Ignite Creation Date:
2025-12-25 @ 5:02 AM
Ignite Modification Date:
2025-12-26 @ 4:03 AM
Study NCT ID:
NCT06962618
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-05-08
First Post:
2025-04-08
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Home-Based Training With Feedback to Improve Outcomes in Adolescents and Young Adults With Cerebral Palsy..
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002547', 'term': 'Cerebral Palsy'}], 'ancestors': [{'id': 'D001925', 'term': 'Brain Damage, Chronic'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'QUADRUPLE', 'whoMasked': ['PARTICIPANT', 'CARE_PROVIDER', 'INVESTIGATOR', 'OUTCOMES_ASSESSOR'], 'maskingDescription': 'Statistician'}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Superiority trial'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 70}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-12-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-04', 'completionDateStruct': {'date': '2029-02-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-04-29', 'studyFirstSubmitDate': '2025-04-08', 'studyFirstSubmitQcDate': '2025-04-29', 'lastUpdatePostDateStruct': {'date': '2025-05-08', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-05-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2028-12-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'The Canadian Occupational Performance Measure (Self-Rated Performance)', 'timeFrame': 'Before baseline (at the motor training program design), at 12 weeks (end of intervention), and at 24 weeks (long-term follow-up)', 'description': 'During a semi-structured interview, participants identify an activity they want, need, or are expected to perform and set one long-term goal. They then rate their performance of that activity on a 0-10 scale, where 0 = not able to perform the activity at all and 10 = able to perform it extremely well.\n\nUnit of Measure: Performance score (0-10 scale)'}, {'measure': 'The Canadian Occupational Performance Measure (Self-Rated Satisfaction)', 'timeFrame': 'Before baseline (at the motor training program design), at 12 weeks (end of intervention), and at 24 weeks (long-term follow-up)', 'description': 'In the same semi-structured interview, participants rate their satisfaction with their performance of the selected activity on a 0-10 scale, where 0 = not satisfied at all and 10 = extremely satisfied.\n\nUnit of Measure: Satisfaction score (0-10 scale)'}, {'measure': 'Change in time spent walking per day (as measured by IMUs)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Time spent walking will be measured using 3-axis accelerometer and gyroscope data collected from seven IMUs worn continuously for 72 hours. Data will be analyzed using a validated deep-learning neural network (Novosel et al., 2023) to classify walking behavior.\n\nUnit of Measure: Minutes per day'}, {'measure': 'Change in time spent standing per day (as measured by IMUs)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Standing time will be extracted from IMU data collected during 72 hours of wear. Signals will be analyzed via a validated deep-learning neural network (Novosel et al., 2023) Time Frame: Baseline, 12 weeks, and 24 weeks Unit of Measure: Minutes per day'}, {'measure': 'Change in time spent sitting per day (as measured by IMUs)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Sitting time will be recorded using IMUs worn on the sternum, wrists, thighs, and lower legs after 72 hours of wear and analysed with a validated deep-learning neural network (Novosel et al., 2023)\n\nUnit of Measure: Minutes per day'}, {'measure': 'Change in time spent lying down per day (as measured by IMUs)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Time spent lying will be measured using 3-axis accelerometer and gyroscope data collected from seven IMUs worn continuously for 72 hours. Data will be analyzed using a validated deep-learning neural network (Novosel et al., 2023) to classify walking behavior.\n\nUnit of Measure: Minutes per day'}, {'measure': 'Change in number of posture transitions per day (as measured by IMUs)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Posture transitions (e.g., sit-to-stand) will be identified from 72-hour IMU data using a validated deep-learning neural network (Novosel et al., 2023)\n\nUnit of Measure: Number of transitions per day'}, {'measure': 'Change in relative extremity usage ratio', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'The movement ratio between the trained and non-trained extremity will be calculated from IMU signals using using a validated deep-learning neural network (Novosel et al., 2023)\n\nUnit of Measure: Ratio (trained / non-trained limb)'}, {'measure': 'Adverse events', 'timeFrame': 'Through week 12 (baseline to end of intervention)', 'description': 'Adverse events include both serious (e.g. death, hospitalization) and non-serious adverse events (e.g. pain, fatigue).\n\nUnit of Measure: Number of events'}], 'primaryOutcomes': [{'measure': 'Percentage change in daytime movement of the trained extremity (right or left arm or leg) as measured by 3-axis accelerometer and gyroscope data analyzed via deep-learning neural network', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Movement data will be collected using seven Inertial Measurement Units (IMUs) worn continuously for 72 hours at three time points: baseline, 12 weeks (end of intervention), and 24 weeks (follow-up).\n\nIMUs will be attached to the sternum, wrists, thighs, and lower legs using adhesive patches and will capture 3-axis accelerometer and gyroscope data. A validated custom neural network (Novosel et al. 2023) will convert signals into images and analyze them using convolutional layers to extract features related to movement behaviors. The primary metric will be the percentage change (minutes a day) in real-world daytime movement of the trained limb, computed relative to baseline.\n\nThis outcome reflects changes in functional mobility resulting from the motor training intervention.'}], 'secondaryOutcomes': [{'measure': 'Number of daily logins to the tablet app', 'timeFrame': 'The app stores the data during the intervention period and will be collected at 12 weeks (end of intervention period)', 'description': 'Attendance will be measured as the number of times participants log into the tablet app during the intervention.\n\nUnit of Measure: Number of logins'}, {'measure': 'Daily session duration recorded in the tablet app', 'timeFrame': 'The app stores the data during the intervention period and will be collectedThe app stores the data during the intervention period and will be collected at 12 weeks (end of intervention period)', 'description': 'Adherence will be assessed by the average length of each daily training session. This outcome reflects how long participants remain engaged with the motor training program once they log in.\n\nUnit of Measure: Minutes'}, {'measure': 'Time spent moving the targeted extremity during training recorded in the tablet app', 'timeFrame': 'The app stores the data during the intervention period and will be collected The app stores the data during the intervention period and will be collected at 12 weeks (end of intervention period)', 'description': 'This measure reflects adherence by quantifying the active movement time of the trained extremity during each training session.\n\nUnit of Measure: Minutes'}, {'measure': 'Time spent within target movement intensity threshold recorded in the tablet app', 'timeFrame': 'The app stores the data during the intervention period and will be collected The app stores the data during the intervention period and will be collected at 12 weeks (end of intervention period)', 'description': 'For participants in the Music Motion Feedback group, adherence will also be evaluated by measuring the time spent at or above a predefined movement intensity threshold.\n\nUnit of Measure: Minutes'}, {'measure': 'Action Research Arm Test (ARAT) total score - (Upper Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'In participants engaged in upper extremity training, the ARAT will be used to evaluate upper extremity functional capacity. It consists of 19 items assessing grasp, grip, pinch, and gross movement. Scores range from 0 to 57, with higher scores indicating better arm function.\n\nTime Frame: Baseline, 12 weeks (end of intervention), and 24 weeks (follow-up) Unit of Measure: ARAT total score (0-57)'}, {'measure': 'Maximum isometric arm strength - (Upper Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Participants engaged in upper extremity training will have the isometric strength of the targeted upper extremity measured using a handheld dynamometer. They will perform maximum voluntary contractions against resistance, and the peak force will be recorded.\n\nUnit of Measure: Kilograms of force (kgf)'}, {'measure': 'Maximum grip strength - (Upper Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'Participants who are engaged in upper extremity training will have their grip strength of the targeted upper limb measured using a hand dynamometer. The highest of three attempts will be recorded.\n\nUnit of Measure: Kilograms of force (kgf)'}, {'measure': 'Gross Motor Function Measure-66 (GMFM-66) total score - (Lower Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'In participants who are engaged in lower extremity training the GMFM-66 will be used to assess gross motor function. It evaluates activities such as standing, walking, and running. Scores range from 0 to 100, with higher scores indicating better function.\n\nUnit of Measure: GMFM-66 total score (0-100)'}, {'measure': 'Maximum isometric leg strength - (Lower Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'The isometric strength of the trained leg will be assessed using a handheld dynamometer. Participants will perform maximum voluntary contractions, and peak force will be recorded.\n\nUnit of Measure: Kilograms of force (kgf)'}, {'measure': 'Distance walked during the Six-Minute Walk Test (6MWT) - (Lower Extremity)', 'timeFrame': 'Baseline, at 12 weeks (end of intervention period), and at 24 weeks (long term follow up)', 'description': 'The 6MWT will be used to evaluate walking endurance and aerobic capacity. Participants engaged in lower extremity training will walk as far as possible in six minutes along a flat, indoor course.\n\nTime Frame: Baseline, 12 weeks, and 24 weeks Unit of Measure: Meters walked'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['cerebral palsy', 'Home-based training', 'Extrinsic feedback', 'Movement behavior', 'Motor learning'], 'conditions': ['Cerebral Palsy']}, 'descriptionModule': {'briefSummary': 'This clinical trial aims to determine whether extrinsic feedback through music enhances the effects of home-based motor training for adolescents and young adults with cerebral palsy (CP) and whether feedback improves adherence to the training program.\n\nThe main questions it aims to answer are:\n\n* Does extrinsic feedback improve real-world movement more than home training alone?\n* Do participants receiving extrinsic feedback adhere more closely to their training program?\n\nTo determine its effectiveness, the investigators will compare home-based training with and without real-time music feedback.\n\nParticipants will:\n\n* Engage in a home-based motor training program for 12 weeks, tailored to their individual needs and goals.\n* Receive real-time music feedback during training or no feedback (control group).\n* Attend weekly virtual coaching sessions to discuss short-term goals and training progress.\n* Undergo movement assessments before training, at 12 weeks (T2) and 24 weeks (T3).\n* Wear movement sensors for 72 hours at T2 and T3 to track real-world movement behavior.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT'], 'maximumAge': '25 Years', 'minimumAge': '15 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Clinical diagnosis of cerebral palsy\n* Sensorimotor deficits in at least one limb\n* Demonstrated motivation to develop or regain motor skills, indicated by the expression of specific goals\n* Ability to follow instructions independently or with caregiver support\n* Ability to provide informed consent\n\nExclusion Criteria:\n\n* Diagnosis of dyskinetic cerebral palsy\n* Presence of significant health risks that could interfere with participation\n* Surgery or first Botox injection within one month before the trial or during the trial period'}, 'identificationModule': {'nctId': 'NCT06962618', 'acronym': 'THRIVE-CP', 'briefTitle': 'Home-Based Training With Feedback to Improve Outcomes in Adolescents and Young Adults With Cerebral Palsy..', 'organization': {'class': 'OTHER', 'fullName': 'University of Copenhagen'}, 'officialTitle': 'The THRIVE-CP Trial - Targeted Home-Based Training With Real-Time Feedback to Improve Versatile Movement Behaviors and Enhance Outcomes in Adolescents and Young Adults With Cerebral Palsy: Protocol for a Randomized Controlled Trial.', 'orgStudyIdInfo': {'id': 'THRIVE-CP'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Music Motion Group', 'interventionNames': ['Behavioral: Music Motion Group']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Control', 'interventionNames': ['Behavioral: Control']}], 'interventions': [{'name': 'Music Motion Group', 'type': 'BEHAVIORAL', 'description': 'Participants will engage in personalized, home-based motor training programs tailored to their individual goals. Each will wear a wireless Inertial Measurement Unit (IMU) on the targeted body part, which transmits movement data via Bluetooth to a tablet app. The training emphasizes task specificity and intensity, with five virtual check-ins to review progress and adjust training parameters.\n\nThe intervention studied is extrinsic feedback; the app analyzes movement data and provides feedback through music. Before each training session, the app guides participants to set personalized intensity thresholds based on current capacity. When participants meet the intensity threshold, musical elements (e.g., drumbeats, vocals) play. If they fall short, elements drop out, providing knowledge of erroneous performance.', 'armGroupLabels': ['Music Motion Group']}, {'name': 'Control', 'type': 'BEHAVIORAL', 'description': 'Participants will follow personalized, home-based motor training programs designed like the Music motion group. They will wear a wireless Inertial Measurement Unit (IMU) on the targeted body part, transmitting movement data via Bluetooth to a tablet app. However, unlike the Music Motion Feedback group, participants in the Control group will not receive any extrinsic feedback during their training.', 'armGroupLabels': ['Control']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Copenhagen', 'country': 'Denmark', 'contacts': [{'name': 'Jakob Lorentzen, Professor', 'role': 'CONTACT', 'email': 'jlorentzen@sund.ku.dk'}], 'facility': 'CP Youth Clinic, Copenhagen University Hospital - Rigshospitalet', 'geoPoint': {'lat': 55.67594, 'lon': 12.56553}}], 'centralContacts': [{'name': 'Ivana B Novosel, PhD student', 'role': 'CONTACT', 'email': 'ivana.novosel@sund.ku.dk', 'phone': '27328961', 'phoneExt': '+45'}, {'name': 'Jakob Lorentzen, Professor', 'role': 'CONTACT', 'email': 'j.lorentzen@sund.ku.dk', 'phone': '+4531521131'}], 'overallOfficials': [{'name': 'Jakob Lorentzen, Professor', 'role': 'STUDY_DIRECTOR', 'affiliation': 'University of Copenhagen and University Hospital Copenhagen, Denmark'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Copenhagen', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Ivana Bardino Novosel', 'investigatorAffiliation': 'University of Copenhagen'}}}}