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Anxiety, Stress, & Coping: AnInternational JournalPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/gasc20
Attentional bias toward personallyrelevant health-threat wordsHanjoo Leea, Jennifer E. Turkela, Stuart P. Cottera, Jennifer M.Millikena, Jesse Cougleb, Amy R. Goetza & Alexandra M. Lesnicka
a Department of Psychology, University of Wisconsin-Milwaukee,Milwaukee, WI, USAb Department of Psychology, Florida State University, Tallahassee,FL, USAAccepted author version posted online: 19 Jul 2012.Publishedonline: 13 Aug 2012.
To cite this article: Hanjoo Lee, Jennifer E. Turkel, Stuart P. Cotter, Jennifer M. Milliken, JesseCougle, Amy R. Goetz & Alexandra M. Lesnick (2013) Attentional bias toward personally relevanthealth-threat words, Anxiety, Stress, & Coping: An International Journal, 26:5, 493-507, DOI:10.1080/10615806.2012.713474
To link to this article: http://dx.doi.org/10.1080/10615806.2012.713474
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Attentional bias toward personally relevant health-threat words
Hanjoo Leea*, Jennifer E. Turkela, Stuart P. Cottera, Jennifer M. Millikena,
Jesse Cougleb, Amy R. Goetza and Alexandra M. Lesnicka
aDepartment of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA;bDepartment of Psychology, Florida State University, Tallahassee, FL, USA
(Received 20 December 2011; final version received 16 July 2012)
Conflicting findings have emerged regarding the presence of attentional biases(ABs) in health anxiety, probably due to methodological limitations in the stimuliused in cognitive tasks and the assessment of health anxiety-relevant factors. Thecurrent study sought to examine ABs toward health-related threats usingidiographically chosen health-threat words in a non-clinical sample. A modifieddot-probe task using idiographically selected health-threat words was adminis-tered to an undergraduate sample. Self-report measures were administered toassess somatic, cognitive, and behavioral aspects of health anxiety, in addition toassessing negative affect, anxiety sensitivity, and experience of actual medicalconditions. Results showed that behavioral and somatic aspects of health anxietywere significantly associated with AB toward personally relevant threat words,even after controlling for negative affect, anxiety sensitivity, and experience ofactual medical conditions. Additional analyses revealed that these biases reflecteddifficulty disengaging attention from threat rather than a facilitated detection ofthreat. In contrast, illness-related cognitions were found to be unrelated to ABs.These findings suggest an association between threat-related ABs and excessivehealth-care seeking efforts.
Keywords: health anxiety; hypochondriasis; attentional bias; attentional disen-gagement; dot-probe task; health-care seeking
Introduction
The core feature of hypochondriasis (HC) is an intense preoccupation with the
irrational belief that one has, or is in danger of developing, a serious medical illness
(American Psychiatric Association, 2000). Individuals with HC experience excessive
worries or concerns about their suspected physical illness and engage in compulsive
self-assessment of health, reassurance seeking, and excessive utilization of medical
resources, although such strenuous efforts are highly unlikely to be successful
(Deacon, Lickel, & Abramowitz, 2008). Currently, HC is classified as a somatoform
disorder (American Psychiatric Association, 2000); However, several authors
(Deacon & Abramowitz, 2008; Noyes, 2001; Olatunji et al., 2009) have proposed
that HC may be better conceptualized as severe health anxiety due to a number of
shared clinical features and elevated comorbidity between HC and anxiety disorders,
particularly panic disorder and obsessive-compulsive disorder. One recent study
found that patients with HC display elevated cognitive biases such as attentional
*Corresponding author. Email: [email protected]
Anxiety, Stress, & Coping, 2013
Vol. 26, No. 5, 493�507, http://dx.doi.org/10.1080/10615806.2012.713474
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vigilance to bodily symptoms, which is central to other anxiety disorders (Deacon &
Abramowitz, 2008).
Similar to cognitive models of anxiety disorders (e.g., Clark, 1986; Salkovskis,
1985), current cognitive-behavioral conceptualizations of HC (Abramowitz,
Schwartz, & Whiteside, 2002; Warwick & Salkovskis, 1990) propose a debilitating
self-sustaining cycle of pathological health anxiety. Individuals with heightenedhealth anxiety are thought to hold dysfunctional beliefs about their bodily symptoms
and possible illnesses. Such beliefs can result in hypervigilance toward (benign)
bodily symptoms and amplified somatosensory perceptions, which may increase
illness-related catastrophic cognitions and strenuous efforts to use safety-seeking
behaviors. The current model posits that cognitive biases (e.g., distorted perceptions
of bodily sensations, vigilant attention toward physical cues, enhanced memory of
illness-related information) are at the center of various mechanisms that maintain
pathological health anxiety. Particularly, attentional vigilance toward potential
health threats appears to be a maintaining factor that may lead an individual to
selectively process negative aspects of health-related information and develop
irrational illness-related beliefs. Attentional biases (ABs) toward threatening
information have been well-documented in emotional disorders (MacLeod, Math-
ews, & Tata, 1986; Williams, Mathews, & MacLeod, 1996), and health anxiety may
not be an exception.
Only a handful of experimental studies have examined AB associated with healthanxiety, and existing data are mixed (see Marcus, Gurley, Marchi, & Bauer, 2007
for a review). Individuals with heightened health anxiety were found to show
greater interference effects toward illness-related stimuli on modified Stroop tasks
(Karademas, Christopoulou, Dimostheni, & Pavlu, 2008; Owens, Asmundson,
Hadjistavropoulos, & Owens, 2004), which suggests that these individuals are less
efficient in preventing attentional interference by task-irrelevant health-threat
information. Another study found that during a bogus pain-delivery task, individuals
with health anxiety showed greater attention toward bodily symptoms, whereas no
such AB was observed among those low in health anxiety (Pauli, Schwenzer, Brody,
& Rau, 1993). However, other studies have been unsuccessful in providing evidence
for AB in health anxiety. For example, Lees, Mogg, and Bradley (2003) found that
those high vs. low in health anxiety did not differ in performance on a visual probe
task, although the magnitude of AB was shown to be greater among individuals with
elevated anxiety sensitivity. Similarly, Lecci and Cohen (2002) failed to find
significant emotional Stroop interference effects unless participants’ illness concerns
were activated (i.e., participants were led to believe that their blood pressure was
‘‘dangerously high’’). Taken together, AB in health anxiety has not been demon-strated consistently across studies, although attentional vigilance is one of the core
components of the current cognitive model of health anxiety (Abramowitz et al.,
2002; Warwick & Salkovskis, 1990). Therefore, AB research is an important step
toward elucidating its underlying cognitive features and guiding the development of
effective cognitive interventions for health anxiety.
There are a few methodological issues that are important to consider to
improving the design of AB research in health anxiety. First, given the vast range
of potential health concerns across individuals, cognitive tasks that present generic
health threats may not be sufficiently sensitive to detect biased attentional processing
(e.g., an individual with concerns over having a heart attack may not display
494 H. Lee et al.
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attentional vigilance toward threatening information related to cancer). It is
important to assess AB toward idiographically chosen health-threat words/pictures
that are relevant to one’s own health concerns. Second, most existing studies (e.g.,
Karademas et al., 2008; Lees et al., 2003; Owens et al., 2004) assess the severity of
health anxiety using measures that are largely focused on cognitive aspects of health
anxiety (e.g., Illness Attitude Scale, Kellner, 1986; Health Anxiety Inventory,
Salkovskis, Rimes, Warwick, & Clark, 2002) rather than instruments that assess
other dimensions of the condition including behavioral (e.g., efforts to seek health-
care resources or illness-related information) and somatic symptoms (e.g., com-
plaints of physical symptoms including palpitations, shortness of breath and chest
pain). Including measures that address behavioral, somatic, and cognitive dimen-
sions of health anxiety would allow investigators to examine how various aspects of
health anxiety are linked to attentional vigilance toward threatening health
information.
The current study sought to examine the association between health anxiety and
attentional vigilance, using a well-established cognitive experimental paradigm (i.e.,
dot-probe task) that has been highly successful in revealing ABs in emotional
disorders (MacLeod et al., 1986). To this end, we generated an individually tailored
dot-probe task using personally relevant health-threat words for each participant, and
assessed how such cognitive biases would be associated with various factors related
to health anxiety. We hypothesized that the severity of health anxiety assessed in
somatic (i.e., current physical symptoms), cognitive (i.e., illness-related negative
cognitions), and behavioral (i.e., efforts toward health-care utilization and informa-
tion-seeking) aspects would be significantly associated with the magnitude of
attentional vigilance toward idiographically chosen health-threats. In addition, we
sought to explore the associations between the three domains of health anxiety and
AB to threatening health information.
Methods
Participants
Participants were recruited from undergraduate psychology classes at a large mid-
western university. We sought to obtain a study sample characterized by a range of
health anxiety scores on the Short Health Anxiety Inventory (SHAI; Salkovskis
et al., 2002). To achieve this recruitment goal, 326 students were screened and 40
students were randomly selected from each of the four quartiles on total scores of the
SHAI and invited to participate in the current study. Of the 160 individuals invited to
the study, a total of 56 responded and participated in return for partial course credit.
Survey responders were evenly distributed across the four quartiles. A one-sample
Kolmogorov-Smirnov test confirmed that SHAI Total scores were normally
distributed in the current sample (Kolomogorov-Smirnov z�.77, p�.59;
Mean�37.82, SD�10.31, Range�19�65). Our sample included 20 males and 36
females (64.3%). Their mean age was 21.16 (SD�2.95) and there were no significant
gender differences. They reported the following racial/ethnic characteristics (with
multiple selections allowed): Caucasian (80.4%), Asian (12.5%), African-American/
Black (10.7%), Hispanic (5.4%), and Pacific Islander (1.8%).
Anxiety, Stress, & Coping 495
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Measures
Short Health Anxiety Inventory
The SHAI is a widely-used self-report measure of health anxiety, consisting of 18
items that assess negative cognitions associated with health anxiety such as perceived
likelihood of illness and negative consequences of illness (Abramowitz, Deacon, &
Valentiner, 2007; Salkovskis et al., 2002). Each item presents four statements that
vary in severity (e.g., 0: I do not worry about my health � 3: I spend most of my time
worrying about my health), and respondents are asked to select one of the four
statements that best describes their feelings over the past week. The SHAI has
adequate internal consistency (Cronbach’s a�.86) and test�retest reliability
(Abramowitz et al., 2007; Salkovskis et al., 2002). The measure is an abbreviated
version of the 64-item Health Anxiety Inventory (HAI; Salkovskis et al., 2002). The
HAI was administered to participants to examine the relevancy of the author-
constructed Health Care Seeking and Utilization Scale (see below).
Patient Health Questionnaire � Somatoform Module (PHQ)
The PHQ is a self-report instrument designed to be used in primary care settings to
diagnose common DSM-IV disorders (Somatoform; Spitzer, Kroenke, & Williams,
1999). The PHQ screens for five groups of disorders frequently present in primary care
settings: Depression, Anxiety, Alcohol Use, Somatoform, and Eating Disorders. The
PHQ showed acceptable internal consistency (Cronbach’s a�.79) among patients who
display moderate levels of somatization (Interian, Allen, Gara, Escobar, & Diaz-
Martinez, 2006). The PHQ-Somatoform section assesses 15 physical symptoms in the
past month on a 3-point scale (0�not bothered at all, 1�bothered a little, 2�bothered
a lot). We used the PHQ-Somatoform module to examine the severity of various
physical complaints experienced over the previous month.
In Section 2 of the PHQ, we administered a list of physical illnesses to examine
the presence of actual medical conditions participants have experienced in the past or
currently (i.e., last four weeks). The list included seven serious illnesses (i.e., heart
disease, respiratory disease, active ulcer, kidney disease, epilepsy, stroke, and head
injury). Additionally, participants were allowed to indicate up to three medical
conditions that were not included in the list, which resulted in reports of fiveadditional medical conditions (i.e., liver disease, cancer, sickle cell disease, spine
problem, and anemia). Overall, 28.5% of the current sample indicated that they have
experienced at least one of these medical conditions. Given the chronic nature of
these conditions, we produced a lifetime prevalence-based index that indicates the
number of actual medical conditions they have experienced (i.e., PHQ-Medical
Conditions).
Health Care Seeking and Utilization Scale (HCSUS)
This is an author-constructed 7-item self-report measure designed to measure
behavioral aspects of health anxiety. The seven items assessed the level of efforts
made to seek and utilize health-care resources over the past month including: (1) the
number of times the individual made a phone call to health-care professionals
(e.g., physician, nurse, counselor), (2) the number of times the individual visited
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non-emergent health care settings (e.g., clinic, hospital, student health center), (3) the
number of times the individual visited an emergency room, (4) the number of
physicians the individual has seen, (5) the number of prescriptions the individual has
received, (6) the number of days the individual has received inpatient treatment, and
(7) the number of hours per week the individual spent checking and collecting
information on his/her potential or diagnosed illness on the Internet. Given the
unstandardized format of the response scales across the seven items, we generated a
summary index by averaging z-scores generated from each item. In the current
sample, internal consistency (Cronbach’s a) for the seven items was .77.
To demonstrate the utility of the HCSUS as a measure of behavioral health
anxiety symptoms, we examined its association with (1) the 64-item HAI and its
relevant subscales (i.e., Reassurance-seeking and Avoidance), and (2) the PHQ-
Medical Conditions index. We found that the HCSUS z-scores were significantly
associated with the HAI-Reassurance subscale (r�.39, pB.005) and HAI-Total
score (r�.39, pB.005), but were not associated with the HAI-Avoidance subscale
(r�.02, p�.91). More importantly, the HCSUS z-scores were not significantly
associated with the PHQ-Medical Conditions Index (r�.22, p�.10). These data
indicate that elevated scores on the HCSUS reflect health anxiety-driven reassurance
seeking and preoccupation, rather than proper health-care seeking efforts propor-
tionate to actual medical conditions. Compared to other measures of health-related
behaviors (e.g., Illness Attitudes Scale � Kellner, 1986; Medical Utilization
Questionnaire � Abramowitz et al., 2007), which mix different facets of health
anxiety symptoms (e.g., various safety behaviors, somatic complaints, concerns
about pain, and clinical impairment), the HCSUS is expected to provide a more pure
assessment of behavioral domains of health anxiety (i.e., health-care seeking
motivated for reassurance).
Depression Anxiety Stress Scale (DASS)
The DASS assesses three negative emotional states including depression, anxiety, and
stress on a 4-point Likert-type scale (0�Did not apply to me at all � 3�Applied to
me very much or most of the time). Acceptable reliability has been found for the
Depression, Anxiety, and Stress scales (Cronbach’s a�.91, .84, and .90, respectively)
in a non-clinical sample (Lovibond & Lovibond, 1995). The total and subscale scores
have also demonstrated excellent construct validity (Henry & Crawford, 2005). The
depression and anxiety subscales were included in the current study to index severity
of negative affect.
Anxiety Sensitivity Index-3 (ASI-3)
The ASI-3 is an 18-item self-report measure assessing the fear of anxiety-related
arousal and sensations based on a 5-point Likert-type scale (0�very little � 4�very
much). The scale contains three subscales: Physical, Social, and Cognitive Concerns.
The ASI-3 has shown good psychometric properties, including adequate internal
consistency (Cronbach’s a; Physical�.76, Social�.78, Cognitive�.86) and con-
struct validity in a nonclinical sample (Taylor et al., 2007).
Anxiety, Stress, & Coping 497
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The Health Threat Word Rating Form
We constructed a rating form containing 106 potentially threatening health-related
words (e.g., ache, blood, cancer, coronary, vomit) adapted from existing studies
(Ferguson, Moghaddam, & Bibby, 2007; Owens et al., 2004; Roberts, Hart, &
Eastwood, 2010) and the Affective Norms for English Words (ANEW; Bradley &
Lang, 1999). Participants were asked to indicate how threatening they found the
meaning of each word based on a 7-point scale (0�Not at all � 6�Extremely). Thisrating form was developed to individualize the dot-probe task by identifying
personally relevant health-threat words for each participant. In the current sample,
internal consistency coefficient for this measure was .98.
Mini International Neuropsychiatric Interview 5.0 � Hypochondriasis Module
(MINI-HC)
The MINI is a widely used clinician-administered brief structured diagnostic
interview for DSM-IV (American Psychiatric Association, 2000) and ICD-10 (World
Health Organization, 1992). Its validity has been established against existing well-validated structured diagnostic interviews such as the Structured Clinical Interview
for DSM-III-R Patient Version and the Composite International Diagnostic
Interview for ICD-10 (Sheehan et al., 1998). We administered the HC module to
examine whether the severity range of health anxiety in the current study would also
encompass the clinical threshold level that warrants the diagnosis of HC based on
DSM-IV criteria. The MINI interviewers were thoroughly trained by completing a
workshop offered by one of the original developers of the MINI, and received
20 hours of training by the first author (HJL). Although inter-rater reliability wasnot formally examined, each interview case was reviewed at weekly supervision
meetings, and there was 100% agreement on the diagnosis of HC (n�6) in the
current sample.
Dot-probe task
We generated a dot-probe task tailored for each participant, using the 20 most
threatening words endorsed on the Health Threat Word Rating Form. Each of these
words was matched with a neutral word of the same length in order to form 20 pairsof health-threat versus neutral words. Neutral words were selected and adapted from
the Affective Norms for English Words (ANEW; Bradley & Lang, 1999). Thus, the
health-threat words and neutral words included in the dot-probe task varied across
participants. Each dot-probe trial proceeded in the following sequence: First, a small
fixation cross was presented at the center of a 17-inch LCD monitor for 500 ms.
Second, a pair of words was presented for 500 ms immediately following the fixation
cross disappearance. One word appeared 1.1 cm above, and the other word appeared
1.1 cm below the position of the central fixation cross. Following the pair of words, aletter probe (‘‘E’’ or ‘‘F’’) appeared in one of the two word locations, and stayed on-
screen until the participant pressed the response key (either ‘‘E’’ or ‘‘F’’) to identify
the letter. The inter-trial interval was 1500 ms.
The task began with eight practice trials, which presented neutral�neutral pairs
of words. A total of 160 dot-probe trials were then administered over two blocks of
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80 trials each. Of 160 trials, 80% (�128 trials) presented an idiographically chosen
health-threat word paired with a neutral word. The other 20% (�32) of trials
presented neutral�neutral word pairs, which enables us to clarify whether attentional
vigilance is characterized by facilitated detection of threatening information ordifficulty in disengaging attention from the threatening information (Koster,
Crombez, Verschuere, & De Houwer, 2004). The thematic category of words (i.e.,
health-threat vs. neutral) and the type of letter probes (‘‘E’’ vs. ‘‘F’’) were balanced
between the two stimulus positions in the current dot-probe task.
From the dot-probe task, we generated the AB index to evaluate the nature and
magnitude of ABs in response to health-threat words as compared with neutral
words, using the following formula:
Attentional Bias ðABÞ Index ¼ Average reaction time ðRTÞcomputed from the trials presenting the letter probe on the neutral
word position� Average RT computed from the trials presenting
the letter probe on the health� threat word position:
If the individual’s attentional allocation is biased toward health-threat words, RTs
should be shorter when the probe appears on the threat word position rather than
the neutral word position. Alternatively, if the individual diverts attention away
from health-threat words, RTs should be longer when the probe appears on the
health-threat word position. Thus, the above AB index is proportionate to thedegree of the individual’s AB toward health-threat words. In contrast, negative
values of the AB index reflect attentional avoidance from health-threat words.
Furthermore, the nature of ABs (e.g., facilitated detection of health-threat cues
vs. difficulty in disengaging attention from them) can be further examined by
comparison with reference RTs produced from the trials displaying neutral�neutral word pairs. For example, if RTs toward neutral words (paired with
health-threat words) are longer than the reference RTs, the positive AB index
suggests difficulty in disengaging attention from health-threat words. In contrast,if RTs toward health-threat words (paired with neutral words) are shorter than
the reference RT, the positive AB index indicates facilitated detection of heath-
threat words.
Procedures
After providing informed consent, each participant was interviewed to determine
diagnostic status based on the MINI-HC. Next, a computerized battery of
instruments was administered with the Health Threat Word Rating Form as the
first measure. Upon the completion of the rating form, the experimenter produced an
individually tailored dot-probe task using a pre-programmed task generationtemplate (which allowed the task to be built quickly incorporating the chosen
health-threat words and matched neutral words), while the participant filled out the
remaining measures in the battery. After a 10-minute break, the participant
completed the dot-probe task as the final step of the single-session assessment
procedure.
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Data analytic strategy
We conducted hierarchical regression analyses to examine potential predictors of AB
toward health-threat words. In Step 1, DASS-Depression and Anxiety subscales were
entered to control for the influence of negative affect. This was designed to test
whether the AB index would be uniquely explained by health anxiety-relevant factors
beyond the contribution of negative affect. Although negative affect may be an
inseparable component of health anxiety, this analytic approach is important giventhe wealth of research that has demonstrated ABs linked to depression and anxiety
(see Cisler & Koster, 2010; Koster, De Raedt, Goeleven, Franck, & Crombez, 2005).
Anxiety sensitivity (as assessed by the ASI-3) was also entered into Step 1 to examine
whether health anxiety-related AB would merely be a function of varying levels of
anxiety sensitivity. In Step 2, the PHQ-Medical Conditions index was entered to
examine whether observed ABs would be the result of the presence of actual medical
conditions rather than health anxiety variables. In Step 3, health anxiety-relevant
factors were entered, including (1) the severity of illness-related cognitions (SHAI-Total score), (2) the severity of various physical complaints (PHQ-Somatoform), and
(3) the efforts to seek and utilize health-care resources (HCSUS � z score). This
analytic strategy allowed us to test the pattern of association between various health
anxiety factors and AB toward health-threat words after controlling for other
relevant variables.
Results
Preparation of RT data
The current sample’s overall correct response rate on the dot-probe task was 96.9%.
In generating the RT data from the dot-probe task, RTs from incorrect trials were
removed. Additionally, RTs falling outside the range of mean92 SD (1.0%) were
excluded to reduce the influence of outliers. Thus, the AB index was generated using
95.9% of the trials.
Basic clinical characteristics of the current sample
Table 1 presents basic clinical characteristics of the current sample, as measured bythe SHAI, ASI-3, DASS, PHQ, and HCSUS. Kolmogorov-Smirnov test revealed
that all subscale and total scores of the study measures and the AB index were
normally distributed. The MINI-HC module showed that six individuals met DSM-
IV diagnostic criteria for HC, and these individuals scored significantly higher on the
SHAI than those without HC: means (SDs)�51.83 (10.32) vs. 36.14 (9.03),
t(54)�3.97, pB.001. Zero-order correlations among the study measures and their
correlations with the AB index are presented in Table 1.
Predicting the AB index with health anxiety-relevant variables
We conducted hierarchical regression analyses to examine the contribution of
various aspects of health anxiety symptoms in predicting AB toward health-threat
words paired with neutral words. None of the variables entered in the first two
steps significantly predicted attention bias (R2DB.03, FsB1.4). In Step 3, SHAI,
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PHQ-Somatoform, and HCSUS scores explained an additional 28.6% of the
variance (R2D�.29, F(3,46)�6.65, pB.001). In the model, the HCSUS emerged
as the strongest predictor of AB toward health-threat words (b�.46, t�3.24,
pB.005). PHQ-Somatoform was also predictive of the AB index (b�.32, t�2.04,
pB.05). In contrast, SHAI-Total was not a significant predictor of the AB index
(b�.12, t�.73, p�.47).1 Overall, the model explained 34.0% of the variance in AB
toward health-threat words. Multicollinearity was not an issue for this regression
model, including the three health anxiety factors entered in Step 3 (their VIF values
ranged between 1.42 and 1.86).
Specific pattern of AB toward threatening health words: facilitated detection or delayedattentional disengagement?
To specify the nature of attentional vigilance associated with health-care seeking
efforts, we examined the top and bottom 30% scorers on the HCSUS (see Figure 1).
A t-test revealed that the high health-care seekers displayed a significantly greater AB
index score (� vigilance toward the health-threat words), relative to the low health-
care seekers (see Table 2): t(33)�2.29, p�.029, Cohen’s d�.80. Among the top 30%
scorers, paired t-tests revealed that the average RT to neutral words (paired with
health-threat words) was significantly longer than the reference RT: means
(SDs)�505 ms (54) vs. 495 ms (59), t(16)�2.59, pB.05; whereas the average RT
to health-threat words was not different from the reference RT: t(16)�.75, p�.46. In
contrast, low health-care seekers (bottom 30% scorers) showed a longer RT to
health-threat words (paired with neutral words), relative to the reference RT: 492 ms
(37) vs. 483 ms (37): t(17)�2.74, pB.05. The average RT to neutral words (paired
with health-threat words) did not differ from the reference RT: t(17)�1.35, p�.20.
Taken together, these data suggest that attentional vigilance observed among high
Table 1. Descriptive statistics and correlational analyses of self-report measures and attention
bias index (N�56).
M (SD)
Attention Bias
Index 1 2 3 4 5 6
1. DASS-
Depression
12.75 (9.68) .03 �
2. DASS-Anxiety 8.82 (7.67) .08 .60*** �3. ASI-Total 20.82 (13.61) �.03 .46*** .77*** �4. SHAI-Total 37.82 (10.31) .24 .51*** .52*** .50*** �5. PHQ-
Somatoform
6.88 (4.57) .26 .51*** .61*** .53*** .44** �
6. HCSUS 5.04 (4.20) .48*** .35** .20 .01 .43** .23 �7. PHQ-Medical
Conditions
.36 (.62) .14 .38** .16 .18 .35** .29* .22
Note: DASS, Depression Anxiety Stress Scale; ASI, Anxiety Sensitivity Index-3; SHAI, Short HealthAnxiety Inventory; PHQ-Somatoform, Patient Health Questionnaire-Somatoform Module; HCSUS,Health Care Seeking and Utilization Scale; PHQ-Medical Conditions, Experience of actual medicalconditions.*pB.05, **pB.01, ***pB.001
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health-care seekers is characterized by difficulty in disengaging attention from
health-threat words rather than facilitated attentional shifts.
Discussion
Considerable evidence has accumulated over the past few decades that anxious
individuals show attentional vigilance toward emotionally threatening information
(Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van Ijzendoorn, 2007;
Cisler & Koster, 2010; MacLeod et al., 1986; Mogg & Bradley, 1998; Williams et al.,
1996). The significant role of AB in anxiety disorders is also indicated by a recently
emerging line of research that has demonstrated promising therapeutic effects of
Figure 1. Reaction times across the different types of dot-probe trials among high versus low
health-care seekers.
*Error bars�standard error of the mean.
Table 2. Descriptive data and attention bias scores from the dot-probe task.
All participants
(n�56)
Low health care
seekers (n�18)
High health care
seekers (n�17)
Errora RT (ms) Error RT (ms) Error
RT (ms)
M (SD)
Mean
(SD)
Mean
(SD)
Mean
(SD)
Mean
(SD)
Mean
(SD)
Probe on the health-
threat word position
486 (51) 2.11 (1.98) 492 (37) 1.72 (1.32) 495 (59) 2.29 (1.86)
Probe on the neutral
word position
488 (47) 1.78 (2.06) 488 (33) 1.22 (1.51) 505 (54) 1.76 (2.36)
Neutral�neutral pair
condition
482 (48) 1.09 (1.50) 483 (37) .83 (.86) 490 (56) 1.24 (1.64)
Attention bias scoresb 2.29 (16.33) �3.54 (12.04) 9.97 (21.80)
aError values indicate the sum of errors made in each section of the task.bAttention bias scores�RT on trials with the probe on neutral word position � RT on trials with the probeon health-threat word position.
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attention-modification procedures on reducing anxiety symptoms (e.g., Amir, Beard,
Burns, & Bomyea, 2009; Amir, Weber, Beard, Bomyea, & Taylor, 2008; Schmidt,
Richey, Buckner, & Timpano, 2009). Several authors have proposed that HC may be
better conceptualized as an excessive health anxiety condition that shares many
phenomenological features with other anxiety disorders (Deacon & Abramowitz,
2008; Noyes, 2001; Olatunji et al., 2009), however, our current knowledge regarding
attentional processing underlying health anxiety is limited.The current study sought to examine the nature of attentional processing
associated with health anxiety, with two important methodological strengths
including: (1) employing a dot-probe task using idiographically selected health-
threat words, and (2) examining AB in light of various health anxiety-relevant
factors (i.e., cognitive, somatic, and behavioral features) while controlling for other
relevant variables, including anxiety sensitivity, negative affect, and experience of
actual medical conditions. Overall, our data show that behavioral (i.e., efforts to seek
and utilize health-care resources) and somatic (i.e., complaints of various physical
symptoms) aspects of health anxiety were significantly associated with AB toward
personally relevant health-threat words even after controlling for the aforementioned
variables.
Among the three domains of health anxiety, health-care seeking efforts emerged
as the strongest predictor of attentional vigilance toward health-threat cues.
Specifically, those who reported elevated efforts to seek health-care resourcesdisplayed greater difficulty in disengaging attention from threatening health
information, whereas those low in health-care seeking efforts tended to divert
attention away from threatening health information. Excessive reassurance seeking
through health-care resources, in the absence of medical evidence for a physical
illness, is a common behavioral feature of HC (e.g., ‘‘doctor-shopping’’ or strenuous
efforts to find a health care professional who can (dis)confirm one’s fears about a
physical condition), and is considered a counter-productive behavior that may
reinforce health anxiety (Abramowitz & Deacon, 2004). Consequently, prolonged
health care seeking and continuous search for the absence (or presence) of somatic
signs of abnormalities may amplify the individual’s emotional sensitivity to potential
health threats and AB toward them. Alternatively, it may be that difficulty in
attentional disengagement renders the individual’s attentional resources fixated
toward threatening health information, and thereby sustaining concerns about the
suspected illness and increasing subsequent efforts for health care and reassurance
seeking. The cross-sectional nature of our data preclude the conclusion as to whether
attentional vigilance to potential health threats is a cause or consequence of
prolonged health-care seeking efforts. Further research is needed to clarify the role ofAB and excessive health care seeking in the maintenance of health anxiety. It is
noteworthy that individuals displaying low health-care seeking efforts showed an
opposite pattern of attentional processing (i.e., avoidance from potential health-
threat cues). Further research is needed for the possibility that low health-care
seekers may exhibit a protective/regulatory mode of attentional processing that
minimizes cognitive processing of threatening health information (without regard to
the experience of actual medical conditions).
It should also be noted that the health-care seeking efforts, assessed by the
HCSUS, were significantly associated with reassurance seeking efforts and overall
health concerns, but not with the experience of chronic bona fide medical conditions
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or general anxiety. The pattern of associations between the HCSUS and other study
measures provide support for its utility as a relevant measure of behavioral aspects of
health anxiety. This also indicates that the current findings on the association
between AB and health-care seeking efforts (assessed by the HCSUS) are unlikely to
be explained by the individual’s personal experience of actual medical conditions. In
future research, it will be important to assess the validity of the HCSUS against other
similar measures (e.g., Medical Utilization Questionnaire � Abramowitz et al., 2007)to establish its validity as a self-report index that reflects hypochondriacal behavior
as opposed to legitimate health-care seeking and utilization.
Cognitive symptoms in health anxiety (as assessed by the SHAI) did not
significantly predict AB toward health-threat words, even though stimuli were
chosen idiographically to increase the personal relevance of the dot-probe task.
Similarly, Lees and colleagues (2003) did not find ABs as a function of health anxiety
during a visual probe task. Lecci and Cohen (2002) also found that slowed Stroop RTs
toward health-threat words were associated with the somatic aspect (i.e., elevated
sensitivity to bodily sensations), but not with the cognitive aspect (i.e., illness
preoccupation and worry) of hypochondriacal tendencies. Unlike behavioral or
somatic features of health anxiety, negative illness-related cognitions might reflect
entrenched beliefs that are relatively unaffected by specific patterns of attentional
allocation at earlier stages of information processing. However, given the central role
of AB in current cognitive models of health anxiety (Abramowitz et al., 2002;
Warwick & Salkovskis, 1990), further research is warranted on the associationbetween AB toward potential health threats and illness-related beliefs.
The current findings have some important clinical implications. First, given
growing evidence for the critical role of AB in the maintenance and treatment of other
anxiety disorders (e.g., Amir et al., 2009; Schmidt et al., 2009), cognitive interventions
that directly target reducing attentional vigilance toward potential health threats may
yield a beneficial therapeutic effect. Specifically, our data hint the possibility that
reducing attentional vigilance to health-threat cues is likely to be associated with
therapeutic changes in a behavioral domain of health anxiety such as maladaptive
health-care seeking efforts. Second, our data suggest that excessive health care seeking
is an important variable that is linked to underlying cognitive biases, and also serves
the purpose of gaining reassurance that may contribute to sustaining health anxiety.
The intervention for health anxiety needs to aim at decreasing excessive health-care
seeking behavior as one of the primary treatment targets.
Some limitations of the study and considerations for future research should be
noted. This study used a non-clinical student sample displaying a wide range of healthanxiety symptoms, assuming a linear association between levels of AB and health
anxiety on a continuum. This limits the generalizability of the findings as individuals
with severely impairing HC may display a different pattern of AB and its cognitive and
behavioral correlates. Other limitations concern the use of the dot-probe task, which
consisted of only word stimuli. A different mode of stimuli (e.g., pictorial health-threat
cues) may trigger a different pattern of attentional processing. For example, Lees et al.
(2003) found an AB that was associated with anxiety sensitivity on a dot-probe task
using pictorial cues, but not on a task based on illness-related words. Relatedly, the
current dot-probe task did not include general emotional threats (e.g., dysphoric
emotional cues) because we aimed to test AB associated with personally relevant health-
threat words. Inclusion of general threat words would have made it difficult to interpret
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whether the observed AB resulted from specific threat content (i.e., health threat) or
from personal relevance. Nonetheless, it is important to further investigate whether
individuals with heightened health anxiety would display ABs toward general
emotional threat. Additionally, the current study did not take into consideration a
potential threat-induced slow-down effect, which might have contributed to the
difficulty in attentional disengagement from health-threat words (observed in high
health-care seekers). Mogg, Holmes, Garner, and Bradley (2008) demonstrated that
differences in RT between threat and neutral cues cannot be assumed to provide pure
measures of shift or disengagement components of AB because of the threat-induced
response slowing. Future investigation may include trials that can index threat-induced
response slowing effects by removing the need for attentional shift (e.g., a central cue
task; see Mogg et al., 2008), which would produce a more pure index of attentional
shift vs. disengagement related to health anxiety.
In sum, the current data suggest that excessive health-care seeking efforts and
somatic complaints are significantly associated with attentional vigilance toward
personally relevant health-threat information. Particularly, individuals displaying
elevated efforts for health-care resource seeking showed difficulty in disengaging
attention from health-threat cues. It is imperative to further investigate the nature of
cognitive processing underlying health anxiety in order to gain better knowledge of
its maintenance and develop effective cognitive interventions, including attention-
modification procedures, for the reduction of symptoms.
Acknowledgements
This research was supported by the Research Growth Initiative Grant from the University ofWisconsin-Milwaukee awarded to Hanjoo Lee.
Note
1. Additionally, we examined whether the binary diagnostic status of HC was significantlyassociated with the AB index, although only six individuals met DSM-IV criteria for thiscondition. Results showed that, similar to the overall level of health anxiety reported on theSHAI, the diagnostic status of HC did not significantly predict the magnitude of the ABindex.
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