WhatsApp Versus SMS for 2-Way, Text-Based Follow-Up After Voluntary Medical Male Circumcision in South Africa: Exploration of Messaging Platform Choice
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".