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Automation Bias in Physician-LLM Diagnostic Reasoning

NCT06963957 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 44

Last updated 2025-08-22

No results posted yet for this study

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

Interventions

OTHER

ChatGPT-4o Recommendations with Hallucinations

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

Sponsors & Collaborators

  • Lahore University of Management Sciences

    lead OTHER

Principal Investigators

  • Ihsan Ayyub Qazi, PhD · Lahore University of Management Sciences (LUMS)

  • Ayesha Ali, PhD · Lahore University of Management Sciences (LUMS)

  • Muhammad Asadullah Khawaja, MBBS · King Edward Medical University

  • Ali Zafar Sheikh, MBBS · Lahore General Hospital

  • Muhammad Junaid Akhtar, MBBS · Children's Hospital, Lahore

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-06-20
Primary Completion
2025-08-15
Completion
2025-08-15

Countries

  • Pakistan

Study Locations

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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 NCT06963957 on ClinicalTrials.gov