Instructors’ Perceptions and Experiences of Teaching Online Exercise Classes to Older Adults: A Qualitative Study
Bibliographic record
Abstract
Online exercise programming has become increasingly popular in recent years, including for older adults. Instructors hold unique perspectives on such programming that could yield important insights for effective program design and delivery. The purpose of this study was to qualitatively examine instructors' perceptions and experiences teaching exercise classes online to older adults. Using qualitative description, 19 instructors from a community exercise program for seniors completed a one-on-one semistructured interview. We analyzed data using reflexive thematic analysis and generated three main themes: (a) characteristics of effective online instructors, (b) challenges to delivering online exercise programming to older adults, and (c) future of online exercise programming. Most participants enjoyed delivering online exercise classes and developing the unique skills (particularly related to fostering social experiences and engaging with participants) required to be effective online exercise instructors. Our findings speak to the importance of ensuring instructors are adequately trained to deliver online exercise to seniors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".