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-...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2022-08-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-022-02086-7 |
| _version_ | 1811315457317142528 |
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| author | Fang Chen Weizheng Yan Vince D. Calhoun Linzhen Yu Lili Chen Xiaoyi Hao Leilei Zheng |
| author_facet | Fang Chen Weizheng Yan Vince D. Calhoun Linzhen Yu Lili Chen Xiaoyi Hao Leilei Zheng |
| author_sort | Fang Chen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T11:30:48Z |
| format | Article |
| id | doaj.art-6018d95f72f3414688347eea2936f2f6 |
| institution | Directory Open Access Journal |
| issn | 2158-3188 |
| language | English |
| last_indexed | 2024-04-13T11:30:48Z |
| publishDate | 2022-08-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj.art-6018d95f72f3414688347eea2936f2f62022-12-22T02:48:34ZengNature Publishing GroupTranslational Psychiatry2158-31882022-08-011211610.1038/s41398-022-02086-7A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemicFang Chen0Weizheng Yan1Vince D. Calhoun2Linzhen Yu3Lili Chen4Xiaoyi Hao5Leilei Zheng6Department of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory UniversityDepartment of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityDepartment of Psychiatry, Second Affiliated Hospital, School of Medicine, Zhejiang UniversityAbstract 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.https://doi.org/10.1038/s41398-022-02086-7 |
| spellingShingle | Fang Chen Weizheng Yan Vince D. Calhoun Linzhen Yu Lili Chen Xiaoyi Hao Leilei Zheng A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic Translational Psychiatry |
| title | A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic |
| title_full | A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic |
| title_fullStr | A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic |
| title_full_unstemmed | A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic |
| title_short | A fast online questionnaire for screening mental illness symptoms during the COVID-19 pandemic |
| title_sort | fast online questionnaire for screening mental illness symptoms during the covid 19 pandemic |
| url | https://doi.org/10.1038/s41398-022-02086-7 |
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