Event-level positive and negative reinforcement risk factors for alcohol use: Moderation by individual-level alcohol consequences and post-traumatic stress disorder symptom severity

BACKGROUND

The multistage model of drug addiction posits that risk processes contributing to alcohol use change as individuals develop alcohol use disorders. However, few studies have tested this theory outside of the lab or at the event level. We assessed whether event-level associations between positive reinforcement (e.g., positive affect, sociability expectancies) and negative reinforcement risk factors (e.g., negative affect, tension reduction expectancies) and same-/next-day alcohol consumption varied as a function of an individual's level of alcohol consequences. Given elevated alcohol use consequences among individuals with post-traumatic stress disorder (PTSD) and disruptions in reward processing that affect this population, we also tested whether these processes differed based on the presence and severity of PTSD.

METHODS

We used data from a 30-day ecological momentary assessment study with 174 undergraduate women who regularly engaged in heavy episodic drinking. A majority (78%) of the sample had experienced sexual assault and 44% had current PTSD. Analyses used Bayesian multilevel structural equation modeling with diffuse (non-informative) priors. We used markov chain monte carlo (MCMC) algorithms to generate a series of 10,000 random draws from the multivariate posterior distribution of our sample for each model.

RESULTS

Results partially supported the multistage model. Event-level negative reinforcement risk factors only predicted more alcohol consumption among individuals who experienced more alcohol consequences. Findings for positive reinforcement risk factors were partially consistent with hypotheses. Overall, findings appear to operate similarly across PTSD symptom severity.

CONCLUSIONS

Results suggest that interventions for heavy episodic drinking could benefit from attending to an individual's level of alcohol consequences. For example, preventive interventions for individuals who tend to experience few consequences may benefit more from addressing positive reinforcement risk factors, while treatment interventions for those who experience more consequences may benefit from attending to both positive and negative reinforcement.