The Effectiveness of a Web-Based Application for a Balanced Diet and Healthy Weight Among Indonesian Pregnant Women: Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Pregnant women have self-declared that they have difficulties in estimating nutrient intakes. The Nutrition Information System for Indonesian Pregnant Women (SISFORNUTRIMIL) application was created as a dietary assessment and calorie-counting tool to guide pregnant women to eat the right portion sizes for each meal. OBJECTIVE: The study aimed to examine the effectiveness of the SISFORNUTRIMIL application in helping users achieve a balanced diet and healthy maternal weight gain in comparison to nonusers in Indonesia. METHODS: First-pregnancy women in the second trimester aged 19-30 years (N=112) participated in the randomized controlled trial. Recruited women who were eligible and consented to participate in the study were allocated into the intervention group, or application user (n=56), and the control group, or application nonuser (n=56). The intervention recommended that pregnant women consume at least 5 food groups and calculate a recommended average portion size for 12 weeks. Both groups were self-monitored and recorded their intake in food records for 3 days every week. The dietary diversity consumed, macro- and micronutrient intake, and maternal weight gain were assessed pre- and postintervention. Data were collected three times during the intervention. Diversity food consumption was measured by the Minimum Dietary Diversity for Women of reproductive age. Furthermore, the Indonesian recommended dietary allowances were used to refer to and validate appropriate energy and nutrient amounts. Independent sample t test was used to compare differences between the intervention and control groups. RESULTS: The mean dietary diversity score for the application user group (7.79, SD 1.20) was significantly greater than for the application nonuser group (7.02, SD 1.39; adjusted mean difference 0.77, 95% CI 0.28-1.25; d=0.28; P=.005). Macro- and micronutrient intake was significantly more in accordance with the dietary recommendations for the user group compared to the control group, including an energy daily intake of 156.88 kcal (95% CI 114.52-199.23; d=-1.39; P=.002), 102.43 g of carbohydrates (95% CI -125.2 to -79.60; d=-1.68; P=.02), 14.33 g of protein (95% CI 11.40-17.25; d=1.86; P<.001), and 10.96 g of fat (95% CI -13.71 to -8.20; d=-1.49; P<.001). Furthermore, there was a significantly higher intake of daily vitamins and minerals in the intervention group than in the control group. Other results showed that maternal weight gain in the intervention group was in accordance with the parameters of healthy weight gain. CONCLUSIONS: Recording food intake using the application was significantly effective in improving the dietary diversity consumed, improving adequate energy and nutrient intake, and producing healthy maternal weight during pregnancy. TRIAL REGISTRATION: ISRCTN Registry ISRCTN42690828; https://www.isrctn.com/ISRCTN42690828.
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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 | 0,016 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».