Your high school friends may have had a bigger influence on your behavior than you once thought.
Prior studies about peer pressure have focused on why adolescents are likely to experiment along with friends who use drugs and alcohol.
Could observing a peer making a safe choice encourage someone to follow their lead?
In a new study published today in the Proceedings of the National Academy of Sciences, Virginia Tech neuroscientists at the Fralin Biomedical Research Institute at VTC show that observing peers making sound decisions may help young people play it safe. The discovery may one day inform measures to help teens make healthy decisions.
“This finding was surprising, because we were expecting to understand brain mechanisms of negative peer pressure. What we found in the brain and behavioral data is that positive social peers are even more important,” said Pearl Chiu, an associate professor with the Fralin Biomedical Research Institute and the Department of Psychology in Virginia Tech’s College of Science. “Watching social peers making safe choices – positive peer pressure – may lead some teens to make safer choices than they would otherwise.”
Risky decision-making in adolescence can have long-term consequences. Research has shown that teens who start using substances are more likely to develop a substance use disorder later in life, according to the Centers for Disease Control and Prevention.
“Our hope is that this work will help explain decision-making processes underlying risky decisions during this critical period of brain development and habit-forming in adolescence.
More long term, this might help researchers develop effective interventions to prevent substance use disorders,” said Brooks King-Casas, an associate professor with the Fralin Biomedical Research Institute and the Department of Psychology in Virginia Tech’s College of Science.
The research team, led by Chiu and King-Casas, recruited 91 adolescent research participants for the study. The teens fell into two categories: substance-naïve adolescents who had never tried illicit substances, and teens who reported that they had consumed alcohol, marijuana, or tobacco before.
The volunteers, who were strangers before the study, met each other briefly before participating in a decision-making game while the scientists monitored their brain activity using functional magnetic resonance imaging (fMRI) machines.
These scanners use powerful magnets to detect blood oxygen levels – an indirect measure of neural activity that helps the researchers see which brain regions are engaged during decision-making tasks.
While in the scanners, the teens were presented with a decision-making game that required choosing between a series of safer and riskier options. For example, they could pick option A, which guaranteed earnings of about $25, or option B, which touted a slim chance of paying $55, but most often produced earnings of just $1.
The teens made these gambling choices on their own and also after seeing what their peers picked. Meanwhile, the research team recorded the decisions and later used computational modeling to identify which brain regions were most active. Teens were paid based on the outcome of one of their choices.
Some of the research findings weren’t a surprise to Chiu and King-Casas. For example, the teens who had tried illicit substances were overall more likely to pick the riskier option, and their choices didn’t waver much when they saw what their peers picked.
Yet teens who had never tried illicit substances were more likely to follow their safe peers’ choices, and therefore also made safer choices for themselves.
The substance-naïve group’s scans also revealed significantly more activity in a brain region responsible for encoding social rewards: the ventromedial prefrontal cortex.
Located just behind the eyebrows and spanning roughly one cubic centimeter, this brain region plays a role in determining whether we will conform to others’ choices or ignore them, according to the research team’s 2015 study in Nature Neuroscience.
“Our results suggest that information from safer peers is processed in the brain like a reward. The reward signal might guide teens toward making the same choices as their safer social peers,” said King-Casas.
During adolescence, the brain’s reward structures swiftly develop. Yet the prefrontal cortex – a brain region responsible for executive functioning that helps reign in risky impulses – does not completely mature until roughly age 25.
“When there is a rapid change in brain development, even a slight interruption can induce a big change,” said Dongil Chung, the study’s co-first author and an assistant professor in the Department of Biomedical Engineering at the Ulsan National Institute of Science and Technology in South Korea. Chung previously worked as a postdoctoral researcher at the Fralin Biomedical Research Institute and was mentored by Chiu and King-Casas during the study.
Building on their previous work from 2015, the research team revealed that the availability of social information alone does not guarantee conformity.
“The individuals who value or care more about the value of social information are the ones who will be swayed to conform,” said Chung.
Among the research collaborators is Mark Orloff, the study’s co-first author and a graduate student in Virginia Tech’s Translational Biology, Medicine, and Health Graduate Program, who is mentored by Chiu. Orloff, who previously studied psychology, chose this topic for his doctoral dissertation because it links the neuroscientific study of decision-making processes and health behaviors.
“By using computational modeling, we can start to understand why decisions are being made,” Orloff said. “This technique allows us to tease apart the different underlying mechanisms of adolescent decision-making and isolate the contribution of safe social influence.”
Nina Lauharatanahirun, an assistant professor of biobehavioral health at PennState, also contributed to the study while she was a Virginia Tech graduate student being mentored by King-Casas.
Chiu and King-Casas intend to launch a study that follows a group of adolescents over a period of three to five years.
“One next step will be to follow adolescents over time and identify better models of how brain responses to safer and riskier social peers change. These developmental trajectories might further explain how peer pressure can be both protective and disruptive,” Chiu said.
Central to intervention science is developing an empirical taxonomy of individuals that guides prevention and treatment strategies (Lahey, Krueger, Rathouz, Waldman, & Zald, 2017). The conventional strategy is to use expert clinical consensus to define mutually exclusive diagnostic groups of youths who display symptoms of a disorder.
For example, the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Statistical Classification of Diseases and Related Health Problems (ICD) systems describe adolescent psychopathology along the lines in which adults are classified.
The approach arises from medical science, in which the first step is to carefully define a nomenclature for disease processes and the second is to understand etiology and treatment. However, various disorders such as depression, anxiety, addiction, and conduct disorder often share etiologies and even common elements in treatment.
Hence, many argue that the current diagnostic system focusing on symptoms of individuals is not sufficient or particularly helpful in guiding the design and selection of the most effective interventions.
As a result, the scientific community is moving away from research on individually oriented diagnostic categories to multifaceted patterns of mental health. The National Institute of Mental Health, for example, encourages research on the pathophysiology of mental health disorders using a research domain criteria (RDoC) framework (Insel et al., 2010).
This research focuses on genomics and neuroscience in search of underlying biosocial mechanisms. The focus on biological mechanisms will likely translate to improvements in psychopharmacological approaches to treatment (McGowan, Fishman, & Lambrix, 2010).
A complimentary and equally important need is to study the functional dynamics in close relationships underlying long-term variation in behavioral and emotional health. There is strong evidence that interventions that improve adolescents’ close interpersonal environments significantly enhance their behavioral and emotional health (Biglan, 2015; Sandler et al, 2011).
Understanding how youths adapt to their interpersonal environment is critical to the design and tailoring of family-based interventions (Dishion & Patterson, 1999). In particular, direct observation of relationship processes among youth can provide a robust, measurable, and pragmatic classification system that could directly link to potential intervention targets (Beauchaine, Gatzke-Kopp, & Mead, 2007).
A unique insight of ecological systems theory is that multiple relationships serve to socialize children and adolescents (Bronfenbrenner, 1979; 1986). An especially useful conceptual advantage of ecological theory is the concept of a “mesosystem.” A mesosystem is a supraordinate system consisting of two or more relationship dynamics.
For example, an adolescent who has conflicts with a parent and spends time with drug-using peers is potentially more likely to escalate to problem behavior. In comparison, an adolescent who is academically engaged and has primarily prosocial peers, but has conflict with parents, may be less at risk for the development of serious problem behavior (Van Ryzin & Dishion, 2012; Véronneau & Dishion, 2010).
Thus, the friendship and family dynamics considered together may uniquely influence socialization. In essence, functional dynamics with parents and peers are functional in that relationships adjust and can present primary risks in which pathology emerges and worsens.
A particularly useful method for understanding relationship dynamics between parents and peers is direct observation. A little over 10 years ago, it was suggested that observed interpersonal dynamics are not only important for predicting adolescents’ behavioral and emotional adjustment issues, but also for further improving diagnostic systems such as DSM (e.g., Beach, Wamboldt, Kaslow, Heyman, & Reiss, 2006; Piehler & Dishion, 2007).
Indeed, direct observation of relationship dynamics has some empirical advantages when attempting to identify salient functional adaptation patterns as intervention targets. First, observations directly measure specific relationship patterns and are less susceptible to global report biases (Dishion, Burraston & Li, 2006; Fiske, 1987).
Second, the computation of inter-observer reliability assures that the measurement will be more objective (Reid, 1978). This aspect of direct observation measurement is especially relevant to intervention research, allowing coding of videotapes of social interaction without observers’ knowledge of the participants’ intervention status. Third, the social interactions can serve as putative mediators of change (Patterson & Reid, 1984), which is at the core of translational research in the development of effective treatment and prevention intervention (MacKinnon, 2008).
Link to psychopathology
One example that suggests that dysfunctional interpersonal dynamics can amplify psychopathology is the coercion theory. Coercion describes the function of aversive behavior in resolving conflict in marital relationships and families (Patterson, 1982). Parent-child coercion is central to the etiology of the early onset of antisocial behavior in childhood (Patterson, Reid, & Dishion, 1992; Smith et al., 2014).
The cornerstone of coercion is family conflict, when two members of a family become angry and negative, and escalate insults and negative behavior (Snyder, Edwards, McGraw, Kilgore, & Holton, 1994). Most recently, a dynamic systems framework was developed to more reliably measure coercive dynamics (Granic & Patterson, 2006; Hollenstein, 2012).
Using state space grids, one can summarize interactions over the course of an observation session in terms of the ‘dyadic states’ of the participants. For example, the duration in which the parent and youth remain mutually aversive defines levels of family coercion. The duration in which the youth and parent(s) remain mutually calm, neutral, and positive during a problem-solving discussion reflects positive engagement, which predicts healthy adjustment (Dishion, Forgatch, Van Ryzin, & Winter, 2012).
A unique feature of the human relationship experience is that narratives can summarize the quality of the relationship. The narrative that emerges about a specific relationship purportedly affects the probabilities of future positive and negative interactions with that person. From relational frame theory (Hayes, Barnes-Holmes, & Roche, 2001), we can conceptualize the relationship narratives as relationship schemas that efficiently summarize overlearned and often unconscious expectancies regarding reinforcement and punishment within a specific relationship.
For example, resenting a parent for favoring a sibling over oneself can translate to a negative schema about that parent. This increases the likelihood of conflict and disengagement from the family. Similarly, a youth’s violation of parent trust through salient misdeed can create a parent’s negative schema, which reduces the likelihood of affectionate or shared pleasant activities. Contrarily, a positive schema can emerge from experiences suggesting trustworthiness or validation within a relationship.
The audiotaped five-minute speech sample (Magaña et al., 1986) is a useful method for capturing both parent and youth positive and negative relational schema. Systematically coding audiotaped speech samples of adolescents and their parents showed that low positive and high negative schema differentiated between families with typically developing adolescents from those with antisocial adolescents. Negative schema of adolescents and parents correlated moderately with observations of parent-youth coercion (Bullock & Dishion, 2007).
Social interaction patterns with friends contribute to peer influence on problem behavior in children and adolescents. In observational studies within adolescent friendships, a process of deviancy training (Dishion, Spracklen, Andrews, & Patterson, 1996) emerged as an important predictor for individual differences in drug use (Patterson, Dishion, & Yoerger, 2000; Piehler, Véronneau, & Dishion, 2012) and antisocial behavior in adulthood (Dishion, Nelson, Winter, & Bullock, 2004). More recently, deviancy training has expanded to include ‘coercive joining’ among adolescent friends.
Coercive joining describes a dynamic in which youth connect with friends by making denigrating statements towards others, suggesting and promoting aggressive behavior towards others, and making efforts to dominate each other. Gang membership was significantly associated with coercive joining in adolescent friendships and coercive joining uniquely predicted future violence over and above antisocial behavior and gang membership (Van Ryzin & Dishion, 2013).
Much of the observational research on families and friends focuses on the development of problem behaviors such as antisocial behavior, violence, and drug use. However, a recent comprehensive review suggests that social interaction patterns in general, and coercive processes in particular, predict a variety of emotional adjustment problems and psychopathology in youth and adults (Dishion & Snyder, 2016).
For example, conflict and coerciveness in families underlie adolescent depression (e.g., Sheeber, Davis, Leve, Hops, & Tildesley, 2007) and anxiety (Crowley & Silverman, 2016). When considering friendships, momentary assessments of conflicts in adolescent friendships also covary with increases in depressed mood (Connell & Dishion, 2006; Silk et al., 2013).
It is likely that there is developmental variation in how friendship and family dynamics define etiological pathways to adult emotional and behavioral health (Cicchetti, 1984). A person-centered framework is particularly useful for identifying subgroups of individuals who share similar family and friend observable dynamic patterns with unique developmental pathways.
There have been various person-centered approaches to understanding psychopathology in prevention science. One of the most popular approaches is to define classes of individuals based on their developmental trajectories of symptoms. In the study of antisocial behavior, this approach results in the identification of early-starting, childhood-persistent, and adolescent-onset trajectories (e.g., Moffitt, 1993; Patterson & Yoerger, 1993; Odgers et al., 2008).
Another approach is to apply a person-centered strategy to the analysis of heterogeneous symptoms. Fergusson, Horwood, and Lynskey (1994) used the reports of various mental health symptoms to classify adolescents. The authors identified a subgroup who presented both mood and problem behaviors.
Searching back to the adolescents’ childhoods, they found that the comorbid group had experienced severely disrupted family environments, both in the affective family climate and in material disadvantage. Expectedly, individuals in the comorbid group showed more mental health problems, criminality, and substance use as adults.
To our knowledge, however, there has been no person-centered analysis of observed relationship patterns in friendships and families during adolescence. This may be a promising approach to identify meaningful classes of adolescents who share distinct functional dynamics with friends, parents, and across the family-peer mesosystem. Such an approach would potentially be informative for the translational goal of identifying which environmental interventions would prove most effective for each adolescent subgroup.
These findings suggest that adolescent interactions patterns with family and friends can identify groups of youth with identifiable strengths and needs. A vast majority of adolescents are in healthy relationships. However, some subgroups display pathogenic relationship dynamics, of which two groups appeared to be most salient (Disaffected and Antisocial). Although some evidence-based interventions exist in addressing those needs, there is a need for translational research that empowers service providers to effectively tailor and personalize interventions based on cost-efficient assessment strategies.
reference link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951801/
More information: Dongil Chung el al., “Valuation of peers’ safe choices is associated with substance-naïveté in adolescents,” PNAS (2020). www.pnas.org/cgi/doi/10.1073/pnas.1919111117