Global epidemiology
CART machine learning peeling pathways for anxiety and depression severity classification in population screening
By Faro A, Tejada J and Al-Delaimy WK.
Abstract
Background
Regular population-level monitoring of anxiety and depression requires brief assessment strategies that reduce respondent burden while retaining classification performance.
Objective
This study aimed to: (1) apply CART decision tree peeling to the GAD-7 and PHQ-9 scales in a nationwide sample; (2) derive abbreviated decision rules that reproduce the severity categories defined by the full scales; and (3) examine multiple classification pathways for epidemiological mental health surveillance.