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Effectiveness of a Large Language Model-Based Educational Tool on Visual Field Test Reliability in Glaucoma Patients

NCT07327242 · Status: ENROLLING_BY_INVITATION · Phase: NA · Type: INTERVENTIONAL · Enrollment: 80

Last updated 2026-01-08

No results posted yet for this study

Summary

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.

Conditions

Interventions

OTHER

LLM-based Education

Participants will receive audiovisual education powered by a large language model (LLM) before their visual field test. The LLM will be presented using a 10 inch tablet or laptop device by a trained research team member. The interaction is intended to be self-guided, with no interference from the staff unless the LLM displays incorrect or "hallucinated" content. In such cases, the research staff will immediately correct any misinformation and record the occurrence, including details and frequency of the hallucination, for quality monitoring. The LLM module will deliver instructions, simulate the visual field test experience, and include a brief knowledge check. This LLM-based education is for research purposes only. Afterward, participants will proceed to their scheduled visual field test, which will include standard support from the clinic perimetrist.

Sponsors & Collaborators

Principal Investigators

  • Robert T Chang, MD · Stanford University

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-01-31
Primary Completion
2026-06-30
Completion
2026-06-30

Countries

  • United States

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07327242 on ClinicalTrials.gov