Enhancing evidence-based practice in population health: staff views, barriers and strategies for change
Bibliographic record
Abstract
STUDY OBJECTIVE: To determine barriers and enablers for evidence-based practice (EBP) in population health and potential strategies for change. DESIGN: Self-administered survey of 104 professional staff (response rate, 73%) in the Division of Population Health, South Western Sydney Area Health Service in NSW serving a disadvantaged urban population. MAIN RESULTS: Most respondents (80%) "strongly agreed" or "agreed" that EBP would improve the effectiveness of their efforts in a disadvantaged region. However, more than half of respondents (56%) "strongly agreed" or "agreed" that there is lack of evidence for interventions in population health. Eighty two per cent of respondents "strongly agreed" or "agreed" that training in EBP is important for all population health workers. Those who used evidence also needed a greater capacity to discriminate "good" from "bad" research (85% in agreement). Contradictory policy was cited by one third of respondents as acting against EBP.
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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 | 0.103 | 0.175 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".