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.
|Title of host publication||26th IEEE Symposium on Computers and Communications, ISCC 2021|
|Number of pages||6|
|Publication status||Published (in print/issue) - 15 Dec 2021|
|Event||ICTS4eHealth - Online conference, Athens, Greece|
Duration: 5 Sept 2021 → 8 Sept 2021
|Name||Proceedings - IEEE Symposium on Computers and Communications|
|Period||5/09/21 → 8/09/21|
Bibliographical noteFunding Information:
The ChatPal consortium acknowledges the support provided by the Interreg VB Northern Periphery & Arctic Programme under the grant for Conversational Interfaces Supporting Mental Health and Wellbeing of People in Sparsely Populated Areas (ChatPal) project number 345.
© 2021 IEEE.
- Conversational user interfaces
- event log
- mental wellbeing