Investigating Attitudes and Preferences Towards a Chatbot Pregnancy Guide within Facebook's Social Media Platform Amongst Pregnant Women in Kenya

Abstract

Background: In Kenya, timely antenatal care, postnatal family planning, breastfeeding and maternal health literacy impact maternal and child health. mHealth interventions such as chatbots offer novel ways to address health literacy and other health determinants. A chatbot is a computer software that can simulate a human conversation. Identifying the feasibility of chatbots in Kenya for pregnancy support within Facebook’s social media platform is uncharted. To map the feasibility of a chatbot for pregnancy support, questions surrounding the current utilization of health resources and attitudes matter. Methods: Phase 1 used focus group discussions (FGDs) to understand health resource usage, attitudes and preferences towards a chatbot application for pregnancy. Participant input was used to develop the chatbot in Phase 2. Phase 3 focused on the experience of those using the chatbot to inform feasibility and acceptability of the chatbot developed. Post-intervention we conducted FGDs and interviews, surveyed the sample and analyzed app usage data. Results: Participants described unsatisfying relationships with health resources including health care providers. These experiences led to mistrust. Participants identified criteria that a chatbot for pregnancy support should have. After making these adaptations to the chatbot developed in Phase 2, the chatbot was tested during Phase 3. Results from Phase 3 indicate positive attitudes towards the chatbot experience and engagement. Conclusions: The current context of Kenya regarding patient provider relationships, internet access and Facebook have proven beneficial for the feasibility of this innovation. Participant experiences were positive and relate to the use of Human Centered Design, Innovation Diffusion Theory and trust.