Public perceptions of diabetes, healthy living and conversational agents in Singapore: a needs assessment

Background: The incidence of chronic diseases such as type 2 diabetes is on the rise in countries worldwide, including Singapore. Health professional-delivered healthy lifestyle interventions have been shown to prevent type 2 diabetes. Yet ongoing personalised guidance from health professionals is not feasible or affordable at the population level. Novel digital interventions delivered using mobile technology such as conversational agents are a potential alternative for delivery of healthy lifestyle change behavioural interventions to the public. Objective: We explored Singaporeans’ perceptions on and experience of healthy living, diabetes and mobile health interventions (apps and conversational agents). This survey was done to help inform the design and development of a conversational agent focusing on healthy lifestyle change. Methods: This qualitative study was conducted over Aug and Sept 2019. 20 participants were recruited from relevant healthy living Facebook pages and groups. Semi-structured interviews were conducted in person or over the telephone using an interview guide. Interviews were transcribed and analysed in parallel by two researchers using Burnard’s method, a structured approach for thematic content analysis. Results: The collected data was organised into four main themes: (1) use of conversational agents, (2) ubiquity of smartphone applications, (3) understanding of diabetes and (4) barriers and facilitators to a healthy living in Singapore. Most participants used health-related mobile applications as well as conversational agents unrelated to healthcare. They provided diverse suggestions for future conversational agent-delivered interventions. Participants also highlighted several knowledge gaps in relation to diabetes and healthy living. In terms of barriers to healthy living, frequent dining out, high stress levels, lack of work-life balance and dearth of free time to engage in physical activity were mentioned. In contrast, discipline, pre-planning and sticking to a routine were important for enabling a healthy lifestyle. Conclusions: Participants in our study commonly used mobile health interventions and provided important insights into their knowledge gaps and needs in relation to healthy lifestyle behaviour change. Future digital interventions like conversational agents focusing on healthy lifestyle and diabetes prevention should aim to address the barriers highlighted in our study and motivate individuals to adopt habits for healthy living

Conversational agents in healthcare: a scoping review and conceptual analysis

Background: Conversational agents also known as chatbots are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including healthcare. By enabling better accessibility, personalization and efficiency, conversational agents have the potential to improve patient care. Objectives: To review the current applications, gaps and challenges in the literature on conversational agents in healthcare and provide recommendations for their future research, design and application. Methods: We performed a scoping review. A broad literature search was done in Medline (Ovid), EMBASE (Ovid), PubMed, Scopus and Cochrane central with the search terms “conversational agents”, “conversational AI”, “chatbots” and associated synonyms. We also searched grey literature using sources such as OCLC World Cat database and Research Gate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by two review authors. The included evidence was analyzed narratively employing the principles of thematic analysis. Results: The literature search yielded 47 study reports (45 articles and two ongoing clinical trials) which matched the inclusion criteria. The identified conversational agents were largely smartphone applications-delivered (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case-studies describing chatbot development (n=18) were most prevalent and only 11 RCTs were identified. Three most commonly reported conversational agent applications in the literature were treatment and monitoring, healthcare service support, and patient education. Conclusions: The literature on conversational agents in healthcare is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, AI-driven and mobile application-delivered conversational agents. There is an urgent need for robust evaluation of diverse healthcare conversational agents’ formats focusing on their acceptability, safety and effectiveness