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Record W3034026879 · doi:10.1123/japa.2019-0393

“Not Everybody’s an Athlete, But They Certainly Can Move”: Facilitators of Physical Activity Maintenance in Older Adults in a Northern and Rural Setting

2020· article· en· W3034026879 on OpenAlexaboutno aff
Kirsten Ward, Anne Pousette, Chelsea Pelletier

Bibliographic record

VenueJournal of Aging and Physical Activity · 2020
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisGerontologyPhysical activityHealthy agingPsychologyIndependent livingSocial supportQualitative researchMedicinePhysical therapySocial psychologySociology

Abstract

fetched live from OpenAlex

Although the benefits of maintaining a physical activity regime for older adults are well known, it is unclear how programs and facilities can best support long-term participation. The purpose of this study is to determine the facilitating factors of physical activity maintenance in older adults at individual, program, and community levels. Nine semistructured interviews were conducted with individuals aged 60 years and older and long-term participants (>6 months) in community-based group exercise at a clinical wellness facility in northern British Columbia, Canada. Interviews were audio recorded, transcribed, and analyzed via inductive thematic analysis. Themes identified as facilitators of physical activity included (a) social connections, (b) individual contextual factors, and (c) healthy aging. Older adults are more likely to maintain physical activity when environments foster healthy aging and provide opportunity for social engagement.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0010.003
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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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