During Adolescents

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“During Adolescents, if Teens are self-regulated and restrict themselves from risky activities or behaviors, they can prevent themselves from harm. An example of this is if a teen drove them self and friends to a house party that had alcohol. While their friends were off getting drunk, the teen was offered a drink, even though they want to have as much “fun” as their friends they refuse the drink. By rejecting that drink, they are inhibiting their impulses instead of taking the risk of driving drunk possibly causing a fatal accident.

Risk-taking itself is when someone participates in activities that can result in a negative or positive consequence. Risk-Taking is seen more in Adolescents than in any other age group. Some teens are still learning to regulate their emotions; Left in an unmonitored situation, with some peer influences. If teens cannot control their impulses to take part in risky behaviors, it can result in injury, social rejection and in extremes even death.

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Considering how important it is to know about risk-taking, we decided that we should investigate how culture plays a part in the number of risks taken by teens. We suspect that culture will play a role in those amount of risks taken. In the next few pages, we conducted prior research and will explain these different studies examined to construct our study.

Previous Research:

By reviewing five other previous studies, it laid the groundwork for our study. The first study by Wood, Dawe, and Gullo (2013) analyzed whether gender differences in relationships (Wood et al., 872/2) had any correlation between Impulsiveness, Substance Use, and Prosocial Behavior. These researchers predicted that Rash Impulsivity, Reward Drive, and family environment would contribute to the prediction of engagement in prosocial behaviors (Wood et al. 872/2) and that all three of those factors would contribute to alcohol and drug use.

While Reward drive and Rash Impulsivity would have a direct correlation with substance use; But Substance use would show a “negative association” (Wood et al. 872/2) with prosocial risk-taking. Participants for this study were recruited from 8 different schools in Queensland, AU, and consisted of 1,149 grade 8 students within a limited age range of 12-14. Participants were given questionaries’ during class time in which they were asked about how frequently and the amount of a substance (Alcohol, Tobacco, and Cannabis) consumed.

They were also asked about their Rash impulsivity which was measured using a subscale of the I7 Impulsivity scale, and their Reward drive using the Appetitive Motivation Scale which is a scale that measures the natural desire to act impulsively. Lastly, participants were asked about the Prosocial risk-taking which they measured using the Prosocial activities scale which is “a list of 14 sports and recreation activities that can be categorized accordingly” (Wood et al. 874/4). The last participants were questioned about was the Family Environment.

They measured this on two scales, the first being the Family Environment Scale and the second the Children of Alcoholic Screening test. This study found that girls traits had a higher correlation with rash impulsivity which was directly associated with higher rates of substance use and, reward drive was indirectly associated with substance use through participation in physical-risk activities, Predicting a greater use.

Boys showed higher rates of participation in physical-risk activities was their only direct indicator of substance use and their reward drive conveyed this risk. Family environment, reward drive, and rash impulsivity were all highly associated with participation in performance-risk activities (ex. theater, dance), and prosocial behavior more a less, but none were related to substance use.

However, the result of this study’s teeters on accuracy. A social desirability effect among genders could hinder the accuracy of the result, for example, while boys are likely to take more risk, in a situation that may be different, they could lie on the questionnaire to seem “cooler” amongst their peers.

There was a very young, limited age-range where result may differ if they spanned it from age 12 to say age 18. Also, this was done in one country where laws or morals may vary from other countries, meaning, for example, alcohol use at that age (12-14) may be more acceptable. Therefore, is ou study I will explore a somewhat larger age-range of adolescences, when risk-taking is commonly seen and while it will only be in one country, it will span across the entire country and include those of all culture.

The second study we read was Galvan et al. (2007) where they explored “the neural correlates of risk-Taking behavior in adolescents, relative to children and adults, to predict who may be at greatest risk” (Galvan et al., F8/1). They predict that Adolescent will show more risk-taking behavior than adult or children. Participants in this study were a subset group of individuals from an fMRI experiment.

There were ten adults, seven adolescents, and nine children, but only those who completed a questionnaire were included in the analysis for this study. This study had several different measures from a basic risk-taking assessment, which assessed their idea of risk and how they perceive the consequences of said risk to an Image Analysis which was when they used random effects on images taken of the participant’s brain. The result showed that While there was no gender difference in data, each age group showed a significant association between accumbens activity and there was a positive correlation between individuals’ ratings of the anticipation of a positive consequence and accumbens activity.

There was a pattern change across development for adults and adolescents who showed an association between accumbens activity and anticipated positive consequences of risk-taking. However negative consequences and accumbens activity showed no correlation. The entire sample showed that the likelihood of someone engaging in risky activities correlated with positive consequences and anticipation of a negative consequence.

This study was strategically done; there is a minimal number of participants made us question the accuracy of the results. By having a smaller number of participants, it can increase the chance of assuming something is true, but it is false. Also, by excluding those with Neurological or Psychiatric diseases/disorders, because the chance of the of them thinking through a risky-decision is less likely than someone who does not, which would change the outcome in the result. While our study will survey a more significant number of people, we will also include those who suffer from these disease/disorder to get more of a different result instead of excluding those who do.

The next studied viewed, Ertac and Gurdal (2012). This study looked at what gender desired to make a risky decision for a group and how that compares to their individual decision making. They predict that there would be a significant gap between the genders on deciding on behalf of a group. Men were making more of the risky-decision on behalf of a group. They also think that women are less likely to take less risk than men in both group setting and individually.

Their study consisted of a total of 128 subjects, more male than female, from two different universities in Turkey. This study was broken down into two parts Individual and group decision-making with the subjects making three decisions for each. Subjects were given 10 Turkish Liras to invest in a riskless option, a safer choice and a risky option, which meant subjects had a 50/50 chance of losing it all. Subject decisions were then randomly selected to be paid.

If one an induvial-decisions was chosen, that subject was paid. However, if a group’s choice was chosen all five members of the group were paid. Group leaders were randomly selected, if more than one person wanted to make the decision or if no one wanted to decide. The results were broken down in three parts, the first Individual Risk-Decisions.

They discovered that Women were less likely to make group decisions even in a leadership position because they do not want to be responsible for a negative turnout. While men took more risks in group settings than they would for themselves took a “leading” role in individual decision making. While this experimental study was done well, the only downside to this study was decisions that were made we do not know what the subject of it was. So, in our study, it will be more specific in terms of questions.

Next was Crone et al. (2008) a two part-study that looked at how risk and reward are influenced depending on how adolescents view it when taking risks. They predict that Risk-taking will decrease as Age increase. In the first experiment conducted, all healthy participants were recruited from schools. Included were 20 children ages 8-9, 18 young adolescents 11-12, 17 middle-age adolescents ages 14-15 and 17 older adolescents age 16-18.

They had participants sit in front of a computer and gave them two baskets of coins to choose from; The first was a non-risky basket where they got one coin, The second, a risky option in which they earned five coins but had a 50/50 chance of losing four coins. The result of the first study showed that there was an age difference in risky decision making because it depended on the situation where risk was involved — while risk does increase with age that risk is beneficial or low-risk. High-risk actives decreased because of the negative consequence it could cause.

The Second experiment looked at if those who are more likely to make risky decisions influenced their peers. They expect that adolescents who have higher SS (Sensation Seeking) tendencies will also make high-risk decisions in the experiment. The recruited sixty-one, all boy participants from a high school in the Netherlands. This High school is known for having students with risky-behavior. The boys all completed Zuckerman’s SS scale that consisted of five subscales that measured topics like impulsivity and thrill and adventure seeking aspects of SS.

Participants then completed three subscales, TAS, Dis/Es, and IMP; All subscales consist of true or false questions. For all scales, the high risk-teens would make deskins for lower risk teens. The result of this experiment was like the ones found in the first experiment. Individual decisions made were different from the ones made for someone else, and there were fewer high-risk decisions made.

Overall this entire study was done well. However, like all the other studies they had a minimal number of participants in whether that be by choice; But as said about the Galvan et al. (2007) study, a small number of participants can lead to thinking a result was, but instead it was false.

The last study we looked at was Duell et al. (2017) were they looked at if the culture had any impact on risk-taking. They predicted that risk-taking would be associated more with late adolescents than any other age group and it would be the same across the countries studied.

They gathered 5,227 participants ranging in age from 10-30, from metropolitan area’s in eleven countries including the U.S. via flyers and spreading the word from one to the next. The used six different measures, including a stoplight, in which participants had to drive through twenty intersections to a radio station where there was a prize for whoever got there the quickest. The BART, in which they were told to fill up a balloon with air, the bigger the balloon, the more points you earned. Self-Reported Risk-Taking, measured on the Benthin risk perception scale.

Their prediction where right as they discovered that risk-taking was seen more in late. Covariates measured two variables (Intelligence and Socioeconomic status) that are linked to risk-taking — intellectual ability, which participants used a computer to determine the non-verbal intelligence of participants. Last was Parental Education were participants were asked to rate the amount of Education their parent received from zero (no education) – fifteen (Education beyond college). Like predicted the results show older adolescences took more risks than younger adolescences, and despite culture, risk-taking tendencies are the same across all countries studied.

This study was one we looked at the most because we felt it gave us the most information about culture since it was based in several countries anyone could participate. The only issues to take up with this study is how it was done, meaning the measures. Which we believe is just us seeing a study done in a more classic structure of scale and survey measures.”

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During Adolescents. (2021, Oct 15). Retrieved from https://papersowl.com/examples/during-adolescents/