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. 2023 Jul;53(9):3897-3907.
doi: 10.1017/S0033291722000563. Epub 2022 Mar 1.

Coping with COVID: risk and resilience factors for mental health in a German representative panel study

Antje Riepenhausen  1   2 , Ilya M Veer  1   3 , Carolin Wackerhagen  1 , Zala C Reppmann  1 , Göran Köber  4   5 , José Luis Ayuso-Mateos  6   7   8 , Sophie A Bögemann  9 , Giovanni Corrao  10   11 , Mireia Felez-Nobrega  7   12 , Josep Maria Haro Abad  7   12 , Erno Hermans  9 , Judith van Leeuwen  9 , Klaus Lieb  13   14 , Vincent Lorant  15 , Murielle Mary-Krause  16 , Roberto Mediavilla  6   7 , Maria Melchior  16 , Ellenor Mittendorfer-Rutz  17 , Matteo Monzio Compagnoni  10   11 , Kuan-Yu Pan  18 , Lara Puhlmann  13   19 , Karin Roelofs  9   20 , Marit Sijbrandij  21 , Pierre Smith  15   22 , Oliver Tüscher  13   14 , Anke Witteveen  21 , Matthias Zerban  23 , Raffael Kalisch  13   23 , Hannes Kröger  24   25 , Henrik Walter  1   2
Affiliations

Coping with COVID: risk and resilience factors for mental health in a German representative panel study

Antje Riepenhausen et al. Psychol Med. 2023 Jul.

Abstract

Background: The coronavirus disease 2019 (COVID-19) pandemic might affect mental health. Data from population-representative panel surveys with multiple waves including pre-COVID data investigating risk and protective factors are still rare.

Methods: In a stratified random sample of the German household population (n = 6684), we conducted survey-weighted multiple linear regressions to determine the association of various psychological risk and protective factors assessed between 2015 and 2020 with changes in psychological distress [(PD; measured via Patient Health Questionnaire for Depression and Anxiety (PHQ-4)] from pre-pandemic (average of 2016 and 2019) to peri-pandemic (both 2020 and 2021) time points. Control analyses on PD change between two pre-pandemic time points (2016 and 2019) were conducted. Regularized regressions were computed to inform on which factors were statistically most influential in the multicollinear setting.

Results: PHQ-4 scores in 2020 (M = 2.45) and 2021 (M = 2.21) were elevated compared to 2019 (M = 1.79). Several risk factors (catastrophizing, neuroticism, and asking for instrumental support) and protective factors (perceived stress recovery, positive reappraisal, and optimism) were identified for the peri-pandemic outcomes. Control analyses revealed that in pre-pandemic times, neuroticism and optimism were predominantly related to PD changes. Regularized regression mostly confirmed the results and highlighted perceived stress recovery as most consistent influential protective factor across peri-pandemic outcomes.

Conclusions: We identified several psychological risk and protective factors related to PD outcomes during the COVID-19 pandemic. A comparison of pre-pandemic data stresses the relevance of longitudinal assessments to potentially reconcile contradictory findings. Implications and suggestions for targeted prevention and intervention programs during highly stressful times such as pandemics are discussed.

Keywords: COVID-19; mental health; psychological distress; resilience; risk factors.

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Conflict of interest statement

RK has received advisory honoraria from JoyVentures, Herzlia, Israel.

Figures

Fig. 1.
Fig. 1.
Timing of data collection for predictors and outcome variables. PHQ-4, Patient Health Questionnaire, 4 item version; ΔPHQ 2019, change in PHQ-4 from 2016 to 2019; ΔPHQ 2020, change in PHQ-4 from 2019 to 2020, ΔPHQ 2021, change in PHQ-4 from 2019 to 2021.
Fig. 2.
Fig. 2.
Psychological distress (PHQ-4) across years (a) and across the nine tranches ranging from 1 April to 28 June 2020 (b). Note. Error bars depict the 95% confidence interval. PHQ-4 values range from 0 to 12, higher values indicating higher PD. As weighted means are used, means of each individual tranche are representative for the German population. In (b), weighted mean PHQ-4 values of the entire sample in 2016 and 2019 are displayed as dotted and dashed horizontal lines, respectively.
Fig. 3.
Fig. 3.
Beta coefficients of multiple linear regressions for ΔPHQ 2020 (a), ΔPHQ 2021 (b), and ΔPHQ 2019 (c). Note. This figure shows beta coefficients of the psychological factors for the three outcomes. Complete output tables of the respective linear regressions can be found in online Supplementary Tables S4–S6. Predictors are z-standardized, outcomes are not standardized. Error bars depict the 95% confidence interval.
See this image and copyright information in PMC

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