Machine Learning-Based Prediction Models for Depression Symptoms Among Chinese Healthcare Workers During the Early COVID-19 Outbreak in 2020: A Cross-Sectional Study.

ABSTRACT:

Background

The 2019 novel coronavirus (COVID-19)-related depression symptoms of healthcare workers have received worldwide recognition. Although many studies identified risk exposures associated with depression symptoms among healthcare workers, few have focused on a predictive model using machine learning methods. As a society, governments, and organizations are concerned about the need for immediate interventions and alert systems for healthcare workers who are mentally at-risk. This study aims to develop and validate machine learning-based models for predicting depression symptoms using survey data collected during the COVID-19 outbreak in China.

Method

Surveys were conducted of 2,574 healthcare workers in hospitals designated to care for COVID-19 patients between 20 Janu

SUBMITTER: Zhou Z 

PROVIDER: S-EPMC9106105 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature