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The distributed pharmaceutical analysis laboratory (DPAL) is a collaboration between 30 academic institutions around the world, whose goal is to determine the quality of medicines collected from partner organizations in low- and middle-income countries (LMICs). Institutions complete system suitability for a high-performance liquid chromatography (HPLC) system using United States Pharmacopeia (USP)-traceable reference standards and are then approved to analyze batches of samples that are collected in LMICs by covert shoppers. Open Science Framework (OSF) gives DPAL participants access to resources for the program including a HPLC methodology manual, a wiki with HPLC troubleshooting information, detailed checklists and Excel templates for system suitability and sample assay, as well as steps for reporting results. Participants incorporate the DPAL program into their academic curriculum as undergraduate research or via lab activities for analytical chemistry or instrumental analysis courses. Over a thousand samples have been analyzed through DPAL in the last three years, and 168 samples with quality problems have been discovered, including falsified acetaminophen, adulterated amoxicillin-clavulanate and doxycycline, and substandard losartan. These quality problems are reported to the medicine regulatory agencies in the countries of origin and the WHO Rapid Alert System for further action. This real-world program gives students a hands-on opportunity to see the importance of analytical metrics taught in the classroom.

The need to determine the correct dimensionality of theoretical constructs and generate valid measurement instruments when underlying items are categorical has generated a significant volume of research in the social sciences. This article presents two studies contrasting different categorical exploratory techniques. The first study compares Mokken scale analysis (MSA) and two-factor-based exploratory techniques for noncontinuous variables: item factor analysis and Normal Ogive Harmonic Analysis Robust Method (NOHARM). Comparisons are conducted across techniques and in reference to the common principal component analysis model using simulated data under conditions of two-dimensionality with different degrees of correlation (r = 0.0 to 0.6). The second study shows the theoretical and practical results of using MSA and NOHARM (the factorial technique which functioned best in the first study) on two nonsimulated data sets. The nonsimulated data are particularly interesting because MSA was used to solve a theoretical debate. Based on the results from both studies, we show that the ability of NOHARM to detect dimensionality and scalability is similar to MSA when the data comprise two uncorrelated latent dimensions; however, NOHARM is preferable when data are drawn from instruments containing latent dimensions weakly or moderately correlated. This article discusses the theoretical and practical implications of these findings.

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded.

A two to three period analytical chemistry experiment has been developed which allows second year students to explore chemical color tests used to detect adulterated pharmaceuticals. Students prepare several paper analytical devices (PADs) to generate positive and negative controls antibiotics, along with cutting agents such as starch and chalk. These PADs are used to identify the active ingredients and excipients in mystery tablets prepared by their classmates. In the second part of the lab, the students select an individual color test and design an experiment to quantify their mystery pill's active pharmaceutical ingredient (API). Nearly all of the student groups were able to successfully identify adulterants present in their mystery tablets. The quantification of the mystery tablets was also successful with all but one group calculating the correct concentration within 6%. In a postlab assessment, the students identified their largest gains in their ability to analyze data and other information, skill in science writing, and learning of laboratory techniques.

This article outlines the U.S. Army's effort to empirically validate and assess the Comprehensive Soldier Fitness (CSF) program. The empirical assessment includes four major components. First, the CSF scientific staff is currently conducting a longitudinal study to determine if the Master Resilience Training program and the Comprehensive Resilience Modules lead to lasting resilience development in soldiers. Second, the CSF program has partnered with other researchers to conduct a series of longitudinal studies examining the link between physiological, neurobiological, and psychological resilience factors. Third, the CSF program is also incorporating institutional-level data to determine if its material influences health, behavioral, and career outcomes. Fourth, group randomized trials are being conducted to ensure that resilience training incorporated under the CSF program is effective with soldiers. A specific rationale and methodologies are discussed.

Researchers have found that there is an increase in mental heath problems as a result of military-related traumatic events, and such problems increase in the months following return from combat. Nevertheless, researchers have not assessed the impact of early intervention efforts with this at-risk population. In the present study, the authors compared different early interventions with 2,297 U.S. soldiers following a year-long deployment to Iraq. Platoons were randomly assigned to standard postdeployment stress education, Battlemind debriefing, and small and large group Battlemind training. Results from a 4-month follow-up with 1,060 participants showed those with high levels of combat exposure who received Battlemind debriefing reported fewer posttraumatic stress symptoms, depression symptoms, and sleep problems than those in stress education. Small group Battlemind training participants with high combat exposure reported fewer posttraumatic stress symptoms and sleep problems than stress education participants. Compared to stress education participants, large group Battlemind training participants with high combat exposure reported fewer posttraumatic stress symptoms and lower levels of stigma and, regardless of combat exposure, reported fewer depression symptoms. Findings demonstrate that brief early interventions have the potential to be effective with at-risk occupational groups. (Contains 4 tables and 2 figures.)

The purpose of the research was to assess the diagnostic efficiency of the Primary Care Posttraumatic Stress Disorder Screen (PC-PTSD) and the Posttraumatic Stress Disorder Checklist (PCL) as clinical screening tools for active duty soldiers recently returned from a combat deployment. A secondary goal was to examine the item-level characteristics of both the PC-PTSD and the PCL. A validation study conducted with a sample of 352 service members showed that both the PC-PTSD and PCL had good diagnostic efficiency. The overall diagnostic efficiency assessed by the area under the curve (AUC) was virtually the same for both the PC-PTSD and PCL. The most efficient cutoff values for the PC-PTSD were either 2 or 3 "yes" responses with the latter favoring specificity. For the PCL, the most efficient cutoff values were between 30 and 34, mirroring recommended PCL cutoff values from some studies in primary care settings. The examination of item characteristics suggested a 4-item PCL with an AUC virtually identical to that of the full PCL. Item analyses also identified that the most discriminate item in both scales pertained to symptoms of avoidance. Implications and limitations are discussed. (Contains 4 tables and 3 figures.)

Outlines Richard M. Weaver's theory of argument, noting that an important aspect of his rhetorical theory involves specific recommendations for conservatives. Assesses Weaver's rhetoric in terms of his own theory, and concludes that Weaver's rhetoric did not closely follow his advice for conservatives. (MM)

Attempts to clarify Richard Weaver's ideas on rhetoric. Outlines the historical development of his classification of arguments and analyzes his axiology of argument and its political applications. (JMF)

Importance: There has been limited systematic examination of whether risk of suicide attempt (SA) among US Army soldiers is associated with time-related deployment variables, such as time in service before first deployment, duration of first deployment, and dwell time (DT) (ie, length of time between deployments).Objective: To examine the associations of time-related deployment variables with subsequent SA among soldiers who had deployed twice.Design, Setting, and Participants: Using administrative data from January 1, 2004, through December 31, 2009, this longitudinal, retrospective cohort study identified person-month records of active-duty Regular Army enlisted soldiers who had served continuously in the US Army for at least 2 years and deployed exactly twice. The dates of analysis were March 1 to December 1, 2017. There were 593 soldiers with a medically documented SA during or after their second deployment. An equal-probability sample of control person-months was selected from other soldiers with exactly 2 deployments (n = 19 034). Logistic regression analyses examined the associations of time in service before first deployment, duration of first deployment, and DT with subsequent SA.Main Outcomes and Measures: Suicide attempts during or after second deployment were identified using US Department of Defense Suicide Event Report records and International Classification of Diseases, Ninth Revision, Clinical Modification E950 to E958 diagnostic codes. Independent variables were constructed from US Army personnel records.Results: Among 593 SA cases, most were male (513 [86.5%]), white non-Hispanic (392 [66.1%]), at least high school educated (477 [80.4%]), currently married (398 [67.1%]), and younger than 21 years when they entered the US Army (384 [64.8%]). In multivariable models adjusting for sociodemographics, service-related characteristics, and previous mental health diagnosis, odds of SA during or after second deployment were higher among soldiers whose first deployment occurred within the first 12 months of service vs after 12 months (odds ratio, 2.0; 95% CI, 1.6-2.4) and among those with a DT of 6 months or less vs longer than 6 months (odds ratio, 1.6; 95% CI, 1.2-2.0). Duration of first deployment was not associated with subsequent SA. Analysis of 2-way interactions indicated that the associations of early deployment and DT with SA risk were not modified by other characteristics. Multivariable population-attributable risk proportions were 14.2% for deployment within the first 12 months of service and 4.0% for DT of 6 months or less.Conclusions and Relevance: Time in service before first deployment and DT are modifiable risk factors for SA risk among soldiers. [ABSTRACT FROM AUTHOR]

Importance: Mental health of soldiers is adversely affected by the death and injury of other unit members, but whether risk of suicide attempt is influenced by previous suicide attempts in a soldier's unit is unknown.Objective: To examine whether a soldier's risk of suicide attempt is influenced by previous suicide attempts in that soldier's unit.Design, Setting, and Participants: Using administrative data from the Army Study to Assess Risk and Resilience in Servicemembers (STARRS), this study identified person-month records for all active-duty, regular US Army, enlisted soldiers who attempted suicide from January 1, 2004, through December 31, 2009 (n = 9650), and an equal-probability sample of control person-months (n = 153 528). Data analysis was performed from August 8, 2016, to April 10, 2017.Main Outcomes and Measures: Logistic regression analyses examined the number of past-year suicide attempts in a soldier's unit as a predictor of subsequent suicide attempt, controlling for sociodemographic features, service-related characteristics, prior mental health diagnosis, and other unit variables, including suicide-, combat-, and unintentional injury-related unit deaths. The study also examined whether the influence of previous unit suicide attempts varied by military occupational specialty (MOS) and unit size.Results: Of the final analytic sample of 9512 enlisted soldiers who attempted suicide and 151 526 control person-months, most were male (86.4%), 29 years or younger (68.4%), younger than 21 years when entering the army (62.2%), white (59.8%), high school educated (76.6%), and currently married (54.8%). In adjusted models, soldiers were more likely to attempt suicide if 1 or more suicide attempts occurred in their unit during the past year (odds ratios [ORs], 1.4-2.3; P < .001), with odds increasing as the number of unit attempts increased. The odds of suicide attempt among soldiers in a unit with 5 or more past-year attempts was more than twice that of soldiers in a unit with no previous attempts (OR, 2.3; 95% CI, 2.1-2.6). The association of previous unit suicide attempts with subsequent risk was significant whether soldiers had a combat arms MOS or other MOS (ORs, 1.4-2.3; P < .001) and regardless of unit size, with the highest risk among those in smaller units (1-40 soldiers) (ORs, 2.1-5.9; P < .001). The population-attributable risk proportion for 1 or more unit suicide attempts in the past year indicated that, if this risk could be reduced to no unit attempts, 18.2% of attempts would not occur.Conclusions and Relevance: Risk of suicide attempt among soldiers increased as the number of past-year suicide attempts within their unit increased for combat arms and other MOSs and for units of any size but particularly for smaller units. Units with a history of suicide attempts may be important targets for preventive interventions. [ABSTRACT FROM AUTHOR]

Importance: Efforts to remediate the multiple cognitive function impairments in schizophrenia should consider white matter as one of the underlying neural mechanisms.Objective: To determine whether altered structural brain connectivity is responsible for 2 of the core cognitive deficits in schizophrenia- reduced information processing speed and impaired working memory.Design, Setting, and Participants: This cross-sectional study design took place in outpatient clinics from August 1, 2004, to August 31, 2015. Participants included 166 patients with schizophrenia and 213 healthy control individuals. These participants were from 3 independent cohorts, each of which had its own healthy control group. No participant had current or past neurological conditions or major medical conditions. Patients were diagnosed with either schizophrenia or schizoaffective disorder as defined by the DSM-IV. Controls had no Axis I psychiatric disorder.Main Outcomes and Measures: Mediation analyses and structural equation modeling were used to analyze the associations among processing speed, working memory, and white matter microstructures. Whole-brain and regional diffusion tensor imaging fractional anisotropy were used to measure white matter microstructures.Results: Of the study participants, the 166 patients with schizophrenia had a mean (SD) age of 38.2 (13.3) years and the 213 healthy controls had a mean (SD) age of 39.2 (14.0) years. There were significantly more male patients than controls in each of the 3 cohorts (117 [70%] vs 91 [43%]), but there were no significant differences in sex composition among the 3 cohorts. Patients had significantly reduced processing speed (Cohen d = 1.24; P = 6.91 × 10-30) and working memory deficits (Cohen d = 0.83; P = 1.10 × 10-14) as well as a significant whole-brain fractional anisotropy deficit (Cohen d = 0.63; P = 2.20 × 10-9). In schizophrenia, working memory deficit was mostly accounted for by processing speed deficit, but this deficit remained when accounting for working memory (Cohen d = 0.89; P = 2.21 × 10-17). Mediation analyses showed a significant association pathway from fractional anisotropy to processing speed to working memory (P = 5.01 × 10-7). The strength of this brain-to-cognition pathway in different white matter tracts was strongly associated with the severity of schizophrenia-associated fractional anisotropy deficits in the corresponding white matter tracts as determined by a meta-analysis (r = 0.85-0.94; all P < .001). The same pattern was observed in patients and controls either jointly or independently.Conclusions and Relevance: Study findings suggest that (1) processing speed contributes to the association between white matter microstructure and working memory in schizophrenia and (2) white matter impairment in schizophrenia is regional tract-specific, particularly in tracts normally supporting processing speed performance. [ABSTRACT FROM AUTHOR]