ArticleDrug and alcohol dependence2011
Psychometric modeling of cannabis initiation and use and the symptoms of cannabis abuse, dependence and withdrawal in a sample of male and female twins.
Article in Drug and alcohol dependence, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Cannabis use in college: Genetic predispositions, peers, and activity participation.Drug and alcohol dependence · 2021Article
- Associations between personality disorders and cannabis use and cannabis use disorder: a population-based twin study.Addiction (Abingdon, England) · 2018Article
- Cannabis Epidemiology: A Selective Review.Current pharmaceutical design · 2017Review
- Cannabis Use in Adolescence and Young Adulthood: A Review of Findings from the Victorian Adolescent Health Cohort Study.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2016Article
- Item Response Theory Analysis to Assess Dimensionality of Substance Use Disorder Abuse and Dependence Symptoms.International journal of person centered medicine · 2016Article
- Comparing factor, class, and mixture models of cannabis initiation and DSM cannabis use disorder criteria, including craving, in the Brisbane longitudinal twin study.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2014Article
- A genetic perspective on the proposed inclusion of cannabis withdrawal in DSM-5.Psychological medicine · 2013Article
- The Brisbane Longitudinal Twin Study: Pathways to Cannabis Use, Abuse, and Dependence project-current status, preliminary results, and future directions.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2013Article
- Categorical vs dimensional classifications of psychotic disorders.Comprehensive psychiatry · 2012Review
- The co-occurring use and misuse of cannabis and tobacco: a review.Addiction (Abingdon, England) · 2012Review
- Are the symptoms of cannabis use disorder best accounted for by dimensional, categorical, or factor mixture models? A comparison of male and female young adults.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2012Article
- Recent advances in the genetic epidemiology and molecular genetics of substance use disorders.Nature neuroscience · 2012Article
- Sex Effects of Marijuana on Brain Structure and Function.Current addiction reportsReview
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundDespite an emerging consensus that the DSM-IV diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying liability, it remains unknown if latent class or hybrid models can better explain the data.
methodUsing structured interviews, 7316 adult male and female twins provided complete data on DSM-IV symptoms of cannabis abuse and dependence. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-III-R/IV criteria by comparing an array of psychometric models (latent factor analysis, latent class analysis and factor mixture modeling) using full information maximum likelihood ordinal data methods in Mx.
resultsWe found little evidence to support population heterogeneity since neither latent class nor hybrid factor mixture models provided a consistently good fit to the data. When conditioned on initiation and cannabis use, the endorsement patterns of the abuse, dependence and withdrawal criteria were best explained by two latent factors for males and females. The first was a general CUD factor for which genetic effects explained 53-54% of the variance. A less interpretable second factor included a mix of cross-loading dependence and withdrawal symptoms.
conclusionsThis is the first study to compare competing measurement models to derive an empirically determined CUD phenotype. Commensurate with proposed changes to substance use disorders in the DSM-V, our results support an emerging consensus that a single CUD latent factor can more optimally assess the risk or liability underpinning correlated measures of use, abuse, dependence and withdrawal criterion.
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