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{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001289', 'term': 'Attention Deficit Disorder with Hyperactivity'}, {'id': 'D065886', 'term': 'Neurodevelopmental Disorders'}], 'ancestors': [{'id': 'D019958', 'term': 'Attention Deficit and Disruptive Behavior Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-09-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-08', 'completionDateStruct': {'date': '2026-01-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-08-14', 'studyFirstSubmitDate': '2025-08-02', 'studyFirstSubmitQcDate': '2025-08-14', 'lastUpdatePostDateStruct': {'date': '2025-08-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-08-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-01-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Saccade frequency during fixation', 'timeFrame': 'Baseline', 'description': 'Number of saccades (eye movements \\> 3°) made during a fixation task. This frequency is hypothesized to be higher in children with ADHD than in controls.'}, {'measure': 'Variability of saccadic latency', 'timeFrame': 'Baseline', 'description': 'Variability in the time it takes for participants to initiate saccadic eye movements in response to visual stimuli. This parameter is expected to be higher in children with ADHD compared to controls.'}, {'measure': 'Sensitivity and Specificity of Composite Oculomotor Biomarker for ADHD Diagnosis', 'timeFrame': 'At completion of baseline assessment (Day 0)', 'description': 'Diagnostic sensitivity and specificity of a composite oculomotor biomarker derived from variables predictive of ADHD. Thresholds for individual parameters (e.g. saccadic latency variability \\> 110 ms, saccade frequency during fixation \\> 10/minute) will be based on literature and refined using internal study data prior to confirmatory analysis. Thresholds and analysis procedures will be pre-specified in the Statistical Analysis Plan.'}], 'secondaryOutcomes': [{'measure': 'Discrimination Between ADHD Subtypes Using Multivariable Model Based on neos™ Eye-Tracking Parameters', 'timeFrame': 'At the end of data collection and prior to final analysis (estimated Month 12)', 'description': 'A multivariable model based on neos™ eye-tracking parameters will be used to distinguish between the three ADHD subtypes: predominantly hyperactive-impulsive, predominantly inattentive and combined subtype. The model will incorporate all available neos™ eye-tracking data. Subtype classification performance (e.g. accuracy, sensitivity and specificity) will be evaluated based on internal validation procedures.'}, {'measure': 'Correlation of Disease Severity with Oculomotor Biomarker for ADHD Severity Assessment', 'timeFrame': 'Assessed at baseline visit (Day 0) - if everything is recorded', 'description': 'Disease severity in ADHD will be assessed in relation to a combined analysis of ocular motor parameters obtained via neos™ eye-tracking. The goal is to establish a new quantitative biomarker for ADHD severity. The correlation between oculomotor metrics and standardized clinical severity ratings (e.g. ADHD symptom scales) will be evaluated.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['ADHD', 'Eye Tracking', 'Oculomotor Function', 'Pupillary Response', 'Pedriatic Neuropsychiatry', 'Neurodevelopmental Disorders', 'Neurocognitive Testing', 'Non-invasive Assessment', 'Eye Movements'], 'conditions': ['Attention Deficit Disorder With Hyperactivity (ADHD)', 'Attention Deficit Disorder (ADD)']}, 'referencesModule': {'references': [{'pmid': '28811624', 'type': 'BACKGROUND', 'citation': 'Wainstein G, Rojas-Libano D, Crossley NA, Carrasco X, Aboitiz F, Ossandon T. Pupil Size Tracks Attentional Performance In Attention-Deficit/Hyperactivity Disorder. Sci Rep. 2017 Aug 15;7(1):8228. doi: 10.1038/s41598-017-08246-w.'}, {'pmid': '36082454', 'type': 'BACKGROUND', 'citation': 'Schulz-Zhecheva Y, Voelkle MC, Beauducel A, Biscaldi M, Klein C. Intra-Subject Variability, Intelligence, and ADHD Traits in a Community-Based Sample. J Atten Disord. 2023 Jan;27(1):67-79. doi: 10.1177/10870547221118523. Epub 2022 Sep 8.'}, {'pmid': '37081447', 'type': 'BACKGROUND', 'citation': 'Salari N, Ghasemi H, Abdoli N, Rahmani A, Shiri MH, Hashemian AH, Akbari H, Mohammadi M. The global prevalence of ADHD in children and adolescents: a systematic review and meta-analysis. Ital J Pediatr. 2023 Apr 20;49(1):48. doi: 10.1186/s13052-023-01456-1.'}, {'pmid': '9746145', 'type': 'BACKGROUND', 'citation': 'Munoz DP, Broughton JR, Goldring JE, Armstrong IT. Age-related performance of human subjects on saccadic eye movement tasks. Exp Brain Res. 1998 Aug;121(4):391-400. doi: 10.1007/s002210050473.'}, {'pmid': '11502907', 'type': 'BACKGROUND', 'citation': 'Mostofsky SH, Lasker AG, Cutting LE, Denckla MB, Zee DS. Oculomotor abnormalities in attention deficit hyperactivity disorder: a preliminary study. Neurology. 2001 Aug 14;57(3):423-30. doi: 10.1212/wnl.57.3.423.'}, {'pmid': '34655657', 'type': 'BACKGROUND', 'citation': 'Maron DN, Bowe SJ, Spencer-Smith M, Mellahn OJ, Perrykkad K, Bellgrove MA, Johnson BP. Oculomotor deficits in attention deficit hyperactivity disorder (ADHD): A systematic review and comprehensive meta-analysis. Neurosci Biobehav Rev. 2021 Dec;131:1198-1213. doi: 10.1016/j.neubiorev.2021.10.012. Epub 2021 Oct 13.'}, {'pmid': '26635643', 'type': 'BACKGROUND', 'citation': 'Hamed AM, Kauer AJ, Stevens HE. Why the Diagnosis of Attention Deficit Hyperactivity Disorder Matters. Front Psychiatry. 2015 Nov 26;6:168. doi: 10.3389/fpsyt.2015.00168. eCollection 2015.'}, {'pmid': '28700580', 'type': 'BACKGROUND', 'citation': 'Constantino JN, Kennon-McGill S, Weichselbaum C, Marrus N, Haider A, Glowinski AL, Gillespie S, Klaiman C, Klin A, Jones W. Infant viewing of social scenes is under genetic control and is atypical in autism. Nature. 2017 Jul 20;547(7663):340-344. doi: 10.1038/nature22999. Epub 2017 Jul 12.'}]}, 'descriptionModule': {'briefSummary': 'Attention Deficit Hyperactivity Disorder (ADHD) affects more than 5 % of children and adolescents, with a globally increasing prevalence. The condition imposes a significant burden on affected individuals, their families, and healthcare systems. Early and accurate diagnosis is crucial to ensure timely therapeutic and educational interventions. However, current diagnostic practices rely heavily on clinical interviews and behavioral observations, which are inherently subjective and resource-intensive.\n\nThere is a growing need for objective diagnostic tools that can complement or even partially replace current clinical assessments. One promising approach involves eye-tracking technology, as ADHD is associated with altered oculomotor control and attention-related neural circuits. These changes may be reflected in measurable eye movement parameters, including saccadic latency and fixation stability.\n\nThis clinical investigation uses a certified, CE-marked medical eye-tracking device (neos™) to assess whether specific eye movement parameters can serve as objective biomarkers for ADHD. Although the device was originally designed to assess visual pathway integrity, it also captures parameters related to attention and executive function through standardized protocols. The test is examiner-independent, non-invasive, and takes approximately 10 minutes.\n\nThe study is observational and non-interventional, involving two groups of participants aged 8 to 16: 50 children with a clinically confirmed diagnosis of ADHD and 50 age-matched non-ADHD controls. All participants will complete a single neos™ eye-tracking assessment.\n\nThe primary hypothesis is that children with ADHD will demonstrate greater variability in saccadic latency and a higher frequency of large saccades (\\> 3°) during fixation compared to controls. These differences will be analyzed as potential diagnostic biomarkers. Diagnostic accuracy will be evaluated using receiver operating characteristic (ROC) analysis, with sensitivity, specificity and area under the curve (AUC) values reported.\n\nSecondary hypotheses include:\n\nOculomotor parameters derived from the neos™ system can distinguish between ADHD subtypes (predominantly inattentive, hyperactive-impulsive and combined).\n\nCombined oculomotor metrics correlate with ADHD symptom severity, potentially enabling a quantitative assessment of disease burden.\n\nThe results of this study could pave the way for the clinical adoption of objective, scalable and rapid diagnostic tools for ADHD. Beyond clinical use, such tools may also be adapted for population screening, telemedicine or integration into consumer-grade technologies such as virtual reality headsets. By validating a market-approved device for a new mental health indication, this study represents a critical step toward bridging research and clinical application in ADHD diagnostics.', 'detailedDescription': "Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in children and adolescents. It is estimated that over 5 % of young people worldwide are affected, with numbers rising in many countries. ADHD can cause serious difficulties in everyday life - at school, at home and in social settings. Children with ADHD often struggle with attention, impulsivity and hyperactivity. If not recognized and treated early, these challenges can persist into adolescence and adulthood, affecting academic success, social relationships and mental health.\n\nA timely and accurate diagnosis is therefore essential. However, diagnosing ADHD is not straightforward. Currently, it relies mainly on interviews with parents and children, behavioral observations and standardized questionnaires. While these methods can be effective, they are also subjective. The process often depends on how clearly the symptoms are described, how experienced the clinician is and how much time is available for assessment. This can lead to uncertainty or delays in diagnosis, especially in borderline or complex cases.\n\nTo improve this situation, researchers are exploring new ways to make the diagnosis of ADHD more objective, faster and easier to reproduce. One promising tool is eye-tracking - a method that measures how a person's eyes move while they look at specific images or follow visual targets on a screen. Scientific studies have shown that people with ADHD tend to have different patterns of eye movement, especially when it comes to focus, reaction time, and maintaining attention.\n\nIn this study, we use a medically certified device called neos™, which is designed to record and analyze eye movements in a highly accurate and standardized way. The neos™ system is already approved for clinical use in Europe for examining the visual system, but in this investigation, it is being tested for a new purpose: supporting the diagnosis of ADHD. The test is short (about 10 minutes), non-invasive and does not require verbal responses or physical interaction. It is fully automated and can be performed in a clinic by non-specialist staff.\n\nThe study will include 100 children between the ages of 8 and 16. Half of the participants will have a prior, clinically confirmed diagnosis of ADHD made by a specialist (such as a pediatrician, child neurologist or neuropsychologist). The other half will be age-matched children without ADHD. All participants will complete the same neos™ eye-tracking assessment.\n\nThe main goal of the study is to find out whether specific eye movement parameters - especially the variability in how fast the eyes move (saccadic latency) and the number of small, rapid eye movements during fixation - can reliably distinguish between children with and without ADHD. The idea is that children with ADHD may show more irregularities or signs of reduced visual focus during the test. These measurable differences could serve as biomarkers, which are objective signs that help confirm a diagnosis.\n\nIn addition to the main analysis, the study will also look at whether these eye movement patterns can help:\n\nto differentiate between the three subtypes of ADHD (inattentive, hyperactive-impulsive, and combined)\n\nand estimate the severity of symptoms, potentially providing a new way to monitor treatment response over time.\n\nImportantly, this is not a treatment study. The children will not receive medication or therapy. The study only involves a single, short eye-tracking test that is safe and well-tolerated.\n\nIf the results of the study are promising, the findings could help bring a new, objective tool into routine ADHD diagnostics. Because the neos™ device is already approved and available on the market, such a test could be implemented quickly in clinical settings. In the future, similar technology could even be adapted for screenings in schools, remote assessments via telemedicine or even self-monitoring with VR headsets, making ADHD diagnostics more accessible and scalable worldwide.\n\nBy making the diagnostic process more objective and less dependent on clinical interpretation alone, this study hopes to contribute to earlier and more accurate diagnoses-and ultimately better outcomes for children living with ADHD."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD'], 'maximumAge': '16 Years', 'minimumAge': '8 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The study population consists of children aged 8 to 16 years. Two groups will be included: children with a clinically confirmed diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) and age-matched children without ADHD. Participants will be recruited from pediatric and ophthalmologic clinics. Both male and female children are eligible. Informed consent will be obtained from participants and/or their legal guardians.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion criteria:\n\nFor the ADHD group:\n\n* Clinically confirmed diagnosis of ADHD by an expert (e.g., pediatrician, neuropsychologist, pediatric neurologist)\n* Age between 8 and 16 years\n* Written informed consent from the participant and/or legal guardian\n\nFor the control group (non-ADHD):\n\n* Age between 8 and 16 years\n* No suspicion of ADHD\n* Written informed consent from the participant and/or legal guardian\n\nExclusion Criteria:\n\nFor both groups:\n\n* Medical conditions known to affect ocular motor behavior (e.g., neurological or ophthalmological disorders)\n* Doubts regarding the accuracy of the ADHD diagnosis (for the ADHD group)\n* Lack of or questionable informed consent\n* Suspicion of ADHD in control group participants (reported by parents, examiner, or physician)'}, 'identificationModule': {'nctId': 'NCT07136259', 'acronym': 'ADHDin15?', 'briefTitle': 'A Quick and Reliable Eye Movement Test to Help Diagnose ADHD in Children.', 'organization': {'class': 'NETWORK', 'fullName': 'Onovis Augenpraxis'}, 'officialTitle': 'Certified Comprehensive Eye-Movement Examination in Children With Attention Deficit Hyperactivity Disorder: An Objective, Reproducible and Quantitative Diagnosis in 15 Minutes?', 'orgStudyIdInfo': {'id': '2025-D0052'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Group 1', 'description': 'ADHD'}, {'label': 'Group 2', 'description': 'Control Children'}]}, 'contactsLocationsModule': {'locations': [{'zip': '3011', 'city': 'Bern', 'state': 'Canton of Bern', 'country': 'Switzerland', 'contacts': [{'name': 'Beate Spychala, MSc.', 'role': 'CONTACT', 'email': 'beate.spychala@onovis.ch', 'phone': '+41 78 677 84 18'}], 'facility': 'OnovisAugenpraxis', 'geoPoint': {'lat': 46.94809, 'lon': 7.44744}}], 'centralContacts': [{'name': 'Mathias Abegg, PD Dr. med. Dr. sc. nat.', 'role': 'CONTACT', 'email': 'mathias.abegg@hin.ch', 'phone': '+41 79 936 88 34'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Onovis Augenpraxis', 'class': 'NETWORK'}, 'responsibleParty': {'type': 'SPONSOR'}}}}