Predicting Substance Use in Young Adults: The Role of Childhood Adversity.

Background and

Objectives

One of the strongest early factors influencing later psychoactive substance use is adverse childhood experiences (ACEs). Studies investigate a variety of adverse experiences in relation to substance use, yet not all adverse childhood experiences are equal in intensity and harm. Our study aimed to address this gap by examining in detail the associations between individual ACEs, broader ACE categories, and different forms of psychoactive substance use. Materials and

Methods

The study included 709 participants who completed self-report questionnaires. ACEs were measured using the MACE questionnaire. Marijuana use was measured using the CUDIT-R, alcohol use using the AUDIT, and heavy psychoactive substance use using the ASSIST. Linear regression analyses were used to predict associations. As expected, only a small part of the sample reported hard drug use; some analyses are limited to substantially fewer observations.

Results

All regression models were statistically significant and predicted all three categories of psychoactive substances, but if we count the individual adverse experiences, the results become different. Although the results showed that ACE is a significant predictor of hard drug use and explains 25% of the variance, it is separately only emotional neglect that is associated with hard drug use. The regression analysis also explains 14% of the variance in marijuana use, but when considered separately, we found associations only with emotional neglect. The severity of alcohol use explains 13% of the variance, but only a few ACEs reach statistical significance: peer physical bullying, physical violence, and sexual abuse.

Conclusions

The findings of our study suggest that adverse childhood experiences may not be qualitatively equivalent and therefore may not be evaluated only as a cumulative risk score. Separate ACE evaluations, instead of aggregate calculation of ACEs, may be useful to understand better which specific negative experiences have the greatest impact on subsequent use of psychoactive substances. The regression models explain only a small portion of the variance, which suggests that other factors may contribute to a larger share.