Childhood sexual abuse and lifetime depressive symptoms: the importance of type and timing of childhood emotional maltreatment

Psychol Med. 2024 Dec 2;54(15):1-11. doi: 10.1017/S003329172400268X. Online ahead of print.

Abstract

Background: Childhood sexual abuse (CSA) and emotional maltreatment are salient risk factors for the development of major depressive disorder (MDD) in women. However, the type- and timing-specific effects of emotional maltreatment experienced during adolescence on future depressive symptomatology in women with CSA have not been explored. The goal of this study was to fill this gap.

Methods: In total, 203 women (ages 20-32) with current depressive symptoms and CSA (MDD/CSA), remitted depressive symptoms and CSA (rMDD/CSA), and current depressive symptoms without CSA (MDD/no CSA) were recruited from the community and completed self-report measures. Depressive symptoms were assessed using the Beck Depression Inventory (BDI-II) and a detailed maltreatment history was collected using the Maltreatment and Abuse Chronology of Exposure (MACE). Differences in maltreatment exposure characteristics, including multiplicity and severity of maltreatment, as well as the chronologies of emotional maltreatment subtypes were compared among groups. A random forest machine-learning algorithm was utilized to assess the impact of exposure to emotional maltreatment subtypes at specific ages on current depressive symptoms.

Results: MDD/CSA women reported greater prevalence and severity of emotional maltreatment relative to rMDD/CSA and MDD/no CSA women [F(2,196) = 9.33, p < 0.001], specifically from ages 12 to 18. The strongest predictor of current depressive symptoms was parental verbal abuse at age 18 for both MDD/CSA women (variable importance [VI] = 1.08, p = 0.006) and MDD/no CSA women (VI = 0.68, p = 0.004).

Conclusions: Targeting emotional maltreatment during late adolescence might prove beneficial for future intervention efforts for MDD following CSA.

Keywords: adolescence; child sexual abuse; depression; life stress; machine learning.