Date of Award

5-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

Committee Chair/Advisor

Kaileigh Byrne

Committee Member

Cynthia Pury

Committee Member

Dawn Sarno

Committee Member

Sab Babu

Abstract

The prevalence of depression in the U.S. has increased over the past decade, leading to an all-time-high during the COVID-19 pandemic (WHO, 2022). With this increase, the number of mental health applications (MHealth apps) on virtual e-stores increases in tandem. Despite this expanding number of MHealth apps, few demonstrate a foundation in empirical research. One design factor that may influence usability and effectiveness is the inclusion of virtual agents. Three studies were conducted to investigate users’ preferences for a variety of characteristics associated with virtual agents. In Experiment 1, users completed a single-session, three-stage CBT-based interaction with virtual characters and were asked about preferences for customization versus evolution. Results demonstrated that participants preferred customization, as it involves more active inclusion in the application. In Experiment 2, users completed four CBT-based modules; two modules with an interactive design and two with a passive design. Results demonstrated a preference for the interactive virtual agent along with higher levels of trust, satisfaction, and comfort. The goal of Experiment 3 was to determine the effect of conversation and animation within a CBT-based MHealth app on depressive symptoms and user experience using a longitudinal experimental design. Results demonstrated a significant decrease in symptoms of depression; however, no significant effect of conversation or animation was observed. This collection of experiments provides insight into user preferences regarding virtual characters. While the addition of virtual agents to MHealth applications holds promise, more research and refinement is necessary to achieve a seamless incorporation into the mental health domain.

Author ORCID Identifier

0000-0002-7435-1773

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.