Subtyping of substance use disorders in a high-risk welfare-to-work sample: A latent class analysis

Schwartz, Bruce; Wetzler, Scott; Swanson, Arthur J.; Sung, So-Young

doi:10.1016/j.jsat.2010.03.001

Cited by 26 publications

(21 citation statements)

References 32 publications

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“…As several studies have used LCA among populations of substance users in the United States (Harrell et al, 2012; Kuramoto et al, 2011; Schwartz et al 2010), to our knowledge the current study is the first of its kind to identify patterns of polysubstance use among drug users in the Pretoria region of South Africa as well as the first study to examine risk factors associated with HIV exposure and possible transmission. Applied to the current study, the use of latent class analysis illustrates the degree and kind of substance use in this population.…”

Section: Discussionmentioning

confidence: 98%

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Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users

Trenz

Scherer

Duncan

et al. 2013

Drug and Alcohol Dependence

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Background HIV transmission risk among non-injection drug users is high due to the co-occurrence of drug use and sexual risk behaviors. The purpose of the current study was to identify patterns of drug use among polysubstance users within a high HIV prevalence population. Methods The study sample included 409 substance users from the Pretoria region of South Africa. Substances used by 20% or more the sample included: cigarettes, alcohol, marijuana and heroin in combination, marijuana and cigarettes in combination, and crack cocaine. Latent class analysis was used to identify patterns of polysubstance use based on types of drugs used. Multivariate logistic regression analyses compared classes on demographics, sexual risk behavior, and disease status. Results Four classes of substance use were found: MJ+Cig (40.8%), MJ+Her (30.8%), Crack (24.7%), and Low Use (3.7%). The MJ+Cig class was 6.7 times more likely to use alcohol and 3 times more likely to use drugs before/during sex with steady partners than the Crack class. The MJ+Cig class was16 times more likely to use alcohol before/during sex with steady partners than the MJ+Her class. The Crack class was 6.1 times more likely to engage in transactional sex and less likely to use drugs before/during steady sex than the MJ+Her class. Conclusions Findings illustrate patterns of drug use among a polysubstance using population that differ in sexual risk behavior. Intervention strategies should address substance use, particularly smoking as a route of administration (ROA), and sexual risk behaviors that best fit this high-risk population.

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Section: Discussionmentioning

confidence: 98%

“…Latent class analysis (LCA) is a method of data reduction used to identify groupings of individuals that illustrate similar patterns or profiles of behavior (McCutcheon, 1987). This method of analysis is gaining popularity among substance abuse researchers (Harrell et al, 2011; Monga et al, 2007; Schwartz et al, 2010). …”

Section: Methodsmentioning

confidence: 99%

Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users

Trenz

Scherer

Duncan

et al. 2013

Drug and Alcohol Dependence

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“…Time varying control variables included linear and quadratic age trends, homelessness, formal employment (full- or part-time), accessing mental health treatment, binge alcohol use, and opioid use, all in the previous six months. Indicators for homelessness and addiction treatment were included to control for their potential association with criminal activity, both directly and mediated through changes in drug use, specifically among opioid co-users (DeBeck et al, 2007; Schwartz et al, 2010). A variable for accessing mental health treatment was included to control for the potential association between mental health problems, drug use and criminal activity (Bolla et al, 1998; Harro, 2015).…”

Section: Methodsmentioning

confidence: 99%

The costs of crime associated with stimulant use in a Canadian setting

Enns

Krebs

DeBeck

et al. 2017

Drug and Alcohol Dependence

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Background: Costs attributable to criminal activity are a major component of the economic burden of substance use disorders, yet there is a paucity of empirical evidence on this topic. Our aim was to estimate the costs of crime associated with different forms and intensities of stimulant use. Methods: Retrospective cohort study, including individuals from three prospective cohorts in Vancouver, Canada, measured biannually (2011-2015), reporting stimulant use at baseline assessment. Monthly crime costs included policing, court, corrections, and criminal victimization (2016 CAD). We estimated monthly crime costs associated with mutually exclusive categories of crack, cocaine, methamphetamine, and polystimulant use, stratified by daily/non-daily use, relative to stimulant abstinence, as well as the independent effects of treatment (opioid agonist (OAT) and other addiction treatment). We used a two-part model, capturing the probability of criminal activity and costs of crime with generalized linear logistic and gamma regression models, respectively, controlling for age, gender, education, homelessness, mental health issues, employment, prior incarceration, alcohol and opioid use. Results: The study sample included 1,599 individuals (median age 39, 65.9% male) assessed over 5299 biannual interviews. Estimates of associated monthly crime costs ranged from $5449 [95%C.I.: $2180, $8719] for non-daily polystimulant use, to $8893 [$4196, $13,589] for daily polystimulant use. Cost differences between daily/non-daily use, injection/non-injection, and stimulant type were not statistically significant. Drug treatment was not associated with lower monthly crime costs in our sample. Conclusions: Substantial crime-related costs were associated with stimulant use, emphasizing the urgency for development and implementation of efficacious treatment regimens.

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“…LCA is commonly used in substance use and misuse research (Harrell et al, 2012;Schwartz et al, 2010). M-Plus 6.0 (Muthén & Muthén, 2010) was used for LCA modeling.…”

Section: Statistical Analysesmentioning

confidence: 99%

Marijuana and Other Substance Use Among Motor Vehicle Operators: A Latent Class Analysis

Scherer

Harrell

Romano

2015

J. Stud. Alcohol Drugs

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ABSTRACT. Objective:The deleterious effect of multiple-substance use on driving performance is well established, but relatively little research has examined the patterns of drug use among multiple-substance users and its relationship to both alcohol use and adverse driving outcomes. Method: The current study used latent class analysis to examine subgroups of substance users among a population of drivers who screened positively for 2 or more of 13 substances other than alcohol (N = 250). A series of logistic regression analyses was conducted to examine demographic predictors of latent class assignment and class association with adverse driving outcomes. Results: Four distinct subclasses of users were identified among multiple-substance-using drivers: Class 1 consisted of individuals who demonstrated high levels of all substances indicators (5%). The second class demonstrated high levels of marijuana and cocaine use and lower levels of all other substances (27%). The third class screened high for marijuana and nonmedical prescription opiate analgesics use (36%), whereas the last class demonstrated high nonmedical prescription opiate analgesics and benzodiazepine use (32%). Drivers in Class 2 (marijuana and cocaine users) were more likely to be younger and have a positive breath alcohol concentration than drivers in any other class. Conclusions: Because multidrug users show dissimilar characteristics, the propensity of researchers to lump all multiple-substance users together may either erroneously attribute the potentially profound impact of those in the marijuana and cocaine use class to all multiple-substance users or dilute their specific contribution to crash risk. (J. Stud. Alcohol Drugs, 76, 916-923, 2015)

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Subtyping of substance use disorders in a high-risk welfare-to-work sample: A latent class analysis

Cited by 26 publications

References 32 publications

Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users

Latent class analysis of polysubstance use, sexual risk behaviors, and infectious disease among South African drug users

The costs of crime associated with stimulant use in a Canadian setting

Marijuana and Other Substance Use Among Motor Vehicle Operators: A Latent Class Analysis

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