ArticleTranslational psychiatry2022
A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic.
Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Evolving role of the internet in China as a medium for promoting psychological well-being and mental health: a scoping review.The Lancet regional health. Western Pacific · 2025Review
- Trends in psychiatric diagnoses by COVID-19 infection and hospitalization among patients with and without recent clinical psychiatric diagnoses in New York city from March 2020 to August 2021.Translational psychiatry · 2022Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
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.
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