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Running head: ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION
Acknowledgement
This article may not exactly replicate the final version published in the journal. It is not the copy of record. Publisher copyright and source : Journal of Experimental Psychopathology, vol(issue), startpage-endpage
Archived version Author manuscript: post-print (post-refereeing)
Published version http://dx.doi.org/10.
Journal homepage (Copyright)
http://jep.textrum.com/ Issn 2043-8087
Author contact at KU Leuven
(article begins on next page)
Abstract Thinking about Negative Events in Dysphoric Students
Leads to Negative Generalization
Jens Van Lier, Bram Vervliet, Koen Vanbrabant, Bert Lenaert, & Filip Raes
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 2
KU Leuven
This research was supported by the Center for Excellence on Generalization Research
(GRIP*TT; KU Leuven grant PF/10/005). Jens Van Lier is a research assistant of the
Research Foundation- Flanders (FWO)
Acknowledgements: The authors would like to thank H. De Meyer and A. Kestens for
their help with the data collection.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 3
ABSTRACT
The severity of many psychological disorders is associated with an increasing
amount of different stimuli or situations that elicit a maladaptive response. This is
known as the process of (over)-generalization and is often characteristic of
individuals with emotional disorders. Recently, abstract repetitive thought has been
proposed to be a transdiagnostic marker in several disorders (e.g., worry in anxiety;
rumination in depression). The present study examined the impact of an abstract
thinking style (compared to a more concrete thinking style) as a mechanism that
contributes to generalization. Students (N=83) were trained in either an abstract or
concrete thinking mode and then completed a learning phase and finally a
generalization test phase. High dysphoric students showed more negative
generalization in the abstract condition compared to the concrete condition. For low
dysphoric participants, the two thinking styles did not result in a difference in
generalization. Implications for the transdiagnostic value of an abstract processing
style in depression and anxiety are discussed.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 4
INTRODUCTION
Consider the following two examples. First, a man is diagnosed with depression. He
recently had a conflict with one of his best friends over a promise that was not kept.
This event has touched him deeply, leading him not to trust any of his friends. His
lack of trust has not only spread to his friends but even to his family and his wife.
This has led him to avoid contact with other people as much as possible. Secondly,
the neighbor’s dog bit Mark one day. His normal fear of the neighbor’s dog rapidly
spreads to a fear of many different dogs. Now he does not only fear the neighbor’s
dog or dogs of that same breed but even small friendly looking dogs. His fear of dogs
escalates to the extent that even a picture of a dog elicits fear. He becomes afraid of
leaving his house because of the chance of encountering a dog. He worries constantly
and his fear of dogs becomes a serious impairment in his life.
These two examples illustrate that it is maybe not so much the intensity of fear or
bad feelings that makes those feelings detrimental to an individual’s functioning.
Rather, many psychological problems are characterized by some form of over-
generalization (e.g., Hermans, Baeyens, & Vervliet, 2013). In the context of fear
conditioning, generalization-conditioning paradigms have been developed to study
generalization in humans (e.g. Lissek et al., 2008; Vervliet, Kindt, Vansteenwegen, &
Hermans, 2010). In the depression literature, using self-report measures of
overgeneralization (Carver & Ganellen, 1983), Carver (1998) found that negative
overgeneralization to the self predicted subsequent depressive symptoms. In a recent
study Fulford, Rosen, Johnson, and Carver (2012) also found a relationship between
negative overgeneralization to the self and symptoms of anxiety. Other studies have
found that depressed participants differ from non-depressed participants on negative
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 5
generalizations across situations (e.g., Klar, Gabai, & Baron, 1997; van den Heuvel,
Derksen, Eling, & van der Staak, 2012). In this study we examine the role of another
important transdiagnostic mechanism, namely the abstract processing of events, in
generalization.
The way people process events (e.g., rumination) has been singled out as one of
the most important factors leading to a pathological outcome (Kinderman,
Schwannauer, Pontin, & Tai, 2013). The foundational and pioneering work of Susan
Nolen-Hoeksema has been of immeasurable value in this context. More recently, she
was also one of the major contributors in the area of transdiagnostic rumination
research (e.g., McLaughlin & Nolen-Hoeksema, 2011; Aldao, Nolen-Hoeksema, &
Schweizer, 2010; Nolen-Hoeksma & Watkins, 2011).
Indeed, repetitive thinking (like rumination, but also worry) has been found to
characterize individuals with many different psychological problems and is thus
considered as a transdiagnostic factor (Harvey, Watkins, Mansell, & Shafran, 2004;
McLaughlin & Nolen-Hoeksema, 2011; Ehring & Watkins, 2008; Aldao et al., 2010).
However, not every single form of repetitive thinking has been found to be
detrimental (Watkins, 2008). Again, in this context, Susan Nolen-Hoeksema led
pioneering work, e.g. her work on the distinction between a maladaptive rumination
type (brooding) and a relatively less maladaptive and in some cases even protective
form of rumination (reflection; Treynor, Gonzalez, & Nolen-Hoeksema, 2003). One
(other) element of repetitive thinking that has been consistently found to be
maladaptive is when this repetitive thinking is abstract (vs. concrete) in nature
(Watkins, 2008).
Watkins (2008) adopted the representations of abstract and concrete construal (or
processing mode) of repetitive thought that originated in the cognitive literature (e.g.,
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 6
Trope & Liberman, 2003). “Abstract construals are general, superordinate, and
decontextualized mental representations that convey the essential gist and meaning of
events and actions, such as inferences of global traits that are invariant across
different situations (e.g., “laziness”) or representations of “why” an action is
performed and of its ends and consequences. In contrast, concrete construals are more
low-level mental representations that include subordinate, contextual, and incidental
details of events and actions, such as inferences of situation-specific states, such as
“tiredness,” or representations of the specific “how” details of an action and of the
means to an end” (Watkins, 2008, p. 187).
The impact of adopting an abstract vs. concrete processing mode has been
examined in several studies with different outcomes. In studies that manipulate these
processing modes, participants in the concrete condition are typically asked to focus
on contextual details and thus on the specific “how” details of an event (e.g., “Think
about what you could hear, smell, touch, etc. in that situation; Moberly & Watkins,
2006), whereas participants in the abstract condition are asked to focus on the causes,
meanings and implications and thus on the “why” aspects of an event (e.g., “Think
about the causes, consequences and implications for that situation”; Moberly &
Watkins, 2006). Experimental studies have shown unconstructive consequences of an
abstract processing mode, such as recalling more overgeneral autobiographical
memories (Raes, Watkins, Williams, & Hermans, 2008), endorsing more global self-
judgments (Rimes & Watkins, 2005), poorer problem solving (Watkins & Moulds,
2005), and poorer emotional recovery from prior failure (Watkins, 2004).
Although manipulations of abstract processing have been used in different
studies, none have looked at the impact of this processing mode on generalization.
However, it has been posited that the mechanism by which abstract processing has its
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 7
unconstructive consequence may be via its impact on the degree of generalization in
response to emotional events (Watkins, 2008); but, again, this has not yet been put to
an experimental test. Therefore, we now directly tested this hypothesis by inducing
participants to adopt either an abstract or concrete processing mode and afterwards
assessed their generalization by using a generalization-conditioning paradigm
commonly used in the context of fear generalization (e.g., Lissek et al., 2008; Vervliet
et al., 2010). A generalization-conditioning paradigm usually consists of two phases,
i.e., an acquisition and generalization phase. In the acquisition phase a stimulus (CS+)
is paired with an aversive outcome (US). Next, in the generalization phase the
response to stimuli similar to the CS+ (e.g., morphs of the CS+), but never paired
with the US, is tested.
In our conditioning procedure we sought to mimic the kind of generalization
across situations seen in depression (e.g., Klar et al., 1997). After some negative
encounters, depressed individuals will make abstraction of the specifics of the
individual situations and (over)-generalize to situations that look (most) similar to the
original situation. By using a conditioning paradigm with negative and neutral events
and including an induction procedure of abstract and concrete thought that has
previously proved to be successful (Moberly & Watkins, 2006) we aim to bridge a
gap between the anxiety literature, in which the use of such procedures is very
common, and the depression literature.
We expected to observe more generalization in participants who received an
abstract processing mode induction compared to those who received a concrete
processing mode. However, Watkins (2008) notes that the negative consequences of
the inductions that trigger abstract thought are often moderated by current mood.
Consequently, studies have found that these abstract thought manipulations often only
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 8
have differential effects in vulnerable groups (i.e., individuals experiencing dysphoric
mood; e.g., Watkins & Teasdale, 2004; Watkins & Moulds, 2005). This means that
the negative effects of the abstract thought induction are mostly (or only) present for
people who are already in a dysphoric mood or people high in the tendency to engage
in repetitive negative thinking. Higher levels of depressive symptoms and repetitive
negative thinking are predicted to moderate (i.e., strengthen) the relationship between
induced abstract (vs. concrete) processing style and generalization.
A somewhat related issue is that in general, depressed individuals show more
generalization for negative events than do non-depressed individuals. However, for
neutral events, Klar and colleagues (1997) found no difference in the degree of
generalization between depressed and non-depressed participants. Consistent with
these findings, we further hypothesized that high dysphoric participants and
individuals high in repetitive negative thinking that are induced in an abstract thinking
mode (vs. a concrete thinking mode) would show more generalization for stimuli with
a closer resemblance to the original negative stimulus (i.e., negative generalization).
METHOD
Participants
We opted to study adolescent participants because this an important age period
concerning the onset of a first major depressive episode (e.g., Zisook et al., 2007).
Participants were recruited from a secondary school (Sint-Jozefscollege, Aalst) in
Flanders, Belgium. All participated without compensation. A total of 83 students (54
boys) participated in the study. Their mean age was 16.9 years (SD = .68, age range:
16 – 19; age info missing for two participants). The experiment in this study was
conducted in accordance with the Declaration of Helsinki and approved by the local
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 9
ethics committee of the University of Leuven. Written informed consent was obtained
from all participants1.
Materials
Training materials for abstract and concrete processing mode (Moberly &
Watkins, 2006). All participants are presented with the same six scenarios as training
materials (three negative: “falling out”, “having a bad day-messing up”, “being new”;
three positive: “dinner party”, “a successful job interview”, “learning to surf”). In
both conditions, participants are asked to spend one minute concentrating on each
scenario. Following each scenario, they are instructed to write down answers to three
questions about the scenario to further reinforce the induced processing mode.
Moberly and Watkins (2006) used this procedure to successfully induce the intended
processing modes: abstract thought mode and concrete thought mode.
In the abstract condition participants are presented with a brief description of the
situation. For example, for the “being new” scenario, the text reads: “You arrive at the
university and you don’t know anyone. You wander around campus and the halls. By
the end of the first day, everyone else seemed to have formed groups and are chatting
and laughing, but you seem to end up alone.” Participants are asked to think about this
situation in words and most importantly to think about the causes, consequences and
implications of each situation. The abstract thought induction is further reinforced by
asking three questions focusing on abstract aspects of each situation (e.g., “What do
you think about yourself at the end of the day?”, “Why did you find it hard to talk to
others?”, “What do you think will happen tomorrow?”).
In the concrete thought condition participants are presented with one or more
black and white photographs illustrating the situation. The photographs encourage a
1 In Belgium, where the experiment was conducted, age of consent is 16.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 10
more concrete, visual imagery-based approach to the situation. For example, for the
“being new” scenario the photographs show a girl sitting alone on a staircase
watching outside with people around her but the people do not notice her. Participants
are asked to use the photographs as a starting point to form a detailed image of the
situation, as if they are playing a movie of that situation in your head. Specifically,
they are asked to “imagine as vividly as possible what you can see, hear, feel, touch
and experience in that situation”. The concrete thought induction is further reinforced
by asking three questions focusing on concrete aspects of each situation (e.g., “What
are the other people doing?”, “What is happening outside the window?”).
Instructions about the training of abstract and concrete thought were read out
loud by the experimenter. In addition, participants could read the instructions on the
first page of the booklet. As recommended by Moberly and Watkins (2006), the
experimenter controlled the time (using a stop-watch) that could be used to think
about the scenario (one minute) and the time spent on writing the answers to the three
questions (one minute and 30 seconds) to ensure that each participant spent an equal
amount of time on every scenario.
Generalization paradigm. Stimuli. Two pictures of inside a train served as
conditioned stimuli, the CS+ and CS- (see ‘blue’ and ‘red’ train in Figure 1). The
generalization stimuli (GS) were seven morphs between the two CSs. We used
specialized software (Norrkross MorphX) to form these GSs in seven gradual steps.
Each of the seven resulting pictures served as a generalization stimulus. Figure 1
shows the CS+ (CS-) and the resulting GSs. The GSs resemble the CS+ (CS-) but in
seven decreasing (increasing) steps of perceptual similarity. For half of the
participants, the ‘blue’ train served as the CS+, while in the other half the ‘red’ train
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 11
served as the CS+. All stimuli were presented in the middle of the computer screen on
a black background.
Scenarios. Following the presentation of the CS+ and CS- in the acquisition
phase, participants heard a positive or neutral scenario of an event that took place in
that train. Twenty scenarios (10 aversive/failure, 10 neutral) were first rated for
valence in a pilot study. The scenarios were always matched in structure. For
example, one of the negative/failure scenarios was as follows: “You are sitting in this
train, and the conductor asks for your ticket. The conductor suddenly starts yelling at
you while others are looking at you. You don’t speak his language and you only
notice that he is really mad and that you have to pay an extra fee.” A neutral scenario,
for example, reads: “You are sitting in this train, and the conductor asks for your
ticket. The conductor asks something else, but you don’t speak his language. You
excuse yourself for not speaking the language. He smiles friendly and goes along.
You get back to watching outside.”
The five most negatively rated failure scenarios and their neutral matches were
chosen for the actual experiment. These failure scenarios were created to be
depression relevant, such that they invoked situations that involved failure or other
people laughing or being angry2. Scenarios were recorded with recording software by
the first author. The recordings of all scenarios were relatively matched (i.e., range:
16–19 seconds). The aversive/failure scenarios served as the US. Hence, the CS+
(e.g., the ‘blue’ train) was always paired with an aversive/failure scenario; that is,
participants learnt that every time they supposedly sit in this ‘blue’ train something
negative happens. The CS- (e.g., the ‘red’ train) was never followed by an aversive
2 We acknowledge that such scenarios are possibly not only relevant for depression but also for
individuals with social anxiety symptoms. However, we would argue that ‘people laughing at you’ and
‘feeling inferior’ are situations that depressed people might also relate to.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 12
scenario but always by a neutral scenario; that is, participants learnt that every time
they supposedly sit in this ‘red’ train something neutral happens.
US-expectancy. Participants were requested to indicate to what extent they expect
an aversive/failure event to occur in that train on an 11-point scale ranging from 0
(definitely NO negative event will follow) to 10 (there will definitely follow a negative
event). This scale was presented below the picture on the computer screen.
Participants had to move a red dot (using the left and right arrows) across the 11-point
expectancy scale to select their desired expectancy score. They confirmed their
answer by hitting ‘Enter’. There was no time limit for this response.
Valence. Participants were requested to indicate to what extent the train felt as
negative or positive to them. They were asked to not think too much about it and to
reflect their opinion. The 11-point valence scale ranged from negative (0) to positive
(10).
Manipulation check. Participants were asked to rate this question: “After hearing
each scenario you had to think in a way that you trained at the start of the experiment.
How well were you able to do this? Indicate on the scale below. Try to judge yourself
in an honest way.” The five-point scale ranged from not well to very well.
Procedure of generalization paradigm. Affect 4.0 software (Spruyt, Clarysse,
Vansteenwegen, Baeyens, & Hermans, 2010) was used to control the stimulus
sequence, the presentation of the stimuli and the inter trial intervals. Participants
started off with a pre-acquisition phase in which each CS was presented three times in
a random order. They were instructed to rate their US expectancy; however, at this
point in the experiment they had not yet experienced the US. This phase was
primarily used to familiarize participants with the pictures.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 13
After this phase, participants received instructions about the acquisition phase
and were asked to put their headphones on to listen to the spoken scenarios
individually. One CS (CS-) was presented five times and was always followed by a
neutral scenario that the participants heard after they gave their US-expectancy rating
(by pressing ‘Enter’). The other CS (CS+), also presented five times, was always
followed by an aversive/failure event. The trials were presented in a random order. In
total the participants had to give 10 US-expectancy ratings. After every trial they were
instructed to think back about the train scenario in the particular mode that was
previously trained. Thus, in the abstract condition group they were again instructed to
think about the causes, implications and consequences of the situation. The CS
remained on the screen for 30 seconds while the participant was thinking.
Once participants completed the acquisition phase they could remove the
headphones. In the generalization test phase there were two blocks of 13 trials. The
CSs were each presented three times (never followed by a US) and the seven GSs
(never followed by a US) were presented one time in each block. US-expectancy was
rated in the same way as in the previous phases. In the last phase valence was
measured for the CSs and the GSs. The CSs were each presented three times and the
seven GSs were each presented once. After completing the valence measure,
participants answered the manipulation check question. This was the last screen on
the computer. Upon completion, participants were instructed to return to the booklet
for the remaining questionnaires.
Perseverative Thinking Questionnaire (PTQ; Ehring, Zetsche, Weidacker, Wahl,
Schönfeld & Ehlers, 2011). The PTQ is a 15-item questionnaire measuring repetitive
negative thought that is independent of a specific content. The items assess the
repetitiveness (e.g., The same thoughts keep going through my mind again and again),
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 14
intrusiveness (e.g., Thoughts just pop into my mind), difficulties to disengage (e.g., I
can’t stop dwelling on them) and unproductiveness of recurrent negative thinking
(e.g., I keep asking myself questions without finding an answer) as well as the degree
to which rumination captures mental capacity (e.g., My thoughts prevent me from
focusing on other things). The instructions read: “In this questionnaire, you will be
asked to describe how you typically think about negative experiences or problems.
Please read the following statements and rate the extent to which they apply to you
when you think about negative experiences or problems.” Participants are asked to
rate the items on a five-point scale, from 0 (never) to 4 (almost always). The PTQ has
shown good psychometric properties (Ehring et al., 2011). In this study the Dutch
version (PTQ-NL) was used (Ehring, Raes, Weidacker & Emmelkamp, 2012;
Cronbach’s α = .93). The internal consistency of the PTQ-NL in this sample was good
(α = .89). A recent study further showed that the PTQ-NL has prospective predictive
validity for depressed mood (Raes, 2012).
Depression Anxiety Stress Scales (DASS 21). The DASS 21 is a 21-item self-
report questionnaire that measures negative emotional states of depression, anxiety
and stress (Lovibond & Lovibond, 1995). The depression subscale has good internal
consistency (α = .81, Lovibond & Lovibond, 1995). The 7-item depression subscale
of the Dutch version (de Beurs, Van Dyck, Marquenie, Lange, & Blonk, 2001) was
used in this study. The instructions read: “Please read each statement and circle a
number (0, 1, 2 or 3) which indicates how much the statement applied to you over the
past week.” Internal consistency for the depression subscale in this sample was good
(α = .78). Each item is scored on a four-point scale, from 0 (did not apply to me at all)
to 3 (applied to me very much, or most of the time).
Procedure
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 15
The study was conducted in a group setting in a computer room of the school.
Classes were randomly allocated to either the concrete or abstract processing mode
condition. Participants gave written informed consent and received an individual
booklet with all materials, presented in the same order. Instructions about the training
of abstract and concrete thought were read out loud by the experimenter. In addition,
participants could read the instructions on the first page of the booklet. After the
training phase, participants were instructed to start the second phase (i.e., the
generalization paradigm) on the computer, and to complete it at their own pace. When
participants were finished with the computer task they were prompted to go back to
the booklet for the remaining questionnaires.
Data analysis.
For acquisition, US-expectancy data were analyzed with a repeated measures
ANOVA with CS type (2 levels: CS+, CS-) and Trial (1-5) as within-subject variables
and Condition (2 levels: abstract and concrete processing mode) as a between-subject
variable. For generalization, US-expectancy and valence data were analyzed with a
repeated measures ANOVA with Condition (2 levels: abstract and concrete
processing mode) as a between-subjects factor and Stimulus (9 levels: CS+, GS1,
GS2, GS3, GS4, GS5, GS6, GS7, CS-) as a within-subject factor. DASS-Depression
was included as a covariate. These analyses were followed by trend analyses. We
considered it important to conduct the latter in order to test the shape of the
generalization gradient. Quadratic or cubic trend analyses of the whole set of 9 stimuli
would show that there might be a difference only at one end of the stimulus set, with
the a priori hypothesis that the gradient would only show a difference between
Conditions for vulnerable participants closest to the CS+ (i.e., showing negative
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 16
generalization). When a quadratic or cubic trend appeared, we opted to look at neutral
(GS5, GS6, GS7, CS-) and negative (CS+, GS1, GS2, GS3) generalization separately.
RESULTS
Participant Characteristics
Means, standard deviations, scoring ranges and correlations for all variables included
are presented in Table 1. There were no differences between the abstract and concrete
processing mode except that participants in the concrete condition scored higher on
the PTQ, t(75) = 2.46, p < .05.
Pre-acquisition
At this stage we should expect no difference in US-expectancy between the two
train-stimuli because they have not yet been paired with an aversive/failure event and
this phase was only used to familiarize participants with the procedure and the
stimuli. However, collapsed across the three trials, it seemed that the ‘red’ train at
baseline had a marginally higher expectancy of a negative event than the ‘blue’ train,
t(81) = 1.31, p = .07. There were no differences between the conditions of abstract
and concrete processing mode.
Acquisition
A repeated measures ANOVA with CS type (2 levels: CS+, CS-) and Trial (1-5)
as within-subject variables and Condition (2 levels: abstract and concrete processing
mode) as a between-subject variable was conducted. The analysis showed a main
effect of Trial, F(4,320) = 12.53, p < .001, ηp2 = .14, a main effect of CS type, F(1,80)
= 51.18, p < .001, ηp2= .39, and a significant CS type × Trial interaction, F(4,320) =
17.12, p < .001, ηp2 = .18. Contrast analyses showed no difference between CS+ and
CS- at trial 1, t(81) < 1, but as expected, at trial 5 the US-expectancy was higher for
the CS+ than for the CS-, t(81) = 7.35, p < .001. There was no main effect of
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 17
Condition, F(1,80) < 1, and no interaction effects with Condition. Hence, the
acquisition did not differ for the concrete and the abstract condition (Figure 2). When
we include DASS-Depression as a continuous between-subject variable in the model,
the same main and interaction effects were found. However, there was a main effect
of DASS-Depression, F(1,76) = 6.69, p < .05, ηp2 = .08, and a marginally significant
DASS-Depression × Condition interaction, F(1,76) = 3.18, p = .08, ηp2 = .04. To
clarify this interaction, additional analyses showed no relation between overall
expectancy scores and DASS-Depression for individuals in the abstract condition (r =
.11). However, for individuals in the concrete condition, there were higher overall
expectancy scores for individuals high on DASS-Depression (r = .41, p < .05).
Generalization Test3
Results presented here are for the first block only. To include participants that
actually learned the difference between the CS+ and CS- (in the generalization test
phase), we selected participants with a mean score of CS+ that was higher than the
CS-, i.e. (Mean CS+) – (Mean CS-) > 0. Fifteen participants did not acquire this
criterion (11 in the abstract condition and 4 in the concrete condition)4.
All analyses were corrected using the Greenhouse-Geisser method when
sphericity was violated. A repeated measures ANOVA with Stimulus (9 levels: CS+,
GS1, GS2, GS3, GS4, GS5, GS6, GS7, CS-) as a within-subject factor showed a main
effect for stimulus, F(4.90, 328.50) = 104.96, p < .001, ηp2 = .61. Polynomial contrast
analysis showed that there was a linear trend, F(1,67) = 305.52, p < .001, ηp2 = .82,
reflecting a clear generalization curve for the sample as a whole (Figure 2).
3 Because of the baseline difference in PTQ scores between conditions, we also controlled for PTQ in
all the analysis. Importantly, the results remained the same. For simplicity, we only report the results
here without controlling for PTQ. 4 The excluded participants did not differ from the included participants for demographics, PTQ,
DASS-Depression and manipulation check.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 18
We conducted a repeated measures ANOVA with Condition (2 levels: abstract
and concrete processing mode) as a between-subjects factor and Stimulus (9 levels:
CS+, GS1, GS2, GS3, GS4, GS5, GS6, GS7, CS-) as a within-subject factor and
included DASS-Depression as a covariate. This ANOVA revealed a main effect of
Stimulus, F(4.90, 308.52) = 47.41, p < .001, ηp2 = .43. Within-subject contrasts
showed a significant linear trend, F(1,63) = 136.77, p < .001, ηp2 = .69, and a
significant cubic trend, F(1,63) = 11.18, p < .01, ηp2 = .15. There were no other
significant effects, but polynomial contrasts revealed a significant cubic trend of the
DASS-Depression × Stimulus interaction, F(1,63) = 12.45, p < .01, ηp2 = .17 , and a
significant cubic trend of the DASS-Depression × Stimulus × Condition interaction,
F(1,63) = 4.42, p < .05, ηp2 = .07. We hypothesized that the negative effects of the
abstract thought induction would be most intensified for people already in a dysphoric
mood and would be most apparent for negative generalization (i.e., more at the CS+
side of the gradient). Both of these cubic trends show that the differences in gradients
are not linear and that this difference is only found at one end of the gradient and is
dependent upon the mood of the participants. Therefore, we further analyzed negative
and neutral generalization separately by looking at the CS+ and GS 1 through 3 for
negative generalization, and examined GS5 through 7 and CS- for neutral
generalization.
Negative Generalization
We conducted a repeated measures ANOVA with Condition (2 levels: abstract
and concrete processing mode) as a between-subjects factor and Negative Stimulus
(CS+, GS1, GS2, GS3) as a within-subject factor and included DASS-Depression as a
covariate. This ANOVA showed a main effect for Negative Stimulus, F(2.41, 151.97)
= 22.09, p < .001, ηp2 = .26, with a significant linear trend, F(1, 63) = 42.16, p < .001,
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 19
ηp2 = .40, and a marginally significant cubic trend, F(1, 63) = 3.81, p = .06, ηp
2 = .06.
There was a marginally significant effect for the Condition × DASS-Depression ×
Negative Stimulus interaction, F(2.41, 151.97) = 2.47, p = .08, ηp2 = .04, but
importantly polynomial contrasts revealed a significant linear trend of the interaction,
F(1, 63) = 4.84, p < .05, ηp2 = .07. As hypothesized, this analysis suggests that the
difference in generalization between the abstract and concrete processing mode
condition, especially for participants who scored higher on DASS-Depression,
increased with more dissimilarity from the CS+ (i.e., the original negative stimulus).
This is reflected in a less steep generalization gradient for more dysphoric participants
in the abstract condition for stimuli CS+ through GS3 (Figure 3).
Neutral Generalization
We conducted a repeated measures ANOVA with Condition (2 levels: abstract
and concrete processing mode) as between-subjects factors and Neutral Stimulus
(GS5, GS6, GS7, CS-) as a within-subject factor and included DASS-Depression as a
covariate. This ANOVA showed a main effect for Neutral Stimulus, F(2.40, 151.15)
= 25.83, p < .001, ηp2 = .29, with a significant linear trend, F(1, 63) = 55.29, p < .001,
ηp2 = .47 . There were no other main or interaction effects. As hypothesized, these
findings suggest that there is no difference in neutral generalization between
conditions.
PTQ.
When we included PTQ instead of DASS-Depression as a covariate, the results
were in the same direction. However, there were no significant results. Note that the
results might have been influenced by the baseline difference in PTQ between the
abstract and concrete condition.
Valence
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 20
A repeated measures ANOVA with Stimulus (CS+, GS1, GS2, GS3, GS4, GS5,
GS6, GS7, CS-) as a within-subject factor showed a main effect for Stimulus,
F(8,536) = 28.26, p < .001, ηp2 = .30. Polynomial contrast analysis showed a linear
trend, F(1,67) = 51.28, p < .001, ηp2 = .43. Hence, there was a clear generalization
curve for the sample as a whole. However, there were no significant interaction
effects between Condition (between-subject) and DASS-Depression or PTQ
(covariates).
DISCUSSION
The present study was conducted in order to examine the impact of abstract
thought on generalization in a depression relevant conditioning procedure. We
hypothesized that participants who received an abstract thinking mode induction
would show more generalization than participants who received a concrete thinking
mode induction. As previous studies have found that induction manipulations may
only have differential effects in vulnerable/dysphoric groups (Watkins & Teasdale,
2004; Watkins & Moulds, 2005; Watkins, 2008), we expected that depression score
might influence the effect of abstract processing style on generalization (i.e., we
predicted more generalization for dysphoric individuals). While most of the negative
repetitive thinking literature is based on adult studies, our results are based on an
adolescent sample, which is an important age period concerning the onset of a first
major depressive episode (e.g., Zisook et al., 2007). Our results showed that
participants with more depressive symptoms in the abstract induction showed more
generalization compared to participants in the concrete induction group. Interestingly,
this increased generalization was only found for the negative stimuli (the
generalization train-stimuli that were closest to the original train-stimulus that was
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 21
always paired with a negative/failure event). This effect was not found for participants
with lower levels of depressive symptoms.
Klar and colleagues (1997) found that depressed individuals tend to generalize
more across negative situations than non-depressed individuals, whereas non-
depressed individuals tend to generalize more across positive situations. No
differences between depressed and non-depressed were found for neutral situations. In
our study, when dysphoric participants were instructed to think abstractly about
negative stimuli this led to negative generalization. Accordingly, participants who
were instructed to adopt a concrete processing style showed no increased
generalization for the negative stimuli. We found no differences in generalization to
the neutral stimulus according to processing mode or dysphoria.
There is evidence that depressed individuals tend to endorse a more abstract
thinking style, especially to negative information or problems (e.g., Takano & Tanno,
2010; Watkins & Moulds, 2007). Hence, these studies and our findings might further
explain the difference in overgeneralization between depressed and non-depressed
individuals for negative situations. However, it remains unclear as to how abstract or
concrete thinking might influence generalization for positive stimuli/situations.
Watkins (2011) posits that abstract processing might have beneficial effects when
faced with easy (positive) or familiar situations but suggests that depressed
individuals do not use the most adaptive mode of processing when faced with positive
content. Related to this, a study by Marigold, Holmes and Ross (2007) showed that
people low in self-esteem tend to identify positive events (compliments from their
romantic partner) more concretely than participants who are high in self-esteem. This
finding could suggest that depressed individuals might act similarly (Watkins, 2011).
If depressed individuals indeed adopt a concrete processing style when they are faced
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 22
with positive stimuli or events, this could explain why non-depressed (compared to
depressed) individuals generalized more across positive situations in Klar and
colleagues’ study (1997). Therefore, further research could focus on positive
generalization by using more explicit positive stimuli in a depression relevant
generalization paradigm.
It has been noted that little is known about cognitive (vulnerability) factors that
influence generalization (see Hermans et al., 2013). Our study builds on the
knowledge about one possible variable (i.e., abstract or concrete processing mode)
that could have an impact upon generalization. In another study, Lenaert et al. (2012)
focused on the effects of autobiographical memory specificity on generalization. They
found that participants high in overgeneral autobiographical memory (OGM) showed
stronger generalization (also with a US-expectancy measure) to the GSs than
participants low in OGM. OGM is known to predict a negative development in
depression (Raes, Hermans, Williams, Beyers, Brunfaut, & Eelen, 2006). Moreover,
studies have found that abstract thought also leads to more overgeneral
autobiographical memory retrieval (Watkins & Teasdale, 2001; Raes, Watkins,
Williams, & Hermans, 2008). Therefore, our results might converge with the findings
of OGM research (Watkins & Teasdale, 2001; Raes et al., 2008; Lenaert et al. 2012)
because we experimentally induced participants in an abstract thinking style (also
leading to more OGM; see Raes et al., 2008), which lead to negative generalization in
dysphoric individuals. Hence, our results provide further evidence in support of the
claim that an abstract thinking style is an important underlying mechanism for related
unconstructive cognitive outcomes.
This study has several limitations. One limitation is that the induction of abstract
and concrete processing style was limited to six scenarios whereas the full induction
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 23
consists of 12 scenarios (Moberly & Watkins, 2006). This may have constrained the
size of our effects and may account for the absence of generalization in the later
stages of the experiment, namely for the second block and the valence measure. Also,
our manipulation check was different to that which has been employed in other
research using inductions of abstract and concrete processing mode5. Another
limitation is that we used a community sample which was only mildly dysphoric. In
future research it would be interesting to see whether these effects would generalize
to, or even be stronger for currently depressed or remitted depressed patients. We
might expect that generalization would be even greater in a depressed group when
they are instructed to adopt an abstract processing style.
Another limitation of the current study is that we do not have a control condition.
We cannot make strong claims as to whether the observed effects are caused by the
active increasing effect of abstract processing or the active diminishing effect of
concrete processing on generalization. However, selecting a suitable control condition
would be challenging. A no-instruction condition in which participants were not given
a specific processing instruction (i.e., were asked to do nothing) might simply result
in them engaging in spontaneous rumination, making a ‘do nothing’ group very
ambiguous as a reference group (for a similar point, see Watkins & Moulds, 2005).
Also, because of practical constraints, participants were assigned to the respective
conditions by class. As such, randomization occurred at the level of the classroom.
Hence, this could have resulted in the higher repetitive negative thinking scores for
5 Other studies have collected written answers to the respective abstract and concrete
manipulations. Ratings of these answers on an abstract/concrete scale served as a
manipulation check (e.g., Moberly & Watkins, 2006; Watkins, 2004). However, our
manipulation of abstract or concrete processing mode was embedded in the
conditioning procedure (i.e., in the acquisition task) where it was crucial that the
participant remained fixated on the picture of the train while thinking in an abstract or
concrete way. Therefore, participants were not able to write their thoughts down in
our procedure.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 24
the concrete condition.
We did not find that our measure of repetitive negative thinking in interaction
with an abstract thinking style was related to generalization. This finding could seem
challenging because of the substantial relationship between repetitive negative
thinking and depression. Therefore one might expect the same pattern for dysphoric
participants as well as for participants who score highly on repetitive negative
thinking. However, in his review, Watkins (2008) points out that only measures of
mood might interact with the induction of abstract or concrete processing style. Also,
the PTQ (as a measure of repetitive negative thinking) does not assess abstract
thinking per se but measures: (1) the key features of repetitive negative thinking (i.e.,
repetitive, intrusive, difficult to engage from), (2) its perceived unproductiveness, and
(3) the extent to which it captures mental capacity (Ehring et al., 2012). Therefore, a
more direct measure of trait abstract thinking might be necessary to observe
interactions with the inductions. Still, it remains very plausible that adopting an
abstract processing style has no detrimental effects when an individual is in a neutral
or happy mood. Watkins and Moulds (2005) note that in the absence of a significant
negative mood, people find it harder to sustain a prolonged and meaningful abstract or
concrete thinking style. This makes it difficult to induce either mode of processing.
This study further emphasizes the clinical value of targeting abstract thought and
training patients to adopt a more concrete processing style. Recent studies that
implemented concreteness training in therapy have found positive effects on
dysphoria (Watkins, Baeyens, & Read, 2009) and depression (Watkins et al., 2012).
Also, Stöber and Borkovec (2002) reported that successful cognitive therapy for
generalized anxiety disorder produced significant reductions in abstract thinking. Our
study promotes concreteness training as a possible valuable transdiagnostic
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 25
therapeutic tool because of the effect the processing styles have on generalization
which is a common underlying factor in several emotional disorders (Hermans et al.,
2013). Future research could thus also focus on the effects that these cognitive
therapies (concreteness training) have on (over)-generalization.
In sum, this study found that for more dysphoric adolescents, manipulating
processing style (abstract vs. concrete) has an impact on negative generalization in a
human conditioning paradigm, such that a concrete thinking mode might decrease
negative generalization. As such, our results are in line with the hypothesis that
abstract thought is an important mechanism affecting the degree of generalization in
response to emotional events (Watkins, 2008). To date, there are only very few
studies that have examined cognitive factors that may influence generalization (see
Hermans et al., 2013). We experimentally tested whether abstract thought could be
such a possible cognitive factor that influences generalization. Our results show that
this generalization might be one way in which abstract thought could have a negative
impact on emotional symptoms or complaints. Hence, this study further emphasizes
the need to study abstract processing as a potentially important (transdiagnostic)
marker, and highlights the need to better understand the effect that this processing
style has on generalization.
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 26
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ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 32
Figure 1. Stimuli used in the study: The CS+, the CS- and the 7 GSs, for half the
participants, the CS+, the CS- and the corresponding GSs were reversed.
CS+ CS- GS1
GS7 GS4 GS4
GS2 GS6
GS3 GS5
GS5 GS3
GS7 GS1
GS6 GS2
CS- CS+
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 33
Figure 2. Mean US-expectancy ratings for Trial 1 – 5 in the acquisition phase and
CS+, GS1, GS2, GS3, GS4, GS5, GS6, GS7 and CS- during the generalization test
phase (error bars denote 1 standard error).
0
1
2
3
4
5
6
7
8
9
10
Trial 1 Trial 2 Trial 3 Trial 4 Trial 5
Exp
ecta
ncy
Rati
ng
Acquisition
CS+/Abs.
CS+/Con.
CS-/Abs.
CS-/Con.
0
1
2
3
4
5
6
7
8
9
10
CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CS-
Exp
ecta
ncy
Rati
ng
Stimulus
Generalization
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 34
Figure 3. Mean US-expectancy ratings for CS+, GS1, GS2, GS3, GS4, GS5, GS6,
GS7 and CS- during the generalization test phase for the abstract and concrete
induction in a higher and lower dysphoric group based on a median-split procedure
(error bars denote 1 standard error).
0
2
4
6
8
10
CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CS-
Ex
pe
cta
ncy
Ra
tin
g
Stimulus
Abstract/High Dysphoric
0
2
4
6
8
10
CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CS-
Ex
pe
cta
ncy
Ra
tin
g
Stimulus
Concrete/High Dysphoric
0123456789
10
CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CS-
Ex
pe
cta
ncy
Ra
tin
g
Stimulus
Abstract/Low Dysphoric
0
2
4
6
8
10
CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CS-
Ex
pe
cta
ncy
Ra
tin
g
Stimulus
Concrete/Low Dysphoric
ABSTRACT THOUGHT AND NEGATIVE GENERALIZATION 35
Table 1
Correlations, means and standard deviations of study measures 1 2 3 M SD Range
1. DASS (depression) – 6.79 6.31 0-26
2. PTQ .39* – 32.12 9.43 10-57
3. Manipulation-check -.20 .13 – 2.75 1.10 1-5
Abstract M (SD) 7.00
(7.33)
29.59
(9.74)
2.66
(1.12)
Concrete M (SD) 6.56
(5.09)
34.71
(8.46)
2.85
(1.09)
Notes: *p < .001. All p-values are two-tailed.