Jente Depoorter, Rudi De Raedt, Matthias Berking, Kristof Hoorelbeke
{"title":"抑郁症中情绪调节过程的特异性:网络分析","authors":"Jente Depoorter, Rudi De Raedt, Matthias Berking, Kristof Hoorelbeke","doi":"10.1007/s10608-024-10530-9","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p><i>Maladaptive</i> 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 <i>adaptive</i> 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.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>The current study (<i>N</i> = 291) applied Network Analysis with Fused Graphical Lasso to jointly estimate emotion regulation networks in MDD (<i>N</i> = 160) and a control sample (<i>N</i> = 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.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>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.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>The results highlight the existence of different processes in emotion regulation and provide further evidence for emotion regulation as a transdiagnostic concept.</p>","PeriodicalId":48316,"journal":{"name":"Cognitive Therapy and Research","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Specificity of Emotion Regulation Processes in Depression: A Network Analysis\",\"authors\":\"Jente Depoorter, Rudi De Raedt, Matthias Berking, Kristof Hoorelbeke\",\"doi\":\"10.1007/s10608-024-10530-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Background</h3><p><i>Maladaptive</i> 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 <i>adaptive</i> 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.</p><h3 data-test=\\\"abstract-sub-heading\\\">Methods</h3><p>The current study (<i>N</i> = 291) applied Network Analysis with Fused Graphical Lasso to jointly estimate emotion regulation networks in MDD (<i>N</i> = 160) and a control sample (<i>N</i> = 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.</p><h3 data-test=\\\"abstract-sub-heading\\\">Results</h3><p>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. 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Specificity of Emotion Regulation Processes in Depression: A Network Analysis
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.
期刊介绍:
Cognitive Therapy and Research (COTR) focuses on the investigation of cognitive processes in human adaptation and adjustment and cognitive behavioral therapy (CBT). It is an interdisciplinary journal welcoming submissions from diverse areas of psychology, including cognitive, clinical, developmental, experimental, personality, social, learning, affective neuroscience, emotion research, therapy mechanism, and pharmacotherapy.