Personality and Mental Health 9: 58–65 (2015) Published online 1 October 2014 in Wiley Online Library (wileyonlinelibrary.com) DOI 10.1002/pmh.1276
Depressive rumination and experiential avoidance: A task based exploration
JUSTIN THOMAS, MONIQUE RAYNOR AND DAVID RIBOTT, Department of Natural Science and Public Health, Zayed University, PO Box 4783, Abu Dhabi, United Arab Emirates ABSTRACT Depressive rumination has been conceptualized as being closely connected with experiential avoidance. Evidence supporting this hypothesis derives primarily from studies using self-report measures. The present study explores this idea using a task-based assessment of avoidance. College students (N = 100) rated their emotional responses to 60 computer-presented images (positive, negative and neutral). Response times for the image-rating task were surreptitiously recorded, along with Ruminative Response Scale and Beck Depression Inventory II scores. Rumination was correlated with faster response times for negative, but not positive or neutral images. These findings are interpreted as lending support to the experiential avoidance conceptualization of rumination; however, consideration is also given to a potentially synergistic interpretation implicating heightened threat monitoring. Copyright © 2014 John Wiley & Sons, Ltd. The response styles theory (RST) of depression began as an attempt to explain the female preponderance in major depressive disorder (MDD) (Nolen-Hoeksema, 1987). Implicating gender role socialization, the RST suggests that women are more likely to respond to negative affect by passively and repetitively focusing attention on the causes and consequences of low mood—in other words ruminating. Irrespective of gender, however, this ruminative response style has been found to exacerbate and prolong negative mood (Knowles, Tai, Christensen, & Bentall, 2005), and is thought to represent a cognitive vulnerability for MDD in both males and females (Just & Alloy, 1997) The RST has received much empirical support; experimental, cross-sectional and prospective studies have all found evidence supportive of the RST’s central claims. For example, the ruminative response style is predictive of MDD onset (Just &
Copyright © 2014 John Wiley & Sons, Ltd.
Alloy, 1997), more severe depressive episodes with poorer outcomes (Kuehner & Weber, 1999; Lam, Schuck, Smith, Farmer, & Checkley, 2003) and exacerbated/prolonged periods of negative affect within non-clinical samples (Morrow & NolenHoeksema, 1990). The evidence to date suggests that the ruminative response style is clearly implicated in the maintenance of MDD and also represents a cognitive vulnerability for the disorder. However, the specific mechanisms through which rumination promotes or maintains depressive states are less apparent. A greater understanding of such mechanisms will undoubtedly have important implications for psychological therapies. Several ideas about how rumination contributes to depressive states have been proposed, none of which are mutually exclusive. For instance, rumination is viewed as interfering with problem solving ability, thereby minimizing the likelihood of resolving issues that might ameliorate negative
9: 58–65 (2015) DOI: 10.1002/pmh
Rumination and experimental avoidance
affect. Similarly, rumination is viewed as activating negative memories, thereby biasing information processing and leading to a depressogenic cognitive style. Furthermore, this self-focused, perseverative thinking style potentially alienates people close to the sufferer, leading to greater isolation and reduced social support (Giorgio et al., 2010). While various strands of evidence lend support to each of the above-mentioned mechanisms, a more recent and slightly paradoxical idea is that rumination is actually a manifestation of experiential avoidance. Experiential avoidance is generally defined as an attempt to avoid unwanted aspects of internal experience, including unwanted thoughts, feelings and physiological states (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996). At face value rumination appears to be very much about experiential absorption, rather than avoidance, with the ruminating individual apparently overly focused on dysphoric thoughts and feelings. However, rumination may serve a subtle avoidant function whereby the recursive cognition enables the ruminator to avoid the experience of sadness. Crane (2009) describes rumination as a ‘smokescreen’, enabling clients to suppress or disconnect from difficult emotions. This idea of rumination serving a subtle avoidant function is highly resonant with the literature examining worry in the context of generalized anxiety disorders (GAD). In Borkovec’s (1994) model of GAD, worry is assigned an essentially avoidant function, where it is viewed as distracting individuals from deeper and perhaps more emotive issues. Like anxious worry, depressive rumination also tends to be perseverative, vague and verbal. Analogous to the role assigned to worry in GAD, depressive rumination perhaps helps individuals avoid the direct experience of sadness, whilst simultaneously giving the mistaken impression (smokescreen) that they are actually, in some way, processing their emotional experiences and dealing with their problems. Several lines of evidence support the experiential avoidance conceptualization of depressive rumination. Cross-sectional correlational studies report
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the anticipated relationship between various selfreport measures of experiential avoidance and rumination. Using an undergraduate student sample, Cribb, Moulds and Carter (2006) found self-report measures of rumination, and experiential avoidance to be significantly correlated, even after controlling for anxiety. Similarly, Moulds, Kandris, Starr and Wong (2007) report a similar study, where selfreported rumination, avoidance and depression are again all significantly correlated. In a transdiagnostic (PTSD & MDD) study, Morina (2011) explored rumination and experiential avoidance amongst war widows. In line with the experiential avoidance conceptualization of rumination, self-reported measures of rumination and experiential avoidance were significantly correlated with each other and also predicted the symptoms of prolonged grief, depression and posttraumatic stress. Another study attempted to explore the temporal relationship between experiential avoidance, rumination and mood (Dickson, Ciesla, & Reilly, 2012). In this study 78 participants (college students) completed daily assessments of rumination, sad and anxious affect, and cognitive avoidance (an aspect of experiential avoidance). Over the 7-day period laggedeffect multilevel models indicated that rumination and cognitive avoidance predicted increases in daily sadness levels. Again, both rumination and avoidance were significantly correlated, with further analysis suggesting that rumination mediated the effect of cognitive avoidance on sadness. The relatively few studies that explore the relationship between experiential avoidance and rumination have relied, almost invariably, on selfreport assessments. To date we can identify only one study exploring the experiential avoidance conceptualization of depressive rumination using a performance or task-based assessment of avoidance (Giorgio et al., 2010). This study implemented a dichotic listening task, originally developed by Laguna, Ham and Hope (2004) as a behavioral measure of avoidance in the context of chronic worry. In this task-based assessment of the rumination-avoidance hypothesis, 100 undergraduate students participated in a dichotic listening
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task, after receiving either a rumination or relaxation induction. Participants also completed selfreport assessments of rumination and avoidance. As with previous studies, the self-report measures confirmed the relationship between rumination status and avoidance; however, for the dichotic listening task no significant effects were found. Giorgio et al. suggest that their null findings might be explicable in terms of the task design. They note that most of the study’s participants performed relatively poorly on the dichotic listening task—a possible floor effect—making discrimination between the rumination and relaxation conditions difficult. Furthermore, Giorgio et al. did not look at the specific sub-factors of rumination previously identified by Treynor, Gonzalez and NolenHoeksema (2003). It is conceivable that these sub-factors, ‘brooding’ and the more constructive form of rumination termed ‘reflection’, may represent avoidant (brooding) and non-avoidant (reflection) aspects of rumination. The current study uses a novel, image-based, task to assess the relationship between experiential avoidance and depressive rumination, and also examines brooding and reflection independently. The image-based task involves asking participants to rate a set of images in terms of their emotional valence. The preselected images—a selection from the IAPS collection (Bradley & Lang, 2007)—depict either positive, negative or neutral scenes. It is hypothesized that higher levels of rumination will be associated with relatively faster response times when participants are rating negative, but not, positive or neutral images. One interpretation of such faster response times is that ruminators are selectively avoidant, quickly passing over the negative images, even in the absence of any time constraints.
Emirates (UAE). Participants each gave informed consent, and full ethical clearance for the study was prospectively obtained from the institution’s research ethics committee. All participants spoke Arabic as their first language, and females comprised 58.3% (N = 55) of the sample. The mean age of participants was 20.49 (SD = 1.96). Females (M = 20.94, SD = 1.54) were slightly older than males (M = 19.93, SD = 2.28); this age difference was statistically significant (t [98] = 2.63, p < .05) Measures All self-report measures were translated into Arabic and back translated by PhD-level faculty within the university’s Arabic language department, with additional input from a bilingual counseling psychologist and a consultant psychiatrist. Measures were presented to participants in dual language form, with items in English and Arabic alongside each other. Presentation in dual language form was deemed necessary within the present population, due to a known variability in language dominance (English/Arabic) amongst the student population. The language of tuition at the university is English.
Participants
Ruminative response styles scale (RRS). (NolenHoeksema, 1991): This 22-item self-report inventory assesses response styles to depressed mood. Respondents rate each of a series of thoughts and behaviors on a scale from 1 to 4 reflecting ascending frequency, from never to always. This scale has previously been found to have excellent psychometric properties in both English and Arabic (Knowles et al., 2005; Thomas & Altareb, 2012; Thomas & Bentall, 2002). In the present study the total rumination score was calculated, as were the previously identified subfactors, termed brooding and reflection (Treynor et al., 2003). The overall internal reliability for the RRS was high, α = .94. Similarly, internal reliability for the brooding and reflection subscales were also acceptable, α = .75 and .80, respectively.
Participants were an opportunity sample of 100 Emirati students taking an introductory psychology course at Zayed University in the United Arab
Beck depression inventory—II (BDI-II). (Beck, Steer & Brown, 1996): This 21-item self-report
Method
Copyright © 2014 John Wiley & Sons, Ltd.
9: 58–65 (2015) DOI: 10.1002/pmh
Rumination and experimental avoidance
Table 1: Mean valence ratings and response times to images by gender Positive images
Valence rating Response timea a
Male Female Male Female
Neutral images
Negative images
M
SD
M
SD
M
7.31 7.28 327.05 227.77
.92 .99 104.03 62.06
4.18 3.43 376.43 285.57
.91 1.00 142.42 80.85
2.53 2.23 303.52 259.08
SD .93 .76 98.19 69.33
All response times are reported in milliseconds.
Table 2: Correlations between rumination and image rating response times Positive Neutral Negative Positive Neutral RRS Brooding
.07
.31 .17
a
RRS .31** .00 .06
Brooding Reflection .19* .05 .04 .63**
.24** .02 .13 .73** .130
*p < .05. **p < .01. a RRS = Ruminative response scale
inventory assesses the severity and intensity of depressive symptoms. Each item reflects either a cognitive or somatic-affective symptom of depression; items are rated from 0 to 3, with higher scores reflecting heightened symptom severity. Amongst North American college students and hospital outpatients the BDI-II was found to have high internal consistency, the coefficient alphas were .93 and .92, respectively (Beck et al., 1996). Subsequent studies of the BDI-II’s psychometric properties report favourably on the instrument’s reliability and validity in various contexts spanning several nations (Al-Musawi, 2001; Osman, Kopper, Barrios, Gutierrez, & Bagge, 2004; Sprinkle et al., 2002; Thomas & Altareb, 2012). In the present study the internal reliability for the BDI-II was α = .84 Computerized image rating task (IRT). The IRT uses a custom-built software application to present images and capture participant’s responses. The
Copyright © 2014 John Wiley & Sons, Ltd.
paper’s first author, using the visual basic.net framework, was involved in the development of this software application. IRT presents participants with a series of 60 digital images (N = 20 positive, N = 20 negative, and N = 20 neutral), along with the following standardized emotional valence rating instructions: How negative or positive does the image make you feel? If the image has a very positive effect on you, for example it makes you feel happy, amused or excited then give it a high score, with 20 being the maximum score. If the image has a negative effect, for example, making you feel sad, scared or angry then rate it with a lower score, 0 being the most negative possible score. Please take as long as you need to complete this task; there are no time constraints.
The image rating instructions given to participants are an adaptation and Arabic translation of those used by Mathews and Barch (2006). Participants respond by indicating their emotional response along a 20-point visual analogue scale, with 0 representing extreme negative, and 20 representing extreme positive. Responses to each image are made by pressing the left or right arrow keys on the computer keyboard to indicate the degree of negative or positive valence. After each image presentation a blank white screen is displayed for 10 s, and then the next trial is presented; image presentation order is randomized by the IRT application. Unbeknownst to the participants the IRT application also records the time—in milliseconds—taken to arrive at a rating for each image.
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Images for the IRT were selected from the widely used International Affective Picture System known as IAPS (Bradley & Lang, 2007). There is extensive normative data for this set of images, so a computer algorithm was used to select 60 images based on the existing date. Each image had previously been rated for valence (10 positive, 1 negative) and arousal (10 high, 1 low). The algorithm used in the present study selected the top 20 positive and negative images (valence), with an arousal rating of between 3 and 5, also selecting 20 neutral images (valence = 5) with arousal ratings between 3 and 5. Using images with medium to low arousal levels prevented the inclusion of pornographic or violent images. One-way ANOVA and post hoc tests confirmed that the positive, negative and neutral images all differed significantly form each other in terms of valence, and did not differ significantly in terms of arousal. Further details of the IRT and the final images selected are available on request from the corresponding author. Procedure All participants were tested individually in an office/psychology lab using a 17 IBM laptop computer. It is very important to note, all participants were given standardized instructions, which included informing then that they could take as long as they needed to complete the tasks, and that their anonymity was assured. Also, prior to commencement, all participants performed a mock trial with the experimenter present to ensure that the specifics of the image-rating task had been fully understood. After ensuring comprehension, the experimenter left the participant alone to view and responded to the IRT images. Upon completion of the IRT, participants worked alone to complete the RRS followed by the BDI-II. Participants were fully debriefed on completion and offered the opportunity to receive their individual results via email. Plan for data analyses Demographic differences were examined using T-test comparisons for continuous variables (e.g. age) Similarly, T-test comparisons were used to examine
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gender differences in response times for the imagerating task, rumination and depressive symptoms. A partial correlational matrix explored the relationships between rumination, depression and response times to negative, positive and neutral images (controlling for gender). Chi-square analyses for categorical variables (e.g. gender) was used to explore the composition of the high and low rumination groups, while univariate general linear models were used to examine differences between these groups (fixed factor) in terms of response times to affective images (dependent variable) including gender as a covariate. Results Gender differences Males and females did not differ significantly in their valence ratings of positive and negative images. They did, however, differ significantly in terms of their response latency; males were significantly slower than females, in their responses to negative images (t [98] = 2.64, p < .02) positive images (t [50.277] = 4.38, p < .001) and neutral images (t [49.39] = 3.39, p < .001). There were no significant gender differences for depressive symptoms (Males: M = 12.86, SD = 7.95. Females: M = 15.28, SD = 8.19), although the trend was toward higher levels of depressive symptoms amongst females. Similarly, females reported higher levels of rumination (M = 53.90, SD = 12.17) compared to males (M = 50.06, SD = 11.54). These differences were statistically significant t [98] = 1.62, p < .05 (Table 1). Correlational analysis As expected, depressive symptom scores were positively correlated with rumination (r = .64, p < .001); this was true also for the rumination subscales: brooding (r = .62, p < .001) and reflection (r = .26, p < .05). Depression scores were not correlated with image rating response times. However, positive image ratings were inversely correlated with depression scores; that is, those reporting higher levels of
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depressive symptoms tended to be less enthusiastic in their ratings of positive images (r = .29, p < .001). As previously mentioned, males were significantly slower at rating images across all affective conditions, and consequently, gender was correlated with response times. Therefore, to test the main hypothesis, partial correlations were calculated controlling for gender. As hypothesized, rumination was inversely correlated with response times for negative images; in other words, higher rumination tended to be associated with faster responses to negative images. This association was unique, in that, rumination did not correlate with response times for either positive or neutral images (Table 2). Discussion The current study provides further support for the experiential avoidance conceptualization of rumination. The correlational analysis revealed that higher rumination scores were associated with faster response times when rating the emotional impact of negative, but not, positive or neutral images. Furthermore, depression scores were also uncorrelated with image rating response times, ruling out a mood congruent facilitation interpretation. Additionally, a high–low rumination analysis produced the same pattern of results, in that those in the high rumination condition (upper quartile) were significantly faster when rating the emotional impact of negative images, compared with individuals in the low rumination condition, with neither group differing significantly in response to neutral or positive images. This would suggest that, irrespective of depressive symptom levels or gender, individuals higher in rumination tended to devote less time to the consideration of negative images, performing the valence rating with greater speed when negative, rather than neutral or positive images were presented. One (our) interpretation of this finding is that individuals higher in rumination are demonstrating an avoidant response, more quickly
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moving on from the negative scenes depicted in the image. There are, however, alternative interpretations for this finding; perhaps those high in rumination are more rapidly able to detect and classify images with a negative valence, a kind of perceptual set, although we might expect depressive symptoms to be a better a predictor if this were solely the case—in the present study depressive symptoms were not predictive of response times in any condition. Taking the avoidant interpretation for the present findings, we add task-based support to the experiential avoidance conceptualization of rumination. Most previous explorations of this idea have been based on self-report measures (Cribb et al., 2006; Dickson et al., 2012; Morina, 2011; Moulds et al., 2007). The only other previous task-based attempt (we are aware of) to explore the avoidance used a dichotic listening task, which essentially resulted in a floor effect. Furthermore, this earlier task-based study did not analyse the sub-factors of rumination (Giorgio et al., 2010). The present study addressed this limitation and included an exploration of rumination that included the brooding and reflection subscales, both of which were associated with the avoidant response, that is, more rapid evaluations of negative images. The significant difference between males and females in terms of the rating task—across all affective categories—is hard to explain, although this was controlled for in the statistical analysis. One explanation for these gender differences might be based on the study population, in that, in the United Arab Emirates, female participation and academic performance within tertiary education far outstrip that of males (Thomas, Al-Marzooqi, & Raynor, 2012). The slower response times for males might be a reflection of lower levels of motivation or technological familiarity or both. The one previous study using a task based assessment of experiential avoidance did not report similar gender differences (Giorgio et al., 2010). While the present study tentatively supports the idea that rumination is associated with experiential avoidance, alternative explanations might be
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considered. The Self-Regulatory Executive Function (SREF) model of psychological disorder (Wells, 2009), for example, provides a good framework for interpreting the present findings. Central to the S-REF model is the cognitive attention syndrome (CAS), which is viewed as comprising numerous ultimately unhelpful coping strategies (Fisher & Wells, 2009). Within this framework, a faster response to negative images could simply reflect a negative bias arising from heightened threat monitoring. It is also possible that heightened threat monitoring (noticing the image’s negative valence) and avoidance (moving quickly away from the image) operate synergistically. It would be particularly important for future studies attempting task-based assessments of experiential avoidance to distinguish between automatic attentional bias, and intentional avoidance. Perhaps a two-phase assessment could be employed where a valence identification task precedes the valence-rating task. The valence identification task is framed so participants are encouraged to respond as quickly as possible. This would tap the idea of heightened threat monitoring. Then the surreptitiously timed valence-rating task would be performed, with faster completion implying avoidance. This would still not be irrefutable; however, this underscores the inherent difficulty in task-based assessments of complex psychological constructs such as experiential avoidance. The study, while supporting the experiential avoidance hypothesis, also has several important limitations. First, the reliance on university students limits the overall generalizability of the findings. The participants in the study were not diagnosed with any mood or anxiety disorders. However, much previous research exploring attentional bias in emotional disorders has been based on nonclinical populations, and has ultimately proved useful in the development of models of psychopathology (Browning, Holmes, & Harmer, 2010). Similarly, the use of nonclinical participants eliminates potential confounds associated with psychotropic medication. However, there is clearly a benefit in attempting to replicate the
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present study within a clinical population. In addition to exploring a clinical sample, future studies might consider including an assessment of the metacognitions associated with avoidance. A further extension would be to include a memory task. One might hypothesize that high ruminators avoid negative images and, therefore, could be expected to exhibit poorer performance on a subsequent memory (incidental learning) task. Over a longer period of time, such an avoidant style, might equate to poorer episodic/autobiographical memory, as has been observed in the context of depression. Further experimental explorations of the experiential avoidance conceptualization of rumination are merited. Such studies may have important implications for the further development and refinement of cognitive therapy for depression, and other psychological complaints characterized by rumination. Acknowledgement This project was supported by a grant (RSA-110800402) from the National Research Foundation (UAE). References Al-Musawi, N. M. (2001). Psychometric Properties of the Beck Depression Inventory–II With University Students in Bahrain. Journal of Personality Assessment, 3(77), 568–579. Beck, A. T., Steer, R. A., & Brown, G. (1996). BDI-II Manual. San Antonio: Harcourt Brace & Company. Borkovec, T. D. (1994). The nature, functions, and origins of worry. In G. C. L. Davey, & F. Tallis (Eds.), Worrying: perspectives on theory, assessment, and treatment. Oxford: John Wiley & Sons. Bradley, M. M., & Lang, P. J. (2007). The International Affective Picture System (IAPS) in the study of emotion and attention. In J. A. Coan & J. J. B. Allen (Eds.), Handbook of Emotion Elicitation and Assessment (pp. 29–46). Oxford: Oxford University Press. Browning, M., Holmes, E. A., & Harmer, C. J. (2010). The modification of attentional bias to emotional information: a review of the techniques, mechanisms, and relevance to emotional disorders. Cognitive, Affective, & Behavioral Neuroscience, 10(1), 8–20.doi:10.3758/CABN.10.1.8.
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Crane, R. (2009). Mindfullness-Based Cognitive Therapy. NY: Routledge. Cribb, G., Moulds, M., & Carter, S. (2006). Rumination and experiential avoidance in depression. Behavior Change, 23, 165–176. doi:10.1375/bech.23.3.165. Dickson, K. S., Ciesla, J. A., & Reilly, L. C. (2012). Rumination, worry, cognitive avoidance, and behavioral avoidance: examination of temporal effects. Behaviour Therapy, 43(3), 629–640. doi: 10.1016/j.beth.2011.11.002. Fisher, P., & Wells, A. (2009). Metacognitive Therapy. New York: Routledge. Giorgio, J. M., Sanflippo, J., Kleiman, E., Reilly, D., Bender, R. E., Wagner, C. A., & Alloy, L. B. (2010). An experiential avoidance conceptualization of depressive rumination: three tests of the model. Behaviour Research and Therapy, 48, 1021–1031. Hayes, S. C., Wilson, K. G., Gifford, E. V., Follette, V. M., & Strosahl, K. (1996). Experiential avoidance and behavioral disorders: a functional dimensional approach to diagnosis and treatment. Journal of Consulting and Clinical Psychology and Psychotherapy: Theory, Research and Practice, 64, 1152e–1168. Just, N., & Alloy, L. B. (1997). The Response Styles Theory of Depression: Test and an Extension of the Theory. Journal of Abnormal Psychology, 106(2), 221–229. Knowles, R., Tai, S., Christensen, I., & Bentall, R. (2005). Coping with depression and vulnerability to mania: a factor analytic study of the Nolen-Hoeksema (1991) Response Styles Questionnaire. British Journal of Clinical Psychology, 44(Pt 1), 99–112. Kuehner, C., & Weber, I. (1999). Responses to depression in unipolar depressed patients: an investigation of NolenHoeksema’s response styles theory. Psychological Medicine, 29(6), 1323–1333. Laguna, L. B., Ham, L. S., & Hope, D. A. (2004). Chronic worry as avoidance of arousal. Cognitive Therapy and Research, 28, 269–281. Lam, D., Schuck, N., Smith, N., Farmer, A., & Checkley, S. (2003). Response style, interpersonal difficulties and social functioning in major depressive disorder. Journal of Affective Disorders, 75(3), 279–283. Mathews, J. R., & Barch, D. M. (2006). Episodic memory for emotional and non-emotional words in individuals with anhedonia. Psychiatry Research, 143, 121–133. Morina, N. (2011). Rumination and Avoidance as Predictors of Prolonged Grief, Depression, and Posttraumatic Stress in Female Widowed Survivors of War. The Journal of Nervous and Mental Disease, 199(12): 921–927.
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Morrow, J., & Nolen-Hoeksema, S. (1990). Effects of Responses to Depression on the Remediation of Depressive Affect. Journal of Personality & Social Psychology March, 58(3), 519–527. Moulds, M., Kandris, E., Starr, S., & Wong, A. C. (2007). The relationship between rumination, avoidance and depression in a non-clinical sample. Behaviour Research Therapy, 45(2), 251–261. Nolen-Hoeksema, S. (1987). Sex Differences in Unipolar Depression: Evidence and Theory. Psychological Bulletin, 101 (2), 259–282. Nolen-Hoeksema, S. (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100(4), 569–582. Osman, A., Kopper, B. A., Barrios, F., Gutierrez, P. M., & Bagge, C. L. (2004). Reliability and validity of the Beck Depression Inventory-II with adolescent psychiatric inpatients. Psychological Assessment, 16(2), 120–132. Sprinkle, S. D., Lurie, D., Insko, S. L., Atkinson, G., Jones, G. L., Logan, A. R., & Bissada, N. N. (2002). Criterion Validity, Severity Cut Scores, and Test-Retest Reliability of the Beck Depression Inventory-II in a University Counseling Center Sample. Journal of Counseling Psychology, 49(3), 381–385. Thomas, J., Al-Marzooqi, A., & Raynor, M. (2012). Marital status and gender as predictors of undergraduate academic performance: A United Arab Emirates Context. Learning and Teaching in the Gulf, 9(2). Thomas, J., & Altareb, B. (2012). Cognitive vulnerability to depression: An exploration of dysfunctional attitudes and response styles to dysphoric mood in UAE nationals. Psychology and Psychotherapy: Theory, Research and Practice, 85(1), 117–121. doi:10.1111/j.2044-8341.2011.02015. Thomas, J., & Bentall, R. (2002). Hypomanic traits and response styles to depression. British Journal of Clinical Psychology, 41(Pt 3), 309–313. Treynor, W., Gonzalez, R., & Nolen-Hoeksema, S. (2003). Rumination Reconsidered: a Psychometric Analysis. Cognitive Therapy and Research, 27(3), 247–259. Wells, A. (2009). Metacognitive Therapy for Anxiety and depression. NY: Guilford Press.
Address correspondence to: Dr Justin Thomas— Assistant Professor, Department of Natural Science and Public Health at Zayed University, PO Box 144534, United Arab Emirates. Email: justin. [email protected]
9: 58–65 (2015) DOI: 10.1002/pmh
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Depressive rumination and experiential avoidance: A task based exploration
JUSTIN THOMAS, MONIQUE RAYNOR AND DAVID RIBOTT, Department of Natural Science and Public Health, Zayed University, PO Box 4783, Abu Dhabi, United Arab Emirates ABSTRACT Depressive rumination has been conceptualized as being closely connected with experiential avoidance. Evidence supporting this hypothesis derives primarily from studies using self-report measures. The present study explores this idea using a task-based assessment of avoidance. College students (N = 100) rated their emotional responses to 60 computer-presented images (positive, negative and neutral). Response times for the image-rating task were surreptitiously recorded, along with Ruminative Response Scale and Beck Depression Inventory II scores. Rumination was correlated with faster response times for negative, but not positive or neutral images. These findings are interpreted as lending support to the experiential avoidance conceptualization of rumination; however, consideration is also given to a potentially synergistic interpretation implicating heightened threat monitoring. Copyright © 2014 John Wiley & Sons, Ltd. The response styles theory (RST) of depression began as an attempt to explain the female preponderance in major depressive disorder (MDD) (Nolen-Hoeksema, 1987). Implicating gender role socialization, the RST suggests that women are more likely to respond to negative affect by passively and repetitively focusing attention on the causes and consequences of low mood—in other words ruminating. Irrespective of gender, however, this ruminative response style has been found to exacerbate and prolong negative mood (Knowles, Tai, Christensen, & Bentall, 2005), and is thought to represent a cognitive vulnerability for MDD in both males and females (Just & Alloy, 1997) The RST has received much empirical support; experimental, cross-sectional and prospective studies have all found evidence supportive of the RST’s central claims. For example, the ruminative response style is predictive of MDD onset (Just &
Copyright © 2014 John Wiley & Sons, Ltd.
Alloy, 1997), more severe depressive episodes with poorer outcomes (Kuehner & Weber, 1999; Lam, Schuck, Smith, Farmer, & Checkley, 2003) and exacerbated/prolonged periods of negative affect within non-clinical samples (Morrow & NolenHoeksema, 1990). The evidence to date suggests that the ruminative response style is clearly implicated in the maintenance of MDD and also represents a cognitive vulnerability for the disorder. However, the specific mechanisms through which rumination promotes or maintains depressive states are less apparent. A greater understanding of such mechanisms will undoubtedly have important implications for psychological therapies. Several ideas about how rumination contributes to depressive states have been proposed, none of which are mutually exclusive. For instance, rumination is viewed as interfering with problem solving ability, thereby minimizing the likelihood of resolving issues that might ameliorate negative
9: 58–65 (2015) DOI: 10.1002/pmh
Rumination and experimental avoidance
affect. Similarly, rumination is viewed as activating negative memories, thereby biasing information processing and leading to a depressogenic cognitive style. Furthermore, this self-focused, perseverative thinking style potentially alienates people close to the sufferer, leading to greater isolation and reduced social support (Giorgio et al., 2010). While various strands of evidence lend support to each of the above-mentioned mechanisms, a more recent and slightly paradoxical idea is that rumination is actually a manifestation of experiential avoidance. Experiential avoidance is generally defined as an attempt to avoid unwanted aspects of internal experience, including unwanted thoughts, feelings and physiological states (Hayes, Wilson, Gifford, Follette, & Strosahl, 1996). At face value rumination appears to be very much about experiential absorption, rather than avoidance, with the ruminating individual apparently overly focused on dysphoric thoughts and feelings. However, rumination may serve a subtle avoidant function whereby the recursive cognition enables the ruminator to avoid the experience of sadness. Crane (2009) describes rumination as a ‘smokescreen’, enabling clients to suppress or disconnect from difficult emotions. This idea of rumination serving a subtle avoidant function is highly resonant with the literature examining worry in the context of generalized anxiety disorders (GAD). In Borkovec’s (1994) model of GAD, worry is assigned an essentially avoidant function, where it is viewed as distracting individuals from deeper and perhaps more emotive issues. Like anxious worry, depressive rumination also tends to be perseverative, vague and verbal. Analogous to the role assigned to worry in GAD, depressive rumination perhaps helps individuals avoid the direct experience of sadness, whilst simultaneously giving the mistaken impression (smokescreen) that they are actually, in some way, processing their emotional experiences and dealing with their problems. Several lines of evidence support the experiential avoidance conceptualization of depressive rumination. Cross-sectional correlational studies report
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the anticipated relationship between various selfreport measures of experiential avoidance and rumination. Using an undergraduate student sample, Cribb, Moulds and Carter (2006) found self-report measures of rumination, and experiential avoidance to be significantly correlated, even after controlling for anxiety. Similarly, Moulds, Kandris, Starr and Wong (2007) report a similar study, where selfreported rumination, avoidance and depression are again all significantly correlated. In a transdiagnostic (PTSD & MDD) study, Morina (2011) explored rumination and experiential avoidance amongst war widows. In line with the experiential avoidance conceptualization of rumination, self-reported measures of rumination and experiential avoidance were significantly correlated with each other and also predicted the symptoms of prolonged grief, depression and posttraumatic stress. Another study attempted to explore the temporal relationship between experiential avoidance, rumination and mood (Dickson, Ciesla, & Reilly, 2012). In this study 78 participants (college students) completed daily assessments of rumination, sad and anxious affect, and cognitive avoidance (an aspect of experiential avoidance). Over the 7-day period laggedeffect multilevel models indicated that rumination and cognitive avoidance predicted increases in daily sadness levels. Again, both rumination and avoidance were significantly correlated, with further analysis suggesting that rumination mediated the effect of cognitive avoidance on sadness. The relatively few studies that explore the relationship between experiential avoidance and rumination have relied, almost invariably, on selfreport assessments. To date we can identify only one study exploring the experiential avoidance conceptualization of depressive rumination using a performance or task-based assessment of avoidance (Giorgio et al., 2010). This study implemented a dichotic listening task, originally developed by Laguna, Ham and Hope (2004) as a behavioral measure of avoidance in the context of chronic worry. In this task-based assessment of the rumination-avoidance hypothesis, 100 undergraduate students participated in a dichotic listening
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task, after receiving either a rumination or relaxation induction. Participants also completed selfreport assessments of rumination and avoidance. As with previous studies, the self-report measures confirmed the relationship between rumination status and avoidance; however, for the dichotic listening task no significant effects were found. Giorgio et al. suggest that their null findings might be explicable in terms of the task design. They note that most of the study’s participants performed relatively poorly on the dichotic listening task—a possible floor effect—making discrimination between the rumination and relaxation conditions difficult. Furthermore, Giorgio et al. did not look at the specific sub-factors of rumination previously identified by Treynor, Gonzalez and NolenHoeksema (2003). It is conceivable that these sub-factors, ‘brooding’ and the more constructive form of rumination termed ‘reflection’, may represent avoidant (brooding) and non-avoidant (reflection) aspects of rumination. The current study uses a novel, image-based, task to assess the relationship between experiential avoidance and depressive rumination, and also examines brooding and reflection independently. The image-based task involves asking participants to rate a set of images in terms of their emotional valence. The preselected images—a selection from the IAPS collection (Bradley & Lang, 2007)—depict either positive, negative or neutral scenes. It is hypothesized that higher levels of rumination will be associated with relatively faster response times when participants are rating negative, but not, positive or neutral images. One interpretation of such faster response times is that ruminators are selectively avoidant, quickly passing over the negative images, even in the absence of any time constraints.
Emirates (UAE). Participants each gave informed consent, and full ethical clearance for the study was prospectively obtained from the institution’s research ethics committee. All participants spoke Arabic as their first language, and females comprised 58.3% (N = 55) of the sample. The mean age of participants was 20.49 (SD = 1.96). Females (M = 20.94, SD = 1.54) were slightly older than males (M = 19.93, SD = 2.28); this age difference was statistically significant (t [98] = 2.63, p < .05) Measures All self-report measures were translated into Arabic and back translated by PhD-level faculty within the university’s Arabic language department, with additional input from a bilingual counseling psychologist and a consultant psychiatrist. Measures were presented to participants in dual language form, with items in English and Arabic alongside each other. Presentation in dual language form was deemed necessary within the present population, due to a known variability in language dominance (English/Arabic) amongst the student population. The language of tuition at the university is English.
Participants
Ruminative response styles scale (RRS). (NolenHoeksema, 1991): This 22-item self-report inventory assesses response styles to depressed mood. Respondents rate each of a series of thoughts and behaviors on a scale from 1 to 4 reflecting ascending frequency, from never to always. This scale has previously been found to have excellent psychometric properties in both English and Arabic (Knowles et al., 2005; Thomas & Altareb, 2012; Thomas & Bentall, 2002). In the present study the total rumination score was calculated, as were the previously identified subfactors, termed brooding and reflection (Treynor et al., 2003). The overall internal reliability for the RRS was high, α = .94. Similarly, internal reliability for the brooding and reflection subscales were also acceptable, α = .75 and .80, respectively.
Participants were an opportunity sample of 100 Emirati students taking an introductory psychology course at Zayed University in the United Arab
Beck depression inventory—II (BDI-II). (Beck, Steer & Brown, 1996): This 21-item self-report
Method
Copyright © 2014 John Wiley & Sons, Ltd.
9: 58–65 (2015) DOI: 10.1002/pmh
Rumination and experimental avoidance
Table 1: Mean valence ratings and response times to images by gender Positive images
Valence rating Response timea a
Male Female Male Female
Neutral images
Negative images
M
SD
M
SD
M
7.31 7.28 327.05 227.77
.92 .99 104.03 62.06
4.18 3.43 376.43 285.57
.91 1.00 142.42 80.85
2.53 2.23 303.52 259.08
SD .93 .76 98.19 69.33
All response times are reported in milliseconds.
Table 2: Correlations between rumination and image rating response times Positive Neutral Negative Positive Neutral RRS Brooding
.07
.31 .17
a
RRS .31** .00 .06
Brooding Reflection .19* .05 .04 .63**
.24** .02 .13 .73** .130
*p < .05. **p < .01. a RRS = Ruminative response scale
inventory assesses the severity and intensity of depressive symptoms. Each item reflects either a cognitive or somatic-affective symptom of depression; items are rated from 0 to 3, with higher scores reflecting heightened symptom severity. Amongst North American college students and hospital outpatients the BDI-II was found to have high internal consistency, the coefficient alphas were .93 and .92, respectively (Beck et al., 1996). Subsequent studies of the BDI-II’s psychometric properties report favourably on the instrument’s reliability and validity in various contexts spanning several nations (Al-Musawi, 2001; Osman, Kopper, Barrios, Gutierrez, & Bagge, 2004; Sprinkle et al., 2002; Thomas & Altareb, 2012). In the present study the internal reliability for the BDI-II was α = .84 Computerized image rating task (IRT). The IRT uses a custom-built software application to present images and capture participant’s responses. The
Copyright © 2014 John Wiley & Sons, Ltd.
paper’s first author, using the visual basic.net framework, was involved in the development of this software application. IRT presents participants with a series of 60 digital images (N = 20 positive, N = 20 negative, and N = 20 neutral), along with the following standardized emotional valence rating instructions: How negative or positive does the image make you feel? If the image has a very positive effect on you, for example it makes you feel happy, amused or excited then give it a high score, with 20 being the maximum score. If the image has a negative effect, for example, making you feel sad, scared or angry then rate it with a lower score, 0 being the most negative possible score. Please take as long as you need to complete this task; there are no time constraints.
The image rating instructions given to participants are an adaptation and Arabic translation of those used by Mathews and Barch (2006). Participants respond by indicating their emotional response along a 20-point visual analogue scale, with 0 representing extreme negative, and 20 representing extreme positive. Responses to each image are made by pressing the left or right arrow keys on the computer keyboard to indicate the degree of negative or positive valence. After each image presentation a blank white screen is displayed for 10 s, and then the next trial is presented; image presentation order is randomized by the IRT application. Unbeknownst to the participants the IRT application also records the time—in milliseconds—taken to arrive at a rating for each image.
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Images for the IRT were selected from the widely used International Affective Picture System known as IAPS (Bradley & Lang, 2007). There is extensive normative data for this set of images, so a computer algorithm was used to select 60 images based on the existing date. Each image had previously been rated for valence (10 positive, 1 negative) and arousal (10 high, 1 low). The algorithm used in the present study selected the top 20 positive and negative images (valence), with an arousal rating of between 3 and 5, also selecting 20 neutral images (valence = 5) with arousal ratings between 3 and 5. Using images with medium to low arousal levels prevented the inclusion of pornographic or violent images. One-way ANOVA and post hoc tests confirmed that the positive, negative and neutral images all differed significantly form each other in terms of valence, and did not differ significantly in terms of arousal. Further details of the IRT and the final images selected are available on request from the corresponding author. Procedure All participants were tested individually in an office/psychology lab using a 17 IBM laptop computer. It is very important to note, all participants were given standardized instructions, which included informing then that they could take as long as they needed to complete the tasks, and that their anonymity was assured. Also, prior to commencement, all participants performed a mock trial with the experimenter present to ensure that the specifics of the image-rating task had been fully understood. After ensuring comprehension, the experimenter left the participant alone to view and responded to the IRT images. Upon completion of the IRT, participants worked alone to complete the RRS followed by the BDI-II. Participants were fully debriefed on completion and offered the opportunity to receive their individual results via email. Plan for data analyses Demographic differences were examined using T-test comparisons for continuous variables (e.g. age) Similarly, T-test comparisons were used to examine
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gender differences in response times for the imagerating task, rumination and depressive symptoms. A partial correlational matrix explored the relationships between rumination, depression and response times to negative, positive and neutral images (controlling for gender). Chi-square analyses for categorical variables (e.g. gender) was used to explore the composition of the high and low rumination groups, while univariate general linear models were used to examine differences between these groups (fixed factor) in terms of response times to affective images (dependent variable) including gender as a covariate. Results Gender differences Males and females did not differ significantly in their valence ratings of positive and negative images. They did, however, differ significantly in terms of their response latency; males were significantly slower than females, in their responses to negative images (t [98] = 2.64, p < .02) positive images (t [50.277] = 4.38, p < .001) and neutral images (t [49.39] = 3.39, p < .001). There were no significant gender differences for depressive symptoms (Males: M = 12.86, SD = 7.95. Females: M = 15.28, SD = 8.19), although the trend was toward higher levels of depressive symptoms amongst females. Similarly, females reported higher levels of rumination (M = 53.90, SD = 12.17) compared to males (M = 50.06, SD = 11.54). These differences were statistically significant t [98] = 1.62, p < .05 (Table 1). Correlational analysis As expected, depressive symptom scores were positively correlated with rumination (r = .64, p < .001); this was true also for the rumination subscales: brooding (r = .62, p < .001) and reflection (r = .26, p < .05). Depression scores were not correlated with image rating response times. However, positive image ratings were inversely correlated with depression scores; that is, those reporting higher levels of
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depressive symptoms tended to be less enthusiastic in their ratings of positive images (r = .29, p < .001). As previously mentioned, males were significantly slower at rating images across all affective conditions, and consequently, gender was correlated with response times. Therefore, to test the main hypothesis, partial correlations were calculated controlling for gender. As hypothesized, rumination was inversely correlated with response times for negative images; in other words, higher rumination tended to be associated with faster responses to negative images. This association was unique, in that, rumination did not correlate with response times for either positive or neutral images (Table 2). Discussion The current study provides further support for the experiential avoidance conceptualization of rumination. The correlational analysis revealed that higher rumination scores were associated with faster response times when rating the emotional impact of negative, but not, positive or neutral images. Furthermore, depression scores were also uncorrelated with image rating response times, ruling out a mood congruent facilitation interpretation. Additionally, a high–low rumination analysis produced the same pattern of results, in that those in the high rumination condition (upper quartile) were significantly faster when rating the emotional impact of negative images, compared with individuals in the low rumination condition, with neither group differing significantly in response to neutral or positive images. This would suggest that, irrespective of depressive symptom levels or gender, individuals higher in rumination tended to devote less time to the consideration of negative images, performing the valence rating with greater speed when negative, rather than neutral or positive images were presented. One (our) interpretation of this finding is that individuals higher in rumination are demonstrating an avoidant response, more quickly
Copyright © 2014 John Wiley & Sons, Ltd.
moving on from the negative scenes depicted in the image. There are, however, alternative interpretations for this finding; perhaps those high in rumination are more rapidly able to detect and classify images with a negative valence, a kind of perceptual set, although we might expect depressive symptoms to be a better a predictor if this were solely the case—in the present study depressive symptoms were not predictive of response times in any condition. Taking the avoidant interpretation for the present findings, we add task-based support to the experiential avoidance conceptualization of rumination. Most previous explorations of this idea have been based on self-report measures (Cribb et al., 2006; Dickson et al., 2012; Morina, 2011; Moulds et al., 2007). The only other previous task-based attempt (we are aware of) to explore the avoidance used a dichotic listening task, which essentially resulted in a floor effect. Furthermore, this earlier task-based study did not analyse the sub-factors of rumination (Giorgio et al., 2010). The present study addressed this limitation and included an exploration of rumination that included the brooding and reflection subscales, both of which were associated with the avoidant response, that is, more rapid evaluations of negative images. The significant difference between males and females in terms of the rating task—across all affective categories—is hard to explain, although this was controlled for in the statistical analysis. One explanation for these gender differences might be based on the study population, in that, in the United Arab Emirates, female participation and academic performance within tertiary education far outstrip that of males (Thomas, Al-Marzooqi, & Raynor, 2012). The slower response times for males might be a reflection of lower levels of motivation or technological familiarity or both. The one previous study using a task based assessment of experiential avoidance did not report similar gender differences (Giorgio et al., 2010). While the present study tentatively supports the idea that rumination is associated with experiential avoidance, alternative explanations might be
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considered. The Self-Regulatory Executive Function (SREF) model of psychological disorder (Wells, 2009), for example, provides a good framework for interpreting the present findings. Central to the S-REF model is the cognitive attention syndrome (CAS), which is viewed as comprising numerous ultimately unhelpful coping strategies (Fisher & Wells, 2009). Within this framework, a faster response to negative images could simply reflect a negative bias arising from heightened threat monitoring. It is also possible that heightened threat monitoring (noticing the image’s negative valence) and avoidance (moving quickly away from the image) operate synergistically. It would be particularly important for future studies attempting task-based assessments of experiential avoidance to distinguish between automatic attentional bias, and intentional avoidance. Perhaps a two-phase assessment could be employed where a valence identification task precedes the valence-rating task. The valence identification task is framed so participants are encouraged to respond as quickly as possible. This would tap the idea of heightened threat monitoring. Then the surreptitiously timed valence-rating task would be performed, with faster completion implying avoidance. This would still not be irrefutable; however, this underscores the inherent difficulty in task-based assessments of complex psychological constructs such as experiential avoidance. The study, while supporting the experiential avoidance hypothesis, also has several important limitations. First, the reliance on university students limits the overall generalizability of the findings. The participants in the study were not diagnosed with any mood or anxiety disorders. However, much previous research exploring attentional bias in emotional disorders has been based on nonclinical populations, and has ultimately proved useful in the development of models of psychopathology (Browning, Holmes, & Harmer, 2010). Similarly, the use of nonclinical participants eliminates potential confounds associated with psychotropic medication. However, there is clearly a benefit in attempting to replicate the
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present study within a clinical population. In addition to exploring a clinical sample, future studies might consider including an assessment of the metacognitions associated with avoidance. A further extension would be to include a memory task. One might hypothesize that high ruminators avoid negative images and, therefore, could be expected to exhibit poorer performance on a subsequent memory (incidental learning) task. Over a longer period of time, such an avoidant style, might equate to poorer episodic/autobiographical memory, as has been observed in the context of depression. Further experimental explorations of the experiential avoidance conceptualization of rumination are merited. Such studies may have important implications for the further development and refinement of cognitive therapy for depression, and other psychological complaints characterized by rumination. Acknowledgement This project was supported by a grant (RSA-110800402) from the National Research Foundation (UAE). References Al-Musawi, N. M. (2001). Psychometric Properties of the Beck Depression Inventory–II With University Students in Bahrain. Journal of Personality Assessment, 3(77), 568–579. Beck, A. T., Steer, R. A., & Brown, G. (1996). BDI-II Manual. San Antonio: Harcourt Brace & Company. Borkovec, T. D. (1994). The nature, functions, and origins of worry. In G. C. L. Davey, & F. Tallis (Eds.), Worrying: perspectives on theory, assessment, and treatment. Oxford: John Wiley & Sons. Bradley, M. M., & Lang, P. J. (2007). The International Affective Picture System (IAPS) in the study of emotion and attention. In J. A. Coan & J. J. B. Allen (Eds.), Handbook of Emotion Elicitation and Assessment (pp. 29–46). Oxford: Oxford University Press. Browning, M., Holmes, E. A., & Harmer, C. J. (2010). The modification of attentional bias to emotional information: a review of the techniques, mechanisms, and relevance to emotional disorders. Cognitive, Affective, & Behavioral Neuroscience, 10(1), 8–20.doi:10.3758/CABN.10.1.8.
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Crane, R. (2009). Mindfullness-Based Cognitive Therapy. NY: Routledge. Cribb, G., Moulds, M., & Carter, S. (2006). Rumination and experiential avoidance in depression. Behavior Change, 23, 165–176. doi:10.1375/bech.23.3.165. Dickson, K. S., Ciesla, J. A., & Reilly, L. C. (2012). Rumination, worry, cognitive avoidance, and behavioral avoidance: examination of temporal effects. Behaviour Therapy, 43(3), 629–640. doi: 10.1016/j.beth.2011.11.002. Fisher, P., & Wells, A. (2009). Metacognitive Therapy. New York: Routledge. Giorgio, J. M., Sanflippo, J., Kleiman, E., Reilly, D., Bender, R. E., Wagner, C. A., & Alloy, L. B. (2010). An experiential avoidance conceptualization of depressive rumination: three tests of the model. Behaviour Research and Therapy, 48, 1021–1031. Hayes, S. C., Wilson, K. G., Gifford, E. V., Follette, V. M., & Strosahl, K. (1996). Experiential avoidance and behavioral disorders: a functional dimensional approach to diagnosis and treatment. Journal of Consulting and Clinical Psychology and Psychotherapy: Theory, Research and Practice, 64, 1152e–1168. Just, N., & Alloy, L. B. (1997). The Response Styles Theory of Depression: Test and an Extension of the Theory. Journal of Abnormal Psychology, 106(2), 221–229. Knowles, R., Tai, S., Christensen, I., & Bentall, R. (2005). Coping with depression and vulnerability to mania: a factor analytic study of the Nolen-Hoeksema (1991) Response Styles Questionnaire. British Journal of Clinical Psychology, 44(Pt 1), 99–112. Kuehner, C., & Weber, I. (1999). Responses to depression in unipolar depressed patients: an investigation of NolenHoeksema’s response styles theory. Psychological Medicine, 29(6), 1323–1333. Laguna, L. B., Ham, L. S., & Hope, D. A. (2004). Chronic worry as avoidance of arousal. Cognitive Therapy and Research, 28, 269–281. Lam, D., Schuck, N., Smith, N., Farmer, A., & Checkley, S. (2003). Response style, interpersonal difficulties and social functioning in major depressive disorder. Journal of Affective Disorders, 75(3), 279–283. Mathews, J. R., & Barch, D. M. (2006). Episodic memory for emotional and non-emotional words in individuals with anhedonia. Psychiatry Research, 143, 121–133. Morina, N. (2011). Rumination and Avoidance as Predictors of Prolonged Grief, Depression, and Posttraumatic Stress in Female Widowed Survivors of War. The Journal of Nervous and Mental Disease, 199(12): 921–927.
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Morrow, J., & Nolen-Hoeksema, S. (1990). Effects of Responses to Depression on the Remediation of Depressive Affect. Journal of Personality & Social Psychology March, 58(3), 519–527. Moulds, M., Kandris, E., Starr, S., & Wong, A. C. (2007). The relationship between rumination, avoidance and depression in a non-clinical sample. Behaviour Research Therapy, 45(2), 251–261. Nolen-Hoeksema, S. (1987). Sex Differences in Unipolar Depression: Evidence and Theory. Psychological Bulletin, 101 (2), 259–282. Nolen-Hoeksema, S. (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100(4), 569–582. Osman, A., Kopper, B. A., Barrios, F., Gutierrez, P. M., & Bagge, C. L. (2004). Reliability and validity of the Beck Depression Inventory-II with adolescent psychiatric inpatients. Psychological Assessment, 16(2), 120–132. Sprinkle, S. D., Lurie, D., Insko, S. L., Atkinson, G., Jones, G. L., Logan, A. R., & Bissada, N. N. (2002). Criterion Validity, Severity Cut Scores, and Test-Retest Reliability of the Beck Depression Inventory-II in a University Counseling Center Sample. Journal of Counseling Psychology, 49(3), 381–385. Thomas, J., Al-Marzooqi, A., & Raynor, M. (2012). Marital status and gender as predictors of undergraduate academic performance: A United Arab Emirates Context. Learning and Teaching in the Gulf, 9(2). Thomas, J., & Altareb, B. (2012). Cognitive vulnerability to depression: An exploration of dysfunctional attitudes and response styles to dysphoric mood in UAE nationals. Psychology and Psychotherapy: Theory, Research and Practice, 85(1), 117–121. doi:10.1111/j.2044-8341.2011.02015. Thomas, J., & Bentall, R. (2002). Hypomanic traits and response styles to depression. British Journal of Clinical Psychology, 41(Pt 3), 309–313. Treynor, W., Gonzalez, R., & Nolen-Hoeksema, S. (2003). Rumination Reconsidered: a Psychometric Analysis. Cognitive Therapy and Research, 27(3), 247–259. Wells, A. (2009). Metacognitive Therapy for Anxiety and depression. NY: Guilford Press.
Address correspondence to: Dr Justin Thomas— Assistant Professor, Department of Natural Science and Public Health at Zayed University, PO Box 144534, United Arab Emirates. Email: justin. [email protected]
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