Gaining and Visualizing Mental Health Insights from Self-Report Data

Presentation of Insights from ESM Data into Client Conditions for Practitioners

Bachelor Thesis (2025)
Author(s)

K. van Maasdam (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Esra Cemre Su de Groot – Graduation committee member (TU Delft - Web Information Systems)

W.P. Brinkman – Graduation committee member (TU Delft - Interactive Intelligence)

Reginald Lagendijk – Graduation committee member (TU Delft - Cyber Security)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
27-06-2025
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

ESM is an important step towards improving mental health care and its efficiency. Most research in this field has focused on the client as its end user. However, mental health practitioners can also use the data gathered using ESM to gain insights into their clients. To discover what methods of visualization practitioners find most insightful and intuitive to identify mental health conditions, and why, a user evaluation containing mock-ups based on existing literature has been performed. In total, 8 people participated in the study, 6 of which were psychology students, 1 was a psychology researcher and 1 was a mental health practitioner. Based on the user evaluation, it was concluded that the use of spider plots comparing the average and variability of the ESM data of a client to that of a cohort with a certain mental health condition is an intuitive visualization method to identify mental health conditions in clients.

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