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Record W4411467779 · doi:10.3390/healthcare13131478

Social Participation Among Older Immigrants: A Cross-Sectional Study in Nine Cities in Canada

2025· article· en· W4411467779 on OpenAlexafffundabout
Sepali Guruge, Souraya Sidani, Jill Hanley

Bibliographic record

VenueHealthcare · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsYork UniversityMcGill UniversityToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImmigrationHobbySocial engagementPsychological interventionMandarin ChineseArabicGerontologyDescriptive statisticsSocial supportSocial mediaQuality of life (healthcare)PsychologyCross-sectional studyMedicineSociologySocial psychologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Background/Objectives: Social participation is important for healthy aging but challenging for older immigrants because of factors such as the loss of cultural community, language and transportation barriers, ageism, and racism. This study aimed to examine (1) the type of social activities in which older immigrants from Arabic (Arab), Mandarin (East Asian), and Punjabi-speaking (South Asian) communities in Canada engage; (2) their desire for more participation in social activities; and (3) factors they perceive as preventing their engagement in more social activities. Methods: Using a cross-sectional design, we collected data, using existing measures, from 476 older immigrants between fall 2022 and winter 2023. Descriptive statistics were used to analyze the data. Results: More than 75% of participants reported engagement in three solitary activities (having a hobby, going on a day trip; and using the internet and/or email) and more than 85% participated in community-based activities with family inside and outside and with friends outside the household. Most (71%) expressed a desire to participate in more social activities in the community, but they were prevented from doing so due to factors such as language barriers or not wanting to go alone. Conclusions: Interventions are needed to facilitate community-based participation among older immigrants and improve their quality of 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.028
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.426
Teacher spread0.374 · 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 teacher head, 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

Citations2
Published2025
Admission routes3
Has abstractyes

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