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OBJECTIVE: To explore the scope of available research and to identify research gaps on in-vehicle interventions for drowsiness that utilize driver monitoring systems (DMS). BACKGROUND: DMS are gaining popularity as a countermeasure against drowsiness. However, how these systems can be best utilized to guide driver attention is unclear. METHODS: A scoping review was conducted in adherence to PRISMA guidelines. Five electronic databases (ACM Digital Library, Scopus, IEEE Xplore, TRID, and SAE Mobilus) were systematically searched in April 2022. Original studies examining in-vehicle drowsiness interventions that use DMS in a driving context (e.g., driving simulator and driver interviews) passed the screening. Data on study details, state detection methods, and interventions were extracted. RESULTS: Twenty studies qualified for inclusion. Majority of interventions involved warnings (n = 16) with an auditory component (n = 14). Feedback displays (n = 4) and automation takeover (n = 4) were also investigated. Multistage interventions (n = 12) first cautioned the driver, then urged them to take an action, or initiated an automation takeover. Overall, interventions had a positive impact on sleepiness levels, driving performance, and user evaluations. Whether interventions effective for one type of sleepiness (e.g., passive vs. active fatigue) will perform well for another type is unclear. CONCLUSION: Literature mainly focused on developing sensors and improving the accuracy of DMS, but not on the driver interactions with these technologies. More intervention studies are needed in general and for investigating their long-term effects. APPLICATION: We list gaps and limitations in the DMS literature to guide researchers and practitioners in designing and evaluating effective safety systems for drowsy driving.
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BACKGROUND: Given the complexity of the operating room (OR), it is unsurprising that surgeons frequently feel distracted while performing operative tasks. However, this relationship is not well studied in live surgeries. The objective of this study is to investigate the relationship between intraoperative distractions and technical events using surgical data. METHODS: Roux-en-Y gastric bypass operation data from three tertiary care hospitals in Toronto, Canada were collected prospectively between 2017 and 2019 by a comprehensive operative capture platform (OR Black Box) and analyzed retrospectively. Time-synchronized audiovisual recordings of the OR and laparoscopic videos of the operation were collected, along with clinical data from the electronic health record. Video data was labeled for technical data, non-technical data, and distractions by trained coders. Procedural steps were categorized based on criticality. The relationship between severe technical events (case having 0 or 1 events vs. 2 or more) and the rate of distractions (machine alarms, external communications, people entering/exiting) in critical procedural steps was assessed through logistic regression, adjusting for team factors (surgeons' technical skills, nurse changeovers). RESULTS: 60 Roux-en-Y cases were analyzed. Average case duration was 83.2 min (SD = 21.97). Distractions occurred 47.6 times/h (SD = 20.3), with most frequent distraction being machine alarms (4.45/10 min, SD = 2.88). For unadjusted analysis, alarms (OR = 1.29, 95% CI 1.05-1.66) and surgeon's technical skills (OR = 0.65, 95% CI 0.43-0.93) were found to be correlated with severe technical events. After adjusting for team factors, alarms were found to be positively related with the presence of severe technical events (OR = 1.58, 95% CI 1.18-2.33) during high-criticality procedural steps. CONCLUSIONS: This study showed a significant association between intraoperative distractions, in particular machine alarms, and severe technical events during high-criticality procedural steps. Further investigation will assess the temporal relationship between distractions and technical events and assess mitigation strategies to create a safer surgical environment.