Improving AI-Assisted Medical Diagnosis and Triage by the General Public

NCT07728513 | Recruiting

• 1 other identifier: AI-Assisted-Diag-Public789
• Study Type: interventional
• Target: 220
• Locations: 1 country
• Sites: 1

Brief Summary

This study is a randomized controlled trial (RCT) investigating whether access to a new LLM interface can improve medical triage and diagnostic accuracy for laypeople compared to access to a standard LLM interface. It addresses previous findings where laypeople using standard LLMs performed worse than those using conventional methods (e.g., web search) due to incomplete symptom sharing and poor interpretation of AI advice. To address this, the research tests a structured LLM system that proactively asks clinical history questions before providing a standardized, easy-to-read diagnostic output.

Conditions

Large Language Models; AI-Assisted Diagnosis

Keywords

LLMs; Diagnosis; Triage

Outcome Measures

Primary Outcomes (2)

• Urgency Assessment Accuracy

  The primary outcome will be the percentage of correct urgency assessments, ranging from 0 to 100%, where higher scores indicate better urgency assessment (or triage) performance. The rating which participants give for the urgency of each case, will be measured on a five-point scale: Self-care, Routine GP, Urgent Primary Care, Accident \& Emergency, and Ambulance. Responses will be compared against the gold-standard answers to produce an accuracy measure. The primary outcome will be compared at the case-level between the randomized groups.

  Assessed at a single time point for each case, during the scheduled diagnostic evaluation session, which takes place between 0-5 days after participant enrollment.

• Condition Identification Accuracy

  The co-primary outcome is the Condition Identification Accuracy, which is the percentage of cases in which the condition was correctly identified, ranging from 0 to 100%., where higher scores indicate better medical condition identification performance. Participants name all medical conditions they considered relevant to their decision. A response is scored as correct for that scenario if at least one named condition matches the physician-generated gold-standard list of relevant conditions. The co-primary outcome will be compared at the case-level between the randomized groups.

  Assessed at a single time point for each case, during the scheduled diagnostic evaluation session, which takes place between 0-5 days after participant enrollment.

Secondary Outcomes (2)

• Self-Reported Confidence

  Assessed at a single time point for each case, during the scheduled diagnostic evaluation session, which takes place between 0-5 days after participant enrollment.

• Time Spent

  Assessed at a single time point for each case, during the scheduled diagnostic evaluation session, which takes place between 0-5 days after participant enrollment.

Study Arms (2)

Treatment Arm (new GPT-4o Interface)

EXPERIMENTAL

Participants can access any assistance methods they would typically employ (e.g., web search or health portals) in addition to a new LLM interface (based on GPT-4o) to complete medical scenarios. The new LLM interface uses a fixed system prompt that (a) instructs the model to ask targeted clarifying questions before providing any diagnostic or triage suggestions, and (b) requires all final responses to follow a structured template listing: possible conditions, approximate likelihood of each, and a recommended triage with brief reasoning.

Device: new GPT-4o Interface

Control

PLACEBO COMPARATOR

Participants can use any assistance methods they would typically employ (e.g., web search or health portals) in addition to a standard LLM (GPT-4o) to complete medical scenarios. AI-overview in web searches will be disabled via an extension. They would not be allowed to access any LLMs other than the standard LLM interface.

Other: Control

Interventions

new GPT-4o Interface DEVICE

Participants can access any assistance methods they would typically employ (e.g., web search or health portals) in addition to a new LLM (GPT-4o) interface to complete medical scenarios. The new LLM interface uses a fixed system prompt that (a) instructs the model to ask targeted clarifying questions before providing any diagnostic or triage suggestions, and (b) requires all final responses to follow a structured template listing: possible conditions, approximate likelihood of each, and a recommended triage with brief reasoning.

Treatment Arm (new GPT-4o Interface)

Control OTHER

Participants use any assistance methods they would typically employ at home (e.g., Google or health portals) in addition to a standard LLM (GPT-4o) to complete medical scenarios. AI-overview in web searches will be disabled via an extension. They would not be allowed to access any LLMs other than the standard LLM interface.

Control

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Enrolled student or employed administrative staff at LUMS.
• years of age or older.
• Able to read and understand English.

You may not qualify if:

• Individuals with any formal education or professional training in medicine, nursing, or any other healthcare profession.

Sponsors & Collaborators

• Lahore University of Management Sciences: lead

Study Sites (1)

Lahore University of Management Sciences

Lahore, Punjab Province, 54000, Pakistan

RECRUITING

MeSH Terms

Conditions

Disease

Condition Hierarchy (Ancestors)

Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Ihsan Ayyub Qazi, PhD

  Lahore University of Management Sciences (LUMS)

  STUDY CHAIR

• Ayesha Ali, PhD

  Lahore University of Management Sciences (LUMS)

  PRINCIPAL INVESTIGATOR

• Zafar Ayyub Qazi, PhD

  Lahore University of Management Sciences (LUMS)

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ihsan Ayyub Qazi, PhD

CONTACT

+923233333766; ihsan.qazi@lums.edu.pk

Ayesha Ali, PhD

CONTACT

04235608368; ayeshaali@lums.edu.pk

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Participants will not be informed of which arm constitutes the "treatment" or what the study hypothesizes.
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: July 22, 2026
• First Posted: July 27, 2026
• Study Start: July 1, 2026
• Primary Completion (Estimated): July 1, 2027
• Study Completion (Estimated): July 1, 2027
• Last Updated: September 17, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will not share

Locations

PA (1)