Purpose This study aimed to identify the components of artificial intelligence-based healthcare interventions and determine their effects on health behaviors and physiological, psychological, and cost-effectiveness outcomes among adults. Methods Nine core electronic databases were searched for articles published between January, 2009 and May, 2021 using terms related to artificial intelligence, healthcare, and randomized controlled trials. Qualitative synthesis was then performed. Results Of the 1,194 retrieved articles, 20 were selected for analysis. Many of the studies targeted adults who wanted to change their health behaviors, patients with diabetes, and those aged 20~50 years. The characteristics of the artificial intelligence-based healthcare interventions were analyzed in terms of the following components: external data, artificial intelligence technology, problem solving, and goals. Many interventions offered personalized suggestions by learning participant behavior patterns using machine learning technology and diet and physical activity data. The majority of interventions targeted health behaviors and physiological outcomes. These artificial intelligence-based healthcare interventions were effective in decreasing hospital visits and improving psychological outcomes and health behaviors. Conclusion Artificial intelligence-based healthcare interventions can be an important part of decreasing hospital visits and improving psychological outcomes and health behaviors among adults. The results suggest that there is a need to develop and apply appropriate artificial intelligence algorithms for patients with chronic diseases that require continuous management in Korea.
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