Perceptions and Attitudes Toward Mobile Health in Development of an Exclusive Breastfeeding Tool: Focus Group Study With Caregivers and Health Promoters in the Dominican Republic
Notice bibliographique
Résumé
BACKGROUND: Despite growing interest in the use of technology to improve health outcomes in low- and middle-income countries (LMICs), local attitudes toward mobile health (mHealth) use in these settings are minimally understood. This is especially true in the Dominican Republic, where mHealth interventions are starting to emerge. This information is critical for developing effective mHealth interventions to address public health issues, such as low exclusive breastfeeding (EBF) rates, which can lead to poor outcomes. With an EBF rate of 5% in the first 6 months of life, the Dominican Republic has one of the lowest EBF rates worldwide. OBJECTIVE: This study aims to describe the current use of information and communication technology (ICT) and to analyze the attitudes and perceptions related to using mHealth interventions among caregivers of children aged ≤5 years and health promoters in the Dominican Republic. Findings can inform mHealth strategies aimed at improving EBF in this, and other, LMICs. METHODS: Participants were recruited from 3 outpatient sites: the Niños Primeros en Salud program at Centro de Salud Divina Providencia in Consuelo (rural setting) and Clínica de Familia La Romana and its program Módulo de Adolescentes Materno Infantil in La Romana (urban setting). Focus groups were conducted with caregivers and community health promoters to identify the use, attitudes, perceptions, and acceptability of mHealth as well as barriers to EBF. Discussions were conducted in Spanish, guided by semistructured interview guides. All sessions were audio-recorded and later transcribed. Thematic content analysis was conducted in Spanish by two bilingual researchers and was structured around a hybrid behavioral theory framework to identify salient themes. RESULTS: All participants (N=35) reported having a mobile phone, and 29 (83%) participants had a smartphone. Sources for obtaining health information included the internet, physicians and clinic, family and friends, health promoters, and television. Barriers to mHealth use included the cost of internet service, privacy concerns, and perceived credibility of information sources. Participants indicated the desire for, and willingness to use, an mHealth intervention to support breastfeeding. The desired features of a possible mHealth intervention included offering diverse methods of information delivery such as images and video content, text messages, and person-to-person interaction as well as notifications for appointments, vaccines, and feeding schedules. Other important considerations were internet-free access and content that included maternal and child health self-management topics beyond breastfeeding. CONCLUSIONS: There is a high level of acceptance of ICT tools for breastfeeding promotion among caregivers in urban and rural areas of the Dominican Republic. As mHealth tools can contribute to increased breastfeeding self-efficacy, identifying desirable features of such a tool is necessary to create an effective intervention. Participants wanted to receive trusted and reliable information through various formats and were interested in information beyond breastfeeding.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».