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Record W2105276634 · doi:10.1177/1078390310393508

Facilitating Knowledge Translation in the “Real World” of Community Psychiatry

2010· article· en· W2105276634 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.

Bibliographic record

VenueJournal of the American Psychiatric Nurses Association · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAppreciative Inquiry and Organizational Change
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyKnowledge translationTranslation (biology)PsychiatryMedicineComputer scienceKnowledge management

Abstract

fetched live from OpenAlex

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.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.307
Teacher spread0.278 · 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