Story perspectives

AI Forecasts Remission; Digital CBT Reduces College Eating Disorders

5/30/2026

Summary

Researchers Validate Model

A. Calderon et al. validated a machine-learning model predicting two-year prevention or remission in 26 cohorts in 2024.
E. E. Fitzsimmons-Craft et al. ran a cluster RCT showing digital CBT self-help cut eating-disorder symptoms in college women in 2020.
L. D. D’Adamo (2023) and S. M. Schueller (2019) reviewed CBT-based digital tools and confirmed broad reach for underserved college students.

Summary

Researchers Identify Predictors

Grant et al. identified sociodemographic and psychopathologic predictors of first onset of DSM-IV substance-use, mood, and anxiety disorders in Wave 2 NESARC.
Moffitt et al. found depression and generalized anxiety disorder often appear sequentially, with cumulative comorbidity through age 32 in a prospective birth-cohort study.
Jacobson and Newman demonstrated a bidirectional relationship between anxiety and depression across longitudinal studies in a meta-analysis.

1 of 2

Researchers Validate Model

A. Calderon et al. validated a machine-learning model predicting two-year prevention or remission in 26 cohorts in 2024.
E. E. Fitzsimmons-Craft et al. ran a cluster RCT showing digital CBT self-help cut eating-disorder symptoms in college women in 2020.
L. D. D’Adamo (2023) and S. M. Schueller (2019) reviewed CBT-based digital tools and confirmed broad reach for underserved college students.

1 / 2