Experimentation versus progression in adolescent drug use: A test of an emerging neurobehavioral imbalance model

Khurana, Atika; Römer, Daniel; Betancourt, Laura M.; Brodsky, Nancy L.; Giannetta, Joan M.; Hurt, Hallam

doi:10.1017/s0954579414000765

Cited by 56 publications

(49 citation statements)

References 98 publications

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“…One advantage is that interventions can yield beneficial effects on alcohol-related outcomes for adolescents even when delivered at young ages (Tanner-Smith and Lipsey, 2015). Although it is difficult to quantify the meaning of the deficit in WM in practical terms, deficits in WM have been shown to be related to academic achievement (Gathercole et al , 2004), and impulsivity and risk-taking behaviours (Khurana et al , 2013; Khurana et al , 2015) in adolescents. Given the impact that cigarette and cannabis use had on the association between alcohol use and WM, it may be important to include these in future studies.…”

Section: Implications and Conclusionmentioning

confidence: 99%

Alcohol Use in Adolescence and Later Working Memory: Findings From a Large Population-Based Birth Cohort

Mahedy

Field

Gage

et al. 2018

Alcohol and Alcoholism

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AimsThe study aimed to examine the association between adolescent alcohol use and working memory (WM) using a large population sample.MethodsData from the Avon Longitudinal Study of Parents and Children were used to investigate the association between alcohol use at age 15 years and WM 3 years later, assessed using the N-back task (N ~ 3300). A three-category ordinal variable captured mutually exclusive alcohol groupings ranging in order of severity (i.e. low alcohol users, frequent drinkers and frequent/binge drinkers). Differential dropout was accounted for using multiple imputation and inverse probability weighting. Adjustment was made for potential confounders.ResultsThere was evidence of an association between frequent/binge drinking (compared to the low alcohol group) and poorer performance on the 3-back task after adjusting for sociodemographic confounding variables, WM at age 11 years, and experience of a head injury/unconsciousness before age 11 years (β = −0.23, 95% CI = −0.37 to −0.09, P = 0.001). However, this association was attenuated (β = −0.12, 95% CI = −0.27 to 0.03, P = 0.11) when further adjusted for baseline measures of weekly cigarette tobacco and cannabis use. Weaker associations were found for the less demanding 2-back task. We found no evidence to suggest frequent drinking was associated with performance on either task.ConclusionsWe found weak evidence of an association between sustained heavy alcohol use in mid-adolescence and impaired WM 3 years later. Although we cannot fully rule out the possibility of reverse causation, several potential confounding variables were included to address the directionality of the relationship between WM and alcohol use problems.

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Section: Implications and Conclusionmentioning

confidence: 99%

Alcohol Use in Adolescence and Later Working Memory: Findings From a Large Population-Based Birth Cohort

Mahedy

Field

Gage

et al. 2018

Alcohol and Alcoholism

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“…Longitudinal evidence linking early onset to dependence has relied heavily on retrospective reports of drug use assessed with high-risk samples [4–6]. Further, this research has overlooked the significant heterogeneity in early drug use patterns [7,8], leaving unaddressed the question whether any early onset or specific forms of early drug use are predictive of later substance use disorders (SUD). Considerable research also finds that an underlying liability for disinhibition predisposes to externalizing behaviors during adolescence, including both early drug use and SUD [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Two forms of impulsivity that index this imbalance, namely acting without thinking (AWT) and delay discounting (DD), predicted progressive drug use trajectories from early to mid-adolescence [7]. AWT is a form of impulsive action that represents the tendency for rapid and unplanned responses to behavioral urges [13,14].…”

Section: Introductionmentioning

confidence: 99%

Working memory ability and early drug use progression as predictors of adolescent substance use disorders

et al. 2017

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Aims To test a neurobehavioral model of adolescent substance use disorder (SUD) resulting from an imbalance between a hyperactive reward motivation system and a hypoactive executive control system. Specifically, we tested (1) if early weakness in working memory (WM) and associated imbalance indicators of acting-without-thinking (AWT) and delay discounting (DD) predict SUD in late adolescence, and (2) if early drug use progression mediates this relation. Design Five waves of longitudinal data collected annually from 2005–2010, with a final follow-up in 2012. Setting & Participants Sample of 387 community adolescents (baseline ages 11–13) recruited from the Philadelphia, Pennsylvania, USA area. Measurements WM was assessed at baseline using 4 different computerized tasks. AWT and DD were assessed at baseline using self-reports. Early drug use patterns were modeled using annual self-reports of recent drug use across the first four waves. Final outcome of SUD was assessed at last wave using self-reports matched to the DSM-5 criteria for three commonly used substances: alcohol, marijuana, and tobacco. Findings Weakness in WM at baseline, associated with neurobehavioral imbalance indicators of AWT, B (SE) = −0.06(0.02), p<0.01, and DD, B (SE) = −7.30(1.93), p<0.01, was a significant predictor of SUD at final follow-up. WM predicted SUD both independent of early drug use, B (SE) = −0.36(0.12), p<0.01, and as mediated by early drug use progression, B (SE) = −0.06(0.02), p<0.01. Conclusions Adolescents with weak working memory have less control over impulsive urges, placing them at risk for later substance use disorder with some of the effects mediated by early drug use progression.

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“…Limited work pointedly explores how a monitored abstinence protocol with adolescents simultaneously influences trajectories of subsyndromal mental health symptoms (e.g., depression and anxiety), sleep disturbance, marijuana use expectancies and consequences, and reward sensitivity in non-treatment seeking marijuana users compared to matched controls (Angarita et al 2016; Boden et al 2013; Brackenbury et al 2016; Gates et al 2016; Hayaki et al 2010; Moitra et al 2016; Moitra et al 2015). Barriers to treatment success (e.g., CM) may be associated with cannabis-related problems (e.g., withdrawal and craving) and processes that can influence emotional processing (e.g., negative affect), cognitive attributions and self efficacy (e.g., marijuana effect expectancies), and risk taking behaviors (e.g., continued use and functional consequences) (Budney et al 2001; Cornelius et al 2008; Fox et al 2011; Khurana et al 2015; Stanger et al 2013; Tims et al 2002; Zvolensky et al 2017). …”

Section: Introductionmentioning

confidence: 99%

Changes in marijuana use symptoms and emotional functioning over 28-days of monitored abstinence in adolescent marijuana users

et al. 2017

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Rationale Advancing marijuana prevention and intervention efforts is important given decreasing perception of harm among adolescents and increasing marijuana legalization. Objectives This study evaluates how a monitored abstinence protocol may contribute to emotional functioning and changes in marijuana problems that can enhance successful outcomes for non-treatment seeking adolescent marijuana users. Methods Adolescent marijuana users (n=26) and demographically matched controls (n=30) completed 28-days of monitored abstinence confirmed by bi-weekly urine toxicology. Participants were given measures of emotional functioning, marijuana use symptoms, and reward sensitivity during monitored abstinence. Results All participants (N=56) completed the protocol, and 69% of marijuana users (n=18 of 26) were confirmed abstinent for 28-days, with all users showing decreasing marijuana use. Reductions in subsyndromal depression, positive marijuana use expectancies, and poor sleep quality were observed by the end of the monitored abstinence period (n=26, ps<.05). Marijuana users also reported more attentional impulsivity and less responsiveness to reward stimuli during the second week of abstinence compared to controls. Later age of onset of regular marijuana use and more cumulative lifetime use was associated with a greater degree of emotional change and increased recognition of the negative effects of marijuana use. Conclusions Monitored abstinence programs may be beneficial in reducing marijuana use, subsyndromal emotional distress symptoms, and changing beliefs about marijuana use. Future prevention and intervention efforts may consider targeting reward sensitivity and impulsivity, in addition to marijuana use, expectancies, and emotional functioning.

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Experimentation versus progression in adolescent drug use: A test of an emerging neurobehavioral imbalance model

Cited by 56 publications

References 98 publications

Alcohol Use in Adolescence and Later Working Memory: Findings From a Large Population-Based Birth Cohort

Alcohol Use in Adolescence and Later Working Memory: Findings From a Large Population-Based Birth Cohort

Working memory ability and early drug use progression as predictors of adolescent substance use disorders

Changes in marijuana use symptoms and emotional functioning over 28-days of monitored abstinence in adolescent marijuana users

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