The Feasibility And Associated Physical Activity Outcomes Using An Online Exercise Program For Older Adults.
Bibliographic record
Abstract
Sedentary behaviour can accelerate age-related diseases and result in depression, anxiety, and loneliness. Physical activity can help to mitigate the risks of sedentary behaviour for older adults and alleviate mental health-related outcomes. Online exercise programs are valuable modes of delivery to facilitate exercise programs for older adults. PURPOSE: To determine the effectiveness and feasibility of an age-appropriate, ability-modified online exercise program delivered by trained exercise professionals for older adults. METHODS: In this pilot RCT, physically inactive community-dwelling older adults (65-80 years) were randomly assigned to a waitlist control (CON) or an active group (ACTIVE) of a thrice-weekly, 8-wk online live exercise program delivered via Zoom. Attendance was recorded, and participant satisfaction with the intervention was assessed. Pre- and post-intervention accelerometry-derived daily steps, daily active energy expenditure, and moderate-to-vigorous physical activity (MVPA) duration over 7 consecutive days were assessed. Depression, anxiety, and loneliness were assessed using the Geriatric Depression Scale (GDS), the Geriatric Anxiety Inventory (GAI), and the revised UCLA Loneliness Scale (R-UCLA). RESULTS: 31 participants (77% women) participated in the RCT. Participants were randomized into the ACTIVE group (n = 16; 70 ± 4 years) and the CON group (n = 15; 72 ± 5 years). The ACTIVE group attended 97% of the online classes, and 98% reported satisfaction with the program. There was no effect of the intervention compared to CON on daily steps (ACTIVE = 4336 ± 2638 steps/d; CON = 3125 ± 1250 steps/d), daily activity energy expenditure (ACTIVE = 227 ± 249 Kcal/d; CON = 119 ± 166 Kcal/d), and MVPA (ACTIVE = 42 ± 44 min/d; CON = 23 ± 30 min/d). An effect of the intervention was observed for depression from pre-intervention (ACTIVE = 3.9 ± 2.4; CON = 3.5 ± 2.1) to post-intervention (ACTIVE = 2.0 ± 1.7; CON = 3.5 ± 2.1; p = 0.015). There was no intervention effect compared to CON on anxiety or loneliness. CONCLUSION: Our age-appropriate, ability-modified online exercise program had good feasibility and adherence. We demonstrated preliminary insights into the feasibility and efficacy of a live online exercise program on older adults’ habitual physical activity levels and mental health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".