Third, AI chatbots can mimic real-life human support by offering services that can assist users in achieving their health behavior goals. Second, the AI algorithm uses machine learning (ML) and natural language processing (NLP) techniques to identify clinically meaningful patterns and understand user needs. First, AI chatbots can collect data sets from diverse sources: electronic health records, unstructured clinical notes, real-time physiological data points using additional sensors (eye-movement tracking, facial recognition, movement tracking, and heartbeat), and user interactions. ĪI chatbots demonstrate their potential for effective behavior change through key steps of data processing in health-related conversations: data input, data analysis, and data output. The overall conversational flexibility offered by AI chatbots in terms of communicating at anytime from anywhere offers a safe space to facilitate interactions with patients who feel or experience stigmatization while seeking health care services. AI chatbots offer the flexibility of on-demand support, personalized support and content, and consistent connectivity (sustainability), contributing to addressing the shortfalls of telehealth services. The existing digital therapeutic and telehealth interventions with didactic components, which enable health care providers to communicate with patients via digital platforms (eg, email and video call), have encountered several challenges, including relatively low adherence, unsustainability, and inflexibility. With the increased access to technological devices (eg, smartphones and computers) and the internet, AI chatbots offer the potential to provide accessible, autonomous, and engaging health-related information and services, which can be promising for technology-facilitated interventions. However, the reported results need to be interpreted with caution because of the moderate to high risk of internal validity, insufficient description of AI techniques, and limitation for generalizability.Īrtificial intelligence (AI)–driven chatbots (AI chatbots) are conversational agents that mimic human interaction through written, oral, and visual forms of communication with a user. The participants also reported that AI chatbots offered a nonjudgmental space for communicating sensitive information. The AI chatbots demonstrated potential for scalability by deployment through accessible devices and platforms (eg, smartphones and Facebook Messenger). Real-time user-chatbot interaction data, such as user preferences and behavioral performance, were collected on the chatbot platform to identify ways of providing personalized services. Selected behavior change theories and expert consultation were used to develop the behavior change strategies of AI chatbots, including goal setting, monitoring, real-time reinforcement or feedback, and on-demand support. However, there were mixed results regarding feasibility, acceptability, and usability. Of the 15 included studies, several demonstrated the high efficacy of AI chatbots in promoting healthy lifestyles (n=6, 40%), smoking cessation (n=4, 27%), treatment or medication adherence (n=2, 13%), and reduction in substance misuse (n=1, 7%).
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