MétaCan
Menu
Back to cohort

Frameworks, theories and models used in the development of health policies: A systematic review of systematic reviews

2025· review· en· W4414555535 on OpenAlexaff
Simone Diamandis, Tracey Thornley, Shalom I. Benrimoj, Kevin Ou, Sarah Dineen‐Griffin

Bibliographic record

VenueHealth Policy · 2025
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsFrancophone University Association
Fundersnot available
KeywordsSystematic reviewHealth policyPolicy developmentPolicy makingPublic healthHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: Health policies are established to address a specific health need, however, are not always the result of a rational process of evaluation or developed using established policy frameworks, theories or models (FTMs). Greater utilisation of FTMs in health policy making may provide further insight into policy development and overcome barriers to policy inaction. OBJECTIVE: The present review aimed to analyse the FTMs and their components underpinning health policy development, and health settings to which they are applied. METHOD: A systematic review was conducted following the PRISMA guidelines. Several databases were searched using keywords and MeSH terms. Quality appraisal was undertaken using the AMSTAR tool. RESULTS: From 1059 citations, 18 systematic reviews were identified. Twenty-eight FTMs were identified with 15 key components, with policy actors (85 %) and policy context (71 %) being most frequently mentioned. Policy FTMs were applied predominantly in health equity, population and public health (n = 16), sexual, reproductive and women's health (n = 14), HIV (n = 12), and physical activity, obesity prevention and nutrition (n = 12). CONCLUSION: The utilisation of health policy FTMs in the development of health policy may allow more targeted and relevant health policies to be developed. Further research into the critical components of health policy making may assist in developing a policy framework specific to health policy development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.073
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0730.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0150.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.736
GPT teacher head0.722
Teacher spread0.014 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueHealth PolicySame topicHealth Policy Implementation ScienceFrench-language works237,207