Motivating PhD candidates with depression symptoms to complete thoughts-strengthening exercises via a conversational agent

Master thesis (2020)

Authors

M.A.S. Al Owayyed Electrical Engineering, Mathematics and Computer Science

Contributors

W.P. Brinkman Interactive Intelligence - EEMCS (mentor)
M.L. Tielman Interactive Intelligence - EEMCS (graduation committee member)
A. Panichella Software Engineering - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 Mohammed Al Owayyed
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Published Date

02-07-2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

PhD students are usually more susceptible than other people to depression-inducing situations, which are not adequately addressed in eHealth systems. Cognitive behavioral therapy (CBT) is a well-established depression treatment, and one of its therapeutic methods is to change negative thought patterns into positive ones. The new positive thoughts need to be more believable than the old ones, so therapists usually ask clients to complete sets of thought-strengthening exercises. However, psychologists have expressed concerns regarding patients’ compliance in doing these exercises, as the majority of clients encounter at least one hurdle that obstructs them from completing the exercises. Therefore, we developed a system aimed at motivating doctoral students to perform thought-strengthening exercises. The system allows the candidates to interact with a conversational agent (i.e., a chatbot) to address motivational barriers related to the exercises and complete the exercises within the same program. We used a double-blind experiment with a mixed design setup that included a healthy general public sample group (n = 174) and three conditions (chatbot support, text support, and no support) to test the defined hypotheses and evaluate the system. We hypothesized that the participants’ perceived usefulness and self-efficacy regarding the thought-strengthening exercises would be higher depending on the presentation format (i.e., motivation via text or interactive chatbot) and content (i.e., with or without motivation). The results related to perceived usefulness showed an increase in the conversational agent condition, which showed a significant difference when compared with the no-support condition. As for self-efficacy, various increases occurred in all three conditions; however, no significant difference appeared between them. In conclusion, the conversational agent support system showed the potential to increase PhD students’ motivation to complete the thought-strengthening exercises.