Hanna Brückner, Sebastian Wallot, Hanne Horvath, David Daniel Ebert, Dirk Lehr
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The primary outcome was insomnia severity, assessed at baseline, after 2 months (T2) and 6 months (T3).</p><p><strong>Findings: </strong>A greater reduction in insomnia was observed in the intervention compared with the WLC group at both T2 (<i>d</i>=1.51; 95% CI=1.12 o 1.91) and T3 (<i>d</i>=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 (<i>BF</i> <sub>10</sub>=3.23×e<sup>60</sup>] 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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Clinical implications: </strong>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.</p><p><strong>Trial registration number: </strong>German Clinical Trial Registration (DRKS): DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.</p>","PeriodicalId":72434,"journal":{"name":"BMJ mental health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11033646/pdf/","citationCount":"0","resultStr":"{\"title\":\"Effectiveness of an online recovery training for employees exposed to blurred boundaries between work and non-work: Bayesian analysis of a randomised controlled trial.\",\"authors\":\"Hanna Brückner, Sebastian Wallot, Hanne Horvath, David Daniel Ebert, Dirk Lehr\",\"doi\":\"10.1136/bmjment-2024-301016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Blurred work-non-work boundaries can have negative effects on mental health, including sleep.</p><p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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). 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引用次数: 0
摘要
背景:工作与非工作界限模糊会对心理健康(包括睡眠)产生负面影响:方法:128 名有严重失眠症状(失眠严重程度指数≥15)并在模糊的工作和非工作条件下工作的参与者(细分供应品):在 T2(d=1.51;95% CI=1.12 o 1.91)和 T3(d=1.63;95% CI=1.23 to 2.03]阶段,观察到干预组与 WLC 组相比,失眠症状减轻幅度更大。贝叶斯协方差分析(ANCOVA)显示了这一点,其中 ANCOVA 模型产生了最高的贝叶斯因子(BF 10=3.23×e60],概率为 99.99%。同样,频数分析显示,在 T2 和 T3 阶段,失眠症明显减少。抑郁、与工作相关的遐想和对工作的精神疏离等次要结果也发现了有益的影响。研究流失率在 T2 和 T3 分别为 16% 和 44%:恢复训练在第二阶段和第三阶段都能有效减少失眠症状、与工作相关的心理健康指标和员工的一般心理健康指标:除了证明干预的有效性外,这项研究还体现了贝叶斯方法在临床环境中的应用,并显示了贝叶斯方法通过提供对结果概率的洞察力,使干预研究的接受者能够得出明智结论的潜力:德国临床试验注册(DRKS):DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.
Effectiveness of an online recovery training for employees exposed to blurred boundaries between work and non-work: Bayesian analysis of a randomised controlled trial.
Background: 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 (BF10=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.
Trial registration number: German Clinical Trial Registration (DRKS): DRKS00006223, https://drks.de/search/de/trial/DRKS00006223.