Automating Health: The Promises and Perils of Biomedical Technologies for Diabetes Management

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.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Science and Technology Studies

Department dc:contributor.department

Science and Technology Studies

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2023

Author dc:creator

• Brantly, Nataliya D.

Chair dc:contributor.committeechair

• Hester, Rebecca

Committee members dc:contributor.committeemember

• Heflin, Ashley Shew
• Dufour, Monique S.
• Abbate, Janet E.

• Automation
• Diabetes
• Risk
• SCOT
• Disability
• STS

Statement dc:rights

• Creative Commons Attribution 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:37234

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/115054