Addressing the health care needs of a 21st-century nation that is experiencing increased diversity and disparity will require new models of educating future providers. The cultural competence and confidence model was the guiding framework in a study evaluating the influence of cultural educational offerings on the transcultural self-efficacy (TSE) perceptions in baccalaureate nursing students. The Transcultural Self-Efficacy Tool was used to measure perceived TSE in a pretest (N = 260), posttest (N = 236) study over an academic year. Significant changes were demonstrated in overall self-efficacy and on the cognitive, practical, and affective subscales. A classification and regression tree analysis identified social orientation as the demographic variable most predictive of the TSE level. This study supports previous research where positive changes were found in students' TSE based on the inclusion of cultural interventions in the nursing curriculum.

Metabolic syndrome (MetS) in young adults (age 20–39) is often undiagnosed. A simple screening tool using a surrogate measure might be invaluable in the early detection of MetS. Methods. A chi-squared automatic interaction detection (CHAID) decision tree analysis with waist circumference user-specified as the first level was used to detect MetS in young adults using data from the National Health and Nutrition Examination Survey (NHANES) 2009-2010 Cohort as a representative sample of the United States population (n = 745). Results. Twenty percent of the sample met the National Cholesterol Education Program Adult Treatment Panel III (NCEP) classification criteria for MetS. The user-specified CHAID model was compared to both CHAID model with no user-specified first level and logistic regression based model. This analysis identified waist circumference as a strong predictor in the MetS diagnosis. The accuracy of the final model with waist circumference user-specified as the first level was 92.3% with its ability to detect MetS at 71.8% which outperformed comparison models. Conclusions. Preliminary findings suggest that young adults at risk for MetS could be identified for further followup based on their waist circumference. Decision tree methods show promise for the development of a preliminary detection algorithm for MetS.

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In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view.

Purpose: The purpose of the current investigation was to assess Metabolic Syndrome prevalence and risk estimates using United States nationally representative data. Methods:Study sample was derived from 6 National Health and Nutrition Examination Survey (NHANES) cohorts from [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012], N = 9,326 (male: n = 4,814; female: n = 4,512) including ages 18-59 presenting as fasted for 12 hours prior to laboratories collection. Variables included AHA/NHBLI Metabolic Syndrome classification criteria as well as additional cardiometabolic measures. Prevalence of Metabolic Syndrome and risk factors across cohorts as well as relative risk estimates were derived. Estimates were adjusted for age, race, and sex.Results: There was no statistically significant difference between Metabolic Syndrome prevalence across cohorts. The order of Metabolic Syndrome criteria from highest to lowest risk were waist circumference, triglycerides, HDL, fasting plasma glucose, and blood pressure for the total sample and across sex, with women presenting with larger risk estimates than men. Women had larger prevalence of waist circumference, HDL, and blood pressure risk factors compared to men who had a larger prevalence of triglyceride and fasting plasma glucose risk factors. Those presenting with Metabolic Syndrome were twice as likely to have a cardiovascular event.Conclusion: Waist circumference and triglycerides were the Metabolic Syndrome risk factors with the highest prevalence and associated risk of developing Metabolic Syndrome. Those with Metabolic Syndrome were at increased risk of having a cardiovascular event.