Community Health Worker Use of Smart Devices for Health Promotion: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Community health workers (CHWs) have become essential to the promotion of healthy behaviors, yet their work is complicated by challenges both within and beyond their control. These challenges include resistance to the change of existing behaviors, disbelief of health messages, limited community health literacy, insufficient CHW communication skills and knowledge, lack of community interest and respect for CHWs, and CHWs' lack of adequate supplies. The rising penetration of "smart" technology (eg, smartphones and tablets) in low- and middle-income countries facilitates the use of portable electronic devices in the field. OBJECTIVE: This scoping review examines to what extent mobile health in the form of smart devices may enhance the delivery of public health messages in CHW-client interactions, thereby addressing the aforementioned challenges and inducing client behavior change. METHODS: We conducted a structured search of the PubMed and LILACS databases using subject heading terms in 4 categories: technology user, technology device, use of technology, and outcome. Eligibility criteria included publication since January 2007, CHWs delivering a health message aided by a smart device, and face-to-face communication between CHWs and clients. Eligible studies were analyzed qualitatively using a modified version of the Partners in Health conceptual framework. RESULTS: We identified 12 eligible studies, 10 (83%) of which used qualitative or mixed methods approaches. We found that smart devices mitigate challenges encountered by CHWs by improving their knowledge, motivation, and creativity (eg, through self-made videos); their status within the community; and the credibility of their health messages. The technology stimulated interest in both CHWs and clients-and sometimes even in bystanders and neighbors. Media content produced locally or reflecting local customs was strongly embraced. Yet, the effect of smart devices on the quality of CHW-client interactions was inconclusive. Interactions suffered as CHWs were tempted to replace educational conversations with clients by passively watching video content. Furthermore, a series of technical difficulties experienced especially by older and less educated CHWs compromised some of the advantages brought about by mobile devices. Adequate CHW training ameliorated these difficulties. Only 1 study (8%) considered client health behavior change as an end point, thus revealing a major research gap. CONCLUSIONS: Smart mobile devices may augment CHWs' field performance and enhance face-to-face interactions with clients, yet they also generate new challenges. The available evidence is scarce, mostly qualitative, and focused on a limited range of health outcomes. Future research should include larger-scale interventions across a wide range of health outcomes and feature client health behavior change as an end point.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,012 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| 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 ».