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Record W4386488551 · doi:10.1123/jsep.2022-0156

Social Supports and Barriers for Older Adults Not Participating in Group Physical Activity

2023· article· en· W4386488551 on OpenAlexaff
Lindsay Morrison, Meghan H. McDonough, Jennifer Hewson, Ann M. Toohey, Cari Din, Sarah Kenny

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2023
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyIntimidationOutreachFeelingSocial supportPhysical activitySocial psychologyAffect (linguistics)PopulationDevelopmental psychologyGerontologyCommunicationSociologyMedicine

Abstract

fetched live from OpenAlex

Group physical activity can provide physical and social benefits; however, social barriers or a lack of social support may affect participation. This study examined social-support needs and barriers among older adults who were not participating in group physical activities. Using interpretive description, semistructured interviews were conducted with 38 older adults (M = 70.9 years; 81.6% women). Themes were grouped into two categories. Category 1, expectations and initial impressions, consisted of the following: (a) Groups cannot meet everyone's expectations or interests, (b) groups are intimidating to join, and (c) the need for inclusive programming. Category 2, social processes within group physical activity, consisted of (a) modeling physical activity behaviors, (b) sharing information and suggestions about physical activity opportunities, and (c) encouragement and genuine interest. Outreach to this population should aim to address these barriers and utilize these supportive behaviors to reduce feelings of intimidation and promote participation among 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)0.001
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.045
GPT teacher head0.400
Teacher spread0.355 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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