MétaCan
Menu
Back to cohort
Record W4413448449 · doi:10.1177/21501319251368708

Integrated Virtual Exercise for Older Adults in Remote Patient Monitoring Program: A Feasibility Study

2025· article· en· W4413448449 on OpenAlexaffabout
Jake Tran, R. Ahluwalia, Danielle Kilby-Lechman, Bonaventure Amandi Egbujie

Bibliographic record

VenueJournal of Primary Care & Community Health · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of WaterlooQueen's University
Fundersnot available
KeywordsMedicinePhysical therapyGerontology

Abstract

fetched live from OpenAlex

Objectives: This study tested the feasibility of integrating a virtually facilitated exercise intervention into routine RPM program for older adults to establish its acceptability and patients’ satisfaction. Methods: We performed a retrospective analysis of data curated from a population-based virtual exercise intervention for older adults receiving RPM in Ontario, Canada. Results: A total of 16 patients participated in at least 1 exercise class, 64% were females, with mean (SD) age of 76 (±10) years. Overall, 100% of participants were “very satisfied” with the program, 81.3% (13) agreed/strongly agreed that the program “motivated them to move,” while 100% (16) agreed/strongly agreed that participating in the intervention has improved their physical endurance. Attendance to the virtual classes were relatively good with patients attending more than 60% of scheduled classes per session. Comorbidity had a strong effect on attendance, with the presence of each additional chronic condition associated with a 15.8% decline in attendance rate ( P = .005) over time Conclusion: Integrating a virtually facilitated exercise program into routine RPM program for older adults is feasible, acceptable, as well as safe. Larger studies are required to establish efficacy of the intervention in improve health outcomes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.373
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Primary Care & Community HealthSame topicStroke Rehabilitation and RecoveryFrench-language works237,207