Development of a Digital Platform to Promote Mother and Child Health in Underserved Areas of a Lower-Middle-Income Country: Mixed Methods Formative Study
Notice bibliographique
Résumé
Background: Primary health care (PHC) is the backbone of universal health coverage, with community health workers (CHWs) being one of its critical pillars in lower-middle-income countries. Most CHW functions require them to be an efficient communicator, but their program development has been deficient in this area. Can IT provide some solutions? Moreover, can some IT-based CHW-delivered innovations help mothers and children in areas not covered by PHC services? We explored these questions during the development and feasibility testing of a digital application designed to improve the communication capacity of CHWs in two underserved areas of Islamabad. Objective: This study aims to explore the perceptions, practices, and related gaps about mother and child health, and child development in an underserved area; develop and deploy a behavior change communication program to address the gaps; and assess the feasibility of the program. Methods: We carried out a mixed methods study with three steps. First, we conducted 13 in-depth interviews and two focus group discussions with stakeholders to explore the issues faced by mothers living in these underserved areas. To address these barriers, we developed Sehat Ghar, a video-based health education application to demonstrate practices mothers and families needed to adopt. Second, we trained 10 volunteer CHWs from the same community to deliver health education using the application and assessed their pre-post knowledge and skills. Third, these CHWs visited pregnant and lactating mothers in the community with random observation of their work by a supporting supervisor. Results: Initial exploration revealed a need for health-related knowledge among mothers and suboptimal utilization of public health care. Sehat Ghar used behavior change techniques, including knowledge transfer, enhancing mothers' self-efficacy, and improving family involvement in mother and child care. Volunteer CHWs were identified from the community, who after the training, showed a significant improvement in mean knowledge score (before: mean 8.00, SD 1.49; after: mean 11.40, SD 1.43; P<.001) about health. During supportive supervision, these CHWs were rated as excellent in their interaction with mothers and excellent or very good in using the application. The CHW and her community reported their satisfaction with the application and wanted its delivery regularly. Conclusions: Sehat Ghar is a simple, easy-to-use digital application for CHWs and is acceptable to the community. Mothers appreciate the content and presentation and are ready to incorporate its messages into their daily practices. The real-world effectiveness of the innovation tested on 250 mother-infant pairs will be important for its proof of effectiveness. With its usefulness and adaptability, and the rapidly spreading use of mobile phones and internet technology, this cost-effective innovation can help in delivering health communications at a large scale in a minimum amount of time.
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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 | 0,020 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».