Analysis of operant self-administration behaviors with supervised machine learning: Protocol for video acquisition and pose estimation analysis using DeepLabCut and Simple Behavioral Analysis (SimBA).

The use of supervised machine learning to approximate poses in video recordings allows for rapid and efficient analysis of complex behavioral profiles. Currently, there are limited protocols for automated analysis of operant self-administration behavior. We provide methodology to 1) obtain videos of training sessions via Raspberry Pi microcomputers or GoPros 2) obtain pose estimation data using the supervised machine learning software packages DeepLabCut (DLC) and Simple Behavioral Analysis (SimBA) with local high performance computer cluster, 3) comparison of standard MedPC lever response vs quadrant time data generated from pose estimation regions of interest and 4) generation of predictive behavioral classifiers.

Heterogeneity in happiness: A latent profile analysis of single emerging adults.

Whether attending college, entering the workforce, or finding a romantic partner, single emerging adults navigate a pivotal stage of their lives. The present cross-sectional study sought to examine the heterogeneity in happiness of single emerging adults (N = 1,073) with a person-centered, group-differential approach. Using five predictors of life satisfaction (friendship satisfaction, family satisfaction, self-esteem, neuroticism, and extraversion) as indicators in latent profile analysis (LPA), we identified five distinct profiles (or groups) of young singles.

The diversity of well-being indicators: a latent profile analysis.

Introduction: Research on the dimensional structure of subjective well-being (SWB) suggests a five-dimensional solution, consisting of the three established dimensions of life satisfaction, positive affect, and negative affect, and two additional empirically supported dimensions: domain satisfaction and happiness. While these dimensions can be aggregated into a superordinate SWB construct, little research has explored how these dimensions differ in their variation across subpopulations of individuals.

Methods: The present study addresses this gap via secondary analysis of a sample of 1,487 partnered individuals, using the five dimensions of SWB as indicators for latent profile analysis.

Expanding relationship science to unpartnered singles: What predicts life satisfaction?

Singles are an understudied yet growing segment of the adult population. The current study aims to expand the lens of relationship science by examining the well-being of unpartnered, single adults using latent profile analysis. We recruited singles ( = 4,835) closely matched to the United States census (ages 18-65; 57.

A Detroit Student-Run Free Clinic's Management of Select Chronic Diseases.

Aim: The Cass Clinic is a student-run free clinic in Detroit, Michigan that treats chronic diseases including hypertension (HTN), diabetes mellitus (DM), and obesity. Our study aims to quantify the effectiveness of our clinic in managing chronic diseases.

Subject And Methods: This study assessed selected health outcomes for 137 patients who visited our clinic between September 1, 2017 and August 31, 2018 based on initial and most recent surrogate markers including manual blood pressure, hemoglobin A1c (HbA1c), and body mass index (BMI) recorded in the clinic's medical record system dating back to 2012.