https://scholars.lib.ntu.edu.tw/handle/123456789/586543
標題: | Simulation study to demonstrate biases created by diagnostic criteria of mental illnesses: Major depressive episodes, dysthymia, and manic episodes | 作者: | Chao Y.-S. Lin K.-F. Wu C.-J. HSING-CHIEN WU Hsu H.-T. Tsao L.-C. Cheng Y.-P. Lai Y.-C. Chen W.-C. |
關鍵字: | bias; forward-stepwise regression; frailty; index mining; the health and retirement study | 公開日期: | 2020 | 出版社: | BMJ Publishing Group | 卷: | 10 | 期: | 11 | 來源出版物: | BMJ Open | 摘要: | Objectives Composite diagnostic criteria alone are likely to create and introduce biases into diagnoses that subsequently have poor relationships with input symptoms. This study aims to understand the relationships between the diagnoses and the input symptoms, as well as the magnitudes of biases created by diagnostic criteria and introduced into the diagnoses of mental illnesses with large disease burdens (major depressive episodes, dysthymic disorder, and manic episodes). Settings General psychiatric care. Participants Without real-world data available to the public, 100 000 subjects were simulated and the input symptoms were assigned based on the assumed prevalence rates (0.05, 0.1, 0.3, 0.5 and 0.7) and correlations between symptoms (0, 0.1, 0.4, 0.7 and 0.9). The input symptoms were extracted from the diagnostic criteria. The diagnostic criteria were transformed into mathematical equations to demonstrate the sources of biases and convert the input symptoms into diagnoses. Primary and secondary outcomes The relationships between the input symptoms and diagnoses were interpreted using forward stepwise linear regressions. Biases due to data censoring or categorisation introduced into the intermediate variables, and the three diagnoses were measured. Results The prevalence rates of the diagnoses were lower than those of the input symptoms and proportional to the assumed prevalence rates and the correlations between the input symptoms. Certain input or bias variables consistently explained the diagnoses better than the others. Except for 0 correlations and 0.7 prevalence rates of the input symptoms for the diagnosis of dysthymic disorder, the input symptoms could not fully explain the diagnoses. Conclusions There are biases created due to composite diagnostic criteria and introduced into the diagnoses. The design of the diagnostic criteria determines the prevalence of the diagnoses and the relationships between the input symptoms, the diagnoses, and the biases. The importance of the input symptoms has been distorted largely by the diagnostic criteria. ? 2020 Author(s). |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096029142&doi=10.1136%2fbmjopen-2020-037022&partnerID=40&md5=3a17de21bed776baf33da908dec9fbb9 https://scholars.lib.ntu.edu.tw/handle/123456789/586543 |
ISSN: | 2044-6055 | DOI: | 10.1136/bmjopen-2020-037022 | SDG/關鍵字: | Article; disease burden; dysthymia; human; major clinical study; major depression; mania; mental health care; prevalence; simulation; statistical bias; dysthymia; major depression; mania; statistical bias; Bias; Depressive Disorder, Major; Dysthymic Disorder; Humans; Mania; Prevalence |
顯示於: | 醫學院附設癌醫中心醫院(臺大癌醫) |
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