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Record W2076820187 · doi:10.1353/cja.2005.0059

Wheelchair Use Among Community-Dwelling Older Adults: Prevalence and Risk Factors in a National Sample

2005· article· en· W2076820187 on OpenAlexaffabout
Philippa Clarke, Angela Colantonio

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsWheelchairLogistic regressionGerontologyOddsSample (material)Manual wheelchairNational Health Interview SurveyMedicineRehabilitationPsychologyPhysical therapyEnvironmental healthPopulationComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Older adults are the largest group of wheelchair users yet there are no peer-reviewed studies on the national profile of older wheelchair users in Canada. We investigated the characteristics of wheelchair users in a national sample of community-dwelling older adults from the Canadian Study of Health and Aging (CSHA-2). Questions on the use of assistive technology were asked of 5395 Canadians (over 64), and 4.6 per cent reported using a wheelchair. Logistic regression was used to model the factors associated with wheelchair use. Controlling for age, gender, and cognitive impairment, older adults who reported greater dependence in basic self-care and instrumental activities of daily living were more likely to use a wheelchair. However, the effects of self-care dependence on wheelchair use varied by gender, with men more likely than women to use wheelchairs with increasing self-care dependence. The number of chronic health conditions and being unmarried also increased the odds of wheelchair use. This paper quantifies the risk of wheelchair use according to critical factors that can be used to project use and plan for services. The data reported in this paper were collected as part of the Canadian Study of Health and Aging. The core study was funded by the Seniors' Independence Research Program, through the National Health Research and Development Program (NHRDP) of Health Canada (project no. 6606-3954-MC[S]). Additional funding was provided by Pfizer Canada Incorporated through the Medical Research Council/Pharmaceutical Manufacturers Association of Canada Health Activity Program, NHRDP (project no. 6603-1417–302[R]), Bayer Incorporated, and the British Columbia Health Research Foundation (projects no. 38[93-2] and no. 34[96-1]). The study was coordinated through the University of Ottawa and the Division of Aging and Seniors, Health Canada. Additional funds for the preparation of this manuscript were made available from the Opportunities Fund of the M-THAC Research Unit (from Medicare to Home and Community) at the University of Toronto, and from a post-doctoral fellowship awarded to the first author by the Social Sciences and Humanities Research Council of Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.036
GPT teacher head0.311
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations44
Published2005
Admission routes2
Has abstractyes

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