Automation Bias in Physician-LLM Diagnostic Reasoning

NCT06963957 | Completed

• 1 other identifier: IRB-0374
• Study Type: interventional
• Target: 44
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to systematically measure the extent and patterns of automation bias among physicians when utilizing ChatGPT-4o in clinical decision-making.

Conditions

Diagnosis

Keywords

clinical reasoning; large language models; automation bias; computer-assisted diagnosis

Outcome Measures

Primary Outcomes (1)

• Diagnostic reasoning

  The primary outcome will be the percent correct for each case, ranging from 0 to 100%, where higher scores indicate better diagnostic performance. For each case, participants will be asked for their three leading diagnoses, findings that support each diagnosis, and findings that oppose each diagnosis. For each plausible diagnosis, participants will receive 1 point. Findings supporting the diagnosis and findings opposing the diagnosis will also be graded based on correctness, with 1 point for each correct response. Participants will then be asked to name their top diagnosis they believe is most likely, earning 9 points for a reasonable response and 18 points for the most accurate response. Finally participants will be asked to name up to 3 next steps to further evaluate the patient with 0.5 point awarded for a partially correct response and 1 point for a completely correct response. 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 reasoning evaluation session, which takes place between 0-4 days after participant enrollment.

Secondary Outcomes (1)

• Top choice diagnosis accuracy score

  Assessed at a single time point for each case, during the scheduled diagnostic reasoning evaluation session, which takes place between 0-4 days after participant enrollment.

Study Arms (2)

ChatGPT-4o Recommendations with Hallucinations

ACTIVE COMPARATOR

Participants will evaluate six clinical vignettes. During the trial, they will have access to clinical recommendations from a specific, commercially available LLM (ChatGPT-4o) in addition to conventional diagnostic resources. LLM recommendations for three vignettes will contain deliberately flawed diagnostic information and for three vignettes it will contain accurate recommendations). The cases will be presented in random order.

Other: ChatGPT-4o Recommendations with Hallucinations

ChatGPT-4o Recommendations without Hallucinations

NO INTERVENTION

Participants will evaluate the same six clinical vignettes as in the intervention arm. During the trial, they will have access to clinical recommendations from a specific, commercially available LLM (ChatGPT-4o) in addition to conventional diagnostic resources. However, the LLM-generated recommendations will not contain any deliberately introduced errors. The cases will be presented in random order.

Interventions

ChatGPT-4o Recommendations with Hallucinations OTHER

ChatGPT-4o's differential diagnoses of six clinical vignettes, three of which will contain deliberately introduced inaccurate information.

ChatGPT-4o Recommendations with Hallucinations

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Completed Bachelor of Medicine, Bachelor of Surgery (MBBS) Exam. The equivalent degree of MBBS in US and Canada is called Doctor of Medicine (MD).
• Full or Provisionally Registered Medical Practitioners with the Pakistan Medical and Dental Council (PMDC).
• Participants must have completed a structured training program on the use of ChatGPT (or a comparable large language model), totaling at least 10 hours of instruction. The program must include hands-on practice related to LLM's aspects, specifically prompt engineering and content evaluation.

You may not qualify if:

• Any other Registered Medical Practitioners (Full or Provisional) with PMDC (e.g., Professionals with Bachelor of Dental Surgery or BDS).

Sponsors & Collaborators

• Lahore University of Management Sciences: lead

Study Sites (1)

Lahore University of Management Sciences

Lahore, Punjab Province, 54000, Pakistan

Location

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)

  PRINCIPAL INVESTIGATOR

• Ayesha Ali, PhD

  Lahore University of Management Sciences (LUMS)

  PRINCIPAL INVESTIGATOR

• Muhammad Asadullah Khawaja, MBBS

  King Edward Medical University

  PRINCIPAL INVESTIGATOR

• Ali Zafar Sheikh, MBBS

  Lahore General Hospital

  PRINCIPAL INVESTIGATOR

• Muhammad Junaid Akhtar, MBBS

  Children's Hospital, Lahore

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Masking Details: Single (Outcomes Assessor)
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Full Professor, PhD

Model Details: The trial will be designed as a randomized, two-arm, single-blind parallel group study.

Study Record Dates

• First Submitted: April 23, 2025
• First Posted: May 9, 2025
• Study Start: June 20, 2025
• Primary Completion: August 15, 2025
• Study Completion: August 15, 2025
• Last Updated: August 22, 2025

Record last verified: 2025-08

Data Sharing

• IPD Sharing: Will not share

Locations

PA (1)