Expert consensus for a digital peer-led approach to improving physical activity among individuals with spinal cord injury who use manual wheelchairs
Bibliographic record
Abstract
Active Living Lifestyles for manual wheelchair users (ALLWheel) uses a digital peer-led approach to incorporate two behavior change theories to address a critical need for leisure-time physical activity (LTPA) programs for individuals with spinal cord injury (iSCI). The objective of this study was to obtain expert opinion and consensus for the ALLWheel program. Mixed-methods (qualitative and quantitative) were used to gather expert opinion and consensus for the ALLWheel program using an action research approach. Rehabilitation center. Experts in SCI and LTPA included iSCI who used manual wheelchairs, healthcare professionals, and community collaborators. Two, 90-minute focus groups were conducted and transcribed verbatim, analyzed thematically, and the results were used to create a Delphi survey. Delphi surveys were completed online using consecutive rounds until ≥70% consensus per item was attained. Cumulative percent concordances were calculated to determine consensus. Twelve experts in SCI and LTPA participated in focus groups. Four themes were generated: Need for LTPA programs; Important considerations; Perceptions about peer-coaches; and Feelings about smartphones, which were used to generate the Delphi survey. Consensus on the ALLWheel program was attained in two rounds. Experts established a need for fun and personalized community-based LTPA programs. Ensuring that healthcare professionals would be involved in the ALLWheel program alleviated safety concerns, and experts agreed there were benefits of peers delivering the program. Experts agreed that the ALLWheel program targeted important psychological factors (i.e. autonomy, relatedness, self-efficacy, and motivation) and affirmed the potential for a potentially large geographic reach.
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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 | 0.146 | 0.177 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".