Maisey Gemma, Cattani Marcus, Devine Amanda, Lo Johnny, Dunican Ian C
School of Medical and Health Science, Edith Cowan University, Perth, WA, Australia.
School of Science, Edith Cowan University, Perth, WA, Australia.
Front Neurosci. 2021 Jan 7;14:579668. doi: 10.3389/fnins.2020.579668. eCollection 2020.
Shiftwork may adversely impact an individual's sleep-wake patterns and result in sleep loss (<6 h. following night shift), due to the circadian misalignment and the design of rosters and shifts. Within a mining operation, this sleep loss may have significant consequences due to fatigue, including an increased risk of accidents and chronic health conditions. This study aims to (i) determine the efficacy of an intervention that comprises a sleep education program and biofeedback through a smartphone app on sleep quality, quantity, and alertness (ii) determine the prevalence of risk for a potential sleep disorder, and (iii) quantify and describe the sleep habits and behaviors of shift workers in a remote mining operation. This study consists of a randomized controlled trial whereby eighty-eight shift workers within a remote mining operation are randomized to a control group or one of three different treatment groups that are: (i) a sleep education program, (ii) biofeedback on sleep through a smartphone app, or (iii) a sleep education program and biofeedback on sleep through a smartphone app. This study utilizes wrist-activity monitors, biomathematical modeling, and a survey instrument to obtain data on sleep quantity, quality, and alertness. A variety of statistical methods will determine the prevalence of risk for a potential sleep disorder and associations with body mass index, alcohol, and caffeine consumption. A generalized linear mixed model will examine the dependent sleep variables assessed at baseline and post-intervention for the control group and intervention groups, as well as within and between groups to determine changes. The findings from this study will contribute to the current understanding of sleep and alertness behaviors, and sleep problems and disorders amongst shift workers. Importantly, the results may inform fatigue policy and practice on interventions to manage fatigue risk within the mining industry. This study protocol may have a broader application in other shiftwork industries, including oil and gas, aviation, rail, and healthcare.
由于昼夜节律失调以及排班和轮班的设计,轮班工作可能会对个人的睡眠-清醒模式产生不利影响,并导致睡眠不足(夜班后睡眠时间<6小时)。在采矿作业中,这种睡眠不足可能会因疲劳而产生重大后果,包括事故风险增加和慢性健康问题。本研究旨在:(i)确定一项包括睡眠教育计划和通过智能手机应用程序进行生物反馈的干预措施对睡眠质量、睡眠时间和警觉性的效果;(ii)确定潜在睡眠障碍风险的患病率;(iii)量化和描述偏远采矿作业中班工人的睡眠习惯和行为。本研究包括一项随机对照试验,将偏远采矿作业中的88名轮班工人随机分为对照组或三个不同治疗组之一,这三个治疗组分别是:(i)睡眠教育计划;(ii)通过智能手机应用程序进行睡眠生物反馈;(iii)睡眠教育计划和通过智能手机应用程序进行睡眠生物反馈。本研究利用手腕活动监测器、生物数学模型和一项调查工具来获取关于睡眠时长、质量和警觉性的数据。多种统计方法将确定潜在睡眠障碍风险的患病率以及与体重指数、酒精和咖啡因摄入量的关联。一个广义线性混合模型将检查对照组和干预组在基线和干预后评估的相关睡眠变量,以及组内和组间的变量,以确定变化情况。本研究的结果将有助于增进目前对轮班工人睡眠和警觉行为、睡眠问题及障碍的理解。重要的是,这些结果可能为矿业中管理疲劳风险的干预措施的疲劳政策和实践提供参考。本研究方案可能在其他轮班工作行业有更广泛的应用,包括石油和天然气、航空、铁路和医疗保健行业。