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Designing Personality-Adaptive Conversational Agents for Mental Health Care

Author

Listed:
  • Rangina Ahmad

    (Technische Universität Braunschweig)

  • Dominik Siemon

    (LUT University)

  • Ulrich Gnewuch

    (Karlsruhe Institute of Technology (KIT))

  • Susanne Robra-Bissantz

    (Technische Universität Braunschweig)

Abstract

Millions of people experience mental health issues each year, increasing the necessity for health-related services. One emerging technology with the potential to help address the resulting shortage in health care providers and other barriers to treatment access are conversational agents (CAs). CAs are software-based systems designed to interact with humans through natural language. However, CAs do not live up to their full potential yet because they are unable to capture dynamic human behavior to an adequate extent to provide responses tailored to users’ personalities. To address this problem, we conducted a design science research (DSR) project to design personality-adaptive conversational agents (PACAs). Following an iterative and multi-step approach, we derive and formulate six design principles for PACAs for the domain of mental health care. The results of our evaluation with psychologists and psychiatrists suggest that PACAs can be a promising source of mental health support. With our design principles, we contribute to the body of design knowledge for CAs and provide guidance for practitioners who intend to design PACAs. Instantiating the principles may improve interaction with users who seek support for mental health issues.

Suggested Citation

  • Rangina Ahmad & Dominik Siemon & Ulrich Gnewuch & Susanne Robra-Bissantz, 2022. "Designing Personality-Adaptive Conversational Agents for Mental Health Care," Information Systems Frontiers, Springer, vol. 24(3), pages 923-943, June.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:3:d:10.1007_s10796-022-10254-9
    DOI: 10.1007/s10796-022-10254-9
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    References listed on IDEAS

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    1. Alfred Benedikt Brendel & Milad Mirbabaie & Tim-Benjamin Lembcke & Lennart Hofeditz, 2021. "Ethical Management of Artificial Intelligence," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Rice, Douglas R. & Zorn, Christopher, 2021. "Corpus-based dictionaries for sentiment analysis of specialized vocabularies," Political Science Research and Methods, Cambridge University Press, vol. 9(1), pages 20-35, January.
    3. Seo Young Kim & Bernd H. Schmitt & Nadia M. Thalmann, 2019. "Eliza in the uncanny valley: anthropomorphizing consumer robots increases their perceived warmth but decreases liking," Marketing Letters, Springer, vol. 30(1), pages 1-12, March.
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    Cited by:

    1. Dominik Siemon & Rangina Ahmad & Henrik Harms & Triparna de Vreede, 2022. "Requirements and Solution Approaches to Personality-Adaptive Conversational Agents in Mental Health Care," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    2. Yu Chen & Scott Jensen & Leslie J. Albert & Sambhav Gupta & Terri Lee, 2023. "Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success," Information Systems Frontiers, Springer, vol. 25(1), pages 161-182, February.
    3. Nikola Finze & Deinera Jechle & Stefan Faußer & Heiko Gewald, 2024. "How are We Doing Today? Using Natural Speech Analysis to Assess Older Adults’ Subjective Well-Being," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 321-334, June.
    4. Babak Abedin & Christian Meske & Iris Junglas & Fethi Rabhi & Hamid R. Motahari-Nezhad, 2022. "Designing and Managing Human-AI Interactions," Information Systems Frontiers, Springer, vol. 24(3), pages 691-697, June.

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