Mobile-Social Learning for Continuing Professional Development in Low- and Middle-Income Countries: Integrative Review
Notice bibliographique
Résumé
BACKGROUND: Access to continuing professional development (CPD) for health care workers in low- and middle-income countries (LMICs) is severely limited. Digital technology serves as a promising platform for supporting CPD for health care workers by providing educational content virtually and enabling virtual peer-to-peer and mentor interaction for enhanced learning. Digital strategies for CPD that foster virtual interaction can increase workforce retention and bolster the health workforce in LMICs. OBJECTIVE: The objective of this integrative review was to evaluate the evidence on which digital platforms were used to provide CPD to health care workers and clinical students in LMICs, which was complemented with virtual peer-to-peer or mentor interaction. We phrased this intersection of virtual learning and virtual interaction as mobile-social learning. METHODS: A comprehensive database and gray literature search was conducted to identify qualitative, quantitative, and mixed methods studies, along with empirical evidence, that used digital technology to provide CPD and virtual interaction with peers or mentors. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Eligible articles were written in English, conducted in an LMIC, and used a mobile device to provide CPD and facilitate virtual peer-to-peer or mentor interaction. Titles, abstracts, and full texts were screened, followed by an assessment of the quality of evidence and an appraisal of the articles. A content analysis was then used to deductively code the data into emerging themes. RESULTS: A total of 750 articles were identified, and 31 (4.1%) were included in the review. SMS text messaging and mobile instant messaging were the most common methods used to provide continuing education and virtual interaction between peers and mentors (25/31, 81%). Across the included articles, participants had high acceptability for using digital platforms for learning and interaction. Virtual peer interaction and mentorship were found to contribute to positive learning outcomes in most studies (27/31, 87%) through increased knowledge sharing, knowledge gains, improved clinical skills, and improved service delivery. Peer-to-peer and mentor interaction were found to improve social support and reduce feelings of isolation (9/31, 29%). There were several challenges in the implementation and use of digital technology for mobile-social learning, including limited access to resources (eg, internet coverage and stable electricity), flexibility in scheduling to participate in CPD, and sociobehavioral challenges among students. CONCLUSIONS: The summary suggests that mobile-social learning is a useful modality for curriculum dissemination and skill training and that the interface of mobile and social learning serves as a catalyst for improved learning outcomes coupled with increased social capital.
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 | 0,004 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 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 | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».