Diversity of the National Medical Student Body - Four Decades of Inequities.

A racially and ethnically diverse health care workforce remains a distant goal, the attainment of which is contingent on the inclusivity of the national medical student body. We examined the diversity of medical school applicants and enrollees over the past four decades with an eye toward assessing the progress made. Data on the gender and race or ethnic group of enrollees in all medical doctorate degree-granting U.S. medical schools from 1978 through 2019 were examined. The percentage of female enrollees doubled during this period, and women now constitute more than half the national medical student body. This upturn has been attributed largely to an increase by a factor of 12 in the enrollment of Asian women. The corresponding decrease in the percentage of male enrollees, most notably White men, was offset by an increase by a factor of approximately 5 in the enrollment of Asian men. The percentages of enrollees from Black, Hispanic, and other racial and ethnic groups that are underrepresented in medicine remain well below the percentages of these groups in the national Census.

Interpersonal Autonomic Physiology: A Systematic Review of the Literature.

Interpersonal autonomic physiology is defined as the relationship between people's physiological dynamics, as indexed by continuous measures of the autonomic nervous system. Findings from this field of study indicate that physiological activity between two or more people can become associated or interdependent, often referred to as physiological synchrony. Physiological synchrony has been found in both new and established relationships across a range of contexts, and it correlates with a number of psychosocial constructs. Given these findings, interpersonal physiological interactions are theorized to be ubiquitous social processes that co-occur with observable behavior. However, this scientific literature is fragmented, making it difficult to evaluate consistency across reports. In an effort to facilitate more standardized scholarly approaches, this systematic review provides a description of existing work in the area and highlights theoretical, methodological, and statistical issues to be addressed in future interpersonal autonomic physiology research.

Modafinil as a potential motion sickness countermeasure.

INTRODUCTION: Motion sickness adversely affects military air and sea operations. Medications help prevent motion sickness but are frequently associated with side effects. Better medications or combinations of medications are needed. Dextroamphetamine has documented anti-motion sickness effects but also has a potential for abuse. Modafinil is a relatively new central nervous system stimulant that has none of the drawbacks of dextroamphetamine, but has not been evaluated for the treatment of motion sickness. METHODS: This double-blind, placebo-controlled study evaluated the anti-motion sickness efficacy of modafinil, alone or in combination with oral scopolamine. Moderate nausea was induced via a Coriolis cross-coupling stimulus. There were 60 participants who were assigned randomly to 1 of 3 conditions: 1) 2 placebo pills (DP); 2) modafinil plus placebo (MP); or 3) modafinil plus oral scopolamine (MS). The primary measure of drug efficacy was the number of head tilts tolerated upon reaching moderate nausea for 1 min without abatement. RESULTS: The combination of modafinil and scopolamine (MS) allowed subjects to tolerate significantly more head tilts than placebo, but modafinil alone (MP) failed to differ significantly from placebo (DP). No significant cognitive performance decrements were observed among the three experimental conditions. CONCLUSION: Modafinil was not found to be more effective than placebo. Further testing is recommended to determine whether the potentially promising combination of modafinil and scopolamine provides better efficacy or fewer side effects than scopolamine administered alone.

Testing demographic differences for alcohol use initiation among adolescents for the decisional balance and situational temptation prevention inventories.

Alcohol use by middle school-aged students is a public health concern because of the numerous adverse social, health and psychological outcomes. Prevention programs attempt to intervene before alcohol use begins. A tailored, computer-delivered program for the prevention of alcohol use and a series of new transtheoretical model measures were developed, including decisional balance (Pros and Cons) of alcohol use and Situational Temptations to Try Alcohol. This study investigated if there were any demographic differences on these measures in a sample of 6th grade middle school students from 20 schools (N=4151) at baseline. Three factorial analysis of variance tests were conducted to explore the impact of race (whites vs. non-whites), ethnicity (Hispanics vs. Non-Hispanics) and gender (males vs. females). A significant two-way interaction effect was found between gender and ethnicity for Pros of Alcohol Use. A significant three-way interaction effect was found between gender, race and ethnicity for Cons of Alcohol Use. Main effects were found for the three demographic factors for Situational Temptations to Try Alcohol. However, the effect sizes for the interaction effects and main effects were very small (all below η(2)=.01), suggesting that race/ethnicity and gender alone may not be highly influential factors in the Decisional Balance for the Prevention of Alcohol and Situational Temptations to Try Alcohol in adolescence. The implications for these results and alcohol use prevention among this group are discussed.

Prevention of smoking in Middle School Students: psychometric assessment of the Temptations to Try Smoking Scale.

Establishment of psychometrically sound measures is critical to the development of effective interventions. The current study examined the psychometric properties, including factorial invariance, of a six item Temptations to Try Smoking Scale on a sample of middle school students. The sample of 6th grade students (N=3527) was from 20 Rhode Island middle schools and was 52% male and 84% white. The Temptations to Try Smoking Scale consisted of two correlated subscales: Positive Social and Curiosity/Stress. Structural equation modeling was implemented to evaluate the factorial invariance across four different subgroups defined by gender (male/female), race (white/black), ethnicity (Hispanic/Non-Hispanic), and school size (<200/ >200 6th graders). A model is factorially invariant when the measurement model is the same in each of the subgroups. Three levels of invariance were examined in sequential order: 1) Configural Invariance (unconstrained nonzero factor loadings); 2) Pattern Identity Invariance (equal factor loadings); and 3) Strong Factorial Invariance (equal factor loadings and measurement errors). Strong Factorial Invariance provided a good fit to the model across gender (CFI=.96), race (CFI=.96), ethnicity (CFI=.94), and school size (CFI=.97). Coefficient Alphas for the two subscales, Positive Social and Curiosity/Stress, were .87 and .86, respectively. These findings provide empirical support for the construct validity of the Temptations to Try Smoking Scale in middle school students.

The effects of EEG data transformations on the solution accuracy of principal component analysis.

Principal component analysis (PCA) is a commonly used multivariate procedure that reduces the dimensionality of a data set. When applied to quantitative electroencephalogram (qEEG) data, PCA produces components that may represent functional systems within the brain. Unfortunately, qEEG, like many other physiological measures, produce distributions that are positively skewed. In response, researchers often transform qEEG data prior to conducting a PCA, which does not require univariate or multivariate normality. Despite this, researchers continue to transform qEEG data with limited knowledge of how such transformations will affect the accuracy (precision) of their component solutions. The purpose of the present investigation was to examine the effects of several commonly used data transformation procedures on PCA solution accuracy.