BackgroundUS military service members have characteristically poor sleep, even when ‘in garrison’ or at one’s home base. The physical sleeping environment, which is often poor in military-provided housing or barracks, may contribute to poor sleep quality in soldiers. The current study aimed to assess whether the sleeping environment in garrison is related to sleep quality, insomnia risk and military readiness.MethodsSeventy-four US army special operations soldiers participated in a cross-sectional study. Soldiers were queried on their sleeping surface comfort and the frequency of being awakened at night by excess light, abnormal temperatures and noise. Subjective sleep quality and insomnia symptoms were also queried, via the Pittsburgh Sleep Quality Index and Insomnia Severity Index, respectively. Lastly, measures of soldier readiness, including morale, motivation, fatigue, mood and bodily pain, were assessed.ResultsSoldiers reporting temperature-related and light-related awakenings had poorer sleep quality higher fatigue and higher bodily pain than soldiers without those disturbances. Lower ratings of sleeping surface comfort were associated with poorer sleep quality and lower motivation, lower morale, higher fatigue and higher bodily pain. Each 1-point increase in sleeping surface comfort decreased the risk for a positive insomnia screen by 38.3%, and the presence of temperature-related awakenings increased risk for a positive insomnia screen by 78.4%. Those living on base had a poorer sleeping environment than those living off base.ConclusionOptimising the sleep environment—particularly in on-base, military-provided housing—may improve soldier sleep quality, and readiness metrics. Providers treating insomnia in soldiers should rule out environment-related sleep disturbances prior to beginning more resource-intensive treatment.

Subjective well-being is a positive psychological construct that has important implications for the U.S. Military's goal to develop service members' strengths and support their overall thriving and downstream resilience. Despite this, the concept of well-being has not been well studied in military populations who have unique work demands, stressors, and autonomy/agency in daily life compared to civilians. To address this shortcoming in the literature, the present study assessed Ryff's measures of psychological well-being (PWB) in 1,333 U.S. service members prior to the deployments in the Middle East. Various methods attempting to validate the theoretical model purported by Ryff were unsuccessful, and exploratory factor analyses did not result in a novel model for this population. Future research should continue to evaluate proposed models of soldier well-being and propose novel theories, as well as measures, to assess this important construct. Implications are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

BACKGROUND: Although multiple studies have documented the impact of insufficient sleep on soldier performance, most studies have done so using artificial measures of performance (e.g., tablet or simulator tests). The current study sought to test the relationship between sleep and soldier performance during infantry battle drill training, a more naturalistic measure of performance.METHODS: Subjects in the study were 15 junior Special Operations infantry soldiers. Soldiers wore an actigraph and reported their subjective sleep duration and quality prior to close quarter battle (CQB) drills. Experienced leaders monitored each iteration of the CQB exercise and recorded the number of errors committed.RESULTS: The number of errors committed during the live ammunition iterations was negatively correlated with subjective number of hours slept and subjective sleep efficiency/quality during the month prior. Soldiers with subjective sleep duration ≥7 h had a significantly lower number of errors than soldiers with subjective sleep duration <7 h (1.71 vs. 0.63 errors), and soldiers with sleep quality <85% committed more errors than those with sleep quality ≥85% (1.50 vs. 0.40 errors).DISCUSSION: These data preliminarily suggest that sleep quality and duration may influence subsequent performance on infantry battle drill training, particularly for soldiers with limited experience in battle drill conduction who have not yet perfected battle drill techniques. Future studies should enact sleep augmentation to determine the causal influence of sleep on performance in this setting.Mantua J, Shevchik JD, Chaudhury S, Eldringhoff HP, Mickelson CA, McKeon AB. Sleep and infantry battle drill performance in Special Operations soldiers. Aerosp Med Hum Perform. 2022; 93(7):557-561.

Importance:Insomnia is common after traumatic brain injury (TBI) and contributes to morbidity and long-term sequelae. Objective:To identify unique trajectories of insomnia in the 12 months after TBI. Design, Setting, and Participants:In this prospective cohort study, latent class mixed models (LCMMs) were used to model insomnia trajectories over time and to classify participants into distinct profile groups. Data from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, a longitudinal, multisite, observational study, were uploaded to the Federal Interagency Traumatic Brain Injury Repository (FITBIR) database. Participants were enrolled at 1 of 18 participating level I trauma centers and enrolled within 24 hours of TBI injury. Additional data were obtained directly from the TRACK-TBI investigators that will be uploaded to FITBIR in the future. Data were collected from February 26, 2014, to August 8, 2018, and analyzed from July 1, 2020, to November 15, 2021. Exposures:Traumatic brain injury. Main Outcomes and Measures:Insomnia Severity Index assessed serially at 2 weeks and 3, 6, and 12 months thereafter. Results:The final sample included 2022 participants (1377 [68.1%] men; mean [SD] age, 40.1 [17.2] years) from the FITBIR database and the TRACK-TBI study. The data were best fit by a 5-class LCMM. Of these participants, 1245 (61.6%) reported persistent mild insomnia symptoms (class 1); 627 (31.0%) initially reported mild insomnia symptoms that resolved over time (class 2); 91 (4.5%) reported persistent severe insomnia symptoms (class 3); 44 (2.2%) initially reported severe insomnia symptoms that resolved by 12 months (class 4); and 15 (0.7%) initially reported no insomnia symptoms but had severe symptoms by 12 months (class 5). In a multinomial logistic regression model, several factors significantly associated with insomnia trajectory class membership were identified, including female sex (odds ratio [OR], 1.65 [95% CI, 1.02-2.66]), Black race (OR, 2.36 [95% CI, 1.39-4.01]), history of psychiatric illness (OR, 2.21 [95% CI, 1.35-3.60]), and findings consistent with intracranial injury on computed tomography (OR, 0.36 [95% CI, 0.20-0.65]) when comparing class 3 with class 1. Conclusions and Relevance:These results suggest important heterogeneity in the course of insomnia after TBI in adults. More work is needed to identify outcomes associated with these insomnia trajectory class subgroups and to identify optimal subgroup-specific treatment approaches.

To examine the relation between acute biomarkers of neuronal injury and trajectories of insomnia following traumatic brain injury (TBI)

There are replicable inter-individual differences in cognitive responsivity to sleep loss. Genetic allele variations have been linked with behavioral differences in cognitive performance under these conditions, yet less burdensome tests or screeners are not available. This study tested whether a survey can classify U.S. Army Soldiers as cognitively vulnerable or resilient to sleep loss and whether Soldiers in these differentiated groups have the expected allele variants. Six genetic targets were sequenced from 75 Soldiers. Cognition was tested after a night of total sleep deprivation during a military exercise. The Iowa Resilience to Sleeplessness Test (iREST) was administered. A Wilcoxon Rank Sum test showed the iREST score of 2.5/5 differentiated groups behaviorally on all cognitive tests. Chi-squared tests showed that for the Catechol-O-Methyltransferase (COMT) gene, 82% of behaviorally vulnerable soldiers had alleles linked with vulnerability, compared with 41% of behaviorally genetic soldiers. If these findings are replicated, the iREST could be used to help military leaders make decisions about personnel placement when sleep loss is unavoidable.

Describe the prevalence of insomnia in TBI patients, understand separate trajectories of patient populations who suffer Insomnia post-TBI and discuss how post-TBI insomnia might be targeted for therapeutic trials.

In 2017, USS Fitzgerald and USS John S. McCain, both guided-missile destroyers, experienced underway collisions that resulted in the deaths of 17 Sailors and degradation of national defense as two warships were removed from the frontline. This incident garnered Congress’ attention leading to numerous fatigue management policies and working groups instituted at various levels across the Department of Defense. One policy of the Department of the Navy (3120.2A; Dec 11, 2020) specifically addressed risk mitigation factors for maritime operations occurring in the overnight and early morning hours around the circadian nadir or trough in alertness and vigilance. Despite these circadian challenges that come with mission demands of military service, there are many opportunities as outlined in the Department of Navy policy to reduce and/or eliminate the performance-related risks associated with circadian misalignment. In regard to actionable systems and processes aligned with these policies, the first step is to perform a risk assessment to identify circadian-related problems that could arise in response to conducting the military training exercise or operation. The second step is to integrate a means to monitor 24-hour physiology, mitigate performance risk through fatigue countermeasures, and/or re-align the circadian timing system of military personnel to enhance sleep, manage fatigue, and optimize performance. Most importantly, the approach is not a one size fits all. Each military operation will require unique adaption (re-alignment) to the environment and each military operation may require a unique countermeasure(s).

Introduction Although multiple studies have documented the impact of insufficient sleep on Soldier performance, most studies have done so using artificial measures of performance (e.g., tablet or simulator tests). The current study sought to test the relationship between sleep and Soldier performance during infantry battle drill training, a more naturalistic measure of performance. Methods Fifteen junior special operations infantry Soldiers participated in the study. Soldiers wore Phillips Actiwatch Spectrum and reported their subjective sleep duration and quality during the week prior to Close Quarters Battle (CQB) drills. CQB training emphasizes close quarter combat tactics and requires a diverse range of cognitive skills (e.g., memory, decision-making, scanning). Each team of Soldiers performed six iterations of CQB – three using Ultimate Training Munitions (UTM; non-lethal rounds of munition) and three with live ammunition. Experienced leaders monitored each iteration and recorded errors on scorecards that are regularly used by the unit during CQB trainings. Results Participating Soldiers were all male and were 24.3 ± 3.82 years old. Soldiers slept an average of 6.6 hours per night leading up to the exercise and had an average sleep efficiency of 82/100%. The average number of errors committed during the UTM trials was 2.5 ± 1.9, and the average number of errors during the live ammunition trials was 1.1 ± 1.1. The number of errors committed during the live ammunition iterations was negatively correlated with subjective number of hours slept (r = -.67, p = .006) and subjective sleep efficiency/quality (r = -.55, p = .03). A t-test showed those with subjective sleep duration ≥ 7 hours had a significantly lower number of errors than Soldiers with subjective sleep duration < 7 hours (t(14) = 2.26, p = .04). Conclusion Enhancing infantry battle drill performance during training may directly translate to greater success in combat scenarios. These data preliminarily suggest that sleep quality and duration may influence subsequent performance on infantry battle drill training, particularly for Soldiers with limited experience in battle drill conduction who have not yet perfected battle drill techniques. Future studies should enact sleep augmentation to determine the causal influence of sleep on performance in this setting. Support (If Any) Support for this study came from the Military Operational Medicine Research Program (MOMRP) of the United States Army Medical Research and Development Command (USAMRDC). Material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors, and are not to be construed as official, or as reflecting true views of the Department of the Army or the Department of Defense. The investigators have adhered to the policies for protection of human subjects as prescribed in AR 70–25. The authors have no conflicts of interest to disclose.

Abstract Introduction Sleep loss that is inherent to military operations can lead to cognitive errors and potential mission failure. Single Nucleotide Polymorphisms (SNPs) allele variations of several genes (COMT, ADORA2A, TNFa, CLOCK, DAT1) have been linked with inter-individual cognitive resilience to sleep loss through various mechanisms. U.S. Army Soldiers with resilience-related alleles may be better-suited to perform cognitively-arduous duties under conditions of sleep loss than those without these alleles. However, military-wide genetic screening is costly, arduous, and infeasible. This study tested whether a brief survey of subjective resilience to sleep loss (1) can demarcate soldiers with and without resilience-related alleles, and, if so, (2) can predict cognitive performance under conditions of sleep loss. Methods Six SNPs from the aforementioned genes were sequenced from 75 male U.S. Army special operations Soldiers (age 25.7±4.1). Psychomotor vigilance, response inhibition, and decision-making were tested after a night of mission-driven total sleep deprivation. The Iowa Resilience to Sleeplessness Test (iREST) Cognitive Subscale, which measures subjective cognitive resilience to sleep loss, was administered after a week of recovery sleep. A receiver operating characteristic (ROC) curve was used to determine whether the iREST Cognitive Subscale can discriminate between gene carriers, and a cutoff score was determined. Cognitive performance after sleep deprivation was compared between those below/above the cutoff score using t-tests or Mann-Whitney U tests. Results The iREST discriminated between allele variations for COMT (ROC=.65,SE=.07,p=.03), with an optimal cutoff score of 3.03 out of 5, with 90% sensitivity and 51.4% specificity. Soldiers below the cutoff score had significantly poorer for psychomotor vigilance reaction time (t=-2.39,p=.02), response inhibition errors of commission (U=155.00,W=246.00,p=.04), and decision-making reaction time (t=2.13,p=.04) than Soldiers above the cutoff score. Conclusion The iREST Cognitive Subscale can discriminate between those with and without specific vulnerability/resilience-related genotypes. If these findings are replicated, the iREST Cognitive Subscale could be used to help military leaders make decisions about proper personnel placement when sleep loss is unavoidable. This would likely result in increased safety and improved performance during military missions. Support (if any) Support for this study came from the Military Operational Medicine Research Program of the United States Army Medical Research and Development Command.

Abstract Introduction Insufficient sleep is ubiquitous among active duty service members in operational settings. Although insufficient sleep has been linked to poor cognitive, psychological, and physiological outcomes in military populations, little research has investigated the impact of insufficient sleep on Soldier occupational wellbeing. This study examined the longitudinal association between sleep quality and occupational functioning in a population of active duty U.S. Army Soldiers. Methods Sixty male Soldiers (age 25.41±3.74 years) participated. Sleep quality and occupational outcomes were assessed four weeks apart (before and after an annual training mission). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Occupational outcome measures included the Emotional Exhaustion Scale, Walter Reed Functional Impairment Short Scale, Role Overload Scale, and Perceived Stress Scale. Linear regressions assessed the prediction of PSQI Global Score on occupational outcome scores. Student’s t-tests compared occupational outcomes between “good” and “poor” sleepers (PSQI Global Score > 5 = poor sleeper). Results Poorer sleep quality at baseline broadly predicted poor occupational outcomes post-training. Specifically, higher PSQI Global Scores predicted higher emotional exhaustion (B = 1.6, p < 0.001, R2 = 0.25), functional impairment (B = 0.29, p < 0.03, R2 = 0.14), role overload (B = 28, p < 0.008, R2 = 0.12), and perceived stress (B = 0.34, p < 0.004, R2 = 0.2). Furthermore, occupational outcome scores were significantly higher in poor sleepers than good sleepers: emotional exhaustion: (t(58) = -4.18, p < .001); functional impairment: (t(59) = -3.68, p = .001); role overload (t(58) = -3.20, p = .002); and perceived stress (t(58) = -2.43, p = .02). Conclusion This study identified a longitudinal relationship between sleep quality and occupational outcomes, suggesting that service members with poor sleep may be at risk for experiencing poor workplace wellbeing. Given the association between service member wellbeing and likelihood to re-enlist, insufficient sleep may negatively impact Soldier attrition. Future studies should aim to augment sleep quality and track occupational outcomes in this population. Support (if any) This work was funded by the Military Operational Medicine Research Program of the United States Army Medical Research and Development Command.

Abstract Introduction There is a well-established connection between sleep and the immune system, and in the midst of a global pandemic, it is vital to understand the relationship between COVID-19 symptomatology and sleep. While our communities practice safety protocols, medical personnel working on the COVID-19 response effort are at high risk for exposure and contraction. This creates an urgent need to better understand whether sleep may contribute to COVID-19 symptom onset, severity, and recovery. This study examined the relationship between subjective and objective sleep during infection. Methods Fifty volunteers (age 35.15±9.97) considered high risk for COVID-19 participated in the study. The sample consisted mostly of medical personnel (93.27%) working through the pandemic. Over six months, participants completed monthly surveys and daily logs via Qualtrics. These surveys included questions about sleep, infection symptoms, COVID-19 tests and diagnoses, and mood. Wrist-worn actigraphy was collected continuously throughout the study. Sleep duration, latency, wake after sleep onset, and efficiency were processed using Philips Actiware 6.0. Actigraphy and survey data were analyzed using SPSS v. 25. Results Sixty-two percent of participants experienced infection symptoms. Those experiencing symptoms were significantly more likely to report having poorer sleep quality t(255.59)=5.78, p=<.001, poorer mood upon waking t(258.03)=6.53, p=<.001, feeling less alert upon waking t(255.61)=4.56, p=<.001, and spending more time awake at night t(2.66.98)=-7.29, p=<.001. Results showed that compared to those asymptomatic, participants with cough t(2164)=2.07, p=.039, diarrhea t(2161)=2.51, p=.012, and headache t(106.18)=7.05, p=<.001 all had significantly less total sleep time, while those with body aches spent significantly more time awake at night t(2164)=2.10, p=.036. Conclusion This preliminary examination of the data broadly suggests that medical personnel experiencing infection symptoms may have difficulty obtaining adequate sleep. Further, specific infection symptoms may share a stronger relationship with key sleep parameters than others. These findings support further testing of the bi-direction relationship between infection symptoms and sleep. Results from this research will contribute to enhancing prevention, detection, and treatment guidance related to future domestic and globally-experienced infections. Support (if any) Support for this study comes from there Military Operational Medicine Research Program of the United States Army Medical Research and Development Command.

Abstract Introduction U.S. Army Reserve Officer Training Corps (ROTC) Advanced Camp (AC) is a month-long capstone course that evaluates Cadet leadership. Although the relationship between sleep and objective performance is well established, less is known about how sleep may impact self-perception of performance, especially in the military context. This study examined the impact of habitual sleep on self-expected and objective AC performance. Methods 577 Cadets (age 22.22 ± 2.74; 74.36% male) completed the Pittsburgh Sleep Quality Index (PSQI) at baseline to measure subjective sleep quality (Global; higher scores indicate poorer sleep quality) and total sleep time (TST) in the month before training. Self-expected AC performance was captured by asking Cadets to estimate what their final performance score would be and objective performance was determined from summary scores from Instructors. Performance discrepancy was calculated as the difference between Cadet’s expected and objective scores. Regression models assessed the predictive utility of habitual TST and Global on performance. Results Ordinal regressions showed that as Global increased, expected AC score also decreased with an OR of .684 (95% CI, -.694 to -.064), Wald χ2(1) = 5.56, p = .018. Further, Global independently predicted performance discrepancies, where the odds of a difference existing between a Cadet’s self-expected and their objective performance was .895 less likely for those with increasing Global (p = .028). Together TST and Global predicted discrepancy magnitude between Cadet self-expected and objective performance, F(2, 349) = 2.99, p = .05, with Global as a independent predictor p < .05. Independent findings related to TST were varied and warrant further testing. Conclusion Cadets with poorer sleep quality prior to AC self-expected to perform worse and had discrepancies between their self-expected and objective performance when compared to those with higher sleep quality. TST enhanced the predictive power of Global when predicting magnitude of performance discrepancy. Therefore future research examining Global, while accounting for TST, is warranted to better understand how sleep may influence self-expectations of military performance. Support (if any) Support for this study came from the Military Operational Medicine Research Program of the United States Army Medical search and Development Command.

Objective: To assess the relationship between sleep quality and occupational well-being in active duty military Service Members. Design: Longitudinal prospective analysis. Setting: An annual military training event. Participants: US Army special operations Soldiers (n = 60; 100% male; age 25.41 +/- 3.74). Intervention: None. Measurements: The Pittsburgh Sleep Quality Index (PSQI) was administered prior to the training event, and the Emotional Exhaustion Scale, the Role Overload Scale, the Walter Reed Army Institute of Research Soldier-Specific Functional Impairment Scale, and the Perceived Stress Scale were administered after the event. Linear regression models were used to assess the relationship between sleep and occupational wellness measures, and the outcome measures of "good" and "poor" sleepers (per the PSQI scoring criteria) were compared with Student's t tests. Results: Higher (poorer) PSQI Global Scores predicted poorer occupational wellness of all measures (emotional exhaustion: B = 1.60, P < .001, R-2 = 0.25; functional impairment: B = 0.29, P = .03, R-2 = 0.14; role overload: B = 0.28, P = .008, R-2 = 0.12; and perceived stress: B = 0.34, P = .004, R-2 = 0.20). There were additional relationships between specific PSQI component scores and occupational wellness measures, which is a replication of This team's previous work. Furthermore, emotional exhaustion (t(58) = -4.18, P < .001), functional impairment (t(59)= -3.68, P = .001), role overload (t(58) = -3.20, P = .002), and perceived stress (t (58) = -2.43, P = .02) were all higher in poor sleepers. Conclusions: The findings of this study suggest that US Army special operations Soldiers who have poorer sleep quality may be at increased risk for having poorer occupational well-being. Published by Elsevier Inc. on behalf of National Sleep Foundation.

Military medical research is critical for enhancing overall wellbeing and readiness of military service members. Recently, in the USA, military research budget allocation has shifted from basic research to more translational research and rapid development of fieldable products. To meet this shift in priorities, applied research in the operational context— rather than in a laboratory—will need to increase but be high quality as well. Although field research provides several distinct advantages over lab research (eg, higher external validity), field research also comes with unique challenges. For example, in instances of largescale data collection, which often entails testing many service members at a time, participant engagement can be low. A lack of participant engagement is not without consequence, as poor engagement may lead to a less representative (and thus, less accurate) snapshot of a military unit, thereby limiting the utility of the findings, and increasing the likelihood of having poorer data quality. Poor quality research—especially in the face of the Coronavirus Disease 19 pandemic—can be financially costly and potentially deadly, both in the USA and internationally. In 2015, the RAND Corporation published a report attempting to identify predictors of low survey response rate among US military service members. The report concluded ‘lack of interest or time’ and ‘poor attitudes towards sponsoring organisation’ were linked to lower participation rate. Anecdotally, throughout several research projects, our team at the Walter Reed Army Institute of Research observed the presence of the same factors cited by RAND as well as additional situational factors—including day of week, time of day and place of testing—that seem to also predict research participant engagement (ie, consent rate, participant effort). To this end, we explored our previously collected data to determine whether anecdotal predictors of participation matched objective participation and effort rates. This Editorial is intended to share these preliminary findings so that other teams who conduct similar military field research can maximise research success and value. In 2017, our team administered roughly 2000 surveys to US Army soldiers in an Armored Brigade Combat Team to assess the unit’s culture, performance and health. Over the course of 5 days, approximately 30 groups of 50–500 soldiers were asked to voluntarily complete a~45 min survey. Unit leadership dictated when and where soldiers were tested. The following data represent how time and place of testing were related to participant consent rate and participant effort during testing. There were two outcome measures of interest. The first was consent rate (number of individuals who consented ‘yes’ for use of their data divided by the number of surveys administered for that testing group). The second was each group’s proportion of individuals putting effort into the survey (‘careful responders’). Careful responders were identified based on the ‘long string’ analysis method, which differentiates careful responders from careless responders based on consistency of responses. An example of a careful responder is a participant with varied responses on a 20item survey. An example of a noncareful responder is a participant who completes a 20item survey with the same response for each item. Long string analysis was conducted only in individuals who completed all survey items. There were several metrics used for prediction of participant engagement: day of the week (Monday through Friday), time of survey administration (06:00–08:00, 08:00–10:00, 10:00–12:00, 12:00–14:00, 14:00–16:00 hours), and whether the survey was administered in the unit’s area (eg, Company Operations Facility) versus a centralised, shared location, such as a classroom. χ2 tests were used to compare the proportion of careful responders to careless responders between predictors. Analysis of variance tests were used to compare and rates of consent between predictors. Results that reached the threshold of statistical significance are presented below. As shown in Figure 1, there was a relationship between day of the week and consent rate. The consent rate was relatively high and stable Monday through Thursday, but the consent rate dropped considerably on Friday. It is possible that participants had work duties to complete before the weekend, and they chose to complete those duties rather than completing the survey. This notion is consistent with findings from the RAND report, which stated participants felt they did not have time to complete the survey. Figure 2 shows the relationship between the proportion of careful responders in each testing group and the time of survey administration. The proportion of careful responders was highest in the morning and lowest in the afternoon. The proportion of careful responding was also more variable

U.S. Army Reserve Officer Training Corps (ROTC) Advanced Camp (AC) is a 29-day training that assesses military skills and leadership potential in college students training to become Commissioned Officers (i.e. Cadets). Military trainings are widely known to disrupt normative sleep. Additionally, operational sleep disruption is linked to performance decrements. This study examined the ability for objective and subjective sleep during ROTC AC to predict Cadet performance. One hundred and fifty-nine ROTC Cadets (age 22.06±2.49 years; 76.1% male) wore an actiwatch device continuously for 29 days during AC. Paper surveys administered at the end of AC captured subjective sleep metrics during the training. ROTC instructors evaluated Cadet performance and provided scores of overall class rank and summary performance. Multiple and ordinal linear regressions assessed the predicative utility of subjective (sleep duration [SD]; Global score [Global] from the Pittsburgh Sleep Quality Index) and objective (Total Sleep Time [TST]; Sleep Efficiency [SE]; Sleep Latency Onset [SOL]; Wake After Sleep Onset [WASO] from actigraphy) sleep on performance. The interaction of SD and Global, when controlling for age and gender, significantly predicted increased Cadet rank, F(4,153) = 3.09, p = 0.018. Models testing the prediction of SD and Global on summary performance score were non-significant. Further, regressing of both Cadet rank and summary performance individually on objective sleep metrics, when controlling for age and gender, resulted in non-significant findings. Subjective and objective sleep showed no significant individual predictive utility on performance. However, the combined subjective model significantly predicted that Cadets who slept worse (lower SD; higher Global) during AC received a lower rank at the end of the training. These findings suggest there may be a unique combined predictive utility of subjective sleep on performance when compared to the predictive power of individual variables. Therefore, subjective sleep may be better for predicting operational performance than objective sleep. Future analyses will refine these models and examine how performance on individual AC events may be influenced by sleep. Support for this study came from the Military Operational Medicine Research Program (MOMRP) of the United States Army Medical Research and Development Command (USAMRDC). Support (if any):

OBJECTIVES:Explore the impact transitioning from daytime to nighttime operations has on performance in U.S. Army Rangers.METHODS:Fifty-four male Rangers (age 26.1±4.0 years) completed the Y-Balance Test (YBT), a vertical jump assessment, and a grip strength test at three time points. Baseline testing occurred while the Rangers were on daytime operations; post-test occurred after the first night into the nighttime operation training (after full night of sleep loss), and follow-up testing occurred six days later (end of nighttime training).RESULTS:On the YBT, performance was significantly worse at post-test compared to baseline during right posteromedial reach (104.1±7.2cm vs 106.5±6.7cm, p=.014), left posteromedial reach (105.4±7.5cm vs 108.5±6.6cm, p=.003), right composite score (274.8±19.3cm vs 279.7±18.1cm, p=.043), left composite score (277.9±18.1cm vs 283.3±16.7cm, p=.016), and leg asymmetry was significantly worse in the posterolateral direction (4.8±4.0cm vs 3.7±3.1cm, p=.030) and the anterior direction (5.0±4.0cm vs 3.6±2.6cm, p=.040). The average vertical jump height was significantly lower at post-test compared to baseline (20.6±3.4 in vs 21.8±3.0 in, p=.004). Baseline performance on YBT and vertical jump did not differ from follow-up.CONCLUSIONS:Army Rangers experienced an immediate, but temporary, drop in dynamic balance and vertical jump performance when transitioning from daytime to nighttime operations. When feasible, Rangers should consider adjusting their sleep cycles prior to anticipating nighttime operations in order to maintain their performance levels. Investigating strategies that may limit impairments during this transition is warranted.

Experimental sleep restriction and deprivation lead to risky decision-making. Further, in naturalistic settings, short sleep duration and poor sleep quality have been linked to real-world high-risk behaviors (HRB), such as reckless driving or substance use. Military populations, in general, tend to sleep less and have poorer sleep quality than nonmilitary populations due to a number of occupational, cultural, and psychosocial factors (e.g. continuous operations, stress, and trauma). Consequently, it is possible that insufficient sleep in this population is linked to HRB. To investigate this question, we combined data from four diverse United States Army samples and conducted a mega-analysis by aggregating raw, individual-level data (n = 2,296, age 24.7 +/- 5.3). A negative binomial regression and a logistic regression were used to determine whether subjective sleep quality (Pittsburgh Sleep Quality Index [PSQI], Insomnia Severity Index [ISI], and duration [h]) predicted instances of military-specific HRB and the commission of any HRB (yes/no), respectively. Poor sleep quality slightly elevated the risk for committing HRBs (PSQI Exp(B): 1.12 and ISI Exp(B): 1.07), and longer duration reduced the risk for HRBs to a greater extent (Exp(B): 0.78), even when controlling for a number of relevant demographic factors. Longer sleep duration also predicted a decreased risk for commission of any HRB behaviors (Exp(B): 0.71). These findings demonstrate that sleep quality and duration (the latter factor, in particular) could be targets for reducing excessive HRB in military populations. These findings could therefore lead to unit-wide or military-wide policy changes regarding sleep and HRB.

PURPOSE: Investigate the association between musculoskeletal injuries and self-reported sleep quality in U.S. Army Rangers. METHODS: This study was part of a larger study investigating the impact of sleep and circadian desynchrony on the health of U.S. Army Rangers. At baseline, the Rangers were asked if they currently have any musculoskeletal injuries. They also completed a modified Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), and were asked to rate their average sleep quality (0 equating to “Poor Quality” and 100 equating to “Best Quality”) and specify their average sleep duration over the preceding week. A total of 82 Rangers (male, 25.4 ± 4.0 years) completed all of these questionnaires. RESULTS: The reported musculoskeletal injury prevalence of the Rangers was 15.9% (n = 13). The Rangers that reported an injury, compared to those that did not, had a significantly higher Global PQSI score (6.7 ± 3.7 versus 4.5 ± 2.7, p = .012) and ISI score (10.9 ± 3.7 versus 7.2 ± 4.1, p = .003), both indicative of poorer sleep. In addition, the group reporting an injury rated their average sleep quality over the preceding week significantly lower compared to those that did not report an injury (50.8 ± 17.5 versus 68.9 ± 18.3, p = .001). There was no significant difference in the reported average nightly sleep duration between the injured group (6.1 ± 1.0 hours) and uninjured group (6.5 ± 0.9 hours). CONCLUSIONS: In this cohort of elite male Army Soldiers, having a musculoskeletal injury was associated with poorer sleep quality. Sleep duration was not associated with reported injuries; however, both the injured group and uninjured group averaged less than the recommended amounts of sleep. Future research should further investigate the relationship between injury and sleep, including in other military populations, to ascertain whether improving sleep quality has any positive impact on subsequent injury rates and to better understand how injuries may negatively impact sleep. The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of Army, Department of Defense, or the U.S. Government.