Clinical Correlates of Smoking Status in Men and Women with Opioid Use Disorder

Assessing Substance Use Disorder Among Social Security Administration Disability Applicants

OBJECTIVE

Co-occurrence of substance use disorder and mental illness complicates treatment and is associated with increased disability. However, identification of substance use disorder in populations recently engaged in treatment can be challenging. This study aimed to examine traditional screening tools for substance use disorder and proxy characteristics (i.e., demographic characteristics, behaviors, and diagnoses) as predictors of clinician-observed substance use disorder.

METHODS

The Supported Employment Demonstration, funded by the Social Security Administration, studied 2,960 adults whose applications for disability benefits because of mental illness were recently denied. In a subsample (N=1,354) for whom substance use disorder was determined by community-based teams during follow-up, the authors used logistic regression to identify baseline predictors of observed substance use disorder and compared the sensitivity and specificity of detection by using standardized screening tools (Alcohol Use Disorder Identification Test [AUDIT], 10-item Drug Abuse Screening Test [DAST-10]) with detection via decision trees based on proxy characteristics.

RESULTS

Using decision trees based on a combination of personal characteristics (sensitivity=0.47, specificity=0.83, area under the curve [AUC]=0.71) or personal characteristics including diagnostic data (sensitivity=0.54, specificity=0.81, AUC=0.72) provided more accurate identification of substance use disorder than using a combination of the AUDIT and DAST-10 (sensitivity=0.34, specificity=0.88, AUC=0.61). Adding the combined AUDIT and DAST-10 substance use disorder indicator to either tree negligibly improved accuracy.

CONCLUSIONS

In populations recently engaged in treatment, for whom standardized substance use disorder screening tools are less accurate than expected, consideration of personal characteristics could improve the detection of substance use disorder essential for treatment planning.

Longitudinal associations between age 20 problematic substance use and opioid use disorder incidence at age 30 - findings from an urban cohort

This study used data from a longitudinal prevention study in an urban cohort to examine associations between nicotine dependence, alcohol, and cannabis use disorder and disorder criteria at age 20, with opioid use disorder (OUD) incidence or criteria onset by age 30. The study sample included 1408 participants (57.5% female, 72.5% African American) drawn from two cohorts of participants in a mid-Atlantic region of the U.S. as part of a series of randomized controlled trials of elementary school-based universal prevention interventions. Lifetime cannabis use disorder (CUD), alcohol use disorder (AUD; both DSM-IV), and current nicotine dependence (Fagerstrom Test for Nicotine Dependence, FTND) assessed at age 20 were used to predict (1) DSM-IV lifetime OUD at age 30, and (2) OUD criteria between ages 20 and 30 in multivariable logistic regression models. Covariates for all analyses included sociodemographics (sex, race, and free/reduced-priced lunch status), community disadvantage, and intervention status. Nicotine dependence (FTND≥3) at age 20 predicted age 30 DSM-IV lifetime OUD (aOR = 2.37; 95% CI 1.02,5.54). The number of CUD criteria (aOR = 1.30; 95% CI 1.09,1.57) and nicotine dependence severity scores (aOR = 1.22; 95% CI = 1.05,1.41) at age 20 predicted any OUD criteria between the ages of 20 and 30. Findings are consistent with previous research on opioid use behavior in young adulthood and suggest that nicotine dependence and CUD criteria among urban young people predict onset of OUD and OUD criteria in young adulthood.

Endogenous opiates and behavior: 2020

This paper is the forty-third consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2020 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Factors mediating pain-related risk for opioid use disorder

Pain is a complex experience with far-reaching organismal influences ranging from biological factors to those that are psychological and social. Such influences can serve as pain-related risk factors that represent susceptibilities to opioid use disorder. This review evaluates various pain-related risk factors to form a consensus on those that facilitate opioid abuse. Epidemiological findings represent a high degree of co-occurrence between chronic pain and opioid use disorder that is, in part, driven by an increase in the availability of opioid analgesics and the diversion of their use in a non-medical context. Brain imaging studies in individuals with chronic pain that use/abuse opioids suggest abuse-related mechanisms that are rooted within mesocorticolimbic processing. Preclinical studies suggest that pain states have a limited impact on increasing the rewarding effects of opioids. Indeed, many findings indicate a reduction in the rewarding and reinforcing effects of opioids during pain states. An increase in opioid use may be facilitated by an increase in the availability of opioids and a decrease in access to non-opioid reinforcers that require mobility or social interaction. Moreover, chronic pain and substance abuse conditions are known to impair cognitive function, resulting in deficits in attention and decision making that may promote opioid abuse. A better understanding of pain-related risk factors can improve our knowledge in the development of OUD in persons with pain conditions and can help identify appropriate treatment strategies. This article is part of the special issue on 'Vulnerabilities to Substance Abuse.'.