Scoping review of propelling aids for manual wheelchairs
Bibliographic record
Abstract
Manual wheelchair (MWC) users face a variety of obstacles limiting their participation. Different MWC models and new add-on components intended to improve propulsion may impact users’ function and participation, although there is a lack of research on this topic. The aims of this study were to: 1) identify MWC propelling aids (PA) that are reported in the literature; 2) classify the outcomes used to evaluate the influence of PA according to the International Classification of Functioning, Disability and Health (ICF); and 3) summarize evidence for the influence of PA. A scoping review was conducted in 2017 using Pubmed, Medline, Embase, CINAHL, Compendex, IEEE Xplore, RESNA and ISS proceedings, Google, and Google Scholar. The content of each manuscript was assessed by two independent reviewers. A total of 28 PA (19 human-powered; 9 power-assisted) were identified from 163 manuscripts. The three most cited ICF subdomains were “Activity & Participation” (n = 125), “Body Function” (n = 100), and “Personal Factors” (n = 55). The findings suggest an overall positive influence of PA on various ICF domains/subdomains, but initial findings should be interpreted with caution. Confirmation of the effect and safety of PA requires higher levels of evidence.
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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 | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".