Ignite Creation Date:
2025-12-25 @ 12:45 AM
Ignite Modification Date:
2026-01-02 @ 1:44 AM
Study NCT ID:
NCT06980467
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-05-20
First Post:
2025-04-28
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Evaluation of AI-Generated Clinical Advice by Physicians
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'interventionBrowseModule': {'meshes': [{'id': 'D000098342', 'term': 'Large Language Models'}], 'ancestors': [{'id': 'D000077321', 'term': 'Deep Learning'}, {'id': 'D000069550', 'term': 'Machine Learning'}, {'id': 'D001185', 'term': 'Artificial Intelligence'}, {'id': 'D000465', 'term': 'Algorithms'}, {'id': 'D055641', 'term': 'Mathematical Concepts'}, {'id': 'D016571', 'term': 'Neural Networks, Computer'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'OTHER', 'interventionModel': 'CROSSOVER'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 8}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-05-15', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2025-05-23', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-05-12', 'studyFirstSubmitDate': '2025-04-28', 'studyFirstSubmitQcDate': '2025-05-12', 'lastUpdatePostDateStruct': {'date': '2025-05-20', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-05-20', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-05-22', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Physician Response to AI-Generated Medical Content', 'timeFrame': 'Through study completion, an average of 1 week', 'description': 'Participants will rate their level of agreement with AI-generated clinical suggestions presented in simulated medical scenarios. Responses will be recorded using a standardized rating scale (range 1-5, where higher scores indicate better agreement).'}], 'secondaryOutcomes': [{'measure': 'Physician Perception of Communication Quality in AI-Generated Content', 'timeFrame': 'Through study completion, an average of 1 week', 'description': 'Participants will assess the communication style of AI-generated content, focusing on factors such as empathy. Ratings will be collected using a standardized 5-point scale (range 1-5, where higher scores reflect higher perceived quality).'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Artificial Intelligence (AI)']}, 'descriptionModule': {'briefSummary': 'This study examines how artificial intelligence systems interact with medical professionals. Researchers will compare physician responses to different AI-generated outputs in simulative medical scenarios.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '80 Years', 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Age ≥ 18 years old;\n* Licensed physician or medical professional qualified to perform clinical evaluations;\n* Willing to sign informed consent and commit time to participate in the study.\n\nExclusion Criteria:\n\n* Unable to dedicate sufficient time to complete the study tasks;\n* Unable or unwilling to understand and follow study instructions.'}, 'identificationModule': {'nctId': 'NCT06980467', 'briefTitle': 'Evaluation of AI-Generated Clinical Advice by Physicians', 'organization': {'class': 'OTHER', 'fullName': 'Tsinghua University'}, 'officialTitle': 'A Study on the Evaluation of Artificial Intelligence-Generated Clinical Advisory Outputs in Medical Professional Contexts', 'orgStudyIdInfo': {'id': '2025-07'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'NO_INTERVENTION', 'label': 'control group', 'description': 'Participants evaluate clinical recommendations generated by Language Model A (LLM-A), with subsequent assessments of communication style characteristics using rating scales.'}, {'type': 'EXPERIMENTAL', 'label': 'intervention group', 'description': 'Participants evaluate clinical recommendations generated by Language Model B (LLM-B), followed by evaluations of communication style characteristics through metric instruments.', 'interventionNames': ['Other: Large Language Model']}], 'interventions': [{'name': 'Large Language Model', 'type': 'OTHER', 'description': 'An artificial intelligence system generating clinical recommendations using prompts, designed to simulate clinical advisory outputs. The protocol focuses on structured medical language generation.', 'armGroupLabels': ['intervention group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100084', 'city': 'Beijing', 'state': 'Beijing Municipality', 'country': 'China', 'contacts': [{'name': 'Yixiao Jin', 'role': 'CONTACT', 'email': 'jin-yx24@mails.tsinghua.edu.cn', 'phone': '+86 17721026692'}], 'facility': 'Tsinghua University', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}, {'zip': '214065', 'city': 'Wuxi', 'state': 'Jiangsu', 'country': 'China', 'contacts': [{'name': 'Jing Gu', 'role': 'CONTACT', 'email': 'g950324@163.com', 'phone': '86+(510)82335104'}], 'facility': 'Shanghai Health and Medical Center', 'geoPoint': {'lat': 31.56887, 'lon': 120.28857}}], 'centralContacts': [{'name': 'Yixiao Jin', 'role': 'CONTACT', 'email': 'jin-yx24@mails.tsinghua.edu.cn', 'phone': '+86 17721026692'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Tsinghua University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Vice-Provost and Senior Vice-Chancellor', 'investigatorFullName': 'Tien Yin Wong', 'investigatorAffiliation': 'Tsinghua University'}}}}