Limited interaction with professionals, infrastructural, and social constraints put barriers in providing holistic support to expectant and new mothers in low-resource settings. We examine the use of digital support groups facilitated through WhatsApp by a non-government organization in India. Complementing prior research, these digital peer support groups inform about an open public space created over a chat platform where rural communities and health professionals can engage. By qualitatively analyzing six months of interaction among 588 group members and collecting the experiences of the group moderators, we inform about how the support groups acted as an important source for compensating the gaps in the existing healthcare, providing reassurance support on routine health, explanation on test reports, validation and counseling support in ongoing treatments. We also derive implications for the future of digital support groups and the need for further research on the use of unplatformed design models in resource-constrained settings.

Care workers are increasingly using digital technology in their daily lives, for monitoring, financial compensation, training, coordination, and more. State and corporate actors have invested significant resources to enable this digital shift, particularly during the COVID-19 pandemic. However, care work has remained chronically underpaid, and continues to rely on women from minoritized and marginalized backgrounds. Our paper examines how care workers carefully navigate digitization, precarity, and complex social relationships, in an attempt to care for their communities and each other. We analyze the emerging digital ecosystem for frontline health workers in India during the COVID-19 pandemic where these dynamics have been highly visible. Our research draws attention to four interconnected ways in which workers practiced care, by directing their efforts towards survival, resilience, advocacy, and/or resistance. We suggest these also as care orientations that can be adopted by researchers and practitioners, to critically reflect on and direct technology design towards enabling more caring futures, for (and with) workers and communities.

In India and other developing countries, Community Health Workers (CHWs) provide the first line of care in delivering necessary maternal and child health services. In this work, we assess the training and skill-building needs of CHWs, through a mobile-based training intervention deployed for six months to 500 CHWs for conducting 144 training sessions in rural India. We qualitatively probed 1178 questions, asked by CHWs, during training sessions, and conducted a content analysis of the learning material provided to CHWs. Further, we interviewed 48 CHWs to understand the rationale of information seeking and perceptions of training needs. We present our understanding of the knowledge gaps of CHWs and how the current learning material and training methods are ineffective in addressing it. Our study presents design implications for HCI4D researchers for mobile learning platforms targeted towards CHWs. We also provide policy-level suggestions to improve the training of CHWs in India or a similar context.

Use of chatbots in different spheres of life is continuously increasing since a couple of years. We attempt to understand the potential of chatbots for breastfeeding education by conducting an Wizard-of-Oz experiment with 22 participants. Our participants included breastfeeding mothers and community health workers from the slum areas of Delhi, India. We prototyped our chatbot as an interactive question-answering application and analyzed users' interaction patterns, perceptions, and contexts of use. The chatbot use cases emerged primarily as the first line of support. The participants, especially the mothers, were enthusiastic with the opportunity to ask questions and get reliable answers. We also observed the influencing role of female relative, e.g. mothers-in-law, in breastfeeding practices. Our analysis of user information-seeking suggests that a majority of questions (88%) are of nature that can be answered by a chatbot application. We further observe that the queries are embedded deeply into myths and existing belief systems. Therefore requiring the designers to focus on subtle aspects for providing information such as positive reinforcement and contextual sensitivity. Further, we discuss, different societal and ethical issues associated with Chatbot usage for a public health topic such as breastfeeding education.