Anatomy Commons^™

Assessments Used By Athletic Trainers To Decide Return-To-Activity Readiness In Patients With An Ankle Sprain, Ryan S. Mccann, Cailee E. Welch Bacon, Ashley M. B. Suttmiller, Phillip A. Gribble, Julie M. Cavallario

Rehabilitation Sciences Faculty Publications

Context: Athletic trainers (ATs) often care for patients with ankle sprains. Expert consensus has been established for rehabilitation-oriented assessments (ROASTs) that should be included in ankle-sprain evaluations. However, the methods ATs use to determine return-to-activity readiness after an ankle sprain are unknown.

Objectives: To identify ATs' methods for determining patients' return-to-activity readiness after an ankle sprain and demographic characteristics of the ATs and their methods.

Setting: Online survey.

Design: Cross-sectional study.

Patients or Other Participants: We recruited 10 000 clinically practicing ATs. A total of 676 accessed the survey, 574 submitted responses (85% completion rate), and 541 respondents met the …

Influences Of Athletic Trainers' Return-To-Activity Assessments For Patients With An Ankle Sprain, Ryan S. Mccann, Cailee E. Welch Bacon, Ashley M. B. Suttmiller, Phillip A. Gribble, Julie M. Cavallario

Rehabilitation Sciences Faculty Publications

Context: Athletic trainers (ATs) inconsistently apply rehabilitation-oriented assessments (ROASTs) when deciding return-to-activity readiness for patients with an ankle sprain. Facilitators and barriers that are most influential to ATs' assessment selection remain unknown.

Objective: To examine facilitators of and barriers to ATs' selection of outcome assessments when determining return-to-activity readiness for patients with an ankle sprain.

Design: Cross-sectional study.

Setting: Online survey.

Patients or other participants: We sent an online survey to 10 000 clinically practicing ATs. The survey was accessed by 676 individuals, of whom 574 submitted responses (85% completion rate), and 541 respondents met the inclusion criteria.

Main outcome …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …