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Record W2012638227 · doi:10.2182/cjot.2010.77.3.4

Analyzing the Barriers and Supports of Knowledge Translation Using the PEO Model

2010· article· en· W2012638227 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsKnowledge translationOccupational therapyKnowledge managementPerspective (graphical)PsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge translation is a current and growing force in Canada's health care environment. PURPOSE: The intent of this paper is to examine current research related to barriers and facilitators of knowledge translation relevant to occupational therapy from the perspective of the person-environment-occupation (PEO) model. KEY ISSUES: Minimum competency and best practice are established drivers of research use in occupational therapy. Knowledge translation is not only complementary to these established drivers but offers a valuable contribution to the profession. Current research offers insight into the facilitators and obstacles of knowledge translation in occupational therapy, and the PEO model provides a framework for this analysis. IMPLICATIONS: Several influences across different levels of the practice system may facilitate or hinder knowledge translation. Awareness of the current research related to these influences, in concert with an awareness of individual circumstances, is an essential precursor to developing more effective knowledge translation strategies.

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.

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)0.003
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 score0.130
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.373
GPT teacher head0.522
Teacher spread0.149 · 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