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Practice parameters for the use of actigraphy in the military operational context: the Walter Reed Army Institute of Research Operational Research Kit-Actigraphy(WORK-A)
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作者 Jaime K.Devine Jake Choynowski +4 位作者 Tina Burke Kajsa Carlsson Vincent F.Capaldi Ashlee B.McKeon Walter J.Sowden 《Military Medical Research》 SCIE CSCD 2021年第1期103-115,共13页
Background: The Walter Reed Army Institute of Research(WRAIR) Operational Research Kit-Actigraphy(WORK-A) is a set of unique practice parameters and actigraphy-derived measures for the analysis of operational military... Background: The Walter Reed Army Institute of Research(WRAIR) Operational Research Kit-Actigraphy(WORK-A) is a set of unique practice parameters and actigraphy-derived measures for the analysis of operational military sleep patterns. The WORK-A draws on best practices from the literature and comprises 15 additional descriptive variables. Here, we demonstrate the WORK-A with a sample of United States Army Reserve Officers’ Training Corps(ROTC) cadets(n=286) during a month-long capstone pre-commissioning training exercise.Methods: The sleep of ROTC cadets(n=286) was measured by Philips Actiwatch devices during the 31-day training exercise. The preliminary effectiveness of the WORK-A was tested by comparing differences in sleep measures collected by Actiwatches as calculated by Philips Actiware software against WORK-A-determined sleep measures and self-report sleep collected from a subset of ROTC cadets(n=140).Results: Actiware sleep summary statistics were significantly different from WORK-A measures and self-report sleep(P≤0.001). Bedtimes and waketimes as determined by WORK-A major sleep intervals showed the best agreement with self-report bedtime(22:21±1:30 vs. 22:13±0:40, P=0.21) and waketime(04:30±2:17 vs. 04:31±0:47, P=0.68). Though still significantly different, the discrepancy was smaller between the WORK-A measure of time in bed(TIB) for major sleep intervals(352±29) min and self-report nightly sleep duration [(337±57) min, P=0.006] than that between the WORK-A major TIB and Actiware TIB [(177±42) min, P≤0.001].Conclusions: Default actigraphy methods are not the most accurate methods for characterizing soldier sleep, but reliable methods for characterizing operational sleep patterns is a necessary first step in developing strategies to improve soldier readiness. The WORK-A addresses this knowledge gap by providing practice parameters and a robust variety of measures with which to profile sleep behavior in service members. 展开更多
关键词 ACTIGRAPHY Sleep-wake patterns Military sleep assessment Operational environment Scoring methodology
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Sleep disturbances and predictors of nondeployability among active-duty army soldiers: an odds ratio analysis of medical healthcare data from fiscal year 2018 被引量:3
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作者 Jaime K.Devine Jacob Collen +1 位作者 Jake J.Choynowski Vincent Capaldi 《Military Medical Research》 SCIE CAS CSCD 2020年第3期335-342,共8页
Background:The impact of sleep disorders on active-duty soldiers’medical readiness is not currently quantified.Patient data generated at military treatment facilities can be accessed to create research reports and th... Background:The impact of sleep disorders on active-duty soldiers’medical readiness is not currently quantified.Patient data generated at military treatment facilities can be accessed to create research reports and thus can be used to estimate the prevalence of sleep disturbances and the role of sleep on overall health in service members.The current study aimed to quantify sleep-related health issues and their impact on health and nondeployability through the analysis of U.S.military healthcare records from fiscal year 2018(FY2018).Methods:Medical diagnosis information and deployability profiles(e-Profiles)were queried for all active-duty U.S.Army patients with a concurrent sleep disorder diagnosis receiving medical care within FY2018.Nondeployability was predicted from medical reasons for having an e-Profile(categorized as sleep,behavioral health,musculoskeletal,cardiometabolic,injury,or accident)using binomial logistic regression.Sleep e-Profiles were investigated as a moderator between other e-Profile categories and nondeployability.Results:Out of 582,031 soldiers,48.4%(n=281,738)had a sleep-related diagnosis in their healthcare records,9.7%(n=56,247)of soldiers had e-Profiles,and 1.9%(n=10,885)had a sleep e-Profile.Soldiers with sleep e-Profiles were more likely to have had a motor vehicle accident(p OR(prevalence odds ratio)=4.7,95%CI 2.63–8.39,P≤0.001)or work/duty-related injury(p OR=1.6,95%CI 1.32–1.94,P≤0.001).The likelihood of nondeployability was greater in soldiers with a sleep e-Profile and a musculoskeletal e-Profile(p OR=4.25,95%CI 3.75–4.81,P≤0.001)or work/dutyrelated injury(p OR=2.62,95%CI 1.63–4.21,P≤0.001).Conclusion:Nearly half of soldiers had a sleep disorder or sleep-related medical diagnosis in 2018,but their sleep problems are largely not profiled as limitations to medical readiness.Musculoskeletal issues and physical injury predict nondeployability,and nondeployability is more likely to occur in soldiers who have sleep e-Profiles in addition to these issues.Addressing sleep problems may prevent accidents and injuries that could render a soldier nondeployable. 展开更多
关键词 Medical readiness Behavioral sleep medicine Deployability Healthcare records Military Big data Data mining
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