Longitudinal interactions between residual symptoms and physiological stress in the remitted symptom network structure of depression

Bibliographic Data

ID21284093
AuthorsAoife Whiston (0000-0002-0300-5910, University of Limerick, corresponding author), Eric R Igou (0000-0001-7744-9648, University of Limerick), Donal G Fortune (0000-0003-0916-3247, University of Limerick), Maria Semkovska (0000-0001-9800-4621, University of Southern Denmark)
Year2023
Volume241
Pages104078
Publication date2023-11-01
Open AccessYes
TypeARTICLE
VenueActa Psychologica (JOURNAL)
Journal identifiersISSN: 0001-6918 • E-ISSN: 1873-6297
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.actpsy.2023.104078
PMID37944268
OpenAlexW4388496845
LanguageEN
References cited88

Residual symptoms and stress are amongst the most reliable predictors of relapse in remitted depression. Standard methodologies often preclude continuous stress sampling or the evaluation of complex symptom interactions. This limits knowledge acquisition relative to the day-to-day interactions between residual symptoms and stress. The study aims to explore the interactions between physiological stress and residual symptoms network structure in remitted depression. Twenty-two individuals remitted from depression completed baseline, daily diary (DD), and post-DD assessments. Self-reported stress and residual symptoms were measured at baseline and post-DD. Daily diaries required participants to use a wearable electrodermal activity (EDA) device during waking hours and complete residual symptom measures twice daily for 3-weeks. Two-step multilevel vector auto-regression models were used to estimate contemporaneous and dynamic networks. Depressed mood and concentration problems were central across networks. Skin conductance responses (SCRs), suicide, appetite, and sleep problems were central in the temporal and energy loss in the contemporaneous network. Increased SCRs predicted decreased energy loss. Residual symptoms and stress showed bi-directional interactions. Overall, depressed mood and concentration problems were consistently central, thus potentially important intervention targets. Non-obtrusive bio-signal measures should be used to provide the clinical evidence-base for modelling the interactions between depressive residual symptoms and stress. Practical implications are discussed throughout related to focusing on symptom-specific interactions in clinical practice, simultaneously reducing residual symptom and stress occurrences, EDA as pioneering signal for stress detection, and the central role of specific residual symptoms in remitted depression

Algorithm · Depression (economics) · Mood · Psychiatry · Residual · Clinical Psychology · Functional Brain Connectivity Studies · Mental Health Research Topics · Psychology · Treatment of Major Depression

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