Design and evaluation of virtual human mediated tasks for assessment of depression and anxiety

Egede, Joy O., Price, Dominic, Krishnan, Deepa B., Jaiswal, Shashank, Elliott, Natasha, Morriss, Richard, Galvez Trigo, Maria J. ORCID: https://orcid.org/0000-0001-6492-0955, Nixon, Neil, Liddle, Peter, Greenhalgh, Christopher and Valstar, Michel 2021. Design and evaluation of virtual human mediated tasks for assessment of depression and anxiety. Presented at: IVA '21: ACM International Conference on Intelligent Virtual Agents, Virtual Event Japan, 14-17 September 2021. Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents. ACM, pp. 52-59. 10.1145/3472306.3478361

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Abstract

Virtual human technologies are now being widely explored as therapy tools for mental health disorders including depression and anxiety. These technologies leverage the ability of the virtual agents to engage in naturalistic social interactions with a user to elicit behavioural expressions which are indicative of depression and anxiety. Research efforts have focused on optimising the human-like expressive capabilities of the virtual human, but less attention has been given to investigating the effect of virtual human mediation on the expressivity of the user. In addition, it is still not clear what an optimal task is or what task characteristics are likely to sustain long term user engagement. To this end, this paper describes the design and evaluation of virtual human-mediated tasks in a user study of 56 participants. Half the participants complete tasks guided by a virtual human, while the other half are guided by text on screen. Self-reported PHQ9 scores, biosignals and participants' ratings of tasks are collected. Findings show that virtual-human mediation influences behavioural expressiveness and this observation differs for different depression severity levels. It further shows that virtual human mediation improves users' disposition towards tasks.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	ACM
ISBN:	9781450386197
Date of First Compliant Deposit:	2 May 2023
Date of Acceptance:	17 June 2021
Last Modified:	02 Jun 2023 01:30
URI:	https://orca.cardiff.ac.uk/id/eprint/158564

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