Wang Yanchi, Wang Yan, Huang Wei, Deng Jianhua, Gu Jian
Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), Nantong, 226001, Jiangsu, China.
Affiliated Hospital of Nantong University, Nantong, 226004, Jiangsu, China.
BMC Psychiatry. 2024 Dec 23;24(1):940. doi: 10.1186/s12888-024-06412-9.
New mothers frequently encounter postpartum depression, anxiety, and stress symptoms, which pose challenges in diagnosis and treatment owing to their intricate interplay. This study employs network analysis to explore the interconnections between these symptoms and identify potential intervention points.
The study was carried out from December 2023 to June 2024 at the postpartum clinics of three representative tertiary hospitals in Nantong City. The participants were mothers undergoing their 42-day postpartum check-up. Participants completed the Edinburgh Postnatal Depression Scale (EPDS), the Depression, Anxiety, and Stress Scales (DASS-21), and the Maternal postpartum stress scale (MPSS). The R language was used to construct the network. Network analysis was also carried out to explore the network structure, centrality indices (strength, closeness, betweenness, and expected influence), and the stability of the network.
A total of 625 women were included. The resulting network indicates a close interconnection between communities associated with depression, anxiety, and stress. As assessed on the centrality index, "I have felt sad or miserable" (EPDS-8), "Baby's irregular patterns of daily sleep" (MPSS-9), "lack of time for myself" (MPSS-19), "I have been so unhappy that I have been crying" (EPDS-4), and "Physical appearance after childbirth" (MPSS-20) are the five most important nodes of these three network structures. High network stability (> 0.7).
Postpartum-specific stress symptoms play a significant role in the network of postpartum depression, anxiety, and stress, and identifying the central symptoms of depression, anxiety, and stress can provide a scientific basis for the development of precise interventions.
Not Applicable.
新妈妈经常会出现产后抑郁、焦虑和压力症状,由于这些症状之间存在复杂的相互作用,给诊断和治疗带来了挑战。本研究采用网络分析方法来探索这些症状之间的相互联系,并确定潜在的干预点。
该研究于2023年12月至2024年6月在南通市三家具有代表性的三级医院的产后门诊进行。参与者为正在进行产后42天检查的母亲。参与者完成了爱丁堡产后抑郁量表(EPDS)、抑郁、焦虑和压力量表(DASS-21)以及产妇产后压力量表(MPSS)。使用R语言构建网络。还进行了网络分析,以探索网络结构、中心性指标(强度、接近性、中介性和预期影响力)以及网络的稳定性。
共纳入625名女性。所得网络表明与抑郁、焦虑和压力相关的群落之间存在紧密的相互联系。根据中心性指标评估,“我感到悲伤或痛苦”(EPDS-8)、“宝宝日常睡眠模式不规律”(MPSS-9)、“自己缺乏时间”(MPSS-19)、“我一直非常不开心以至于哭泣”(EPDS-4)以及“产后的外貌”(MPSS-20)是这三种网络结构中最重要的五个节点。网络稳定性较高(>0.7)。
产后特定的压力症状在产后抑郁、焦虑和压力网络中起着重要作用,识别抑郁、焦虑和压力的核心症状可为制定精准干预措施提供科学依据。
不适用。