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Record W4399261480 · doi:10.1123/japa.2023-0214

Synchronous Group-Based Online Exercise Programs for Older Adults Living in the Community: A Scoping Review

2024· review· en· W4399261480 on OpenAlexaff
Maria Fernanda Fuentes Diaz, Brianna Leadbetter, Vanessa Pitre, Martin Sénéchal, Danielle R. B̀ouchard

Bibliographic record

VenueJournal of Aging and Physical Activity · 2024
Typereview
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPsychologyGerontologyPhysical activityPhysical therapyApplied psychologyMedicine

Abstract

fetched live from OpenAlex

Older adults are the least physically active group with specific barriers to regular exercise, and online exercise programs could overcome some of those barriers. This scoping review aimed to describe the characteristics of supervised group-based synchronous online exercise programs for older adults living in the community, their feasibility, acceptability, and potential benefits. MEDLINE (Ovid), Embase, SPORTDiscus, and the Cumulative Index to Nursing and Allied Health Literature were searched until November 2022. The included studies met the following criteria: participants aged 50 years and above, a minimum of a 6-week group-based supervised and synchronous intervention, and original articles available in English. Eighteen articles were included, with 1,178 participants (67% female, average age of 71 [57-93] years), most (83%) published in the past 3 years. From the limited reported studies, delivering supervised, synchronous online exercise programs (one to three times/week, between 8 and 32 weeks) for older adults living in the community seems feasible, accepted, and can improve physical function.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.397
Teacher spread0.341 · 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 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

Citations8
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Aging and Physical ActivitySame topicTechnology Use by Older AdultsFrench-language works237,207