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Record W4385751231 · doi:10.1017/s1368980023001714

An audit of the dissemination strategies and plan included in international food-based dietary guidelines

2023· article· en· W4385751231 on OpenAlexaboutno aff
Sze Lin Yoong, Heidi Turon, Carrie K. Wong, Lyndal Bayles, Meghan Finch, Courtney Barnes, Emma Doherty, Luke Wolfenden

Bibliographic record

VenuePublic Health Nutrition · 2023
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilSwinburne University of TechnologyHunter Medical Research Institute
KeywordsDisseminationInfographicInformation DisseminationAuditBusinessPopulationPublic relationsTarget audiencePublic healthMedicineMedical educationPolitical scienceEnvironmental healthComputer scienceMarketingWorld Wide WebNursingAccounting

Abstract

fetched live from OpenAlex

OBJECTIVE: Food-based dietary guidelines (FBDG) are an important resource to improve population health; however, little is known about the types of strategies to disseminate them. This study sought to describe dissemination strategies and content of dissemination plans that were available for FBDG. DESIGN: A cross-sectional audit of FBDG with a published English-language version sourced from the United Nations FAO repository. We searched for publicly available dissemination strategies and any corresponding plans available in English language. Two authors extracted data on strategies, which were grouped according to the Model for Dissemination Research Framework (including source, audience, channel and message). For guidelines with a dissemination plan, we described goals, audience, strategies and expertise and resources according to the Canadian Institute for Health Research guidance. SETTING: 18, 34 %) areas were included. PARTICIPANTS: n/a. RESULTS: The source of guidelines was most frequently health departments (79·2 %). The message included quantities and types of foods, physical activity recommendations and 88·7 % included summarised versions of main messages. The most common channels were infographics and information booklets, and the main end-users were the public. For twelve countries (22·6 %), we were able to source an English-language dissemination plan, where none met all recommendations outlined by the Canadian Institute for Health Research. CONCLUSIONS: The public was the most frequently identified end-user and thus most dissemination strategies and plans focused on this group. Few FBDG had formal dissemination plans and of those there was limited detailed provided.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.382
GPT teacher head0.537
Teacher spread0.156 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2023
Admission routes1
Has abstractyes

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