A Knowledge Transfer Strategy for Public Health Decision Makers
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to discover public health decision makers' preferences for content, format, and channels for receiving research knowledge, so as to begin development of a comprehensive national public health knowledge transfer strategy. A preliminary knowledge transfer strategy developed in part from the views expressed by public health decision makers in an earlier study (Dobbins et al. 2002b) was used as a foundation on which to base discussions. The research team believes strongly that consultation with potential users is crucial to ensure the conduct of relevant and timely research as well as the development of an effective knowledge transfer strategy. METHODS: Nine focus groups of five to seven participants were held in seven Canadian cities. Participants included medical officers of health, public health managers and directors, health promotion mangers, and health policymakers at provincial and federal levels. A semi-structured, open-ended interview guide was used to facilitate the discussion. The focus groups were audiotaped, and results were analyzed independently by two members of the research team who then developed key themes through a consensus process. RESULTS: Generally, participants spoke positively about the knowledge transfer strategy to which they were exposed. In addition, they supported the development of a registry of reviews evaluating the effectiveness of public health interventions rated by methodological quality of the evidence, with a summary statement of the reviews highlighting the results along with specific implications for practice. Participants also indicated they wanted to receive personalized updates of new reviews in their area of interest. Finally, the results highlighted a significant challenge related to knowledge management indicating opportunities for ongoing professional development and training. CONCLUSIONS: These findings were used to create an online registry of reviews evaluating the effectiveness of public health and health promotion interventions. The registry is one component of a comprehensive national public health knowledge transfer strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.128 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.015 | 0.022 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".