Time-Varying Network Models for the Temporal Dynamics of Depressive Symptomatology in Patients With Depressive Disorders: Secondary Analysis of Longitudinal Observational Data
Background: As depression is highly heterogenous, an increasing number of studies investigate person-specific associations of depressive symptoms in longitudinal data. However, most studies in this area of research conceptualize symptom interrelations to be static and time invariant, which may lea...
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Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Philipps-Universität Marburg
2024
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Subjects: | |
Online Access: | PDF Full Text |
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Summary: | Background: As depression is highly heterogenous, an increasing number of studies investigate person-specific associations
of depressive symptoms in longitudinal data. However, most studies in this area of research conceptualize symptom interrelations
to be static and time invariant, which may lead to important temporal features of the disorder being missed.
Objective: To reveal the dynamic nature of depression, we aimed to use a recently developed technique to investigate whether
and how associations among depressive symptoms change over time.
Methods: Using daily data (mean length 274, SD 82 d) of 20 participants with depression, we modeled idiographic associations
among depressive symptoms, rumination, sleep, and quantity and quality of social contacts as dynamic networks using time-varying
vector autoregressive models.
Results: The resulting models showed marked interindividual and intraindividual differences. For some participants, associations
among variables changed in the span of some weeks, whereas they stayed stable over months for others. Our results further
indicated nonstationarity in all participants.
Conclusions: Idiographic symptom networks can provide insights into the temporal course of mental disorders and open new
avenues of research for the study of the development and stability of psychopathological processes. |
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Item Description: | Gefördert durch den Open-Access-Publikationsfonds der UB Marburg. |
Physical Description: | 15 Pages |
DOI: | 10.2196/50136 |