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

Stanford University

Status: Invitation-only

Conditions: Eye Disorders; Glaucoma; Visual Fields; Visual Field Tests

Treatments: Other: LLM-based Education

Study type: Interventional

Funder types: Other

Identifiers

NCT07327242

82165

Details and patient eligibility

About

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.

Enrollment: 80 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 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 criteria

• Unable to comply with study and questionnaires
• 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.

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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80 participants in 2 patient groups

Standard of Care

No Intervention group

Description:

Patients will be informed of the standard protocol of Humphrey visual field testing by visual field technicians prior to their testing. Their education and knowledge will primarily come from the technicians themselves.

LLM-based Education + Standard of Care

Experimental group

Description:

Participants will receive audiovisual education powered by a large language model (LLM) before their visual field test, in addition to the standard of care information provided by the Humphrey visual field technicians.

Treatment:

Other: LLM-based Education