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Record W2574562295 · doi:10.1080/17483107.2016.1277793

Preliminary reliability and internal consistency of the Wheelchair Components Questionnaire for Condition

2017· article· en· W2574562295 on OpenAlexaff
Karen Rispin, Melanie Dittmer, Jessica McLean, Joy Wee

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2017
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsQueen's University
FundersW. M. Keck Foundation
KeywordsWheelchairReliability (semiconductor)Consistency (knowledge bases)Manual wheelchairReliability engineeringRehabilitationPhysical medicine and rehabilitationPhysical therapyEngineeringMedicineComputer science

Abstract

fetched live from OpenAlex

Wheelchair durability and maintenance condition are key factors of wheelchair function. Durability studies done with double drum and drop testers, although valuable, do not perfectly imitate conditions of use. Durability may be harvested from clinical records; however, these may be inconsistent because protocols for recording information differ from place to place. Wheelchair professionals with several years of experience often develop a good eye for wheelchair maintenance condition. The Wheelchair Components Questionnaire for Condition (WCQc) was developed as a professional report questionnaire to provide data specifically on the maintenance condition of a wheelchair. The goal of this study was to obtain preliminary test-retest reliability and internal consistency for the WCQc. Participants were a convenience sample of wheelchair professionals who self-reported more than two years' of wheelchair experience, and completed the WCQc on the same wheelchair twice. Results indicated preliminary reliability and internal consistency for domain related questions and the entire questionnaire. Implications for rehabilitation The WCQc, if administered routinely at regular intervals, can be used to monitor wheelchair condition and alert users and health professionals about the need for repair or replacement. The WCQc is not difficult to use, making early monitoring for wear or damage more feasible. The earlier a tool can detect need for maintenance, the higher likelihood that appropriate measures may be employed in a timely fashion to maximize the overall durability of wheelchairs and minimize clinical complications. Keeping wheelchairs appropriately maintained allows users to minimize effort expended when using them, and maximize their function. It also lowers the risk of injury due to component failure. When assessing groups of similar wheelchairs, organizations involved in funding wheelchairs can use data from the WCQc to make purchase decisions based on durability, and manufacturers can use WCQc data for responsive design change.

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)0.018
metaresearch head score (Gemma)0.037
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 score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.024
GPT teacher head0.364
Teacher spread0.340 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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