| 1. |
- Boyd, Kyle, et al.
(författare)
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Usability testing and trust analysis of a mental health and wellbeing chatbot
- 2022
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Ingår i: Proceedings of the 33rd European Conference on Cognitive Ergonomics (ECCE 2022). - New York, NY, USA : Association for Computing Machinery.
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Konferensbidrag (refereegranskat)abstract
- Mental health chatbots are particularly useful for those who are isolated and may have difficulty attending services or for those who are reluctant to speak to a professional. In this study, the usability and trust of a chatbot known as ’ChatPal’ has been assessed. ChatPal has been developed by an interdisciplinary team encompassing health service providers, local authorities, charities and universities to promote positive mental wellbeing among individuals in rural areas across Europe. This study employed a usability test protocol to recruit representative users to complete a set of tasks using the ChatPal chatbot. Usability issues were assessed along with trust and users’ satisfaction on the System Usability Scale and the Chatbot Usability Questionnaire. The study shows the usability issues and trust with a mental health chatbot and highlights recommendations for improvement.
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| 2. |
- Potts, Courtney, et al.
(författare)
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Insights and lessons learned from trialling a mental health chatbot in the wild
- 2021
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Ingår i: 2021 IEEE Symposium on Computers and Communications (ISCC). - : IEEE. ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- This study reports on the development and ‘in the wild’ trialling of a chatbot (ChatPal) which promotes good mental wellbeing. A stakeholder-centered approach for design was adopted where end users, mental health professionals and service users were involved in the design which was centered around positive psychology. In the wild usage of the chatbot was investigated from Jul-20-Mar-21. Exploratory analyses of usage metrics were carried out using the event log data. User tenure, unique usage days, total chatbot interactions and average daily interactions were used in K-means clustering to identify user archetypes. The chatbot was used by a variety of age groups (18-65+) and genders, mainly those living in Ireland. K-means clustering identified three clusters: sporadic users (n=4), frequent transient users (n=38) and abandoning users (n=169) each with distinct usage characteristics. This study highlights the importance of event log data analysis for making improvements to the mental health chatbot.
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| 3. |
- Sweeney, Colm, et al.
(författare)
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Can Chatbots Help Support a Person’s Mental Health? Perceptions and Views from Mental Healthcare Professionals and Experts
- 2021
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Ingår i: ACM Transactions on Computing for Healthcare. - : ACM Digital Library. - 2691-1957 .- 2637-8051. ; 2:3
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this study was to understand the attitudes of professionals who work in mental health regarding the use of conversational user interfaces, or chatbots, to support people’s mental health and wellbeing. This study involves an online survey to measure the awareness and attitudes of mental healthcare professionals and experts. The findings from this survey show that more than half of the participants in the survey agreed that there are benefits associated with mental healthcare chatbots (65%, p < 0.01). The perceived importance of chatbots was also relatively high (74%, p < 0.01), with more than three-quarters (79%, p < 0.01) of respondents agreeing that mental healthcare chatbots could help their clients better manage their own health, yet chatbots are overwhelmingly perceived as not adequately understanding or displaying human emotion (86%, p < 0.01). Even though the level of personal experience with chatbots among professionals and experts in mental health has been quite low, this study shows that where they have been used, the experience has been mostly satisfactory. This study has found that as years of experience increased, there was a corresponding increase in the belief that healthcare chatbots could help clients better manage their own mental health.
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