Trends in Strategic Napping in Surgical Residents by Gender, Postgraduate Year, Work Schedule, and Clinical Rotation

Devine, Jaime K; Schwartz, Lindsay P.; Hursh, Steven R.; Mosher, E; Schumacher, Sarah M.; Boyle, Lisa; Davis, Jonathan E.; Smith, Mark S.; Fitzgibbons, Shimae

doi:10.1016/j.jsurg.2020.11.010

Cited by 4 publications

(4 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Extended battery life and on-wrist scoring are two aspects of device design that should be considered if the wearable is intended for operational or epidemiological data collection where compliance, continuous data collection, and data security are concerns. The next step after laboratory validation testing of the Zulu watch will be to test its utility in real-world operations, not only to measure sleep compared to field actigraphy or self-report, but also to see how the Zulu watch measurements of sleep or sleep depth can be used to inform assumptions about sleep behavior in military, aviation, or healthcare workers, in order to predict fatigue risk and on-the-job performance [ 37 , 38 ].…”

Section: Discussionmentioning

confidence: 99%

Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation

Devine

Chinoy

Markwald

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

Traditional measures of sleep or commercial wearables may not be ideal for use in operational environments. The Zulu watch is a commercial sleep-tracking device designed to collect longitudinal sleep data in real-world environments. Laboratory testing is the initial step towards validating a device for real-world sleep evaluation; therefore, the Zulu watch was tested against the gold-standard polysomnography (PSG) and actigraphy. Eight healthy, young adult participants wore a Zulu watch and Actiwatch simultaneously over a 3-day laboratory PSG sleep study. The accuracy, sensitivity, and specificity of epoch-by-epoch data were tested against PSG and actigraphy. Sleep summary statistics were compared using paired samples t-tests, intraclass correlation coefficients, and Bland–Altman plots. Compared with either PSG or actigraphy, both the accuracy and sensitivity for Zulu watch sleep-wake determination were >90%, while the specificity was low (~26% vs. PSG, ~33% vs. actigraphy). The accuracy for sleep scoring vs. PSG was ~87% for interrupted sleep, ~52% for light sleep, and ~49% for deep sleep. The Zulu watch showed mixed results but performed well in determining total sleep time, sleep efficiency, sleep onset, and final awakening in healthy adults compared with PSG or actigraphy. The next step will be to test the Zulu watch’s ability to evaluate sleep in industrial operations.

show abstract

Section: Discussionmentioning

confidence: 99%

Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation

Devine

Chinoy

Markwald

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Because the sleep data collected in the papers analyzed were collected using two different methods, a further analysis was conducted to assess whether the form of data acquisition makes a difference to the sleep time recorded. Sleep times were recorded either by a wrist-worn actigraph [44][45][46][47][48][49][50][51][52][53], such as a FitBit, or through a questionnaire [54][55][56][57]. A boxplot (Figure 6) comparing the two methods shows that while the mean sleep times are similar, 6.1 and 6.6 h, respectively, the data collected by actigraph have a greater variance, with a value of 1.33 compared to a variance of 0.32 for data collected by a questionnaire.…”

Section: Comparison Of Data Collection Methodsmentioning

confidence: 99%

Insomnia—A Systematic Review and Comparison of Medical Resident’s Average Off-Call Sleep Times

Ardizzone

Lerchbaumer

Heinzel

et al. 2023

IJERPH

View full text Add to dashboard Cite

Sleep deprivation is known to have serious consequences, including a decrease in performance, attention and neurocognitive function. It seems common knowledge that medical residents are routinely sleep deprived, yet there is little objective research recording their average sleep times. To discern whether residents may be suffering from the abovementioned side effects, this review aimed to analyze their average sleep times. Thirty papers recording the average sleep time of medical residents were found via a literature search using the key words “resident” and “sleep”. An analysis of the mean sleep times cited therein revealed a range of sleep from 4.2 to 8.6 h per night, the median being 6.2 h. A sub-analysis of papers from the USA showed barely any significant differences in sleep time between the specialties, but the mean sleep times were below 7 h. The only significant difference (p = 0.039) was between the mean sleep times of pediatric and urology residents, with the former achieving less sleep. The comparison of methods for data collection showed no significant difference in the sleep times collected. The results of this analysis imply that residents are regularly sleep deprived and may therefore suffer from the abovementioned consequences.

show abstract

“…39 A recent line of research by our group has focused on modifying a biomathematical model of fatigue based on residents' own sleep patterns with the intent to create schedule mitigations which are tailored to the needs of the medical resident. These articles by Schwartz et al 40,41 and Devine et al 42 demonstrate the utility of fatigue modeling to identify areas of fatigue risk and evaluate how schedule changes could impact fatigue and performance. Devine et al, characterized the trends and patterns in medical resident sleep using actigraph-collected sleep data over two months.…”

Section: Modeling For Graduate Medical Educationmentioning

confidence: 99%

Addressing fatigue in medical residents with biomathematical fatigue modeling

Schwartz

Devine

Hursh

et al. 2021

Journal of Occupational Health

Self Cite

View full text Add to dashboard Cite

Fatigue in resident physicians has been identified as a factor that contributes to burnout and a decline in overall wellbeing. Fatigue risk exists because of poor sleep habits and demanding work schedules that have only increased due to the COVID‐19 pandemic. At this time, it is important not to lose sight of how fatigue can impact residents and how fatigue risk can be mitigated. While fatigue mitigation is currently addressed by duty hour restrictions and education about fatigue, Fatigue Risk Management Systems (FRMSs) offer a more comprehensive strategy for addressing these issues. An important component of FRMS in other shiftwork industries, such as aviation and trucking, is the use of biomathematical models to prospectively identify fatigue risk in work schedules. Such an approach incorporates decades of knowledge of sleep and circadian rhythm research into shift schedules, taking into account not just duty hour restrictions but the temporal placement of work schedules. Recent research has shown that biomathematical models of fatigue can be adapted to a resident physician population and can help address fatigue risk. Such models do not require subject matter experts and can be applied in graduate medical education program shift scheduling. It is important for graduate medical education program providers to consider these alternative methods of fatigue mitigation. These tools can help reduce fatigue risk and may improve wellness as they allow for a more precise fatigue management strategy without reducing overall work hours.

show abstract

Trends in Strategic Napping in Surgical Residents by Gender, Postgraduate Year, Work Schedule, and Clinical Rotation

Cited by 4 publications

References 32 publications

Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation

Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation

Insomnia—A Systematic Review and Comparison of Medical Resident’s Average Off-Call Sleep Times

Addressing fatigue in medical residents with biomathematical fatigue modeling

Contact Info

Product

Resources

About