Older Adults’ Perspectives on Participating in a Synchronous Online Exercise Program: Qualitative Study
Bibliographic record
Abstract
Background: Older adults face several barriers to exercise participation, including transportation, lack of access, and poor weather conditions. Such barriers may influence whether older adults meet the Canadian 24-Hour Movement Guidelines. Recently, older adults have adopted technology for health care and are increasingly using digital health technologies to improve their access to care. Therefore, technology may be a valuable tool to reduce barriers to exercise and increase exercise participation rates within this population. Objective: This study aimed to explore older adults' perceptions and experiences of exercise, in general, and specifically related to our synchronous online exercise program for community-dwelling older adults. Methods: A total of 3 registered kinesiologists and 1 physiotherapist with experience working with older adults delivered an 8-week, thrice-weekly synchronous online group-based exercise program for older adults in 3 cohorts. The program focused on strength, balance, and aerobic activity. Following the program, a qualitative study with interpretive descriptive design was conducted to explore participants' perceptions and experiences. Participants were invited to take part in a 30-minute, one-on-one semistructured interview via Zoom with a research team member. Interview data were thematically analyzed to identify common themes. Results: A total of 22 older adults (16 women, 6 men; mean age 70, SD 4 years) participated in interviews. Three themes were identified as follows: (1) health, exercise, and aging beliefs; (2) the pandemic interruption and impacts; and (3) synchronous online exercise programs attenuate barriers to exercise. Participants discussed their exercise beliefs and behaviors and their desire to safely and correctly participate in exercise. Older adults found that their physical activity was curtailed, routines disrupted, and access to in-person exercise programs revoked due to the pandemic. However, many suggested that our synchronous online exercise program was motivational and attenuated commonly reported environmental barriers to participation, such as transportation concerns (eg, time spent traveling, driving, and parking), accessibility and convenience by participating at a location of their choice, and removing travel-related concerns during poor weather conditions. Conclusions: Given these reported experiences, we posit that synchronous online exercise programs may help motivate and maintain adherence to exercise programs for older adults. These findings may be leveraged to improve health outcomes in community-dwelling older adults.
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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) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".