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Record W2328275098 · doi:10.1177/0008417414546743

Randomized controlled trial protocol feasibility: The Wheelchair Self-Efficacy Enhanced for Use (WheelSeeU)

2014· article· en· W2328275098 on OpenAlexafffundvenue
Krista L. Best, William C. Miller, Janice J. Eng, François Routhier, Charles H. Goldsmith

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité LavalSimon Fraser UniversityCentre for Interdisciplinary Research in RehabilitationGF Strong Rehabilitation CentreUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsWheelchairRandomized controlled trialManual wheelchairPhysical therapyMedicineQuality of life (healthcare)Protocol (science)Physical medicine and rehabilitationRehabilitationPopulationPsychologyComputer scienceNursingAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Manual wheelchairs (MWCs) can improve mobility and social participation for individuals who experience difficulty walking; however, older adults receive little training for wheelchair use. The Wheelchair Self-Efficacy Enhanced for Use (WheelSeeU) research program provides peer-led training that may positively influence wheelchair use while reducing clinician burden. PURPOSE: The purpose of this study is to evaluate the feasibility and clinical outcomes of WheelSeeU. METHOD: A randomized control trial (RCT) recruits and randomly assigns 40 MWC users (55+ years). Feasibility indicators assessing process, resource, management, and treatment issues are measured, and clinical outcomes (wheelchair skills, safety, confidence, mobility, social participation, quality of life, health utility) are collected at three time points. IMPLICATIONS: WheelSeeU provides an innovative approach for teaching wheelchair skills to an aging population that may improve wheelchair use and decrease clinician burden. Since RCTs are expensive and challenging in rehabilitation, establishing feasibility prior to larger effectiveness trials is prudent.

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)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.192
GPT teacher head0.463
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations17
Published2014
Admission routes3
Has abstractyes

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