Predicting depression and anxiety of Chinese population during COVID-19 in psychological evaluation data by XGBoost.

ABSTRACT:

Background

Due to the onset of sudden stress, COVID-19 has greatly impacted the incidence of depression and anxiety. However, challenges still exist in identifying high-risk groups for depression and anxiety during COVID-19. Studies have identified how resilience and social support can be employed as effective predictors of depression and anxiety. This study aims to select the best combination of variables from measures of resilience, social support, and alexithymia for predicting depression and anxiety.

Methods

The eXtreme Gradient Boosting (XGBoost¹) model was applied to a dataset including data on 29,841 participants that was collected during the COVID-19 pandemic. Discriminant analyses on groups of participants with depression (DE²), anxiety (AN

SUBMITTER: Tian Z 

PROVIDER: S-EPMC9710109 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature