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Construction of a rapid depression screening model for blood donors in Guangzhou based on decision tree / 中国输血杂志
Chinese Journal of Blood Transfusion ; (12): 705-709, 2023.
Artigo em Chinês | WPRIM | ID: wpr-1004770
ABSTRACT
【Objective】 To investigate the prevalence of depression in blood donors and analyze the related factors, so as to develop a rapid depression screening model for blood donors. 【Methods】 A total of 13 015 street whole blood donors in Guangzhou Blood Center during May to August, 2020 filled in an anonymous e-questionnaire, including social demography information and the Patient Health Questionnaire-9 before donation. The cut-off value for detecting depression was 10. Logistic regression by SPSS 26.0 was used to analyze depression related factors. 2-level decision tree with 30/10 as the minimum number of cases in parent/child node, 10-fold cross validation was used to cut items of PHQ-9 to form the depression screening model. 【Results】 364 out of 13 015 (2.80%) street whole blood donors reported a score ≥ 10. Donors with 18-29 years old (P <0.05), unmarried (P<0.05), less than 50 000 RMB household income per year (P< 0.05) were more prone to depression. 81.96% donors in "<10 scores" group, while 3.85%donors in "≥ 10 scores" group were in two terminal nodes formed by Item-6, 2 and 4 of PHQ-9. After verification by the 10 fold crossover method, the estimated misclassification risk of the model was 1.7%. 【Conclusion】 The screening prevalence of depression based on PHQ-9 in Guangzhou blood donors was 2.8%(95% CI 2.52%-3.09%) . Donation frequency was not related to depression. A rapid and efficient depression screening model for blood donors based on item-6, 2 and 4 of PHQ-9 was developed.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Blood Transfusion Ano de publicação: 2023 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Blood Transfusion Ano de publicação: 2023 Tipo de documento: Artigo