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User Experiences of Well-Being Chatbots.

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Summary
This summary is machine-generated.

This study explored user experiences with well-being conversational agents (CAs), finding that accessibility, communication style, and anthropomorphism are key for engagement. Dynamic responses and clear expectations enhance user interaction with these digital health tools.

Keywords:
health-information technologyhuman-automation interactionmental health and related technologiesmobile devicesusability testing and evaluation

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Area of Science:

  • Human-Computer Interaction
  • Digital Health
  • Mental Health Technology

Background:

  • University students often neglect well-being due to academic and financial pressures, exacerbated by pandemic-related healthcare access limitations.
  • Conversational agents (CAs) show potential for improving healthcare accessibility, particularly for mental well-being, but physical well-being support and accessibility for socio-economically disadvantaged groups remain underexplored.

Purpose of the Study:

  • To investigate user experiences with well-being conversational agents (CAs).
  • To identify crucial features that enhance user engagement with CAs for well-being.
  • To explore the usability of SMS-based CAs and compare them with commercial alternatives.

Main Methods:

  • Thematic analysis of user feedback on mental health CAs from Reddit (Study One).
  • Usability testing of an SMS-based well-being CA and a commercial CA (Woebot) (Study Two).

Main Results:

  • Study One highlighted the importance of CA accessibility, availability, communication style, and anthropomorphism.
  • Study Two identified user response modality, perceived CA role, question specificity, and conversation flow control as critical for engagement.

Conclusions:

  • User experiences with CAs reveal diverse motivations for utilizing them for mental and physical well-being.
  • Key features for continued CA use include dynamic response modalities, anthropomorphism, and early expectation setting.