Prevalence of Disordered Eating Behaviors Among Sexual and Gender Minority Youth Varies at the Intersection of Gender Identity and Race/Ethnicity.

Objective: Prior work has documented inequities in disordered eating behavior (DEB) prevalence across gender identity, race, and ethnicity, yet has often ignored the fact that individuals belong to multiple social groups simultaneously. The present study assessed DEB inequities at the intersection of gender identity and race/ethnicity.

Method: The sample included n = 10,287 adolescents (68% gender-diverse, 33% belonging to marginalized racial/ethnic groups).

Examining Longitudinal Relations Between Eating Disorder Symptoms and Negative Emotion Variability in Military Members.

Up to a third of service members and Veterans experience disordered eating. Disordered eating can be maintained through negative reinforcement of painful and unpleasant emotions such as guilt, shame, sadness, and hostility. Hostility is a negative emotion that may be particularly relevant for service members and Veterans, yet hostility's relation to disordered eating remains understudied.

Data mining identifies meaningful severity specifiers for anorexia nervosa.

The fifth edition of defines anorexia nervosa (AN) severity based on body mass index (BMI). However, BMI categories do not reliably differentiate the intensity of AN and comorbid symptoms. Shape/weight overvaluation has been proposed as an alternative severity specifier.

Expanded Functionality and Portability for the Colvars Library.

Colvars is an open-source C++ library that provides a modular toolkit for collective-variable-based molecular simulations. It allows practitioners to easily create and implement descriptors that best fit a process of interest and to apply a wide range of biasing algorithms in collective variable space. This paper reviews several features and improvements to Colvars that were added since its original introduction.