Developing Culturally Appropriate Content for a Child-Rearing App to Support Young Children’s Socioemotional and Cognitive Development in Afghanistan: Co-Design Study
Notice bibliographique
Résumé
BACKGROUND: Optimal child-rearing practices can help mitigate the consequences of detrimental social determinants of health in early childhood. Given the ubiquity of personal digital technologies worldwide, the direct delivery of evidence-based information about early childhood development holds great promise. However, to make the content of these novel systems effective, it is crucial to incorporate place-based cultural beliefs, traditions, circumstances, and value systems of end users. OBJECTIVE: This paper describes the iterative approach used to develop the Thrive by Five child-rearing app in collaboration with Afghan parents, caregivers (eg, grandparents, aunts, and nannies), and subject matter experts (SMEs). We outline how co-design methodologies informed the development and cultural contextualization of content to meet the specific needs of Afghan parents and the content was tested and refined in collaboration with key Afghan stakeholders. METHODS: The preliminary content was developed based on a comprehensive literature review of the historical and sociocultural contexts in Afghanistan, including factors that influence child-rearing practices and early childhood development. After an initial review and refinement based on feedback from SMEs, this content was populated into a beta app for testing. Overall, 8 co-design workshops were conducted in July and August 2021 and February 2022 with 39 Afghan parents and caregivers and 6 SMEs to collect their feedback on the app and its content. The workshops were audio recorded and transcribed; detailed field notes were taken by 2 scribes. A theoretical thematic analysis using semantic codes was conducted to inform the refinement of existing content and development of new content to fulfill the needs identified by participants. RESULTS: The following 4 primary themes were identified: child-rearing in the Afghan sociocultural context, safety concerns, emotion and behavior management, and physical health and nutrition. Overall, participants agreed that the app had the potential to deliver valuable information to Afghan parents; however, owing to the volatility in the country, participants recommended including more activities that could be safely done indoors, as mothers and children are required to spend most of their time at home. Additionally, restrictions on public engagement in music required the removal of activities referencing singing that might be performed outside the home. Further, activities to help parents reduce their children's screen time, promote empathy, manage emotions, regulate behavior, and improve physical health and nutrition were requested. CONCLUSIONS: Direct engagement with Afghan parents, caregivers, and SMEs through co-design workshops enabled the development and refinement of evidence-based, localized, and contextually relevant child-rearing activities promoting healthy social, emotional, and cognitive development during the first 5 years of children's lives. Importantly, the content was adapted for the ongoing conflict in Afghanistan with the aim of empowering Afghan parents and caregivers to support their children's developmental potential despite the security concerns and situational stressors.
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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 | 0,019 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 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 ».