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Temporal dynamics in mental health symptoms and loneliness during the COVID-19 pandemic in a longitudinal probability sample: a network analysis

Psychology

Temporal dynamics in mental health symptoms and loneliness during the COVID-19 pandemic in a longitudinal probability sample: a network analysis

M. Odenthal, P. Schlechter, et al.

This study by Michael Odenthal, Pascal Schlechter, Christoph Benke, and Christiane A. Pané-Farré explores the intricate relationships between mental health symptoms and loneliness during the COVID-19 pandemic. By analyzing data from over 17,000 participants, it reveals how loneliness and feelings of worthlessness played crucial roles in symptom escalation, offering important insights for targeted interventions.

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Playback language: English
Abstract
This study investigated the temporal dynamics of mental health symptoms and loneliness during the COVID-19 pandemic using a network analysis approach. Data from the Understanding Society study (N=17,761) in the UK were analyzed across three time points: pre-pandemic, pandemic onset, and later pandemic phases. Loneliness and feeling worthless emerged as central symptoms driving symptom escalation, while feeling depressed and inability to overcome difficulties were identified as downstream consequences. These findings highlight the importance of targeting loneliness and self-worth in interventions.
Publisher
Translational Psychiatry
Published On
May 10, 2023
Authors
Michael Odenthal, Pascal Schlechter, Christoph Benke, Christiane A. Pané-Farré
Tags
mental health
loneliness
COVID-19
network analysis
interventions
symptom escalation
self-worth

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