Influence of <i>Roulez avec confiance</i> , a peer-led community-based wheelchair skills training program, on manual wheelchair users
Bibliographic record
Abstract
Purpose Few studies have demonstrated that peer-led manual wheelchair (MWC) skills training can increase MWC skills, MWC use self-efficacy and satisfaction with participation of MWC users. Limited information is available on MWC skills training in the community. The primary objective was to measure the influence of Roulez avec confiance (RAC, which translated to “Wheeling with confidence”), a peer-led community-based wheelchair skills training program, on satisfaction with participation. The secondary objectives were to explore the: (1) influence of RAC on MWC use self-efficacy, MWC skills, and quality of life; (2) experiences of the participants who completed RAC and (3) three-month retention of outcomes.Methods A parallel mixed design was used with validated questionnaires on satisfaction with participation (WhOM), MWC use self-efficacy (WheelCon-M), MWC skills (WST-Q), quality of life (SWLS) and a semi-structured interview on participants’ experiences. Non-parametric longitudinal analyses of the questionnaires and thematic content analysis of the interviews were completed.Results Nineteen community-dwelling MWC users participated. There was a statistically significant increase (p < 0.0001) in all outcomes except quality of life (p = 0.16). Improvements were retained after three months. Participants mentioned their background influenced their experiences in RAC. Positive elements about RAC and areas for improvement were discussed. Participants reported overall positive social experiences and stated that the physical environment influenced RAC. Finally, participants spoke about what they learned and emotions they felt during RAC.Conclusions Peer-led community-based MWC training influenced satisfaction with participation, MWC skills, and MWC use self-efficacy. This study was a first step in demonstrating the efficiency of RAC.IMPLICATIONS FOR REHABILITATIONLimited information is available on manual wheelchair skills training in the community.Peer-led community-based manual wheelchair training influenced satisfaction with participation, manual wheelchair skills and use self-efficacy.This study was a first step in demonstrating the efficiency of Roulez Avec Confiance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".