Rethinking the Social Determination of Food in Chile Through Practices and Interactions of Actors in Food Environments: Nonexperimental, Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Food environments are crucial for promoting healthy and sustainable eating and preventing obesity. However, existing food environment frameworks assume an already installed causality and do not explain how associations in food environments are established or articulated, especially from an integrative and transdisciplinary approach. This research attempts to bridge these gaps through the use of Actor-Network Theory, which traces the relationship network between human (and nonhuman) actors in order to describe how these interact and what agencies (direct or remote) are involved. OBJECTIVE: This study aims to explain the practices and interactions of actors in food environments in order to approach the problem of unhealthy eating with a transdisciplinary approach. METHODS: This is a nonexperimental, cross-sectional study. Due to the complexity of the study phenomena, a mixed methods approach with 4 consecutive phases will be developed in Chile. Phase 1 involves a systematic literature review of food environment evidence since 2015, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol; phase 2 involves the application of a shortened version of the Nutrition Environment Measure Scale-Perceptions adapted to Chile (NEMS-P-Ch) in 2 neighborhoods with different socioeconomic levels; in phase 3, six focus groups in each neighborhood will be conducted to address social determinants such as gender, employment status, and migration; and in phase 4, participant observation and in-depth interviews will be used to analyze the direct and empirical exploration of the actors in their daily interaction with food environments. The triangulation and complementarity of the data will allow us to create a practical model about the practices and interactions of actors in their food environments, which reflects the complexity and transdisciplinary nature of the study. RESULTS: We have advanced in phases 1-3 of the study. In phase 1, a total of 109 manuscripts are being revised for data extraction. In phase 2, we applied the NEMS-P-Ch to 785 people, 49.4% (388/785) of whom belong to a low socioeconomic neighborhood. Participants from phase 2 are being contacted to participate in the focus groups (phase 3). By the end of July, we have conducted 6 focus groups with 5-11 participants. CONCLUSIONS: This study will provide a comprehensive understanding of how individuals interact with their food environments, offering deep insights into the factors influencing their food-related decisions. In addition, the study aims to develop a model that more accurately reflects reality by examining not only the food environments themselves but also the interactions among various stakeholders within these environments and their daily practices. The findings of this study will offer evidence-based insights to inform public policies tailored to the specific territories and communities under investigation or those with similar characteristics. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/62765.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».