[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100639484":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":12,"centralContacts":17,"locations":24,"responsibleParty":40,"collaborators":10,"id":42,"slug":43,"hasResults":44,"nctId":45,"briefTitle":46,"officialTitle":47,"acronym":48,"eligibilityCriteria":49,"healthyVolunteers":50,"sex":51,"minAge":52,"maxAge":10,"enrollmentInfo":53,"targetDuration":10,"studyType":56,"phases":10,"briefSummary":57,"conditions":58,"keywords":63,"overallStatus":69,"whyStopped":10,"lastUpdateSubmitDate":70,"lastUpdatePostDateStruct":71,"startDateStruct":74,"completionDateStruct":76,"leadSponsor":78,"locationsCount":79},{"fullName":5,"class":6},"Clover Link","INDUSTRY",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"Multi-company workforce cohort",null,"Single-cohort design. All participants receive the same observational protocol: 4 WB6Dim assessments over 6 months. The predictive analysis is conducted at the company level, comparing companies above versus below the sample median of collective critical ICA proportion at T0. No group assignment is made at the individual level. Stratification is performed post-hoc based on observed ICA distributions.",[13],{"name":14,"affiliation":15,"role":16},"Frédérique RETORNAZ, MD, PhD","European Hospital, Unit of Care and Research in Internal Medicine and Infectious Diseases.","STUDY_CHAIR",[18],{"name":19,"role":20,"phone":21,"phoneExt":22,"email":23},"Quentin ALITTA, MBA","CONTACT","686505361","+33","quentin.alitta@gmail.com",[25],{"facility":5,"status":10,"city":26,"state":10,"zip":27,"country":28,"countryCode":29,"cosmosGeoPoint":30,"geoPoint":35,"contacts":36},"Bandol","83150","France","FR",{"type":31,"coordinates":32},"Point",[33,34],5.74718,43.14247,{"lat":34,"lon":33},[37],{"name":38,"role":20,"phone":39,"phoneExt":10,"email":23},"quentin ALITTA","0686505361",{"type":41,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100639484","wb6dim-ltsa-can-workplace-well-being-scores-predict-collective-absenteeism-100639484",false,"NCT07606261","WB6Dim-LTSA: Can Workplace Well-Being Scores Predict Collective Absenteeism?","Predictive Value of the Adaptive Load Index (ICA) Derived From the WB6Dim Instrument on Collective Absenteeism Rates at a 6-Month Horizon: A Prospective Multicenter Cohort Study","WB6Dim-LTSA","Inclusion Criteria:\n\n* Employee of a participating French company (≥ 50 employees)\n* Age 18 years or older\n* Access to a smartphone or computer to complete the digital questionnaire\n* Electronic informed consent provided at baseline\n\nExclusion Criteria:\n\n* Refusal to participate or withdrawal of consent\n* Inability to complete the questionnaire in French",true,"ALL","18 Years",{"count":54,"type":55},2000,"ESTIMATED","OBSERVATIONAL","This prospective multicenter cohort study evaluates the predictive value of the Adaptive Load Index (ICA), a composite indicator derived from the WB6Dim well-being instrument, on long-duration sick leave (≥ 30 days) in French companies at a 6-month horizon. In France, 7% of sick leave episodes (those exceeding 6 months) account for 45% of total sickness benefit expenditure (Cour des Comptes 2024). Group disability insurance charges rose +24.4% in 2024 (France Assureurs 2025). Critically, a substantial proportion of long-duration sick leave occurs without prior escalation in administrative absence data - the 'cliff effect' - where presenteeism masks progressive deterioration (Gustafsson \\& Marklund 2011). Prediction models based solely on absence history plateau at AUC 0.65 for cumulative days (Roelen 2013), while composite psychometric instruments reach C-index 0.73-0.74 (Airaksinen et al. 2018, SJWEH). The WB6Dim is a validated 28-item psychometric tool measuring 9 dimensions of workplace well-being (NCT07301879, NCT07433764; test-retest ICA .904). The ICA classifies respondents into 4 adaptive load levels. Aggregated at the company level, the ICA distribution may detect deterioration during the presenteeism window, before costly sick leave materializes. The study collects 4 WB6Dim assessments over 6 months alongside company-level absence data stratified by duration (2024-2026) and individual self-reported absence data (duration and episode count). Six pre-registered hypotheses test whether ICA predicts long-duration leave, including an exploratory hypothesis targeting companies with no prior absence signal but degraded well-being scores.",[59,60,61,62],"Absenteeism","Sick Leave","Workplace Well-Being","Occupational Stress",[64,65,66,67,68],"WB6Dim","Adaptive Load Index","absenteeism prediction","cliff effect","ICA","NOT_YET_RECRUITING","2026-05-17",{"date":72,"type":73},"2026-05-26","ACTUAL",{"date":75,"type":55},"2026-06-01",{"date":77,"type":55},"2026-11-30",{"name":5,"class":6},1]