Rural Opioid and Other Drug Use Disorder Diagnosis: Assessing Measurement Invariance and Latent Classification of DSM-IV Abuse and Dependence Criteria

• Main Author: Brooks, Billy
• Format: Others
• Language: English
• Published: Digital Commons @ East Tennessee State University 2015
• Subjects: prescription drug abuse and misuse; measurement invariance; differential item functioning; item response theory; MIMIC; rural health; Epidemiology
• Online Access: https://dc.etsu.edu/etd/2569; https://dc.etsu.edu/cgi/viewcontent.cgi?article=3952&context=etd

The rates of non-medical prescription drug use in the United States (U.S.) have increased dramatically in the last two decades, leading to a more than 300% increase in deaths from overdose, surpassing motor vehicle accidents as the leading cause of injury deaths. In rural areas, deaths from unintentional overdose have increased by more than 250% since 1999 while urban deaths have increased at a fraction of this rate. The objective of this research was to test the hypothesis that cultural, economic, and environmental factors prevalent in rural America affect the rate of substance use disorder (SUD) in that population, and that diagnosis of these disorders across rural and urban populations may not be generalizable due to these same effects. This study applies measurement invariance analysis and factor analysis techniques: item response theory (IRT), multiple indicators, multiple causes (MIMIC), and latent class analysis (LCA), to the DSM-IV abuse and dependency diagnosis instrument. The sample used for the study was a population of adult past-year illicit drug users living in a rural or urban area drawn from the 2011-2012 National Survey on Drug Use and Health data files (N = 3,369| analyses 1 and 2; N = 12,140| analysis 3). Results of the IRT and MIMIC analyses indicated no significant variance in DSM item function across rural and urban sub-groups; however, several socio-demographic variables including age, race, income, and gender were associated with bias in the instrument. Latent class structures differed across the sub-groups in quality and number, with the rural sample fitting a 3-class structure and the urban fitting 6-class model. Overall the rural class structure exhibited less diversity and lower prevalence of SUD in multiple drug categories (e.g. cocaine, hallucinogens, and stimulants). This result suggests underlying elements affecting SUD patterns in the two populations. These findings inform the development of surveillance instruments, clinical services, and public health programming tailored to specific communities.