Measuring Adverse Childhood Experiences (ACEs) and deprivation during early childhood and it's link to self-reported victimisation during adolescence

Adverse Childhood Experiences (ACEs) are known to have long-term effects on individuals, shaping their emotional, social, and psychological well-being. This study explores the relationship between ACEs and adolescent victimisation using data from the Millennium Cohort Study (MCS), which has followed a group of children born in the UK between 2000 and 2002. The research aims to understand how childhood adversity influences the likelihood of experiencing different forms of victimisation, such as emotional, physical, and sexual victimisation, cyberbullying, and theft. A key aspect of the study is examining how socio-economic conditions (SECs) impact this relationship, providing insights that could help policymakers develop better support systems for at-risk youth.

The primary objective of this study is to refine how ACEs are measured using large-scale data. Traditional approaches to measuring ACEs often rely on self-reported data collected in adulthood, which can be biased by memory and perception. Instead, this research takes a data-driven approach, using statistical techniques to assess ACEs based on parental reports collected when the children were young. Another crucial aim is to examine how exposure to ACEs influences the likelihood of victimisation during adolescence, particularly at ages 14 and 17. Additionally, the study seeks to determine whether socio-economic factors play a role in this relationship, helping to clarify whether financial hardship or other social disadvantages increase the risk of victimisation.

To achieve these objectives, ACEs are measured using reports from both mothers and fathers, capturing different aspects of childhood adversity such as household dysfunction, neglect, and potential abuse. These measures are refined using Item Response Theory (IRT), a statistical approach that ensures the reliability of ACEs indicators. Victimisation is assessed based on self-reported experiences at ages 14 and 17, covering a wide range of harmful experiences, including cyberbullying and theft. The analysis is conducted using logistic regression models, to determine how strongly ACEs predict different forms of victimisation while controlling for socio-economic factors. Data processing and statistical models are carried out using Stata 18, while the IRT ACE measure are implemented in R using the MIRT package.


One of the key challenges identified in this study is the complexity of measuring ACEs accurately. Since childhood adversity is a broad and multifaceted concept, it is difficult to capture its full impact using observational data. The study highlights the need for rigorous methods to ensure that ACEs are measured consistently across different populations and time periods. Accurate measurement is essential for policymakers and practitioners, as it helps them understand which forms of adversity are most relevant to specific generations and social contexts. Moreover, the widespread use of ACEs in public health and social policy has created a risk of misapplying the concept, leading to inappropriate policy responses and misallocation of resources. By improving how ACEs are measured, this research helps ensure that interventions are based on reliable evidence.