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Record W4387381446 · doi:10.1080/21642850.2023.2265136

Primary healthcare provider experience of knowledge brokering interventions for mood management

2023· article· en· W4387381446 on OpenAlexafffund
Nadia Minian, Anika Saiva, Sheleza Ahad, Allison Gayapersad, Laurie Zawertailo, Scott Veldhuizen, Arun Ravindran, Claire de Oliveira, Carol Mulder, Dolly Baliunas, Peter Selby

Bibliographic record

VenueHealth Psychology and Behavioral Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsQueen's UniversityPublic Health OntarioUniversity of TorontoInstitute for Clinical Evaluative SciencesCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsPsychological interventionPrimary careMoodHealth careHealth professionalsMedicinePsychologyKnowledge managementNursingFamily medicinePsychiatryComputer science

Abstract

fetched live from OpenAlex

Background: Knowledge brokering is a knowledge translation strategy used in healthcare settings to facilitate the implementation of evidence into practice. How healthcare providers perceive and respond to various knowledge translation approaches is not well understood. This qualitative study used the Theoretical Domains Framework to examine healthcare providers' experiences with receiving one of two knowledge translation strategies: a remote knowledge broker (rKB); or monthly emails, for encouraging delivery of mood management interventions to patients enrolled in a smoking cessation program. Methods: Semi-structured interviews were conducted with 21 healthcare providers recruited from primary care teams. We used stratified purposeful sampling to recruit participants who were allocated to receive either the rKB, or a monthly email-based knowledge translation strategy as part of a cluster randomized controlled trial. Interviews were structured around domains of the Theoretical Domains Framework (TDF) to explore determinants influencing practice change. Data were coded into relevant domains. Results: Both knowledge translation strategies were considered helpful prompts to remind participants to deliver mood interventions to patients presenting depressive symptoms. Neither strategy appeared to have influenced the health care providers on the domains we probed. The domains pertaining to knowledge and professional identity were perceived as facilitators to implementation, while domains related to beliefs about consequences, emotion, and environmental context acted as barriers and/or facilitators to healthcare providers implementing mood management interventions. Conclusion: Both strategies served as reminders and reinforced providers' knowledge regarding the connection between smoking and depressed mood. The TDF can help researchers better understand the influence of specific knowledge translation strategies on healthcare provider behavior change, as well as potential barriers and facilitators to implementation of evidence-informed interventions. Environmental context should be considered to address challenges and facilitate the movement of knowledge into clinical practice.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.790
GPT teacher head0.756
Teacher spread0.034 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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