From Machine Learning to Deep Learning: A comprehensive study of alcohol and drug use disorder

This study aims to train and validate machine learning and deep learning models to identify patients with risky alcohol and drug misuse in a Screening, Brief Intervention, and Referral to Treatment (SBIRT) program. An observational cohort of 6978 adults was admitted in the western region of Alabama at three medical facilities between January and December of 2019. Data were cleaned and pre-processed using data imputation techniques and an augmented sampling data method. The primary analysis involved the multi-class classification of alcohol and drug misuse. Our study shows that accurate identification of alcohol and drug use screening instrument scores was best accomplished with mixed-effects models following the imputation of missing data using the Generative Adversarial Imputation Networks (GAIN) method and then followed by applying the Synthetic Minority Over-sampling TEchnique-Nominal Continuous (SMOTE-NC) data augmentation method. Although mixed models are commonly employed in studies of electronic health records (EHRs), using the GAIN method followed by SMOTE-NC for diagnosing alcohol and drug use disorder is novel and original

Belonging and Support: Women Veterans' Perceptions of Veteran Service Organizations

Background and Purpose: This research sought to better understand female veterans’ underutilization of veteran and military service organizations (VSO/MSOs).  Specifically, the Service Women’s Action Network (SWAN) conducted a needs assessment examining historically low levels of social cohesion among women veterans, and then a research team analyzed data for its statistical and practical significance. The intent of this research was to provide guidance about how best to develop organizational programming around the needs of military women. Materials &amp; Methods: Secondary analysis of 2016 SWAN needs assessment survey data involved mixed-methods analysis of open- and closed-ended questions related to VSO/MSO participation and included: frequency tables, geospatial analysis, multivariate regression analysis with educational achievement, race/ethnicity, service branch, and service era predicting participation. Quantitative analyses were followed by content analysis of questions that provided additional insight into the participants’ perceptions of VSO/MSOs. Results: Of the sample (n = 829) in the present study, 31.1% of respondents were members of one or more VSO/MSOs. Current members (n = 219, response rate 84.9%) identified three primary organizations in which they participated, including: The American Legion (32%), Disabled American Veterans (28%), and the Veterans of Foreign Wars (28%). Some variation in VSO membership was evident geographically, with participation highest in Maryland and Wisconsin. Regression models indicated that participation in VSOs by female veterans is predicted by higher levels of education (OR = 1.66, 95% CI [1.04, 2.66]) and Hispanic/Latino ethnicity (OR = 2.60, 95% CI [1.07, 6.33]). Statistical significance was not found for predictor variables of service branch or service era, although greater proportions were Army (30.4%) and Post-9/11 (27.6%). Qualitative analyses indicated that respondents (n = 773) did not feel welcome in existing service member and veteran groups (25.23%) and stated that this was among the reasons they were not currently a member (29.75%).    Conclusion: Study findings offer perspective regarding women veterans’ participation in and perceptions of VSO/MSOs. The findings offer important feedback for organizations hoping to reach women veterans, the fastest growing veteran population. Targeted programming is indicated.  Recommendations also include single-sex offerings, available child care at some events, and tailored outreach with peer support efforts. </p

Psychological Resilience and Cognitive Function Among Older Military Veterans.

The purpose of this study was to explore the association between psychological resilience and cognitive function in military veterans. We obtained public-use data from the Health and Retirement Study (HRS) for this cross-sectional study of military veterans aged 52 to 101 years (n = 150). We estimated a multivariable linear regression model in which cognitive function served as the dependent variable and psychological resilience served as the independent variable. After controlling for demographics, health conditions, and health behaviors, veterans who had higher psychological resilience scores had better cognitive function (b = 0.22, p = 0.03). Our findings suggest that psychological resilience may be associated with cognitive function among veterans. These findings highlight the importance of assessing psychological resilience in gerontological social work practice

Social Support Mediates the Relationship Between Mental-Physical Multiple Morbidities and Engagement in Aerobic Physical Activity Among Military Service Members and Veterans

Some research shows that physical activity levels are low among veterans, but research gaps exist specifically in regards to promoting physical activity in veterans with multiple morbidities. For the present study, we retrieved data from the 2015 Behavioral Risk Factor Surveillance System. The study sample included 57,842 military service members and veterans. We carried out a mediation analysis to determine the effect of social support on the relationship between multiple morbidities and aerobic physical activity. Social support partially mediated the relationship between the presence of multiple morbidities and aerobic physical activity, a*b= -0.003, [95% CI = -0.007, -0.001]. Programs aimed at facilitating adequate social support among service members and veterans with multiple morbidities may increase their uptake of aerobic physical activity, and thus, decrease concomitant risk for health-related disorders. </p

Is Large Lepton Mixing Excluded?

The original \bnum -(or $\bar{\nu}_{\tau}$-) energy spectrum from the gravitational collapse of a star has a larger average energy than the spectrum for \bnue since the opacity of \bnue exeeds that of \bnum (or $\nu_{\tau}$). Flavor neutrino conversion, \bnue $\leftrightarrow$ \bnum, induced by lepton mixing results in partial permutation of the original \bnue and \bnum spectra. An upper bound on the permutation factor, $p \leq 0.35$ (99$\%$ CL) is derived using the data from SN1987A and the different models of the neutrino burst. The relation between the permutation factor and the vacuum mixing angle is established, which leads to the upper bound on this angle. The excluded region, $\sin^2 2\theta > 0.7 - 0.9$, covers the regions of large mixing angle solutions of the solar neutrino problem: ``just-so" and, partly, MSW, as well as part of region of $\nu_{e} - \nu_{\mu}$ oscillation space which could be responsible for the atmospheric muon neutrino deficit. These limits are sensitive to the predicted neutrino spectrum and can be strengthened as supernova models improve.Comment: 20 pages, TeX file. For hardcopy with figures contact [email protected]. Institute for Advanced Study number AST 93/1

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease