Ignite Creation Date:
2026-03-26 @ 3:16 PM
Ignite Modification Date:
2026-03-30 @ 8:42 PM
Study NCT ID:
NCT07418632
Status:
RECRUITING
Last Update Posted:
2026-02-18
First Post:
2025-08-10
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Kinematic Training in Patients With Neck Pain Based on Machine Learning Classification Approach
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NON_RANDOMIZED', 'maskingInfo': {'masking': 'DOUBLE', 'whoMasked': ['PARTICIPANT', 'INVESTIGATOR']}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 38}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2026-03-18', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-02', 'completionDateStruct': {'date': '2026-09-20', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-02-13', 'studyFirstSubmitDate': '2025-08-10', 'studyFirstSubmitQcDate': '2026-02-13', 'lastUpdatePostDateStruct': {'date': '2026-02-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-02-18', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-06-20', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': '16 VSP (16 item visual symptoms proforma)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': 'Visual Disturbances - 16-Item Proforma\n\nSubjective visual disturbances will be assessed using a 16-item proforma designed to evaluate visual symptoms commonly reported in individuals with neck pain.\n\nThe items include: blurred vision, words or objects moving on the page, need to concentrate to read, difficulty judging distance, heavy eyes, sore eyes, red eyes, eye strain, visual fatigue, itchy eyes, squinting, difficulty focusing on close work, double vision, spots before the eyes, sensitivity to light, and dizziness when reading.\n\nFor each symptom, participants rate:\n\n* Intensity on a 3-point scale (1 = mild, 2 = moderate, 3 = severe)\n* Frequency on a 4-point scale (1 = rare, 2 = occasional, 3 = frequent, 4 = always)\n\nIf a symptom is absent, it is scored as 0 (not present).\n\nHigher scores indicate greater severity and/or frequency of visual disturbance.'}], 'primaryOutcomes': [{'measure': 'Vas score (Visual analogue scale - pain intensity level)', 'timeFrame': 'Start of the study, after 4 week training period and after 3 months follow up period', 'description': 'The Visual Analogue Scale (VAS) is a patient-reported measure of pain intensity. Participants rate their current neck pain on a 10-cm horizontal line anchored by:\n\n* 0 = no pain (best outcome)\n* 10 = worst imaginable pain (worst outcome)\n\nThe score is determined by measuring the distance (in centimeters or millimeters) from the "no pain" anchor to the participant\'s mark. Total scores therefore range from 0 to 10 (or 0-100 mm), with higher scores indicating greater pain intensity.\n\nA decrease in VAS score over time indicates improvement, while an increase indicates worsening pain. For responder analyses, a clinically meaningful improvement is defined as a reduction of at least 2 points (or 20 mm) from baseline.'}, {'measure': 'NDI score', 'timeFrame': 'Start of the study, after 4 week training period and after 3 months follow up period', 'description': 'The Neck Disability Index is a patient-reported questionnaire assessing how neck pain affects daily activities. It includes 10 items (pain intensity, personal care, lifting, reading, headaches, concentration, work, driving, sleeping, and recreation). Each item is scored from 0 to 5, where:\n\n* 0 indicates no pain or no functional limitation (best outcome)\n* 5 indicates maximum pain or complete functional limitation (worst outcome)\n\nThe total score ranges from 0 to 50, with:\n\n* 0 = no neck-related disability (best possible score)\n* 50 = maximum disability (worst possible score)\n\nFor reporting purposes, the total score may also be expressed as a percentage from 0% (no disability) to 100% (complete disability).\n\nA decrease in score over time indicates improvement, while an increase indicates worsening disability.\n\nFor analyses using a responder threshold, participants are considered to have achieved a clinically meaningful improvement if their total NDI score decreases by at least 5 points (on'}], 'secondaryOutcomes': [{'measure': 'Precision time (in movement control test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': 'Precision Time is an objective outcome derived from the cervical movement control tests, a computerized cervical movement control task. Participants control a visual cursor using head or neck movements and are instructed to keep the cursor aligned with a moving or stationary on-screen target.\n\nPrecision Time is expressed as the percentage of total trial time during which the cursor remains within a predefined target zone. Scores range from 0% (cursor never within the target; worst performance) to 100% (cursor within the target for the entire trial; best performance).\n\nHigher Precision Time values indicate better cervical sensorimotor control and movement accuracy. An increase in Precision Time across assessments reflects improvement.'}, {'measure': 'Underreaching (in movement control test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': 'Underreaching (undershoot) is an objective performance metric derived from a computerized cervical movement control test. During the test, participants use head or neck movements to guide a visual cursor toward a target displayed on a screen.\n\nUnderreaching represents the percentage of total trial time during which the cursor remains short of the target zone (i.e., does not reach the required amplitude or position). Scores range from 0% (no undershoot; best performance) to 100% (cursor consistently fails to reach the target; worst performance).\n\nHigher underreaching values indicate reduced movement amplitude control and impaired cervical sensorimotor accuracy. A decrease in underreaching across repeated assessments reflects improvement.'}, {'measure': 'Overreaching (movement control test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': 'Overshoot (overreaching) is an objective performance metric derived from a computerized cervical movement control test. During the test, participants use head or neck movements to guide a visual cursor toward a target displayed on a screen.\n\nOvershoot represents the percentage of total trial time during which the cursor exceeds the predefined target zone (i.e., moves beyond the required amplitude or position). Scores range from 0% (no overshoot; best performance) to 100% (cursor consistently exceeds the target zone; worst performance).\n\nHigher overshoot values indicate reduced movement precision and impaired control of movement amplitude. A decrease in overshoot across repeated assessments reflects improvement.'}, {'measure': 'Jerk index (in movement control test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': 'Jerk Index is an objective kinematic performance metric derived from a computerized cervical movement control test. During the test, participants use head or neck movements to guide a visual cursor toward a target displayed on a screen.\n\nThe Jerk Index quantifies movement smoothness by calculating the rate of change of acceleration (jerk) across the movement trajectory, normalized to trial duration and amplitude. Higher values reflect less smooth, more abrupt or irregular movements, whereas lower values indicate smoother and more controlled motion.\n\nScores range from 0 (perfectly smooth movement; best performance) upward, with no fixed upper limit; higher scores represent poorer movement control (worse performance). A decrease in Jerk Index across repeated assessments indicates improvement in cervical motor control.'}, {'measure': 'Absolute error (in head-to-neutral relocation test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': "Absolute Error is an objective performance metric derived from a computerized cervical movement control test. During the test, participants use head or neck movements to guide a visual cursor to a target displayed on a screen.\n\nAbsolute Error quantifies amplitude accuracy as the absolute difference between the required target position/amplitude and the participant's achieved cursor position/amplitude (averaged across the trial, repetition, or task segment as defined by the software).\n\nScores range from 0 (no error; best performance) upward, with no fixed upper limit. Lower Absolute Error indicates better accuracy, while higher values indicate poorer amplitude accuracy (worse performance). A decrease in Absolute Error across assessments reflects improvement."}, {'measure': 'Gain (smooth pursuit eye movement test)', 'timeFrame': 'At start, after 4 week intervention and at 3 month follow-up period.', 'description': "Gain is an objective oculomotor performance metric derived from a smooth pursuit eye movement test. During the test, the participant's head is stabilized in a predefined neutral position, and the participant follows a continuously moving on-screen target using focal vision only.\n\nGain is calculated as the ratio of eye movement velocity to target velocity (eye velocity ÷ target velocity), typically averaged across the tracking interval. A value of 1.0 indicates perfect pursuit accuracy (eye velocity matches target velocity).\n\nValues \\>1.0 indicate excessive eye velocity. The optimal value is 1.0 (best performance). Negative deviations from 1.0 reflect impaired smooth pursuit control, consistent with reports of altered oculomotor function in individuals with neck pain. Improvement is defined as gain values moving closer to 1.0 across assessments."}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Chronic Neck Pain']}, 'descriptionModule': {'briefSummary': "The goal of this clinical trial is to study if kinematic training based on novel kinematic assessment clasification approach can decrease chronic neck pain and prevent its reoccurance better than conventional kinematic training in adults. The main question\\[s\\] it aims to answer \\[is/are\\]:\n\nDoes clustering patients with neck pain based on head and neck movement characteristics lead to more efficient kinematic rehabilitation training and improved clinical outcomes\n\nResearchers will compare effects of cluster specific kinematic training to see if it effects pain levels and its reoccurance.\n\nParticipants will \\[describe the main tasks participants will be asked to do, interventions they'll be given and use bullets if it is more than 2 items\\].", 'detailedDescription': 'Chronic idiopathic neck pain represents one of the most prevalent musculoskeletal conditions worldwide and is characterized by recurrent episodes, fluctuating symptom intensity, and frequent transition to persistent disability. While clinical management commonly focuses on short-term pain reduction, the more substantial societal burden arises from recurrence and chronicity rather than isolated acute episodes. Recurrent neck pain contributes to repeated healthcare consultations, prolonged work absenteeism, reduced productivity, and increasing healthcare expenditure. Despite the widespread use of exercise-based rehabilitation, recurrence rates remain high, suggesting that prevailing treatment approaches may insufficiently address the mechanisms underlying persistent dysfunction. As the prevalence of neck pain continues to rise across working-age populations, it is reasonable to question whether current rehabilitation models adequately target the neuromuscular and sensorimotor contributors to chronicity and repeated symptom exacerbations.\n\nMost individuals presenting for physical therapy are diagnosed with non-specific or idiopathic neck pain, a broad category encompassing heterogeneous clinical presentations with variable combinations of pain, stiffness, dizziness, visual disturbances, and impaired movement control. Patients may differ substantially in movement strategies, proprioceptive acuity, neuromuscular coordination, and adaptive motor patterns, yet they are frequently managed using standardized exercise protocols. Conventional clinical assessment tools are effective in distinguishing patients from asymptomatic individuals but provide limited resolution for identifying meaningful subgroups within the idiopathic neck pain population. Over the last decade, patient-centered evaluation in spinal disorders has frequently relied on numerical pain rating scales and disability questionnaires, while comparatively less emphasis has been placed on objective assessment of neuromuscular control mechanisms that may drive chronicity. Emerging evidence demonstrates that individuals with a history of neck pain exhibit persistent alterations in sensorimotor function even during symptom remission, implying that underlying neuromuscular adaptations may predispose individuals to recurrence and reduced resilience to mechanical or psychosocial stressors.\n\nCervical sensorimotor control, often conceptualized as cervicocephalic kinaesthetic awareness, integrates proprioceptive input from cervical musculature and joint mechanoreceptors with visual and vestibular information to coordinate accurate head positioning and smooth eye-head movements. Altered cervical afferent input can disrupt this integration, leading to inaccurate movement perception, impaired position sense, and maladaptive motor output strategies. Prolonged proprioceptive disturbances may induce central neural plasticity changes within brainstem and cortical sensorimotor networks, potentially sustaining dysfunction beyond the initial pain episode and contributing to the maintenance of chronic symptoms. Systematic reviews report variable findings regarding the magnitude of kinaesthetic impairments in neck pain populations, likely reflecting recruitment heterogeneity, differences in symptom duration, and variability in functional deficits. These inconsistencies underscore the importance of multidimensional characterization of sensorimotor performance rather than reliance on isolated parameters or single test outcomes.\n\nKinaesthetic training targeting movement accuracy, proprioceptive recalibration, and coordinated motor output has demonstrated clinically meaningful short-term improvements in pain and disability, with some effects persisting for several months. However, approximately one third of patients fail to demonstrate improvement in pain intensity or disability, and nearly half do not exhibit measurable gains in objective kinematic performance variables. Additionally, dropout rates of up to twenty percent have been reported, frequently attributed to discomfort, fatigue, or symptom aggravation during exercises that challenge impaired sensorimotor systems. These observations suggest that uniform rehabilitation protocols may not optimally address individualized neuromuscular profiles and that subgroup-specific interventions may enhance treatment responsiveness, improve adherence, and reduce variability in outcomes.\n\nCervical movement control involves coordinated interaction between proprioceptive, vestibular, and visual systems. Movement tasks performed at varying amplitudes and velocities challenge different components of sensorimotor processing and may reveal distinct deficit patterns. Slow, large-amplitude movements increase reliance on proprioceptive discrimination and smoothness regulation, often reflected in elevated jerk index values when coordination is impaired. Faster movements may engage vestibular-dependent mechanisms and dynamic stability control. Furthermore, altered afferent input from cervical muscles can influence adaptive plastic changes in vestibular-dependent motion sensitivity, potentially affecting head and neck control at higher movement velocities. Consequently, assessment and training should incorporate movements across multiple amplitudes and velocities to adequately capture subgroup-specific impairments.\n\nHead and neck movement control tests frequently require participants to track visually presented targets while performing controlled movements, thereby demanding coordinated eye and head interaction. The importance of the visual system in neck pain is supported by neurophysiological connections between upper cervical afferent pathways and visual and vestibular nuclei at the brainstem level. Patients with neck pain frequently present with oculomotor disturbances, particularly during neck torsion maneuvers, likely arising from altered cervico-ocular and cervico-collic reflex contributions. Previous work has suggested associations between cervical kinaesthetic deficits and eye movement control, yet it remains unclear to what extent targeted kinaesthetic training can modify these oculomotor adaptations and whether such changes parallel improvements in pain and functional status.\n\nTraditional analytical strategies commonly evaluate individual kinematic parameters independently, potentially overlooking complex interactions among movement precision, amplitude regulation, and smoothness. High-dimensional datasets generated from movement control testing contain non-linear relationships that may not be adequately captured using conventional univariate statistical methods. Data mining and machine learning approaches enable identification of latent structure within multidimensional datasets and facilitate clustering of patients according to shared functional characteristics. Prior analyses conducted on a cohort of 135 individuals with idiopathic neck pain identified four distinct clusters based on combinations of movement control variables, pain intensity, and demographic characteristics. These clusters demonstrated unique kinematic profiles, supporting the existence of clinically meaningful heterogeneity within this population and suggesting that targeted therapeutic strategies may be warranted.\n\nThe present study applies a classification-based rehabilitation framework derived from these previous clustering findings. Cervical kinaesthetic function will be comprehensively assessed using movement control testing and head-to-neutral relocation testing, supplemented by demographic and clinical variables including pain intensity. Participants will be assigned to previously defined clusters using established classification algorithms that integrate multidimensional movement and demographic data. Following classification, participants will receive either cluster-specific kinematic training designed to target the predominant impairments characteristic of their subgroup or a general kinematic training program not tailored to cluster membership. The structure, frequency, and duration of training exposure will be comparable between groups to ensure that differences in outcome are attributable to content rather than dose. Three-month follow-up measurements will be conducted to evaluate the persistence of intervention effects and to explore whether individualized rehabilitation influences medium-term symptom stability.\n\nMovement control assessment will involve visually guided head tracking tasks performed with inertial measurement units capturing high-resolution angular displacement data in real time. Participants will complete repeated trials across four progressively challenging movement paths characterized by increasing target amplitude and velocity to systematically stress different components of the sensorimotor system. Derived parameters will include precision time, representing percentage of trial time within the target zone; underreaching and overreaching, representing directional amplitude control errors; jerk index, reflecting smoothness of movement derived from the third derivative of position data; and amplitude accuracy, calculated as the average angular mismatch between target and performed movement. Position sense will be evaluated through blindfolded relocation to a self-selected neutral head position, with absolute error computed across repetitions and movement directions to quantify repositioning accuracy. Oculomotor control will be assessed using smooth pursuit testing in neutral and torsion positions, with eye movement recordings filtered for artifacts, synchronized with reference trajectories, and analyzed to compute pursuit gain as the ratio of eye velocity amplitude to target velocity amplitude. Cervical range of motion will be quantified in all primary movement planes to characterize mobility profiles and potential mobility-related subgroup distinctions.\n\nData processing will involve systematic filtering of motion and eye movement signals, removal of blinks and saccades where appropriate, synchronization of reference trajectories, normalization of movement cycles, and averaging across repetitions to ensure stable parameter estimation. Statistical analyses will be performed using repeated-measures analysis of variance to evaluate time-by-group interactions across baseline, post-intervention, and follow-up assessments. Normality assumptions will be examined using distributional metrics, and data transformations will be applied when required to satisfy model assumptions. Machine learning procedures for cluster assignment will be conducted using dedicated data mining software, while inferential statistical analyses will be executed using established statistical packages. Effect sizes will be interpreted alongside statistical significance to contextualize clinical relevance.\n\nBy integrating multidimensional kinematic profiling with subgroup-specific rehabilitation strategies, this study seeks to determine whether classification-based training improves clinical outcomes, enhances neuromuscular adaptation, and reduces variability in treatment response compared with conventional non-individualized kinematic rehabilitation. In addition, the study aims to clarify mechanistic relationships between improvements in cervical sensorimotor control and changes in pain intensity, disability, dizziness, visual symptoms, and oculomotor function. The findings are expected to contribute to development of personalized, mechanism-based rehabilitation models aimed at reducing recurrence, limiting chronicity, and improving long-term functional outcomes in individuals with idiopathic neck pain.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '65 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* presence of neck pain\n* pain level minimum 3 of 10 on VAS\n* did not receive conventional physiotherapy in last 6 months\n\nExclusion Criteria:\n\n* any upper extremity pain within last 2 years\n* any neurological or vestibular dissorders\n* type 2 diabetes\n* diagnosed psychiatric dissorders\n* medication or alcohol consumptin in last 30 hours'}, 'identificationModule': {'nctId': 'NCT07418632', 'briefTitle': 'Kinematic Training in Patients With Neck Pain Based on Machine Learning Classification Approach', 'organization': {'class': 'OTHER', 'fullName': 'University of Ljubljana'}, 'officialTitle': 'What is the Ability of Datamining Approaches to Cluster Patients With Idiopathic Neck Pain and Can Machine Learning Algorithms Provide More Efficient Rehabilitation and Less Recurrence Based on Kinaesthetic Training Protocols', 'orgStudyIdInfo': {'id': '0120-48/2023/8'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Patietns with smallest movement deficits', 'description': 'A group that in kinematic movement assessment presents with most time and closest to the target, with lowest overeaching and low unereaching. This group presents with mild to moderate pain levels.\n\nKinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with changing velocities, amplitudes and changes of direction without specific range of motion limits. The listed parameters are increased when the average session accuracy reaches 60% time-on-target.\n\nPatients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'interventionNames': ['Other: Smallest movement deficit training protocol']}, {'type': 'EXPERIMENTAL', 'label': 'Patients with smaller movement deficits', 'description': 'This group stays considerable amount of time and close to the target, has high underreaching at medium and difficult level and smallest overreaching at all difficulty levels; presents with mild to moderate pain levels.\n\nKinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with randomly changing velocities, in a predefined movement directions. The listed parameters are increased when the average session accuracy reaches 60% time-on-target. When 60% time-on-target is reached at the difficult level, random moveemnt directions are introduced. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'interventionNames': ['Other: Smaller movement deficit training protocol']}, {'type': 'EXPERIMENTAL', 'label': 'Patients with lerger movement deficits', 'description': 'This gorup stays less time and further away from the target, with high underreaching, most prominent feature is high overreaching; presents with mild to moderate pain levels.\n\nKinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with constant velocities, amplitudes with no changes of direction and with range of motion limits relative to the pain onset. The listed parameters are increased when the average session accuracy reaches 60% time-on-target. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'interventionNames': ['Other: Larger movement deficit training group']}, {'type': 'EXPERIMENTAL', 'label': 'Patients with largest movement deficits', 'description': 'This gorup stays least time and furthest away from the target, with highest undershoot (all difficulty levels, with significantly affected performance already at easy level) and overshoot; presents with moderate to severe pain levels', 'interventionNames': ['Other: Largest movement deficit training protocol']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Control group of patinets with neck pain', 'description': 'Group of patients with neck pain consisting equally from all four cluster groups.', 'interventionNames': ['Other: Control group intervention protocol']}], 'interventions': [{'name': 'Smallest movement deficit training protocol', 'type': 'OTHER', 'description': 'Kinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with changing velocities (ranges of difficulty levels from 0,5 to 3, 3 to 5, and 4 to 7 deg/s), amplitudes (40 to 90% ROM), and changes of direction/movements (combination of single and mixed axis of movement - flexion/extension and lef or right rotations). The listed parameters are increased when the average accuracy of two following training sessions reaches 60% time-on-target. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'armGroupLabels': ['Patietns with smallest movement deficits']}, {'name': 'Smaller movement deficit training protocol', 'type': 'OTHER', 'description': 'Kinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with the task to catch the moving target (always starting 2-15 deg in front of the starting position of the head) moving at different constant velocities (ranges of individual trial velocities at different difficulty levels - 0,5 to 3, 3 to 5, and 4 to 7 deg/s), amplitudes (40 to 90% ROM). Movements will be perfromed in a diagonal 2D line encompasing flexion/extension and rotations). The listed parameters are increased when the average session accuracy reaches 60% time-on-target. If 60% time-on-target will be reached before the end of 4 week training period, general training intervention will be continued. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'armGroupLabels': ['Patients with smaller movement deficits']}, {'name': 'Larger movement deficit training group', 'type': 'OTHER', 'description': 'Kinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with the task to follow the moving target (always starting at the same starting position of the head) moving at different constant velocities (ranges of individual trial velocities at different difficulty levels - 0,5 to 3, 3 to 5, and 4 to 7 deg/s), amplitudes (40 to 90% ROM). All movements finish at random point which has to be maintained for 5 s. Movements will be performed in diagonal 2D lines simultaneously encompasing flexion/extension and rotations). The listed parameters are increased when the average session accuracy reaches 60% time-on-target. If 60% time-on-target will be reached before the end of 4 week training period, training intervention of the group with smaller movement deficits will be continued. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'armGroupLabels': ['Patients with lerger movement deficits']}, {'name': 'Largest movement deficit training protocol', 'type': 'OTHER', 'description': 'Kinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with the goal to follow the moving target (always starting at the same starting position as the head) moving at different constant velocities (ranges of individual trial velocities at different difficulty levels - 0,5 to 3, 3 to 5, and 4 to 7 deg/s), amplitudes (40 to 90% ROM). All movements finish at random point which has to be maintained for 5 s. Movements will be performed in a single axis (flexion/extension and seperatelly rotations). The listed parameters are increased when the average session accuracy reaches 60% time-on-target. If 60% time-on-target will be reached before the end of 4 week training period, training intervention of the group with larger movement deficits will be continued. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'armGroupLabels': ['Patients with largest movement deficits']}, {'name': 'Control group intervention protocol', 'type': 'OTHER', 'description': 'Kinematic training intervention (head and neck movement training): focused on head and neck movement training in a sitting position with constant velocities (ranges of difficulty levels from 0,5 to 3, 3 to 5, and 4 to 7 deg/s), at different amplitudes between trials (40 to 90% ROM), and at predefined movement paths (square, circle, zig-zag and figure of 8 pattern). The listed parameters are increased when the average accuracy of two following training sessions reaches 60% time-on-target. Patients will perform 4 training sessions per week (20 min duration each), for four weeks.', 'armGroupLabels': ['Control group of patinets with neck pain']}]}, 'contactsLocationsModule': {'locations': [{'zip': '1000', 'city': 'Ljubljana', 'status': 'RECRUITING', 'country': 'Slovenia', 'contacts': [{'name': 'Živa Majcen Rošker, PhD, PT', 'role': 'CONTACT', 'email': 'ziva.majcen-rosker@fsp.uni-lj.si', 'phone': '00386 51267383'}], 'facility': 'Faculty of Sport', 'geoPoint': {'lat': 46.05108, 'lon': 14.50513}}], 'centralContacts': [{'name': 'Ziva Majcen rosker, PhD, PT', 'role': 'CONTACT', 'email': 'ziva.majcen-rosker@fsp.uni-lj.si', 'phone': '00386 51267383'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'The results of the study demand analysis of patient groups not individual data. Therefore IPD will be analyzed and shared in any way.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Ljubljana', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'assist. prof. Ziva Majcen Rosker, PT, PhD', 'investigatorFullName': 'Ziva Majcen Rosker', 'investigatorAffiliation': 'University of Ljubljana'}}}}