User engagement, attitudes, and the effectiveness of chatbots as a mental health intervention: A systematic review - Sucharat Limpanopparat; Erin Gibson; Dr Andrew Harris (Computers in Human Behavior: Artificial Humans)
Background: In recent years, chatbots developed for mental health intervention purposes have been widely implemented to solve the challenges of workforce shortage and accessibility issues faced by traditional health services. Nevertheless, research assessing the technologies’ potential and risks remains sporadic. Purpose: This review aims to synthesise the existing research on engagement, user attitude, and effectiveness of psychological chatbot interventions. Method: A systematic review was conducted using relevant peer-reviewed literature since 2010. These studies were derived from six databases: PubMed, PsycINFO, Web of Science, Science Direct, Scopus and IEEE Xplore. Results: Engagement level with chatbots that complied with digital intervention standards, lead to positive mental health outcomes. Although users had some uncertainties about the usability of these tools, positive attitudes towards chatbots regarding user experience and acceptability were frequently identified due to the chatbots' psychological capabilities and unique functions. High levels of outcome efficacy were found for those with depression. The differences in demographics, psychological approaches, and featured technologies could also influence the extent of mental health chatbot performances. Conclusion: Positive attitudes and engagement with chatbots, as well as positive mental health outcomes, shows chatbot technology is a promising modality for mental health intervention. However, implementing them amongst some demographics or with novel features should be carefully considered. Further research using mainstream mental health chatbots and evaluating them simultaneously with standardised measures of engagement, user attitude, and effectiveness is necessary for intervention development.