Fatigue in transportation: NTSB investigations and safety recommendations

Marcus, Jeffrey H.; Rosekind, Mark R.

doi:10.1136/injuryprev-2015-041791

Cited by 53 publications

(34 citation statements)

References 5 publications

(1 reference statement)

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“…For example, high workload, sleep loss, circadian misalignment, and mode confusion are all examples of potential points of vulnerability, but when combined, the risk of operational failure increases. There are numerous examples of accidents that have occurred when highly trained individuals failed to perform while sleep deprived (Mitler et al, 1988;Marcus and Rosekind, 2016). In these cases, it was typically the convergence of many factors that led to the accident, with sleep loss or circadian misalignment being one point of vulnerability.…”

Section: Discussionmentioning

confidence: 99%

Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation

et al. 2020

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Exploration of deep space poses many challenges. Mission support personnel will not be immediately available to assist crewmembers performing complex operations on future long-duration exploration operations. Consequently, it is imperative that crewmembers have objective, reliable, and non-invasive metrics available to aid them in determining their fitness for duty prior to engaging in potentially dangerous tasks. The Robotics On-Board Trainer (ROBoT) task is NASA's platform for training astronauts to perform docking and grappling maneuvers. It is regularly used by crewmembers during spaceflight for refresher training. The operational ROBoT system, however, does not record data. Thus, a research version of ROBoT, called ROBoT-r, was developed so that operationally relevant data could be mined to provide feedback to crewmembers. We investigated whether ROBoT-r metrics would change according to sleep loss and circadian phase in a 28-h laboratory-based sleep deprivation study. Overall, participants showed improvement over time despite sleep loss, indicating continued learning. Performance on the psychomotor vigilance task (PVT) followed an expected profile, with reduced performance across the night. These findings suggest that individuals may be able to temporarily compensate for sleep loss to maintain performance on complex, novel tasks. It is possible that some ROBoT-r metrics may be sensitive to sleep loss after longer bouts of wakefulness or after individuals have habituated to the task. Studies with additional participants and extended pre-training on the ROBoT-r task should be conducted to disentangle how brain activity may change as individuals learn and habituate to complex tasks during sleep loss.

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Section: Discussionmentioning

confidence: 99%

Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation

et al. 2020

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“…However, high workload was considered less strenuous if breaks were allowed. Several respondents felt that fatigue could be conciously avoided by scheduling high priority tasks at times of peak performance (Avers & Johnson, 2011;Civil Aviation Safety Authority, 2012;Goode, 2003;Marcus & Rosekind, 2015). Another respondent argued that "grounding" oneself to take care of other personal or work related issues could be helpful.…”

Section: Table 1 Participant's Demographicsmentioning

confidence: 99%

Fatigue In Collegiate Aviation

Levin¹,

Mendonca²,

Keller³

et al. 2019

IJAAA

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“…[21] Besides, a continuation of chronic fatigue decreases health status and performance[22] and increases the risk of accidents and job disability. [2324]…”

Section: Introductionmentioning

confidence: 99%

Relationship between job stress and fatigue based on job demand-control-support model in hospital nurses

et al. 2019

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Background: This study aimed to examine nurses’ job stress based on Karasek's demand-control-support model and assess its relationship with different aspects of fatigue. Methods: This cross-sectional study was conducted on 522 nurses working in educational hospitals. Job stress dimensions and fatigue were measured by the Persian version of Job Content Questionnaire (JCQ) and Multidimensional Fatigue Inventory (MFI), respectively. Results: The results showed that psychological and physical job demands obtained high scores, but social support and decision latitude got low scores. MFI results indicated that the highest score was related to the general fatigue. Moreover, the results showed a significant positive relationship between psychological job demands and general fatigue, but a significant negative correlation to reduced activity. Conclusions: Considering the effects of job stress on nurses’ fatigue, it is necessary to develop a suitable interventional program for nurses in healthcare centers, especially hospitals, to decrease job stress and improve working conditions.

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Fatigue in transportation: NTSB investigations and safety recommendations

Cited by 53 publications

References 5 publications

Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation

Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation

Fatigue In Collegiate Aviation

Relationship between job stress and fatigue based on job demand-control-support model in hospital nurses

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