AbstractBackgroundResearch has not identified which patients optimally benefit from brief Motivational Interviewing (bMI) for heavy drinking when delivered to young adults in the Emergency Department (ED).MethodsWe conducted secondary analyses of data from a randomized controlled trial in which 344 young adults (18–35 years) presenting to the ED with alcohol intoxication received either bMI or Brief Advice (BA, control group). We used Latent Class Analysis to derive participants' profiles from baseline characteristics (i.e., sex, age, severity of alcohol use disorder, attribution of ED admission to alcohol use, importance, and confidence to change, cognitive discrepancy, anxiety, depression, and trait reactance). We then conducted a moderation analysis to assess the number of heavy drinking days at short‐term (1‐month) and long‐term (12‐month) follow‐up using negative binomial regressions with interactions between the intervention and derived classes.ResultsFit statistics indicated that a 4‐class solution best fit the data. Class 3 (high severity, importance and discrepancy, and low confidence and anxiety) benefitted more from bMI than BA at short‐ and long‐term follow‐up than Class 1 (younger; lowest severity, importance, discrepancy, reactance, anxiety and depression, and highest confidence). Class 2 (older; highest severity, importance, discrepancy, reactance, anxiety and depression, and lowest confidence) also benefitted more from bMI than BA than did Class 1 at short‐term follow‐up. In these significant contrasts, Class 1 benefitted more from BA than bMI. There were no significant interactions involving Class 4 (more likely to be women; low severity; high levels of anxiety, depression, and reactance).ConclusionsThis study identified the patient profiles that benefitted more from bMI than BA among nontreatment‐seeking young adults who present intoxicated to the ED. The findings have implications for intervention design and argue for the importance of research aimed at developing intervention content tailored to patient profiles.