Tests an AI education tool before visual field tests in glaucoma patients
Tests an AI teaching tool before a vision test in adults with glaucoma.
Plain-language title generated from the registry record
Registry title: Effectiveness of a Large Language Model-Based Educational Tool on Visual Field Test Reliability in Glaucoma Patients
Key facts
- Where
- Palo Alto, United StatesSee the site
Where in United States
- Byers Eye InstitutePalo Alto, United StatesNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Stanford University
- Trial code
- NCT07327242
- Record updated
- 8 January 2026
- Original description
The purpose of this study is to evaluate whether a large language model (LLM)-based audiovisual educational tool improves the test time and reliability of standard automated perimetry (SAP) using the SITA Standard 24-2 protocol in English-speaking glaucoma patients.Read full original descriptionShow less
Effectiveness of a Large Language Model-Based Educational Tool on Visual Field Test Reliability in Glaucoma Patients: A Randomized Controlled Trial
The purpose of this study is to evaluate whether a large language model (LLM)-based audiovisual educational tool improves the test time and reliability of standard automated perimetry (SAP) using the SITA Standard 24-2 protocol in English-speaking glaucoma patients.
Glaucoma is a disease that can lead to blindness if not properly monitored and treated. One of the most important tests for glaucoma is the visual field (VF) test, which checks how well a person can see in different directions. However, this test is difficult for many patients to perform correctly, especially if they don't fully understand how it works. Unreliable test results can lead to repeated visits, wasted time, and incorrect treatment decisions.
This study is testing whether a computer-based educational tool, powered by artificial intelligence (AI), can help patients better understand the VF test before taking it. The study team want to see if this helps make the test results more reliable. The goal is to improve the quality of care while reducing the burden on patients and clinic staff.
The LLMs will be used as an educational tool only, not for the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease.
Inclusion: Adults (≥18 years) with a diagnosis or suspected diagnosis of glaucoma; English-speaking; Scheduled for Humphrey visual field testing 24-2 SITA standard; Having at least 2 prior visual field tests , with the most recent prior test performed using the 24-2 SITA Standard strategy within 2 years before enrollment; Best corrected visual acuity in both eyes ≥ 20/40.
Exclusion: Participant has, in the opinion of the investigator, any physical or mental condition that would affect the participation in the study or may interfere with the study procedures, evaluations and outcome assessments; Unable to comply with study and questionnaires.