Overview of chatbot usage on mental health: A scoping review

¹ Master of Public Health Program, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
² Department of Biostatistics, Epidemiology, and Population Health, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia

^* Corresponding author: ririnindahpermatasari@mail.ugm.ac.id

Abstract

Mental disorders have become the second most significant global health burden. One approach to reducing the medical and socio-economic impacts of mental illnesses/disorders is leveraging the power of digital health technology. Chatbots, in particular, hold great potential for providing social and psychological support, akin to human interactions. This research aims to map the use of mental health chatbot technology using the scoping review method based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extensions for Scoping Reviews. The results are categorized according to use, including acceptability, effectiveness, usability, adoption, and features. Study selection was assisted by Rayyan. Data extraction used a narrative approach. Chatbots were classified based on purpose, target population, targeted mental health disorders, and usage metrics. 21 out of 172 research articles met the inclusion criteria. Anxiety, depression, and stress were the most common target disorders for chatbot use, although a combination of focuses is quite ideal for mental health chatbots. Many chatbots have been used for various types of mental disorders. Their purposes range from prevention and training to therapy, with most being a combination. Further research is needed to understand the changes that occur following interventions using mental health chatbots.