Identifying Cross-Sectional Predictors of Adolescent Sleep Health Through Machine Learning

Featuring: Emily Ricketts, PhD, MS

Learning Objectives:

1. List important cross-sectional predictors of sleep health among diverse adolescents.
2. Recognize the utility of machine learning approaches like random forest or Least Absolute Shrinkage and Selection Operator (LASSO).
3. Describe research implications for adolescent sleep management practices.