Wheelchair services and use outcomes: A cross-sectional survey in Kenya and the Philippines
Bibliographic record
Abstract
BACKGROUND: The World Health Organisation recommends that services accompany wheelchair distribution. This study examined the relationship of wheelchair service provision in Kenya and the Philippines and wheelchair-use-related outcomes. METHOD: We surveyed 852 adult basic manual wheelchair users. Participants who had received services and those who had not were sought in equal numbers from wheelchair-distribution entities. Outcomes assessed were daily wheelchair use, falls, unassisted outdoor use and performance of activities of daily living (ADL). Descriptive, bivariate and multivariable regression model results are presented. RESULTS: Conditions that led to the need for a basic wheelchair were mainly spinal cord injury, polio/post-polio, and congenital conditions. Most Kenyans reported high daily wheelchair use (60%) and ADL performance (80%), while these practices were less frequent in the Philippine sample (42% and 74%, respectively). Having the wheelchair fit assessed while the user propelled the wheelchair was associated with greater odds of high ADL performance in Kenya (odds ratio [OR] 2.8, 95% confidence interval [CI] 1.6, 5.1) and the Philippines (OR 2.8, 95% CI 1.8, 4.5). Wheelchair-related training was associated with high ADL performance in Kenya (OR 3.2, 95% CI 1.3, 8.4). In the Philippines, training was associated with greater odds of high versus no daily wheelchair use but also odds of serious versus no falls (OR 2.5, 95% CI 1.4, 4.5). CONCLUSION: Select services that were associated with some better wheelchair use outcomes and should be emphasised in service delivery. Service providers should be aware that increased mobility may lead to serious falls.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".