Actively Recruiting

Phase Not Applicable
All Genders
Healthy Volunteers
NCT07402668

Does AI Make Clinicians More Appropriately Confident? A Randomized Study in Preterm Birth Prediction

Led by Rigshospitalet, Denmark · Updated on 2026-05-05

125

Participants Needed

7

Research Sites

16 weeks

Total Duration

On this page

Sponsors

R

Rigshospitalet, Denmark

Lead Sponsor

T

Technical University of Denmark

Collaborating Sponsor

AI-Summary

What this Trial Is About

The goal of this randomized questionnaire-based study is to evaluate how different presentations of artificial intelligence (AI) decision support influence clinical judgment among medical doctors working in obstetrics and gynecology when assessing the risk of spontaneous preterm birth using clinical case vignettes with cervical ultrasound images. The study specifically compares two AI presentation formats: a binary classification (preterm vs term birth) and an individualized risk estimate of preterm birth. The main questions it aims to answer are: * Which AI presentation format leads to better alignment between clinicians' confidence and decision accuracy (diagnostic calibration)? * Do different AI presentation formats lead to helpful or harmful changes in clinical decisions? Participants will complete an online questionnaire in which they review clinical cases, make diagnostic and management decisions, rate their diagnostic confidence before and after seeing the AI output, and report their trust in the AI.

CONDITIONS

Official Title

Does AI Make Clinicians More Appropriately Confident? A Randomized Study in Preterm Birth Prediction

Who Can Participate

All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Medical doctors currently working in or training within the field of obstetrics and gynecology.
  • Experience performing transvaginal cervical ultrasound examinations.
Not Eligible

You will not qualify if you...

  • No prior experience performing transvaginal cervical ultrasound examinations.

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 7 locations

1

Copenhagen University Hospital, Rigshospitalet

Copenhagen, Denmark, 2100

Not Yet Recruiting

2

Herlev Hospital

Herlev, Denmark, 2730

Actively Recruiting

3

Copenhagen University Hospital, North Zealand

Hillerød, Denmark, 3400

Actively Recruiting

4

Holbæk Hospital

Holbæk, Denmark, 4300

Not Yet Recruiting

5

Hvidovre Hospital

Hvidovre, Denmark, 2650

Not Yet Recruiting

6

Zealand University Hospital, Roskilde

Roskilde, Denmark, 4000

Actively Recruiting

7

Slagelse Hospital

Slagelse, Denmark, 4200

Not Yet Recruiting

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Research Team

E

Emilie Pi F Sejer, MD

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

SINGLE

Allocation

RANDOMIZED

Model

PARALLEL

Primary Purpose

OTHER

Number of Arms

2

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