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Record W3173557039 · doi:10.1123/jsep.2020-0335

Experiences With Social Participation in Group Physical Activity Programs for Older Adults

2021· article· en· W3173557039 on OpenAlexaff
Chantelle Zimmer, Meghan H. McDonough, Jennifer Hewson, Ann M. Toohey, Cari Din, Peter R.E. Crocker, Erica Bennett

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2021
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsPsychosocialPsychologyRecreationFocus groupSocial engagementSocial contactContext (archaeology)Social environmentSocial relationGerontologyDevelopmental psychologySocial psychologySociologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Little is known about how social participation can be facilitated among older adults in group physical activity and its psychosocial benefits that contribute to successful aging. This study aimed to understand older adults' experiences with social participation in group physical activity programs. Using interpretive description methodology, 16 observations, eight focus groups, and two interviews with participants unable to attend focus groups were conducted with adults 55 years and older attending programs across four recreation facilities. Group programs were found to influence social participation through (a) a meaningful context for connecting and (b) instructors' expectations of social interaction. Social participation in these programs addressed psychosocial needs by (c) increasing social contact and interaction, (d) fostering social relationships and belonging, and (e) promoting regular engagement. Training for instructors should include balancing the physical aspects of program delivery with the social, while also considering older adults' diverse needs and preferences for social interaction.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.395
Teacher spread0.354 · 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

Citations38
Published2021
Admission routes1
Has abstractyes

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