Feasibility, Usability, and Acceptability of Online Mind–Body Exercise Programs for Older Adults: A Scoping Review
Bibliographic record
Abstract
Objectives:Engaging in mind–body exercises (MBEs: e.g., Tai Chi and yoga) can have physical and mental health benefits particularly for older adults. Many MBEs require precise timing and coordination of complex body postures posing challenges for online instruction. Such challenges include difficulty viewing instructors as they demonstrate different movements and lack of feedback to participants. With the shift of exercise programs to online platforms during the COVID-19 pandemic, we conducted a scoping review to examine the feasibility, usability, and acceptability of online MBE classes for older adults. Materials and Methods:We followed the scoping review methodology and adhered to the PRISMA reporting checklist. We searched five databases: Medline, Embase, CINHAL, Web of Science, and ACM digital library. Screening of articles and data extraction was conducted independently by two reviewers. Results:Of 6711 studies retrieved, 18 studies were included (715 participants, mean age 66.9 years). Studies reported moderate to high retention and adherence rates (mean >75%). Older adults reported online MBE classes were easy to use and reported high satisfaction with the online format. We also identified barriers (e.g., lack of space and privacy and unstable internet connection) and facilitators (e.g., convenience and technical support) to the online format. Opinions related to social connectedness were mixed. Conclusion:Online MBE programs for older adults appear to be a feasible and acceptable alternative to in-person programs. It is important to consider the type of exercise (e.g., MBE), diverse teaching styles, and learner needs when designing online exercise classes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".