Clinicians' Trust in AI-Based Fetal Growth Estimates

Sponsor
Rigshospitalet, Denmark
Study ID
NCT07401368
Status
Not Yet Recruiting

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Conditions

  • Clinical Decision-making
  • Fetal Growth
  • Obstetric Ultrasonography
  • Pregnancy

Eligibility Criteria

Sex
ALL
Age
N/A - N/A
Healthy Volunteers
Accepted

Interventions

  • Intervention - AI Performance Information — OTHER
    Participants receive brief information about the AI model's overall performance before completing the questionnaire.

Study Details

This study examines how clinicians trust and use artificial intelligence (AI) when estimating fetal weight during pregnancy. Accurate assessment of fetal growth is important for identifying growth problems that may affect pregnancy management. New AI-based tools can estimate fetal weight from ultrasound images, but little is known about how clinicians trust these estimates or how uncertainty information influences their decisions. In this study, clinicians will review anonymized ultrasound cases and compare fetal weight estimates generated by an AI model with traditional estimates. Some clinicians will also be shown information about the AI model's performance and uncertainty, while others will not. Participants will be asked to choose which estimate they find most reliable, indicate their level of confidence, and decide whether they would recommend follow-up scans. The study aims to better understand how AI and uncertainty information affect clinical decision-making and trust among clinicians with different levels of experience.

Key Dates

First listed
Feb 10, 2026
Start date
Jun 1, 2026
Status verified
Feb 2026
Primary completion
Dec 1, 2027
Completion
Dec 1, 2028

Study Design

Enrollment
308 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH

Arms

  • No Intervention: Control - No AI Performance Information
    Participants complete the questionnaire without receiving information about the AI model's overall performance.
  • Other: ntervention - AI Performance Information
    Participants receive brief information about the AI model's overall performance before completing the questionnaire.

Primary Outcome Measure

Clinicians' choice of fetal weight estimation method [ Time Frame: Immediately after questionnaire completion ]

Central Contacts

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