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Record W4386935218 · doi:10.1186/s13012-023-01295-y

Strategies for enacting health policy codesign: a scoping review and direction for research

2023· review· en· W4386935218 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueImplementation Science · 2023
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsHealth policyHealth services researchCINAHLHealth informaticsNursing researchTerminologyKnowledge translationHealth administrationHealth careMedicinePublic relationsKnowledge managementPolitical sciencePublic healthComputer scienceNursingPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Strategies for supporting evidence-informed health policy are a recognized but understudied area of policy dissemination and implementation science. Codesign describes a set of strategies potentially well suited to address the complexity presented by policy formation and implementation. We examine the health policy literature describing the use of codesign in initiatives intended to combine diverse sources of knowledge and evidence in policymaking. METHODS: The search included PubMed, MEDLINE, PsychInfo, CINAHL, Web of Science, and Google Scholar in November 2022 and included papers published between 1996 and 2022. Terms included codesign, health, policy, and system terminology. Title and abstracts were reviewed in duplicate and included if efforts informed policy or system-level decision-making. Extracted data followed scoping review guidelines for location, evaluation method, health focus, codesign definition, description, level of health system user input, sectors involved, and reported benefits and challenges. RESULTS: From 550 titles, 23 citations describing 32 policy codesign studies were included from multiple continents (Australia/New Zealand, 32%; UK/Europe, 32%; South America, 14%; Africa, 9%; USA/Canada 23%). Document type was primarily case study (77%). The area of health focus was widely distributed. Policy type was more commonly little p policy (47%), followed by big p policy (25%), and service innovations that included policy-enabled funding (25%). Models and frameworks originated from formal design (e.g., human-centered or participatory design (44%), political science (38%), or health service research (16%). Reported outcomes included community mobilization (50%), policy feasibility (41%), improved multisector alignment (31%), and introduction of novel ideas and critical thinking (47%). Studies engaging policy users in full decision-making roles self-reported higher levels of community mobilization and community needs than other types of engagement. DISCUSSION: Policy codesign is theoretically promising and is gaining interest among diverse health sectors for addressing the complexity of policy formation and implementation. The maturity of the science is just emerging. We observed trends in the association of codesign strategies and outcomes that suggests a research agenda in this area could provide practical insights for tailoring policy codesign to respond to local contextual factors including values, needs, and resources.

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.

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)0.057
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0570.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.006
Science and technology studies0.0080.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.977
GPT teacher head0.882
Teacher spread0.095 · 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