[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100644861":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":25,"locations":25,"responsibleParty":30,"collaborators":25,"id":32,"slug":33,"hasResults":34,"nctId":35,"briefTitle":36,"officialTitle":37,"acronym":38,"eligibilityCriteria":39,"healthyVolunteers":40,"sex":41,"minAge":42,"maxAge":25,"enrollmentInfo":43,"targetDuration":25,"studyType":46,"phases":47,"briefSummary":49,"conditions":50,"keywords":54,"overallStatus":64,"whyStopped":25,"lastUpdateSubmitDate":65,"lastUpdatePostDateStruct":66,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":25},{"fullName":5,"class":6},"University Hospitals, Leicester","OTHER",[8,15],{"label":9,"type":10,"description":11,"interventionNames":12},"Original CXR First Sequence","EXPERIMENTAL","Participants complete the original chest X-ray first timing condition in Session 1, followed by the AI output first timing condition in Session 2. Sessions are separated by at least four weeks.",[13,14],"Behavioral: Original CXR First Timing","Behavioral: AI Output First Timing",{"label":16,"type":10,"description":17,"interventionNames":18},"AI Output First Sequence","Participants complete the AI output first timing condition in Session 1, followed by the original chest X-ray first timing condition in Session 2. Sessions are separated by at least four weeks.",[13,14],[20,26],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":25},"BEHAVIORAL","Original CXR First Timing","Participants first review the original chest X-ray without AI output and complete an initial structured interpretation response. AI output is then introduced, and participants may review or revise their response before submitting the final response for that case.",[16,9],null,{"type":21,"name":27,"description":28,"armGroupLabels":29,"otherNames":25},"AI Output First Timing","Participants first view AI output before reviewing the original chest X-ray. The original chest X-ray is then introduced, and participants complete or revise their structured interpretation response before submitting the final response for that case.",[16,9],{"type":31,"investigatorFullName":25,"investigatorTitle":25,"investigatorAffiliation":25,"oldNameTitle":25,"oldOrganization":25},"SPONSOR","100644861","ai-timing-in-chest-x-ray-interpretation-using-eye-tracking-100644861",false,"NCT07675694","AI Timing in Chest X-ray Interpretation Using Eye-Tracking","A Within-Subject Eye-Tracking Study Examining How the Timing of AI Decision Support Influences Visual Search Behaviour, Diagnostic Accuracy, and Trust During Chest X-ray Interpretation","CREAITED","Inclusion Criteria:\n\nMain reader study:\n\n* Healthcare professionals aged 18 years or over\n* Registered to practise in the UK\n* Employed by the NHS or another healthcare service operating in the UK\n* Current or recent, within the last 3 years, clinical experience involving chest X-ray interpretation, review, or use in clinical practice\n* Able to attend two onsite study sessions at University Hospitals of Leicester NHS Trust at mutually agreed times\n* Able and willing to provide written informed consent\n* Compatible with the eye-tracking equipment\n\nSupplementary survey:\n\n* Adults aged 18 years or over\n* Live in the UK or have used the NHS or another UK healthcare service within the last 5 years\n* Able to provide informed electronic consent\n* Belong to one of the following respondent groups: healthcare professionals or healthcare staff, patients or carers, or members of the public\n* Healthcare professional respondents may include adults involved in requesting, interpreting, checking, or acting on chest X-ray findings in clinical practice\n\nExclusion Criteria:\n\nMain reader study:\n\n* Inability to attend both onsite study sessions at University Hospitals of Leicester NHS Trust\n* Eye-tracking incompatibility, such as visual, neurological, or physical conditions preventing adequate gaze tracking or participant comfort\n* Direct involvement in selection, adjudication, or preparation of the chest X-rays used in the study\n* Conflicts of interest, including direct involvement in development of the AI system under evaluation\n* Prior participation in a closely related AI chest X-ray study where overlap in image sets or study procedures may compromise validity, assessed on a case-by-case basis\n\nSupplementary survey:\n\n* Aged under 18 years\n* Does not live in the UK and has not used the NHS or another UK healthcare service within the last 5 years\n* Unable to provide informed electronic consent\n* Does not meet one of the eligible respondent groups for the survey",true,"ALL","18 Years",{"count":44,"type":45},24,"ESTIMATED","INTERVENTIONAL",[48],"NA","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.\n\nThis 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.\n\nHealthcare 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.\n\nIn 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.\n\nThe 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.",[51,52,53],"Diagnostic Imaging","Eye Tracking","Artificial Intelligence (AI)",[55,56,57,58,59,60,61,62,63],"Artificial intelligence timing","Chest X-ray interpretation","Visual search behaviour","Diagnostic accuracy","Trust in automation","Automation bias","Clinician confidence","Decision support systems","Human-AI interaction","NOT_YET_RECRUITING","2026-06-29",{"date":67,"type":68},"2026-06-30","ACTUAL",{"date":70,"type":45},"2026-06",{"date":72,"type":45},"2026-12",{"name":5,"class":6}]