Evidence map›Paper›PMID 41069831›Full record

ArticleFrontiers in public health2025

Average or extraordinary? A tale of two studied samples' anxiety related recovery work after COVID-19.

Gail Low, Alex Bacadini Franca, Anila Naz, Gloria Gutman, Zhiwei Gao, Sofia Von Humboldt

Abstract read
In one paragraph

Article in Frontiers in public 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

6 authors.

Gail LowFaculty of Nursing, MacEwan University, Edmonton, AB, Canada.
Alex Bacadini FrancaLaboratory of Human Development and Cognition, Federal University of São Carlos, São Paulo, Brazil.
Anila NazFaculty of Nursing, University of Alberta, Edmonton, AB, Canada.
Gloria GutmanDepartment of Gerontology, Simon Fraser University, Vancouver, BC, Canada.
Zhiwei GaoFaculty of Medicine, Memorial University, St. John's, NL, Canada.
Sofia Von HumboldtWilliam James Center for Research, Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A global pandemic is a hardship and mentally distressing event for any of us, and particularly for people living at a greater risk of post-infectious health harms. Public discourse about COVID-19 largely characterizes older people as a physically and mentally vulnerable demographic. Research findings largely now to the contrary consider age an asset, a perspective in keeping with Seligman's idea that everyday people can also see the positive side of life and act accordingly when faced with events that are neither positive nor within their control. With this in mind, we explore how average older people were managing pandemic-related anxiety when mandated COVID-19 public health measures were lifted. Methods: Our primary study sample was a national census-based quota sample ( Results: Convenience sample responders were largely residing in Ontario ( Discussion: Average older Canadians managed their anxiety as capably as healthier, better educated, and generally older peers. Our findings are explored through a lens of positivity, not vulnerability. Methodological provocations are offered for future research, including post-pandemic between-sampling comparisons.

Indexed as

AnxietyCOVID-19AgedAged, 80 and overCanadaFemaleHumansMaleMiddle AgedOntarioPandemicsSARS-CoV-2Surveys and Questionnairesanxiety managementconvenience sampleflourishing and positive and negative feelingsnetwork analysesrepresentative sample

Identifiers

PMID41069831
PMCPMC12506091

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.