Facilitating Knowledge Translation in the “Real World” of Community Psychiatry
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.
Bibliographic record
Abstract
BACKGROUND: Tobacco use disproportionately affects the well-being of individuals with mental illness. In community psychiatric settings, there are culturally embedded attitudes and behaviors regarding smoking that enable practitioners to remain ambivalent about their clients' tobacco use. OBJECTIVES: Given these cultural norms, the authors aimed to introduce evidence-informed smoking cessation interventions to a variety of interdisciplinary mental health care providers by using an innovative approach to knowledge translation. DESIGN: The authors used a case study design in which six community psychiatric settings were targeted. The organizational culture related to smoking was examined at each site before tailored tobacco reduction interventions were delivered. The study design was guided by the knowledge-to-action (KTA) process and two supplementary approaches to change: motivational interviewing (MI) and appreciative inquiry (AI). RESULTS/CONCLUSIONS: The principles of the KTA process, MI, and AI helped the authors to meaningfully engage with practice groups and change the organizational culture surrounding tobacco use in several community psychiatric settings.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it