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Extensive summary of all the articles of the course: Risk behavior and addiction in adolescence €8,49
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  3. Universiteit Utrecht (UU)
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  5. Risk behavior and addiction in adolescence (RBA)

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Extensive summary of all the articles of the course: Risk behavior and addiction in adolescence

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Very extensive summary of all the articles from the 8 lectures of Risk behavior and addiction in adolescence. The summary consists of the articles from: - Gladwin et al. - Dobbs - Sussman - Lopez-Leon & Raley - Brand et al. - Van den Eijnden et al. - Ryan et al. - Koning et al. - Kildare & Middlemi...

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  • 2 september 2020
  • 79
  • 2019/2020
  • Samenvatting

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Voorbeeld van de inhoud

Lecture 1: Intro risk behavior and addiction in
adolescence
Gladwin et al: Addiction, adolescence, and the integration of control and motivation (3,5)
Introduction
Adolescence and addiction exemplify situations in which development of motivational processes can
result in excessively risky or otherwise dysfunctional behavior.
This article: focus on symmetries between adolescence- and addiction-related changes in motivation
and cognitive control that may help explain increased the likelihood of substance abuse and the
onset of addiction in adolescence.
Adolescence = developmental period between childhood and adulthood  changes in body
appearance and function and hormonal changes + changes in behavior and psychological processes
(= motivation/ cognitive control/ emotion/ social orientation).
 During this adolescence; children increasingly master the ability to control their behavior for the
benefit of longer-term goals = advances in self-regulation abilities.
These advances are accompanied by changes in motivational processes. These can have
profound consequences for health in adolescence, as the imbalance between relatively strong
affective processes and still immature regulatory skills might contribute to the onset of
developmental disorders.

Risky decision making in adolescence
Adolescents do take more and greater risks than people of other ages in f.e. criminal behavior,
dangerous behavior in traffic and experimenting with alcohol and drugs. The occurrence of these
risk-taking behaviors follows an inverted U-shape pattern across development (low in childhood,
increasing/peaking in adolescence and young adulthood, and declining thereafter).

Differences between “hot” affect-charged versus “cold” predominantly deliberative processes in risky
choice and risk taking (Columbia Card Task = CCT).
 Heightened involvement of affective processes in risky decision-making (in the hot CCT) leads to
increased risk taking in adolescents, compared to children and adults.
 In contrast, when risky decisions are made involving mainly deliberative processes and no or little
affect (cold CCT), adolescents show the same levels of risk taking as children and adults.

Presence of peers leads to increased risk taking in adolescents (not adults) when making choices =
socio-emotional influence of peers. Much risk taking behavior occurs in presence of peers. In
adolescence, changes in social motivations occur, achieving greater independence from their parents
and in turn the importance of peers grow.
Several studies have found evidence for monotonically decreasing risk-taking levels across childhood,
adolescence, and adults, which may indicate that these tasks captured more the cognitive or cold
processes involved in evaluating risks. More research is needed to further investigate precisely which
“ingredients” of a risky choice situation (besides substantial affective involvement and peer-
presence) lead to increased risk taking in adolescence.

Neural developments underlying risky decision making
The adolescent brain has two interacting systems:
 The relatively early maturing and “hot” affective-motivational bottom-up system
 More slowly developing “cold” top-down control system  involve prefrontal regions,
particularly the lateral prefrontal cortex, and posterior parietal brain regions, which have been
implicated in self-control, planning, abstract thinking, working memory and goal-directed
behavior.



1

,The affective-motivational system involves subcortical brain areas, including dopamine-rich areas in
midbrain and their subcortical and cortical targets, including the striatum and medial prefrontal
cortex.
Studies have shown converging evidence of neural changes in several brain areas during transition
from childhood to adulthood. Includes changes in dopamine-receptor densities, changes in white
matter, and changes in gray matter.

The frontostriatal model of adolescent decisonmaking describes a potential for imbalance in
motivational bottom-up vs. controlling top-down processes. For example, an adolescent
encountering a salient reward during risky choice may experience strong temptation and approach
motivation, which may result in a prepotent response to take a risk in order to achieve the potential
reward. An adult in this situation may be better able than the adolescent to inhibit this prepotent
response, resist the immediate temptation, perhaps wait before acting and think twice about it
whether it is worth taking this risk. This dynamic of strong motivational processes vs. relatively weak
prefrontal control can be particularly disadvantageous with respect to high and dangerous levels of
risk taking when affective-motivational processes are strongly triggered, for example in affect-
charged situations or in presence of peers.

Addiction
Neural sensitization leads to strong impulsive reactions to classically conditioned cues that signal
alcohol or drugs. This occurs more rapidly during adolescence. In later phases of addiction, habitual
responses become important, with cues automatically triggering approach-reactions, outside
voluntary control. New initiation of drug use may be triggered by negative affect, which is then
temporarily relieved. Such negative reinforcement processes are associated with severe drug
dependence.
Heavy alcohol and drug use results in impaired control functions, especially when heavy use takes
place during adolescence. Binge drinking has strong effects on subsequent brain development
involving cognitive and emotional regulatory processes. F.e. adolescent rats who had voluntarily
consumed high levels of alcohol demonstrated greater risk preferences in adulthood than control
rats who had not consumed alcohol during adolescence. Human studies (cross-sectional)
demonstrated that adolescent binge-drinking and heavy use of marijuana is associated with
abnormalities, both regarding white matter structure, and regarding functional properties, including
stronger cue-reactivity as well as impaired executive functions. Longitudinal human data confirms
the assumption that binge drinking can result in brain damage in a variety of regions, including those
involved in cognitive control.

While most adolescents experiment at least some addictive substances, only few of them become
addicted. Thus, individual differences. There is mounting evidence that adolescent substance use
may exaggerate the normal inverted U curve of risky behavior in adolescence, and may in some cases
(related to heavy substance use/ premorbid levels of impulsivity) postpone or even prevent the
decrease in risky behaviors normally starting in early adulthood.

Dual-process models of addiction
In both adolescence and addiction, risky behavior results from an inability of reflective processes to
sufficiently modulate the effects of impulsive processes, for instance by modulating the saliency of
information in working memory. This imbalance is made explicit in dual-process models of addiction,
which emphasize the importance of drug-related consequences on relation between impulsive and
reflective processes. Such models supported by findings showing that higher working memory
capacity and interference control capacity weaken the impact of alcohol-related automatic
processes.



2

, The primary aim of this model is to address the legitimate criticism of dual-process models. The
viewpoint developed here predicts that the reinforcement of top-down biasing functions and time
factors are essential to reflective processing. The time required to activate previously reinforced
biasing functions and to evaluate their outcomes may be an essential individual difference
determining whether drug-related automatic processes can be controlled. The time allowed for
searching for better outcomes and the internal criteria for settling on a currently preferred
(cognitive) action may play similar roles. In particular during adolescence, if it is the case that
prefrontal top-down biasing functions are yet to fully mature, then it appears almost unavoidable
that there is lag between the development of motivational processes and sufficient reinforcement
of top-down biasing functions to be applied to them in novel situations. This may explain the
difference between adolescent controlled processing in “hot” and “cold” situations.
In hot situations, the top-down biasing functions may in fact be present, but not recruited because
they are not strongly enough associated with the situation to compete with more immediate
responses.

Consistent relations between controlled processing and time-frequency domain activity, i.e., event-
related changes in the amplitude or phase of rhythmic neural firing patterns.




Interventions
Interventions can be seen as beneficially biased learning environments, in which reinforcement can
be provided that will either increase the chance of successful controlled processing, or reduce the
need for it.

Working memory (WM) training
Training the likelihood of successful control. It helped problem drinkers with strong positive memory
associations for alcohol, presumably because it helped them to overcome the bias to approach
alcohol, driven by these associations. Generalized improvement may be due to increased
frontoparietal connectivity and changes involving the basal ganglia. This suggests that the top-down
biasing aspects of WM, or executive control functions, as well as control of access to WM are
trainable.

Attentional bias modification
Promising clinical effects in anxiety and alcoholism. In this procedure, typically a modified version of
assessment instrument is used, with a contingency built in. In assessment instrument, the probe to
which people react, appears equally often in location of disorder-related stimulus and neutral
stimulus. The attentional bias is then calculated by subtracting the reaction time on threat-trials from
reaction time to non-threat trials. First controlled training in alcohol domain found change in
patients’ attentional bias for alcohol after training and an effect on post-treatment abstinence after 3
months. Investigated neurocognitive changes due to this type of training. It appears that training
attention towards or away from feat stimuli modifies relations between lateral prefrontal and
posterior regions, as evidenced by the need to recruit lateral prefrontal cortex to overcome the
trained bias.

3

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