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Background/aims: This study compares illegal drug and alcohol use behaviors between medical and nonmedical users of prescription opioids (PO) and nonmedical users with distinct motives to use., Method: An ethically approved cross-sectional study (2010) was conducted on a representative sample of private university students (n = 570), using a self-filled anonymous questionnaire., Results: About 25% reported using PO only medically and 15% nonmedically. The prevalence of alcohol and illegal drug use was consistently higher among nonmedical than medical PO users. Adjusting for age and gender, lifetime medical users of PO were more likely to use marijuana only (OR = 1.8, 95% CI: 1.1, 2.8), while nonmedical users were at higher odds of using marijuana, ecstasy, cocaine/crack, and alcohol problematically. Compared to nonusers, students who took PO nonmedically for nontherapeutic reasons were more likely to use various illegal drugs, but nonmedical users who took PO to relieve pain/help in sleep were only more likely to use marijuana (OR = 2.5, 95% CI: 1.1, 5.4) and alcohol (e.g. alcohol abuse; OR = 3.8, 95% CI: = 1.4, 10.1)., Conclusion: Youth who use PO nonmedically to self-treat have a different alcohol and illegal drug-using profile than those who take it for nontherapeutic reasons., (Copyright © 2013 S. Karger AG, Basel.)

Prevalence of extramedical opioid analgesic use in the US is rising, yet little is known about the nature and extent of problems of dependence related to the use of these drugs. This study uses Latent Class Analysis to empirically define classes of past-year extramedical opioid analgesic users based on observed clustering of DSM-IV defined clinical dependence features; multinomial logistic regression is used to describe differences across these groups. The 2002-2003 public data-files of the National Survey on Drug Use and Health were used to identify 7810 extramedical opioid analgesic users in the past-year. The best-fitting four-class model identified classes that differed quantitatively and qualitatively, with 2% of the users in Class 4 (most severe) and 84% in Class 1 (least severe). Classes 2 and 3 had parallel symptom profiles, but those in Class 3 reported additional problems. Adolescents (12-17 year olds) were at higher odds of being in Class 3 versus older age groups; females were two times as likely to be in Classes 2 and 4, and those with mental health problems were at higher odds of belonging to the more severe classes. Differences by type of past year opioid users were also detected. This study sheds light on the classification and distribution of extramedical opioid analgesic dependence symptoms in the US general population, identifying subgroups that warrant immediate attention., (Copyright (c) 2008 John Wiley & Sons, Ltd.)

Little is known about the extent of problems due to extramedical opioid analgesic use ('analgesic misuse') in the US general population. This study explores the distribution of the seven DSM-IV-defined past-year dependence symptoms in a total household sample of 7,810 past-year extramedical opioid analgesic users using the 2002-2003 National Survey on Drug Use and Health (NSDUH). We tested for differences in opioid analgesic dependence symptom profiles across four subgroups of opioid analgesic users, different levels of deviant behaviors, and presence/absence of serious mental health problems quantified by the Composite International Diagnostic Interview Short Form (CIDI-sf). Generalized Estimated Equations (GEE) models were used to analyze the data. The most common opioid analgesic dependence symptoms were 'tolerance' (17.0%) and 'salience' (13.3%). Opioid analgesic dependence symptom profiles were 'parallel' across the groups of past-year opioid analgesic users, across deviant behavior groups and across presence/absence of serious mental health problems. Extramedical use of opioid analgesics associated with prescription drug use, having high levels of deviant behaviors, and having serious mental health problems were more strongly associated with endorsement of opioid analgesics dependence symptoms.