Chest X-rays are commonly used to help diagnose and manage chest conditions. Artificial intelligence (AI) tools are increasingly being used to support chest X-ray interpretation. However, it is not yet clear whether the timing of AI information affects how clinicians review images, make decisions, and use AI support. This study will look at whether showing AI information before or after a clinician first reviews a chest X-ray changes how they look at the image, how long they take, their interpretation decisions, their confidence, and their trust in AI support. Healthcare professional participants will complete two chest X-ray interpretation sessions in a controlled NHS research setting. During each session, participants will review de-identified chest X-ray images while wearing eye-tracking equipment. Eye-tracking will record where a participant looks on the image and how long they spend looking at different areas. In one session, AI information will be shown before the participant reviews the chest X-ray. In the other session, AI information will be shown after the participant has first reviewed the chest X-ray. The order of these two sessions will be balanced across participants. The study uses de-identified chest X-ray images from existing examinations. It does not involve patients directly, does not change clinical care, and no clinical decisions will be made from the study readings. Participants will also complete a short questionnaire about their experience of using AI support. A separate anonymous survey will collect wider views from clinicians, patients, members of the public, and healthcare staff about the use of AI in chest X-ray interpretation.
Age range
18 Years
Sex
ALL
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Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
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A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Change in Chest X-ray Case Interpretation Time
Timeframe: Session 1 at enrolment and Session 2 at least 4 weeks later, anticipated average 5 weeks
Change in Chest X-ray Case Diagnostic Accuracy
Timeframe: Session 1 at enrolment and Session 2 at least 4 weeks later, anticipated average 5 weeks
Change in Chest X-ray Case Visual Search Behaviour
Timeframe: Session 1 at enrolment and Session 2 at least 4 weeks later, anticipated average 5 weeks
Trust in AI Support After Reader-Study Completion
Timeframe: Immediately after Session 2, anticipated average 5 weeks after enrolment