Comparison of Evidence Review Methodologies Used to inform Nutrition Recommendations
Notice bibliographique
Résumé
In an era of rising chronic disease rates and conflicting healthy eating messages, the public needs evidence-informed, credible healthy eating information to help guide their food choices. This is why credible scientific bodies have developed systematic approaches to reviewing evidence in order to inform nutrition recommendations. Health Canada compared the latest evidence review processes and grading methodologies that are used by credible scientific bodies to develop nutrition recommendations. An environmental scan of evidence review approaches used by credible scientific bodies was conducted. Websites of scientific bodies were searched, and flowcharts and summaries of each scientific body's evidence review process were developed. The evidence review processes were then assessed and compared between scientific bodies, and with their own previous approaches. Evidence review processes of 11 scientific bodies were included in the comparison. All scientific bodies use a systematic approach to gather and review evidence, including the use of systematic reviews, and involve experts in the review of evidence to determine its strength. However, expert groups use varying criteria to grade the evidence. Interesting similarities also exist in how the evidence review processes have evolved over time to strengthen scientific rigour and credibility. For efficiency, scientific bodies are increasingly using ‘review of systematic reviews’ in their evidence review as more systematic reviews have become available. In addition, there is improved transparency in evidence review methods and scientific bodies have increased efforts to engage the public. Overall, the methodologies of the scientific bodies are similar in their rigorous approach to reviewing evidence to inform the development of nutrition recommendations. However, they differ in how they engage experts and grade the strength of the evidence. Another difference is the transparency of their evidence review methods, which is important to allow for meaningful comparison and understanding of conclusions across scientific bodies. The authors received no specific funds for this work. The authors have no conflict of interest to declare.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».