Purpose of review Our 24/7 society is dependent on shift work, despite mounting evidence for negative health outcomes from sleep displacement due to shift work. This paper reviews short- and long-term health consequences of sleep displacement and circadian misalignment due to shift work. Recent findings We focus on four broad health domains: metabolic health; risk of cancer; cardiovascular health; and mental health. Circadian misalignment affects these domains by inducing sleep deficiency, sympathovagal and hormonal imbalance, inflammation, impaired glucose metabolism, and dysregulated cell cycles. This leads to a range of medical conditions, including obesity, metabolic syndrome, type II diabetes, gastrointestinal dysfunction, compromised immune function, cardiovascular disease, excessive sleepiness, mood and social disorders, and increased cancer risk. Summary Interactions of biological disturbances with behavioral and societal factors shape the effects of shift work on health and well-being. Research is needed to better understand the underlying mechanisms and drive the development of countermeasures.

Research Summary Race‐related debates often assume that implicit racial bias will result in racially biased decisions to shoot. Previous research has examined racial bias in police decisions by pressing “shoot” or “don't‐shoot” buttons in response to pictures of armed and unarmed suspects. As a result of its lack of external validity, however, this methodology provides limited insight into officer behavior in the field. In response, we conducted the first series of experimental research studies that tested police officers and civilians in strikingly realistic deadly force simulators. Policy Implications This article reports the results of our most recent experiment, which tested 80 police patrol officers by applying this leading edge method. We found that, despite clear evidence of implicit bias against Black suspects, officers were slower to shoot armed Black suspects than armed White suspects, and they were less likely to shoot unarmed Black suspects than unarmed White suspects. These findings challenge the assumption that implicit racial bias affects police behavior in deadly encounters with Black suspects.

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Objective: To demonstrate that psychophysiology may have applications for objective assessment of expertise development in deadly force judgment and decision making (DFJDM).Background: Modern training techniques focus on improving decision-making skills with participative assessment between trainees and subject matter experts primarily through subjective observation. Objective metrics need to be developed. The current proof of concept study explored the potential for psychophysiological metrics in deadly force judgment contexts.Method: Twenty-four participants (novice, expert) were recruited. All wore a wireless Electroencephalography (EEG) device to collect psychophysiological data during high-fidelity simulated deadly force judgment and decision-making simulations using a modified Glock firearm. Participants were exposed to 27 video scenarios, one-third of which would have justified use of deadly force. Pass/fail was determined by whether the participant used deadly force appropriately.Results: Experts had a significantly higher pass rate compared to novices (p < 0.05). Multiple metrics were shown to distinguish novices from experts. Hierarchical regression analyses indicate that psychophysiological variables are able to explain 72% of the variability in expert performance, but only 37% in novices. Discriminant function analysis (DFA) using psychophysiological metrics was able to discern between experts and novices with 72.6% accuracy.Conclusion: While limited due to small sample size, the results suggest that psychophysiology may be developed for use as an objective measure of expertise in DFDJM. Specifically, discriminant function measures may have the potential to objectively identify expert skill acquisition.Application: Psychophysiological metrics may create a performance model with the potential to optimize simulator-based DFJDM training. These performance models could be used for trainee feedback, and/or by the instructor to assess performance objectively.