Best Practices for Designing Chatbots in Mental Healthcare – A Case Study on iHelpr

Abstract

This paper outlines the design and development of a chatbot called iHelpr for mental healthcare that 1) administers self-assessment instruments/scales, 2) provides wellbeing and self-help guidance and information, all within a conversational interface. Chatbots are becoming more prevalent in our daily lives, with bots available to provide the user with daily weather forecasts, book holidays, and even converse with a virtual therapist. It is predicted that users may soon prefer to complete tasks using a conversational interface that are traditionally done through a webpage or mobile application. In the context of mental healthcare, demand exceeds supply, waiting lists are ever growing, and populations in rural communities still struggle to access mental healthcare. Chatbots can be utilised to improve and broaden access to mental healthcare. When designing chatbots for mental healthcare, there are further considerations, such as managing risk and ethical considerations. Furthermore, usability and the design of conversational flow are important factors to consider when developing chatbots for any domain. This paper outlines best practices and experiences extrapolated from developing the iHelpr chatbot.

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