Mental Disorders, Comorbidity, and Suicidal Behavior: Results from the National Comorbidity Survey Replication

Mental disorders are among the strongest predictors of suicide attempts. However, little is known about which disorders are uniquely associated with suicidal behavior due to high levels of psychiatric comorbidity. We examined the unique associations between individual disorders and subsequent suicidal behavior (suicide ideation, plans, and attempts) using data from the National Comorbidity Survey Replication, a nationally representative household survey of 9,282 US adults. Results revealed that approximately 80% of suicide attempters in the US have a temporally prior mental disorder. Anxiety, mood, impulse-control, and substance disorders all significantly predict subsequent suicide attempts in bivariate analyses (odds ratios=2.7-6.7); however, these associations decrease substantially in multivariate analyses controlling for comorbidity (odds ratios=1.5-2.3) but remain statistically significant in most cases. Disaggregation of the observed effects reveals that depression predicts suicide ideation, but not suicide plans or attempts among those with ideation. Instead, disorders characterized by severe anxiety/agitation (e.g., PTSD) and poor impulse-control (e.g., conduct disorder, substance disorders) predict which suicide ideators go on to make a plan or attempt. These results advance understanding of the unique associations between mental disorders and different forms of suicidal behavior. Future research must further delineate the mechanisms through which people come to think about suicide and progress from suicidal thoughts to attempts.Psycholog

Complementary cooperation, minimal winning coalitions, and power indices

We introduce a new simple game, which is referred to as the complementary weighted multiple majority game (C-WMMG for short). C-WMMG models a basic cooperation rule, the complementary cooperation rule, and can be taken as a sister model of the famous weighted majority game (WMG for short). In this paper, we concentrate on the two dimensional C-WMMG. An interesting property of this case is that there are at most $n+1$ minimal winning coalitions (MWC for short), and they can be enumerated in time $O(n\log n)$, where $n$ is the number of players. This property guarantees that the two dimensional C-WMMG is more handleable than WMG. In particular, we prove that the main power indices, i.e. the Shapley-Shubik index, the Penrose-Banzhaf index, the Holler-Packel index, and the Deegan-Packel index, are all polynomially computable. To make a comparison with WMG, we know that it may have exponentially many MWCs, and none of the four power indices is polynomially computable (unless P=NP). Still for the two dimensional case, we show that local monotonicity holds for all of the four power indices. In WMG, this property is possessed by the Shapley-Shubik index and the Penrose-Banzhaf index, but not by the Holler-Packel index or the Deegan-Packel index. Since our model fits very well the cooperation and competition in team sports, we hope that it can be potentially applied in measuring the values of players in team sports, say help people give more objective ranking of NBA players and select MVPs, and consequently bring new insights into contest theory and the more general field of sports economics. It may also provide some interesting enlightenments into the design of non-additive voting mechanisms. Last but not least, the threshold version of C-WMMG is a generalization of WMG, and natural variants of it are closely related with the famous airport game and the stable marriage/roommates problem.Comment: 60 page

Field procedures in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multi‐component epidemiological and neurobiological study of unprecedented size and complexity designed to generate actionable evidence‐based recommendations to reduce US Army suicides and increase basic knowledge about determinants of suicidality by carrying out coordinated component studies. A number of major logistical challenges were faced in implementing these studies. The current report presents an overview of the approaches taken to meet these challenges, with a special focus on the field procedures used to implement the component studies. As detailed in the paper, these challenges were addressed at the onset of the initiative by establishing an Executive Committee, a Data Coordination Center (the Survey Research Center [SRC] at the University of Michigan), and study‐specific design and analysis teams that worked with staff on instrumentation and field procedures. SRC staff, in turn, worked with the Office of the Deputy Under Secretary of the Army (ODUSA) and local Army Points of Contact (POCs) to address logistical issues and facilitate data collection. These structures, coupled with careful fieldworker training, supervision, and piloting, contributed to the major Army STARRS data collection efforts having higher response rates than previous large‐scale studies of comparable military samples. Copyright © 2013 John Wiley & Sons, Ltd .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102238/1/mpr1400.pd

Response bias, weighting adjustments, and design effects in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multi‐component epidemiological and neurobiological study designed to generate actionable recommendations to reduce US Army suicides and increase knowledge about determinants of suicidality. Three Army STARRS component studies are large‐scale surveys: one of new soldiers prior to beginning Basic Combat Training (BCT; n  = 50,765 completed self‐administered questionnaires); another of other soldiers exclusive of those in BCT ( n  = 35,372); and a third of three Brigade Combat Teams about to deploy to Afghanistan who are being followed multiple times after returning from deployment ( n  = 9421). Although the response rates in these surveys are quite good (72.0–90.8%), questions can be raised about sample biases in estimating prevalence of mental disorders and suicidality, the main outcomes of the surveys based on evidence that people in the general population with mental disorders are under‐represented in community surveys. This paper presents the results of analyses designed to determine whether such bias exists in the Army STARRS surveys and, if so, to develop weights to correct for these biases. Data are also presented on sample inefficiencies introduced by weighting and sample clustering and on analyses of the trade‐off between bias and efficiency in weight trimming. Copyright © 2013 John Wiley & Sons, Ltd .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102203/1/mpr1399.pd

Lifetime Prevalence Of Dsm‐Iv Mental Disorders Among New Soldiers In The U.S. Army: Results From The Army Study To Assess Risk And Resilience In Servicemembers (Army Starrs)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110630/1/da22316.pd

Mental Disorders, Comorbidity, and Pre‐enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115994/1/sltb12153.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115994/2/sltb12153_am.pd

Endoscopic Ultrasound and Related Technologies for the Diagnosis and Treatment of Pancreatic Disease - Research Gaps and Opportunities: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop

A workshop was sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases to address the research gaps and opportunities in pancreatic endoscopic ultrasound (EUS). The event occurred on July 26, 2017 in 4 sessions: (1) benign pancreatic diseases, (2) high-risk pancreatic diseases, (3) diagnostic and therapeutics, and (4) new technologies. The current state of knowledge was reviewed, with identification of numerous gaps in knowledge and research needs. Common themes included the need for large multicenter consortia of various pancreatic diseases to facilitate meaningful research of these entities; to standardize EUS features of different pancreatic disorders, the technique of sampling pancreatic lesions, and the performance of various therapeutic EUS procedures; and to identify high-risk disease early at the cellular level before macroscopic disease develops. The need for specialized tools and accessories to enable the safe and effective performance of therapeutic EUS procedures also was discussed

Prior sleep problems and adverse post-traumatic neuropsychiatric sequelae of motor vehicle collision in the AURORA study.

STUDY OBJECTIVES: Many patients in Emergency Departments (EDs) after motor vehicle collisions (MVCs) develop post-traumatic stress disorder (PTSD) or major depressive episode (MDE). This report from the AURORA study focuses on associations of pre-MVC sleep problems with these outcomes 8 weeks after MVC mediated through peritraumatic distress and dissociation and 2-week outcomes. METHODS: A total of 666 AURORA patients completed self-report assessments in the ED and at 2 and 8 weeks after MVC. Peritraumatic distress, peritraumatic dissociation, and pre-MVC sleep characteristics (insomnia, nightmares, daytime sleepiness, and sleep duration in the 30 days before the MVC, trait sleep stress reactivity) were assessed retrospectively in the ED. The survey assessed acute stress disorder (ASD) and MDE at 2 weeks and at 8 weeks assessed PTSD and MDE (past 30 days). Control variables included demographics, MVC characteristics, and retrospective reports about PTSD and MDE in the 30 days before the MVC. RESULTS: Prevalence estimates were 41.0% for 2-week ASD, 42.0% for 8-week PTSD, 30.5% for 2-week MDE, and 27.2% for 8-week MDE. Pre-MVC nightmares and sleep stress reactivity predicted 8-week PTSD (mediated through 2-week ASD) and MDE (mediated through the transition between 2-week and 8-week MDE). Pre-MVC insomnia predicted 8-week PTSD (mediated through 2-week ASD). Estimates of population attributable risk suggest that blocking effects of sleep disturbance might reduce prevalence of 8-week PTSD and MDE by as much as one-third. CONCLUSIONS: Targeting disturbed sleep in the immediate aftermath of MVC might be one effective way of reducing MVC-related PTSD and MDE

A Dissection and Enhancement Technique for Combined Damage Characterisation in Composite Laminates using Laser-line Scanning Thermography

Impact induced combined damage in composite laminates attracts great attention due to its significant degradation of the structural integrity. However, the provision of the quantitative analysis of each damage portion is challenging due to its bare visibility and structural mixture complexity, so-called barely visible impact damage (BVID), which is referred to as inter-laminar delamination, and is inherently coupled with in-plane transverse and matrix damage also known as combined damage. Instead of focusing on one type of damage in most of the existing studies, this paper proposes a decomposition and targeted enhancement technique based on Stationary Wavelet Transform (SWT) for such coupled BVID in composite laminates using laser-line scanning thermography. Firstly, a combined damage model composed of in-plane damage and inter-laminar delamination is established by finite element numerical modelling to predict the thermal response pattern in the laser scanning thermography. Then, a feature separation and targeted enhancement strategy based on SWT in the frequency domain is proposed to improve the contrast of the matrix crack and delamination in combined damage scenarios induced by low-velocity rigid impact via drop-tower tests, meanwhile eliminating noise and suppressing the laser pattern background. The enhanced images of in-plane damage and delamination are furtherly processed by Random Sample Consensus (RANSAC) method and confidence map algorithms to calibrate the damage profile. The proposed technique is validated through inspecting a group of unidirectional carbon fibre-reinforced polymer composite samples, impacted by a variety of energy levels, in fibre-parallel (0°), 45° and orthogonal scanning modes. The results demonstrate that the proposed technique can pertinently isolate, enhance and characterise the inspected in-plane crack and inter-laminates delamination in a flexible manner. The proposed methodology paves the way towards automated infrared thermography data analysis for quantitative dissection of actual combined damage in composite laminates