MétaCan
Menu
Back to cohort
Record W3028508710 · doi:10.1186/s13012-020-00984-2

Use of the GRADE approach in health policymaking and evaluation: a scoping review of nutrition and physical activity policies

2020· review· en· W3028508710 on OpenAlexaff
Jasmin Zähringer, Lukas Schwingshackl, Ani Movsisyan, Jan M Stratil, Sara Capacci, Jürgen M. Steinacker, Sarah Forberger, Wolfgang Ahrens, Daniela Kuellenberg de Gaudry, Holger J. Schünemann, Joerg J Meerpohl

Bibliographic record

VenueImplementation Science · 2020
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsImpactHealth Sciences CentreMcMaster University Medical Centre
FundersLudwig-Maximilians-Universität MünchenNarodowe Centrum Badań i RozwojuNorges ForskningsrådMinistero dell’Istruzione, dell’Università e della RicercaEconomic and Social Research CouncilBundesministerium für Bildung und ForschungInstitut National de la Recherche AgronomiqueZonMwUniversity of AucklandAlbert-Ludwigs-Universität FreiburgJoint Programming Initiative A healthy diet for a healthy life
KeywordsGrading (engineering)MedicineSystematic reviewCochrane LibraryMEDLINEHealth policyPhysical activityKnowledge translationPublic healthMedical educationAlternative medicineNursingPolitical sciencePhysical therapyKnowledge managementComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Nutrition and physical activity policies have the potential to influence lifestyle patterns and reduce the burden of non-communicable diseases. In the world of health-related guidelines, GRADE (Grading of Recommendations, Assessment, Development and Evaluation) is the most widely used approach for assessing the certainty of evidence and determining the strength of recommendations. Thus, it is relevant to explore its usefulness also in the process of nutrition and physical activity policymaking and evaluation. The purpose of this scoping review was (i) to generate an exemplary overview of documents using the GRADE approach in the process of nutrition and physical activity policymaking and evaluation, (ii) to find out how the GRADE approach has been applied, and (iii) to explore which facilitators of and barriers to the use of GRADE have been described on the basis of the identified documents. The overarching aim of this work is to work towards improving the process of evidence-informed policymaking in the areas of dietary behavior, physical activity, and sedentary behavior. METHODS: A scoping review was conducted according to current reporting standards. MEDLINE via Ovid, the Cochrane Library, and Web of Science were systematically searched up until 4 July 2019. Documents describing a body of evidence which was assessed for the development or evaluation of a policy, including documents labeled as "guidelines," or systematic reviews used to inform policymaking were included. RESULTS: Thirty-six documents were included. Overall, 313 GRADE certainty of evidence ratings were identified in systematic reviews and guidelines; the strength of recommendations/policies was assessed in four documents, and six documents mentioned facilitators or barriers for the use of GRADE. The major reported barrier was the initial low starting level of a body of evidence from non-randomized studies when assessing the certainty of evidence. CONCLUSION: This scoping review found that the GRADE approach has been used for policy evaluations, in the evaluation of the effectiveness of policy-relevant interventions (policymaking), as well as in the development of guidelines intended to guide policymaking. Several areas for future research were identified to explore the use of GRADE in health policymaking and evaluation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.312
metaresearch head score (Gemma)0.615
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.688
Threshold uncertainty score0.848

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3120.615
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0120.016
Bibliometrics0.0740.049
Science and technology studies0.0040.005
Scholarly communication0.0160.013
Open science0.0060.010
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.917
GPT teacher head0.793
Teacher spread0.124 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainMethods
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

Citations22
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueImplementation ScienceSame topicHealth Policy Implementation ScienceFrench-language works237,207