Measurement invariance of DSM ‐ IV alcohol, marijuana and cocaine dependence between community‐sampled and clinically overselected studies

Year: 2013

Type: article

Abstract: AIMS: To examine whether DSM-IV symptoms of substance dependence are psychometrically equivalent between existing community-sampled and clinically overselected studies. PARTICIPANTS: A total of 2476 adult twins born in Minnesota and 4121 unrelated adult participants from a case-control study of alcohol dependence. MEASUREMENTS: Life-time DSM-IV alcohol, marijuana and cocaine dependence symptoms and ever use of each substance. DESIGN: We fitted a hierarchical model to the data, in which ever use and dependence symptoms for each substance were indicators of alcohol, marijuana or cocaine dependence which were, in turn, indicators of a multi-substance dependence factor. We then tested the model for measurement invariance across participant groups, defined by study source and participant sex. FINDINGS: The hierarchical model fitted well among males and females within each sample [comparative fit index (CFI) > 0.96, Tucker-Lewis index (TLI) > 0.95 and root mean square error of approximation (RMSEA) < 0.04 for all], and a multi-group model demonstrated that model parameters were equivalent across sample- and sex-defined groups (ΔCFI = 0.002 between constrained and unconstrained models). Differences between groups in symptom endorsement rates could be expressed solely as mean differences in the multi-substance dependence factor. CONCLUSIONS: Life-time substance dependence symptoms fitted a dimensional model well. Although clinically overselected participants endorsed more dependence symptoms, on average, than community-sampled participants, the pattern of symptom endorsement was similar across groups. From a measurement perspective, DSM-IV criteria are equally appropriate for describing substance dependence across different sampling methods.

Source: Addiction

DOI: 10.1111/add.12187

Authors: Jaime Derringer, Robert F. Krueger, Danielle M. Dick, Arpana Agrawal, Kathleen K. Bucholz, Tatiana Foroud, Richard A. Grucza, Michie N. Hesselbrock, Victor Hesselbrock, John Kramer, John I. Nurnberger, Marc Schuckit, Laura J. Bierut, William G. Iacono, Matt McGue

Institutions: University of Colorado Boulder, University of Minnesota, Virginia Commonwealth University, Washington University in St. Louis, Indiana University Indianapolis, University of Connecticut, University of Iowa, University of California San Diego

Language: English

Topic: Substance Abuse Treatment and Outcomes

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism, National Institute of Mental Health, National Institute on Drug Abuse, National Human Genome Research Institute, National Cancer Institute

OpenAlex ID: W2115930982