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Record W4400982320 · doi:10.1037/hea0001395

Training physicians in motivational communication: An integrated knowledge transfer study protocol.

2024· article· en· W4400982320 on OpenAlexafffund
Brigitte Voisard, Anda I. Dragomir, Vincent Gosselin Boucher, Geneviève Szczepanik, Simon Bacon, Kim Lavoie

Bibliographic record

VenueHealth Psychology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité du Québec à Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsKnowledge translationBehavior changeIntervention (counseling)Protocol (science)Health careMedicinePsychologyKnowledge managementMedical educationApplied psychologyNursingAlternative medicineComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: While behavior change counseling (BCC) targeting health risk behaviors has shown efficacy for improving patient health outcomes, barriers to knowledge translation have resulted in poor uptake among health care providers (HCPs). This article outlines the development of a new BCC training framework for HCPs, from inception to readiness for efficacy testing. It provides an example of integrated knowledge translation (iKT) used in alignment with the obesity-related behavioral intervention trials model. METHOD: (a) A modified Delphi process identified essential BCC skills for HCPs; (b) a survey assessed HCP attitudes and training needs; (c) an online competency assessment tool was developed using iKT mixed methods; (d) a training program was developed and refined using a logic model; and (e) the program was optimized using iterative rounds of participant feedback. A future proof-of-concept trial (f) will determine the program's readiness for full efficacy testing. RESULTS: = 11) provided key feedback, with minor changes being made to the program. CONCLUSIONS: In developing a new BCC framework, obstacles to BCC implementation were addressed through an iterative iKT process. This should improve eventual intervention uptake. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.785
GPT teacher head0.767
Teacher spread0.018 · 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 designNot applicable
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

Citations3
Published2024
Admission routes2
Has abstractyes

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