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Record W2600254199 · doi:10.1080/17483107.2017.1299805

A longitudinal study assessing the maintenance condition of cadres of four types of wheelchairs provided in low-resource areas

2017· article· en· W2600254199 on OpenAlexaff
Karen Rispin, Kristofer Riseling, Joy Wee

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsQueen's University
FundersW. M. Keck Foundation
KeywordsWheelchairManual wheelchairResource (disambiguation)RehabilitationPhysical medicine and rehabilitationEngineeringTransport engineeringComputer sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

Wheelchair breakdowns increase the risk of injury and limit the mobility of wheelchair users. In the endeavour to meet the enormous global need for wheelchairs, manufacturers of wheelchairs for low-resource settings face a cost-benefit tension between affordability and durability. Field studies are needed to provide feedback on durability. Four manufacturers provided cadres of wheelchairs to the organization providing rehabilitation to students at a boarding school for children with disabilities in a low-resource area. The Wheelchair Components Questionnaire for Condition was used to evaluate wheelchair maintenance condition at several time intervals after fitting. Because the maintenance regime was not identical for the four wheelchair types, wheelchair types were not compared. Analysis of variance indicated differences in condition across time and between wheelchair components. Tukey's simultaneous comparison of means indicated that across the entire group, brakes, seats, casters and foot rests received lower ratings than frame. Preliminary data after each iteration of this study were provided to manufactures and resulted in responsive design changes. Implications for Rehabilitation Longitudinal studies with the Wheelchair Components Questionnaire for Condition (WCQc) have enabled manufacturers to make responsive design improvements. Additional studies could be done with other wheelchair types to result in responsive positive design changes for those wheelchairs as well. The WCQc can be used in studies on wheelchair condition even when records of repair history are not reliably available, a situation which is not uncommon in low-resource areas. Data sets collected at an individual clinic uses the WCQc could focus attention on wheelchair components needing regular repair. With that data in mind, the maintenance regime could be modified to respond and in so doing improve wheelchair condition and reduce loss of mobility or risk of injury. Organizations involved in funding wheelchairs for a particular location could use data from longitudinal studies done with the WCQc at that location to inform purchasing decisions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.431
Teacher spread0.378 · 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 teacher head, not a consensus.

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

Citations14
Published2017
Admission routes1
Has abstractyes

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