title: Cognitive performance profiles by latent classes of drug use.
abstract: OBJECTIVE
  The relationship between substance use and cognitive deficits is complex and requires innovative methods to enhance understanding. The present study is the first to use LCA to examine associations of drug use patterns with cognitive performance.
  
  
  METHODS
  Cocaine/heroin users (N = 552) completed questionnaires, and cognitive measures. LCA identified classes based on past-month drug use and adjusted for probabilities of group membership when examining cognitive performance. Latent indicators were: alcohol (ALC), cigarettes (CIG), marijuana (MJ), crack smoking (CS), nasal heroin (NH), injection cocaine (IC), injection heroin (IH), and injection speedball (IS). Age and education were included as covariates in model creation.
  
  
  RESULTS
  Bootstrap likelihood ratio test (BLRT) supported a 5-class model. Prevalent indicators (estimated probability of over 50%) for each class are as follows: "Older Nasal Heroin/Crack Smokers" (ONH/CS, n = 166.9): ALC, CIG, NH, CS; "Older, Less Educated Polysubstance" (OLEP, n = 54.8): ALC, CIG, CS, IH, IC, and IS; "Younger Multi-Injectors" (MI, n = 128.7): ALC, CIG, MJ, IH, IC, and IS; "Less Educated Heroin Injectors" (LEHI, n = 87.4): CIG, IH; and "More Educated Nasal Heroin" users (MENH, n = ALC, CIG, NH. In general, all classes performed worse than established norms and older, less educated classes performed worse, with the exception that MENH demonstrated worse cognitive flexibility than YMI.
  
  
  CONCLUSIONS
  This study demonstrated novel applications of a methodology for examining complicated relationships between polysubstance use and cognitive performance.
  
  
  CONCLUSIONS
  Education and/or nasal heroin use are associated with reduced cognitive flexibility in this sample of inner city drug users.
authors.affiliation: Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, Florida.
authors.forename: P Truman
authors.initials: PT
authors.lastname: Harrell
authors.forename: Brent Edward E
authors.initials: BE
authors.lastname: Mancha
authors.forename: Silvia S
authors.initials: SS
authors.lastname: Martins
authors.forename: Pia M
authors.initials: PM
authors.lastname: Mauro
authors.forename: Julie H
authors.initials: JH
authors.lastname: Kuo
authors.forename: Michael
authors.initials: M
authors.lastname: Scherer
authors.forename: Karen I
authors.initials: KI
authors.lastname: Bolla
authors.forename: William W
authors.initials: WW
authors.lastname: Latimer
mesh_terms: D000328:Adult; D000367:Age Factors; D000428:Alcohol Drinking / Q000009:adverse effects; D019969:Amphetamine-Related Disorders / Q000523:psychology; D015142:Baltimore; D019970:Cocaine-Related Disorders / Q000523:psychology; D003072:Cognition Disorders / Q000139:chemically induced / Q000523:psychology*; D055030:Drug Users / Q000523:psychology*; D004522:Educational Status; D005260:Female; D006556:Heroin Dependence / Q000523:psychology; D006801:Humans; D008297:Male; D008385:Marijuana Smoking / Q000009:adverse effects; D008960:Models, Psychological; D009483:Neuropsychological Tests; D012907:Smoking / Q000009:adverse effects; D015819:Substance Abuse, Intravenous / Q000523:psychology; D014505:Urban Population / Q000706:statistics & numerical data; D055815:Young Adult