Should I stay or should I go? An exploratory study comparing wheelchair-adapted rowing at home vs. in community gyms
Bibliographic record
Abstract
PURPOSE: Wheelchair users experience many barriers to physical activity as affordable and accessible exercise equipment options are limited. Thus, the home-based adapted rower (aROW) and gym-based aROW were developed. The objectives were to determine: 1) wheelchair users' preferences, perspectives, facilitators, and barriers to using the home-based versus the gym-based aROW, 2) perceived usability of the home and gym aROWs, and 3) recommendations to adapt the aROW further for home and community use. MATERIALS AND METHODS: In this two-phase exploratory mixed-methods study, participants completed one month of using a home aROW, followed by one month of using a community gym aROW. After each phase, participants completed a semi-structured interview and the System Usability Scale (SUS) questionnaire. Interview data were analyzed using conventional content analysis and effect size comparing SUS data was calculated. RESULTS AND CONCLUSIONS: Four categories were identified: what worked well, barriers to using the aROWs, what could be improved and important considerations. There was a large effect size in perceived usability between the aROWs with participants preferring the home aROW. Overall, rowing was enjoyable, and participants achieved positive physical outcomes. As preferences are individual, the home aROW provides wheelchair users with a potential choice between home or gym exercise.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".