Literature DB >> 24588857

Comparing factor, class, and mixture models of cannabis initiation and DSM cannabis use disorder criteria, including craving, in the Brisbane longitudinal twin study.

Thomas S Kubarych1, Kenneth S Kendler1, Steven H Aggen1, Ryne Estabrook1, Alexis C Edwards1, Shaunna L Clark2, Nicholas G Martin3, Ian B Hickie4, Michael C Neale1, Nathan A Gillespie1.   

Abstract

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use.

Entities:  

Mesh:

Year:  2014        PMID: 24588857      PMCID: PMC3996924          DOI: 10.1017/thg.2014.9

Source DB:  PubMed          Journal:  Twin Res Hum Genet        ISSN: 1832-4274            Impact factor:   1.587


  46 in total

1.  Finite mixture modeling with mixture outcomes using the EM algorithm.

Authors:  B Muthén; K Shedden
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

2.  An item-response theory analysis of DSM-IV alcohol-use disorder criteria and "binge" drinking in undergraduates.

Authors:  Cheryl L Beseler; Laura A Taylor; Robert F Leeman
Journal:  J Stud Alcohol Drugs       Date:  2010-05       Impact factor: 2.582

3.  Comorbidity between DSM-IV alcohol and specific drug use disorders in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions.

Authors:  Frederick S Stinson; Bridget F Grant; Deborah A Dawson; W June Ruan; Boji Huang; Tulshi Saha
Journal:  Drug Alcohol Depend       Date:  2005-04-18       Impact factor: 4.492

4.  A finite mixture model for genotype and environment interactions: detecting latent population heterogeneity.

Authors:  Nathan A Gillespie; Michael C Neale
Journal:  Twin Res Hum Genet       Date:  2006-06       Impact factor: 1.587

5.  Local solutions in the estimation of growth mixture models.

Authors:  John R Hipp; Daniel J Bauer
Journal:  Psychol Methods       Date:  2006-03

Review 6.  The science of making drug-addicted animals.

Authors:  S H Ahmed
Journal:  Neuroscience       Date:  2011-08-10       Impact factor: 3.590

7.  Psychometric properties of DSM assessments of illicit drug abuse and dependence: results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC).

Authors:  M T Lynskey; A Agrawal
Journal:  Psychol Med       Date:  2007-04-04       Impact factor: 7.723

8.  Construct validity of the dependence syndrome as measured by DSM-IV for different psychoactive substances.

Authors:  A Feingold; B Rounsaville
Journal:  Addiction       Date:  1995-12       Impact factor: 6.526

9.  The role of cannabis use within a dimensional approach to cannabis use disorders.

Authors:  Wilson M Compton; Tulshi D Saha; Kevin P Conway; Bridget F Grant
Journal:  Drug Alcohol Depend       Date:  2008-12-04       Impact factor: 4.492

10.  Factor and item-response analysis DSM-IV criteria for abuse of and dependence on cannabis, cocaine, hallucinogens, sedatives, stimulants and opioids.

Authors:  Nathan A Gillespie; Michael C Neale; Carol A Prescott; Steven H Aggen; Kenneth S Kendler
Journal:  Addiction       Date:  2007-06       Impact factor: 6.526

View more
  2 in total

1.  Associations between personality disorders and cannabis use and cannabis use disorder: a population-based twin study.

Authors:  Nathan A Gillespie; Steven H Aggen; Michael C Neale; Gun Peggy Knudsen; Robert F Krueger; Susan C South; Nikolai Czajkowski; Ragnar Nesvåg; Eivind Ystrom; Kenneth S Kendler; Ted Reichborn-Kjennerud
Journal:  Addiction       Date:  2018-04-13       Impact factor: 6.526

2.  Cannabis use disorders among adults in the United States during a time of increasing use of cannabis.

Authors:  Wilson M Compton; Beth Han; Christopher M Jones; Carlos Blanco
Journal:  Drug Alcohol Depend       Date:  2019-09-12       Impact factor: 4.492

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.