Predicting posttraumatic stress and depression symptoms among adolescents in the extended postpartum period

预测产后延长期内青少年创伤后应激障碍和抑郁症状

阅读:1

Abstract

BACKGROUND: Adolescent childbirth continues as a public health concern, and investigation of postpartum posttraumatic stress symptoms (PTSS) and depression is important to inform future research and practice. Longitudinal studies exploring PTSS alone or in combination with depression are non-existent for postpartum adolescent populations. This study aimed to identify stress/PTSS and depression symptoms at 72 hours and three, six, and nine months postpartum, and determine if symptoms at each time point predicted later symptoms. METHODS: A convenience sample of 303 adolescents 13-19 years of age were recruited from two postpartum units of one, large, public hospital. The Impact of Event Scale and the Edinburgh Postpartum Depression Inventory provided a screen of symptoms for stress/PTSS and depression at all time points. A lagged autoregressive model was developed to assess the predictive power of symptoms at each time point to the next across the extended postpartum period. RESULTS: About 30% of adolescents displayed early symptoms; 20% showed symptoms at the final time point. Early symptoms did not predict symptoms at 3 months; yet, symptoms at 3 months predicted symptoms at 6-9 months. LIMITATIONS: Attrition at final time points necessitated pooled data. Adolescents were primarily older, Hispanics, and recruited from one public hospital decreasing demographic representation. Use of screening tools prevented diagnostic outcomes. Unknown stressors occurring before and after pregnancy or birth may have influenced final outcomes. CONCLUSIONS: Early symptoms were common and 3 month symptoms predicted later symptoms. For at risk adolescents, a plan for follow-up beyond hospital discharge is recommended.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。