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Record W2138497408 · doi:10.5993/ajhb.39.1.8

Psychosocial Factors and Theory in Physical Activity Studies in Minorities

2014· review· en· W2138497408 on OpenAlexaff
Scherezade K. Mama, Lorna H. McNeill, Sheryl McCurdy, Alexandra E. Evans, Pamela M. Diamond, Heather J. Adamus-Leach, Rebecca E. Lee

Bibliographic record

VenueAmerican Journal of Health Behavior · 2014
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Calgary
FundersNational Institute of Nursing ResearchNational Institutes of Health
KeywordsPsychosocialPsychological interventionEthnic groupPhysical activityClinical psychologyPsychologySocial supportMedicineGerontologyPsychotherapistPsychiatryPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVES: To summarize the effectiveness of interventions targeting psychosocial factors to increase physical activity (PA) among ethnic minority adults and explore theory use in PA interventions. METHODS: Studies (N = 11) were identified through a systematic review and targeted African American/Hispanic adults, specific psychosocial factors, and PA. Data were extracted using a standard code sheet and the Theory Coding Scheme. RESULTS: Social support was the most common psychosocial factor reported, followed by motivational readiness, and self-efficacy, as being associated with increased PA. Only 7 studies explicitly reported using a theoretical framework. CONCLUSIONS: Future efforts should explore theory use in PA interventions and how integration of theoretical constructs, including psychosocial factors, increases PA.

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)0.009
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.204
GPT teacher head0.524
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2014
Admission routes1
Has abstractyes

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