A review of mobile chatbot apps for anxiety and depression and their self-care features - Arfan Ahmed (17541309) (2021)
Background Anxiety and depression rates are at an all-time high. Smartphone-based mental health chatbots can aid psychiatrists replacing some of the costly human based interaction providing a unique opportunity to expand the availability and quality of mental health intervention whilst providing an alternative approach to fill the much-needed self-care gap. Objective Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. Methods A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbot apps for anxiety and depression. Eligibility was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and post-installation by two reviewers. Information on quality was assessed by following the mHONcode principles. Results Only a handful (n=11) of chatbots were included from an initial search of 1000 that provide a substitute for human-human based interaction and clearly had a therapeutic human substitute goal in mind. The majority of reviewed apps had a high number of downloads indicating their popularity. The apps were also of a general high quality based on our assessment according to the mHONcode principles. Conclusion The general popularity of apps reviewed, and results of our quality assessment indicate chatbots have a promising future within the realm of anxiety and depression. Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed low-cost assistance to professionals. Other Information Published in: Computer Methods and Programs in Biomedicine Update License: http://creativecommons.org/licenses/by/4.0/ See article on publisher's website: https://dx.doi.org/10.1016/j.cmpbup.2021.100012