Health & Justice (Nov 2022)

Psychometric evaluation of an Adverse Childhood Experiences (ACEs) measurement tool: an equitable assessment or reinforcing biases?

  • Xiaohan Mei,
  • Jiayu Li,
  • Zhi-Shu Li,
  • Shun Huang,
  • Li-Li Li,
  • Yang-Hong Huang,
  • Jianhong Liu

DOI
https://doi.org/10.1186/s40352-022-00198-2
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Abstract Background Utilizing Adverse Childhood Experiences (ACEs) measurement scales to assess youths’ adversities has expanded exponentially in health and justice studies. However, most of the ACEs assessment scales have yet to meet critical psychometric standards, especially for key demographic and minority groups. It is critical that any assessment or screening tool is not reinforcing bias, warranting the need for validating ACEs tools that are equitable, reliable and accurate. The current study aimed to examine the structural validity of an ACEs scale. Using data from the 2019 Behavioral Risk Factor Surveillance System (BRFSS), which collected of 97,314 responses collected from adults across sixteen states. This study assessed the psychometric properties and measurement invariance of the ACEs tool under the structural equation modeling framework. Results We found the 11-item ACEs screening tool as a second-order factor with three subscales, all of which passed the measurement invariance tests at metric and scalar levels across age, race, sex, socioeconomic status, gender identity, and sexual orientation. We also found that minority groups experienced more childhood adversity with small effect size, with the exception of the gender identity. Conclusion The ACEs measurement scale from the BRFSS is equitable and free from measurement bias regardless of one’s age, race, sex, socioeconomic status, gender identity, and sexual orientation, and thus is valid to be used to compare group mean differences within these groups. The scale is a potentially valid, viable, and predictive risk assessment in health and justice and research settings to identify high-risk groups or individuals for treatments.

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