WhatsApp Versus SMS for 2-Way, Text-Based Follow-Up After Voluntary Medical Male Circumcision in South Africa: Exploration of Messaging Platform Choice
Notice bibliographique
Résumé
BACKGROUND: Telehealth is growing, especially in areas where access to health facilities is difficult. We previously used 2-way texting (2wT) via SMS to improve the quality of postoperative care after voluntary medical male circumcision in South Africa. In this study, we offered males aged 15 years and older WhatsApp or SMS as their message delivery and interaction platform to explore user preferences and behaviors. OBJECTIVE: The objectives of this process evaluation embedded within a larger 2wT expansion trial were to (1) explore 2wT client preferences, including client satisfaction, with WhatsApp or SMS; (2) examine response rates (participation) by SMS and WhatsApp; and (3) gather feedback from the 2wT implementation team on the WhatsApp approach. METHODS: Males aged 15 years and older undergoing voluntary medical male circumcision in program sites could choose their follow-up approach, selecting 2wT via SMS or WhatsApp or routine care (in-person postoperative visits). The 2wT system provided 1-way educational messages and an open 2-way communication channel between providers and clients. We analyzed quantitative data from the 2wT database on message delivery platforms (WhatsApp vs SMS), response rates, and user behaviors using chi-square tests, z tests, and t tests. The team conducted short phone calls with WhatsApp and SMS clients about their perceptions of this 2wT platform using a short, structured interview guide. We consider informal reflections from the technical team members on the use of WhatsApp. We applied an implementation science lens using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework to focus results on practice and policy improvement. RESULTS: Over a 2-month period-from August to October, 2023-337 males enrolled in 2wT and were offered WhatsApp or SMS and were included in the analysis. For 2wT reach, 177 (53%) participants chose WhatsApp as their platform (P=.38). Mean client age was 30 years, and 253 (75%) participants chose English for automated messages. From quality assurance calls, almost all respondents (87/89, 98%) were happy with the way they were followed up. For effectiveness, on average for the days on which responses were requested, 58 (33%) WhatsApp clients and 44 (28%) SMS clients responded (P=.50). All 2wT team members believed WhatsApp limited the automated message content, language choices, and inclusivity as compared with the SMS-based 2wT approach. CONCLUSIONS: When presented with a choice of 2wT communication platform, clients appear evenly split between SMS and WhatsApp. However, WhatsApp requires a smartphone and data plan, potentially reducing reach at scale. Clients using both platforms responded to 2wT interactive prompts, demonstrating similar effectiveness in engaging clients in follow-up. For telehealth interventions, digital health designers should maintain an SMS-based platform and carefully consider adding WhatsApp as an option for clients, using an implementation science approach to present evidence that guides the best implementation approach for their setting.
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 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 | 0,012 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 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 ».