INTRODUCTION AND AIMS

Prescription drug misuse is a considerable problem among young adults, and the identification of types of misuse among this population remains important for prevention and intervention efforts. We use latent class analysis to identify possible distinct latent groups of prescription drug misusers across multiple prescription drug types (pain killers, sedatives and stimulants).

DESIGN AND METHODS

Our data are comprised of a sample of 404 young adults recruited from nightlife scenes via time-space sampling. Through the specification of a zero-inflated Poisson latent class analysis, we evaluate differences in class membership by various demographic factors as well as assess the relationship between class membership and health outcomes, including indications of dependence, problems associated with substance use and mental health.

RESULTS

Our assessment of fit indices led to a four-class solution (dabblers, primary stimulant users, primary downers users and extensive regulars). No demographic differences existed between latent classes. The extensive regular class report the greatest number of symptoms related to dependence, greatest number of problems related to misuse and the greatest mental health problems. The dabblers report the fewest problems and symptoms, while the other two classes experiences problems and symptoms in between the classes on the extremes.

DISCUSSION AND CONCLUSIONS

Prevention efforts should take into account that young adults who misuse prescription drug have different profiles of misuse, and there may be a need for varied interventions to target these different types of misuse.