[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100591284":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":10,"centralContacts":26,"locations":32,"responsibleParty":45,"collaborators":10,"id":49,"slug":50,"hasResults":51,"nctId":52,"briefTitle":53,"officialTitle":54,"acronym":10,"eligibilityCriteria":55,"healthyVolunteers":56,"sex":57,"minAge":58,"maxAge":59,"enrollmentInfo":60,"targetDuration":10,"studyType":63,"phases":10,"briefSummary":64,"conditions":65,"keywords":10,"overallStatus":35,"whyStopped":10,"lastUpdateSubmitDate":67,"lastUpdatePostDateStruct":68,"startDateStruct":71,"completionDateStruct":73,"leadSponsor":75,"locationsCount":76},{"fullName":5,"class":6},"Ahram Canadian University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Pain Group",null,"Professional e-sports athletes reporting wrist pain ≥3\u002F10 on VAS during play",[13],"Other: Pain Group",{"label":15,"type":10,"description":16,"interventionNames":17},"No-Pain Group","Professional e-sports athletes reporting minimal to no wrist pain (\\\u003C3\u002F10 on VAS during play)",[18],"Other: No-Pain Group",[20,23],{"type":6,"name":9,"description":21,"armGroupLabels":22,"otherNames":10},"Professional e-sports athletes who report wrist pain rated at 3 or higher on a 10-point Visual Analog Scale during gaming activities. These participants play video games professionally for at least 35 hours per week, are between 18-30 years old, and have no history of neurologic or rheumatic disease.",[9],{"type":6,"name":15,"description":24,"armGroupLabels":25,"otherNames":10},"Professional e-sports athletes who report minimal to no wrist pain (less than 3 on a 10-point Visual Analog Scale) during gaming activities. These participants play video games professionally for at least 35 hours per week, are between 18-30 years old, and have no history of neurologic or rheumatic disease.",[15],[27],{"name":28,"role":29,"phone":30,"phoneExt":10,"email":31},"Mohamed M ElMeligie, Ph.D","CONTACT","01159880001","mohamed.elmeligie@acu.edu.eg",[33],{"facility":34,"status":35,"city":36,"state":37,"zip":38,"country":39,"countryCode":40,"cosmosGeoPoint":10,"geoPoint":10,"contacts":41},"Outpatient clinic of faculty of physical therapy, Ahram Canadian University","RECRUITING","Al Ḩayy Ath Thāmin","Giza Governorate","3221405","Egypt","EG",[42],{"name":43,"role":29,"phone":44,"phoneExt":10,"email":31},"Mohamed M ElMeligie, Ph.d","01064442032",{"type":46,"investigatorFullName":47,"investigatorTitle":48,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Mohamed Magdy ElMeligie","Lecturer of Physical Therapy","100591284","hand-held-dynamometer-assessment-e-sports-grip-asymmetry-index-as-a-predictor-of-wrist-pain-100591284",false,"NCT06978426","Hand-Held Dynamometer Assessment: E-Sports Grip-Asymmetry Index as a Predictor of Wrist Pain","Evaluation of Grip Strength Asymmetry Index in Professional E-Sports Athletes as a Predictive Measure for Wrist Pain","Inclusion Criteria:\n\n* Professional e-sports athletes (receiving compensation for gaming activities)\n* Age between 18 and 30 years\n* Gaming for at least 35 hours per week\n* For Pain Group: Reports wrist pain rated ≥3\u002F10 on VAS during gaming activities\n* For No-Pain Group: Reports minimal to no wrist pain (\\\u003C3\u002F10 on VAS) during gaming activities\n\nExclusion Criteria:\n\n* History of neurologic disease\n* History of rheumatic disease\n* Previous wrist surgery\n* Recent wrist trauma (within 3 months)\n* Use of pain medication within 24 hours of assessment\n* Inability to perform grip strength testing",true,"ALL","18 Years","30 Years",{"count":61,"type":62},56,"ESTIMATED","OBSERVATIONAL","This cross-sectional study investigates whether a simple Grip-Asymmetry Index (GAI) can predict self-reported wrist pain in professional e-sports athletes. Professional gamers (aged 18-30) who play at least 35 hours per week will be assessed using a Jamar dynamometer to measure maximal grip force in both hands. The study will compare GAI between two groups: those with wrist pain (≥3\u002F10 on Visual Analog Scale during play) and those without pain. A GAI cutoff value for predicting wrist pain risk will be established through ROC analysis, with additional factors such as gaming hours, BMI, and sex incorporated into a multivariable logistic regression model.",[66],"Wrist Injuries","2025-05-10",{"date":69,"type":70},"2025-05-18","ACTUAL",{"date":72,"type":62},"2025-06-01",{"date":74,"type":62},"2025-12-01",{"name":5,"class":6},1]