Opioid dependence latent structure: Two classes with differing severity?

Fiona L. Shand, Tim Slade, Louisa Degenhardt, Andrew Baillie, Elliot C. Nelson

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Aims To examine the structure of illicit opioid abuse and dependence within an opioid dependent sample and its relationship to other clinical variables. Design, setting and participants A cross-sectional study of 1511 opioid dependent individuals recruited through opioid pharmacotherapy clinics in the Sydney area, Australia. Measurements A face-to-face structured interview covering substance use and dependence, psychiatric history, child maltreatment, family background, adult violence and criminal history. Dimensional, latent class and factor mixture models were fit to the opioid abuse and dependence data. Classes were then compared on a range of demographic and clinical covariates. Findings A two-class, one-factor model provided the best fit of all the models tested. The two classes differed with respect to endorsement probabilities on a range of abuse and dependence criteria, and also with respect to the odds of other drug dependence diagnoses, antisocial personality disorder and non-fatal opioid overdose. Within-class severity was associated with similar variables: other drug dependence, borderline personality disorder and opioid overdose. Conclusion In an in-treatment, opioid-dependent sample, there appears to be two classes of individuals exhibiting distinct patterns of abuse and dependence criteria endorsement and to differ on externalizing but not internalizing disorders. This study provides preliminary evidence that the proposed DSM-V opioid use disorder distinction between moderate and severely dependent people is valid. Class one participants were not only more severely dependent, but had greater odds for opioid overdoses, other drug dependence and antisocial personality disorder.

Original languageEnglish
Pages (from-to)590-598
Number of pages9
Issue number3
StatePublished - Mar 2011


  • Factor mixture model
  • Heroin dependence
  • Latent class analysis
  • Latent structure
  • Opioid dependence
  • Opioids


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