Exercise before bed does not impact sleep inertia in young healthy males.

Sleep inertia is the transitional state marked by impaired cognitive performance and reduced vigilance upon waking. Exercising before bed may increase the amount of slow-wave sleep within the sleep period, which has previously been associated with increased sleep inertia. Healthy males (n = 12) spent 3 nights in a sleep laboratory (1-night washout period between each night) and completed one of the three conditions on each visit - no exercise, aerobic exercise (30 min cycling at 75% heart rate), and resistance exercise (six resistance exercises, three sets of 10 repetitions). The exercise conditions were completed 90 min prior to bed. Sleep was measured using polysomnography. Upon waking, participants completed five test batteries every 15 min, including the Karolinska Sleepiness Scale, a Psychomotor Vigilance Task, and the Spatial Configuration Task. Two separate linear mixed-effects models were used to assess: (a) the impact of condition; and (b) the amount of slow-wave sleep, on sleep inertia. There were no significant differences in sleep inertia between conditions, likely as a result of the similar sleep amount, sleep structure and time of awakening between conditions. The amount of slow-wave sleep impacted fastest 10% reciprocal reaction time on the Psychomotor Vigilance Task only, whereby more slow-wave sleep improved performance; however, the magnitude of this relationship was small. Results from this study suggest that exercise performed 90 min before bed does not negatively impact on sleep inertia. Future studies should investigate the impact of exercise intensity, duration and timing on sleep and subsequent sleep inertia.

Effects of fatigue on teams and their role in 24/7 operations.

In 24/7 operations, fatigue from extended work hours and shift work is ubiquitous. Fatigue is a significant threat to performance, productivity, safety, and well-being, and strategies for managing fatigue are an important area of research. At the level of individuals, the effects of fatigue on performance are relatively well understood, and countermeasures are widely available. At the level of organizations, the effects of fatigue are also relatively well understood, and organizational approaches to fatigue risk management are increasingly well documented. However, in most organizational settings, individuals work in teams, and teams are the building blocks of the organizational enterprise. Yet, little is known about the effects of fatigue on team functioning. Here we discuss the effects of fatigue at the levels of individuals, teams, and organizations, and how the consequences of fatigue cross these levels to impact overall productivity and safety. Furthermore, we describe the pivotal role of teams in understanding the adverse organizational effects of fatigue in 24/7 operations and argue that teams may be leveraged to mitigate these effects. Systematic investigation of the effects of fatigue on teams is a promising avenue toward advances in fatigue risk management and provide some ideas for how this may be approached.

Does Implementation of Biomathematical Models Mitigate Fatigue and Fatigue-related Risks in Emergency Medical Services Operations? A Systematic Review.

BACKGROUND: Work schedules like those of Emergency Medical Services (EMS) personnel have been associated with increased risk of fatigue-related impairment. Biomathematical modeling is a means of objectively estimating the potential impacts of fatigue on performance, which may be used in the mitigation of fatigue-related safety risks. In the context of EMS operations, our objective was to assess the evidence in the literature regarding the effectiveness of using biomathematical models to help mitigate fatigue and fatigue-related risks. METHODS: A systematic review of the evidence evaluating the use of biomathematical models to manage fatigue in EMS personnel or similar shift workers was performed. Procedures proposed by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology were used to summarize and rate the certainty in the evidence. Potential bias attached to retained studies was documented using the Cochrane Collaboration's Risk of Bias tool for experimental studies. RESULTS: The literature search strategy, which focused on both EMS personnel and non-EMS shift workers, yielded n = 2,777 unique records. One paper, which investigated non-EMS shift workers, met inclusion criteria. As part of a larger effort, managers and dispatchers of a trucking operation were provided with monthly biomathematical model analyses of predicted fatigue in the driver workforce, and educated on how they could reduce predicted fatigue by means of schedule adjustments. The intervention showed a significant reduction in the number and cost of vehicular accidents during the period in which biomathematical modeling was used. The overall GRADE assessment of evidence quality was very low due to risk of bias, indirectness, imprecision, and publication bias. CONCLUSIONS: This systematic review identified no studies that investigated the impact of biomathematical models in EMS operations. Findings from one study of non-EMS shift workers were favorable toward use of biomathematical models as a fatigue mitigation scheduling aid, albeit with very low quality of evidence pertaining to EMS operations. We propose three focus areas of research priorities that, if addressed, could help better elucidate the utility and impact of biomathematical models as a fatigue-mitigation tool in the EMS environment.

A combined field and laboratory design for assessing the impact of night shift work on police officer operational performance.

OBJECTIVES: This study assessed the utility of a combined field and laboratory research design for measuring the impact of consecutive night shift work on the sleepiness, vigilance, and driving performance of police patrol officers. DESIGN: For police patrol officers working their normal night shift duty cycles, simulated driving performance and psychomotor vigilance were measured in a laboratory on two separate occasions: in the morning after the last of five consecutive 10.7-h night shifts, and at the same time in the morning after three consecutive days off duty. Order of participation in conditions was randomized among subjects. SETTING: Subjects experienced manipulation of sleep schedules due to working night shifts in a real operational environment, but performance testing was conducted under controlled laboratory conditions. PARTICIPANTS: N = 29 active-duty police patrol officers (27 male, 2 female; age 37.1 ± 6.3 years) working night shift schedules participated in this study. RESULTS: Simulated driving performance, psychomotor vigilance, and subjective sleepiness were significantly degraded following 5 consecutive night shifts as compared to 3 consecutive days off duty, indicating that active-duty police officers are susceptible to performance degradation as a consequence of working nights. CONCLUSIONS: This combined field and laboratory research design succeeded in bridging the gap between the realism of the operational environment and the control of laboratory performance testing, demonstrating that this is a useful approach for addressing the relationship between shift work induced fatigue and critical operational task performance.