Etiology of early age onset substance use disorder: A maturational perspective

Tarter, Ralph E.; Vanyukov, Michael; Giancola, Peter R.; Dawes, Michael A.; Blackson, Timothy C.; Mezzich, Ada C.; Clark, Duncan B.

doi:10.1017/s0954579499002266

Cited by 272 publications

(221 citation statements)

References 34 publications

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“…Euphoria may have evolved as an indicator of the positive Darwinian value of an experience, but it is possible that the true indicator of a Darwinian fitnesssignificant behavior is any positive affect change rather than necessarily euphoria [31]. Norm violation and rebelliousness, elevated novelty-seeking and risk-taking, are common features of adolescence [47], especially when exacerbated by maturational mistiming [48]. They may be additional stimuli for drug consumption, often initiated in adolescence.…”

Section: Systematic Reviewsmentioning

confidence: 99%

Risk and resistance perspectives in translation-oriented etiology research

Vanyukov

Tarter

Conway

et al. 2015

Behav. Med. Pract. Policy Res.

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Risk for a disorder and the mechanisms that determine its elevation, risk factors, are the focus of medical research. Targeting risk factors should serve the goal of prevention and treatment intervention. Risk, however, is but one of the aspects of liability to a disorder, a latent trait that encompasses effects of all factors leading to or from the diagnostic threshold. The coequal but opposite aspect of liability is resistance to a disorder. The factors that increase resistance and thus enable prevention or recovery may differ from those that elevate risk. Accordingly, there are nontrivial differences between research perspectives that focus on risk and on resistance. This article shows how this distinction translates into goals and methods of research and practice, from the choice of potential mechanisms tested to the results sought in intervention. The resistance concept also differs from those of Bresilience^and Bprotective factors,^subsuming but not limited to them. The implications of the concept are discussed using substance use disorder as an example and substantiate the need for biomedical research and its translation to shift to the resistance perspective. Keywords

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Section: Systematic Reviewsmentioning

confidence: 99%

Risk and resistance perspectives in translation-oriented etiology research

Vanyukov

Tarter

Conway

et al. 2015

Behav. Med. Pract. Policy Res.

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“…An undercontrolled temperament is thought to predispose to emotional and behavioral regulation problems that are neurobiologically based and increase the likelihood of developing an alcohol or drug use disorder (Tarter et al, 1999). The present study is focused 2 The EM algorithm was originally introduced by Dempster, Laird, and Rubin (1977) to provide iterative computation of the maximum likelihood estimates from incomplete data.…”

Section: Emotional and Behavioral Regulation And Alcohol Usementioning

confidence: 99%

Finding groups using model-based cluster analysis: Heterogeneous emotional self-regulatory processes and heavy alcohol use risk.

Mun¹,

Eye²,

Bates³

et al. 2008

Developmental Psychology

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Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of non-nested models using the Bayesian Information Criterion (BIC) to compare multiple models and identify the optimum number of clusters. The current study clustered 36 young men and women based on their baseline heart rate (HR) and HR variability (HRV), chronic alcohol use, and reasons for drinking. Two cluster groups were identified and labeled High Alcohol Risk and Normative groups. Compared to the Normative group, individuals in the High Alcohol Risk group had higher levels of alcohol use and more strongly endorsed disinhibition and suppression reasons for use. The High Alcohol Risk group showed significant HRV changes in response to positive and negative emotional and appetitive picture cues, compared to neutral cues. In contrast, the Normative group showed a significant HRV change only to negative cues. Findings suggest that the individuals with autonomic selfregulatory difficulties may be more susceptible to heavy alcohol use and use alcohol for emotional regulation. KeywordsModel-based Cluster Analysis; Mixture Model; Emotional Regulation; Heart Rate Variability (HRV); Alcohol Use Finding or classifying groups of individuals who are similar to one another within a group but sufficiently different from those of other groups has been a key interest in the behavioral sciences. Cluster analysis is a widely used approach for this purpose. It is empirically driven and exploratory in the sense that the number of groups and nature of the groups are unknown in advance (Everitt, Landau, & Leese, 2001;Webb, 2002). In the field of developmental psychology, a number of influential studies have found clusters of individuals based on their early temperamental and behavioral styles, and characterized their long-term patterns of behavioral outcomes, including the classic work on three temperamental styles from the New York Longitudinal Study (easy, difficult, slow to warm up;Thomas, Chess & Birch, 1968) and the more contemporary work from the Dunedin Multidisciplinary Health and Development (undercontrolled, inhibited, well-adjusted;Caspi, 2000;Caspi & Silva, 1995 NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptFurthermore, recent literature has increasingly postulated that qualitatively heterogeneous subpopulations exist in developmental pathways, and heterogeneous causal processes exist for subpopulations. Evidence of heterogeneity consisting of normative as well as atypical processes can be found in many behaviors, including depressive symptoms, aggressive behaviors, and substance use behaviors (for a brief review, see Mun, Windle, & Schainker, 2008). In addition, identifying heterogeneous subpopulations can be useful for determining individuals who may be at different stages of development. For example, in the domain of cognitive stage develo...

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“…Consider the growing evidence for a common liability to addiction across all substances from neurobiology (e.g., dopamine mediated reward neural circuitry, Koob & Le Moal, 2001;Nestler 2004Nestler ,2005 and psychiatric epidemiology (e.g., behavior genetics and neurobehavioral disinhibition; Agrawal, Neale, Jacobson, Prescott, & Kendler, 2005;Agrawal, Neale, Prescott, & Kendler, 2004;Clark, Cornelius, Kirisci, & Tarter, 2005;Iacono, Carlson, Taylor, Elkins, & McGue, 1999;Kirisci, Tarter, Vanyukov, Reynolds, & Habeych, 2004;Tarter et al, 2003Tarter et al, ,1999Tsuang et al, 1998;Vanyukov et al, 2003). Theoretical underpinnings of neural substrates that mediate common addictive liability rely heavily on animal studies (Nestler, 2004).…”

Section: Length Of Time For Transition To Greater Substance Involvementmentioning

confidence: 99%

Different lengths of times for progressions in adolescent substance involvement

Ridenour

Lanza

Donny

et al. 2006

Addictive Behaviors

Self Cite

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The present study examined Lengths Of Times for important transitions in substance involvement from Initiation to Regular use (LOTIR), first Problem from drug use (LOTIP), and first experience of Dependence (LOTID) for alcohol, tobacco, cannabis, cocaine, and opiates. Data were from a longitudinal study of 590 children (22.2% female) at different levels of risk for substance use disorders based on their fathers' substance use-related diagnoses. Participants' substance involvement was assessed at four ages: 10-12, and follow-ups at two, five, and eight years later. Results suggested that faster transitions were more due to drug-related constructs (including possible social milieus of different drug classes and interactions between drug class and neurophysiology) than intrapersonal constructs. The shortest transition times (and greatest addictive liabilities) were for opiates followed respectively by cocaine, cannabis, tobacco, and alcohol. Females had shorter transition times, though gender differences were small. Some evidence was found for a familial influence on transition times above what was accounted for by differences between substances.

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Etiology of early age onset substance use disorder: A maturational perspective

Cited by 272 publications

References 34 publications

Risk and resistance perspectives in translation-oriented etiology research

Risk and resistance perspectives in translation-oriented etiology research

Finding groups using model-based cluster analysis: Heterogeneous emotional self-regulatory processes and heavy alcohol use risk.

Different lengths of times for progressions in adolescent substance involvement

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