Literature DB >> 30613129

Socioemotional Dynamics of Emotion Regulation and Depressive Symptoms: A Person-Specific Network Approach.

Xiao Yang1, Nilam Ram1,2, Scott D Gest1, David M Lydon-Staley1, David E Conroy1, Aaron L Pincus1, Peter C M Molenaar1.   

Abstract

Socioemotional processes engaged in daily life may afford and/or constrain individuals' emotion regulation in ways that affect psychological health. Recent findings from experience sampling studies suggest that persistence of negative emotions (emotion inertia), the strength of relations among an individual's negative emotions (density of the emotion network), and cycles of negative/aggressive interpersonal transactions are related to psychological health. Using multiple bursts of intensive experience sampling data obtained from 150 persons over one year, person-specific analysis, and impulse response analysis, this study quantifies the complex and interconnected socioemotional processes that surround individuals' daily social interactions and on-going regulation of negative emotion in terms of recovery time. We also examine how this measure of regulatory inefficiency is related to interindividual differences and intraindividual change in level of depressive symptoms. Individuals with longer recovery times had higher overall level of depressive symptoms. As well, during periods where recovery time of sadness was longer than usual, individuals' depressive symptoms were also higher than usual, particularly among individuals who experienced higher overall level of stressful life events. The findings and analysis highlight the utility of a person-specific network approach to study emotion regulation, how regulatory processes change over time, and potentially how planned changes in the configuration of individuals' systems may contribute to psychological health.

Entities:  

Keywords:  EMA; depression; dynamic systems; intensive longitudinal data; network analysis; personalized health

Year:  2018        PMID: 30613129      PMCID: PMC6319954          DOI: 10.1155/2018/5094179

Source DB:  PubMed          Journal:  Complexity        ISSN: 1076-2787            Impact factor:   2.833


  7 in total

1.  The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research.

Authors:  Donald J Robinaugh; Ria H A Hoekstra; Emma R Toner; Denny Borsboom
Journal:  Psychol Med       Date:  2019-12-26       Impact factor: 7.723

2.  Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.

Authors:  D M Lydon-Staley; I Barnett; T D Satterthwaite; D S Bassett
Journal:  Curr Opin Biomed Eng       Date:  2018-12-14

3.  Dynamics among borderline personality and anxiety features in psychotherapy outpatients: An exploration of nomothetic and idiographic patterns.

Authors:  William D Ellison; Kenneth N Levy; Michelle G Newman; Aaron L Pincus; Stephen J Wilson; Peter C M Molenaar
Journal:  Personal Disord       Date:  2019-10-17

4.  Temporal networks of tobacco withdrawal symptoms during smoking cessation treatment.

Authors:  David M Lydon-Staley; Adam M Leventhal; Megan E Piper; Robert A Schnoll; Danielle S Bassett
Journal:  J Abnorm Psychol       Date:  2020-11-30

Review 5.  Single-Subject Research in Psychiatry: Facts and Fictions.

Authors:  Marij Zuidersma; Harriëtte Riese; Evelien Snippe; Sanne H Booij; Marieke Wichers; Elisabeth H Bos
Journal:  Front Psychiatry       Date:  2020-11-13       Impact factor: 4.157

6.  Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results.

Authors:  Aditya Ponnada; Shirlene Wang; Daniel Chu; Bridgette Do; Genevieve Dunton; Stephen Intille
Journal:  JMIR Form Res       Date:  2022-02-09

Review 7.  Modeling brain, symptom, and behavior in the winds of change.

Authors:  David M Lydon-Staley; Eli J Cornblath; Ann Sizemore Blevins; Danielle S Bassett
Journal:  Neuropsychopharmacology       Date:  2020-08-28       Impact factor: 8.294

  7 in total

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