participants to disengage from

processing the content of these stimuli at all. As the current task included both word and

non-word stimuli on the second trial decision it is possible to assess whether there was

indeed a decline in the stimulus activation evoked by the word encountered in the first

lexical decision by the time this was assessed by the final word-naming response. If there

184

is a reduction in priming effect for words presented immediately prior to the word-

naming response (the second lexical decision target) as compared to words presented

initially (the first lexical decision target), this could be taken to suggest that such a

decline in activation did occur, indicating that the task is sensitive to disengagement from

initial word content.

To assess this possibility a two-way ANOVA was conducted with word recency

(word as first or second lexical decision target) and priming condition (primed or

unprimed) as within subject factors. A significant two-way interaction between lexical

decision order and priming condition was indeed observed, F (1, 45) = 20.69, p < .01.

Simple main effects analyses of this interaction revealed that the magnitude of the

priming effect for primed words (M = 561.90, SD = 12.92) versus unprimed words (M =

596.01, SD = 15.76), on trials where such words were presented as the first lexical

decision target, F (1, 45) = 19.98, p < .01, was less than the magnitude of the priming

effect for primed words (M = 510.19, SD = 11.84) versus unprimed words (M = 595.51,

SD = 15.55), on trials where such words were presented as the second lexical decision

target, F (1, 45) = 67.22, p < .01. Thus the priming effect for words presented as the first

lexical decision target (34.11ms) was less than half the magnitude of the priming effect

for words presented as the second lexical decision target (85.32ms effect). This pattern is

entirely consistent with what would be expected from the decline in representational

activation of stimulus content when it has been presented as the first as compared to the

second lexical decision target before then being verbally named. Therefore, while

priming data suggest that a word processed first will remain active to some degree, the

above result suggests that the inclusion of the second (non-word) lexical decision after

initially processing a word will result in some decline in the representation of the

185

stimulus. This result permits confidence that the current task was indeed sensitive to the

decline in activation of a stimulus representation when disengaging from the initial

stimulus to process the subsequent non-word. This would further suggest that the absence

of effects implicating biased attentional disengagement are unlikely to be due to the

task‟s inability to require disengagement from processing the content of negative and

non-negative words.

Therefore, the results of the current study provide no support for the Biased

Attentional Disengagement account, likewise, although the results of Experiments 5

suggested that anxiety is characterised by the rapid engagement of attention with the

content of negative as compared to non-negative stimuli, it revealed no evidence of

biased attentional disengagement. However, in Experiments 5 it was noted that

conclusions were limited due to the insensitivity of the task (and indeed all previous

tasks) to ongoing semantic processing of stimulus content while performing the second

trial decision. The results of the current study therefore build on the findings of

Experiment 5 to suggest that, once the representation of a word has been activated, high

trait anxious individuals are not disproportionately slow to perform a subsequent

decision, even when this decision recruits the same cognitive subsystem as the first

response. Furthermore, the results highlight that while all participants experience some

decline in the activation of the initially processed word content when they perform the

second lexical decision, the degree of this disengagement from stimulus content does not

differ according to anxiety vulnerability or stimulus valence. Therefore, taken together

with the findings of Experiment 5, the results of the current study implicate the role of

biased attentional engagement with emotional content as the mechanism underpinning

anxiety-linked attentional bias.

186

While repetition priming provides a reliable, consistent means of assessing

ongoing activation of stimulus words, past researchers have questioned whether

repetition priming tasks necessarily measure conceptual activation of stimulus meaning.

Some researchers have argued that the priming effect observed in such tasks could be

attributed to the encoding of perceptual rather than conceptual aspects of a stimulus

(Morris, Bransford, & Franks, 1977). This suggests that the stimulus word may equally

be encoded according to its form rather than its semantic properties. If this were the case,

it is possible that the absence of anxiety-linked differences in ongoing processing of

negative and non-negative words in the current study could be due to the encoding of

lexical targets according to perceptual rather than conceptual properties. This would

suggest that stimuli were perceptually primed rather than conceptually primed. However,

a number of studies have highlighted that repetition priming effects on word-naming

tasks results from both perceptual and conceptual encoding. In a demonstration of this,

Strain, Patterson, and Seidenberg (1995) revealed that words with imageable meanings

(e.g. soot) have shorter naming latencies when subsequently presented than words with

abstract meanings (e.g. scarce). This result was taken to suggest that the associated

conceptual properties of words were automatically activated and this more readily

occurred for imageable words resulting in greater priming effects as compared to words

with abstract meanings. Subsequent research has provided converging support for the

contention that repetition priming results from both conceptual and perceptual encoding

of stimulus words (MacLeod & Masson, 2000). This research provides reassurance that

the priming results of the current task do reflect the conceptual activation of stimulus

words. It would further suggest that the absence of differences for high and low trait

anxious individuals in ongoing activation of negative and non-negative words is an

187

accurate reflection of the ongoing conceptual processing of these words and not merely a

reflection of a lack of conceptual encoding.

As highlighted in the discussion of Experiment 5, despite yielding evidence of

effects consistent with enhanced attentional engagement, the results of all previous

studies conducted in the current research program have failed to yield evidence for a bias

in attentional disengagement from negative stimuli. The results of the present study pose

further difficulties for the Biased Attentional Disengagement account, suggesting that

high trait anxious individuals are not disproportionately slow to disengage attention

having initially discriminated a negative word as compared to a non-negative word and

further, that the relative decline in activation for these differentially valenced words,

having performing a subsequent lexical decision, does not significantly differ for high

and low trait anxious individuals. Thus the weight of evidence as revealed by the present

series of experiments would strongly suggest that attentional bias in anxiety is

characterised by a propensity to selectively engage attention with the content of more

negative stimuli but is not associated with a relative difficulty disengaging attention from

such material once it has been identified.

In summary, the current study aimed to address the possibility that previous

measures of biased attentional disengagement from emotional content were insensitive to

potential differences in continued processing of negative and non-negative word content

while performing a second, unrelated task decision. Two key modifications were made in

the current task in order to address this question. The first was to change the second

decision on each trial such that it required the same decision making process as the first.

It was anticipated that greater ongoing activation of the initially attended stimulus content

would result in slowing to perform the second decision, thus representing greater

188

difficulty disengaging attention from the emotional content of the initial stimulus. The

second key feature of the task was the inclusion of a repetition priming measure. This

was designed to yield a measure of ongoing activation of initially processed negative and

non-negative words subsequent to performing the second trial decision. Analyses

revealed no anxiety-linked differences in latencies to identify non-words after initially

processing negative or non-negative words. Similarly, despite reassurance that priming

measures were sensitive to the decline in activation of a stimulus content resulting from

performing the second lexical decision, no anxiety-linked differences in the ongoing

activation of negative and non-negative stimulus content were observed. The current

results provide further problems for the Biased Attentional Disengagement account of

attentional bias and together with the results of Experiment 5, implicate the role of biased

attentional engagement with emotional content in anxiety-linked attentional bias.

189

CHAPTER 8

GENERAL DISCUSSION

Review of Research Findings

The central purpose of the current research program was to evaluate two

hypothetical accounts of anxiety-linked attentional bias, the Biased Attentional

Disengagement account and the Biased Attentional Engagement account. The Biased

Attentional Disengagement account of anxiety-linked biased attention contends that

vulnerability to anxious mood is associated with greater difficulty orienting attention

away from negative, as compared to non-negative material, once such material has

recruited attention, while the Biased Attentional Engagement account contends that

attentional bias in anxiety will be associated with enhanced engagement of attention with

negative, as compared to non-negative material. Past experimental approaches which

have demonstrated an attentional bias in anxiety have been unable to differentiate

whether individuals vulnerable to anxious mood selectively attend to more negative

material due to a heightened tendency to selective engage attention with such

information, or due to a greater difficulty disengaging attention from such information.

As reviewed in the introduction, recent research which has claimed support for the

existence of impaired attentional disengagement from negative material (e.g. Fox et al,

2001, 2002; Koster et al., 2004) has employed experimental methodologies which cannot

differentially attribute observed effects to biased attentional engagement or

disengagement with confidence. The present series of experiments employed a number of

task variants designed to overcome past methodological limitations and so determine

whether anxiety-linked attentional bias is associated with biased disengagement from, or

190

biased attentional engagement with negative stimuli. The evidence obtained for each of

these hypotheses in the current research program will be reviewed in turn below.

Evidence for the Biased Attentional Disengagement account of anxiety-linked attentional bias

As described in the introduction, a problem with previous tasks designed to

examine individual differences in attentional disengagement from negative stimuli, has

been that the cue used to secure initial attention has been an emotionally valenced

stimulus. Slowing to process a probe appearing in an opposite screen location to this

initial cue could therefore equally well be caused by increased initial engagement of

attention with this information, or by greater difficulty subsequently disengaging

attention from this information. Experiments 1 and 2 examined anxiety-linked differences

in alternatively valenced material with variants of the attentional probe task (MacLeod &

Mathews, 1986), designed to overcome this problem. Specifically, to measure biased

attentional disengagement, attention was initially secured with a neutral cue before a

negative or non-negative word then was presented in the cued spatial locus, with

participants subsequently being required to keep attention in the same locus as this

valenced word, or relocate attention to a spatially removed location. The results of

Experiment 1 demonstrated that, when the task ensures attention has been equivalently

secured in the locus of a differentially valenced stimulus word, high and low trait anxious

participants do not exhibit disproportionately slow responding to identify probes

appearing opposite negative, as compared to non-negative stimuli. Such findings are

clearly inconsistent with the predictions of the Biased Attentional Disengagement

account of anxiety-linked attentional bias.

The probe task used in Experiment 1 also produced some seemingly

counterintuitive results, whereby high trait anxious participants were slower to process

191

probes appearing in the locus of negative as opposed to non-negative words and faster to

process probes in the location opposite negative as compared to non-negative words,

regardless of the location of initial attention. As this pattern of results did not involve the

initial cue locus factor, it was not informative in differentiating attentional engagement

and disengagement processes. However, this pattern of effects was clearly inconsistent

with past results using attentional probe tasks which have reliably demonstrated that high

trait anxious individuals are faster to process probes appearing in the locus of negative, as

compared to non-negative material. In discussing possible reasons for obtaining such a

result, it was highlighted that while the task used in Experiment 1 permitted confidence

that initial attention was equivalently located in the spatial vicinity of a word, it still

allowed for possible differences in the semantic processing of the word in this spatially

attended region. The second probe task variant employed in Experiment 2 therefore

included the requirement that all participants must process the semantic content of the

initial stimulus word, before then discriminating a probe in the same position, or in the

opposite screen position. Again, this study observed no anxiety-linked differences in

latencies to discriminate probes appearing in the opposite, as compared to the same locus

as initially processed negative and non-negative words, thereby providing no evidence for

biased attentional disengagement of spatial attention from negative stimuli for high trait

anxious individuals.

Hence, the evidence obtained from modified probe tasks in the current research

program does not support the position that anxiety vulnerability is characterised by an

impaired ability to disengage attention from the spatial locus of more negative material.

This is inconsistent with the claims of researchers such as Yiend and Mathews (2001) and

Koster et al. (2004) who propose that high trait anxiety is associated with an impaired

192

ability to relocate spatial attention away from the locus of initially attended negative

material. The current research instead suggests that when initial attention is equivalently

secured in the locus of a differentially valenced stimulus word, and participants then

process the semantic content of the word appearing in that initial locus, then high and low

trait anxious individuals are not observed to differ in the speed with which they can

subsequently relocate attention away from this region to a different spatial locus.

The modified Stroop tasks employed in the current research program moved from

exclusively focusing on spatial disengagement of attention to instead examine whether

individuals who vary in anxiety vulnerability may have differential difficulty switching

attention between differentially emotional dimensions of a single stimulus. The modified

Stroop tasks which assessed biased attentional disengagement required participants to

first process the semantic content of negative or non-negative words, before then

switching attention to process a non-emotional dimension of these stimuli which

immediately became available, namely the colour of the word. These modified Stroop

tasks employed in Experiments 4 and 5 did not reveal any anxiety-linked differences in

latencies to colour-name negative or non-negative stimulus words, having initially

processed the content of these stimuli. The absence of such an effect on this task means

that these modified emotional Stroop task also revealed no evidence that heightened

anxiety vulnerability is associated with selective difficulty disengaging attention from

negative information.

In considering the implication of examining non-spatial or dimensional shifts in

attention in the modified Stroop task, it was noted that, if attentional engagement can be

considered to occur when a word‟s representation becomes active, then it could be argued

that attentional disengagement can only be considered to occur when the activation of the

193

stimulus representation returns to baseline. By this definition, a shift in spatial attention,

or an attentional shift to a non-semantic stimulus dimension, may or may not involve

attentional disengagement from the processing of stimulus meaning. It was considered

possible, therefore, that individual differences in disengagement may be revealed by

measuring the degree to which there is a decline in the activation of the initial

representation following the second decision. The investigation of this possibility formed

the basis of the final study. The task in Experiment 6 was designed to maximise the

possibility that participants would be required to cease processing the initial stimulus

meaning in order to execute the required decision about the second stimulus. It also

provided a measure of any ongoing activation of this first stimulus content, capable of

revealing individual differences in the continued activation of the first stimulus content,

as a function of its valence and participant anxiety level. The results indicated that the

performance of the second decision was accompanied by a reduction in the activation of

the first stimulus content, but there was no significant differences in continued activation

of negative and non-negative word content between high and low trait anxious

individuals. Again, this result yields no support for the Biased Attentional

Disengagement account of anxiety-linked attentional bias.

In summary therefore, the results of the current research program have

consistently failed to find support for the existence of an anxiety-linked difference in

attentional disengagement from negative stimuli. Specifically, when it is ensured that

high and low trait anxious participants equivalently engage attention initially with

negative or non-negative information, these groups do not subsequently differ in their

speed to shift attention away from either category of information to a spatially removed

locus. Furthermore, high and low trait anxious participants do not evidence differences in

194

the speed with which they can switch attention from processing the emotional content of

a negative or non-negative word, to instead process a non-emotional dimension of this

stimulus. Also, high and low trait anxious individuals do not evidence differences in the

ongoing activation of these initially attended stimulus words, when a subsequent task

invites the attenuation of this activation. Collectively, these results are inconsistent with

the Biased Attentional Disengagement hypothesis.

Evidence for the Biased Attentional Engagement account of anxiety-linked attentional bias

To test the hypothesis that anxiety-linked attentional bias is associated with biased

attentional engagement with negative material in high trait anxious individuals, the

current research program again employed variants of the two tasks that have most

consistently demonstrated attentional bias favouring negative material, the dot probe and

emotional Stroop tasks. The versions of these tasks developed for this purpose overcame

methodological limitations of previous tasks by securing initial attention with a non-

emotional stimulus, or non-emotional stimulus dimension, before then measuring speed

to subsequently engage attention with the spatial locus, or semantic content of

differentially valenced stimuli.

Measures of individual differences in attentional engagement with negative and

non-negative material were assessed by the probe task in Experiment 1 by first requiring

participants to attend to the locus of a non-word before either discriminating a probe in

this same locus, or orienting attention to a spatially removed position to discriminate a

probe in that region. Contrary to the predictions generated by the Biased Attentional

Engagement account, no anxiety-linked differences in the relative speed to orient

attention toward the spatial locus of probes appearing in the vicinity of negative or non-

negative words was revealed in probe discrimination latencies. However, participants

195

were not required to process the semantic content of stimulus words on this task, and so it

was possible that attention could be moved to the spatial vicinity of a particular word

without a participant engaging attention with its semantic meaning. The possibility

therefore remained that anxiety-linked differences may exist in the engagement of

attention with the semantic content of negative words.

Assessing whether attentional bias in anxiety is characterised by disproportionate

speeding to spatially shift attention to engage with the semantic content of negative and

non-negative words formed the basis of investigation in Experiment 3. The probe task

was modified such that participants first attended to a probe before then processing the

content of a negative or non-negative word appearing in the same or spatially distal

position to the initial probe. Again, however, results did not support the predictions of the

biased engagement hypothesis. No difference in latencies for participants to process

probes appearing in the vicinity of either negative or non-negative stimuli in the opposite

location to initial fixation was observed, suggesting no anxiety-linked difference in

speeding to shift spatial attention to process negative rather than neutral words. However,

it was observed that high trait anxious participants were faster to process the content of

negative, relative to non-negative words, that appeared within the initial locus of spatial

attention, a pattern that was not observed for low trait anxious participants. The results of

Experiment 3 therefore underscored the possibility that attentional switching between

alternative stimulus information within an attended spatial locus may be associated with

an anxiety-linked bias in attentional engagement, favouring the content of negative

information within the spatially attended region. This possibility highlighted the

appropriateness of examining biased attentional engagement using a task methodology

which would not require such spatial shifts in attention.

196

Experiments 4 and 5 therefore adopted a modified version of the emotional Stroop

task to assess whether anxiety vulnerability is associated with biased attentional

engagement with the content of negative words appearing within a spatially attended

region. Attentional engagement was indexed on these tasks by relative speeding to

process the content of negative and non-negative words, having previously processed the

colour dimension of these stimuli. The high rate of error in performing grammatical

judgments on the task in Experiment 4 undermined confidence in measures of attentional

engagement obtained in this study, which revealed no significant effects. However, the

equivalent measures for attentional engagement obtained in Experiment 5 using lexical

decision latencies to infer speed of engagement with semantic content of words clearly

supported the Biased Attentional Engagement account. The results demonstrated that

high trait anxious individuals were disproportionately fast to engage in processing the

content of negative relative to non-negative words appearing within the spatially attended

region, while low trait anxious individuals demonstrated the reverse pattern. This result

was consistent with the predictions of the Biased Attentional Engagement account of

anxiety-linked attentional bias, however, it specifically suggests that this engagement bias

operates only in selectively processing the content of negative stimuli already within an

attended locus.

Theoretical Implications and Future Theoretical Research Directions

The current research program set out to address the question of whether the

anxiety-linked attentional bias favouring negative material reflects either enhanced

engagement with or impaired disengagement from negatively valenced stimuli. As

previously acknowledged, it is not possible to dismiss the possibility that a

197

disengagement bias may be observed under different conditions and it remains uncertain

whether the engagement bias always will explain observed attentional selectivity.

However, if future research confirms that the attentional bias shown in those with

elevated anxiety vulnerability reflects enhanced engagement of attention with negative

stimuli, and not impaired disengagement of attention from such negative stimuli once it

has recruited attention then this will have important implications.

The findings of the present research program could generally be considered

consistent with past research regarding attentional bias in anxiety, in that it provides

further evidence that high trait anxious individuals preferentially process negative as

compared to non-negative stimuli. Such findings support the common prediction of the

three cognitive models of anxiety vulnerability described in some detail in the

introduction, that high trait anxious individuals will selectively attend to more negative

information. Bower‟s associative network model (Bower, 1981; Bower, 1987; Bower, et

al., 1994) contends the operation of emotion nodes and their associated structures

containing anxiety-congruent information. This model suggests that stronger connections

between emotion nodes and associated structures resulting from frequent state anxiety

responses will contribute to cognitive biases in information processing and greater

emotional vulnerability to anxious mood, including an attentional bias favouring anxiety-

congruent information. Beck‟s schema model (1976; Beck & Clark, 1988; 1997; Beck, et

al., 1985) contends that anxiety vulnerability is characterised by the presence of danger

schemata, which develop as a result of historical events involving personal threat. When

activated by a stressful event or stimulus, these schemata act to bias information

processing in a anxiety-congruent manner. This model therefore predicts that high trait

anxious individuals will exhibit biased processing of stimuli which are emotionally

198

negative or threatening in tone. Williams et al.‟s (1988; 1997) integrative processing

model of emotional vulnerability proposes that high trait anxiety is associated with highly

integrated representations of negative information. Such integrated representations will

lead to partial matches in the environment activating the entire representation. Williams

et al.‟s model specifically predicts that this will contribute to a lower threshold for

detecting anxiety-congruent information in individuals more vulnerable to anxious mood

and this in turn will result in rapid detection of negative material.

Clearly the studies which demonstrated selective attention in the present research

are consistent with the general predictions of all of these cognitive models, in that high

trait anxious individuals did exhibit an attentional bias favouring more negative material.

The present research went beyond the scope of past research examining the presence of

attentional bias in anxiety, to examine the precise nature of this bias with respect to

attentional engagement and disengagement. When anxiety-linked attentional bias has

been demonstrated within the present research program it has always been the case that

this has involved differential engagement. The present findings therefore specifically

implicate the role of biased attentional engagement with emotional content as

underpinning anxiety-linked attentional bias. In considering the implications of these

finding for the specific cognitive models discussed above, both Beck and Bower‟s

models suggest general activation of anxiety-congruent cognitive structures, and so

predict a very wide range of processing biases associated with anxiety, including, but not

restricted to, an attentional preference for negative stimuli. While neither of these models

makes specific reference to attentional engagement or disengagement processes, the

generality of their predictions in relation to information processing biases suggests that

these models lead to the expected operation of a bias in both attentional engagement and

199

disengagement among individuals vulnerable to anxious mood. However, the Williams et

al. (1988; 1997) model specifically indicates that the highly integrated nature of anxiety-

related information in the cognitive system will lead to enhanced detection of negative

information, which would be expected to influence attentional engagement with such

information rather than attentional disengagement from it. In studies which have

demonstrated an attentional bias in the current research, the pattern of findings obtained

suggest that attentional bias in anxiety is indeed associated with a tendency to selectively

engage attention with the content of negative stimuli. Alternatively, the present research

has failed to demonstrate support for the position that such an anxiety-linked bias is

associated with an impaired ability to disengage attention from such stimuli once it has

been identified. Thus, this pattern of support for the Biased Attentional Engagement

account of attentional bias could be considered most consistent with Williams et al.‟s

model of anxiety-linked cognitive bias, which specifically implicates the role of enhanced

detection of negative material in anxiety, but not impaired reallocation of attention from

such stimuli once they have been identified.

The present research findings lend weight to the concerns expressed in the general

introduction regarding previous studies that have claimed to demonstrate anxiety-related

impaired disengagement from negative material. It will be recalled that one of the most

consistently used tasks employed to examine biased attentional disengagement from

negative stimuli has been based on Posner‟s (1980, Posner et al., 1987) attentional cueing

paradigm. The modified version of this task has involved presenting negative or non-

negative stimuli to a left or right screen position as initial cues, and then requiring

participants to identify the position of a subsequently presented probe which appears in

either the same location as the initial stimuli, or the opposite screen position. Slowing to

200

identify the location of the probes appearing opposite the initial cue stimulus has been

taken as a measure of the latency to disengage attention from the initial valenced stimuli.

A number of studies have reported an anxiety-linked difference in the response latencies

for probes appearing in the screen position opposite negative as compared to non-

negative stimuli and have attributed this to differences in attentional disengagement from

emotional info (Fox et al., 2001; 2002; Koster et al, 2006; Yiend & Mathews, 2001).

However, one of the key criticisms previously discussed regarding the use of this task for

measuring biased attentional disengagement was the absence of a means of ensuring that

participants equivalently attend to the initially presented stimuli, and process its content

to the same degree. Without this, it is impossible to attribute the observed effects

specifically to either attentional engagement or attentional disengagement as initial

attentional engagement is not controlled.

The consistent absence of support for the Biased Attentional Disengagement

account in the current research could be taken to suggest that when care is taken to ensure

equivalent initial engagement with the locus and content of emotional stimuli, no anxiety-

linked differences emerge in the subsequent disengagement of attention from

differentially valenced stimuli. Conversely, the present research findings in relation to

anxiety-linked attentional bias suggest that when initial attention is equivalently focused

on non-emotional information then high trait anxious individuals subsequently display

enhanced attentional engagement with the content of newly presented negative over non-

negative information. It is entirely possible therefore, that past research claiming to have

revealed anxiety-linked impaired disengagement from negative material has in fact been

demonstrating a flow on effect of the same attentional engagement bias observed in the

current research. A clear implication is that any task designed to assess differential biases

201

in attentional engagement and attentional disengagement must be able to ensure

equivalent attentional engagement with the valence of the information being shifted from.

The experimental tasks employed in the current research therefore provide a model for

future studies wishing to assess the unique contributions made by attentional engagement

and disengagement processes to any observed pattern of attentional bias.

The presence of support for the Biased Attentional Engagement account in the

current research allows us to discount the possibility that all past research which has

demonstrated an anxiety-linked attentional bias has actually been disengagement effects

wrongly interpreted as engagement effects. Indeed the present findings have shown that

some recent research claiming to reveal biased attentional disengagement effects could

plausibly be instead attributed to reflect attentional engagement effects. Although the

present research has revealed evidence for selective attentional engagement that is not

attributable to biased disengagement, it is also the case that across the present series of

studies evidence for anxiety-linked attentional engagement was not always found. Indeed,

the series of studies described in the current thesis suggests that whether or not evidence

is obtained for an engagement bias at least depends upon the nature of the task used to

assess such a bias. Therefore, while we can be confident that future research is likely to

reveal the presence of an engagement bias, it is unlikely that such a bias will be

universally observed. An important line of future research will therefore be to establish

which set of experimental circumstances do and do not reveal such an effect, which will

likely advance understanding of the precise mechanisms that give rise to anxiety-linked

engagement bias.

While the present program of research has revealed no evidence of an anxiety-

linked engagement bias on any of the six experiments conducted it would be

202

inappropriate to dismiss the possibility that biased attentional disengagement effects may

occur under some circumstances, or in certain populations, on the basis of the current null

findings. For example, in the present research we compared patterns of attentional

disengagement for high and low trait anxious members of the normal population,

however, it is possible that a group difference in attentional disengagement from threat

would emerge if we compared clinically anxious individuals with normal members of the

population. It is conceivable that while high trait anxious members of the normal

population may not demonstrate biased disengagement, an impaired ability to disengage

attention from negative stimuli may be a feature of clinically anxious populations and

form a key difference between these groups. Indeed, different clinical conditions may

also reflect different combinations of biased attentional disengagement and engagement.

Clinical disorders associated with a high degree of emotional reactivity to perceived

threat (e.g. Panic Disorder) could conceivably be more associated with high levels of

biased attentional engagement with emotionally negative stimuli. This may therefore

increase the likelihood that individuals possessing such a bias will identify and react

strongly to negative stimuli in their environment but also experience a relatively rapid

reduction in their anxiety. Alternatively, those conditions which reflect greater

perseveration of an anxiety response (e.g. Generalised Anxiety Disorder) may be more

associated with an impaired ability to disengage attention. Therefore, while these

individuals may not demonstrated enhanced detection of negative material, an impaired

ability to reallocate attention away from emotionally negative material once it is

identified may prolong elevated anxiety levels. It is plausible therefore, that comparing a

population based on anxiety reactivity and anxiety perseveration could reveal a different

203

pattern of biased attentional engagement and disengagement to that observed in the

present series of studies.

While such possibilities are certainly intriguing it should be emphasised that their

identification in this discussion is not intended to persuade the reader of their validity.

Indeed, to date no demonstrated anxiety-linked attentional bias requires the conclusion

that elevated anxiety is ever associated with impaired disengagement from threat. The

main point being made here is that the absence of evidence to confirm the existence of an

anxiety-linked disengagement bias does not permit confidence that such a bias does not

exists or makes a distinctive contribution to certain aspects of anxiety not investigated in

the present research program.

Setting aside the important distinction between attentional engagement and

attentional disengagement, it is important to note that some present variants of the

attentional probe task revealed no evidence of any anxiety-linked attentional bias despite

this having been demonstrated on previous attention probe task variants. Prior studies

employing attentional probe methodologies have consistently demonstrated that

individuals more vulnerable to anxious mood show an attentional bias favouring the

spatial locus of negative as compared to non-negative stimuli (e.g. MacLeod et al., 1986;

MacLeod & Mathews, 1988, Mogg, et al., 1992). However, the modified probe tasks

used in Experiments 1, 2 and 3 provided no evidence for an anxiety-related bias in either

spatial engagement with or spatial disengagement from the locus of emotionally valenced

stimuli. Indeed, the results of Experiment 3 suggested that the attentional bias observed in

high trait anxious individuals when orienting attention from the probe to engage with the

content of a negative word in the same spatial locus was eliminated when they were

required to relocate spatial attention to engage with the content of such words. The fact

204

that an attentional bias favouring negative stimuli is consistently revealed for high trait

anxious individuals in traditional probe tasks, poses the question as to why the current

studies were unable to reveal biases in the allocation of spatial attention for either

attentional engagement or disengagement.

It is possible to introduce a conceptual dichotomy to distinguish two hypothetical

ways in which either an attentional engagement or disengagement bias might operate,

that could account for the absence of anxiety-linked effects in spatial attention in the

present probe task variants. This dichotomy concerns the potential difference between an

individual‟s ability to selectively attend to one type of stimulus rather than another, and

their tendency to attend to one type of stimulus rather than another. When an individual is

presented with processing options and is permitted but not required to attend to one class

of stimuli then the degree to which they attend to this stimulus, will depend upon their

tendency to preferentially allocate attention to this stimulus. However, when an

individual is presented with a processing option and is required to attend to one type of

stimulus rather than another, then a measure of their compliance with this requirement

will reflect their relative ability to preferentially attend to this stimulus. Given that

traditional attentional probe tasks require participants to move attention to the probe locus

to make the discriminate response, but also permit individual differences in which locus

was preferentially attended to prior to the probe presentation, it follows that these

traditional tasks may either assess high trait anxious individuals‟ ability to selectively

attend to the vicinity of negative stimuli, or their tendency to do so.

In order to accurately measure attentional engagement with and disengagement

from valenced stimuli, the probe task variants used in the current series of studies

required participants to attend to an initial location, before then requiring participants to

205

either remain in the same locus, or relocate attention toward or away from differentially

valenced stimuli. The necessity of requiring that participants equivalently attended to an

initial locus and/or stimulus then move attention or not, essentially meant that the current

probe tasks provided a measure of participants‟ ability to engage attention with, or their

ability to disengage attention from, the spatial vicinity of a negative or non-negative

word. Unlike traditional probe tasks, these new variants would not assess differences in

the tendency to allocate attention between competing stimuli. It is possible therefore, that

the anxiety-linked bias observed on traditional probe task variants may reflect a

heightened tendency for participants to attend to negative material, but no increased

ability to do so. Most conventional tasks would, however, have difficulty distinguishing

whether observed attentional bias effects are due to a differential ability or a differential

tendency. For example, time to perform a task which requires attentional disengagement

may be influenced by tendency rather than ability if at an earlier point in the task

disengagement has been possible, even though not required. To develop tasks capable of

sensitively distinguishing ability and tendency requires a consistent concentrated and

creative effort.

Developing future probe tasks capable of distinguishing between biases in ability

and tendency to engage with and to disengage from valenced stimuli could provide a

means of pursuing the possibility that the anxiety-linked bias observed on traditional

probe tasks may reflect tendency to attend to negative material, but not the ability to do

so. In order to achieve this, it would be necessary to construct two variants of the

modified probe task; one which assesses the ability of participants to spatially engage

attention with, and disengage attention from valenced stimuli, and one which assesses the

tendency of participants to spatially engage attention with and disengage attention from

206

valenced stimuli. Such a task could be structurally similar to that employed in

Experiment 1 with a few critical modifications. All trials could involve securing attention

in an initial locus with a cue that participants are required to note the structure of (e.g. an

arrow facing left or right). Two letter strings would then be presented (a negative or non-

negative word paired with a non-word), one in the same position as the initial cue the

other in the opposite screen position. For trials assessing participant‟s ability to engage

attention with, and disengage attention from valenced stimuli, a single arrow probe would

subsequently appear on the screen with participants being required to indicate if this

probe arrow is a match or mismatch to the initial cue arrow. Those trials assessing

engagement ability therefore would reveal participants‟ speed to engage with the location

of a negative or non-negative word, when this was required. Trials assessing

disengagement ability would be identical, except initial attention would be secured in the

locus of a negative or non-negative word with the probe arrow appearing opposite this.

Here the decision latency would reveal participants‟ ability to disengage from the

location of the negative or non-negative word, when required to do so. In contrast, on

trials assessing engagement and disengagement tendency, two arrows would instead be

presented, one in the vicinity of each of the two letter strings and each facing a different

direction. These would appear only briefly with participants being instructed to respond

by indicating whether the first arrow that they see matches the cue arrow or not. This

would therefore provide an indication of the location that participants tended to be in

when the probe appeared, revealed by the direction of the arrow that they reported. Thus

for trials assessing disengage tendency, attention would be secured in the locus of a

negative or non-negative word and whether participants identify the arrow in the same

versus the opposite screen position would provide an indication of their tendency to

207

disengage from this initial position. Conversely, for trials assessing engage tendency,

attention would be secured in the locus of a non-word and participants‟ response to either

the arrow in the same location or the arrow in the locus of a negative or non-negative

word in the opposite screen position would provide an indication of their tendency to

engage with these differentially valenced stimuli. A task with this structure would have

the capacity to differentiate relative ability and relative tendency to demonstrate biased

attentional engagement with, and disengagement from the spatial locus of valenced

stimuli.

Probe

Fixation Cue Brief Stimulus Cue Word stimuli Remain until response

Probe

Fixation Cue Brief Stimulus Cue Word stimuli Very brief presentation

Figure 8.1. Example of a probe task which could reveal individual differences in the tendency and

ability to engage with and disengage from valenced stimuli. Initial cue position and match/mismatch

between cue and probe shown randomly. Actual task would also include non-negative stimuli.

+

+

CRITICISE

IVFKLZJID

+

CRUEL

LFGPQ

+

CRUEL

LFGPQ

CRITICISE

IVFKLZJID

NONWORD

Ability to Engage

Secure attention in locus of nonword

Require shift toward the locus of a

valenced word

Ability to Disengage

Secure attention in locus of

valenced word

Require shift away from this locus

Tendency to Engage

Secure attention in locus of a nonword

Tendency to engage revealed by which

probe is identified

Tendency to Disengage

Secure attention in locus of valenced word

Tendency to disengage revealed by which

probe is identified

CRITICISE

IVFKLZJID

CRUEL

LFGPQ

CRUEL

LFGPQ

CRITICISE

IVFKLZJID

NONWORD

208

While it is possible that differences in ability and tendency could account for the

absence of anxiety-linked differences in attentional engagement and disengagement of

spatial attention on the present probe task variants, an alternative account could also

provide a plausible explanation for the absence of such effects. The central finding

resulting from the present series of studies suggests that high trait anxious individuals

selectively engage with the content of negative over non-negative stimuli, when this

material is presented within an already attended locus. Such an attentional bias could

accommodate the pattern of results from prior probe tasks which indicate that high trait

anxious individuals are faster to discriminate probes presented in the vicinity of negative

stimuli. It is possible that high trait anxious individuals may attend with equal frequency

to either the locus of negative or non-negative stimuli, but, the likelihood that they will

engage with the content of the word in that locus will be disproportionately great when

the word is negatively valenced. If we consider that greater engagement with the content

of such material may result in attention pausing longer in this locus than would be the

case if word meaning was not processed, this then would facilitate identification of

probes appearing in the vicinity of negative as compared to non-negative stimuli. An

attentional engagement bias which involves selective processing of the content of

negative stimuli in an already attended locus could readily accommodate findings in the

traditional probe task. Also, such a bias would not emerge on present variants of the

attentional probe task as these tasks controlled for engagement with the content (or locus

of) differentially valenced stimuli, which may underlie this individuals difference, while

focusing on differences in speed to move attention from or toward such information.

209

A non-spatial attentional bias favouring engagement with the content of negative

stimuli could also accommodate the pattern of findings on previous research examining

attentional engagement with and disengagement from differentially valenced stimuli

using variants of Posner‟s (1980, Posner et al., 1987) attentional cueing paradigm (e.g.

Fox et al., 2001; 2002, Yiend & Mathews, 2001). Such a non-spatial attentional

engagement bias could resemble a spatial disengage bias in that, once attention is in a

spatial region, it would not move away as quickly if the material in that locus was

negative in valence. This slowing would reflect enhanced engagement with the semantic

content of negative words in whatever spatial locus happened to be attended to, rather

than a selective difficulty orienting attention away from such information. It is plausible

therefore that in modified variants of the attentional cueing task (e.g. Yiend & Mathews,

2001) the slower responses to process probes presented opposite cues containing

negative, as compared to non-negative information for high trait anxious individuals,

could represent biased engagement with the content of these negative stimuli when

attention is directed to their locus, rather than a selective difficulty to spatially relocate

attention away from such material.

When turning to findings regarding non-spatial attention, the results obtained in

the current research program are less inconsistent with past research. The pattern of

effects observed on the modified Stroop task in Experiment 5 is entirely consistent with

past findings using the traditional emotional Stroop task, which have demonstrated

disproportionate slowing for high trait anxious individuals to colour-name negative as

compared to non-negative words. The results of the present modified Stroop tasks

specifically suggest that such slowing to colour-name negative stimuli on traditional

emotional Stroop tasks may reflect a bias in selective attentional engagement with the

210

content of negative words for high trait anxious individuals. Such a selective processing

bias could readily cause slowing to colour name negative stimuli for high trait anxious

individuals, as greater engagement with the content of negative stimuli for these

individuals is likely to result in greater interference with the task of colour-naming than

for those who do not engage with this stimuli to the same degree.

When one considers the engagement effect observed on the present modified

Stroop task with reference to the distinction discussed between biased ability and

tendency, clearly the present emotional Stroop task provides a measure of engagement

ability. That is, the nature of the present variant of the emotional Stroop task required that

participants access the meaning of the stimulus word and assessed the speed with which

they were able to do so. The results derived from this task would therefore suggest that

high trait anxious individuals do show enhanced engagement with the content of negative

stimuli, and that this bias reflects engagement ability. It is less clear, however, whether

the component of the present emotional Stroop task variant assessing attentional

disengagement measured ability or tendency to disengage, and it is also unknown what

pattern of results would be revealed if the task had also measured engagement tendency.

A recent study conducted within our research group (Barnes, 2008; unpublished

manuscript) used an extension of the modified emotional Stroop task used in Experiment

5 to distinguish anxiety-linked differences in ability and tendency to engage with and

disengage from emotional material. The study confirmed the presence of an anxiety-

linked bias in engagement using an ability version of the task, with results again

suggesting that high trait anxious participants switch attention to selectively process the

content of negative stimuli when required to do so. The study also revealed that such an

engagement bias was absent on the tendency version of the task. The study did not reveal

211

any evidence to support the existence of an anxiety-linked bias in tendency or ability to

disengage attention from negative or non-negative stimuli. Therefore, while the present

series of experiments did not directly examine differential tendency, the finding that high

trait anxious individuals have an increased ability to engage with negative stimuli on a

task assessing both ability and tendency is consistent with the results observed on the

emotional Stroop task employed in Experiment 5. This finding also acts to clarify the

question of whether the absence of anxiety-linked effects on the disengagement version

of the emotional Stroop task in the present research reflects the absence of differential

disengagement ability, tendency or both, suggesting that for neither of these processes is

differential disengagement evident.

The current research program has produced findings consistent with the presence

of an attentional bias favouring negative stimuli for high trait anxious individuals. More

specifically, these findings suggest that anxiety-linked attentional bias may be

characterised by Biased Attentional Engagement with negative stimuli. The present

research could therefore be considered most consistent with theoretical models, such as

Williams et al. (1988; 1997) integrative processing model, that implicate enhanced

attentional engagement with emotionally negative material.

Applied Implications and Future Applied Research Directions

There are a number of applied reasons that researchers or clinicians may seek to

assess attentional bias. For example, indices of such a bias predict future emotional

reactions to adverse events (MacLeod & Hagen, 1992) or long term stress (Clarke,

MacLeod, & Shirazee, 2008), and measures of attentional bias have been used as an

index of progress and/or recovery from anxiety dysfunction (Mathews et al., 1995). The

212

present research strongly suggests that such measures will be of greatest applied value

when they index biased attentional engagement with the content of negative material,

rather than biased attentional disengagement from such material. If, as the present

findings suggest, the attentional bias associated with anxiety vulnerability reflects

selective engagement with negative stimuli, then the most useful measures of anxiety-

linked attentional bias will specifically reveal individual differences in selective

attentional engagement with negative information. This could lead to more precise means

of indexing attentional biases for a number of purposes including improved measures for

predicting negative emotional reactions to stressful life events, or for monitoring the

degree to which psychological interventions remediate the specific forms of cognitive

processing biases most strongly associated with anxiety vulnerability.

The observation that biases in attentional engagement with negative information

underlie the anxiety-linked attentional bias favouring negative material can also inform

cognitive rehabilitation approaches designed to reduce anxiety vulnerability by directly

modifying the pattern of selective attention characteristic of such vulnerability. It will be

recalled from the introduction that a modified version of the attentional probe task has

proven capable of directly manipulating attentional response to negative stimuli, by

presenting probes consistently in the location of non-negative words or consistently in the

location of negative words (MacLeod et al., 2002). This previous research has further

demonstrated that induced processing biases can systematically modify emotional

reactivity to a stressor, such that individuals become more or less vulnerable to anxious

mood depending on whether the contingency has encouraged attentional processing of

negative or non-negative material respectively (MacLeod et al., 2002). Preliminary

research has also suggested that extended exposure to such attentional training

213

procedures designed to induce attentional avoidance of negative stimuli, can reduce

symptoms of anxiety in high trait anxious members of the general population (Amir,

Selvina, Elias & Rousseau, 2002) and in clinically anxious patients (Vasey, Hazen, &

Schmitd, 2002).

The present research clearly suggests that such attentional training procedures

should be rendered maximally effective by optimising their ability to reduce selective

engagement with the content of negative material while promoting engagement with the

content of non-negative stimuli. A training task designed to specifically modify

attentional engagement bias could take a similar format to the emotional Stroop variant

used in Experiment 5. In order to reduce an attentional engagement bias favouring

negative stimuli, an attentional training variant of this task could introduce a contingency

such that, having initially processed the text colour of the stimulus, individuals then

consistently must processes the content of non-negative stimuli, while instead performing

a second structural judgment on negative stimuli. While speculative, it is possible that a

task which specifically targets biased attentional engagement with negative stimuli may

be more effective in reducing anxiety vulnerability. The scope of such investigation lies

considerably beyond the current research program but presents as a potentially rich area

for future studies.

Limitations of Present Research and Future Research Directions to Overcome These

As is the case with all research programs, the present series of studies reported in

the current dissertation are subject to certain limitations in population samples, stimulus

materials, experimental tasks and measures which it is appropriate to recognise.

214

The focus on high trait anxious individuals as a population sample of emotionally

vulnerable individuals was deliberate in that the purpose of the research was to address

the hypothesis concerning the specific information processing biases that distinguish high

trait anxious individuals from individuals who are lower in vulnerability to anxious

mood. Nevertheless, the fact that participants have not been selected on the basis of

anxiety pathology clearly limits the capacity to extrapolate conclusions to such clinically

anxious groups. It is possible therefore, that factors which differentiate high trait anxious

from low trait anxious members of the normal population, may not be related to those

that distinguish clinically anxious people from those without anxiety dysfunction.

Some confidence that the present pattern of findings may replicate in individuals

with clinical levels of anxiety can be drawn from the previously demonstrated similarities

between patterns of attentional effects shown by both clinically anxious and high trait

anxious individuals. For example, the emotional Stroop task has consistently

demonstrated that both high trait anxious individuals and clinically anxious patients

exhibit a disproportionate slowing to colour-name negative stimulus words (cf. Williams,

Mathews, & MacLeod, 1996). Similarly, selective attention favouring the locus of

negative words in the dot probe task has been observed in both high trait anxious

members of the general population (Mogg, et al., 1994) and clinically anxious individuals

(MacLeod, et al, 1986). Also, the observation that high trait anxiety represents a powerful

risk factor for the development of clinical anxiety disorders (Eysenck, 1992), supports the

notion that patterns of information processing associated with high trait anxiety are also

likely to be features of clinical pathology. Nevertheless, as earlier discussed, it is possible

that features which distinguish high trait anxious members of the normal population with

clinically anxious individuals may include differences in the pattern of attentional

215

engagement and disengagement. Therefore, despite confidence that attentional bias exists

in both high trait anxious and clinically anxious groups, it cannot be concluded that the

contribution made by engagement and disengagement mechanisms to the occurrence of

these biases is equivalent for clinically anxious individuals and high trait anxious

members of the normal population. This is because previous research paradigms which

have demonstrated consistency in attentional bias across high trait anxious and clinically

anxious groups have not been able to distinguish engagement and disengagement aspects

of attentional bias. A clear avenue for future research will therefore be to assess whether

the present findings implicating the role of biased attentional engagement with the

content of negative stimuli generalise to clinically anxious populations.

Another noteworthy issue regarding the sample employed in the present series of

studies is that it does not readily allow differentiation of the relative roles of state and

trait anxiety. Individuals were deliberately selected for participation in the present

experiments due to the interest in individual differences in vulnerability to anxious mood.

However, because state and trait anxiety are generally highly correlated it can be difficult

to attribute observed findings to the effects of one or the other. It is entirely plausible

therefore that the pattern of biased attentional engagement and disengagement exhibited

by individuals may differ depending on both their general vulnerability to anxious mood

and their current anxious state. It is possible to envisage a research design capable of

differentiating the role of these two dimension of anxiety. One way of doing this would

be to examine measures of biased attentional engagement and disengagement in high and

low trait anxious individuals at times of relatively high and low stress. This would

provide an indication of whether these components of attention differ with respect to the

processing of negative and non-negative stimuli depending on current anxious mood. At

216

present, however, the findings observed in this thesis must be limited to patterns of

attention in individuals who differ in general vulnerability to anxious mood.

The key findings of this dissertation were based on tasks that exclusively

employed lexical information, with the critical stimuli being negative and non-negative

words. Of course, the purpose of the current research was to resolve alternative

explanations of attentional bias in anxiety which have been demonstrated in past research

using lexical information making this the appropriate material for use in the present

studies. There were also a number of practical advantages to using these stimuli in the

present experimental tasks. In the current research program the majority of tasks (with the

exception of Experiment 1) included a stimulus that could require processing of its

content and a measure of the speed with which that content could either be engaged with

and/or disengaged from. With lexical representations, the nature of the content is readily

contained within a single stimulus and there are tasks which readily enable measurement

of the speed to access the representation of that information (e.g. lexical decision). Word

stimuli therefore provided an appropriate stimulus that fulfilled these experimental

requirements.

Not only did lexical stimuli provide an appropriate stimulus for use in these

assessment tasks, but it is worth noting that a large amount of information that we obtain

naturally is conveyed lexically, either through written material or verbal communication.

Researchers have estimated that between 50% and 80% of the workday is spent

transmitting or receiving verbal information, either through text or spoken language

(Klemmer & Snyder, 1972). Other research has found that the amount of time spent on

„information behaviour‟ (using printed media, computers, personal communication and

visual media) is in excess of 7 hours a day (Suzuki, Hashimoto, & Ishii, 1997).

217

Considering the considerable amount of time devoted to expressing or receiving written

or verbal lexical information and the amount of information conveyed in this form, the

use of lexical stimuli could therefore be considered highly appropriate. Nevertheless, this

does not mean that future research should neglect to examine biases in attentional

engagement with and disengagement from non-lexical information.

In considering types of stimuli that could be adapted for use in tasks assessing

biased attentional engagement with and disengagement from emotional material, an

obvious alternative is pictorial stimuli. Using pictorial stimuli which convey negative or

non-negative information could potentially yield different effects to those obtained in the

current research. Constructing a task capable of measuring attentional engagement with

and disengagement from such information could prove challenging. To ensure

participants processed these stimuli, and to obtain a measure confirming that this was

achieved, decisions regarding content would need to be uncomplicated and readily

performed on the stimulus. This itself could necessitate a contrivance of pictorial stimuli

which may undermine the ecological validity derived from using such stimuli in the first

place. Such a dilemma essentially reflects the tradeoff between isolating and measuring a

construct under contrived circumstances, and accurately approximating the conditions as

they occur naturally, whereby the closer approximation of naturalistic conditions often

leads to a diminished capacity for control that compromise measurement of the critical

processes under consideration.

It would be possible, however, to design a task measuring biased attentional

engagement with and disengagement from emotional content that could employ non-

lexical stimuli. Such a variant could include pictorial stimuli, such as faces whose

expressions differ in emotional tone to convey either negative (e.g. angry) or non-

218

negative meanings (e.g. happy). Indeed, variants of the traditional probe task utilising

negative and non-negative face stimuli have obtained results consistent with past probe

methodologies using word stimuli, demonstrating that individuals more vulnerable to

anxious mood show disproportionate speeding to detect probes appearing in the locus of

faces conveying negative expressions relative to faces showing non-negative expressions

(e.g. Pishyar, Harris, & Menzies, 2004; e.g. Santesso et al., 2008). Variants of the

emotional Stroop task using coloured faces in place of words have also demonstrated

consistent results with traditional Stroop tasks where higher levels of anxiety are

associated with disproportionate slowing to colour-name negative faces (Heim-Dreger,

Kohlmann, Eschenbeck, & Burkhardt, 2006).

To develop a pictorial variant of the emotional Stroop or probe task capable of

assessing biased attentional engagement with or disengagement from emotional content,

it would be necessary to include a means of assessing engagement with the content of

pictorial stimuli. By using face stimuli, such as that outlined above depicting negative

and non-negative emotions, and requiring judgments based on a variable such as age (e.g.

young vs old) it would be possible to infer engagement with the stimulus content.

Requiring participants to make such a judgment based on stimulus content before then

processing a structural (non-emotional) aspect of the image would provide a measure of

attentional disengagement from the content of such stimuli, while processing non-

emotional information before then engaging with the content of the pictorial stimuli

would provide a measure of attentional engagement. While the consistency in past

findings regarding attentional bias and anxiety using both lexical and pictorial stimuli

could encourage speculation that the pattern of results observed in the present series of

experiments may generalise to other, non-lexical information, until this research is

219

replicated with such non-lexical stimuli the implications of the present findings should be

limited to lexical information.

Another aspect of the stimuli used in the current research that must be recognised

is the relatively mild valence of the negative emotional material used. Again, because the

current research was attempting to clarify whether effects demonstrated in past research

could be attributed to alternative accounts of anxiety-linked attentional bias, using stimuli

that was similar in emotional tone to that employed in past research was entirely

appropriate in the present series of studies. Nevertheless, it is readily apparent that these

word stimuli are not likely to be highly evocative in terms of anxiety responses.

However, in considering the nature of adaptive relative to problematic anxiety, it is

apparent that stimuli which conveys moderately negative emotional tone may be

preferable than highly negative stimuli when examining individual differences in anxiety

vulnerability. It will be recalled from the introduction that the function of adaptive

anxiety is to anticipate and avoid potentially adverse events or situations. Identifying

genuine sources of threat in the environment is therefore likely to be highly adaptive to

avoiding negative consequences associated with these. Alternatively, problematic anxiety

is tending to become anxious in response to material that only mildly represents threat.

Indeed, diagnostic criteria for some anxiety pathology specify that the level of anxiety

experienced is disproportionate to the actual level of threat. In order to receive a

diagnosis of Specific Phobia for example, an individual must experience “marked and

persistent fear that is excessive or unreasonable” (American Psychiatric Association,

1994, p. 449).

Based on this understanding of adaptive versus problematic anxiety, it could be

anticipated that highly threatening or intensely negative stimuli might elicit similar

220

affective and cognitive responses across all individuals, because detecting genuine

sources of threat will be highly functional. Problematic anxiety may involve

disproportionate attention to, and disproportionate anxiety responses to, only relatively

mild negative information. Therefore, if research seeks to examine the basis of the

individual differences in anxiety vulnerability then it makes sense to be using only mildly

negative stimuli that will differentiate responses across individuals with high and low

levels of anxiety vulnerability. Highly negative stimuli may instead produce a consistent

attentional response for all individuals.

While this logic suggests that the use of more strongly negative stimuli may be

less effective in eliciting individual differences in information processing biases, the

question remains however, as to whether similar results would be obtained in the current

research with more extremely negative stimuli. There are empirical reasons to believe

that such materials may be less effective in eliciting valenced-linked information

processing biases than moderately negative stimuli. Wilson and MacLeod (2003)

conducted a study aimed at examining whether stimuli that systematically varied in terms

of threat value would elicit different patterns of selective attention for high and low trait

anxious individuals. Using a probe task methodology, their study suggested that for

stimuli with very low and very high threat value, high and low trait anxious individuals

did not significantly differ in their pattern of attention, with both groups attending away

from stimuli with very low threat value and toward stimuli with very high threat value. It

was only for stimuli with intermediate threat value that the participants demonstrated a

different pattern of attention, with results suggesting that low trait anxious individuals

attended away from such moderately threatening stimuli and high trait anxious

individuals attended toward them. While these results lend credence to the argument that

221

moderately negative stimuli are more likely to elicit individual differences in information

processing biases, it is true that we do not know if there are anxiety-related differences in

the more specific processes of biased attentional engagement with or disengagement from

more extremely negative stimuli. The conclusions drawn in the present research program

cannot yet be extended beyond the mild to moderately negative stimuli employed in the

current series of studies.

An additional limitation of the current research, concerns the nature of the

experimental measures gathered in the current research program. The key measures of

selective information processing were based only on reaction-time data. In these studies,

reaction time data provided an appropriate measure of the speed with which participants

processed information in a given location or, processed a particular stimulus dimension,

which allowed us to infer speed of allocation of attention across different stimuli and

participant groups. Depending on the structure of the experimental task, reaction time

measures can reveal and distinguish many different types of processes, including implicit

and explicit memory (Bradley, Mogg, & Williams, 1995), biases in processing

ambiguous information (Richards & French, 1992), acquisition of conditioned responses

(Hermans et al., 2005), and the effects of medication on task performance (Tucha et al.,

2006) to name merely a few.

While reaction time data can yield useful information for many different

empirical questions, there are other measures of attentional distribution that also could

potentially be used to assess anxiety-linked biases in attentional engagement and

disengagement, and it would be useful to establish whether similar conclusions would be

warranted from studies using such measures. One such methodology could involve

tracking an individual‟s foveal vision when presented with various visual stimuli, to

222

assess dimensions of eye gaze such as initial shift direction or „orienting response‟ and

the length of dwell time on particular stimuli. Using such techniques researchers have

demonstrated that when presented with a stimulus array containing a number of words,

one of which is negative in valence, individuals with clinical levels of anxiety

(Posttraumatic Stress Disorder) preferentially fixate on negative stimuli as compared to

controls (Bryant, Harvey, Gordon, & Barry, 1995). Such eye tracking methodology has

also been used with variants of the traditional dot probe task. Mogg, Millar, & Bradley

(2000) demonstrated that on such a task, clinically anxious individuals (Generalised

Anxiety Disorder) were more likely to demonstrate initial eye movement in the direction

of negative stimuli as compared to controls. While the design of their study was not

constructed to differentiate attentional engagement and disengagement processes, their

finding that clinically anxious individuals preferentially orient eye-gaze toward the locus

of negative material could be considered indicative of selective engagement with such

stimuli. Clearly such eye tracking methodology could readily be combined with the kinds

of experimental tasks developed for use in the current research program, to provide

converging support for conclusions regarding biased attentional engagement with and

disengagement from emotional material. Future research examining these processes is

therefore likely to benefit from the inclusion of such techniques.

While eye movement research may provide converging evidence to compliment

other sources, such as those obtained from reaction-time data, it should be noted that

measures of eye gaze do not necessarily provide a superior means of assessing attentional

distribution. There is considerable research to suggest that, while visual attention and eye

gaze are closely related, individuals can readily attend to information that is not the

current focus of foveal vision and conversely, that information that is the focus of foveal

223

vision is not always the focus of attention. Indeed, early research by Posner (1980, Posner

et al., 1987) was explicitly designed to assess the cueing of attention in the absence of eye

movements and demonstrated that this could readily be achieved. Therefore, while eye-

gaze data would provide useful, complimentary evidence to the information gained from

reaction time studies, such studies would not be without their own limitations.

The various limitations outlined above serve to identify potential avenues for

future research. In addition to these it will also be the role of further research to

determine the relative reliability of the task designs employed in the present series of

experiments and whether the observed findings will generalise. Should it be the case that

such research demonstrates converging support for the pattern of effects observed in the

current research program, using different sample populations, stimulus materials, and

assessment methodologies, then the clear implication would be that vulnerability to

anxious mood is characterised by biased attentional engagement with the emotional

content of negative as compared to non-negative material.

Concluding Comments

The current research program introduced a number of novel task variants to

address the question of whether the anxiety-linked attentional bias favouring negative

stimuli reflects Biased Attentional Engagement with or Biased Attentional

Disengagement from negative stimuli. The key finding arising from studies which

revealed an anxiety-linked attentional bias was that high trait anxious individuals show

facilitated attentional engagement with the content of negative stimuli. Alternatively, the

present series of studies consistently failed to find evidence to support the presence of an

anxiety-linked attentional disengagement bias. Thus, the present findings provide support

224

for the role of biased attentional engagement with negative information in the patterns of

attentional selectivity that characterise heightened anxiety vulnerability, and identify a

number of potentially fruitful avenues for future inquiry.

225

REFERENCES

Abdel-Khalek, A. M. (1989). The development and validation of an Arabic form of the

STAI: Egyptian results. Personality and Individual Differences, 10, 277-285.

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental

disorders : DSM-IV. Washington, DC: American Psychiatric Press.

Amir, N., Elias, J., Klumpp, H., & Przeworski, A. (2003). Attentional bias to threat in

social phobia: Facilitated processing of threat or difficulty disengaging attention

from threat? Behaviour Research & Therapy, 41, 1325-1335.

Amir, N., Selvina, A., Elias, J., & Rousseau, G. (2002). Manipulation of information

processing bias in anxiety: Malleability of attention and interpretation biases.

Paper presented at the 36th Annual Convention of the Association for

Advancement of Behavior Therapy, Reno, NV.

Apter, A., Horesh, N., Gothelf, D., Zalsman, G., Erlich, Z., Soreni, N., et al. (2003).

Depression and suicidal behavior in adolescent inpatients with obsessive

compulsive disorder. Journal of Affective Disorders, 75, 181-189.

Baddeley, A. (1992). Working memory. Science, 255, 556-559.

Baddeley, A. D. (2001). Is Working Memory Still Working? American Psychologist 56,

851-864.

Barlow, D. H. (2002). Anxiety and its disorders: The nature and treatment of anxiety and

panic (2nd ed.).

Barnes, A. (2008). Anxiety-linked bias in attentional engagement with, and attentional

disengagement from, negative information: the relevance of the attentional

ability/tendency distinction: Unpublished Manuscript. School of Psychology, The

University of Western Australia.

226

Barnes, L. L., Harp, D., & Jung, W. S. (2002). Reliability generalizability of scores on

the Spielberger State-Trait Anxiety Inventory. Educational and Psychological

Measurement, 62, 603-618.

Beck, A. T. (1976). Cognitive therapy and the emotional disorders. Oxford, England:

International Universities Press.

Beck, A. T., & Clark, D. A. (1988). Anxiety and depression: An information processing

perspective. Anxiety Research, 1, 23-36.

Beck, A. T., & Clark, D. A. (1997). An information processing model of anxiety:

Automatic and strategic processes. Behaviour Research and Therapy 35, 49-58.

Beck, A. T., Emery, G., & Greenberg, R. L. (1985). Anxiety disorders and phobias: A

cognitive perspective. New York, NY: Basic Books.

Besner, D., & Swan, M. (1982). Models of lexical access in visual word recognition. The

Quarterly Journal of Experimental Psychology A: Human Experimental

Psychology, 34, 313-325.

Bleiker, E. M., Pouwer, F., van der Ploeg, H. M., Leer, J.-W. H., & Ader, H. J. (2000).

Psychological distress two years after diagnosis of breast cancer: Frequency and

prediction. Patient Education and Counseling, 40, 209-217.

Borden, J. W., & Turner, S. M. (1989). Is panic a unique emotional experience?

Behaviour Research and Therapy, 27, 263-268.

Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 129-148.

Bower, G. H. (1987). Commentary on mood and memory. Behaviour Research &

Therapy, 25, 443-455.

227

Bower, G. H., Lazarus, R., LeDoux, J. E., Panksepp, J., Davidson, R. J., & Ekman, P.

(1994). What is the relation between emotion and memory? In P. Ekman & R.

Davidson (Eds.), The nature of emotion (pp. 301-318). York, NY, US: Oxford

University Press.

Bradley, B. P., Mogg, K., & Williams, R. (1995). Implicit and explicit memory for

emotion-congruent information in clinical depression and anxiety. Behaviour

Research & Therapy, 33, 755-770.

Broadbent, D., & Broadbent, M. (1988). Anxiety and attentional bias: State and trait.

Cognition & Emotion, 2, 165-183.

Bryant, R., Harvey, A., Gordon, E., & Barry, R. (1995). Eye movement and

electrodermal responses to threat stimuli in post-traumatic stress disorder.

International Journal of Psychophysiology, 20, 209-213.

Bryant, R. A., & Harvey, A. G. (1995). Processing threatening information in

posttraumatic stress disorder. Journal of Abnormal Psychology, 104, 537-541.

Bryant, R. A., & Harvey, A. G. (1997). Attentional bias in posttraumatic stress disorder.

Journal of Traumatic Stress, 10, 635-644.

Campbell, L. (2001). An investigation of the causal association between attentional bias

and anxiety vulnerability. Doctorial Dissertation: Departmet of Psychology,

University of Western Australia.

Chambers, J. A., Power, K. G., & Durham, R. C. (2004). The relationship between trait

vulnerability and anxiety and depressive diagnoses at long-term follow-up of

Generalized Anxiety Disorder. Journal of Anxiety Disorders, 18, 587-607.

Clarke, P., MacLeod, C., & Shirazee, N. (2008). Prepared for the worst: Readiness to

acquire threat bias and susceptibility to elevate trait anxiety. Emotion, 8, 47-57.

228

Czarnocka, J., & Slade, P. (2000). Prevalence and predictors of post-traumatic stress

symptoms following childbirth. British Journal of Clinical Psychology, 39, 35-51.

Duncan-Jones, P. (1987). Modelling the aetiology of neurosis: Long-term and short-term

factors. In B. Cooper (Ed.), The epidemiology of psychiatric disorders. (pp. 179-

191). Baltimore, MD, USA: John Hopkins University Press.

Dupuis, G., Perrault, J., Kennedy, E., & Lambany, M. (1991). The diagnostic and

prognostic validity of an instrument for early detection of psychological problems

before coronary bypass surgery. Science et Comportement, 21, 241-257.

Ehlers, A., Margraf, J., Davies, S., & Roth, W. T. (1988). Selective processing of threat

cues in subjects with panic attacks. Cognition & Emotion, 2, 201-219.

Endler, N. S. (1997). Stress, anxiety and coping: The multidimensional interaction model.

Canadian Psychology Psychologie Canadienne, 38, 136-153.

Endler, N. S., Edwards, J. M., Vitelli, R., & Parker, J. D. (1989). Assessment of state and

trait anxiety: Endler Multidimensional Anxiety Scales. Anxiety Research, 2, 1-14.

Estes, W., & Skinner, B. (1941). Some quantitative properties of anxiety. Journal of

Experimental Psychology, 29, 390-400.

Eysenck, M. W. (1992). The nature of anxiety. In A. E. Gale & M. W. E. Eysenck (Eds.),

Handbook of individual differences: Biological perspectives (pp. 157-178).

Oxford, England, UK: John Wiley & Sons.

Eysenck, M. W., & Byrne, A. (1992). Anxiety and susceptibility to distraction.

Personality and Individual Differences, 13, 793-798.

Feldman, L. B., & Moskovljevic, J. (1987). Repetition priming is not purely episodic in

origin. Journal of Experimental Psychology: Learning, Memory, and Cognition,

13, 573-581.

229

Fisher, P. L., & Durham, R. C. (1999). Recovery rates in generalized anxiety disorder

following psychological therapy: An analysis of clinically significant change in

the STAI-T across outcome studies since 1990. Psychological Medicine, 29,

1425-1434.

Fowler, C. A., Napps, S. E., & Feldman, L. (1985). Relations among regular and irregular

morphologically related words in the lexicon as revealed by repetition priming.

Memory & Cognition, 13, 241-255.

Fox, E. (1993). Allocation of visual attention and anxiety. Cognition & Emotion, 7, 207-

215.

Fox, E., Russo, R., Bowles, R., & Dutton, K. (2001). Do threatening stimuli draw or hold

visual attention in subclinical anxiety? Journal of Experimental Psychology:

General, 130, 681-700.

Fox, E., Russo, R., & Dutton, K. (2002). Attentional bias for threat: Evidence for delayed

disengagement from emotional faces. Cognition & Emotion, 16, 355-379.

Giacobbi, Jr., & Weinberg, R. S. (2000). An examination of coping in sport: Individual

trait anxiety differences and situational consistency. The Sport Psychologist, 14,

42-62.

Grenard, J. L., Ames, S. L., Wiers, R. W., Thush, C., Sussman, S., & Stacy, A. W.

(2008). Working memory capacity moderates the predictive effects of drug-

related associations on substance use. Psychology of Addictive Behaviors, 22(3),

426-432.

Heim-Dreger, U., Kohlmann, C.-W., Eschenbeck, H., & Burkhardt, U. (2006).

Attentional biases for threatening faces in children: Vigilant and avoidant

processes. Emotion, 6, 320-325.

230

Hermans, D., Dirikx, T., Vansteenwegenin, D., Baeyens, F., Van den Bergh, O., & Eelen,

P. (2005). Reinstatement of fear responses in human aversive conditioning.

Behaviour Research and Therapy, 43, 533-551.

Hofmann, W., Gschwendner, T., Friese, M., Wiers, R. W., & Schmitt, M. (2008).

Working memory capacity and self-regulatory behavior: Toward an individual

differences perspective on behavior determination by automatic versus controlled

processes. Journal of Personality and Social Psychology, 95(4), 962-977.

Hubert, W., & de Jong-Meyer, R. (1992). Saliva cortisol responses to unpleasant film

stimuli differ between high and low trait anxious subjects. Neuropsychobiology,

25(2), 115-120.

James, C. T. (1975). The role of semantic information in lexical decisions. Journal of

Experimental Psychology: Human Perception and Performance, 1, 130-136.

Jorm, A. (1989). Modifiability of trait anxiety and neuroticism: A meta-analysis of the

literature. Australian and New Zealand Journal of Psychiatry, 23, 21-29.

Joubert, S. A., & Lecours, A. R. (2000). The role of sublexical graphemic processing in

reading. Brain and Language, 72, 1-13.

Karch, S., Jager, L., Karamatskos, E., Graz, C., Stammel, A., Flatz, W., et al. (2008).

Influence of trait anxiety on inhibitory control in alcohol-dependent patients:

Simultaneous acquisition of ERPs and BOLD responses. Journal of Psychiatric

Research, 42(9), 734-745.

Keedwell, P., & Snaith, R. (1996). What do anxiety scales measure? Acta Psychiatrica

Scandinavica, 93, 177-180.

231

Kendler, K. S., Kessler, R. C., Walters, E. E., MacLean, C., Neale, M. C., Heath, A. C., et

al. (1995). Stressful life events, genetic liability, and onset of an episode of major

depression in women. American Journal of Psychiatry, 152, 833-842.

Kerr, B. (1973). Processing demands during mental operations. Memory & Cognition, 1,

401-412.

Klemmer, E., & Snyder, F. (1972). Measurement of time spent communicating. Journal

of Communication, 22, 142-158.

Koster, E. H., Crombez, G., Van Damme, S., Verschuere, B., & De Houwer, J. (2004).

Does Imminent Threat Capture and Hold Attention? Emotion, 4, 312-317.

Koster, E. H., Crombez, G., Verschuere, B., Van Damme, S., & Wiersema, J. R. (2006).

Components of attentional bias to threat in high trait anxiety: Facilitated

engagement, impaired disengagement, and attentional avoidance. Behaviour

Research and Therapy, 44, 1757-1771.

Kroeze, S., & van den Hout, M. A. (2000). Selective attention for cardiac information in

panic patients. Behaviour Research and Therapy, 38, 63-72.

Kucera, H., & Francis, W. N. (1967). Computational analysis of present-day American

English. Providence, Rhode Island Brown University Press.

LaBerge, D. L. (1973). Identification of two components of the time to switch attention.

In S. Kornblum (Ed.), Attention and performance (Vol. 4, pp. 71-85). New York:

Academic Press.

Logie, R. H. (1986). Visuo-spatial processing in working memory. The Quarterly Journal

of Experimental Psychology A: Human Experimental Psychology, 38A, 229-247.

232

MacLeod, C., & Hagan, R. (1992). Individual differences in the selective processing of

threatening information, and emotional responses to a stressful life event.

Behaviour Research & Therapy, 30, 151-161.

MacLeod, C., & Mathews, A. (1988). Anxiety and the allocation of attention to threat.

Quarterly Journal of Experimental Psychology A, 40, 653-670.

MacLeod, C., & Mathews, A. (1991). Biased cognitive operations in anxiety:

Accessibility of information or assignment of processing priorities. Behaviour

Research & Therapy, 29, 599-610.

MacLeod, C., Mathews, A., & Tata, P. (1986). Attentional bias in emotional disorders.

Journal of Abnormal Psychology, 95, 15-20.

MacLeod, C., Rutherford, E., Campbell, L., Ebsworthy, G., & Holker, L. (2002).

Selective attention and emotional vulnerability: Assessing the causal basis of their

association through the experimental manipulation of attentional bias. Journal of

Abnormal Psychology, 111, 107-123.

MacLeod, C., & Rutherford, E. M. (1992). Anxiety and the selective processing of

emotional information: Mediating roles of awareness, trait and state variables, and

personal relevance of stimulus materials. Behaviour Research & Therapy, 30,

479-491.

MacLeod, C. M., & Masson, M. E. (2000). Repetition priming in speeded word reading:

Contributions of perceptual and conceptual processing episodes. Journal of

Memory and Language, 42, 208-228.

Marteau, T. M., & Bekker, H. (1992). The development of a six-item short-form of the

state scale of the Spielberger State-Trait Anxiety Inventory (STAI). British

Journal of Clinical Psychology, 31, 301-306.

233

Martin, M., Williams, R. M., & Clark, D. M. (1991). Does anxiety lead to selective

processing of threat-related information? Behaviour Research and Therapy, 29,

147-160.

Mathews, A., & MacLeod, C. (1985). Selective processing of threat cues in anxiety

states. Behaviour Research & Therapy, 23, 563-569.

Mathews, A., Mogg, K., Kentish, J., & Eysenck, M. (1995). Effect of psychological

treatment on cognitive bias in generalized anxiety disorder. Behaviour Research

& Therapy, 33, 293-303.

Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words:

Evidence of a dependence between retrieval operations. Journal of Experimental

Psychology, 90, 227-234.

Mogg, K., Bradley, B. P., & Hallowell, N. (1994). Attentional bias to threat: Roles of

trait anxiety, stressful events, and awareness. The Quarterly Journal of

Experimental Psychology A: Human Experimental Psychology, 47A, 841-864.

Mogg, K., Bradley, B. P., & Williams, R. (1995). Attentional bias in anxiety and

depression: The role of awareness. British Journal of Clinical Psychology, 34, 17-

36.

Mogg, K., Kentish, J., & Bradley, B. P. (1993). Effects of anxiety and awareness on

colour-identification latencies for emotional words. Behaviour Research and

Therapy, 31, 559-567.

Mogg, K., Mathews, A., & Eysenck, M. (1992). Attentional bias to threat in clinical

anxiety states. Cognition & Emotion, 6, 149-159.

234

Mogg, K., Mathews, A., Bird, C., & Macgregor-Morris, R. (1990). Effects of stress and

anxiety on the processing of threat stimuli. Journal of Personality & Social

Psychology, 59(6), 1230-1237.

Mogg, K., Mathews, A., & Weinman, J. (1989). Selective processing of threat cues in

anxiety states: A replication. Behaviour Research and Therapy, 27, 317-323.

Mogg, K., Millar, N., & Bradley, B. P. (2000). Biases in eye movements to threatening

facial expressions in generalized anxiety disorder and depressive disorder.

Journal of Abnormal Psychology, 109, 695-704.

Morris, C., Bransford, J. D., & Franks, J. J. (1977). Levels of processing versus transfer

appropriate processing. Journal of Verbal Learning & Verbal Behavior, 16, 519-

533.

Musa, C., Lepine, J., Clark, D., Mansell, W., & Ehlers, A. (2003). Selective attention in

social phobia and the moderating effect of a concurrent depressive disorder.

Behaviour Research and Therapy, 41, 1043-1054.

Ohman, A. (1979). Fear relevance, autonomic conditioning and phobias: A laboratory

model. In P. O. Sjoden, S. Bates & W. S. Dockens (Eds.), Trends in behaviour

therapy. New York: Academic.

Pavlov, I. (1934). An attempt at a physiological interpretation of obsessional neurosis and

paranoia. Journal of Mental Science, 80, 187-197.

Pishyar, R., Harris, L. M., & Menzies, R. G. (2004). Attentional bias for words and faces

in social anxiety. Anxiety, Stress & Coping: An International Journal, 17, 23-36.

Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental

Psychology A, 32, 3-25.

235

Posner, M. I., Inhoff, A. W., Friedrich, F. J., & Cohen, A. (1987). Isolating attentional

systems: A cognitive-anatomical analysis. Psychobiology, 15, 107-121.

Quinn, J., & McConnell, J. (1996). Irrelevant pictures in visual working memory. The

Quarterly Journal of Experimental Psychology A: Human Experimental

Psychology, 49a, 200-215.

Rachman, S. (1977). The conditioning theory of fear-acquisition: A critical examination.

Behaviour Research and Therapy, 15, 375-387.

Rachmann, S. (1998). Anxiety. Hove, East Sussex, UK: Psychology Press Ltd.

Rapee, R. M. (1991). Generalized anxiety disorder: A review of clinical features and

theoretical concepts. Clinical Psychology Review, 11, 419-440.

Reiss, S. (1997). Trait anxiety: It's not what you think it is. Journal of Anxiety Disorders,

11, 201-214.

Resick, P. A., & Calhoun, K. S. (2001). Posttraumatic stress disorder. In D. H. Barlow

(Ed.), Clinical handbook of psychological disorders (3rd ed., pp. 60-113). New

York, NY, US: Guilford Press.

Richards, A., & French, C. C. (1992). An anxiety-related bias in semantic activation

when processing threat/neutral homographs. Quarterly Journal of Experimental

Psychology A, 45A, 503-525.

Richards, A., French, C. C., Johnson, W., Naparstek, J., & Williams, J. (1992). Effects of

mood manipulation and anxiety on performance of an emotional Stroop task.

British Journal of Psychology, 83, 479-491.

Robbins, T., Anderson, E., Barker, D., Bradley, A., Fearnyhough, C., Henson, R., et al.

(1996). Working memory in chess. Memory & Cognition, 24, 83-93.

236

Rutherford, E. M., MacLeod, C., & Campbell, L. W. (2004). Negative selectivity effects

and emotional selectivity effects in anxiety: Differential attentional correlates of

state and trait variables. Cognition & Emotion, 18, 711-720.

Salame, P., & Baddeley, A. D. (1982). Disruption of short-term memory by unattended

speech: Implications for the structure of working memory. Journal of Verbal

Learning & Verbal Behavior, 21, 150-164.

Santesso, D. L., Meuret, A. E., Hofmann, S. G., Mueller, E. M., Ratner, K. G., Roesch, E.

B., et al. (2008). Electrophysiological correlates of spatial orienting towards angry

faces: A source localization study. Neuropsychologia, 46, 1338-1348.

Scarborough, D. L., Cortese, C., & Scarborough, H. S. (1977). Frequency and repetition

effects in lexical memory. Journal of Experimental Psychology: Human

Perception and Performance, 3, 1-17.

Scarrabelotti, M. B., Duck, J. M., & Dickerson, M. M. (1995). Individual differences in

obsessive-compulsive behaviour: The role of the Eysenckian dimensions and

appraisals of responsibility. Personality and Individual Differences, 18, 413-421.

Schvaneveldt, R. W., Meyer, D. E., & Becker, C. A. (1976). Lexical ambiguity, semantic

context, and visual word recognition. Journal of Experimental Psychology:

Human Perception and Performance, 2, 243-256.

Shalev, A. Y., Freedman, S., Peri, T., Brandes, D., & Sahar, T. (1997). Predicting PTSD

in trauma survivors: Prospective evaluation of self-report and clinician-

administered instruments. British Journal of Psychiatry, 170, 558-564.

Slamecka, N. J. (1968). A Methodological Analysis of Shift Paradigms in Human

Discrimination Learning. Psychological Bulletin, 69, 423-438.

237

Spector, I., Pecknold, J. C., & Libman, E. (2003). Selective attentional bias related to the

noticeability aspect of anxiety symptoms in generalized social phobia. Journal of

Anxiety Disorders, 17, 517-531.

Spielberger, C., Gorsuch, R., Lushene, R., Vagg, P., & Jacobs, G. (1983). Manual for the

State-Trait Anxiety Inventory STAI (Form Y): Self-evaluation questionnaire. Palo

Alto: Ca: Consulting Psychologist Press.

Spielberger, C. D. (1985). Assessment of state and trait anxiety: Conceptual and

methodological issues. Southern Psychologist 6-16, 2, 6-16.

Strain, E., Patterson, K., & Seidenberg, M. S. (1995). Semantic effects in single-word

naming. Journal of Experimental Psychology: Learning, Memory, and Cognition,

21, 1140-1154.

Stroop, J. (1935). Studies of interference in serial verbal reactions. Journal of

Experimental Psychology, 18, 643-662.

Stroop, J. (1938). Factors affecting speed in serial verbal reactions. Psychological

Monographs, 50, 38-48.

Sutker, P. B., Bugg, F., & Allain, A. N. (1991). Psychometric prediction of PTSD among

POW survivors. Psychological Assessment, 3, 105-110.

Suzuki, H., Hashimoto, Y., & Ishii, K. (1997). Measuring information behavior: A time

budget survey in Japan. Social Indicators Research, 42, 151-169.

Tambs, K. (1991). Transmission of symptoms of anxiety and depression in nuclear

families. Journal of Affective Disorders, 21, 117-126.

Tata, P. R., Leibowitz, J. A., Prunty, M. J., Cameron, M., & Pickering, A. D. (1996).

Attentional bias in Obsessional Compulsive Disorder. Behaviour Research and

Therapy, 34, 53-60.

238

Thush, C., Wiers, R. W., Ames, S. L., Grenard, J. L., Sussman, S., & Stacy, A. W.

(2008). Interactions between implicit and explicit cognition and working memory

capacity in the prediction of alcohol use in at-risk adolescents. Drug and Alcohol

Dependence, 94(1-3), 116-124.

Tucha, O., Prell, S., Mecklinger, L., Bormann-Kischkel, C., Kubber, S., Linder, M., et al.

(2006). Effects of methylphenidate on multiple components of attention in

children with attention deficit hyperactivity disorder. Psychopharmacology, 185,

315-326.

Vasey, M. W., Hazen, R., & Schmitd, N. B. (2002). Attentional retraining for chronic

worry and GAD. Paper presented at the 36th Annual Convention of the

Association for Advancement of Behavior Therapy, Reno, NV.

Watts, F. N., McKenna, F. P., Sharrock, R., & Trezise, L. (1986). Colour naming of

phobia-related words. British Journal of Psychology, 77, 97-108.

Williams, J., Mathews, A., & MacLeod, C. (1996). The emotional Stroop task and

psychopathology. Psychological Bulletin, 120, 3-24.

Williams, J. M. G., Watts, F. N., MacLeod, C., & Mathews, A. (1988). Cognitive

psychology and emotional disorders. Chichester: Wiley.

Williams, J. M. G., Watts, F. N., MacLeod, C., & Mathews, A. (1997). Cognitive

psychology and emotional disorders (2nd ed.). Chichester: Wiley.

Wilson, E., & MacLeod, C. (2003). Contrasting two accounts of anxiety-linked

attentional bias: Selective attention to varying levels of stimulus threat intensity.

Journal of Abnormal Psychology, 112, 212-218.

Wolff, J. L. (1967). Concept-Shift and Discrimination-Reversal Learning in Humans.

Psychological Bulletin, 68, 369-408.

239

Wolpe, J. (1958). Psychotherapy by reciprocal inhebition. Stanford: Stanford University

Press.

Wolpe, J., & Rachman, S. (1960). Psychoanalytic "evidence": A critique based on Freud's

case of little Hans. Journal of Nervous and Mental Disease, 131, 135-148.

Yiend, J., & Mathews, A. (2001). Anxiety and attention to threatening pictures. The

Quarterly Journal of Experimental Psychology A: Human Experimental

Psychology, 54A, 665-681.

240

APPENDIX A

STIMULUS SET USED IN EXPERIMENT 1: NEGATIVE AND NON-NEGATIVE

WORDS WITM MEAN NEGATIVITY AND RELEVANCE RATINGS WITH LENGTH

MATCHED NON-WORDS

Negative Words

Word Non-Word Pair Mean Relevance Mean Valence

AGGRESSIVE ZWYGPRNBLZ 2.57 2.29

ALONE XZBRT 3.79 1.93

ATTACKS RMNZKPW 2 1.79

BRUTAL VKWRZB 1.21 1.64

CANCER ZRYWKB 2.86 1.57

CONDEMN OKWBMNZ 2 1.79

CRISIS JGWBNK 2.21 2.07

CRITICISE YRBWKLZXD 3.43 2.21

CRUEL LFGPQ 2.71 2

DAMAGE QTNPRB 1.71 2.57

DANGER SWBZGR 3.36 1.85

DEATHBED KVWBGMDP 2.5 1.5

DESPISED HNPWKDNF 2.14 1.86

EMERGENCY YLZGWKRQP 2.57 2.14

EVIL MGBN 1.5 1.64

FAIL NQZF 4.36 2.21

FATAL FJSKW 2.21 1.64

FEAR PZWD 2.36 2.07

FEARFUL GMJBZQR 2.07 2.14

GRAVE TBWGR 1.5 2.14

GRIEVING BZWRNMQV 1.93 1.93

HOSTILE TJKBWMF 3.36 2.14

HUMILIATED JBMGZVRDFP 2.86 1.57

HURT OBZF 3.71 2.29

IGNORED WPVGBFN 4.07 2.14

241

Negative Words Continued

LOATHED VQPWXZB 2.14 2

LOST ZUMB 3 1.93

MISERY FXCPZY 2.86 2.14

PAIN VTST 2.93 2.21

PETRIFIED QXZPVRFYB 1.93 2.21

POWERLESS SZPFKQMWN 4.36 2.07

PREJUDICE XZRBWNVHY 3.86 1.79

REJECTED LMFVKPDG 4.07 1.93

RIDICULE MFPWJGTN 3.07 2.07

SHAMEFUL DKGBMZRL 2.79 2.14

SORROW WBXYMZ 2.36 2.07

STRANGLED BFCWHNZLD 2.29 1.57

STRESS YHDCBL 5.57 2.07

SUFFER KXBZWQ 3.07 1.85

SUFFOCATING PFZDBQWZUNF 2.43 1.64

SUICIDE KDINGFP 2.29 1.07

TERROR PVNXDJ 2.21 2

THREAT CJRDQN 2.14 2.07

TORMENTED SPBQHMVKJ 2.21 1.71

TRAGEDY WZYQVMP 1.93 1.64

TRAUMA HVPBQR 1.86 2.07

UNHAPPY RZQBMVH 3.64 2.21

USELESS ZFTPBMQ 2.86 1.86

242

Neutral Words

Word Non-Word Pair Mean Relevance Mean Valence

ILLUSTRATE YOBFHQMZCL 0.5 4.21

WOMEN NFPWH 2.5 4.29

PHYSICS SWPGNFV 0.71 3.14

SPONGE NPKWRT 0.21 4.21

SADDLE QSMVXR 0.64 4.07

HOPPING TZXVQMF 0.5 4.21

PRODUCE CMRSKNM 0.57 4.21

DELICIOUS GFQDLWZTN 1.57 6.29

ONION XHDVM 0.07 4.14

CAMPUS DPHQMF 1.71 4.21

LEAGUE ZWRHFJ 0.36 4.14

SOFTNER JHCBTSYM 0.14 4.36

TOMATOES LXRMSQBG 0.79 4.14

LISTENING VBDWGSMLH 3.71 5

HILL FBHS 0.5 4.29

EARS RQBW 0.71 4.07

CROWN CVNPX 0.79 4.57

NOTE SZMH 0.5 4.14

POSTURE DFBMUXG 1.93 4

STEMS MZXVP 0.07 4.36

HALLMARK NRVZWJDS 0.14 4.21

ROLLING TVBZHFX 0.21 4.14

WATERPROOF BQHFXRTMWP 0.21 4.21

CORE GPMF 0.07 4.21

LIGHTED NWZHQVY 0.57 4.57

FILTERS WPRZHDC 0 4

READ YCLQ 1.64 4.29

ANCHOR LXBNJF 0.29 4

LAWS ZRQF 1.93 4.15

243

Neutral Words Continued

JUNCTURES YJGKQSZMW 0.43 4

MULTITUDE WTCZMPFHN 0.79 4

FRAMEWORK PZLFMQNTW 0.5 4.14

QUANTITY FZRHQPNQ 0.43 4.21

BANNISTER XFHBZNPVT 0.14 4.07

LEAPFROG HZLFWMBX 0.14 4.36

CHEESE TPFQZM 0.21 4.21

SIGNATURE RQSZMWVPF 0.07 4

CITIES JXFZPW 1.07 4.29

PARKED MDQBVH 0.29 4.07

CONSTITUENT SZBWQFMHTPG 0.29 4.14

SUMMERS OSWUTVJ 1.36 5.36

PUPILS GZMFLT 0.57 4

VARIED NZLBYP 0 4.43

MYTHOLOGY BPZRQMFTW 0.64 4.5

REQUEST KWFPMDR 1.07 4.5

ENJOIN CPDVLT 0 4.21

BRIDGES JTMQSPF 0.79 4.29

FLOWING GZRNXQT 0.57 4.86

244

APPENDIX B

REVISED STIMULUS SET: NEGATIVE AND NON-NEGATIVE WORDS WITH LENGTH

MATCHED GRAPHEMICALLY LEGITIMATE NON-WORDS USED IN EXPERIMENT 2

Negative/Non-Word Pairs Non-Negative/Non-Word Pairs

AGGRESSIVE GRAVASEGIS ANCHOR RHANCO

ALONE NELOA BANNISTER NISTRABEN

ATTACKS SKACTAT BRIDGES SRIBEOG

BRUTAL TARLUB CAMPUS PUCSAM

CANCER ARCNEC CHEESE ESHECE

CONDEMN DONNCEM CITIES STICIE

CRISIS SCIRIS CONSTITUENT STINOCTUNET

CRITICIZE TIRCISECI CORE ECRO

CRUEL ERLUC CROWN WROCN

DAMAGE MAGEDA DELICIOUS ILIDESUCO

DANGER GADRNE EARS RESA

DEATHBED TEDDAHEB ENJOIN JOENIN

DESPISED SPEDDISE FILTERS STRILFE

EMERGENCY GRECYNEME FLOWING GIFLONW

EVIL ILVE FRAMEWORK WAFREMROK

FAIL LAFI HALLMARK KRAHLMAL

FATAL TAFLA HILL LIHL

FEAR ERAF HOPPING PHINPOG

FEARFUL RELAFUF ILLUSTRATE LIRTALUTES

GRAVE AVERG JUNCTURES JENCURTUS

GRIEVING VEIGNIRG LAWS ASWL

HOSTILE LISHOTE LEAGUE AGULEE

HUMILIATED TUMHILIADE LEAPFROG GROFPALE

HURT TRUH LIGHTED DEGHILT

IGNORED ROGEDIN LISTENING TILNENGIS

LOATHED DOTLAEH MULTITUDE MITTULUDE

245

Negative/Non-Word Pairs Continued Non-Negative/Non-Word Pairs Continued

LOST SOTL MYTHOLOGY GHOMYLOTY

MISERY IRMSEY NOTE ENOT

PAIN NAPI ONION NOINO

PETRIFIED IFIPETRED PARKED KRADEP

POWERLESS SELWROSEP PHYSICS SHYCIPS

PREJUDICE UDREJICPE POSTURE RUSPOTE

REJECTED JERTEDCE PRODUCE CREPUDO

RIDICULE LUCIRDIE PUPILS SLUPIP

SHAMEFUL MAFESHLU QUANTITY NATIQUYT

SORROW WROSOR READ ERDA

STRANGLED DARSTNELG REQUEST QUETRES

STRESS ASESSR ROLLING LIRGNOL

SUFFER FRUSFE SADDLE DLASED

SUFFOCATING OFSUCTAFING SIGNATURE NAGITUSER

SUICIDE DUISICE SOFTENER ROSFNETE

TERROR RERTRO SPONGE PEGONS

THREAT ERTATH STEMS MESTS

TORMENTED MERONTTED SUMMERS MEMSRUS

TRAGEDY GARYDET TOMATOES MOOTEAST

TRAUMA AMURTA VARIED DRAIVE

UNHAPPY PHAYNUP WATERPROOF FOWPRORETA

USELESS SUSLESE WOMEN MEWNO

246

APPENDIX C

ADDITIONAL NON-WORD/NON-WORD AND WORD/WORD STIMULI USED IN

EXPERIMENT 3

Non-Word/Non-Word Pairs Word/Word Pairs

ANOTEQUI PSYHOMNY ABDOMEN COMPOSE

BLERMUP GISTNAC ABOARD PARADE

BONADEM SOOPMEC ALLOCATION REFLECTING

CHAMSUTE TILLCOYA ALLOTMENT SELECTION

CINIPC MELUHI BOAT WINE

CLUHN ESADL BRANCH POLAND

CRABNH NADLOP BRASS LODGE

DITHR LATEB CLIMATE TANGENT

DRIVAYEN HOBKODAN COTTAGE OPTICAL

EGTA HAWS DRUMMING GENERATE

ESEWP WRAST DUPLICATE RATIONALE

GARCNIT NOBCIME EQUATION SYMPHONY

GENHELTN REEMPUFD FACTOR ASKING

GNAPKIC GNALDRI FOAM ATOM

HISTINH NETILGM GATE WASH

IDEW MARF GRACED UMPIRE

LEMTIY HEPWEN GYMNASTIC ENTOURAGE

LOBMAVE RUNTEEV HOLD DATA

LODH TAAD INSIGHT MELTING

MEERNTAPY RIGOTURGE INSTRUCT FOOTNOTE

MOAF TAMO INTRODUCE SCULPTURE

NETTMOLAL OLEESNICT JACKET NAMELY

NOPEED MEDARC LANTERN VISITOR

NUGRUMIM REENEGAT LENGTHEN PERFUMED

ONCORENI LUPTCUSE LUNCH LEADS

OTBA NIWE MOVABLE VENTURE

247

Non-Word/Non-Word Pairs Continued Word/Word Pairs Continued

PALECUDIT LARITANOE MUSTACHE LOCALITY

RACTOF GISKAN OPENED MARKED

REGCAD REPUMI PACKING DARLING

RENNLAT IRIVSOT PARAPHRASE COLLOQUIAL

RESAPPARAH QUALOOLCIL PASS KING

RODABA REDAPA PASSAGE SPEAKER

SAPEGAS RASEPKE PICNIC HELIUM

SBSRA EDGLO PLUMBER CASTING

SOTALP MUSEDM POSTAL SUMMED

SPEERDOSREC GREALNUTRAC PREDECESSOR RECTANGULAR

SPSA GINK PRETTY SEASON

TACALOIONL GNERECLIFT PROTOTYPE INCLUSION

TAJECK NYEALM QUOTATION LETTERING

TAMSICGNY TEENOARGT REPAYMENT OUTRIGGER

TILEMAC TENANGT SMOOTH GOLDEN

TOGCATE TOPILAC SUBTLE JERSEY

TOOQUINOA TEELTGRIN SWEEP STRAW

TOSOHM NELDOG THIRD TABLE

TREPTY OSSNEA TIMELY NEPHEW

TROOPYEPT CONNISULI TRACING COMBINE

TUSLEB SYJEER VINEYARD HANDBOOK

URSTTCIN TENOOTOF WIDE FARM

248

APPENDIX D

WORD STIMULI, PART OF SPEECH CLASSIFICATION CATEGORY AND CORRECT

RESPONSES USED IN EXPERIMENT 4

Negative Words

Word

Part of speech

category 1 Correct Answer

Part of speech

category 2 Correct Answer

AGGRESSIVE Verb No Noun No

ALONE Noun No Adjective Yes

ATTACKS Verb Yes Noun Yes

BRUTAL Noun No Verb No

CANCER Verb No Noun Yes

CONDEMN Verb Yes Noun No

CRISIS Verb No Noun Yes

CRITICISE Verb Yes Noun No

CRUEL Noun No Verb No

DAMAGE Verb No Noun Yes

DANGER Noun Yes Verb No

DEATHBED Noun Yes Adjective Yes

DESPISED Noun No Adjective No

EMERGENCY Adjective Yes Noun Yes

EVIL Verb No Noun No

FAIL Noun No Verb Yes

FATAL Adjective Yes Noun Yes

FEAR Noun Yes Adjective No

FEARFUL Verb No Adjective Yes

GRAVE Verb No Adjective Yes

GRIEVING Noun No Adjective No

HOSTILE Noun Yes Adjective Yes

HUMILIATED Verb Yes Noun No

HURT Noun Yes Verb Yes

249

Negative Words Continued

Word

Part of speech

category 1 Correct Answer

Part of speech

category 2 Correct Answer

IGNORED Noun Yes Adjective No

LOATHED Noun No Verb Yes

LOST Adjective Yes Verb Yes

MISERY Verb No Noun Yes

PAIN Noun Yes Verb No

PETRIFIED Verb Yes Noun No

POWERLESS Verb No Noun No

PREJUDICE Verb No Noun Yes

REJECTED Noun Yes Verb No

RIDICULE Verb Yes Noun Yes

SHAMEFUL Verb No Adjective Yes

SORROW Noun Yes Verb No

STRANGLED Noun No Verb Yes

STRESS Noun Yes Verb No

SUFFER Verb Yes Noun No

SUFFOCATING Verb Yes Noun No

SUICIDE Noun Yes Verb No

TERROR Verb No Noun Yes

THREAT Noun Yes Verb Yes

TORMENTED Verb No Adjective No

TRAGEDY Verb No Noun Yes

TRAUMA Noun Yes Verb No

UNHAPPY Noun No Verb No

USELESS Verb No Adjective Yes

250

Non-Negative Words

Word

Part of speech

category 1 Correct Answer

Part of speech

category 2 Correct Answer

ILLUSTRATE Adjective No Noun No

WOMEN Noun Yes Verb No

PHYSICS Noun Yes Verb No

SPONGE Adjective No Verb No

SADDLE Noun Yes Verb No

HOPPING Verb Yes Noun No

PRODUCE Verb Yes Noun Yes

DELICIOUS Verb No Adjective Yes

ONION Noun Yes Verb No

CAMPUS Verb No Adjective No

LEAGUE Verb No Noun Yes

SOFTNER Verb No Noun Yes

TOMATOES Verb No Noun Yes

LISTENING Verb Yes Noun No

HILL Adjective No Verb No

EARS Verb No Noun Yes

CROWN Noun Yes Verb No

NOTE Noun Yes Verb No

POSTURE Verb Yes Noun Yes

STEMS Verb No Noun Yes

HALLMARK Verb No Noun Yes

ROLLING Adjective Yes Verb Yes

WATERPROOF Verb No Adjective Yes

CORE Noun Yes Adjective Yes

LIGHTED Noun Yes Verb Yes

FILTERS Noun Yes Verb No

READ Noun No Verb Yes

251

Non-Negative Words Continued

Word

Part of speech

category 1 Correct Answer

Part of speech

category 2 Correct Answer

ANCHOR Verb No Noun Yes

LAWS Verb No Adjective No

JUNCTURES Verb No Noun Yes

MULTITUDE Verb No Adjective No

FRAMEWORK Noun Yes Verb No

QUANTITY Noun Yes Verb No

BANNISTER Noun Yes Verb No

LEAPFROG Noun Yes Verb No

CHEESE Noun Yes Verb No

SIGNATURE Noun Yes Verb No

CITIES Verb No Noun Yes

PARKED Noun No Adjective No

CONSTITUENT Adjective Yes Noun Yes

SUMMERS Verb No Noun Yes

PUPILS Verb No Noun Yes

VARIED Verb No Adjective Yes

MYTHOLOGY Verb No Adjective No

REQUEST Verb Yes Noun Yes

ENJOIN Verb Yes Noun No

BRIDGES Verb No Noun Yes

FLOWING Verb Yes Noun Yes