Personality Traits and Insomnia Symptoms in Shift Workers

The discrepancy between natural sleep-wake rhythm and actual sleep times in shift workers can cause sleep loss and negative daytime consequences. Irregular shift schedules do not follow a fixed structure and change frequently, which makes them particularly harmful and makes affected individuals more susceptible to insomnia. The present study compares insomnia symptoms of non-shift workers, regular shift workers, and irregular shift workers and takes into account the moderating role of the Big Five personality traits and levels of perfectionism. Employees of an Austrian railway company completed an online survey assessing shift schedules, sleep quality and duration, daytime sleepiness, and personality traits. A total of 305 participants, of whom 111 were non-shift workers, 60 regular shift workers, and 134 irregular shift workers, made up the final sample. Irregular shift workers achieved significantly worse scores than one or both of the other groups in time in bed, total sleep time, sleep efficiency, sleep duration, sleep quality, sleep latency, and the number of awakenings. However, the values of the irregular shifts workers are still in the average range and do not indicate clinical insomnia. Participants working regular shifts reported the best sleep quality and longest sleep duration and showed the least nocturnal awakenings, possibly due to higher conscientiousness- and lower neuroticism scores in this group. Agreeableness increased the effect of work schedule on total sleep time while decreasing its effect on the amount of sleep medication taken. Perfectionism increased the effect of work schedule on time in bed and total sleep time. Generalization of results is limited due to the high percentage of males in the sample and using self-report measures only.

Longer Work Shifts, Faster Forward Rotation—More Sleep and More Alert in Aircraft Inspection

The purpose of this intervention study is to compare sleep, alertness, and work ability among aircraft inspectors working under two different shift schedules. The original schedule was forward rotating: MMM – – EEE – NNN – – – (M = morning, E = evening, N = night, – = day off). The new schedule was fast forward rotating: MEN – – with 10-h shifts. The baseline data were collected before the schedule changed, and the follow-up data 12 months (n = 10, Group A) or 5 months (n = 13, Group B) after the change. Three of subjects were women and average age was 46.6 years (range 31–58). The surveys included questions on sleep quantity, sleep quality, severe sleepiness, alertness, perceived stress, current work ability, and satisfaction with the shift schedule. The results indicated that in the new schedule, the sleeping times were longer and sleep loss was less. Moreover, shift specific severe sleepiness decreased, and alertness during shifts improved. Compared to baseline, perceived stress was lower and work ability was better. Satisfaction with the shift system had also improved. To conclude, the quickly forward rotating shift system might be beneficial in terms of increased sleep length and improved alertness and overall well-being especially among older aircraft inspectors.

Prediction Of Shiftworker Alertness, Sleep, And Circadian Phase Using A Model Of Arousal Dynamics Constrained By Shift Schedules And Light Exposure

Study Objectives The study aimed to, for the first time, (i) compare sleep, circadian phase, and alertness of Intensive Care Unit (ICU) nurses working rotating shifts with those predicted by a model of arousal dynamics; and (ii) investigate how different environmental constraints affect predictions and agreement with data. Methods The model was used to simulate individual sleep-wake cycles, urinary 6-sulphatoxymelatonin (aMT6s) profiles, subjective sleepiness on the Karolinska Sleepiness Scale (KSS), and performance on a Psychomotor Vigilance Task (PVT) of 21 ICU nurses working day, evening, and night shifts. Combinations of individual shift schedules, forced wake time before/after work and lighting, were used as inputs to the model. Predictions were compared to empirical data. Simulations with self-reported sleep as an input were performed for comparison. Results All input constraints produced similar prediction for KSS, with 56-60% of KSS scores predicted within ±1 on a day and 48-52% on a night shift. Accurate prediction of an individual’s circadian phase required individualised light input. Combinations including light information predicted aMT6s acrophase within ±1 h of the study data for 65% and 35-47% of nurses on diurnal and nocturnal schedules. Minute-by-minute sleep-wake state overlap between the model and the data was between 81±6% and 87±5% depending on choice of input constraint. Conclusions The use of individualised environmental constraints in the model of arousal dynamics allowed for accurate prediction of alertness, circadian phase and sleep for more than half of the nurses. Individual differences in physiological parameters will need to be accounted for in the future to further improve predictions.

056 Effects of Simulated Shift Schedules on Visual Search

Introduction Visual search is important in many operational tasks, such as passive sonar monitoring in naval operations. Shift work can contribute to fatigue and task performance impairment; in particular, backward rotating shift schedules have been shown to impair vigilant attention performance. However, the impact on visual search performance, above and beyond impaired vigilant attention, is unknown. We investigated the effects of two distinct shift work schedules using a visual search task with properties of real-life visual search performance. Methods N=13 adult males (ages 18–39) completed a 6-day/5-night laboratory study with an acclimation day, four simulated shift days, and a recovery day. Shift days involved either a 5h-on/15h-off backward rotating schedule (n=8) or a 3h-on/9h-off fixed schedule (n=5). The visual search task was performed once per shift at varying time of day depending on shift. Participants viewed search arrays where stimuli consisted of colored letters of different shapes. Over three trial blocks of 24 trials each, participants determined if a target was present or absent among 1, 5, 15, or 30 distractors. Similarity between targets and distractors was manipulated between blocks, such that targets differed from distractors by color only, shape only, or either color or shape but not both. For each distinct target feature block, and separately for presence or absence of a target, slopes of response times regressed against number of stimuli were calculated to quantify visual search rates. Mixed-effects ANOVA was used to analyze visual search rates by shift schedule and shift day. Results There were no significant effects of shift schedule (all p>0.30), shift day (all p>0.13), or their interaction (all p>0.22) on visual search rates. Conclusion Previous work showed degraded vigilant attention in the shift schedules considered here, especially in the backward rotating schedule, which may compromise operational performance. However, while our sample may have been too small to have adequate statistical power, we failed to identify specific impairments in visual search with statistical significance. It remains to be determined whether greater levels of fatigue, such as could be induced by total sleep deprivation, would reveal significant visual search deficits. Support (if any) Naval Postgraduate School award N62271-13-M-1228

Integrating Gear Shifting Preference into Personalized Shift-Scheduling Calibration

Shift-scheduling calibration of automatic transmission (AT) vehicles is vital for both driving experience and automobile industry. Shifting schedules are usually calibrated with the consideration of fuel economy and drivability while neglecting the individual driving preference. In this work, we propose to exemplify the individual shifting preference by integrating the manual transmission (MT) shifting habit into the AT shift-scheduling calibration, where the habit is reflected as the shifting points and is available in most automated manual transmission (AMT) vehicles. The automated calibration of AT shifting schedules is directed by using the particle swarm optimization (PSO), during the virtual automobile cycle test, i.e., FTP-72. Candidate shifting-schedules are generated in the overlapped zone of MT shifting points and the space around the base map, and are evaluated on both shifting quality and fuel economy. Through iterations, the generated candidate shift schedules are tested and assessed until the overall performance reach the optimum. Experimental results are presented to show the effectiveness of the proposed method, which retains the shifting preferences as well as enhances the performance index by about 5%, 4%, and 2% for the drivers with aggressive, moderate, and mild styles, respectively.

Shift Work Disorder, Insomnia, and Depression among Offshore Oil Rig Workers

Objective: Numerous offshore jobs require 24-hour tasks, such as in industrial workplaces (eg, oil rigs). The purpose of this study was to assess shift work disorder (SWD), insomnia, daytime sleepiness, and depression among Iranian offshore oil rig workers in different shift schedules. Method: This cross-sectional study was conducted on Iranian offshore oil workers at the Persian Gulf. A questionnaire package consisted of Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Beck Depression Inventory (BDI- II), and SWD filled. The scores were calculated among different groups of shift schedules (fixed-day, fixed-night, swing and standby shift workers). ISI, BDI-II, and ESS scores were also compared between individuals with or without SWD. Results: A total of 188 participants were recruited in the study, and all were male. The mean age was 37.06 ± 9.2 years. Among different shift schedules, the highest and lowest ISI and ESS scores were related to fixed-night shifts workers and fixed-day shift workers, respectively. ISI, ESS, and BDI mean scores in different shift schedules were not significantly different (p values = 0.14, 0.57, and 0.93, respectively). SWD was diagnosed in 57 (30.3%) of studied shift workers. The difference between SWD prevalence was not significant between different shift schedules (P value =0.13). Workers with SWD had higher ISI, ESS, and BDI-II score (P values <0.0001, <0.0001, and <0.0001, respectively) and workers without SWD had higher job satisfaction (p value = 0.04). Conclusion: SWD is considered as a serious health-related issue in Persian Gulf oil rig shift workers. Insomnia, daytime sleepiness, and depression are associated with SWD.

Sleep-Related Problems in Night Shift Nurses: Towards an Individualized Interventional Practice

Rotating shifts (mostly 8- or 12-h) are common among nurses to ensure continuity of care. This scheduling system encompasses several adverse health and performance consequences. One of the most injurious effects of night-time shift work is the deterioration of sleep patterns due to both circadian rhythm disruption and increased sleep homeostatic pressure. Sleep problems lead to secondary effects on other aspects of wellbeing and cognitive functioning, increasing the risk of errors and workplace accidents. A wide range of interventions has been proposed to improve the sleep quality of nurses and promote an increase in attention levels. In recent years, particular attention has been paid to individual and environmental factors mediating the subjective ability to cope with sleep deprivation during the night shift. Given the predictive role of these factors on the negative impact of a night shift, an individualized intervention could represent an effective countermeasure by ensuring suitable management of shift schedules. Therefore, the aims of this mini-review are to: (a) provide an updated overview of the literature on sleep problems in night shift nurses and their adverse consequences; and (b) critically analyze the psychosocial factors that mediate the negative impact of shift work with the ultimate goal of defining an effective countermeasure based on an individualized approach.

Reducing Handoffs and Improving Patient Flow in the ED

Over 145 million people visit US Emergency Departments annually. The diverse nature and overwhelming volume of patient visits make the ED one of the most complicated healthcare settings. In particular, handoffs, the transfer of patient care from one physician to another during shift transition are a common source of errors resulting from workflow interruptions and high cognitive workload. This research focuses on developing a hybrid agent-based discrete event simulation model to identify physician shifts that minimize handoffs without affecting other performance metrics. By providing overlapping shift schedules as well as implementing policies that restrict physicians from signing up a new patient during the last hour of the shift, we observed that handoffs and patient time in the emergency department could be reduced by as much as 42% and 17%, respectively.