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IntroductionMobile Academy is a mobile-based training course for India’s accredited social health activist (ASHA) community health workers (CHW). The course, which ASHAs access by dialling a number from their phones, totals 4 hours of audio content. It consists of 11 chapters, each with their own quiz, and provides a cumulative pass or fail score at the end. This qualitative study of Mobile Academy explores how the programme was accessed and experienced by CHWs, and how they perceive it to have influenced their work.MethodsWe conducted in-depth interviews (n=25) and focus group discussions (n=5) with ASHAs and other health system actors. Open-ended questions explored ASHA perspectives on Mobile Academy, the course’s perceived influence on ASHAs and preferences for future training programmes. After applying a priori codes to the transcripts, we identified emergent themes and grouped them according to our CHW mLearning framework.ResultsASHAs reported enjoying Mobile Academy, specifically praising its friendly tone and the ability to repeat content. They, and higher level health systems actors, conceived it to primarily be a test not a training. ASHAs reported that they found the quizzes easy but generally did not consider the course overly simplistic. ASHAs considered Mobile Academy’s content to be a useful knowledge refresher but said its primary benefit was in modelling a positive communications approach, which inspired them to adopt a kinder, more ‘loving’ communication style when speaking to beneficiaries. ASHAs and health system actors wanted follow-on mLearning courses that would continue to compliment but not replace face-to-face training.ConclusionThis mLearning programme for CHWs in India was well received by ASHAs across a wide range of education levels and experience. Dial-in audio training has the potential to reinforce topical knowledge and showcase positive ways to communicate.

ObjectivesEfforts to understand the factors influencing the uptake of reproductive, maternal, newborn, child health and nutrition (RMNCH&N) services in high disease burden low-resource settings have often focused on face-to-face surveys or direct observations of service delivery. Increasing access to mobile phones has led to growing interest in phone surveys as a rapid, low-cost alternatives to face-to-face surveys. We assess determinants of RMNCH&N knowledge among pregnant women with access to phones and examine the reliability of alternative modalities of survey delivery.ParticipantsWomen 5–7 months pregnant with access to a phone.SettingFour districts of Madhya Pradesh, India.DesignCross-sectional surveys administered face-to-face and within 2 weeks, the same surveys were repeated among two random subsamples of the original sample: face-to-face (n=205) and caller-attended telephone interviews (n=375). Bivariate analyses, multivariable linear regression, and prevalence and bias-adjusted kappa scores are presented.ResultsKnowledge scores were low across domains: 52% for maternal nutrition and pregnancy danger signs, 58% for family planning, 47% for essential newborn care, 56% infant and young child feeding, and 58% for infant and young child care. Higher knowledge (≥1 composite score) was associated with older age; higher levels of education and literacy; living in a nuclear family; primary health decision-making; greater attendance in antenatal care and satisfaction with accredited social health activist services. Survey questions had low inter-rater and intermodal reliability (kappaConclusionsPhone surveys are a reliable modality for generating population-level estimates data about pregnant women’s knowledge, however, should not be used for individual-level tracking.Trial registration numberNCT03576157.

ObjectivesTo understand factors underpinning the accuracy and timeliness of mobile phone numbers and other health information captured in India’s government registry for pregnant and postpartum women. Accurate and timely registration of mobile phone numbers is necessary for beneficiaries to receive mobile health services.SettingMadhya Pradesh and Rajasthan states in India at the community, clinical, and administrative levels of the health system.ParticipantsInterviews (n=59) with frontline health workers (FLHWs), data entry operators, and higher level officials. Focus group discussions (n=12) with pregnant women to discuss experiences with sharing data in the health system. Observations (n=9) of the process of digitization and of interactions between stakeholders for data collection.Primary and secondary outcome measuresThematic analysis identified how key actors experienced the data collection and digitisation process, reasons for late or inaccurate data, and mechanisms that can bolster timeliness and accuracy.ResultsPregnant women were comfortable sharing mobile numbers with health workers, but many were unaware that their data moved beyond their FLHW. FLHWs valued knowing up-to-date beneficiary mobile numbers, but felt little incentive to ensure accuracy in the digital record system. Delays in registering pregnant women in the online portal were attributed to slow movement of paper records into the digital system and difficulties in gathering required documents from beneficiaries. Data, including women’s phone numbers, were handwritten and copied multiple times by beneficiaries and health workers with variable literacy. Supervision tended to focus on completeness rather than accuracy. Health system actors noted challenges with the digital system but valued the broader project of digitisation.ConclusionsIncreased focus on training, supportive supervision, and user-friendly data processes that prioritise accuracy and timeliness should be considered. These inputs can build on existing positive patient–provider relationships and health system actors’ enthusiasm for digitisation.

ObjectivesDirect to beneficiary (D2B) mobile health communication programmes have been used to provide reproductive, maternal, neonatal and child health information to women and their families in a number of countries globally. Programmes to date have provided the same content, at the same frequency, using the same channel to large beneficiary populations. This manuscript presents a proof of concept approach that uses machine learning to segment populations of women with access to phones and their husbands into distinct clusters to support differential digital programme design and delivery.SettingData used in this study were drawn from cross-sectional survey conducted in four districts of Madhya Pradesh, India.ParticipantsStudy participant included pregnant women with access to a phone (n=5095) and their husbands (n=3842)ResultsWe used an iterative process involving K-Means clustering and Lasso regression to segment couples into three distinct clusters. Cluster 1 (n=1408) tended to be poorer, less educated men and women, with low levels of digital access and skills. Cluster 2 (n=666) had a mid-level of digital access and skills among men but not women. Cluster 3 (n=1410) had high digital access and skill among men and moderate access and skills among women. Exposure to the D2B programme ‘Kilkari’ showed the greatest difference in Cluster 2, including an 8% difference in use of reversible modern contraceptives, 7% in child immunisation at 10 weeks, 3% in child immunisation at 9 months and 4% in the timeliness of immunisation at 10 weeks and 9 months.ConclusionsFindings suggest that segmenting populations into distinct clusters for differentiated programme design and delivery may serve to improve reach and impact.Trial registration numberNCT03576157.