Evidence map›Paper›PMID 38183562›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024

Individual differences in the long-term impact of the pandemic: moderators of COVID-related hardship, worry, and social support.

Carolyn E Schwartz, Katrina Borowiec, Yuelin Li, Bruce D Rapkin

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In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.5field-weighted citation impact, top 6% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Toward characterizing brain fog in long COVID: correlates and impact on measurement metrics.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  2. Review
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  4. Disabled from work and depressed: cognitive factors associated with exacerbated or attenuated depression over the COVID-19 pandemic.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
  5. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 1 country.

Carolyn E SchwartzDeltaQuest Foundation, Inc., 31 Mitchell Road, Concord, MA, USA. carolyn.schwartz@deltaquest.org.ORCID http://orcid.org/0000-0002-9173-7774
Katrina BorowiecDeltaQuest Foundation, Inc., 31 Mitchell Road, Concord, MA, USA.
Yuelin LiDepartment of Psychiatry & Behavioral Sciences and the Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bruce D RapkinDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
Albert Einstein College of Medicine · USBoston College · USMemorial Sloan Kettering Cancer Center · USTufts Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUnderstanding people's response to the pandemic needs to consider individual differences in priorities and concerns. The present study sought to understand how individual differences in cognitive-appraisal processes might moderate the impact of three COVID-specific factors-hardship, worry, and social support-on reported depression.

methodsThis longitudinal study of the psychosocial impact of the COVID-19 pandemic included 771 people with data at three timepoints over 15.5 months. Participants were recruited from panels of chronically ill or general population samples. Depression was measured by an item response theory validated depression index created using items from existing measures that reflected similar content to the Patient Health Questionnaire-8. COVID-specific factors of hardship, worry, and social support were assessed with items compiled by the National Institutes of Health. The Quality of Life Appraisal Profile

resultsOver time the association between low social support and depression was greater (p = 0.0181). Emphasizing the negative was associated with exacerbated depression, in particular for those with low social support (p = 0.0007). Focusing on demands and habituation was associated with exacerbated depression unless one experienced greater hardship (p = 0.0074). There was a stronger positive connection between recent changes and depression for those people with higher worry scores early in the pandemic as compared to later, but a stronger positive correlation for those with lower worry scores later in the pandemic (p = 0.0015). Increased endorsement of standards of comparison, emphasizing the negative, problem goals, and health goals was associated with worse depression scores (all p < 0.0001). People who were younger, disabled, or had greater difficulty paying bills also reported worse depression (p < 0.0001, 0.0001, and 0.002, respectively).

conclusionAt the aggregate level, COVID-specific stressors changed over the course of the pandemic, whereas depression and social-support resources seemed stable. However, deeper analysis revealed substantial individual differences. Cognitive-appraisal processes showed considerable variability across individuals and moderated the impact of COVID-specific stressors and resources over time. Future work is needed to investigate whether coaching individuals away from maladaptive cognitive-appraisal processes can reduce depression and lead to better overall well-being.

Indexed as

COVID-19HumansIndividualityLongitudinal StudiesPandemicsQuality of LifeSocial SupportAppraisalCOVIDDepressionHardshipResponse shiftSocial supportWorry

Identifiers

PMID38183562
OpenAlexW4390639703

What OpenQuestion holds

Textmetadata
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.