Higher Frailty Levels Are Associated With Increased Improvement in Health-Related Quality of Life Following a 12-Week Medical Student-Led Walking Program
Bibliographic record
Abstract
Higher frailty, or the accumulation of health deficits, is associated with worse health-related quality of life (HRQoL). Sustaining HRQoL is vital for overall well-being. Walk with a Future Doc (WWAFD) is a student-led community-based exercise and education program that is feasible and well-received by older adults. However, it is unknown how WWAFD influences HRQoL. This study tested the hypothesis that a 12-week WWAFD education and low-impact walking program would improve HRQoL, particularly among those with higher baseline frailty levels. Community-dwelling adults participated in a 12-week, medical student-led program including a 10-min educational talk and 50 min of self-paced walking once per week. All participants completed a 65-item validated Frailty Index and the EuroQol five-dimensions questionnaire at baseline and 12-weeks. Sixty-six participants were included (age: 65 ± 7 years [range: 47–85 years]; 47 females). Although there was no change in HRQoL from baseline (0.877 ± 0.137 [range: 0.038–0.949] to follow-up 0.878 ± 0.077 [range: 0.450–0.949]; p = .107), frailty at baseline (0.090 ± 0.073 [range: 0.000–0.394]) was associated with both baseline HRQoL (β = −1.353, 95% CI [−1.704, −1.003], p < .001) and larger improvements in HRQoL (0.001 ± 0.081 [range: −0.120, 0.415]; β = .663, 95% CI [0.387, 0.880], p < .001). Those with a higher frailty level at baseline exhibited the greatest improvements in HRQoL following the WWAFD community exercise program.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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 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".