Developing a decision aid to guide public sector health policy decisions: A study protocol
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.
Bibliographic record
Abstract
BACKGROUND: Decision aids have been developed in a number of health disciplines to support evidence-informed decision making, including patient decision aids and clinical practice guidelines. However, policy contexts differ from clinical contexts in terms of complexity and uncertainty, requiring different approaches for identifying, interpreting, and applying many different types of evidence to support decisions. With few studies in the literature offering decision guidance specifically to health policymakers, the present study aims to facilitate the structured and systematic incorporation of research evidence and, where there is currently very little guidance, values and other non-research-based evidence, into the policy making process. The resulting decision aid is intended to help public sector health policy decision makers who are tasked with making evidence-informed decisions on behalf of populations. The intent is not to develop a decision aid that will yield uniform recommendations across jurisdictions, but rather to facilitate more transparent policy decisions that reflect a balanced consideration of all relevant factors. METHODS/DESIGN: The study comprises three phases: a modified meta-narrative review, the use of focus groups, and the application of a Delphi method. The modified meta-narrative review will inform the initial development of the decision aid by identifying as many policy decision factors as possible and other features of methodological guidance deemed to be desirable in the literatures of all relevant disciplines. The first of two focus groups will then seek to marry these findings with focus group members' own experience and expertise in public sector population-based health policy making and screening decisions. The second focus group will examine issues surrounding the application of the decision aid and act as a sounding board for initial feedback and refinement of the draft decision aid. Finally, the Delphi method will be used to further inform and refine the decision aid with a larger audience of potential end-users. DISCUSSION: The product of this research will be a working version of a decision aid to support policy makers in population-based health policy decisions. The decision aid will address the need for more structured and systematic ways of incorporating various evidentiary sources where applicable.
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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 | 0.025 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it