Ayesha-Mae Bilal: The Space Between: Bridging Emotion and Data in Mental Health Research

Abstract

Smartphone apps offer new opportunities to study mental health in real-world settings through a combination of passive sensor data and active self-report. This thesis explores how digital mental health research tools can be designed to collect meaningful, ecologically valid data while respecting user experience, motivation, and autonomy. Across four interrelated studies, I examine two app-based cohort studies targeting perinatal women (Mom2B) and young people (UPIC) in Sweden.

The first study presents the technical and ethical foundations of the Mom2B platform, including its integration of digital phenotyping methods. The second study applies machine learning techniques to self-reported data to assess the potential for early prediction of antenatal depression. The third study investigates user attitudes toward data sharing and task engagement, revealing the nuanced balance between research goals and participant comfort. The fourth study follows a user-centered design and usability testing process in the development of the UPIC app, highlighting how early user involvement can improve design, trust, and engagement.

Together, the findings demonstrate the importance of aligning technological possibilities with thoughtful, user-informed design. The thesis contributes to the growing field of digital mental health research by offering practical and ethical insights into the design and evaluation of emotion- and experience-aware research tools.