Evidence map›Paper›PMID 40995334›Full record

ArticleRural mental health2025

Sociodemographic Factors and Mental Health in Health Care Professionals and Patients During COVID-19.

Anna K Radin, Zihan Zheng, Jenny Shaw, Siobhan P Brown, Elizabeth McCue, Tara Fouts, Anton Skeie, Cecelia Peña, Jonathan Youell, Hilary Flint and 6 more

Abstract read
In one paragraph

Article in Rural mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Anna K RadinSt. Luke's Health System, Applied Research Division, Boise, ID, USA.ORCID 0000-0000-8535-8287
Zihan ZhengUniversity of Washington, Department of Biostatistics, Seattle, WA, USA.
Jenny ShawSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Siobhan P BrownUniversity of Washington, Department of Biostatistics, Seattle, WA, USA.
Elizabeth McCueSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Tara FoutsSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Anton SkeieSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Cecelia PeñaSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Jonathan YouellSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Hilary FlintSt. Luke's Health System, Applied Research Division, Boise, ID, USA.
Amelia Doty-JonesSt. Luke's Health System, Behavioral Health Service Line, Boise, ID, USA.
Jacob WilsonSt. Luke's Health System, Behavioral Health Service Line, Boise, ID, USA.
Kwun C G ChanUniversity of Washington, Department of Biostatistics, Seattle, WA, USA.
Martina FruhbauerovaUniversity of Kentucky, Department of Psychology, Lexington, KY, USA.
Michael WaltonSt. Luke's Health System, Behavioral Health Service Line, Boise, ID, USA.
Katherine Anne ComtoisUniversity of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA.

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
NCATS NIH HHS UL1 TR002319
6 · The paper itself

Abstract

The COVID-19 pandemic worsened mental health. This study aimed to: (1) measure the prevalence of loneliness, anxiety, depression, suicidal ideation or behavior, and stress in primary care patients, and physicians, healthcare providers, and healthcare staff; and (2) measure the association of socio-demographic and employment characteristics with mental health measures. A cross-sectional survey measured the prevalence of mental health outcomes in healthcare providers and staff and primary care patients in Idaho during the COVID-19 pandemic from January 18 - July 7, 2021. Descriptive statistics and multivariate linear regression models with robust standard errors were used to assess the association between mental health measures and demographic characteristics, employment status, healthcare occupation type, financial security, and local COVID-19 hospitalizations. Each outcome was modeled separately. 3,646 participants completed the survey, including 1,687 patients and 1,959 healthcare providers and staff. Participants were 73.5% female, 92.5% White, and 6.6% Hispanic, with a mean age of 46.8 (SD: 15.6). Overall, 32.2% of patients and 29% of healthcare providers and staff reported moderate to high levels of at least one measure of mental distress. Male sex, older age, larger household size, not caring for dependents, being a healthcare provider or staff, and being financially secure were associated with better mental health conditions, with financial security being the association of largest magnitude. Understanding which sociodemographic factors were associated with disproportionate adverse mental health outcomes from COVID-19 may inform how mental health support is prioritized in future public health emergencies.

Indexed as

AnxietyCOVID-19DepressionHealth personnellonelinessMental healthSuicide

Identifiers

PMID40995334
PMCPMC12456348

What OpenQuestion holds

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Registered trials

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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.