Applying machine learning to ecological momentary assessment data to identify predictors of loss-of-control eating and overeating severity in adolescents: A preliminary investigation.

ABSTRACT:

Objective

Several factors (e.g., interpersonal stress, affect) predict loss-of-control (LOC) eating and overeating in adolescents, but most past research has tested predictors separately. We applied machine learning to simultaneously evaluate multiple possible predictors of LOC-eating and overeating severity in pooled and person-specific models.

Method

Twenty-eight adolescents (78.57% female, age = 15.87 ± 1.59 years, BMI %ile = 92.71 ± 8.86) who endorsed ≥ two past-month LOC-eating episodes completed a week-long ecological momentary assessment protocol. Pooled models were fit to the aggregated data with elastic-net regularized regression and evaluated using nested cross-validation. Person-specific models were fit and evaluated as proof-of-concept.

Results

Across adol

SUBMITTER: Hagan K 

PROVIDER: S-EPMC11884998 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature