Publication type
Journal Article
Authors
Publication date
November 15, 2023
Summary:
To understand psychological distress during COVID-19, we need to ensure that the same construct is measured over time and investigate how much of the variance in distress is attributable to chronic time-invariant variance compared to transient time-varying variance. We conducted secondary data analyses of Understanding Society, a U.K. probability-based longitudinal study of adults, using prepandemic (2015–2020) and pandemic data (N = 17,761, April 2020–March 2021). Using the General Health Questionnaire–12 (GHQ-12), analyses encompassed (a) five annual waves before COVID-19 plus the first survey wave during COVID-19 and (b) eight (bi)monthly waves during COVID-19. We investigated (a) longitudinal measurement invariance of distress, (b) time-invariant and time-varying variance components of distress using latent trait–occasion modeling, and (c) predictors of these different variance components. In all analyses, unique measurement invariance in distress was established, indicating the same unidimensional construct was measured using the GHQ before and during COVID-19. Time-varying variance was higher at the first COVID-19 lockdown (April 2020, 61.2%) compared to before COVID-19 (∼50%), suggesting increased fluctuations in distress at the start of the pandemic. Sensitivity analyses with equal time lags pre- and during COVID-19 confirmed this interpretation. During the pandemic, the highest distress time-varying variance (40.7%) was detected in April 2020, decreasing to 29.0% (July 2020) after restrictions eased. Despite mean-level fluctuations, time-varying variance remained stable during subsequent lockdowns, indicating more rank-order stability after this first major disruption. Loneliness most strongly predicted time-varying variance during the first lockdown. Life dissatisfaction and financial difficulties were associated with both variance components throughout the pandemic.
Published in
Psychological Assessment
Volume and page numbers
Volume: 35 , p.959 -973
DOI
https://doi.org/10.1037/pas0001237
ISSN
10403590
Subjects
Notes
Open Access
Open Access funding provided by University of Cambridge: This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0; http://creativecommons.org/licenses/by/4.0). This license permits copying and redistributing the work in any medium or format, as well as adapting the material for any purpose, even commercially.
© 2023 The Author(s)
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