Impacts of consumption tracking and tailored feedback on meeting nutritional recommendations: a longitudinal regression discontinuity study
Notice bibliographique
Résumé
BACKGROUND: Malnutrition continues to have large and negative impacts on millions of people. Lack of nutrition education and access to accurate information can be large barriers to healthy eating. METHODS: In this paper, we causally tested if providing participants with consumption tracking information accompanied by tailored messaging that referenced internationally recognized dietary guidelines improved their consumption patterns. To do so, we developed a smartphone application that participants used to record their consumption and that of their children. Those self-recorded data were then used to provide the participants with tailored feedback by comparing their recorded consumption against recommended consumption patterns. The causal impacts of the tailored feedback were estimated using a regression discontinuity estimation strategy and validated using alternative empirical strategies and a parallel dataset collected from the same participants by Community Health Volunteers. RESULTS: We found that the informational and feedback treatments improved consumption patterns of the caregivers and their children. Specifically, once caregivers began receiving tracking information and tailored feedback on their children's diet, their children's likelihood of meeting the minimum dietary threshold increased by at least 23 percentage points. An analogous, although smaller and less precisely estimated, effect on the caregivers' consumption was caused by providing them with tracking and feedback information on their own consumption. To verify these findings, we tested for the same effects using a parallel dataset collected by Community Health Volunteers from the same participants at the same period. The results of these analysis remained consistent with those estimated from self-recorded data but showed smaller effect sizes. Tests for persistence of the effects found no loss in impacts over the remaining months of the project. CONCLUSIONS: These findings show that improving access to information on recommended consumption and providing easy methods for tracking own performance against those recommendations can improve consumption patterns while also demonstrating that low-cost, light-touch approaches can be effective for collecting related data and delivering such services. TRIAL REGISTRATION: Pan African Clinical Trial Registry ACTR202407500217236. Retrospectively registered on July 15 2024.
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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 | 0,002 | 0,001 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».