[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100621699":3},{"organization":4,"armGroups":7,"interventions":25,"overallOfficials":40,"centralContacts":44,"locations":50,"responsibleParty":70,"collaborators":31,"id":72,"slug":73,"hasResults":74,"nctId":75,"briefTitle":76,"officialTitle":76,"acronym":77,"eligibilityCriteria":78,"healthyVolunteers":79,"sex":80,"minAge":81,"maxAge":82,"enrollmentInfo":83,"targetDuration":31,"studyType":86,"phases":87,"briefSummary":89,"conditions":90,"keywords":92,"overallStatus":97,"whyStopped":31,"lastUpdateSubmitDate":98,"lastUpdatePostDateStruct":99,"startDateStruct":102,"completionDateStruct":104,"leadSponsor":106,"locationsCount":107},{"fullName":5,"class":6},"Centre Hospitalier Universitaire de Saint Etienne","OTHER",[8,14,19],{"label":9,"type":10,"description":11,"interventionNames":12},"GEN: generic training plan group","ACTIVE_COMPARATOR","The GEN group will follow a generic training plan that will be created from a platform that is both free and popular, offering training plans for trail-running (The Decathlon Pacer application).",[13],"Procedure: Training recommendations GEN",{"label":15,"type":10,"description":16,"interventionNames":17},"PERSO: non-adaptive personalized group","The PERSO group will follow a plan that takes into consideration the training history, in particular the number of hours per week over the previous two years; the runner's level; age and sex; time available for training; and access to mountainous terrain.",[18],"Procedure: Training recommendations PERSO",{"label":20,"type":21,"description":22,"interventionNames":23},"PERSO-ADAPT group: adaptive personalized group","EXPERIMENTAL","The PERSO-ADAPT group will include the same information as the PERSO group, but the training will also be adapted on a weekly basis according to the following feedback: state of fatigue assessed by questionnaire and heart rate variability; state of overtraining, assessed by questionnaire; degree of session completion).",[24],"Procedure: Training recommendations PERSO-ADAPT",[26,32,36],{"type":27,"name":28,"description":29,"armGroupLabels":30,"otherNames":31},"PROCEDURE","Training recommendations GEN","Generic training plan that will be created from a platform that is both free and popular, offering training plans for trail-running (The Decathlon Pacer application).",[9],null,{"type":27,"name":33,"description":34,"armGroupLabels":35,"otherNames":31},"Training recommendations PERSO","A training plan that takes into account the rider's training history, in particular the number of hours per week over the last two years, the rider's level, age and gender, the time available for training and access to mountainous terrain.",[15],{"type":27,"name":37,"description":38,"armGroupLabels":39,"otherNames":31},"Training recommendations PERSO-ADAPT","A training plan that takes into account the rider's training history, in particular the number of hours per week over the last two years, the level, age and gender of the rider, the time available for training and access to mountainous terrain. Training will also be adapted on a weekly basis according to the following feedback: state of fatigue assessed by questionnaire and heart rate variability; state of overtraining, assessed by questionnaire; degree of completion of sessions.",[20],[41],{"name":42,"affiliation":5,"role":43},"Leonard FEASSON, MD PhD","PRINCIPAL_INVESTIGATOR",[45],{"name":42,"role":46,"phone":47,"phoneExt":48,"email":49},"CONTACT","(0)4 77 12 03 83","+33","leonard.feasson@chu-saint-etienne.fr",[51],{"facility":52,"status":31,"city":53,"state":54,"zip":55,"country":54,"countryCode":56,"cosmosGeoPoint":57,"geoPoint":62,"contacts":63},"Unités de Myologie et de Médecine du Sport","Saint-Etienne","France","42055","FR",{"type":58,"coordinates":59},"Point",[60,61],4.39,45.43389,{"lat":61,"lon":60},[64,67],{"name":65,"role":46,"phone":47,"phoneExt":48,"email":66},"Léonard FEASSON, MD PhD","leonard.feasson@chu-st-etienne.fr",{"name":68,"role":46,"phone":31,"phoneExt":31,"email":69},"Diana RIMAUD","diana.rimaud@chu-st-etienne.fr",{"type":71,"investigatorFullName":31,"investigatorTitle":31,"investigatorAffiliation":31,"oldNameTitle":31,"oldOrganization":31},"SPONSOR","100621699","evaluation-of-a-training-recommendation-strategy-for-trail-runners-100621699",false,"NCT07374016","Evaluation of a Training Recommendation Strategy for Trail Runners.","TRAILWISE","Inclusion Criteria:\n\n* Have no contraindications to trail running (Fédération Française d'Athlétisme test procedures)\n* Have been trail running competitively for at least 1 year\n* In possession of an ITRA performance index\n* Intends to run at least one ITRA-indexed race in the second half of the follow-up period\n* Own a training watch, and intend to record all training sessions of more than 10 minutes in their shared database\n* Have freely given their written consent.\n\nExclusion Criteria:\n\n* Any person with chronic joint pathologies (e.g. recurrent sprains, patellar or ligament problems) or cardiac pathologies.\n* Any person with chronic or central neurological pathologies.\n* Any person deprived of their liberty or under legal protection (guardianship, curatorship, safeguard of justice, family habilitation).",true,"ALL","18 Years","65 Years",{"count":84,"type":85},1209,"ESTIMATED","INTERVENTIONAL",[88],"NA","Finding the optimal training, i.e. the training that enables the athlete to achieve the best performance while preserving their physical and psychological integrity, is a multi-factorial issue.\n\nEach individual's background and training capacity are very different, hence the need for personalised training. The availability of data combined with advances in Artificial Intelligence (data modelling and analysis sciences, big data, machine learning, deep learning, etc.) offer the opportunity to refine our understanding of training and adapt recommendations according to the runner's profile for a given objective (achieving a time over a distance, completing an event, etc.). The strategy that the investigators wish to evaluate as part of this trial could make it possible to recommend an optimal training load, as well as the distribution of intensities (as a percentage of the aerobic threshold, anaerobic threshold, VVO2max, etc). The two features are (i) the personalisation will be based on training history, the level of the runner, age and gender, and the runner can focus on training, and (ii) the strategy will be adaptive, i.e. the algorithm will update the training load in real time based on contextual data about the athlete (level of fatigue via heart rate variability, feedback on recent training sessions, feelings of stress).",[91],"Endurance Training",[93,94,95,96],"Trail running","Performance","Training recommendations","Artificial intelligence","NOT_YET_RECRUITING","2026-01-21",{"date":100,"type":101},"2026-01-28","ACTUAL",{"date":103,"type":85},"2026-03",{"date":105,"type":85},"2027-12",{"name":5,"class":6},1]