CoChat
Sign Up
Cited by 676COVID-19 and Mental HealthMaternal Mental Health During Pregnancy and PostpartumStudent Stress and Coping

The DOI matches its Crossref record; 39 of the 41 references it cites were found in a registry or an index, and 2 are not checked yet.

Emotional distress in young adults during the COVID-19 pandemic: evidence of risk and resilience from a longitudinal cohort study

Open access
Shanahan, Lilly, Steinhoff, Annekatrin, Bechtiger, Laura, Murray, Aja L., Nivette, Amy, Hepp, Urs, Ribeaud, Denis, Eisner, Manuel·2022·Psychological Medicine
DOI 10.1017/s003329172000241xPMC PMC7338432
Open this paper in CoChat — free accountOpen PDF

Abstract

Background: The coronavirus disease 2019 (COVID-19) pandemic and associated lockdown could be considered a ‘perfect storm’ for increases in emotional distress. Such increases can only be identified by studies that use data collected before and during the pandemic. Longitudinal data are also needed to examine (1) the roles of previous distress and stressors in emotional distress during the pandemic and (2) how COVID-19-related stressors and coping strategies are associated with emotional distress when pre-pandemic distress is accounted for. Methods: Data came from a cohort study ( N = 768). Emotional distress (perceived stress, internalizing symptoms, and anger), COVID-19-related stressors, and coping strategies were measured during the pandemic/lockdown when participants were aged 22. Previous distress and stressors were measured before COVID-19 (at age 20). Results: On average, participants showed increased levels of perceived stress and anger (but not internalizing symptoms) during the pandemic compared to before. Pre-COVID-19 emotional distress was the strongest predictor of during-pandemic emotional distress, followed by during-pandemic economic and psychosocial stressors (e.g. lifestyle and economic disruptions) and hopelessness, and pre-pandemic social stressors (e.g. bullying victimization and stressful life events). Most health risks to self or loved ones due to COVID-19 were not uniquely associated with emotional distress in final models. Coping strategies associated with reduced distress included keeping a daily routine, physical activity, and positive reappraisal/reframing. Conclusions: In our community sample, pre-pandemic distress, secondary consequences of the pandemic (e.g. lifestyle and economic disruptions), and pre-pandemic social stressors were more consistently associated with young adults' emotional distress than COVID-19-related health risk exposures.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1017/s003329172000241x

Cites

39 of 41 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1. Associations of sociodemographic and risk variables with levels of emotional distress during the COVID-19 pandemic/lockdown. Models that used stressors and health risks as predictors were adjusted for all sociodemographic variables. Risk factors were entered one at a time (i.e. a separate model for each risk factor). Standardized regression coefficients (β) and 95% confidence intervals (CIs) were applied. For exact coefficients, CIs, and p values, see online Supplementary Table S3.
Fig. 1. Associations of sociodemographic and risk variables with levels of emotional distress during the COVID-19 pandemic/lockdown. Models that used stressors and health risks as predictors were adjusted for all sociodemographic variables. Risk factors were entered one at a time (i.e. a separate model for each risk factor). Standardized regression coefficients (β) and 95% confidence intervals (CIs) were applied. For exact coefficients, CIs, and p values, see online Supplementary Table S3.CC BY · PubMed Central
Fig. 2. Associations of sociodemographic and risk variables with changes in emotional distress from the pre-pandemic to the during-pandemic/lockdown assessment (i.e. adjusted for pre-pandemic distress). Models that used stressors and health risks as predictors were adjusted for all sociodemographic variables. Risk factors were each entered one at a time (i.e. a separate model for each risk factor). Standardized regression coefficients (β) and 95% CIs were applied. For exact coefficients, CIs, and p values, see online Supplementary Table S4.
Fig. 2. Associations of sociodemographic and risk variables with changes in emotional distress from the pre-pandemic to the during-pandemic/lockdown assessment (i.e. adjusted for pre-pandemic distress). Models that used stressors and health risks as predictors were adjusted for all sociodemographic variables. Risk factors were each entered one at a time (i.e. a separate model for each risk factor). Standardized regression coefficients (β) and 95% CIs were applied. For exact coefficients, CIs, and p values, see online Supplementary Table S4.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 38 references

Research works printed but not linked: 3

  1. Eisner, 2011, The SAGE handbook of criminological research methods, 410
  2. Veer, I. , Riepenhausen, A. , Zerban, M. , Wackerhagen, C. , Engen, H. , Puhlmann, L. , … Kalisch, R. (2020). Mental resilience in the Corona lockdown: First empirical insights from Europe. preprint. Retrieved from https://psyarxiv.com/4z62t
  3. Muthén, 2012, Mplus user's guide

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Shanahan, L., Steinhoff, A., Bechtiger, L., Murray, A. L., Nivette, A., Hepp, U., Ribeaud, D., & Eisner, M.
Affiliations
  • University of Zurich (CH)
  • University of Edinburgh (GB)
  • Utrecht University (NL)
  • Integrierte Psychiatrie Winterthur (CH)
Corresponding author
Shanahan, Lilly
ORCID
Venue
Psychological Medicine
Publisher
Cambridge University Press (CUP)
Published
2020-06-23
Volume
52
Issue
5
Pages
824-833
ISSN
  • 0033-2917 (ISSN-L)
  • 1469-8978
DOI
10.1017/s003329172000241x
PMC
PMC7338432
OpenAlex
W3036964275
Cited by
675
References
38
Citations by year
2026: 22 · 2025: 42 · 2024: 78 · 2023: 118 · 2022: 168 · 2021: 213 · 2020: 34
FWCI
53.24
Type
journal article
Language
en
Open access
Licence
Locations
  • Psychological Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Topics
  • Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Maternal Mental Health During Pregnancy and Postpartum
  • Social Sciences › Psychology › Developmental and Educational Psychology › Student Stress and Coping
Keywords
COVID-19 pandemic, emotional distress, young adults, perceived stress, internalizing problems, anger, coping strategies, hopelessness, economic stressors, psychosocial stressors, bullying victimization, life events, lockdown, resilience, positive reappraisal
MeSH terms
Psychological Distress, COVID-19, Adult, Communicable Disease Control, Humans, Longitudinal Studies, Cohort Studies, Young Adult, Pandemics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review