A Smartphone App (PRIMI) to Promote Healthy Diet, Physical Activity, and Health Literacy After Childbirth Among Migrant Women: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Migrant health, including reproductive health, is an important public health priority. The postpartum period is a critical window for establishing healthy behaviors that can impact long-term health. Mobile health interventions offer a scalable solution, but existing tools are often not culturally or linguistically adapted for diverse populations. To the best of our knowledge, no previous study has evaluated the effectiveness of a culturally targeted mobile health intervention delivered after childbirth to promote a healthy diet and physical activity among migrant women. OBJECTIVE: The PRIMI (Promoting Reproductive Health in Migrant Women) trial will determine the effectiveness of a smartphone app (the PRIMI app) on primary (diet quality and moderate-to-vigorous physical activity) and secondary (health literacy, BMI, self-efficacy, and self-rated health) outcomes in first-generation migrant women after childbirth. METHODS: A 2-arm randomized controlled trial will be conducted to examine the effectiveness of the PRIMI app. First-generation migrant women who have given birth within 6 months, are aged 18 years or older, and prefer to receive health-related information in any of the provided languages are eligible to participate in the study and will be recruited through health care services in Sweden. The women will be randomized to the control group (standard care, eg, parental guidance and support within child health care) or the intervention group (PRIMI app+standard care) in a 1:1 ratio. A total of 200 women (100 per group) will be included in the study. A waitlist control strategy will be applied so that women in the control group will receive the PRIMI app after the follow-up measurement at 6 months. Outcomes will be assessed at baseline and at the 6-month follow-up. The PRIMI app, developed within the PRIMI project, is compatible with both Android and iOS. It contains weekly changing themes focusing on physical activity, diet, and health literacy throughout the 6-month intervention period. The app integrates behavior change techniques such as feedback and monitoring, goal setting, and instructions on how to perform the behavior. The app's language can be switched among 4 common languages (Arabic, Somali, English, and Swedish), and all textual content can be accessed through audio files for listening. All procedures have been approved by the Swedish Ethical Review Authority (reference 2022-06733-01 and 2024-00135-02). RESULTS: Recruitment of study participants is planned to begin in September 2025. We anticipate completing recruitment in 2026 and that the results of the PRIMI trial will be available in 2027. CONCLUSIONS: This study will provide novel evidence on the effectiveness of the PRIMI app in promoting healthy behaviors and supporting postpartum health among migrant women. This is highly relevant given the lack of previous comparable studies and the urgent need for tailored postpartum interventions for migrant populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT06881277; https://clinicaltrials.gov/study/NCT06881277. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/79277.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,038 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,005 |
| Méta-épidémiologie (sens large) | 0,014 | 0,008 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,009 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,103 | 0,017 |
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 source (Gemma direct ou Codex distillé), 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 ».