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Virginia Tech

Centering the Disabled User Experience of Health Information in a World Driven by Artificial Intelligence: A Mixed Methods Investigation

Abstract

dc:description.abstract

Disabled people are more susceptible to infectious diseases (like COVID-19) than nondisabled people; finding accurate, relevant health information is especially pressing. Internet search technologies are often touted as empowering disabled people who seek healthcare information online, but does this depiction reflect reality? This dissertation encompasses three studies assessing disabled user experiences in finding health information online: a structured literature review, a cross-sectional survey, and a concurrent think-aloud study. The literature review shows that, across 11 articles, disabled people were often not considered in public health messaging surrounding COVID-19. We then analyze 142 cross-sectional survey responses about usability and satisfaction regarding web-based COVID-19 information. Usability and satisfaction were both lower in people who had developmental or mental health disabilities (r=-0.21, p=0.0131 for usability; r=-0.24, p=0.0111 for satisfaction). Satisfaction was also lower among screen magnification or closed caption users (r=-0.21, p=0.0262). In the concurrent think-aloud study, ten participants were asked to internet search four prompts and narrate their experiences in real-time. Themes included concerns about accessibility/usability, AI-generated information, peer-reviewed articles, hospital or government webpages, news/advertising, and sentiment/trust. Participants also reported physical fatigue (n=5) and distracting layouts (n=5) while searching online. All participants encountered AI-generated information in their searches. This dissertation ends in reflection on how future work by scholars in health and information sciences should be shaped by the input of disabled people.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Individual Interdisciplinary PhD
Department dc:contributor.department
Graduate School
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sathe, Sonal Shridhar
Chairs dc:contributor.committeechair
  • Shew, Ashley
  • Porter, Nathaniel D.
Committee members dc:contributor.committeemember
  • Miller, Chreston Allen
  • Rockwell, Michelle S.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:45062
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/139899

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Sathe, Sonal Shridhar. Centering the Disabled User Experience of Health Information in a World Driven by Artificial Intelligence: A Mixed Methods Investigation. doctoral thesis, Virginia Tech, 2025. https://hdl.handle.net/10919/139899