Abstract Thinking about Negative Events in Dysphoric ... - KU Leuven

Journal of Experimental Psychopathology JEP Volume 5 (2014), Issue 3, 314-328 ISSN 2043-8087 / DOI:10.5127/jep.037913

Abstract Thinking about Negative Events in Dysphoric Students Leads to Negative Generalization Jens Van Lier, Bram Vervliet, Koen Vanbrabant, Bert Lenaert, & Filip Raes KU Leuven

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. © Copyright 2014 Textrum Ltd. All rights reserved. Keywords: Rumination; Worry; Abstract Repetitive Thinking; Generalization; Transdiagnostic Correspondence to: Jens Van Lier, Centre for the Psychology of Learning and Experimental Psychopathology , University of Leuven , Tiensestraat 102, B - 3000 Leuven. Email: [email protected] Received 22-Aug-2013; received in revised form 10-Jun-2014; accepted 20-Jun-2014

Journal of Experimental Psychopathology, Volume 5 (2014), Issue 3, 314-328

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Table of Contents Introduction Method Participants Materials Training materials for abstract and concrete processing mode (Moberly & Watkins, 2006). Generalization paradigm Perseverative Thinking Questionnaire (PTQ; Ehring, Zetsche, Weidacker, Wahl, Schönfeld & Ehlers, 2011) Depression Anxiety Stress Scales (DASS 21) Procedure Data Analysis Results Participant Characteristics Pre-acquisition Acquisition Generalization Test Negative Generalization Neutral Generalization PTQ Valence Discussion Acknowledgements References

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 selfpredicted 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 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


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was also one of the major contributors in the area of transdiagnostic rumination research (e.g., Aldao, NolenHoeksema, & Schweizer, 2010; McLaughlin & Nolen-Hoeksema, 2011; 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 (Aldao et al., 2010; Ehring & Watkins, 2008; Harvey, Watkins, Mansell, & Shafran, 2004; McLaughlin & Nolen-Hoeksema, 2011). 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., 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 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,


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studies have found that these abstract thought manipulations often only 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 et al. (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 (SintJozefscollege, 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 ethics committee of the University of Leuven. Written informed consent was obtained from all participants 1.

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 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

1

In Belgium, where the experiment was conducted, age of consent is 16.


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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 served as the CS+. All stimuli were presented in the middle of the computer screen on a black background.

CS+ CS-

GS1 GS7

GS2 GS6

GS3 GS5

GS5 GS3

GS6 GS2

GS7 GS1

CSCS+

GS4 GS4

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.

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.”


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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 angry 2. 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 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 preacquisition 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. 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

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.


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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), 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 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 betweensubjects 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 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.


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Results Participant Characteristics Means, standard deviations, scoring ranges and correlations for all variables included are presented in Table 1: Correlations, means and standard deviations of study measures. 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. Table 1: Correlations, means and standard deviations of study measures 1 1. DASS (depression)

2

3

– *

2. PTQ

.39

–

3. Manipulation-check

−.20

.13

–

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)

M

SD

Range

6.79

6.31

0-26

32.12

9.43

10-57

2.75

1.10

1-5

*

Notes: p < .001. All p-values are two-tailed.

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 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 betweensubject 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 Test 3 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+

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.


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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.

Acquisition 10

Expectancy Rating

9 8 7 6

CS+/Abs.

5

CS+/Con.

4

CS-/Abs.

3

CS-/Con.

2 1 0 Trial 1

Trial 2

Trial 3

Trial 4

Trial 5

Generalization 10

Expectancy Rating

9 8 7 6 5 4 3 2 1 0 CS+

GS1

GS2

GS3

GS4

GS5

GS6

GS7

CS-

Stimulus

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). 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). 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-

4

The excluded participants did not differ from the included participants for demographics, PTQ, DASS-Depression and manipulation check.


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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.

Abstract/High Dysphoric

Concrete/High Dysphoric 10

8

Expectancy Rating

Expectancy Rating

10

6 4 2 0

8 6 4 2 0

CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CSStimulus

CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CSStimulus

Concrete/Low Dysphoric

Abstract/Low Dysphoric 10 Expectancy Rating

Expectancy Rating

10 8 6 4 2 0 CS+GS1GS2GS3GS4GS5GS6GS7 CSStimulus

8 6 4 2 0 CS+ GS1 GS2 GS3 GS4 GS5 GS6 GS7 CSStimulus

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).

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, ηp2 = .40, and a marginally significant cubic trend, F(1, 63) = 3.81, p = .06, ηp2 = .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


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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 A repeated measures ANOVA with Stimulus (CS+, GS1, GS2, GS3, GS4, GS5, GS6, GS7, CS−) as a withinsubject 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 always paired with a negative/failure event). This effect was not found for participants with lower levels of depressive symptoms. Klar et al. (1997) found that depressed individuals tend to generalize more across negative situations than nondepressed 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


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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 with positive stimuli or events, this could explain why non-depressed (compared to depressed) individuals generalized more across positive situations in Klar et al.’s 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 (Raes et al., 2008; Watkins & Teasdale, 2001). Therefore, our results might converge with the findings of OGM research (Lenaert et al. 2012; Raes et al., 2008; Watkins & Teasdale, 2001) 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 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 mode 5. 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 the concrete condition.

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.


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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 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.

Acknowledgements The authors would like to thank H. De Meyer and A. Kestens for their help with the data collection. 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)

References Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30, 217–237. http://dx.doi.org/10.1016/j.cpr.2009.11.004 Carver, C. S. (1998). Generalization, adverse events, and development of depressive symptoms. Journal of Personality, 66, 607–19. http://dx.doi.org/10.1111/1467-6494.00026 Carver, C. S., & Ganellen, R. J. (1983). Depression and components of self-punitiveness: High standards, selfcriticism, and overgeneralization. Journal of Abnormal Psychology, 92, 330–7. http://dx.doi.org/10.1037/0021843X.92.3.330 Beurs, E. de, van Dyck, R., Marquenie, L. A., Lange, A., & Blonk, R. W. B. (2001). De DASS: Een vragenlijst voor het meten van depressie, angst and stress [The DASS: A questionnaire for the measurement of depression, anxiety and stress]. Gedragstherapie, 34, 35-53.


327

Ehring, T., Raes, F., Weidacker, K., & Emmelkamp, P. M. G. (2012). Validation of the perseverative thinking questionnaire – Dutch version (PTQ-NL). European Journal of Psychological Assessment, 28, 102–108. http://dx.doi.org/10.1027/1015-5759/a000097 Ehring, T., & Watkins, E. R. (2008). Repetitive negative thinking as a transdiagnostic process. International Journal of Cognitive Therapy, 1, 192–205. http://dx.doi.org/10.1680/ijct.2008.1.3.192 Ehring, T., Zetsche, U., Weidacker, K., Wahl, K., Schönfeld, S., & Ehlers, A. (2011). The Perseverative Thinking Questionnaire (PTQ): Validation of a content-independent measure of repetitive negative thinking. Journal of Behavior Therapy and Experimental Psychiatry, 42, 225–32. http://dx.doi.org/10.1016/j.jbtep.2010.12.003 Fulford, D., Rosen, R. K., Johnson, S. L., & Carver, C. S. (2012). Negative Generalization and Symptoms of Anxiety Disorders. Journal of Experimental Psychopathology, 3, 62–68. http://dx.doi.org/10.5127/jep.019811 Harvey, A. G., Watkins, E., Mansell, W., & Shafran, R. (2004). Cognitive behavioural processes across psychological disorders. Oxford, UK: Oxford University Press. Hermans, D., Baeyens, F., & Vervliet, B. (2013). Generalization of acquired emotional responses. In M. D. Robinson, E. R. Watkins, & E. Harmon-Jones (Eds.), Handbook of cognition and emotion (pp. 117–134). New York: Guilford Press. Kinderman, P., Schwannauer, M., Pontin, E., & Tai, S. (2013). Psychological Processes Mediate the Impact of Familial Risk, Social Circumstances and Life Events on Mental Health. PLoS ONE, 8, e76564. http://dx.doi.org/10.1371/journal.pone.0076564 Klar, Y., Gabai, T., & Baron, Y. (1997). Depression and generalization about the future: Who overgeneralizes what? Personality and Individual Differences, 22, 575–584. doi:10.1016/S0191- 8869(96)00186-9 Lenaert, B., Claes, S., Raes, F., Boddez, Y., Joos, E., Vervliet, B., Hermans, D. (2012). Generalization of conditioned responding: Effects of autobiographical memory specificity. Journal of Behavior Therapy and Experimental Psychiatry, 43, S60–S66. http://dx.doi.org/10.1016/j.jbtep.2010.12.010 Lissek, S., Biggs, A. L., Rabin, S. J., Cornwell, B. R., Alvarez, R. P., Pine, D. S., & Grillon, C. (2008). Generalization of conditioned fear-potentiated startle in humans: Experimental validation and clinical relevance. Behaviour Research and Therapy, 46, 678–87. http://dx.doi.org/10.1016/j.brat.2008.02.005 Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales (Second edition). Sydney: Psychology Foundation. Marigold, D. C., Holmes, J. G., & Ross, M. (2007). More Than Words : Reframing Compliments From Romantic Partners Fosters Security in Low Self-Esteem Individuals. Journal of Personality and Social Psychology, 92, 232–248. http://dx.doi.org/10.1037/0022-3514.92.2.232 McLaughlin, K., & Nolen-Hoeksema, S. (2011). Rumination as a transdiagnostic factor in depression and anxiety. Behaviour Research and Therapy, 49, 186–93. http://dx.doi.org/10.1016/j.brat.2010.12.006 Moberly, N. J., & Watkins, E. R. (2006). Processing Mode Influences the Relationship Between Trait Rumination and Emotional Vulnerability. Behavior Therapy, 37, 281–291. http://dx.doi.org/10.1016/j.beth.2006.02.003 Nolen-hoeksema, S., & Watkins, E. R. (2011). A Heuristic for Developing Transdiagnostic Models of Psychopathology : Explaining Multifinality and Divergent Trajectories. Perspectives on Psychological Science. http://dx.doi.org/10.1177/1745691611419672 Raes, F., Hermans, D., Williams, J. M. G., Beyers, W., Brunfaut, E., & Eelen, P. (2006). Reduced autobiographical memory specificity and rumination in predicting the course of depression. Journal of abnormal psychology, 115, 699–704. http://dx.doi.org/10.1037/0021-843X.115.4.699 Raes, F., Watkins, E. R., Williams, J. M. G., & Hermans, D. (2008). Non-ruminative processing reduces overgeneral autobiographical memory retrieval in students. Behaviour Research and Therapy, 46, 748–56. http://dx.doi.org/10.1016/j.brat.2008.03.003 Raes, F. (2012). Repetitive negative thinking predicts depressed mood at 3-year follow-up in students. Journal of Psychopathology and Behavioral Assessment, 34, 497–501. http://dx.doi.org/10.1007/s10862-012-9295-4 Rimes, K. A., &Watkins, E. (2005). The effects of self-focused rumination on global negative self-judgments in depression. Behaviour Research and Therapy, 43, 1673–1681. http://dx.doi.org/10.1016/j.brat.2004.12.002 Spruyt, A., Clarysse, J., Vansteenwegen, D., Baeyens, F., & Hermans, D. (2010). Affect 4.0: a free software package for implementing psychological and psychophysiological experiments. Experimental Psychology, 57, 36–45. http://dx.doi.org/10.1027/1618-3169/a000005


328

Stöber, J., & Borkovec, T. D. (2002). Reduced concreteness of worry in generalized anxiety disorder: Findings from a therapy study. Cognitive Therapy and Research, 26, 89–96. http://dx.doi.org/10.1023/A:1013845821848 Takano, K., & Tanno, Y. (2010). Concreteness of thinking and self-focus. Consciousness and Cognition, 19, 419– 425. http://dx.doi.org/10.1016/j.concog.2009.11.010 Treynor, W., Gonzalez, R., & Nolen-Hoeksema, S. (2003). Rumination reconsidered: A psychometric analysis. Cognitive Therapy and Research, 27, 247–259. http://dx.doi.org/10.1023/A:1023910315561 Trope, Y., & Liberman, N. (2003). Temporal construal. Psychological Review, 110, 403–421. http://dx.doi.org/10.1037/0033-295X.110.3.403 van den Heuvel, T. J., Derksen, J. J. L., Eling, P. A. T. M., & van der Staak, C. P. F. (2012). An investigation of different aspects of overgeneralization in patients with major depressive disorder and borderline personality disorder. British Journal of Clinical Psychology, 51, 376–395. http://dx.doi.org/10.1111/j.20448260.2012.02034.x Vervliet, B., Kindt, M., Vansteenwegen, D., & Hermans, D. (2010). Fear generalization in humans: Impact of prior non-fearful experiences. Behaviour Research and Therapy, 48, 1078–1084. http://dx.doi.org/10.1016/j.brat.2010.07.002 Watkins, E. (2004). Adaptive and maladaptive ruminative self-focus during emotional processing. Behaviour Research and Therapy, 42, 1037–52. http://dx.doi.org/10.1016/j.brat.2004.01.009 Watkins, E. (2008). Constructive and unconstructive repetitive thought. Psychological Bulletin, 134, 163–206. doi:10.1037/0033-2909.134.2.163 http://dx.doi.org/10.1037/0033-2909.134.2.163 Watkins, E. (2011). Dysregulation in level of goal and action identification across psychological disorders. Clinical Psychology Review, 31, 260–278. http://dx.doi.org/10.1016/j.cpr.2010.05.004 Watkins, E. R., Baeyens, C. B., & Read, R. (2009). Concreteness training reduces dysphoria: proof-of-principle for repeated cognitive bias modification in depression. Journal of Abnormal Psychology, 118, 55–64. http://dx.doi.org/10.1037/a0013642 Watkins, E., & Moulds, M. (2005). Distinct modes of ruminative self-focus: impact of abstract versus concrete rumination on problem solving in depression. Emotion, 5, 319–28. http://dx.doi.org/10.1037/1528-3542.5.3.319 Watkins, E., & Moulds, M. L. (2007). Reduced concreteness of rumination in depression: A pilot study. Personality and Individual Differences, 43, 1386–1395. http://dx.doi.org/10.1016/j.paid.2007.04.007 Watkins, E. R., Taylor, R. S., Byng, R., Baeyens, C., Read, R., Pearson, K., & Watson, L. (2012). Guided self-help concreteness training as an intervention for major depression in primary care : a Phase II randomized controlled trial. Psychological Medicine, 1359–1371. http://dx.doi.org/10.1017/S0033291711002480 Watkins, E., & Teasdale, J. D. (2001). Rumination and Overgeneral Memory in Depression : Effects of Self-Focus and Analytic Thinking. Journal of Abnormal Psychology, 110, 353–357. doi:10.1037//0021-843X.110.2.353 Watkins, E., & Teasdale, J. D. (2004). Adaptive and maladaptive self-focus in depression. Journal of Affective Disorders, 82, 1–8. http://dx.doi.org/10.1016/j.jad.2003.10.006 Zisook, S., Lesser, I., Stewart, J.W.,Wisniewski, S. R., Balasubramani, G. K., Fava, M., et al. (2007). Effect of age at onset on the course of major depressive disorder. The American Journal of Psychiatry, 164,1539–1546. http://dx.doi.org/10.1176/appi.ajp.2007.06101757