The intergenerational transmission of child maltreatment: A three-level meta-analysis

Child Abuse Negl. 2018 Oct:84:131-145. doi: 10.1016/j.chiabu.2018.07.037. Epub 2018 Aug 4.

Abstract

A parental history of experiencing child maltreatment is an important risk factor in several etiological theories of child maltreatment. In the past, two reviews have been conducted on the available evidence for intergenerational continuity in child maltreatment, but were only qualitative in nature. Therefore, the present review aimed to provide a quantitative summary of the current knowledge on intergenerational transmission of child maltreatment. In our 3-level random-effects meta-analysis, we included 84 studies reporting on 285 effect sizes and found a medium summary effect of r = 0.289; 95% CI [0.257, 0.337], with significant variation in effect sizes within (level 2) and between (level 3) studies. This implies that in families of parents who experienced maltreatment in their own childhood, the odds of child maltreatment are almost three times the odds of child maltreatment in families of parents without a history of experiencing child maltreatment (OR = 2.990). However, as indications for bias were found, caution is warranted in interpreting this effect. Moderator analyses revealed that the effect of intergenerational transmission was the smallest in children who experienced physical abuse. Further, study quality was negatively associated with effect size magnitude. We highlight the need for an improvement in quality of primary research, and discuss implications of our findings for clinical practice.

Keywords: Child abuse; Child maltreatment; Intergenerational transmission; Maltreatment cycle; Meta-analysis.

Publication types

  • Meta-Analysis
  • Review

MeSH terms

  • Adult Survivors of Child Abuse
  • Child
  • Child Abuse / psychology
  • Child Abuse / statistics & numerical data*
  • Female
  • Humans
  • Intergenerational Relations
  • Male
  • Parents / psychology
  • Physical Abuse / psychology
  • Physical Abuse / statistics & numerical data*
  • Risk Factors