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首页> 外文期刊>Frontiers in Public Health >Work Habit-Related Sleep Debt; Insights From Factor Identification Analysis of Actigraphy Data
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Work Habit-Related Sleep Debt; Insights From Factor Identification Analysis of Actigraphy Data

机译:工作习惯相关的睡眠债务; 思想识别分析的洞察力数据

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The present study investigates the factors of “Weekday sleep debt (WSD)” by comparing activity data collected from persons with and without WSD. Since it has been reported that the amount of sleep debt as well the difference between the social clock and the biological clock is associated with WSD, specifying the factors of WSD other than chronotype may contribute to sleep debt prevention. We recruited 324 healthy male employees working at the same company and collected their 1-week wrist actigraphy data and answers to questionnaires. Because 106 participants were excluded due to measurement failure of the actigraphy data, the remaining 218 participants were included in the analysis. All participants were classified into WSD or non-WSD groups, in which persons had WDS if the difference between their weekend sleep duration and the mean weekday sleep duration was more than 120 min. We evaluated multiple measurements derived from the collected actigraphy data and trained a classifier that predicts the presence of WSD using these measurements. A support vector machine (SVM) was adopted as the classifier. In addition, to evaluate the contribution of each indicator to WSD, permutation feature importance was calculated based on the trained classifier. Our analysis results showed significant importance of the following three out of the tested 32 factors: (1) WSD was significantly related to persons with evening tendency. (2) Daily activity rhythms and sleep were less stable in the WSD group than in the non-WSD group. (3) A specific day of the week had the highest importance in our data, suggesting that work habit contributes to WSD. These findings indicate some WSD factors: evening chronotype, instability of the daily activity rhythm, and differences in work habits on the specific day of the week. Thus, it is necessary to evaluate the rhythms of diurnal activities as well as sleep conditions to identify the WSD factors. In particular, the diurnal activity rhythm influences WSD. It is suggested that proper management of activity rhythm may contribute to the prevention of sleep debt.
机译:本研究通过比较从有和没有WSD的人员收集的活动数据来调查“平日睡眠债务(WSD)”的因素。由于据报道,睡眠债务的数量以及社会时钟和生物钟之间的差异与WSD相关,因此指定比率以后的WSD的因素可能有助于睡眠债务预防。我们招募了324名健康男性员工在同一家工作,并收集了他们的1周手腕活动数据并回答问卷。由于106名参与者由于演出数据的测量失败而被排除,所以剩余的218名参与者被列入分析中。所有参与者分为WSD或非WSD组,如果周末睡眠持续时间和平均平时睡眠时间之间的差异超过120分钟,则在其中有WDS的人。我们评估了从收集的戏曲数据中得出的多种测量,并训练了使用这些测量的预测WSD的存在的分类器。作为分类器采用支持向量机(SVM)。另外,为了评估每个指示器对WSD的贡献,基于训练的分类器计算置换特征重要性。我们的分析结果表明,在测试的32个因素中出现了以下三种因素的重要意义:(1)WSD与晚上倾向的人有关。 (2)每日活动节奏和睡眠在WSD组中比非WSD集团更稳定。 (3)本周的特定日子在我们的数据中具有最高的重要性,这表明工作习惯为WSD贡献。这些调查结果表明了一些WSD因素:晚间时间顺序,日常活动节奏的不稳定,以及在本周特定日期的工作习惯的差异。因此,有必要评估昼夜活动的节奏以及睡眠条件以识别WSD因素。特别是,昼夜活动节奏会影响WSD。建议适当管理活动节律可能有助于预防睡眠债务。

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