Honors Theses

Date of Award

Spring 4-27-2026

Document Type

Undergraduate Thesis

Department

Economics

First Advisor

Charles Joukhadar

Second Advisor

Yasmine Sedeek

Third Advisor

Noa Valcarcel

Relational Format

Dissertation/Thesis

Abstract

This thesis analyzes the call for a dialect-specific healthcare navigation mobile application for Arabic-speaking patients with limited English proficiency (LEP). Language access is a promised right to the citizens of the United States, yet many systems currently in place fail to provide adequate translation resources. Native Arabic speakers are being failed by the current healthcare system in the United States. Arabic is complex in dialect, culture, and health literacy. No current AI technologies or digital applications provide full coverage to healthcare navigation, and this leaves many patients at risk.

The qualitative thesis below will introduce Shifa Rx, a full-spectrum navigation to the American Healthcare system. The study employed a mixed-methods approach across three phases: the first was a broad community-based survey of native Arabic speakers from Mississippi and Southern Tennessee. Findings show a clear interest in the need for the app, with an emphasis on specific dialect translation requests. Second, a primary testing of two popular AI chatbots, ChatGPT and Google Gemini, across medical translation scripts. Preliminary results showed a large weakness in dialectal accuracy, and interestingly, the highest risk fell into mental health screening. Lastly, the paper discusses the next step that is currently in beta phase, the UX design that will provide the first interactive platform to test Shifa Rx.

Together, these findings will provide both empirical and design-based justification for Shifa Rx. By centering the app around the real-life needs of Arabic-speaking patients, the application is positioned to identify and address the shortcomings in healthcare access and communication. Shifa Rx aims to reduce communication barriers, enhance patient safety, and promote healthcare awareness among the underrepresented population.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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