System disruptions
We are currently experiencing disruptions on the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Insights and lessons learned from trialling a mental health chatbot in the wild
School of Computing, Ulster University, Newtownabbey, UK.
School of Computing, Ulster University, Newtownabbey, UK.
School of Computing, Ulster University, Newtownabbey, UK.
School of Psychology Ulster, University Derry, Londonderry, UK.
Show others and affiliations
2021 (English)In: 2021 IEEE Symposium on Computers and Communications (ISCC), IEEE, 2021, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2021. p. 1-6
Keywords [en]
Measurement, Computers, Data analysis, Mood, Mental health, Medical services, Chatbots, Conversational user interfaces, event log, eHealth, mental wellbeing, co-design, COVID-19
National Category
Human Computer Interaction
Research subject
Nursing
Identifiers
URN: urn:nbn:se:ltu:diva-88453DOI: 10.1109/ISCC53001.2021.9631395ISI: 000936276000026Scopus ID: 2-s2.0-85123221410OAI: oai:DiVA.org:ltu-88453DiVA, id: diva2:1621072
Conference
2021 IEEE Symposium on Computers and Communications (ISCC),Athens, Greece, 5-8 Septemper 2021
Note

ISBN för värdpublikation:978-1-6654-2744-9, 978-1-6654-2745-6

Available from: 2021-12-17 Created: 2021-12-17 Last updated: 2024-03-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Kostenius, Catrine

Search in DiVA

By author/editor
Kostenius, Catrine
By organisation
Nursing and Medical Technology
Human Computer Interaction

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 76 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf