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Record W4385995166 · doi:10.1093/geroni/igad086

Worsened Ability to Engage in Social and Physical Activity During the COVID-19 Pandemic and Older Adults’ Mental Health: Longitudinal Analysis From the Canadian Longitudinal Study on Aging

2023· article· en· W4385995166 on OpenAlexafffundabout
Theodore D. Cosco, Andrew Wister, John R. Best, Indira Riadi, Lucy Kervin, Shawna Hopper, Nicole E. Basta, Christina Wolfson, Susan Kirkland, Lauren E. Griffith, Jacqueline M. McMillan, Parminder Raina

Bibliographic record

VenueInnovation in Aging · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsMcMaster UniversityDalhousie UniversityUniversity of CalgaryImpactMcGill UniversityMcGill University Health CentreSimon Fraser University
FundersCanadian Institutes of Health ResearchMcMaster Institute for Research on Aging, McMaster UniversityMichael Smith Health Research BCPublic Health Agency of CanadaGovernment of CanadaPublic Health AgencyMcMaster University
KeywordsLongitudinal studyAnxietyPandemicDepression (economics)Mental healthGerontologyCohort studyEpidemiologyOdds ratioPsychologyCohortConfidence intervalOddsMedicineMulticenter AIDS Cohort StudyLogistic regressionDemographyCoronavirus disease 2019 (COVID-19)PsychiatryDiseaseHuman immunodeficiency virus (HIV)Viral loadFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background and Objectives Restrictions implemented to mitigate the transmission of coronavirus disease 2019 (COVID-19) affected older adults’ ability to engage in social and physical activities. We examined mental health outcomes of older adults reporting worsened ability to be socially and physically active during the pandemic. Research Design and Methods Using logistic regression, we examined the relationship between positive screen for depression (10-item Center for Epidemiological Studies—Depression Scale) or anxiety (7-item Generalized Anxiety Scale) at the end of 2020 and worsened ability to engage in social and physical activity during the first 6–9 months of the pandemic among older adults in Canada. Interactions between ability to participate in social and physical activity and social participation pre-COVID (2015–2018) and physical activity were also examined. We analyzed data collected before and during the COVID pandemic from the Canadian Longitudinal Study on Aging, a nationally representative longitudinal cohort: pre-pandemic (2015–2018), COVID-Baseline survey (April to May 2020), and COVID-Exit survey (September to December 2020). Results Of the 24,108 participants who completed the COVID-Exit survey, 21.96% (n = 5,219) screened positively for depression and 5.04% (n = 1,132) for anxiety. Worsened ability to participate in social and physical activity was associated with depression (odds ratio [OR] = 1.85 [95% confidence interval {CI} 1.67–2.04]; OR = 2.46 [95% CI 2.25–2.69]), respectively, and anxiety (OR = 1.66 [95% CI 1.37–2.02] and OR = 1.96 [95% CI 1.68–2.30]). Fully adjusted interaction models identified a buffering effect of social participation and the ability to participate in physical activity on depression (χ2 [1] = 8.86, p = .003 for interaction term). Discussion and Implications Older adults reporting worsened ability to participate in social and physical activities during the COVID-19 pandemic had poorer mental health outcomes than those whose ability remained the same or improved. These findings highlight the importance of fostering social and physical activity resources to mitigate the negative mental health impacts of future pandemics or other major life stressors that may affect the mental health of older adults.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.181
GPT teacher head0.472
Teacher spread0.290 · 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 designObservational
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

Citations5
Published2023
Admission routes3
Has abstractyes

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