Exploring the latent trait of opioid use disorder criteria among frequent nonmedical prescription opioid users

Abstract

Background There is a need to explore the dimensional and categorical phenotypes of criteria of opioid use disorder among frequent nonmedical users of prescription opioids (NMUPO) users. Methods We used pooled data of 2011–2012 National Survey on Drug Use and Health to examine reliability and phenotypic variability in the diagnosis of OUD secondary to NMUPO in a nationally-representative sample of 18+ years-old frequent past-year NMUPO users (120+ days, n=806). Through exploratory factor analysis (EFA) and latent class analysis (LCA), we examined 10 past-year OUD criteria. We examined associations between the latent classes and sociodemographic/psychiatric/NMUPO correlates. Results OUD criteria were unidimensional, and a three-class model was the overall best fitting solution for characterizing individuals into phenotypes along this unidimensional continuum: a “non-symptomatic class” (40.7%), “Tolerance-Time spent class” (29.0%) with high probability of endorsing Tolerance/Time Spent criteria, and a “High-moderate symptomatic class” (30.1%). The last class was significantly associated with being male, having insurance and obtaining prescription opioids (PO) nonmedically via “doctor shopping” as compared to the non-symptomatic class. “Tolerance-Time spent class” was significantly associated with being younger (18–25 years) and obtaining PO nonmedically from family/friends as compared to the non-symptomatic class. Conclusion This study revealed the different characteristics and routes of access to PO of different classes of frequent NMUPO users. It is possible that these groups may respond to different interventions, however such conclusions would require a clinical study.

An Item Response Theory Analysis of DSM-5 Heroin Use Disorder in a Clinical Sample of Chinese Adolescents

“…As expected, the HUD criteria measured a single underlying construct in this clinical sample of adolescent heroin users. This finding echoes the previous studies focusing on other substance use disorders in adults or adolescents (Wu et al, 2009b; Hasin et al, 2012; Saha et al, 2012; Caetano et al, 2016; Castaldelli-Maia et al, 2016; Duresso et al, 2016).…”

“…Since the publication of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition ( DSM-5 ) (American Psychiatric Association, 2013), many studies have examined the psychometric properties of the DSM - 5 diagnostic criteria for substance use disorders in adult users using item response theory (IRT). These studies involved the use of alcohol (e.g., Mewton et al, 2011; Caetano et al, 2016), cannabis (Hasin et al, 2012), khat (Duresso et al, 2016), prescription opioids (Castaldelli-Maia et al, 2016), and cocaine (Hasin et al, 2012). These studies are of great importance because they testified to the validity of DSM-5 diagnoses and disorders in the samples of users.…”

Psychometric Performance of a Substance Use Symptom Checklist to Help Clinicians Assess Substance Use Disorder in Primary Care

“…To our knowledge, this is the first study to evaluate a Substance Use symptom checklist of DSM-5 criteria when used routinely in primary care; however, findings are consistent with psychometric studies of SUD criteria in epidemiology studies 31 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 and clinical trials. 31 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 Psychometric studies were instrumental in the decision to revise DSM criteria, from abuse and dependence ( DSM-IV ) to a single SUD represented by a continuum of severity from 2 to 11 symptoms ( DSM-5 ).…”

Opioid use disorder (OUD) and treatment for opioid problems among OUD symptom subtypes in individuals misusing opioids

“…Although several studies have found heterogeneity among individuals with OUD symptoms ( Castaldelli-Maia et al, 2016 , Ghandour et al, 2008 , Tarrahi et al, 2015 , Wu et al, 2011 ), little is known about 1) subtypes among persons that misuse opioids that vary by patterns of OUD symptoms, 2) the association of subtypes with other demographics and clinical characteristics, and 3) how these subtypes differ with respect to OUD treatment. A better understanding of OUD symptom subtypes is important for addressing unmet treatment needs.…”