Use of systematic reviews in the development of new provincial public health policies in Ontario
Bibliographic record
Abstract
OBJECTIVES: The study determined whether the results of recently completed systematic reviews evaluating the effectiveness of public health interventions were used in the development of new provincial policies for public health practice. METHODS: This telephone survey included all members from five review groups who updated the Ontario Mandatory Health Programs and Services guidelines for Public Health in 2000. Independent variables included characteristics of the systematic reviews, organization, and the individual. Outcomes included the use of the reviews in developing new policies and the extent to which the reviews led to new recommendations for practice. Descriptive summaries as well as multiple linear regression were conducted. RESULTS: Eighty-five percent of decision-makers agreed to participate in the study. Ninety-six percent of respondents reported that the systematic reviews played a part in developing the new guidelines, while 47 percent indicated that the reviews contributed a great deal to the development of new recommendations for practice. The multiple linear regression model explained 42 percent of the variation in use of the reviews for developing new recommendations for practice. Significant predictor variables included the importance of the reviews in comparison to other sources of information and relevance of the reviews to the policy decisions. CONCLUSION: Public health decision-makers in Ontario have very positive perceptions of the usefulness of systematic reviews in policy development. Therefore, ongoing efforts to promote the usefulness and relevance of systematic reviews to public health decision-makers should remain a priority for health services researchers.
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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 | 0.446 | 0.756 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.018 | 0.023 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".