The Impact of AI-Assisted Diagnosis and Treatment on Physicians' Potential Legal Liability: An Expert Perspective

NCT07869303 | Not Yet Recruiting

• 1 other identifier: [2026] Thesis Review No.(S102）
• Study Type: interventional
• Target: 440
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this randomized vignette-based experiment is to investigate how AI-related contextual factors influence expert assessment of physician negligence in AI-assisted diagnosis and treatment scenarios among experts in medical malpractice assessment. The main questions it aims to answer are: Does physician acceptance or rejection of AI recommendations, compared with non-AI use, influence the likelihood of being assessed as negligent? Researchers will compare a no-AI assistance control group with four AI-assistance groups under different AI use conditions to examine how AI involvement and contextual factors affect assessments of physician negligence. Participants will: Complete a web-based questionnaire after eligibility confirmation. Evaluate a series of clinical vignettes describing adverse patient outcomes following physician decision-making under different AI-use conditions.

Conditions

Medical Malpractice; Artificial Intelligence in Medicine; Clinical Decision-Making

Keywords

Artificial intelligence; clinical decision support; medical negligence

Outcome Measures

Primary Outcomes (1)

• Physician Negligence Assessment

  Participants will assess whether the physician fulfilled the duty of care in each clinical vignette. Responses are recorded as "Yes" (no negligence) or "No" (negligence).

  Immediately after each clinical vignette during the single online survey session.

Secondary Outcomes (6)

• Reasonableness of the Physician's Decision

  Immediately after each clinical vignette during the single online survey session.

• Magnitude of Physician Fault

  Immediately after each clinical vignette during the single online survey session.

• Allocation of Responsibility

  Immediately after each clinical vignette during the single online survey session.

• Confidence in the Assessment

  Immediately after each clinical vignette during the single online survey session.

• Intention to Use AI in Future Clinical Practice

  Immediately after completion of all four clinical vignettes during the single online survey session.

Study Arms (5)

No AI Assistance (Control Group)

NO INTERVENTION

No AI Assistance (Control Group)

Intervention Group 1

ACTIVE COMPARATOR

General AI with a Standard-of-Care Recommendation

Other: General AI With a Standard-of-Care Recommendation

Intervention Group 2

ACTIVE COMPARATOR

General AI with a Non-Standard-of-Care Recommendation

Other: General AI With a Non-Standard-of-Care Recommendation

Intervention Group 3

ACTIVE COMPARATOR

Expert AI with a Standard-of-Care Recommendation

Other: Expert AI With a Standard-of-Care Recommendation

Intervention Group 4

ACTIVE COMPARATOR

Expert AI with a Non-Standard-of-Care Recommendation

Other: Expert AI With a Non-Standard-of-Care Recommendation

Interventions

General AI With a Standard-of-Care Recommendation OTHER

Participants will evaluate four clinical vignettes involving a general AI system whose historical performance is comparable to that of a township hospital attending physician. The AI provides a recommendation consistent with the standard of care. Physician capability and acceptance or rejection of the AI recommendation vary across the vignettes.

Intervention Group 1

General AI With a Non-Standard-of-Care Recommendation OTHER

Participants will evaluate four clinical vignettes involving a general AI system whose historical performance is comparable to that of a township hospital attending physician. The AI provides a recommendation inconsistent with the standard of care. Physician capability and acceptance or rejection of the AI recommendation vary across the vignettes.

Intervention Group 2

Expert AI With a Standard-of-Care Recommendation OTHER

Participants will evaluate four clinical vignettes involving an expert AI system whose historical performance is comparable to that of a tertiary hospital chief physician. The AI provides a recommendation consistent with the standard of care. Physician capability and acceptance or rejection of the AI recommendation vary across the vignettes.

Intervention Group 3

Expert AI With a Non-Standard-of-Care Recommendation OTHER

Participants will evaluate four clinical vignettes involving an expert AI system whose historical performance is comparable to that of a tertiary hospital chief physician. The AI provides a recommendation inconsistent with the standard of care. Physician capability and acceptance or rejection of the AI recommendation vary across the vignettes.

Intervention Group 4

Eligibility Criteria

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

You may qualify if:

• Physicians qualified to participate in medical negligence assessments, generally holding the title of associate chief physician or above and having relevant clinical experience; or forensic medical experts affiliated with an officially recognized forensic assessment institution and qualified to conduct medical negligence assessments independently.
• Able to read and understand the clinical vignettes and complete the online survey independently.

You may not qualify if:

• Physicians who are not qualified to participate in medical negligence assessments.
• Forensic medical experts who are not qualified to conduct medical negligence assessments independently or are not affiliated with an officially recognized forensic assessment institution.
• Unable to understand or complete the vignette-based online survey.

Sponsors & Collaborators

• Xie Xiaoyun: lead

Central Study Contacts

Xiaoyun Xie, Master

CONTACT

+86 18061291721; xxy996269@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, INVESTIGATOR
• Masking Details: Due to the nature of intervention, participants will be aware of their groups (control vs intervention), but blinded to the specific intervention group if assigned to one. All participants will initiate the study by accessing an identical, standardized link to the study website. Upon entering the website and provide consent, the built-in, automated randomization algorithm will assign participants to one of the five groups (ratio: 1:1:1:1:1).
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Head of Otolaryngology

Study Record Dates

• First Submitted: September 16, 2026
• First Posted: October 9, 2026
• Study Start: September 30, 2026
• Primary Completion (Estimated): June 15, 2027
• Study Completion (Estimated): August 20, 2027
• Last Updated: October 9, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP
• Time Frame: Data will be available following publication of the study results and for five years thereafter.
• Access Criteria: Researchers with a methodologically sound proposal may request access to the data. Requests will be reviewed by the principal investigator, and approved applicants will be required to sign a data-sharing agreement.