[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"leadSponsorName\":\"Clover Link\",\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:":78},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,49],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":4,"briefSummary":24,"conditions":25,"keywords":30,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":37,"lastUpdatePostDateStruct":38,"startDateStruct":41,"completionDateStruct":43,"leadSponsor":45,"locationsCount":48},"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":21,"type":22},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.",[26,27,28,29],"Absenteeism","Sick Leave","Workplace Well-Being","Occupational Stress",[31,32,33,34,35],"WB6Dim","Adaptive Load Index","absenteeism prediction","cliff effect","ICA","NOT_YET_RECRUITING","2026-05-17",{"date":39,"type":40},"2026-05-26","ACTUAL",{"date":42,"type":22},"2026-06-01",{"date":44,"type":22},"2026-11-30",{"name":46,"class":47},"Clover Link","INDUSTRY",1,{"id":50,"slug":51,"hasResults":11,"nctId":52,"briefTitle":53,"officialTitle":54,"acronym":55,"eligibilityCriteria":56,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":57,"targetDuration":59,"studyType":23,"phases":4,"briefSummary":60,"conditions":61,"keywords":63,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":71,"lastUpdatePostDateStruct":72,"startDateStruct":74,"completionDateStruct":75,"leadSponsor":77,"locationsCount":48},"100626294","test-retest-reliability-of-the-wb6dim-digital-well-being-tool-a-3-day-interval-study-100626294","NCT07433764","Test-Retest Reliability of the WB6Dim Digital Well-Being Tool: A 3-Day Interval Study","Psychometric Validation of Test-Retest Reliability of the WB6Dim Digital Self-Assessment Tool for Well-Being Using a 3-Day Interval Protocol and Contamination Control","WB6Dim-TRT","Inclusion Criteria:\n\n* Adults aged 18 years or older\n* Able to read and understand French\n* Access to an internet-connected device\n* Willing to complete the WB6Dim questionnaire at T1 and T2\n* Consent to anonymous data collection for research purposes\n\nExclusion Criteria:\n\n* Under 18 years of age\n* Unable to read or understand French",{"count":58,"type":22},500,"9 Weeks","This study aims to establish the test-retest reliability of the WB6Dim digital self-assessment tool across its eight well-being dimensions, using a 3-day interval protocol designed to minimize the probability of genuine well-being changes between assessments.\n\nParticipants complete the 28-item WB6Dim questionnaire at baseline (T1) and again 3 days later (T2). A single contamination control question at T2 identifies participants who experienced a significant life event during the interval; these pairs are excluded from primary ICC analyses and retained for exploratory analyses.\n\nAn optional third assessment at 9 weeks (T3) provides preliminary exploratory data on sensitivity to change following access to a well-being program. T3 is not part of the primary design.",[62],"Psychological Well Being",[64,65,66,67,31,68,69],"well-being","Test-retest reliability","Intraclass correlation","Digital self-assessment","Psychometric validation","Workplace well-being","RECRUITING","2026-02-19",{"date":73,"type":40},"2026-02-25",{"date":71,"type":40},{"date":76,"type":22},"2026-05-09",{"name":46,"class":47},""]