title: Adverse childhood experiences: translating knowledge into identification of children at risk for poor outcomes.
abstract: OBJECTIVE
  To pilot test a tool to screen for adverse childhood experiences (ACE), and to explore the ability of this tool to distinguish early child outcomes among lower- and higher-risk children.
  
  
  METHODS
  This cross-sectional study used data collected of 102 children between the ages of 4 and 5 years presenting for well-child visits at an urban federally qualified health center. Logistic regression analyses adjusted for child sex, ethnicity, and birth weight were used to test the association between each dichotomized child outcome and risk exposure based on a 6-item (maltreatment suspected, domestic violence, substance use, mental illness, criminal behavior, single parent) and 7-item (plus maternal education) Child ACE tool.
  
  
  RESULTS
  Effect sizes were generally similar for the 6-item and 7-item Child ACE tools, with the exception of 2 subscales measuring development. The adjusted odds of behavior problems was higher for children with a higher compared to a lower 7-item Child ACE score (adjusted odds ratio [aOR] 3.12, 95% confidence interval [CI] 1.34-7.22), as was the odds of developmental delay (aOR 3.66, 95% CI 1.10-12.17), and injury visits (aOR 5.65, 95% CI 1.13-28.24), but lower for obesity (aOR 0.32, 95% CI 0.11-0.92).
  
  
  CONCLUSIONS
  Brief tools can be used to screen for ACE and identify specific early child outcomes associated with ACE. We suggest that follow-up studies test the incorporation of the 7-item Child ACE tool into practice and track rates of child behavior problems, developmental delays, and injuries.
authors: Loma Linda University, Preventive Medicine Department, Loma Linda, CA 92354, USA. amariemitchell@llu.edu
authors: Ariane
authors: A
authors: Marie-Mitchell
authors: Thomas G
authors: TG
authors: O'Connor
mesh_terms: D002649:Child Abuse / Q000517:prevention & control / Q000706:statistics & numerical data*; D002675:Child, Preschool; D003415:Crime / Q000517:prevention & control / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D002658:Developmental Disabilities / Q000453:epidemiology; D017579:Domestic Violence / Q000517:prevention & control / Q000706:statistics & numerical data; D004522:Educational Status; D005260:Female; D006304:Health Status; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D016017:Odds Ratio; D010865:Pilot Projects; D011203:Poverty; D018570:Risk Assessment / Q000379:methods; D020954:Single-Parent Family / Q000706:statistics & numerical data*; D019966:Substance-Related Disorders / Q000453:epidemiology* / Q000517:prevention & control; D014505:Urban Population