Evidence map›Paper›PMID 41607029›Full record

ArticleInternational journal of methods in psychiatric research2026

Bayesian Mixed Models Approach to Exploring Resilience: Impact of Stress on Subjective Health and Affects Over Time During the COVID-19 Pandemic.

Markus Schepers, Irene Schmidtmann, Sarah K Schäfer, Simge Yilmaz, Rieke Baumkötter, Alica Hartmann, Julia Petersen, Nora Hettich-Damm, Philipp Wild, Daniela Zahn and 1 more

Abstract read
In one paragraph

Article in International journal of methods in psychiatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Markus SchepersInstitute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.ORCID 0000-0003-2436-1540
Irene SchmidtmannInstitute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Sarah K SchäferLeibniz Institute for Resilience Research, Mainz, Germany.
Simge YilmazPreventive Cardiology and Medical Prevention, Center of Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Rieke BaumkötterPreventive Cardiology and Medical Prevention, Center of Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Alica HartmannDepartment of Ophthalmology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
Julia PetersenDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Nora Hettich-DammDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Philipp WildPreventive Cardiology and Medical Prevention, Center of Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Daniela ZahnPreventive Cardiology and Medical Prevention, Center of Cardiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Daniel WollschlägerInstitute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.

Funding

European Regional Development Fund 84007232European Regional Development Fund 84009735National University Medicine Research Network on Covid-19 01KX2021ReALity Initiative of the Life Sciences of the Johannes Gutenberg University Mainz
6 · The paper itself

Abstract

backgroundProfound stressors such as the COVID-19 pandemic have highlighted the importance of understanding resilience mechanisms and approaches for quantifying them in longitudinal studies.

methodsWe used Bayesian mixed models to analyze resilience dynamics with ordinal dependent variables: subjective physical and mental health, and fear, sadness, and anger. The models included fixed effects for individual stressors and random intercepts for participants, applied to the Gutenberg-COVID-19 cohort study.

resultsThere were 206,912 responses from 7386 participants (mean age 55.09 years, 51.52% women) over one year (Oct 29, 2020 - Oct 25, 2021). Social stressors, such as loss of social contacts, had stronger negative associations with health and negative affects than work-related stress. Subjective health and emotions declined during lockdowns but quickly recovered afterward.

conclusionOur longitudinal study design and mixed-model analysis highlight the role of social stress and encourage further research into protective factors like social support and positive reappraisal.

Indexed as

COVID-19Health StatusResilience, PsychologicalStress, PsychologicalAgedBayes TheoremFemaleHumansLongitudinal StudiesMaleMiddle AgedSubjective Stress

Identifiers

PMID41607029
PMCPMC12852500

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.