Acceptability of home-based high-intensity functional strength training (HIFST) for older adults with preclinical mobility limitations after a slip, trip or fall: a qualitative description
Bibliographic record
Abstract
PURPOSE: To determine the acceptability of 12-weeks of a home-based high-intensity functional strength training (HIFST) intervention to older adult participants (≥ 55 years) with preclinical mobility limitations following a slip, trip, or fall. MATERIALS AND METHODS: A qualitative description study was conducted following a pilot randomized controlled trial of HIFST. HIFST was delivered virtually by a physiotherapist and utilized an interval format (alternating periods of "hard" effort of strengthening exercises with "easy" recovery). Participants randomized to the HIFST intervention were invited to participate in semi-structured interviews and an anonymous survey following intervention completion. RESULTS: Eleven participants (of 12 randomized to HIFST) completed interviews and 8 survey responses were received. Our findings were organized into six themes; "overall impression," "intervention coherence," "facilitators," "challenges and future suggestions," "perceived effectiveness," and "sustainability." Participants reported that the program was efficient, met their expectations and "made sense." Various facilitators to participation were noted including support from the physiotherapist and preference for a shorter interval length. Virtual delivery and intensity were not participation barriers. Participants reported benefits and clear individualized plans for future exercise. CONCLUSIONS: A home-based HIFST intervention delivered virtually was acceptable to participants. Participants reported a positive experience and minimal challenges encountered.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".