Prevalence of Wheelchair and Scooter Use Among Community-Dwelling Canadians
Bibliographic record
Abstract
BACKGROUND: Mobility impairments are the third leading cause of disability for community-dwelling Canadians. Wheelchairs and scooters help compensate for these challenges. There are limited data within the last decade estimating the prevalence of wheelchair and scooter use in Canada. OBJECTIVE: The aims of this study were: (1) to estimate the prevalence of wheelchair and scooter use in Canada and (2) to explore relevant demographic characteristics of wheelchair and scooter users. DESIGN: This study was a secondary analysis of a cross-sectional national survey. METHODS: The Canadian Survey on Disability (2012) collected data on wheelchair and scooter use from community-dwelling individuals aged 15 years and over with a self-identified activity limitation on the National Household Survey. Prevalence estimates were calculated as weighted frequencies, with cross-tabulations to determine the number of wheelchair and scooter users in Canada, by province, and demographic characteristics (ie, age, sex) and bootstrapping to estimate the variance of all point estimates. RESULTS: There were approximately 288,800 community-dwelling wheelchair and scooter users aged 15 years and over, representing 1.0% of the Canadian population. The sample included 197,560 manual wheelchair users, 42,360 powered wheelchair users, and 108,550 scooter users. Wheelchair and scooter users were predominantly women, with a mean age of 65 years. Approximately 50,620 individuals used a combination of 2 different types of devices. LIMITATIONS: The results are representative of individuals living in the community in Canada and exclude individuals in residential or group-based settings; estimates do not represent the true population prevalence. CONCLUSION: This analysis is the first in more than 10 years to provide a prevalence estimate and description of wheelchair and scooter users in Canada. Since 2004, there has been an increase in the proportion of the population who use wheelchairs and scooters, likely related to an aging Canadian population. These new prevalence data have potential to inform policy, research, and clinical practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".