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Ai chatbot for healthcare12/30/2023 ![]() 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.Ĭonclusions: AI chatbots have demonstrated the efficacy of health behavior change interventions among large and diverse populations however, future studies need to adopt robust randomized control trials to establish definitive conclusions.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. Results: 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%). The screening, extraction, and analysis of the identified articles were performed by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Methods: A comprehensive search was conducted in 7 bibliographic databases (PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications) for empirical articles published from 1980 to 2022 that evaluated the feasibility or efficacy of AI chatbots for behavior change. Objective: The aim of this systematic review was to evaluate the feasibility, efficacy, and intervention characteristics of AI chatbots for promoting health behavior change. Online Journal of Public Health Informaticsĭepartment of Health Promotion, Education and BehaviorĮmail: Artificial intelligence (AI)–based chatbots can offer personalized, engaging, and on-demand health promotion interventions.Asian/Pacific Island Nursing Journal 11 articles.JMIR Bioinformatics and Biotechnology 35 articles.JMIR Biomedical Engineering 69 articles.Journal of Participatory Medicine 80 articles.JMIR Perioperative Medicine 91 articles.JMIR Rehabilitation and Assistive Technologies 206 articles.JMIR Pediatrics and Parenting 287 articles.Interactive Journal of Medical Research 315 articles. ![]() ![]() JMIR Public Health and Surveillance 1176 articles.Journal of Medical Internet Research 7628 articles. ![]()
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