A Tailored mHealth Intervention for Improving Antenatal Care Seeking and Health Behavioral Determinants During Pregnancy Among Adolescent Girls and Young Women in South Africa: Development and Protocol for a Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: South Africa, a middle-income country, has an adolescent fertility rate far higher than that of high-income countries. Adolescent girls and young women have an increased risk of pregnancy-related complications and lower antenatal appointment attendance rates than older adult pregnant women. Mobile health (mHealth) interventions to improve health behaviors among pregnant adolescent girls and young women in low- and middle-income countries are scarce. OBJECTIVE: This paper describes the development and components of an mHealth intervention to improve antenatal appointment attendance and health behavioral determinants among pregnant adolescent girls and young women in South Africa and details the protocol for a pilot randomized controlled trial that evaluated the intervention's efficacy and user acceptability. METHODS: The intervention, Teen MomConnect, sent tailored motivational behavior change and behavioral reinforcement SMS text messages to participants about antenatal appointment keeping and pregnancy behaviors. The delivery methodology of the intervention was adapted from MomConnect, an mHealth education program for pregnant women in South Africa that has nationwide coverage. In addition, participants received a face-to-face motivational interviewing session delivered by a trained research assistant. Pregnant adolescent girls and young women aged 13 to 20 years were recruited from health facilities and community networks. Participants were randomized into the control group that received the standard MomConnect health SMS text messages or the experimental group that received the Teen MomConnect intervention. Participants completed a baseline questionnaire upon enrollment in the study and a follow-up questionnaire after the end of their pregnancy. The questionnaires assessed demographic characteristics, pregnancy behaviors, and the psychosocial determinants of antenatal appointment attendance (knowledge, attitudes, social support, risk perceptions, self-efficacy, intention, and action planning). Feasibility was assessed using descriptive analyses of acceptability, study implementation processes, and perceived satisfaction with the intervention. The number of appointments attended was obtained from the participants' clinic records. Appointment attendance was compared between the control and experimental groups, as were awareness of HIV status and the psychosocial determinants of antenatal appointment attendance. RESULTS: Participant recruitment was conducted from May 2018 to December 2018, and the questionnaire-based data collection was completed by December 2019. Overall, 412 participants were enrolled. CONCLUSIONS: This paper describes the Teen MomConnect intervention to improve antenatal appointment attendance and pregnancy health behaviors among adolescent girls and young women. The results on the intervention's preliminary efficacy and user acceptability will inform policy makers and health program officers on how tailored, age-appropriate, and motivational health behavior messages can be delivered via mobile phone to pregnant adolescent girls and young women. TRIAL REGISTRATION: Pan African Clinical Trial Registry (PACTR) PACTR201912734889796; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=9565. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43654.
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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 | 0,017 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,046 | 0,005 |
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 ».