Requirements and Solution Approaches to Personality-Adaptive Conversational Agents in Mental Health Care
Dominik Siemon,
Rangina Ahmad,
Henrik Harms and
Triparna de Vreede
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Dominik Siemon: Department of Software Engineering, School of Engineering Science, LUT University, 53850 Lappeenranta, Finland
Rangina Ahmad: Chair of Information Management, Institute of Business Information Systems, Technische Universität Braunschweig, 38106 Braunschweig, Germany
Henrik Harms: Chair of Information Management, Institute of Business Information Systems, Technische Universität Braunschweig, 38106 Braunschweig, Germany
Triparna de Vreede: School of Information Systems and Management, Muma College of Business, University of South Florida, Tampa, FL 33620, USA
Sustainability, 2022, vol. 14, issue 7, 1-18
Abstract:
Artificial intelligence (AI) technologies enable Conversational Agents (CAs) to perform highly complex tasks in a human-like manner and may help people cope with anxiety to improve their mental health and well-being. To support patients with their mental well-being in an authentic way, CAs need to be imbued with human-like behavior, such as personality. In this paper we cover an innovative form of CA, so-called Personality-Adaptive Conversational Agents (PACAs) that automatically infer users’ personality traits and adapt accordingly to their personality. We empirically investigate their benefits and caveats in mental health care. The results of our study show that PACAs can be beneficial for mental health support, but they also raise concerns about trust and privacy issues. We present a set of relevant requirements for designing PACAs and provide solution approaches that can be followed when designing and implementing PACAs for mental health care.
Keywords: conversational agents; Personality-Adaptive Conversational Agents; mental health care (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:7:p:3832-:d:778582
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