[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100652057":3},{"organization":4,"armGroups":7,"interventions":25,"overallOfficials":37,"centralContacts":42,"locations":30,"responsibleParty":48,"collaborators":30,"id":51,"slug":52,"hasResults":53,"nctId":54,"briefTitle":55,"officialTitle":56,"acronym":57,"eligibilityCriteria":58,"healthyVolunteers":59,"sex":60,"minAge":61,"maxAge":30,"enrollmentInfo":62,"targetDuration":30,"studyType":65,"phases":66,"briefSummary":68,"conditions":69,"keywords":72,"overallStatus":83,"whyStopped":30,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":88,"completionDateStruct":90,"leadSponsor":92,"locationsCount":30},{"fullName":5,"class":6},"Zhejiang University","OTHER",[8,14,20],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-Supported Personalized Feedback","EXPERIMENTAL","Participants will receive standardized Tuina instruction and practice using a mechanical simulation model equipped with a pressure-sensing system. After each practice attempt, participants will receive objective sensor measurements and personalized, actionable feedback generated by a generative AI system under instructor supervision.",[13],"Behavioral: AI-Supported Personalized Feedback",{"label":15,"type":16,"description":17,"interventionNames":18},"Sensor-Based Data Feedback","ACTIVE_COMPARATOR","Participants will receive the same standardized Tuina instruction, practice tasks, number of practice opportunities, and training duration as the experimental group. After each practice attempt, participants will receive sensor-generated numerical measurements, performance curves, and target ranges, without AI-generated interpretation or personalized recommendations.",[19],"Behavioral: Sensor-Based Data Feedback",{"label":21,"type":16,"description":22,"interventionNames":23},"Traditional Instructor Feedback","Participants will receive the same standardized Tuina instruction, practice tasks, number of practice opportunities, and training duration as the other groups. Feedback will be provided through conventional instructor observation and verbal guidance. Participants will not view sensor-generated performance data or AI-generated recommendations.",[24],"Behavioral: Traditional Instructor Feedback",[26,31,34],{"type":27,"name":9,"description":28,"armGroupLabels":29,"otherNames":30},"BEHAVIORAL","Participants will complete four standardized training sessions over two weeks, with each session lasting approximately 45 to 60 minutes. A pressure-sensing system will measure force accuracy, force variability, operating frequency, rhythm stability, and time within the target range. After each practice attempt, a generative AI system will provide feedback using a structured task-gap-action format. The feedback will describe the target task, identify differences between measured performance and the predefined standard, and recommend specific actions for the next practice attempt. AI output will be restricted to educational use and overseen by instructors.",[9],null,{"type":27,"name":15,"description":32,"armGroupLabels":33,"otherNames":30},"Participants will complete four standardized training sessions over two weeks, with each session lasting approximately 45 to 60 minutes. After each practice attempt, participants will view numerical sensor measurements, force-time curves, rhythm information, and predefined target ranges. No generative AI interpretation, personalized action plan, or AI-generated recommendation will be provided.",[15],{"type":27,"name":21,"description":35,"armGroupLabels":36,"otherNames":30},"Participants will complete four standardized training sessions over two weeks, with each session lasting approximately 45 to 60 minutes. Instructors will observe performance and provide conventional verbal feedback based on the standardized teaching protocol. Participants will not receive sensor-derived performance displays or AI-generated feedback.",[21],[38],{"name":39,"affiliation":40,"role":41},"Xing-Chen Zhou","The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Shangcheng District, Hangzhou, Zhejiang","PRINCIPAL_INVESTIGATOR",[43],{"name":44,"role":45,"phone":46,"phoneExt":30,"email":47},"Xing-Chen Zhou, Ph.D.","CONTACT","+86-18370133761","zhouxingchen0210@163.com",{"type":41,"investigatorFullName":39,"investigatorTitle":49,"investigatorAffiliation":50,"oldNameTitle":30,"oldOrganization":30},"Prof.","First Affiliated Hospital of Zhejiang University","100652057","ai-assisted-feedback-for-learning-standardized-tuina-skills-100652057",false,"NCT07767916","AI-Assisted Feedback for Learning Standardized Tuina Skills","Effects of Sensor- and Generative AI-Supported Personalized Feedback on the Acquisition of Standardized Tuina Skills Among Rehabilitation Trainees: A Randomized Controlled Trial","AI-TUINA","Inclusion Criteria:\n\n* Aged 18 years or older.\n* Currently enrolled in or receiving training in rehabilitation medicine, physical therapy, rehabilitation therapy, or a related health profession.\n* Has not previously achieved the predefined competency standard for the standardized Tuina skill evaluated in this study.\n* Able to understand the study instructions and independently complete the training tasks and study questionnaires.\n* Able and willing to attend all scheduled training sessions and the four-week follow-up assessment.\n* Willing to participate voluntarily and provide written informed consent.\n\nExclusion Criteria:\n\n* Current acute injury, clinically significant pain, or functional limitation involving the hand, wrist, upper limb, shoulder, neck, or lower back that may interfere with repeated manual skill practice.\n* Previous systematic training in the same standardized Tuina technique with performance at or above the predefined competency standard.\n* Any medical, physical, cognitive, or psychological condition that, in the investigator's judgment, may make participation unsafe or prevent valid completion of the study procedures.\n* Unable to understand the study procedures or provide informed consent.\n* Direct involvement in the design, randomization, intervention delivery, outcome assessment, data management, or statistical analysis of this study.\n* Concurrent participation in another training study that may substantially affect performance of the standardized Tuina skill.",true,"ALL","18 Years",{"count":63,"type":64},81,"ESTIMATED","INTERVENTIONAL",[67],"NA","The goal of this educational study is to determine whether personalized feedback generated using sensor data and generative artificial intelligence (AI) can improve the learning of standardized Tuina skills among rehabilitation trainees. Tuina is a form of manual therapy that requires learners to control the location, force, rhythm, and consistency of their hand movements.\n\nA total of 81 rehabilitation trainees will be randomly assigned to one of three training groups: AI-supported personalized feedback, sensor-based data feedback without AI-generated recommendations, or traditional instructor feedback. All groups will receive the same standardized demonstration, training tasks, practice duration, and number of practice sessions.\n\nThe main question is whether trainees receiving AI-supported personalized feedback achieve better retention of standardized Tuina skills four weeks after training. The researchers will also compare immediate skill performance, force and rhythm control, transfer of skills to a related task, learning efficiency, self-efficacy, cognitive load, satisfaction, and the safety and acceptability of AI-generated feedback.\n\nSkill performance will be assessed using a blinded Objective Structured Clinical Examination (OSCE) and objective sensor-based measurements. The study activities will be conducted using a mechanical simulation model and a pressure-sensing system, rather than on patients.",[70,71],"Medical Education","Clinical Skills",[73,74,75,76,77,78,79,80,81,82],"Artificial Intelligence","Generative Artificial Intelligence","Rehabilitation Education","Health Professions Education","Tuina","Manual Therapy Skills","Sensor-Based Feedback","Personalized Feedback","Deliberate Practice","Objective Structured Clinical Examination","NOT_YET_RECRUITING","2026-08-12",{"date":86,"type":87},"2026-08-17","ACTUAL",{"date":89,"type":64},"2026-08-13",{"date":91,"type":64},"2028-08-01",{"name":5,"class":6}]