Evidence-informed decision-making in public health in Canada: a qualitative exploration
Bibliographic record
Abstract
INTRODUCTION: Evidence-informed decision-making (EIDM) plays a vital role in public health practice. Canada has invested in support for evidence-informed approaches in public health. Despite growing expectations for EIDM, evidence integration has not been thoroughly evaluated. OBJECTIVE: This study explores EIDM within Canadian public health organizations before the COVID-19 pandemic. A secondary objective is to explore how EIDM in public health was affected by the COVID-19 pandemic. METHODS: Using a qualitative descriptive approach, data were collected and analyzed from interviews with public health professionals across Canada. RESULTS: From interviews with 20 participants in four Canadian provinces and one territory, all participants noted that EIDM was valued, but there was considerable variation in implementation. Participants reported differences in consistency of evidence use, resources available at their public health organizations to support EIDM, and staff knowledge and skills in EIDM. Leadership emerged as a strong influencer of EIDM; however, leadership investment in EIDM varied. Changes in evidence use during the COVID-19 pandemic revealed an urgency for decision-making amidst an influx of evidence and reallocated staff roles. CONCLUSIONS: Despite gains in the recognized value of EIDM, gaps remain in the integration of evidence into decision-making and adequate resource investment to support EIDM. Time, resources, and skills to adapt processes and implement EIDM are needed for public health organizations in Canada to fully integrate EIDM into all aspects of public health decision-making. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A249.
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How this classification was reachedexpand
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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".