Longitudinal measurement invariance and growth curve modeling of psychological resilience across the deployment cycle.

The concept of resilience is embedded within military culture and professional identity. To date, temporal changes in individuals' perceptions of their own resilience have not been systematically assessed in highstakes occupational contexts, like the military. The current study examined change in selfreported resilience over time by: (1) examining the longitudinal measurement invariance of the Brief Resilience Scale (BRS); (2) assessing the longitudinal pattern of resilience across a combat deployment cycle; and (3) examining predictors of postdeployment resilience and change in resilience scores across time. U.S. Army soldiers assigned to a combat brigade completed a survey at four time points over the course of a deployment cycle: (a) prior to deployment to Afghanistan; (b) during deployment; (c) immediately following return to home station; and (d) approximately 2-3 months thereafter. The longitudinal measurement invariance of the BRS was established. Growth curve modeling indicated that, on average, self-reported resilience decreased across the deployment cycle, but there was considerable individual variation in the rate of change. Of note, loneliness, as measured during deployment, predicted the rate of change in self-reported resilience over time. Results have implications for the longitudinal analysis of resilience and for the development of interventions with military personnel.

Order effects in PTSD network analysis: important implications for diagnostic conceptualization, treatment refinement, and research.

BACKGROUND: For decades confirmatory factor analysis (CFA) has been the preeminent method to study the underlying structure of posttraumatic stress disorder (PTSD); however, methodological limitations of CFA have led to the emergence of other analytic approaches. In particular, network analysis has become a gold standard to investigate the structure and relationships between PTSD symptoms. A key methodological limitation, however, which has significant clinical implications, is the lack of data on the potential impact of item order effects on the conclusions reached through network analyses. METHODS: The current study, involving a large sample (N = 5055) of active duty army soldiers following deployment to Iraq, assessed the vulnerability of network analyses and prevalence rate to item order effects. This was done by comparing symptom networks of the DSM-IV PTSD checklist items to these same items distributed in random order. Half of the participants rated their symptoms on traditionally ordered items and half the participants rated the same items, but in random order and interspersed between items from other validated scales. Differences in prevalence rate and network composition were examined. RESULTS: The prevalence rate differed between the ordered and random item samples. Network analyses using the ordered survey closely replicated the conclusions reached in the existing network analyses literature. However, in the random item survey, network composition differed considerably. CONCLUSION: Order effects appear to have a significant impact on conclusions reached from PTSD network analysis. Prevalence rates were also impacted by order effects. These findings have important diagnostic and clinical treatment implications.

Variability in the stability of personality traits across a single combat deployment.

This study assessed changes in measures of personality traits across a 12-month combat deployment in a sample of conventional US Army soldiers. Results revealed Impulsive Sensation-Seeking (ImpSS) and Sociability (Sy) decreased significantly, whereas Neuroticism-Anxiety (N-Anx) increased. Changes in ImpSS scores were mainly attributed to age, but were inversely related to increases in traumatic stress symptoms. Combat exposure, concussion, age, education, and changes in traumatic stress scores all independently contributed to changes in N-Anx scores. Changes in Sy were not associated with any of the data available from pre-deployment or deployment measures. Changes in Aggression-hostility (Agg-Hos) and Activity (Act) across the deployment were not significant. The findings suggest significant variability in the stability of personality traits when exposed to combat stress and injury while deployed, which may be influenced by factors such as age and education.

Indirect effects of soldier healthy eating and physical activity on suicidal ideation through psychological health symptoms in active-duty military.

The suicide rate within the military continues to rise. New approaches for prevention are needed which capitalize on existing strengths, are scalable at multiple levels, and promote mental fortitude. Healthy eating (HE) and physical activity (PA) represent scalable practices and methods for promoting mental health and protective factors within the military. A cross-sectional sample of N = 1019 active-duty Soldiers completed self-report measures of HE, PA, major depressive disorder (MDD) symptoms, generalized anxiety disorder (GAD) symptoms, and suicidal ideation (SI). Moderated mediation analyses using bootstrapping techniques were used to determine if HE and PA interact to relate to lower SI through reduced psychological health (PH) symptoms. Results indicated an indirect effect of HE on presence versus absence of past month SI through GAD symptoms at moderate-to-high levels of cardiovascular PA. A similar pattern was demonstrated for strength training PA where HE had an indirect effect on past month SI through GAD symptoms at only high levels of strength training PA. HE was indirectly related to lower MDD symptoms at all levels of cardiovascular PA and moderate to high levels of strength training PA. Study limitations and implications for secondary suicide prevention strategies within the military are discussed.

Psychometric properties of the interpersonal needs questionnaire (INQ-15) in Army soldiers: Implications and future directions.

The Interpersonal Theory of Suicide posits that two unmet interpersonal needs, thwarted belongingness and perceived burdensomeness, interact to predict suicide desire. These two constructs are frequently assessed using the 15-item Interpersonal Needs Questionnaire (INQ-15); however, this measure has never been validated in military service members. The current study analyzed the psychometric properties of the INQ-15 in a sample of (N = 1096) military personnel stationed overseas. Results indicated that the two-factor model of the INQ-15 had a poor model fit in this population; however, a bifactor model with two specific factors representing TB and PB demonstrated good fit. As seen in previous research, perceived burdensomeness was more strongly related to suicidal ideation severity than thwarted belongingness. Implications and future directions for research are discussed.

Perceptions of purpose, cohesion, and military leadership: A path analysis of potential primary prevention targets to mitigate suicidal ideation.

Rates of suicide in the US Army continue to rise, and by some accounts exceed the general population. This increase has renewed efforts to identify protective factors that may inform novel suicide prevention strategies. Previous research has demonstrated that a sense of purpose in life and perceived cohesion with military peers are related to a reduction in the severity of suicidal ideation (SI). Additionally, research in military samples supports decreased SI in Soldiers who endorse that their leaders convey a sense of purpose and meaning in their shared mission. However, no work has investigated whether these leadership styles relate to a sense of felt purpose and perceived cohesion in Soldiers and thus the indirect effect of these leadership styles on SI. Active duty Army Soldiers (n = 1,160) completed self-report measures of purpose in life (PiL), perceived cohesion, ethical leadership, loneliness, and SI. Indirect effect analyses were conducted to determine how leadership behaviors indirectly relate to SI through PiL and perceived cohesion. Indirect effect analyses revealed that ethical leadership had an indirect effect on reduced SI through increased PiL. In the same parallel indirect effect analysis, ethical leadership was related to less SI through increased perceived cohesion and decreased loneliness sequentially. Enhanced leadership training that effectively increases Soldier purpose may be an important primary prevention tool to mitigate the effect of suicide risk factors. This primary prevention strategy may help augment existing suicide surveillance and clinical prevention efforts to reduce Soldier risk for suicide.

Network Analysis of Research on Mild Traumatic Brain Injury in US Military Service Members and Veterans During the Past Decade (2010-2019).

OBJECTIVE: To evaluate trends in the extant literature on mild traumatic brain injury (mTBI) in military service members and veterans using network analysis based on a comprehensive search of original, peer-reviewed research articles involving human participants published between January 1, 2010, and December 31, 2019. Specifically, we employed network analysis to evaluate associations in the following areas: (1) peer-reviewed journals, (2) authors, (3) organizations/institutions, and (4) relevant key words. PARTICIPANTS: Included studies were published in peer-reviewed journals available on Web of Science database, using US military service members or veterans. DESIGN: Bibliometric network analytical review. MAIN MEASURES: Outcomes for each analysis included number of articles, citations, total link strength, and clusters. RESULTS: The top publishing journals were (1) Journal of Head Trauma and Rehabilitation, (2) Military Medicine, (3) Brain Injury, (4) Journal of Neurotrauma, and (5) Journal of Rehabilitation Research and Development. The top publishing authors were (1) French, (2) Lange, (3) Cooper, (4) Vanderploeg, and (5) Brickell. The top research institutions were (1) Defense and Veterans Brain Injury Center, (2) Uniformed Services University of the Health Sciences, (3) University of California San Diego, (4) Walter Reed National Military Medical Center, and (5) Boston University. The top co-occurring key words in this analysis were (1) posttraumatic stress disorder (PTSD), (2) persistent postconcussion symptoms (PPCS), (3) blast injury, (4) postconcussion syndrome (PCS), and (5) Alzheimer's disease. CONCLUSIONS: The results of this network analysis indicate a clear focus on veteran health, as well as investigations on chronic effects of mTBI. Research in civilian mTBI indicates that delaying treatment for symptoms and impairments related to mTBI may not be the most precise treatment strategy. Increasing the number of early, active, and targeted treatment trials in military personnel could translate to meaningful improvements in clinical practices for managing mTBI in this population.

Cognitive disinhibition and infrequent moderate-to-intense physical activity linked with obesity in U.S. soldiers.

PURPOSE: To explore the relationship between body weight status and neurocognitive functioning in soldiers. METHODS: U.S. soldiers (N = 109) answered survey questions and completed neurocognitive tests including simple reaction time, code substitution, procedural reaction time, go-no-go, matching to sample, code substitution recall, and four versions of the Stroop test including congruent (color and meaning of word agreed); incongruent (color and meaning of word differed); neutral (nonsense words appeared), and emotional (combat-related words such as "I.E.D" and "convoy" appeared). Self-reported heights and weights were used to calculate BMI. A BMI ≥ 30.00 kg/m2 was categorized as obese. Multivariate analysis of variance was used to analyze weight status differences (p ≤ 0.05) across neurocognitive variables. Binomial logistic regression analysis with obesity as the dependent variable was used to ascertain the contributions (p ≤ 0.05) of exercise and the neurocognitive measures that differed based on weight status. RESULTS: Twenty-nine participants (26.6%) were obese. The obese group had significantly lower scores on code substitution, and both neutral and emotional Stroop tasks. Only Stroop emotional scores, p = 0.022, OR = 0.97, and frequency of moderate/intense physical activity, p = 0.009, OR = 0.10, were significant predictors of weight status. CONCLUSIONS: Obesity was associated with less frequent moderate/intense physical activity and compromised executive functioning, namely decrements in response inhibition. Given the design and sample size, additional research is needed to better understand the direction of the relationship between these variables and to inform research related to the treatment and prevention of obesity within military populations. LEVEL OF EVIDENCE: Level III, case-control analytic study.

Sleep disturbance mediates the association of adverse childhood experiences with mental health symptoms and functional impairment in US soldiers.

Adverse childhood experiences (ACEs) can have long-term impacts on a person's mental health, which extend into adulthood. There is a high prevalence of ACEs among service members. Further, service members also report frequently experiencing disrupted sleep. We hypothesized that disrupted sleep may serve a mechanistic function connecting ACEs to functional impairment and poorer mental health. In a cross-sectional sample (n = 759), we found evidence for an indirect effect of ACEs on mental health outcomes through disrupted sleep. In a different sample using two time-points (n = 410), we found evidence for an indirect effect of ACEs on changes in mental health outcomes and functional impairment during a reset period, through changes in disrupted sleep during the same period. Implications, limitations and future research directions are discussed.

Saliva microRNA Biomarkers of Cumulative Concussion.

Recurrent concussions increase risk for persistent post-concussion symptoms, and may lead to chronic neurocognitive deficits. Little is known about the molecular pathways that contribute to persistent concussion symptoms. We hypothesized that salivary measurement of microribonucleic acids (miRNAs), a class of epitranscriptional molecules implicated in concussion pathophysiology, would provide insights about the molecular cascade resulting from recurrent concussions. This hypothesis was tested in a case-control study involving 13 former professional football athletes with a history of recurrent concussion, and 18 age/sex-matched peers. Molecules of interest were further validated in a cross-sectional study of 310 younger individuals with a history of no concussion (n = 230), a single concussion (n = 56), or recurrent concussions (n = 24). There was no difference in neurocognitive performance between the former professional athletes and their peers, or among younger individuals with varying concussion exposures. However, younger individuals without prior concussion outperformed peers with prior concussion on three balance assessments. Twenty salivary miRNAs differed (adj. p < 0.05) between former professional athletes and their peers. Two of these (miR-28-3p and miR-339-3p) demonstrated relationships (p < 0.05) with the number of prior concussions reported by younger individuals. miR-28-3p and miR-339-5p may play a role in the pathophysiologic mechanism involved in cumulative concussion effects.

Modest utility of brief oculomotor test for concussion screening in military mixed-martial arts training.

Primary Objective: To assess a rapid concussion screening tool in Service members participating in combatives (mixed martial arts; MMA) training school.Research Design: This prospective study included baseline and either post-training or post-injury assessments.Methods and Procedures: Baseline (N = 152) and post-assessments (n = 129) of Service members included symptom reporting and the King-Devick (KD) oculomotor test.Outcomes and Results: Headache, balance problems, and dizziness were the most severe concussive symptoms. KD scores for those who sustained a concussion (n = 31) were significantly worse compared to baseline, but not for participants who finished the course with no concussion (n = 98). For concussed, 74.2% had scores that were worse from baseline (slower) compared to 39.8% of the post-training group. KD scores were worse 34.4% more in individuals who sustained a concussion compared to those who did not. However, there was poor discriminant ability of the KD test (AUC = .60, sensitivity/specificity) to distinguish between concussed and non-concussed participants.Conclusions: The KD test should not be used in isolation as a sideline or field concussion assessment during training scenarios. Rather, it has potential utility for evaluating individual cases to supplement decision making when an established baseline is available.

Identifying disease foci from static and dynamic effective connectivity networks: Illustration in soldiers with trauma.

Brain connectivity studies report group differences in pairwise connection strengths. While informative, such results are difficult to interpret since our understanding of the brain relies on region-based properties, rather than on connection information. Given that large disruptions in the brain are often caused by a few pivotal sources, we propose a novel framework to identify the sources of functional disruption from effective connectivity networks. Our approach integrates static and time-varying effective connectivity modeling in a probabilistic framework, to identify aberrant foci and the corresponding aberrant connectomics network. Using resting-state fMRI, we illustrate the utility of this novel approach in U.S. Army soldiers (N = 87) with posttraumatic stress disorder (PTSD), mild traumatic brain injury (mTBI) and combat controls. Additionally, we employed machine-learning classification to identify those significant connectivity features that possessed high predictive ability. We identified three disrupted foci (middle frontal gyrus [MFG], insula, hippocampus), and an aberrant prefrontal-subcortical-parietal network of information flow. We found the MFG to be the pivotal focus of network disruption, with aberrant strength and temporal-variability of effective connectivity to the insula, amygdala and hippocampus. These connectivities also possessed high predictive ability (giving a classification accuracy of 81%); and they exhibited significant associations with symptom severity and neurocognitive functioning. In summary, dysregulation originating in the MFG caused elevated and temporally less-variable connectivity in subcortical regions, followed by a similar effect on parietal memory-related regions. This mechanism likely contributes to the reduced control over traumatic memories leading to re-experiencing, hyperarousal and flashbacks observed in soldiers with PTSD and mTBI. Hum Brain Mapp 39:264-287, 2018. © 2017 Wiley Periodicals, Inc.

Compromised hippocampus-striatum pathway as a potential imaging biomarker of mild-traumatic brain injury and posttraumatic stress disorder.

OBJECTIVES: Military service members risk acquiring posttraumatic stress disorder (PTSD) and mild-traumatic brain injury (mTBI), with high comorbidity. Owing to overlapping symptomatology in chronic mTBI or postconcussion syndrome (PCS) and PTSD, it is difficult to assess the etiology of a patient's condition without objective measures. Using resting-state functional MRI in a novel framework, we tested the hypothesis that their neural signatures are characterized by functionally hyperconnected brain regions which are less variable over time. Additionally, we predicted that such connectivities possessed the highest ability in predicting the diagnostic membership of a novel subject (top-predictors) in addition to being statistically significant. METHODS: U.S. Army Soldiers (N = 87) with PTSD and comorbid PCS + PTSD were recruited along with combat controls. Static and dynamic functional connectivities were evaluated. Group differences were obtained in accordance with our hypothesis. Machine learning classification (MLC) was employed to determine top predictors. RESULTS: From whole-brain connectivity, we identified the hippocampus-striatum connectivity to be significantly altered in accordance with our hypothesis. Diffusion tractography revealed compromised white-matter integrity between aforementioned regions only in the PCS + PTSD group, suggesting a structural etiology for the PCS + PTSD group rather than being an extreme subset of PTSD. Employing MLC, connectivities provided worst-case accuracy of 84% (9% more than psychological measures). Additionally, the hippocampus-striatum connectivities were found to be top predictors and thus a potential biomarker of PTSD/mTBI. CONCLUSIONS: PTSD/mTBI are associated with hippocampal-striatal hyperconnectivity from which it is difficult to disengage, leading to a habit-like response toward episodic traumatic memories, which fits well with behavioral manifestations of combat-related PTSD/mTBI. Hum Brain Mapp 38:2843-2864, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The Community Balance and Mobility Scale: A Pilot Study Detecting Impairments in Military Service Members With Comorbid Mild TBI and Psychological Health Conditions.

OBJECTIVE: To compare the capacity of the Community Balance and Mobility Scale (CB&M) to identify balance and mobility deficits in Service Members (SMs) with mild traumatic brain injury and comorbid psychological health conditions (mTBI/PH) to other commonly used balance assessments. SETTING: A clinical research institute that provides a 4-week, outpatient, interdisciplinary program for active-duty SMs with mTBI/PH. DESIGN: A nonrandomized, cross-sectional design that compared multiple measures between 2 groups-active duty SMs with (n = 8) and without (n = 8) the dual diagnosis of mTBI/PH. MAIN MEASURES: Gait speed, Activities-specific Balance Confidence scale (ABC), Functional Gait Assessment (FGA), and CB&M to assess functional balance among the community-dwelling, TBI population. RESULTS: Across all measures, the mTBI/PH group performed significantly worse (P ≤ .01) with the exception of the FGA. The abilities of all objective measures to distinguish participants with mTBI/PH from healthy controls ranged from fair to excellent (area under the curve [AUC] = 0.66-0.94). However, the CB&M showed the largest group differences in effect size (d = 2.6) and had the highest discriminate ability (AUC = 0.98; sensitivity 100%; specificity 88%). CONCLUSION: The CB&M appears to have higher sensitivity and specificity than other measures of balance in SMs with mTBI/PH. A higher cut score for the CB&M is needed for this population.

Three Scoring Approaches to the Neurobehavioral Symptom Inventory for Measuring Clinical Change in Service Members Receiving Intensive Treatment for Combat-Related mTBI.

OBJECTIVE: To examine the use of the Neurobehavioral Symptom Inventory to measure clinical changes over time in a population of US service members undergoing treatment of mild traumatic brain injury and comorbid psychological health conditions. SETTING: A 4-week, 8-hour per day, intensive, outpatient, interdisciplinary, comprehensive treatment program at the National Intrepid Center of Excellence in Bethesda, Maryland. PARTICIPANTS: Three hundred fourteen active-duty service members being treated for combat-related comorbid mild traumatic brain injury and psychological health conditions. DESIGN: Repeated-measures, retrospective analysis of a single-group using a pretest-posttest treatment design. MAIN MEASURES: Three Neurobehavioral Symptom Inventory scoring methods: (1) a total summated score, (2) the 3-factor method, and (3) the 4-factor method (with and without orphan items). RESULTS: All 3 scoring methods yielded statistically significant within-subject changes between admission and discharge. The evaluation of effect sizes indicated that the 3 different Neurobehavioral Symptom Inventory scoring methods were comparable. CONCLUSION: Findings indicate that the different scoring methods all have potential for assessing clinical changes in symptoms for groups of patients undergoing treatment, with no clear advantage with any one method.

Comparison of baseline-referenced versus norm-referenced analytical approaches for in-theatre assessment of mild traumatic brain injury neurocognitive impairment.

PRIMARY OBJECTIVE: To examine differences between the baseline-referenced and norm-referenced approaches for determining decrements in Automated Neuropsychological Assessment Metrics Version 4 TBI-MIL (ANAM) performance following mild traumatic brain injury (mTBI). RESEARCH DESIGN: ANAM data were reviewed for 616 US Service members, with 528 of this sample having experienced an mTBI and 88 were controls. METHODS AND PROCEDURES: Post-injury change scores were calculated for each sub-test: (1) normative change score = in-theater score - normative mean and (2) baseline change score = in-theater score - pre-deployment baseline. Reliable change cut-scores were applied to the change and the resulting frequency distributions were compared using McNemar tests. Receiver operator curves (ROC) using both samples (i.e. mTBI and control) were calculated for the change scores for each approach to determine the discriminate ability of the ANAM. MAIN OUTCOMES AND RESULTS: There were no statistical differences, p < 0.05 (Bonferonni-Holm corrected), between the approaches. When the area under the curve for the ROCs were averaged across sub-tests, there were no significant differences between either the norm-referenced (0.65) or baseline-referenced (0.66) approaches, p > 0.05. CONCLUSIONS: Overall, the findings suggest there is no clear advantage of using the baseline-referenced approach over norm-referenced approach.

Human Performance Optimization Metrics: Consensus Findings, Gaps, and Recommendations for Future Research.

Human performance optimization (HPO) is defined as "the process of applying knowledge, skills and emerging technologies to improve and preserve the capabilities of military members, and organizations to execute essential tasks." The lack of consensus for operationally relevant and standardized metrics that meet joint military requirements has been identified as the single most important gap for research and application of HPO. In 2013, the Consortium for Health and Military Performance hosted a meeting to develop a toolkit of standardized HPO metrics for use in military and civilian research, and potentially for field applications by commanders, units, and organizations. Performance was considered from a holistic perspective as being influenced by various behaviors and barriers. To accomplish the goal of developing a standardized toolkit, key metrics were identified and evaluated across a spectrum of domains that contribute to HPO: physical performance, nutritional status, psychological status, cognitive performance, environmental challenges, sleep, and pain. These domains were chosen based on relevant data with regard to performance enhancers and degraders. The specific objectives at this meeting were to (a) identify and evaluate current metrics for assessing human performance within selected domains; (b) prioritize metrics within each domain to establish a human performance assessment toolkit; and (c) identify scientific gaps and the needed research to more effectively assess human performance across domains. This article provides of a summary of 150 total HPO metrics across multiple domains that can be used as a starting point-the beginning of an HPO toolkit: physical fitness (29 metrics), nutrition (24 metrics), psychological status (36 metrics), cognitive performance (35 metrics), environment (12 metrics), sleep (9 metrics), and pain (5 metrics). These metrics can be particularly valuable as the military emphasizes a renewed interest in Human Dimension efforts, and leverages science, resources, programs, and policies to optimize the performance capacities of all Service members.

Imaging chronic traumatic brain injury as a risk factor for neurodegeneration.

Population-based studies have supported the hypothesis that a positive history of traumatic brain injury (TBI) is associated with an increased incidence of neurological disease and psychiatric comorbidities, including chronic traumatic encephalopathy, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. These epidemiologic studies, however, do not offer a clear definition of that risk, and leave unanswered the bounding criteria for greater lifetime risk of neurodegeneration. Key factors that likely mediate the degree of risk of neurodegeneration include genetic factors, significant premorbid and comorbid medical history (e.g. depression, multiple head injuries and repetitive subconcussive impact to the brain, occupational risk, age at injury, and severity of brain injury). However, given the often-described concerns in self-report accuracy as it relates to history of multiple TBIs, low frequency of patient presentation to a physician in the case of mild brain injuries, and challenges with creating clear distinctions between injury severities, disentangling the true risk for neurodegeneration based solely on population-based studies will likely remain elusive. Given this reality, multiple modalities and approaches must be combined to characterize who are at risk so that appropriate interventions to alter progression of neurodegeneration can be evaluated. This article presents data from a study that highlights uses of neuroimaging and areas of needed research in the link between TBI and neurodegenerative disease.

Alcohol motivations associated with frequency of alcohol use, binge drinking, and alcohol problems among active duty junior enlisted soldiers and non-commissioned officers.

Problematic alcohol use is a serious threat to the behavioral health of active-duty Service Members (ADSM), resulting in numerous calls from governmental agencies to better understand mechanistic factors contributing to alcohol misuse within the military. Alcohol use motives are reliable predictors of alcohol-related behaviors and are considered malleable targets for prevention and intervention efforts. However, empirical research indicates that drinking motives vary across contextually distinct populations. Although some research has been conducted among veteran and reservist populations, limited work has been specifically focused on ADSM and no research has evaluated motives and alcohol metrics among ADSM based on military rank. Participants for the current study included 682 ADSM recruited from a large military installation in the U.S. Structural equation modeling evaluated associations between four drinking motives (i.e., enhancement, social, conformity, coping) and three alcohol misuse metrics (i.e., alcohol frequency, binge frequency, alcohol problems). Three models were evaluated: one full (combined) model and two separate models based on military rank - junior enlisted (i.e., E1-E4) and non-commissioned officers (NCOs) (i.e., E5-E9). Results for junior enlisted ADSM indicated that coping and enhancement motives were most strongly associated with all alcohol misuse metrics. However, among NCOs, results indicated that alcohol problems were only associated with coping motives. Notably, results also indicated that alcohol use motives accounted for substantively more variance across all alcohol-related metrics among NCOs. Findings generally support extant military-related literature indicating use of alcohol for coping (e.g., with anxiety) as the motivation most consistently associated with increased alcohol misuse. However, novel findings highlight enhancement motives - using alcohol to attain some positive internal reward - as another, often stronger, motivation impacting alcohol use outcomes. Further, findings highlight notable distinctions between alcohol use motives (i.e., coping vs. enhancement) and the impact of alcohol use motives (i.e., effect size) on alcohol metrics between junior enlisted and NCOs.

The Use of Generative Adversarial Network and Graph Convolution Network for Neuroimaging-Based Diagnostic Classification.

Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases.