Feasibility of the Enhancing Participation In the Community by improving Wheelchair Skills (EPIC Wheels) program: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Many older adults rely on a manual wheelchair for mobility but typically receive little, if any, training on how to use their wheelchair effectively and independently. Standardized skill training is an effective intervention, but limited access to clinician trainers is a substantive barrier. Enhancing Participation in the Community by Improving Wheelchair Skills (EPIC Wheels) is a 1-month monitored home training program for improving mobility skills in older novice manual wheelchair users, integrating principles from andragogy and social cognitive theory. The purpose of this study is to determine whether feasibility indicators and primary clinical outcome measures of the EPIC Wheels program are sufficiently robust to justify conducting a subsequent multi-site randomized controlled trial. METHODS: A 2 × 2 factorial randomized controlled trial at two sites will compare improvement in wheelchair mobility skills between an EPIC Wheels treatment group and a computer-game control group, with additional wheelchair use introduced as a second factor. A total of 40 community-dwelling manual wheelchair users at least 55 years old and living in two Canadian metropolitan cities (n = 20 × 2) will be recruited. Feasibility indicators related to study process, resources, management, and treatment issues will be collected during data collection and at the end of the study period, and evaluated against proposed criteria. Clinical outcome measures will be collected at baseline (pre-randomization) and post-intervention. The primary clinical outcome measure is wheelchair skill capacity, as determined by the Wheelchair Skills Test, version 4.1. Secondary clinical outcome measures include wheelchair skill safety, satisfaction with performance, wheelchair confidence, life-space mobility, divided-attention, and health-related quality of life. DISCUSSION: The EPIC Wheels training program offers several innovative features. The convenient, portable, economical, and adaptable tablet-based, home program model for wheelchair skills training has great potential for clinical uptake and opportunity for future enhancements. Theory-driven design can foster learning and adherence for older adults. Establishing the feasibility of the study protocol and estimating effect size for the primary clinical outcome measure will be used to develop a multi-site randomized controlled trial to test the guiding hypotheses. TRIAL REGISTRATION: Clinical Trials NCT01740635.
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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 | 0.067 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".