[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100623822":3},{"organization":4,"outcomesModule":7,"designInfo":69,"detailedDescription":68,"studyPopulation":68,"armGroups":75,"interventions":86,"overallOfficials":92,"centralContacts":97,"locations":106,"responsibleParty":122,"collaborators":124,"id":129,"slug":68,"hasResults":130,"nctId":131,"briefTitle":132,"officialTitle":133,"acronym":134,"eligibilityCriteria":135,"healthyVolunteers":136,"sex":137,"minAge":138,"maxAge":68,"enrollmentInfo":139,"targetDuration":68,"studyType":142,"phases":143,"briefSummary":145,"conditions":146,"keywords":68,"overallStatus":108,"whyStopped":68,"lastUpdateSubmitDate":149,"lastUpdatePostDateStruct":150,"startDateStruct":153,"completionDateStruct":155,"leadSponsor":157,"locationsCount":158},{"fullName":5,"class":6},"University of Bern","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":68},[9],{"measure":10,"description":11,"timeFrame":12},"Diagnostic accuracy (AUROC) of a multimodal machine-learning model for detection of cannabis-impaired driving","Area under the receiver operating characteristic curve (AUROC) of a single machine-learning classifier that integrates multimodal in-vehicle data (including vehicle controller area network \\[CAN\\] data, driver monitoring camera \\[DMC\\] features, and physiological signals). All modalities are combined into one predictive model, and performance is reported as one aggregated AUROC value distinguishing non-impaired (sober) driving from cannabis-impaired driving.","Baseline (sober driving) and up to 6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.",[14,18,21,24,27,30,33,36,39,42,45,49,53,56,59,62,65],{"measure":15,"description":16,"timeFrame":17},"Diagnostic accuracy (AUROC) using CAN data","AUROC for detecting cannabis-impaired driving using vehicle controller area network (CAN) data only.","Baseline (sober driving) and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm, with matched time points in the reference arm.",{"measure":19,"description":20,"timeFrame":17},"Diagnostic accuracy (AUROC) using DMC data","AUROC for detecting cannabis-impaired driving using driver monitoring camera (DMC) data only.",{"measure":22,"description":23,"timeFrame":17},"Diagnostic accuracy (AUROC) of a physiology-based machine-learning model for detection of cannabis-impaired driving","AUROC of a single machine-learning classifier trained and evaluated using aggregated physiological features only, derived from signals including heart rate, heart-rate variability, oxygen saturation, electrodermal activity, skin temperature, and respiration-related measures. All physiological signals are combined into one predictive model, and performance is reported as a single AUROC value distinguishing non-impaired (sober) driving from cannabis-impaired driving.",{"measure":25,"description":26,"timeFrame":17},"Change in driving behavior derived from vehicle CAN data","Change in driving behavior between sober driving and post-cannabis driving, derived from vehicle controller area network (CAN) signals, including steering, braking, acceleration, and velocity-related measures.",{"measure":28,"description":29,"timeFrame":17},"Change in driver gaze behavior derived from DMC data","Change in gaze behavior between sober and post-cannabis driving, derived from driver monitoring camera (DMC) data, including gaze direction and gaze dynamics during driving.",{"measure":31,"description":32,"timeFrame":17},"Change in head movement behavior derived from DMC data","Change in head movement behavior between sober and post-cannabis driving, derived from driver monitoring camera (DMC) data.",{"measure":34,"description":35,"timeFrame":17},"Driving instructor assessment of driving performance","Assessment of driving performance conducted by a certified driving instructor, quantified as the number of safety interventions required during each standardized driving session.",{"measure":37,"description":38,"timeFrame":17},"Diagnostic accuracy (AUROC) of an in-vehicle pre-driving readiness test for detection of cannabis-impaired driving","AUROC of a machine-learning (ML) classification model implementing a study-specific in-vehicle pre-driving readiness test. The test produces an ML-derived readiness score, computed from features derived from the pre-driving test (e.g., attention-related, reaction-time-related, and psychomotor-related features), and is used to classify driving sessions as sober versus post-cannabis.",{"measure":40,"description":41,"timeFrame":17},"Performance in the standardized Psytest assessment","Performance in the standardized Psytest assessment (mobility version of the Test of Attentional Performance), administered under sober conditions and after cannabis consumption. Test performance is summarized using a standardized test score reflecting overall attentional and psychomotor performance relevant for driving.",{"measure":43,"description":44,"timeFrame":17},"Self-reported subjective effects","Self-reported subjective effects assessed using study questionnaires, including subjective feeling of \"high\" and degree of sleepiness. Responses are recorded using a Likert scale ranging from 0 to 10, where 0 indicates \"not at all\" and 10 indicates \"extremely.\" Higher scores indicate a worse outcome, reflecting stronger subjective drug effects and greater sleepiness.",{"measure":46,"description":47,"timeFrame":48},"Cannabinoid biomarker concentrations in biological samples","Concentrations of Δ9-tetrahydrocannabinol (THC) measured in capillary blood, oral fluid, and breath samples.","Baseline in all participants, and approximately 1-2, 3-4, and 5-6 hours after cannabis administration in the experimental arm.",{"measure":50,"description":51,"timeFrame":52},"Incidence of adverse events","Incidence of adverse events and serious adverse events recorded during all study visits.","From the first study procedure (i.e. baseline assessment) to the end of the main study day (i.e. driving assessment) expected to be on average up to 6 hours.",{"measure":54,"description":55,"timeFrame":17},"Change in heart rate during driving","Change in heart rate measured during driving between sober conditions and post-cannabis conditions.",{"measure":57,"description":58,"timeFrame":17},"Change in oxygen saturation during driving","Change in oxygen saturation measured during driving between sober conditions and post-cannabis conditions.",{"measure":60,"description":61,"timeFrame":17},"Change in electrodermal activity during driving","Change in electrodermal activity measured during driving between sober conditions and post-cannabis conditions.",{"measure":63,"description":64,"timeFrame":17},"Change in skin temperature during driving","Change in skin temperature measured during driving between sober conditions and post-cannabis conditions.",{"measure":66,"description":67,"timeFrame":17},"Change in respiration during driving","Change in respiration measured during driving between sober conditions and post-cannabis conditions.",null,{"allocation":70,"interventionModel":71,"interventionModelDescription":68,"primaryPurpose":72,"observationalModel":68,"timePerspective":68,"maskingInfo":73},"RANDOMIZED","PARALLEL","DIAGNOSTIC",{"masking":74,"maskingDescription":68,"whoMasked":68},"NONE",[76,82],{"label":77,"type":78,"description":79,"interventionNames":80},"Controlled Cannabis Administration","EXPERIMENTAL","Participants assigned to this arm receive a single, controlled inhalative administration of cannabis by smoking a THC-containing joint with a target dose of approximately 0.67 mg THC per kg body weight. Participants complete standardized driving sessions in an instrumented vehicle on a closed test track under sober baseline conditions and repeatedly after cannabis administration (approximately 1-6 hours post-dose). All driving sessions are conducted with a certified driving instructor seated in the front passenger seat with access to dual pedals, allowing immediate intervention if required. Multimodal in-vehicle sensor data, physiological signals, driving performance measures, and biological samples are collected throughout the study.",[81],"Drug: Cannabis (THC)",{"label":83,"type":84,"description":85,"interventionNames":68},"Reference (No Cannabis)","NO_INTERVENTION","Participants assigned to this reference arm receive no cannabis administration. They complete the same screening procedures, standardized driving sessions, assessments, and data collection as the experimental group under sober conditions, following the same schedule and time points. All driving sessions are conducted with a certified driving instructor seated in the front passenger seat with access to dual pedals, ensuring identical safety conditions. This arm serves as a non-impaired reference for comparison of driving behavior and in-vehicle sensor data.",[87],{"type":88,"name":89,"description":90,"armGroupLabels":91,"otherNames":68},"DRUG","Cannabis (THC)","Participants assigned to the experimental arm receive a single, controlled inhalative administration of cannabis by smoking a THC-containing joint (target dose 0.67 mg THC per kg body weight; cannabis flowers with 15-18% THC).",[77],[93],{"name":94,"affiliation":95,"role":96},"Wolfgang Weinmann, Prof. Dr.","Institute for Forensic Medicine, Forensic Chemistry and Toxicology University of Bern","PRINCIPAL_INVESTIGATOR",[98,102],{"name":94,"role":99,"phone":100,"phoneExt":68,"email":101},"CONTACT","+41 31 684 01 61","wolfgang.weinmann@irm.unibe.ch",{"name":103,"role":99,"phone":104,"phoneExt":68,"email":105},"Michal Bechny, Dr.","+41 76 221 62 56","mbechny@ethz.ch",[107],{"facility":95,"status":108,"city":109,"state":68,"zip":110,"country":111,"countryCode":112,"cosmosGeoPoint":113,"geoPoint":118,"contacts":119},"RECRUITING","Bern","3008","Switzerland","CH",{"type":114,"coordinates":115},"Point",[116,117],7.44744,46.94809,{"lat":117,"lon":116},[120,121],{"name":94,"role":99,"phone":100,"phoneExt":68,"email":101},{"name":103,"role":99,"phone":104,"phoneExt":68,"email":105},{"type":123,"investigatorFullName":68,"investigatorTitle":68,"investigatorAffiliation":68,"oldNameTitle":68,"oldOrganization":68},"SPONSOR",[125,127],{"name":126,"class":6},"ETH Zurich",{"name":128,"class":6},"University of St.Gallen","100623822",false,"NCT07401628","In-Vehicle Real-Time Cannabis Influenced Driving Detection","Randomised, Controlled, Interventional Single-center Study for the Design and Evaluation of an In-vehicle Real-time System for Detecting Cannabis-impaired Driving (CID)","REVELIO","Inclusion Criteria:\n\n* Informed consent as documented by signature\n* Recreational cannabis-consumption (more than once per month)\n* In possession of a definite Swiss or European Union (EU) driving license\n* At least 21 years old\n* Active, regular driving a car in the last 6 months\n* Must be in good health condition\n* No special equipment needed when driving (special seats, levers, etc.)\n* Fluent in (Swiss) German and no speech impairment\n\nExclusion Criteria:\n\n* Health concerns where cannabis consumption is contra-indicated (such as: high blood pressure, psychiatric problems (e.g. psychosis, depression, attention-deficit conditions, etc.)\n* Cannabis-abstinence or excessive consumption, , assessed using the Cannabis Use Disorders Identification Test-Revised (CUDIT-R)\n* For women: pregnancy or breastfeeding or if intention to become pregnant during study period (time between telephone screening and study day (visit 2)\n* Alcohol misuse or excessive alcohol consumption habits\u002Frisky drinking behaviour, assessed using the Alcohol Use Disorders Identification Test (AUDIT) and\u002For phosphatidylethanol (PEth) in capillary blood \\> 200 ng\u002FmL at first visit\n* If breath alcohol test is positive at Visit 1 or Visit 2 (study day)\n* Consumption of drugs of abuse (others than cannabis) within 4 weeks before the study\n* Consumption of medications \u002F pharmaceutical drugs which interfere with driving ability\n* Inability to follow the procedures of the study, e.g., due to language",true,"ALL","21 Years",{"count":140,"type":141},45,"ESTIMATED","INTERVENTIONAL",[144],"NA","The goal of this clinical trial is to evaluate whether in-vehicle sensor data can be used to detect cannabis-impaired driving in healthy adult recreational cannabis users.\n\nThe study aims to assess whether changes in vehicle, driver, and physiological sensor data can distinguish sober driving from cannabis-impaired driving, and how driving performance changes from baseline to approximately 1 to 6 hours after controlled cannabis consumption.\n\nResearchers will compare driving behavior and in-vehicle sensor data from participants who receive controlled cannabis administration with data from a randomized reference group without cannabis exposure, to determine whether cannabis-related impairment driving can be identified on the basis of machine learning.\n\nParticipants will complete screening and baseline assessments and drive an instrumented vehicle on a closed test track under sober conditions. Participants assigned to the experimental arm will receive controlled cannabis administration, while participants in the reference arm will receive no intervention. All participants will perform repeated standardized driving sessions over several hours and complete traffic-medical, traffic-psychological, and in-vehicle pre-driving tests. Biological samples and in-vehicle sensor data will be collected throughout the study.",[147,148],"Driving Under the Influence","Cannabis-impaired Driving","2026-02-03",{"date":151,"type":152},"2026-02-10","ACTUAL",{"date":154,"type":152},"2026-01-05",{"date":156,"type":141},"2026-06-19",{"name":5,"class":6},1]