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Record W2100930557 · doi:10.3138/ptc.2012-61

Examining the Use of Constraint-Induced Movement Therapy in Canadian Neurological Occupational and Physical Therapy

2013· article· en· W2100930557 on OpenAlexafffundvenueabout
Alana Fleet, Marion Che, Marilyn MacKay-Lyons, Diane MacKenzie, Stephen J. Page, Gail A. Eskes, Alison McDonald, Joy Boyce, Shaun G. Boe

Bibliographic record

VenuePhysiotherapy Canada · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsDalhousie University
FundersDalhousie UniversityHeart and Stroke Foundation of Canada
KeywordsOccupational therapyConstraint-induced movement therapyMedicineRehabilitationPhysical therapyPerceptionCognitionFamily medicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the use of constraint-induced movement therapy (CIMT) in Canadian neurological occupational and physical therapy. METHOD: An online survey was completed by occupational and physical therapists practising in Canadian adult neurological rehabilitation. We measured participants' practices, perceptions, and opinions in relation to their use of CIMT in clinical practice. RESULTS: A total of 338 surveys were returned for a 13% response rate; 92% of respondents knew of CIMT, and 43% reported using it. The majority (88%) of respondents using CIMT employed a non-traditional protocol. Self-rating of level of CIMT knowledge was found to be a significant predictor of CIMT use (p≤0.001). Commonly identified barriers to use included "patients having cognitive challenges that prohibit use of this treatment" and "lack of knowledge regarding treatment." CONCLUSIONS: Although the majority of respondents knew about CIMT, less than half reported using it. Barriers to CIMT use include lack of knowledge about the treatment and institutional resources to support its use. Identifying and addressing barriers to CIMT use-for example, by using continuing professional education to remediate knowledge gaps or developing new protocols that require fewer institutional resources-can help improve the feasibility of CIMT, and thus promote its clinical application.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.355
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.056
GPT teacher head0.279
Teacher spread0.223 · 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 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

Citations41
Published2013
Admission routes4
Has abstractyes

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