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03-09-2024 | Original Article

Specificity of Emotion Regulation Processes in Depression: A Network Analysis

Auteurs: Jente Depoorter, Rudi De Raedt, Matthias Berking, Kristof Hoorelbeke

Gepubliceerd in: Cognitive Therapy and Research | Uitgave 2/2025

Abstract

Background

Maladaptive emotion regulation has received a lot of attention as a potential mechanism underlying major depressive disorder (MDD). However, less is known about the role of adaptive emotion regulation skills and its specificity for MDD. The Adaptive Coping with Emotions model provides a framework for this, distinguishing early (Awareness, Sensations, Clarity, Understanding) and later processes (Modification, Acceptance, Tolerance, Readiness to confront and Effective Self-Support) relevant for emotion regulation.

Methods

The current study (N = 291) applied Network Analysis with Fused Graphical Lasso to jointly estimate emotion regulation networks in MDD (N = 160) and a control sample (N = 131). Within the two obtained network models, we investigated how different aspects of emotion regulation cluster together. In addition, level of centrality and unique associations between constructs were modeled. Permutation tests were applied to identify significant differences between both networks.

Results

Two communities were detected, with one including variables related to preparatory processes in emotion regulation and the other including variables related to regulation processes. Additionally, ‘Identifying and Labeling’ was ranked among the most central nodes. Furthermore, our results suggest similar pathways connecting emotion regulation skills in MDD and controls.

Conclusions

The results highlight the existence of different processes in emotion regulation and provide further evidence for emotion regulation as a transdiagnostic concept.

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In this context, it should be noted that the obtained edge accuracy and centrality stability indices likely provide an underestimation of the stability of the parameters presented in the current manuscript. That is, our results are based on a joint estimation procedure (FGL). However, this procedure has not been implemented in bootnet. As a result, in line with previous literature (e.g., Fried et al., 2018) evaluation of edge accuracy and centrality stability was based on network models (Supplemental Figs. 9–10) that were estimated for the subgroups separately (instead of relying on the full dataset, potentially resulting in reduced power). Similarly, node predictability was estimated for the subgroups separately. NCT took place on the subgroups, although reported correlations and SHD are based on the jointly estimated models. Tests for significant differences at a single-edge level were informed by the obtained SHD for the jointly estimated models.

Acid, S., & de Campos, L. M. (2003). Searching for bayesian network structures in the space of restricted acyclic partially directed graphs. Journal of Artificial Intelligence Research, 18, 445–490. https://doi.org/10.1613/jair.1061CrossRef

American Psychiatric Association (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.). https://doi.org/10.1176/appi.books.9780890425787

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57, 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.xCrossRef

Berking, M., & Lukas, C. A. (2015). The affect regulation training (ART): A transdiagnostic approach to the prevention and treatment of mental disorders. Current Opinion in Psychology, 3, 64–69. https://doi.org/10.1016/j.copsyc.2015.02.002CrossRef

Berking, M., & Whitley, B. (2014). The adaptive coping with emotions Model (ACE model). Affect regulation training. Springer. https://doi.org/10.1007/978-1-4939-1022-9_3

Berking, M., & Znoj, H. (2008). Entwicklung Und Validierung eines Fragebogens Zur Standardisierten Selbsteinschätzung emotionaler Kompetenzen (SEK-27) [Development and validation of the emotion-regulation skills Questionnaire, ERSQ-27]. Zeitschrift für Psychiatrie Psychologie und Psychotherapie, 56(2), 141–153. https://doi.org/10.1024/1661-4747.56.2.141CrossRef

Berking, M., Margraf, M., Ebert, D., Wupperman, P., Hofmann, S. G., & Junghanns, K. (2011). Deficits in emotion-regulation skills predict alcohol use during and after cognitive-behavioral therapy for alcohol dependence. Journal of Consulting and Clinical Psychology, 79(3), 307–318. https://doi.org/10.1037/a0023421CrossRefPubMedPubMedCentral

Berking, M., Wirtz, C. M., Svaldi, J., & Hofmann, S. G. (2014). Emotion regulation predicts symptoms of depression over five years. Behaviour Research and Therapy, 57, 13–20. https://doi.org/10.1016/j.brat.2014.03.003CrossRefPubMed

Berking, M., Eichler, E., Luhmann, M., Diedrich, A., Hiller, W., & Rief, W. (2019). Affect regulation training reduces symptom severity in depression - A randomized controlled trial. PloS One, 14(8), e0220436. https://doi.org/10.1371/journal.pone.0220436CrossRefPubMedPubMedCentral

Borsboom, D., & Cramer, A. O. J. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608CrossRefPubMed

Bringmann, L. F., Albers, C., Bockting, C., Borsboom, D., Ceulemans, E., Cramer, A., Epskamp, S., Eronen, M. I., Hamaker, E., Kuppens, P., Lutz, W., McNally, R. J., Molenaar, P., Tio, P., Voekle, M. C., & Wichers, M. (2022). Psychopathological networks: Theory, methods and practice. Behaviour Research and Therapy, 149., Article 104011. https://doi.org/10.1016/j.brat.2021.104011

Burger, J., Isvoranu, A. M., Lunansky, G., Haslbeck, J. M. B., Epskamp, S., Hoekstra, R. H. A., Fried, E. I., Borsboom, D., & Blanken, T. F. (2023). Reporting standards for psychological network analyses in cross-sectional data. Psychological Methods, 28(4), 806–824. https://doi.org/10.1037/met0000471CrossRefPubMed

Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006). Effects of suppression and acceptance on emotional responses of individuals with anxiety and mood disorders. Behaviour Research and Therapy, 44(9), 1251–1263. https://doi.org/10.1016/j.brat.2005.10.001CrossRefPubMed

Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mottus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis on personality data in R. Journal of Research in Personality, 54, 13–29. https://doi.org/10.1016/j.jrp.2014.07.003CrossRef

Costantini, G., Richetin, J., Preti, E., Casini, E., Epskamp, S., & Perugini, M. (2019). Stability and variability of personality networks. A tutorial on recent developments in network psychometrics. Personality and Individual Differences, 136, 68–78. https://doi.org/10.1016/j.paid.2017.06.011CrossRef

Costantini, G., Kappelmann, N., & Epskamp, S. (2021). EstimateGroupNetwork: Perform the Joint Graphical Lasso and Selects Tuning Parameters. R-package.

Danaher, P., Wang, P., & Witten, D. M. (2014). The joint graphical lasso for inverse covariance estimation across multiple classes. J R Stat Soc Series B Stat Methodol, 76, 373–397. https://doi.org/10.111/rssb.12033CrossRefPubMed

Derogatis, L. R. (1993). BSI brief Symptom Inventory. Administration, scoring and procedures manual (4th ed.). National Computer Systems.

Eaton, N. R., Bringmann, L. F., Elmer, T., Fried, E. I., Forbes, M. K., Greene, A. L., Krueger, R. F., Kotov, R., McGorry, P. D., Mei, C., & Waszczuk, M. A. (2023). A review of approaches and models in psychopathology conceptualization research. Nature Reviews Psychology. https://doi.org/10.1038/s44159-023-00218-4CrossRef

Ehring, T., Tuschen-Caffier, B., Schnülle, J., Fischer, S., & Gross, J. J. (2010). Emotion regulation and vulnerability to depression: Spontaneous versus instructed use of emotion suppression and reappraisal. Emotion, 10(4), 563–572. https://doi.org/10.1037/a0019010CrossRefPubMed

Epskamp, S., & Fried, E. I. (2017). bootnet: Bootstrap Methods for Various Network Estimation Routines. R package.

Epskamp, S., Cramer, A., Waldorp, L., Schmittmann, V. D., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48, 1–18. https://doi.org/10.18637/jss.v048.i04CrossRef

Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2018a). The gaussian graphical model in cross-sectional and time-series data. Multivariate Behavioral Research, 53(4), 453–480. https://doi.org/10.1080/00273171.2018.1454823CrossRefPubMed

Epskamp, S., Borsboom, D., & Fried, E. I. (2018b). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50, 195–212. https://doi.org/10.3758/s13428-017-0862-1CrossRefPubMed

Franke, G. H. (2000). Brief Symptom Inventory (BSI). Beltz.

Fried, E. I., Eidhof, M. B., Palic, S., Costantini, G., Huisman-van Dijk, H. M., Bockting, C. L. H., Engelhard, I., Armour, C., Nielsen, A. B. S., & Karstoft, K-I. (2018). Replicability and generalizability of posttraumatic stress disorder (PTSD) networks: A cross-cultural multisite study of PTSD symptoms in four trauma patient samples. Clinical Psychological Science, 6, 335–351. https://doi.org/10.1177/2167702617745092CrossRefPubMedPubMedCentral

Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21, 1129–1164. https://doi.org/10.1002/spe.4380211102CrossRef

Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS One, 12, e0174035. https://doi.org/10.1371/journal.pone.0174035CrossRefPubMedPubMedCentral

Golino, H. F., Christensen, A., & Moulder, R. (2020). EGAnet: Exploratory graph analysis: A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package.

Gross, J. J., & Directions (2015). Psychological Inquiry, 26(1), 130–137. https://doi.org/10.1080/1047840X.2015.989751.CrossRef

Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. https://doi.org/10.1037/0022-3514.85.2.348CrossRefPubMed

Hamilton, M. (1967). Development of a rating scale for primary depressive illness. The British Journal of Social and Clinical Psychology, 6(4), 278–296. https://doi.org/10.1111/j.2044-8260.1967.tb00530.xCrossRefPubMed

Haslbeck, J. M. B., & Waldorp, L. J. (2018). How well do Network models predict observations? On the importance of predictability in Network models. Behavior Research, 50, 853–861. https://doi.org/10.3758-017-0910-xCrossRef

Hemming, L., Haddock, G., Sham, J., & Pratt, D. (2019). Alexithymia and its associations with Depression, Suicidality, and aggression: An overview of the literature. Frontiers in Psychiatry, 10. https://doi.org/10.3389/fpsyt.2019.00203

Hofmann, S. G. (2014). Interpersonal emotion regulation model of Mood and anxiety disorders. Cognitive Therapy and Research, 38(5), 483–492. https://doi.org/10.1007/s10608-014-9620-1CrossRefPubMedPubMedCentral

Hofmann, S. G., Sawyer, A. T., Fang, A., & Asnaani, A. (2012). Emotion dysregulation model of mood and anxiety disorders. Depression and Anxiety, 29(5), 409–416. https://doi.org/10.1002/da.21888CrossRefPubMed

Jamison, L., Christensen, A. P., & Golino, H. (2021). Optimizing Walktrap’s Community Detection in Networks Using the Total Entropy Fit Index. Preprint https://doi.org/10.31234/osf.io/9pj2m

Joormann, J., & Gotlib, I. H. (2010). Emotion regulation in depression: Relation to cognitive inhibition. Cognition & Emotion, 24(2), 281–298. https://doi.org/10.1080/02699930903407948CrossRef

Joormann, J., & Siemer, M. (2014). Emotion regulation in mood disorders. In J. J. Gross (Ed.), Handbook of emotion regulation (pp. 413–427). The Guilford Press.

Joormann, J., & Stanton, C. H. (2016). Examining emotion regulation in depression: A review and future directions. Behaviour Research and Therapy, 86, 35–49. https://doi.org/10.1016/j.brat.2016.07.007CrossRefPubMed

Kessler, R. C. (2012). The costs of Depression. Psychiatric Clinics of North America, 35(1), 1–14. https://doi.org/10.1016/j.psc.2011.11.005CrossRefPubMed

LeMoult, J., Joormann, J., Sherdell, L., Wright, Y., & Gotlib, I. H. (2009). Identification of emotional facial expressions following recovery from depression. Journal of Abnormal Psychology, 118(4), 828–833. https://doi.org/10.1037/a0016944CrossRefPubMedPubMedCentral

Liu, D. Y., & Thompson, R. J. (2017). Selection and implementation of emotion regulation strategies in major depressive disorder: An integrative review. Clinical Psychology Review, 57, 183–194. https://doi.org/10.1016/j.cpr.2017.07.004CrossRefPubMed

Liu, H., Han, F., Yuan, M., Lafferty, J. D., & Wasserman, L. (2012). High-dimensional semiparametric gaussian copula graphical models. The Analysis of Statistics, 40(4), 2293–2326.

Liverant, G. I., Kamholz, B. W., Sloan, D. M., & Brown, T. A. (2011). Rumination in clinical depression: A type of emotional suppression? Cognitive Therapy and Research, 35(3), 253–256. https://doi.org/0.1007/s10608-010-9304-4CrossRef

Lukas, C. A., Ebert, D. D., Fuentes, H. T., Caspar, F., & Berking, M. (2018). Deficits in general emotion regulation skills-evidence of a transdiagnostic factor. Journal of Clinical Psychology, 74(6), 1017–1033. https://doi.org/10.1002/jclp.22565CrossRefPubMed

Lyvers, M., Lysychka, O., & Thorberg, F. A. (2014). Alexithymia and drinking in young adults: The role of alcohol-related intrusive thoughts. Personality and Individual Differences, 57, 70–73. https://doi.org/10.1016/j.paid.2013.09.021CrossRef

Marchetti, D., Verrocchio, M. C., & Porcelli, P. (2019). Gambling problems and Alexithymia: A systematic review. Brain Sciences, 9(8), 191. https://doi.org/10.3390/brainsci9080191CrossRefPubMedPubMedCentral

McEvoy, P. M., Watson, H., Watkins, E. R., & Nathan, P. (2013). The relationship between worry, rumination, and comorbidity: Evidence for repetitive negative thinking as a transdiagnostic construct. Journal of Affective Disorders, 151(1), 313–320. https://doi.org/10.1016/j.jad.2013.06.014CrossRefPubMed

Nolen-Hoeksema, S., Wisco, B. E., & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science: A Journal of the Association for Psychological Science, 3(5), 400–424. https://doi.org/10.1111/j.1745-6924.2008.00088.xCrossRefPubMed

Pons, P., & Latapy, M. (2005). In P. Yolum, T. Güngör, F. Gürgen, & C. Özturan (Eds.), Computing communities in large networks using Random walks (Vol. 3733). Springer. https://doi.org/10.1007/11569596_31

Sanchez, A., Romero, N., Maurage, P., & De Raedt, R. (2017). Identification of emotions in mixed disgusted-happy faces as a function of depressive symptom severity. Journal of Behavior Therapy and Experimental Psychiatry, 57, 96–102. https://doi.org/10.1016/j.jbtep.2017.05.002CrossRefPubMed

Thompson, R. A. (1994). Emotion regulation: A theme in search of definition. Monographs of the Society for Research in Child Development, 59, 25–52. https://doi.org/10.1111/j.1540-5834.1994.tb01276.xCrossRefPubMed

van Borkulo, C. D., Epskamp, S., & Millner, A. (2016). Network Comparison Test: Statistical comparison of two networks based on three invariance measures. R Package.

van Borkulo, C. D., Boschloo, L., Kossakowski, J. J., Tio, P., Schoevers, R. A., Borsboom, D., & Waldorp, L. J. W. (2022). Comparing Network structures on three aspects: A permutation test. Psychological Methods. https://doi.org/10.1037/met0000476CrossRefPubMed

Visted, E., Vøllestad, J., Nielsen, M. B., & Schanche, E. (2018). Emotion regulation in current and remitted Depression: A systematic review and Meta-analysis. Frontiers in Psychology, 9, 756. https://doi.org/10.3389/fpsyg.2018.00756CrossRefPubMedPubMedCentral

Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138(4), 775–808. https://doi.org/10.1037/a0027600CrossRefPubMed

Wittchen, H. U., Zaudig, M., & Fydrich, T. (1997). Skid. Strukturiertes klinisches interview für DSM-IV. Achse I und II. Handanweisung. Hogrefe. https://doi.org/10.1026//0084-5345.28.1.68

World Health Organization [WHO] (2023). Depression: World Health Organization Fact Sheet. Available online at: https://www.who.int/news-room/fact-sheets/detail/depression (accessed May 22, 2023).

Zhao, T., Li, X., Liu, H., Roeder, K., Lafferty, J., & Wasserman, L. (2015). huge: High-Dimensional undirected graph.

Titel: Specificity of Emotion Regulation Processes in Depression: A Network Analysis
Auteurs: Jente Depoorter
Rudi De Raedt
Matthias Berking
Kristof Hoorelbeke
Publicatiedatum: 03-09-2024
Uitgeverij: Springer US
Gepubliceerd in: Cognitive Therapy and Research / Uitgave 2/2025
Print ISSN: 0147-5916
Elektronisch ISSN: 1573-2819
DOI: https://doi.org/10.1007/s10608-024-10530-9

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Specificity of Emotion Regulation Processes in Depression: A Network Analysis

Abstract

Background

Methods

Results

Conclusions

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