adolescence Flashcards
What are the three mechanisms by which peer drug use is associated with individual adolescent drug use?
Peer pressure- overt pressure from peers
Social facilitation
Peer selection
Describe the two kind of peer influence
Direct influences range from polite gestures such as “would you like a cigarette?” to overt commands such as “finish your beer.” Refusal of these direct commands, especially when surrounded by peers, may result in feelings of inferiority, loss of social ease, fear of rejection and exclusion, and actual rejection or exclusion. In contrast, social facilitation is more subtle. This includes modeling or imitation of perceived normative behaviour of the group. For example, if someone were to observe a group of their friends using marijuana, that person would be more likely to imitate and even adopt this behaviour.
Is smoking largely due to peer pressure or internal pressure of perceived group norms
With cigarette smoking, adolescents tend to report that overt peer pressure for smoking is not a factor, but they feel internal pressure due to perceived norms of the group, rather than peer pressure (Nichter et al, 1997) thus suggesting that social facilitation may be more common.
is everyone susceptible to peer influence
one study
Gardner and Steinberg (2005) examined age differences in the effect of peer context on risky decision making in adolescents (aged 13-16), young adults (aged 18-22) and adults (24+). The three groups were tested on a computerized driving task called the Chicken Game, which challenges the driver to advance a vehicle as far as possible on a driving course while avoiding crashing into a wall that could appear, without warning, on the course at any point. The task was completed alone or in the presence of two similar-aged peers. When tested alone, participants in each of the three age groups engaged in a comparable amount of risk taking. In contrast, early adolescents scored twice as high on an index of risky driving when tested with their peers in the room than when tested alone, whereas late adolescents’ driving was approximately 50% riskier in the presence of peers, and adults showed no difference in risky driving related to social context. It appears that the presence of peer groups may influence risk of substance use amongst adolescents, possibly due to desire to be liked by the group. However, a limitation of this study is that risky behavior on a computerized task may not reflect risks that the individual would be willing to take in rel life circumstances. This does not mean that peers would not influence behavior, but that the influence may not be as pronounced as was found by Gardner and Stienberg (2005). Stienberg (2008) proposed a theory of neurobiological mechanisms to explain why adolescents may be more susceptible to peer influence.
Why are adolescents more susceptible to peer influence?
One proposed theory of the neurobiological mechanisms of adolescent risk for substance abuse, referred to as the “dual systems model”, posits that increased risk-taking during adolescence is due to a combination of heightened reward sensitivity and immature impulse control, which are tied to the development of two brain systems that undergo significant change during this age period, but that develop along different timetables. One system, which has been called the “socioemotional” incentive processing system is localized mainly in the ventral striatum (VS), the amygdala and ventromedial prefrontal cortex. The socioemotional network is especially sensitive to social and emotional stimuli, that is particularly important for reward processing, and that is remodeled in early adolescence by the hormonal changes of puberty. The second system, referred to as the “cognitive control” system is localized mainly in lateral prefrontal, parietal, and anterior cingulate cortices. The cognitive control system subserves executive functions such as planning, thinking ahead, and self-regulation, and that matures gradually over the course of adolescence and young adulthood largely independently of puberty. Briefly, the dual systems (DS) perspective posits that risk-taking during mid-adolescence is the product of the heightened reactivity of the socioemotional system against a backdrop of still maturing cognitive control. With further maturation, the socioemotional system becomes less reactive and the cognitive control system becomes stronger and more efficient. Together, these changes lead to an increase in risk taking during adolescence followed by a decrease in risk taking as individuals move into adulthood.
Neuroimaging support for socio-emotional network
As well as consistency with behavioral findings of Gardner and Steinbergs (2005) study, the fMRI data indicated that the presence of peers activated certain regions that were not activated when the driving game was played in the peer-absent condition. This included the medial frontal cortex, left ventral striatum (primarily in the accumbens), left superior temporal sulcus, and left medial temporal structures. In other words, the presence of peers activated the socio-emotional network and led to more risky behavior, thus supporting the dual process model which suggests that this network is strongly influential in adolescence. However, this was a pilot study so findings should be interpreted with caution. Additionally, studies indicate the ventral striatum does not always bias adolescents towards susceptibility to peer influence.
Neuroimaging evidence against the soci-emotional network as a vulnerability to substance us in adolecence
study (Pfeifer et al., 2011), 38 neurotypical participants underwent two fMRI sessions across the transition from late childhood (10 years) to early adolescence (13 years). The study found increases in VS response to emotional facial expressions were associated with increases in resistance to peer influence and decreases in risky behavior. These results suggest that VS responses to viewing emotions may play a regulatory role (as opposed to promoting risky impulsive behaviour) that is critical to adolescent interpersonal functioning thus, the dual system model seems to have overlooked some inconsistencies in the literature. However, there is further empirical support for the dual mechanism model of adolescent risk taking which has demonstrated the existence of the cognitive control system that is proposed to be not yet fully developed in adolescence.
Describe peer selection
An issue when applying this model peer influence to substance use is that the association between peer use and individual use could be due to peer selection. The peer influence and peer selection models assume opposite causal directions, and knowing which is true or relatively important is fundamental to understanding the etiology of drug behavior. Friends have similar drug behavior when their friendships are formed on the basis of common drug behavior. In these cases, selection rather than influence produces the association between friend and adolescent drug use.
Study for peer influence
Robinson et al (2006) conducted a study investigating whether adolescent cigarette smoking was related to peer influences. A survey was administered to 4461 seventh-graders assessing usual sources of cigarettes and related variables. Of the target population, 79% provided baseline data, and 64.2% participated in all surveys. At baseline, 30% of the 1144 smokers got cigarettes from peers, compared with 11% using stores, 6% using vending machines, and 17% who stole them. Adolescents are therefore much more likely to get their first cigarette from peers than from any other source, suggesting the important influence of peer socialisation on substance use onset. It was also found that the longer students smoked, the more likely they were to have friends who smoked. Therefore, this would suggest that onset of substance may be largely associated with peer influence, but development and maintenance of substance use behaviours may occur in a process of peer selection whereby the individual select peers who share the same attitudes towards substances. This is supported by studies showing that this applies to not only cigarette smoking, but also to alcohol and cannabis use. Poulin et al (2011) conducted a longitudinal study on reciprocal effects of selection and substance use. Canadian adolescents (n = 143) were assessed four times over a school year. Each assessment measured amount of new friends at each stage, and how many of these smoked, drank, or used cannabis. It was found that adolescents select new friends with similar substance use patterns, but that these friends in turn contribute to individual use.
Introduction for adolescent risk
Adolescence is a particularly vulnerable time period for long lasting impacts on the executive functions. Adolescence can be defined as the phase of gradual transition between childhood and adulthood, which is overlapping yet conceptually distinct from the physical changes marking puberty and physical maturation. Substance use in adolescence has been attributed as a risk taking behavior. It is well established that adolescents are more likely than children or adults to take risks, as evinced by elevated rates of experimentation with alcohol, tobacco, and drugs, unprotected sexual activity, violent and nonviolent crime, and reckless driving (Steinberg, 2008). This essay will discuss psychological and neurobiological development during adolescence that influences risk taking and makes individuals vulnerable to substance use.
Evidence for late maturation of cognitive control in adolescence
Across adolescence, performance on response inhibition tasks improves with age—a pattern that appears to be explained by continuing maturation of the lPFC, with most studies finding either a linear increase in lPFC recruitment with age. For example, Vink et al (2014) conducted a study in which 60 subjects in a cross-sectional design, underwent functional MRI and a stop-signal task measuring two forms of inhibitory control: reactive inhibition (outright stopping) and proactive inhibition (anticipation of stopping). The task used was a stop-signal anticipation task (SSAT). In this task, Three horizontal lines formed the background displayed continuously during the task. In ‘go trials’, in each trial, a bar moved at constant speed from the bottom up, reaching the middle line in 800 ms. The main task was to stop the bar as close to the middle line as possible by pressing a button with the right thumb. In other words, the target response time was 800 ms. These trials measure reactive inhibition. B: In a minority of trials, the bar stopped moving automatically before reaching the middle line (i.e., the stop-signal), indicating that a response had to be withheld. These trials are referred to as ‘stop trials’ and measure proactive inhibition. The probability that a stop-signal would occur was manipulated across trials and was indicated by the color of the target response line. . The level of proactive inhibition increased, with older subjects slowing down responding more than younger subjects when anticipating a stop-signal. Moreover, functional connectivity during proactive inhibition increased between striatum and frontal regions with age. These findings support the dual processes model by showing that improvements in this aspect of cognitive control are paralleled by increases in activation and functional connectivity of the frontostriatal network. However, in order for these findings to be considered reliable they would ideally be replicated in a within-subject longitudinal study to reduce effects of individual differences.
Limitations of dual processes model
A key limitation of the dual process model is that the effects of maturation of the socioemotional system and cognitive control system on real-world risk taking are likely to be modest and difficult to detect. Undoubtedly, contextual constraints on the behavior of adolescents relative to adults overwhelm any putative effect on actual risk taking. To take an obvious example, even if 15-year-olds are higher in sensation seeking and lower in self-regulation than people in their 20s, these differences will not be reflected in age differences in reckless driving in a country where 15-year-olds are not permitted to drive. Thus, tests of the dual systems model will require the continued development of laboratory tasks that are ecologically valid but that afford individuals of different ages equal opportunity to take risks.
Conclusions about neurbiological and psychological process in adolescence that underpin increased adolescent risk
In conclusion, research has firmly established that peer pressure has a substantial influence on substance misuse in adolescence. Research has shown that the mere presence of peer increases risky behavior, suggesting that it is motivated by a desire to be liked by the group. The particular vulnerability of adolescents to peer influence can be explained by the dual process model, which offers the socioemotional network as a neurobiological underpinning for the strength of peer influence in adolescence. This model also explains that adolescents experience difficulties in cognitive control, which in conjunction with susceptibility to peer influence further increases their risk. The dual process model is contradicted by some literature which can dispute the socioemotional emotional network and the theory also has limitations with regards to the role of these networks in real life decision making. However the framework has a wealth of supporting evidence and continues to offer a useful model for understanding risk for substance use in adolescence.
Study showing parental substance use as a risk factor for adolescent use
In conclusion, research has firmly established that peer pressure has a substantial influence on substance misuse in adolescence. Research has shown that the mere presence of peer increases risky behavior, suggesting that it is motivated by a desire to be liked by the group. The particular vulnerability of adolescents to peer influence can be explained by the dual process model, which offers the socioemotional network as a neurobiological underpinning for the strength of peer influence in adolescence. This model also explains that adolescents experience difficulties in cognitive control, which in conjunction with susceptibility to peer influence further increases their risk. The dual process model is contradicted by some literature which can dispute the socioemotional emotional network and the theory also has limitations with regards to the role of these networks in real life decision making. However the framework has a wealth of supporting evidence and continues to offer a useful model for understanding risk for substance use in adolescence.
Study showing heritability as a mechanism underlying parental use as a risk factor for adolescent use
Heritability: Findings about the genetic transmission of substance use disorders such as alcoholism have shown that genetic risk can mediate environmental influences on adolescent SUD’s. Blomeyer et al 2008 Used 280 ps aged 15, who were genotyped and filled out a self-report questionnaire of alcohol consumption. Increased severity of adolescent Stressful Life Evenets was associated with earlier initiation of drinking alcohol and heavier alcohol consumption, but only in carriers of the CRHR1 rs1876831 CC major homozygote (gene conferring to corticotroping-releasing-factor). Therefore heritability of risk genes from parents could be one mechanism by which parental substance abuse is a risk factor for adolescents. However, this study has limitations. While the results appear robust, the sample size is relatively small for a genetic association study. Further research with larger samples would be required to support the reliability of this finding.
