潜在类模型
爱丁堡产后忧郁量表
萧条(经济学)
神经质
队列
心理学
临床心理学
心情
苦恼
沉思
精神科
焦虑
医学
人格
认知
内科学
抑郁症状
社会心理学
统计
数学
经济
宏观经济学
作者
Jiwei Sun,Jiahuan Li,Xuan Zhang,Ying Wang,Danfeng Cao,Juan Wang,Huayu Bai,Pingzhen Lin,Huihui Zhang,Yaoyao Sun,Fenglin Cao
标识
DOI:10.1016/j.jad.2020.07.040
摘要
Perinatal depression is the most prevalent mental disorder during the perinatal period, and research suggests that it presents heterogeneously. We aimed to explore how subtypes of perinatal depression present in terms of multivariate patterns of stable characteristics. A cohort study was conducted from March 2016 to March 2018 with Chinese women in the prenatal period (n = 3186). Of the participants, 682 (21.41%) women with Edinburgh Postnatal Depression Scale scores ≥10, indicating probable depression, were included, with the remaining 2504 (78.59%) representing the control group. We assessed mood distress, cognition, life history, emotional regulation, and personality, and used latent class analysis and latent transition analysis to identify perinatal depression subtypes. Of the 682 women with probable depression, only 598 were included in the full analyses, as they completed at least 10 questionnaires. A second, non-overlapping sample and a follow-up cohort were used. We identified four subtypes: 1) a highly distressed type characterized by distress across all domains, high levels of rumination and neuroticism, and reduced trait mindfulness; 2) two moderately distressed types: one with high trauma and low perceived social support, and another with low trauma, high perceived social support, and expressive suppression; and 3) a slightly distressed subtype. We only collected cost and time spent in hospital from medical records. We only had a small follow-up sample. This multidimensional subtyping of women with perinatal depression could help reduce the apparent heterogeneity of perinatal depression. Distinguishing the subtype characteristics facilitates identifying underlying causes of perinatal depression.
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