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Record W4379801195 · doi:10.3390/ijerph20126058

Is Social Participation Associated with Successful Aging among Older Canadians? Findings from the Canadian Longitudinal Study on Aging (CLSA)

2023· article· en· W4379801195 on OpenAlexafffundabout
Mabel Ho, Eleanor Pullenayegum, Esme Fuller‐Thomson

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsLongitudinal studySuccessful agingGerontologyRecreationActivities of daily livingMental healthHealthy agingSocial engagementCohortHappinessBaseline (sea)PsychologyNeighbourhood (mathematics)MedicinePsychiatry

Abstract

fetched live from OpenAlex

The present study examines various activities of social participation (i.e., church or religious activities; educational or cultural activities; service club or fraternal organization activities; neighbourhood, community, or professional association activities; volunteer or charity work; and recreational activities) as contributing factors to successful aging. Successful aging in this study includes the following: adequate social support, no limitations with respect to Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs), no mental illness in the preceding year, no serious cognitive decline or pain that prevents activity, as well as high levels of happiness, and self-reports of good physical health, mental health, and successful aging. Methods: The Canadian Longitudinal Study on Aging (CLSA) is a large, national, longitudinal study on aging. A secondary analysis of the baseline (i.e., 2011–2015) and Time 2 (i.e., 2015–2018) data of the CLSA was conducted on a sample of 7623 older adults who were defined as “aging successfully” at baseline and were aged 60+ at Time 2. Binary logistic regression analyses were employed to examine the association between engaging in various social participation activities at baseline and aging successfully at Time 2. Results: In a subsample (n = 7623) of the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort who were aging successfully at baseline, the prevalence of successful aging at Time 2 was significantly higher among the participants who participated in volunteer or charity work and recreational activities compared to those who were not involved in these activities. After adjusting for 22 potential factors, the results of the binary logistic regression analyses reported that participants who, at baseline, participated in volunteer or charity work and recreational activities had higher age–sex-adjusted odds of achieving successful aging (volunteer or charity work: aOR = 1.17, 95% CI: 1.04, 1.33; recreational activities: aOR = 1.15, 95% CI: 1.00, 1.32). Conclusions: Among six types of social participation activities, people who participated in volunteer or charity work and recreational activities were more likely to achieve successful aging than their counterparts who did not engage in these activities. If these associations are found to be causal, policies and interventions encouraging older adults to participate in volunteer or charity work and recreational activities may support older adults to achieve successful aging in later life.

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 score0.015
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.182
GPT teacher head0.458
Teacher spread0.276 · 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

Citations17
Published2023
Admission routes3
Has abstractyes

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