Estimating the causal effect of conduct disorder on the time from first substance use to substance use disorders using g-estimation.

BACKGROUND: The effect of conduct disorder (CD) as a major risk factor of substance use disorder (SUD), controlling for other psychiatric problems, has been well established in the literature. However, other psychiatric problems are associated as confounders with an increased risk of SUD. When confounding exists, the use of the standard survival analysis approach would lead to a biased estimate of the effect of a time-varying exposure on the time to event. METHODS: The authors used a G-estimation approach to estimate the causal effect of CD while controlling for time-varying confounders. RESULTS: The present study (N = 1420) found a substantial difference in the estimated hazard ratio of CD (4.49 vs. 1.93) when the results from G-estimation and Cox regression were compared. CONCLUSIONS: G-estimation fixed the problem of underestimating the hazard ratio of conduct disorder (CD) while controlling for all measured covariates.

Factor structure of the Internet Addiction Scale and its associations with psychiatric symptoms for Korean adolescents.

In this paper, we explore underlying factors of Internet Addiction Scale (IAS) and examine how the dimensions of the IAS relate to psychiatric symptoms in Korean adolescents. Exploratory factor analysis with a sample of N = 1,722 consisted of 13-15 year old Korean adolescents identified three distinctive factors of IAS and they were labeled 'time management', 'withdrawal behaviors' and 'neglect work'. Then, multiple regression models were applied to assess the association between each factor and eight psychological problems, which were evaluated by Youth Self Report. The overall IAS was significantly associated with Somatic, Immature, Thought, Attention, Delinquent and Aggressive behaviors. However, three factor scores showed different association patterns and indicated multidimensional aspects of problematic Internet use.

Does psychopathology in childhood predict internet addiction in male adolescents?

This study investigated childhood psychopathology and Internet addiction in adolescents. Initial assessment data were obtained from 1998 to 1999, and a follow-up assessment was performed in 2006, when the original subjects entered middle school. Personal information for the 524 male subjects was obtained from the original data. The subjects were evaluated with the Korean version of the child behavior checklist, which was administered to the children's parents. Demographic and psychosocial factors were also evaluated. Children were reassessed with the self-reported Korea Internet Addiction Scale. Our results indicated that 3.6 % of the subjects had Internet addiction, and revealed a significant relationship between withdrawal and anxiety/depression and future Internet addiction. The results suggest that withdrawal and anxiety/depression during childhood should be considered in the etiology of problematic Internet use in boys. Accordingly, clinicians should consider anxiety/depression and withdrawal during childhood to prevent Internet addiction.

The pathway of internalizing and externalizing problems from childhood to adolescence: a prospective study from age 7 to 14-16 in Korea.

This study prospectively investigated developmental psychopathology pathway from the age of 7 to ages 14-16. The subjects (N = 1,857) were evaluated using the Korean version of the Child Behavior Checklist and reassessed using the Korean Youth Self Report. In path analyses, total problems, externalizing problems, and internalizing problems in childhood associated significantly with problems in adolescence. In particular, childhood externalizing problems associated with adolescent externalizing problems, for both genders. However, our results differ from those of previous studies in that internalizing problems showed a restrictive stability by gender and in that early externalizing problems correlated negatively with later internalizing problems for girls. In the syndrome scales analyses, we confirmed that some syndromes showed heterotypic pathways, despite the general continuity of the developmental psychopathology. The importance of Anxiety/Depression and Attention problems in childhood suggested that adolescent difficulties are a consequence of an accumulation of such risk factors.

Pubertal maturation and the development of alcohol use and abuse.

OBJECTIVE: To examine the impact of various aspects of puberty on risk of using alcohol and developing alcohol use disorder (AUD). METHODS: Data come from the Great Smoky Mountains Study, a longitudinal study of a representative sample of 1420 youth aged 9-13 at recruitment. Participants were interviewed annually to age 16. A parent was also interviewed. Information was obtained about use of a range of drugs including alcohol, drug abuse and dependence, other psychiatric disorders, life events, and a wide range of family characteristics. Pubertal hormones were assayed annually from blood samples, and morphological development was assessed using a pictorial measure of Tanner stage. RESULTS: Controlling for age, Tanner stage predicted alcohol use and AUD in both boys (OR 1.58, 95% CI 1.18-2.22) and girls (OR 1.62, 95% CI 1.17-2.23). The effect of morphological development was strongest in those who matured early. Early pubertal maturation predicted alcohol use in both sexes, and AUD in girls. The highest level of excess risk for alcohol use was seen in early maturing youth with conduct disorder and deviant peers. Lax supervision predicted alcohol use in early maturing girls, while poverty and family problems were predictive in early maturing boys. CONCLUSIONS: Among the many biological, morphological, and social markers of increasing maturation, the visible signs of maturity are important triggers of alcohol use and AUD, especially when they occur early and in young people with conduct problems, deviant peers, problem families and inadequate parental supervision.

Effects of age at first substance use and psychiatric comorbidity on the development of substance use disorders.

In this paper, we examine the effects of age at first substance use, and history of psychiatric disorders, on the development of substance use disorder (SUD) by age 16. We use a prospective, longitudinal design to disaggregate the effects of age at first use and time since first use on the development of adolescent SUD. Second, we test the hypothesis that adolescent SUD is an unlikely progression from early substance use unless children also show other early conduct problems. A population sample of 1,420 children from the Great Smoky Mountains Study (GSMS) was assessed annually between ages 9 and 16. Logistic regression models were applied within the hierarchical Bayesian framework, where the covariate effects were described by time-varying parameters having a first-order auto-regressive prior distribution. Posterior analyses based on a Gibbs sampling approach revealed that, controlling for years of exposure, the risk of transition to SUD increased with age at onset for onsets before age 13, but began to fall for onset at 14. Among users, use alone, without early conduct problems, led to a 11% prevalence of SUD by age 16. Past conduct disorder (CD) had a strong additive effect at ages 13-15, but at age 16, when substance use and abuse became more normative, the excess risk from prior CD decreased. Boys, but not girls, with a history of depression were at increased risk of SUD. Anxiety increased the risk of SUD in girls at age 16, but not before that. Results only partially support the study hypothesis; early use was a major predictor of adolescent SUD even in the absence of CD.

Bayesian analysis of non-homogeneous Markov chains: application to mental health data.

In this paper we present a formal treatment of non-homogeneous Markov chains by introducing a hierarchical Bayesian framework. Our work is motivated by the analysis of correlated categorical data which arise in assessment of psychiatric treatment programs. In our development, we introduce a Markovian structure to describe the non-homogeneity of transition patterns. In doing so, we introduce a logistic regression set-up for Markov chains and incorporate covariates in our model. We present a Bayesian model using Markov chain Monte Carlo methods and develop inference procedures to address issues encountered in the analyses of data from psychiatric treatment programs. Our model and inference procedures are implemented to some real data from a psychiatric treatment study.

Bayesian semi-parametric ROC analysis.

This paper describes a semi-parametric Bayesian approach for estimating receiver operating characteristic (ROC) curves based on mixtures of Dirichlet process priors (MDP). We address difficulties in modelling the underlying distribution of screening scores due to non-normality that may lead to incorrect choices of diagnostic cut-offs and unreliable estimates of prevalence of the disease. MDP is a robust tool for modelling non-standard diagnostic distributions associated with imperfect classification of an underlying diseased population, for example, when a diagnostic test is not a gold standard. For posterior computations, we propose an efficient Gibbs sampling framework based on a finite-dimensional approximation to MDP. We show, using both simulated and real data sets, that MDP modelling for ROC curve estimation closely parallels the frequentist kernel density estimation (KDE) approach.