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

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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Chatbot, Microsoft Bot Framework, Mental healthcare, Screening instruments, Coping mechanisms, E-learning, Chatbot Usability, Chatbot Development, Chatbot Methodology, Ethical considerations

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          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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          Most cited references 11

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          The Sleep Condition Indicator: a clinical screening tool to evaluate insomnia disorder

          Objective Describe the development and psychometric validation of a brief scale (the Sleep Condition Indicator (SCI)) to evaluate insomnia disorder in everyday clinical practice. Design The SCI was evaluated across five study samples. Content validity, internal consistency and concurrent validity were investigated. Participants 30 941 individuals (71% female) completed the SCI along with other descriptive demographic and clinical information. Setting Data acquired on dedicated websites. Results The eight-item SCI (concerns about getting to sleep, remaining asleep, sleep quality, daytime personal functioning, daytime performance, duration of sleep problem, nights per week having a sleep problem and extent troubled by poor sleep) had robust internal consistency (α≥0.86) and showed convergent validity with the Pittsburgh Sleep Quality Index and Insomnia Severity Index. A two-item short-form (SCI-02: nights per week having a sleep problem, extent troubled by poor sleep), derived using linear regression modelling, correlated strongly with the SCI total score (r=0.90). Conclusions The SCI has potential as a clinical screening tool for appraising insomnia symptoms against Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria.
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            Chatbots and the new world of HCI

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              Development of the alcohol use disorders identification test (AUDIT)

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                Author and article information

                Contributors
                Conference
                July 2018
                July 2018
                : 1-5
                Affiliations
                Ulster University

                Belfast, N. Ireland
                Inspire Workplaces

                Belfast, N. Ireland
                Article
                10.14236/ewic/HCI2018.129
                © Cameron et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                HCI
                32
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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