Online Exercise Programming Among Older Adults: A Scoping Review
Bibliographic record
Abstract
Online exercise programming may promote physical activity while at home, but little is known about its use among older adults. Using the Arksey and O'Malley framework, we describe the nature and extent of the research pertaining to the use of online exercise programming among adults 65 years of age and older. We ran two separate searches (January 2005-September 2020 and October 2020-October 2021), yielding 17 articles that met our inclusion criteria. A total of 1,767 participants (69% female) ranging from 65 to 94 years of age were included. Most studies delivered the online programs asynchronously. The majority of studies assessed the feasibility of online programs, with 14 studies investigating health-related outcomes such as physical, psychological, and social health. Future research should explore perceptions and experiences of online exercise programming among older adults and the mechanisms by which it impacts physical, psychological, social, and behavioral outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".