Work

Classification for Symptoms of Depression, Anxiety and Stress in Students During the First Covid-19 Lockdown

Year: 2025

Type: article

Abstract: This study presents a comprehensive analysis of the classification of depression, anxiety, and stress levels among students during the COVID-19 pandemic lockdown in Greece using machine learning methods. Leveraging a dataset derived from 1016 responses to the Dass21 questionnaire, this research evaluates the efficacy of five classifiers, IBk (KNN=3), Random Forest, MLP, FURIA, and SMO—in categorizing individuals' mental health status. The findings underscore the potential of machine learning in psychiatric evaluation and the importance of early detection and tailored interventions in mental health care. Article visualizations:

Source: European Journal of Open Education and E-learning Studies

DOI: 10.46827/ejoe.v10i1.5898

Authors: Iliou Theodoros, Georgia Konstantopoulou

Institutions: Democritus University of Thrace, University of Patras

Language: English

Topic: COVID-19 and Mental Health

Subfield: Clinical Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: diamond

Funders: University of Patras, Trakya Üniversitesi