A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic

Abstract

The COVID-19 pandemic has caused massive effects on the situation of public mental health. A fast online questionnaire for screening and evaluating mental symptoms is urgent. In this work, we developed a new 19-item self-assessment Fast Screen Questionnaire for Mental Illness Symptoms (FSQ-MIS) to quickly identify mental illness symptoms. The FSQ-MIS was validated on a total of 3828 young adult mental disorder patients and 984 healthy controls. We applied principal component analysis (PCA), receiver operating characteristic (ROC) curve, and general log-linear analysis (GLA) to evaluate the construct and parallel validity. Results demonstrate that the proposed FSQ-MIS shows high test-retest reliability (0.852) and split-half reliability (0.844). Six factors obtained using PCA explained 54.3% of the variance and showed high correlations with other widely used scales. The ROC results (0.716–0.983) revealed high criterion validity of FSQ-MIS. GLA demonstrated the advantage of FSQ-MIS in predicting anxiety and depression prevalence in COVID-19, supporting the efficiency of FSQ-MIS as a tool for research and clinical practice.