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The Effect of Varying User Risk Levels on Perceived Social Presence in Mental Health Chatbots

  • Sagarika Suresh Thimmanayakanapalya
  • , Raghvendra Singh
  • , Pavankumar Mulgund
  • , Ying Chih Sun
  • , Raj Sharman
  • SUNY Buffalo
  • University of Memphis
  • Harrisburg University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The COVID-19 outbreak has witnessed a significant increase in the development and testing of healthcare chatbots. However, this could raise ethical concerns and pose challenges for responsible research in sensitive healthcare areas such as mental health. Our study focuses on the application of the Social Presence theory to mental-health chatbots. We use quantitative content analysis to determine if users in high-risk mental-health situations require a higher level of social presence from chatbots. Our research contributes to designing improved mental-health chatbots.

Original languageEnglish
Title of host publication29th Annual Americas Conference on Information Systems, AMCIS 2023
PublisherAssociation for Information Systems
ISBN (Electronic)9781713893592
StatePublished - 2023
Event29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023 - Panama City, Panama
Duration: Aug 10 2023Aug 12 2023

Publication series

Name29th Annual Americas Conference on Information Systems, AMCIS 2023

Conference

Conference29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023
Country/TerritoryPanama
CityPanama City
Period08/10/2308/12/23

Keywords

  • chatbot
  • mental health app
  • risk levels
  • Social presence
  • Social Presence theory

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