Social and Behavioral Sciences Commons^™

Artificial Intelligence: An Interprofessional Perspective On Implications For Geriatric Mental Health Research And Care, Brenna N. Renn, Matthew Schurr, Oleg Zaslavsky, Abhishek Pratap

Psychology Faculty Research

Artificial intelligence (AI) in healthcare aims to learn patterns in large multimodal datasets within and across individuals. These patterns may either improve understanding of current clinical status or predict a future outcome. AI holds the potential to revolutionize geriatric mental health care and research by supporting diagnosis, treatment, and clinical decision-making. However, much of this momentum is driven by data and computer scientists and engineers and runs the risk of being disconnected from pragmatic issues in clinical practice. This interprofessional perspective bridges the experiences of clinical scientists and data science. We provide a brief overview of AI with the main …

Psychometric Properties Of The Contextual Body Image Questionnaire For Athletes: A Replication And Extension Study In Female Collegiate Athletes, Tiffany Stewart, Lisa S. Kilpela, Nicole Wesley, K. Baule, Carolyn Becker

Psychology Faculty Research

Background

Although the link between body dissatisfaction and eating disorder (ED) pathology is well-established in general female samples, less is known about contextual body image (CBI) among female athletes. CBI refers to female athletes’ body image concerns in two contexts: sport and daily life. The Contextual Body Image Questionnaire for Athletes (CBIQA) measures four dimensions of body image (Appearance, Thin-Fat Self-Evaluation, Thin-Fat Others’ Evaluation, and Muscularity) in both contexts. In a sample of female collegiate athletes, this study sought to A) investigate the psychometric properties of the CBIQA, B) examine the cross-sectional relation of CBI with ED pathology and negative …