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RessourcentypZeitschriftenartikel
TitelEffectiveness of an online recovery training for employees exposed to blurred boundaries between work and non-work: Bayesian analysis of a randomised controlled trial
DOI10.48548/pubdata-1423
Handle20.500.14123/1492
Autor*inBrückner, Hanna  0009-0003-4406-7872
Wallot, Sebastian  0000-0002-3626-3940
Horvath, Hanne  0000-0001-5594-754X
Ebert, David Daniel  0000-0001-6820-0146
Lehr, Dirk  0000-0002-5560-3605
AbstractBackground Blurred work–non-work boundaries can have negative effects on mental health, including sleep. Objectives In a randomised control trial, we aimed to assess the effectiveness of an online recovery training programme designed to improve symptoms of insomnia in a working population exposed to blurred boundaries. Methods 128 participants with severe insomnia symptoms (Insomnia Severity Index ≥15) and working under blurred work and non-work conditions (segmentation supplies <2.25) were randomly assigned to either the recovery intervention or a waitlist control group (WLC). The primary outcome was insomnia severity, assessed at baseline, after 2 months (T2) and 6 months (T3). Findings A greater reduction in insomnia was observed in the intervention compared with the WLC group at both T2 (d=1.51; 95% CI=1.12 o 1.91) and T3 (d=1.63; 95% CI=1.23 to 2.03]. This was shown by Bayesian analysis of covariance (ANCOVA), whereby the ANCOVA model yielded the highest Bayes factor (BF 10=3.23×e60] and a 99.99% probability. Likewise, frequentist analysis revealed significantly reduced insomnia at both T2 and T3. Beneficial effects were found for secondary outcomes including depression, work-related rumination, and mental detachment from work. Study attrition was 16% at T2 and 44% at T3. Conclusions The recovery training was effective in reducing insomnia symptoms, work related and general indicators of mental health in employees exposed to blurred boundaries, both at T2 and T3. Clinical implications In addition to demonstrating the intervention’s effectiveness, this study exemplifies the utilisation of the Bayesian approach in a clinical context and shows its potential to empower recipients of interventional research by offering insights into result probabilities, enabling them to draw informed conclusions.
SpracheEnglisch
SchlagwörterBayes Theorem; Cognitive Behavior; Therapy; Sleep; Sleep Initiation; Disorder; Sleep Onset
Jahr der Veröffentlichung in PubData2024
Art der VeröffentlichungZweitveröffentlichung
PublikationsversionVeröffentlichte Version
Datum der Erstveröffentlichung2024-04-19
EntstehungskontextForschung
AnmerkungenThis publication was funded by the German Research Foundation (DFG).
Veröffentlicht durchMedien- und Informationszentrum, Leuphana Universität Lüneburg
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ElementWert
RessourcentypZeitschrift
Titel des RessourcentypsBMJ Mental Health
IdentifierDOI: 10.1136/bmjment-2024-301016
Publikationsjahr2024
Band27
Heft1
Nummere301016
NummerntypArtikel
Verlag / AnbieterBMJ Publishing Group
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