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Record W2486392379 · doi:10.1017/cjn.2016.258

Building a Knowledge to Action Program in Stroke Rehabilitation

2016· review· en· W2486392379 on OpenAlexafffundvenue
Shannon Janzen, Amanda McIntyre, Marina Richardson, Eileen Britt, Robert Teasell

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2016
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsWestern UniversitySt Joseph's Health CareCanadian Agency for Drugs and Technologies in HealthParkwood InstituteLondon Health Sciences CentreLawson Health Research Institute
FundersCanadian Stroke NetworkOntario Ministry of Health and Long-Term CareAcademic Medical Organization of Southwestern OntarioHeart and Stroke Foundation of Canada
KeywordsRehabilitationAuditAction (physics)Process (computing)Stroke (engine)Best practiceEvidence-based practiceClinical PracticePsychologyAction researchMedical educationMedicinePhysical medicine and rehabilitationProcess managementNursingPhysical therapyComputer scienceAlternative medicineBusinessEngineeringPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

The knowledge to action (KTA) process proposed by Graham et al (2006) is a framework to facilitate the development and application of research evidence into clinical practice. The KTA process consists of the knowledge creation cycle and the action cycle. The Evidence Based Review of Stroke Rehabilitation is a foundational part of the knowledge creation cycle and has helped guide the development of best practice recommendations in stroke. The Rehabilitation Knowledge to Action Project is an audit-feedback process for the clinical implementation of best practice guidelines, which follows the action cycle. The objective of this review was to: (1) contextualize the Evidence Based Review of Stroke Rehabilitation and Rehabilitation Knowledge to Action Project within the KTA model and (2) show how this process led to improved evidence-based practice in stroke rehabilitation. Through this process, a single centre was able to change clinical practice and promote a culture that supports the use of evidence-based practices in stroke rehabilitation.

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)0.019
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0050.003
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0030.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.297
GPT teacher head0.521
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2016
Admission routes3
Has abstractyes

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