First-onset major depression during the COVID-19 pandemic: A predictive machine learning model.

ABSTRACT:

Background

This study longitudinally evaluated first-onset major depression rates during the pandemic in Italian adults without any current clinician-diagnosed psychiatric disorder and created a predictive machine learning model (MLM) to evaluate subsequent independent samples.

Methods

An online, self-reported survey was released during two pandemic periods (May to June and September to October 2020). Provisional diagnoses of major depressive disorder (PMDD) were determined using a diagnostic algorithm based on the DSM criteria of the Patient Health Questionnaire-9 to maximize specificity. Gradient-boosted decision trees and the SHapley Additive exPlanations technique created the MLM and estimated each variable's predictive contribution.

Results

There were 3532 partic

SUBMITTER: Caldirola D 

PROVIDER: S-EPMC9044654 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature