Clinicians' Trust in AI-Based Fetal Growth Estimates
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
AgeNot listed
SponsorRigshospitalet, Denmark
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Clinicians working in obstetrics and gynecology departments.
Regular use of obstetric ultrasound in clinical practice.
Willingness to participate in a questionnaire-based study.
Disqualifiers
Clinicians who do not perform obstetric ultrasound examinations.
Clinicians with a known conflict of interest related to the AI system being evaluated.
Trial design
Design model
Parallel
Treatments tested in this trial
Intervention - AI Performance Information
Other interventionParticipants receive brief information about the AI model's overall performance before completing the questionnaire.
Treatment groups
308 Participants
are divided into 2 treatment groupsGroup A: Control - No AI Performance InformationNo intervention 0 interventions
Group B: ntervention - AI Performance InformationOther 1 intervention
Trial outcomes
Primary outcomes
1
Clinicians' choice of fetal weight estimation method
The proportion of cases in which clinicians choose the AI-based fetal weight estimate rather than the traditional Hadlock estimate when assessing anonymized ultrasound cases.
Time frame
Immediately after questionnaire completionSecondary outcomes
1
Clinicians' confidence in selected fetal weight estimate
Clinicians' self-reported confidence in the selected fetal weight estimate, measured on a 7-point Likert scale for each case.
Time frame
Immediately after questionnaire completion2
Recommendation of follow-up growth scan
Whether clinicians recommend a follow-up fetal growth scan based on the selected fetal weight estimate, recorded as a binary outcome (yes/no).
Time frame
Immediately after questionnaire completion3
Impact of uncertainty information on model preference
Difference in clinicians' preference for AI-based versus traditional fetal weight estimates when AI predictions are presented with versus without uncertainty information.
Time frame
Immediately after questionnaire completionSponsors and contacts
Click on the lead sponsor to view all of their trials.
Rigshospitalet, Denmark
Lead sponsor
Slagelse Hospital
Collaborator
Copenhagen Academy for Medical Education and Simulation
Collaborator
Source ClinicalTrials.gov
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