![]() ![]() According to a Pew Research Center survey, 46% of American adults interact with voice-based chatbots (e.g., Apple’s Siri and Amazon’s Alexa) on smartphones and other devices. Powered by natural language processing and cloud computing infrastructures, AI chatbots can participate in a broad range, from constrained (i.e., rule-based) to unconstrained conversations (i.e., human-to-human-like communication). International Prospective Register of Systematic Reviews (PROSPERO): CRD42020216761.Īrtificial Intelligence (AI) chatbots, also called conversational agents, employ dialogue systems to enable natural language conversations with users by means of speech, text, or both. ![]() Thus, standardization of designing and reporting chatbot interventions is warranted in the near future. Application of AI chatbots is an emerging field of research in lifestyle modification programs and is expected to grow exponentially. ConclusionĬhatbots may improve physical activity, but we were not able to make definitive conclusions regarding the efficacy of chatbot interventions on physical activity, diet, and weight management/loss. ![]() Over half (56%) of the studies used a constrained chatbot (i.e., rule-based), while the remaining studies used unconstrained chatbots that resemble human-to-human communication. Eighty-nine and thirty-three percent of the studies specified a name and gender (i.e., woman) of the chatbot, respectively. Outcome assessments, however, were reported inconsistently across the studies. In contrast, the number of studies focusing on changing diet and weight status was limited. Five out of the seven studies suggest chatbot interventions are promising strategies in increasing physical activity. Of the 9 studies, 4 were randomized controlled trials and 5 were quasi-experimental studies. The database search retrieved 1692 citations, and 9 studies met the inclusion criteria. We applied the AI Chatbot Behavior Change Model to characterize components of chatbot interventions, including chatbot characteristics, persuasive and relational capacity, and evaluation of outcomes. The National Institutes of Health quality assessment tools were used to assess risk of bias in individual studies. Studies were screened by two independent reviewers, and any discrepancy was resolved by a third reviewer. Only randomized controlled trials or quasi-experimental studies were included. In collaboration with a medical librarian, six electronic bibliographic databases (PubMed, EMBASE, ACM Digital Library, Web of Science, PsycINFO, and IEEE) were searched to identify relevant studies. This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight management behaviors, and other related health outcomes. ![]()
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