Visualizing Experience Sampling Data to Enhance Clinical Insights into Mental Resilience

Bachelor Thesis (2025)
Author(s)

A. Economides (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

E.C.S. de Groot – Mentor (TU Delft - Web Information Systems)

WP Brinkman – Mentor (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
26-06-2025
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

Understanding mental resilience-how individuals recover from stressors-is a critical focus area for mental health practitioners. To support this, the Experience Sampling Method (ESM) can be utilized, which offers rich, real-time data for tracking emotional dynamics. However, visualizing these data in an informative and actionable way remains a challenge. This study presents a set of visualizations designed to depict emotional recovery trajectories by focusing on mood, emotions, types of stressors and the influence of coping activities. To assess whether the developed visuals are interpretable and useful to mental health professionals, a survey-based evaluation was conducted. Afterwards, thematic analysis was applied in order to analyze and present the results. What was highlighted in the results is that easy-to-interpret visuals, such as line graphs and heatmaps, were more likely to be considered intuitive and clinically relevant. Moreover, visualizations that incorporated contextual details, like specific emotional responses or coping strategies, were regarded as more insightful and valuable for guiding therapy.

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