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Record W4408304298 · doi:10.1016/j.tjfa.2025.100034

Community-based physical activity and nutrition interventions in low-income and/or rural older adults: A scoping review

2025· review· en· W4408304298 on OpenAlexafffund
Elizabeth Bernard, N.T. Brewer, Jeanette Prorok, Perry Kim, John Muscedere

Bibliographic record

VenueThe Journal of Frailty & Aging · 2025
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersPublic Health Agency of Canada
KeywordsMedicinePsychological interventionGerontologyPhysical activityRural communityLow incomeEnvironmental healthPhysical therapyNursingEconomic growthSocioeconomics

Abstract

fetched live from OpenAlex

The objective of this review was to identify evidence-based, community-based physical activity (PA) and nutrition-based programs aimed at facilitating health behaviour change among low-income older adults and/or those living in rural/remote areas. This review followed the scoping review methodology proposed by Arksey & O'Malley. The Michie behaviour change wheel was used to categorize intervention types. Of the 2954 retrieved citations, 25 articles met the inclusion criteria. All study interventions demonstrated positive outcomes, including improvements in fruit and vegetable consumption, PA levels, physical function and nutrition knowledge. Study findings highlight that PA and nutrition-based interventions can be effective to facilitate behavior change in low-income and/or rural older adults. Limited research exists looking specifically at older adults living in rural communities, with only two of the 25 included articles including rural study populations.

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)0.002
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.365
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.121
GPT teacher head0.472
Teacher spread0.351 · 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 designSystematic review
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

Citations5
Published2025
Admission routes2
Has abstractyes

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