Year: 2020
Type: dissertation
Abstract: Health technologies are increasingly prevalent and important to support the management of chronic health conditions. Such health technologies often rely on self-tracking, or the practice of collecting and reflecting on personal data, to help people better understand their symptoms and learn how their habits and behaviors affect those symptoms. Many people with chronic conditions and their health providers believe that self-tracking offers a potential for a more complete and accurate understanding of an individual’s personal health. However, people and their health providers often struggle to collect, interpret, and act on self-tracked data, leaving this potential largely unmet. My dissertation research examines how health technologies can better support the goals an individual may bring to their chronic condition management, focusing on three distinct health contexts. I first summarize my work in mental health and irritable bowel syndrome, in which I investigated how systems could support common condition management goals that people and health providers pursue within these domains. My research in these areas revealed nuanced and personalized goals that individuals often developed throughout the management of their condition. I then describe my development of goal-directed self-tracking, a novel method that aims to explicitly elicit, represent, and support the goals people and their health providers may have for their personalized health management. I explored goal-directed self-tracking in the context of migraine, synthesizing findings from my prior work and formative studies to explore how tools could help people and their health providers: 1) express their tracking goals; 2) collect exactly and only the data they need to achieve those goals; and 3) interpret the resulting data appropriately for those goals. Finally, I discuss next steps and future challenges for goal-directed self-tracking, including opportunities for additional research in supporting holistic health management, patient-provider collaboration with patient-generated data, and artificial intelligence to further personalize health technologies. My dissertation therefore contributes new understanding, methods, and tools to support people and their health providers in expressing and pursuing their multiple, distinct, and evolving goals.
Author: Jessica Schroeder
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: green
Funder: National Science Foundation
Awards: Graduate Research Fellowship Program (GRFP), SCH: INT: Supporting Healthy Sleep Behaviors through Ubiquitous Computing, CHS: Small: Support for Self-Tracking and Patient-Provider Collaboration Using Data for Multiple and Evolving Goals in People with Migraine, III: Large: Collaborative Research: Analysis Engineering for Robust End-to-End Data Science, CAREER: Inspecting Personal Informatics: Reflection Practices to Unlock Value in Self-Tracked Data
OpenAlex ID: W3162721377