Access to and Use of Mobile Phone by Postpartum, Married Women in Punjab, India: Secondary Analysis of mHealth Intervention Pilot Data
Notice bibliographique
Résumé
BACKGROUND: As mobile phone uptake in India continues to grow, there is also continued interest in mobile platform-based interventions for health education. There is a significant gender gap in mobile phone access-women's access to mobile phones is constrained by economic and social barriers. Pregnancy and postpartum care is one of many targets for mobile health (mHealth) interventions that particularly rely upon women's access to and facility with mobile phone use. OBJECTIVE: We aimed to describe the dynamics and patterns of married pregnant and postpartum women's mobile phone access and use (among both phone owners and nonowners) who participated in an mHealth postpartum care intervention and to identify potential barriers to their participation in mobile platform-based interventions. METHODS: A secondary analysis was performed on mixed methods data obtained for a pilot mHealth intervention for postpartum care of mothers in rural Punjab from July 2020 to February 2021. Two formative sources included exploratory in-depth interviews among postpartum women (n=20; 1-3 months postpartum) and quantitative maternal health survey among women who were pregnant or who had recently given birth (n=102). We also utilized mixed methods intervention assessment data from early postpartum women who participated in the pilot intervention (n=29), including intervention moderator perspectives. Qualitative and quantitative analyses were performed, and pertinent findings were grouped thematically. RESULTS: The majority of women owned a phone (maternal health survey: 75/102, 74%; demographic survey: 17/29, 59%), though approximately half (53/102, 52%) still reported sharing phones with other family members. Sharing a phone with female family members typically allowed for better access than sharing with male family members. Some households had strict preferences against daughters-in-law having phones, or otherwise significantly restricted women's phone access. Others reported concerns about phone use-related health hazards for mother and infant during the pregnancy or postpartum period. CONCLUSIONS: These findings suggest nuance regarding what is meant by women's phone ownership and access-there were numerous additional constraints on women's use of phones, particularly during pregnancy and the postpartum period. Future research and mHealth interventions should probe these domains to better understand the dynamics governing women's access, use, and fluency with mobile phones to optimally design mHealth interventions.
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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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».