MétaCan
Menu
Back to cohort
Record W4311280924 · doi:10.1177/10901981221139808

Motivational Interviewing Implementation in Primary Care: A “Terrifying Challenge” Becoming a “Professional Revelation”

2022· article· en· W4311280924 on OpenAlexaff
Sophie Langlois, Johanne Goudreau

Bibliographic record

VenueHealth Education & Behavior · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMotivational interviewingMedicineFocus groupMedical educationQualitative researchNursingPsychologyHealth carePsychological intervention

Abstract

fetched live from OpenAlex

INTRODUCTION: Motivational interviewing (MI) is an evidence-based counseling approach within primary care. However, MI rarely translates to practice following introductory training programs, and a lack of evidence regarding its implementation persists today. This study describes primary care clinicians' professional transformation in implementing MI through interprofessional communities of practice (ICP-MI). METHOD: Qualitative data collection involved the research journal, participant observation of four ICP-MIs (76 hours/16 clinicians), and focus groups. A general inductive approach was used for data analysis. Results were conceptualized based on the Consolidated Framework for Implementation Research. RESULTS: Four processes of MI implementation in primary care are presented as a motivational endeavor: ambivalence, introspection, experimentation, and mobilization. The clinicians were initially ambivalent, taking into consideration the significant challenges involved. After introspecting actual practices, they realized the limits of their previous clinician-centered approaches. The experimentation of MI in the workplace followed and enabled clinicians to witness MI feasibility and its added value. Finally, they were mobilized to ensure MI sustainability in their practices/organization. Intrinsic factors of influence included the clinicians' personal traits and their perception about MI as a clinical priority. Organizational support was also a crucial extrinsic factor in encouraging the clinicians' efforts. CONCLUSION: As described in a fragmented manner in previous studies, MI implementation processes and influencing factors are presented as integrated findings. Incorporating engaging educational activities to provide clinicians with motivational support and collaborating with health care organizations to plan appropriate resources should be considered in the development of MI implementation programs from the onset.

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)0.087
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.075
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0050.003
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.530
GPT teacher head0.662
Teacher spread0.133 · 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 designQualitative
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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHealth Education & BehaviorSame topicHealth Policy Implementation ScienceFrench-language works237,207