Type 1 Diabetes (T1D) is an irreversible chronic autoimmune disease that affects millions in the United States. Individuals with T1D rely on biomedical technologies to manage their disability and to stay alive. The increased use of and reliance on automated technologies creates complex entanglements between human bodies, technologies and external factors including digital infrastructures creating what I term as "biotechnological organism." This U.S.-based study focuses on the most advanced biomedical technology used to manage T1D today, the Artificial Pancreas System (APS), to demonstrate how seemingly liberating automated biomedical technologies can entangle, subjugate, and confine those they aim to free. This study features the analysis of two distinct social groups by focusing on their risk discourses and risk reduction efforts. The first group is a community of regulatory experts represented by the American Diabetes Association (ADA). It provides an important perspective grounded in evidence-based science, established norms, and professional standards of medicine, healthcare, and research. The second group is the Do-It-Yourself (DIY) biological community represented by DIY innovators, patients, caregivers, and advocates. It provides a different but equally important perspective shaped by affective dimensions that reflect a phenomenological experience with biomedical technologies. The combination of these two perspectives along with the improved understanding of this disability, the complexity of entanglements between humans and machines, differing approaches to health automation and knowledge production practices elucidates important social, economic, and political issues. The significance of this work lies in its examination of how the improved understanding of health automation efforts can help inform policy and healthcare decisions. / Doctor of Philosophy / Type 1 Diabetes (T1D) is a chronic condition when the pancreas does not make enough insulin necessary for the body to allow blood glucose (blood sugar) to enter cells and produce energy. This disability affects millions in the United States. Individuals with T1D rely on biomedical technologies to manage their blood glucose levels and need to inject insulin to stay alive. The increased use of and reliance on automated technologies is encouraged to reduce the risks of health complications and reduce the demands of T1D management. But automated biomedical technologies also pose additional burdens related to technological use, maintenance, data overload, decision-making, and risk. This U.S.-based study focuses on the most advanced biomedical technology used to manage T1D today, the Artificial Pancreas System (APS). I coin the term "biotechnological organism" to describe the complex relationship between humans and biomedical technologies. The study demonstrates how seemingly liberating automated biomedical technologies can burden those they aim to free from the demands of disease. This study features the analysis of two distinct groups by focusing on their risk perceptions and risk reduction efforts. The first group is regulatory experts represented by the American Diabetes Association (ADA). This group provides an important perspective grounded in evidence-based science, established norms, and professional standards of medicine, healthcare, and research. The second group is the Do-It-Yourself (DIY) biological community, which includes DIY innovators, patients, caregivers, and advocates. This group provides a different but equally important perspective shaped by the diverse lived experiences of people using biomedical technologies. The improved understanding of differing approaches to health automation and knowledge production practices within these two groups elucidates important social, economic, and political issues. This work aims to understand how health automation efforts can help inform policy and healthcare decisions.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115054 |
| Date | 15 May 2023 |
| Creators | Brantly, Nataliya D. |
| Contributors | Science and Technology Studies, Hester, Rebecca, Heflin, Ashley Shew, Dufour, Monique S., Abbate, Janet E. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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