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Record W4416239174 · doi:10.1123/japa.2024-0167

Challenges of the COVID-19 Pandemic for Recreational Group Physical Activities for Older Adults: Participant and Service Provider Perspectives

2025· article· en· W4416239174 on OpenAlexaff
Meghan H. McDonough, Michelle Patterson, Bobbie-Ann P. Craig, Delaney Duchek, Stephanie Won, Jennifer Hewson

Bibliographic record

VenueJournal of Aging and Physical Activity · 2025
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRecreationPandemicService providerPhysical activityCoronavirus disease 2019 (COVID-19)Service (business)Balance (ability)

Abstract

fetched live from OpenAlex

BACKGROUND: Social participation and physical activity are lifestyle factors that improve well-being and health. Older adult populations are at greater risk of inactivity and social isolation, both of which were exacerbated by COVID-19 restrictions (e.g., physical distancing, recreational program closures). Recreational programs that provide opportunities for physical activity and social interaction are important for addressing these concerns in communities. This research examined lived experiences with changes in physical activity and social participation among adults ≥65 years during the COVID-19 pandemic, their perspectives on precautionary measures and alternate forms of program delivery, and experiences and challenges service providers in the recreation sector faced in adapting programs for older adults during the pandemic. METHODS: Using interpretive description methodology, we interviewed older adults (n = 20) and service providers (n = 10). RESULTS: Four themes were identified: (a) concerns about safety and risk given heightened vulnerability, (b) alternate options helped with participation but inequities in access persist, (c) forging new routines after a major lapse, and (d) social connections supported resilience but sense of community dwindled. CONCLUSION: It is important that organizations balance risks of participation with nonparticipation; address the compounding challenges and inequities of a disruption; understand the importance of social benefits of physical activity in this population; and plan to support resilience, cope with the aftermath of COVID-19, and prepare for future challenges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.024
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0050.004
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.112
GPT teacher head0.398
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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