Peer Influence on Deviant Behavior
Sponsored by Missouri Western State University Sponsored by a grant from the National Science Foundation DUE-97-51113
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The proper APA Style reference for this manuscript is:
HOBBS, M. E. (2007). Peer Influence on Deviant Behavior. National Undergraduate Research Clearinghouse, 10. Available online at http://www.webclearinghouse.net/volume/. Retrieved June 27, 2017 .

Peer Influence on Deviant Behavior
MEGHAN E. HOBBS
MIAMI UNIVERSITY DEPARTMENT OF PSYCHOLOGY

Sponsored by: ZACHARY BIRCHMEIER (birchmzp@muohio.edu)
ABSTRACT
AbstractThe purpose of this study is to investigate how the deviance level of an individual’s peer group and whether they are alone or part of a group affects their likelihood to engage in deviant behavior. Participants included 63 females and 67 males between the ages of 18 and 26. Using a web based survey, researchers randomly assigned participants to an experimental condition where they read a brief scenario and answered follow-up questions. Using a modified version of the Myers-Briggs Type Indicator and other measures created by the researchers, extroversion/introversion, peer deviance, and participant deviance were examined. A bivariate correlation showed a significant relationship between peer deviance and the participant deviance. A multiple regression showed that the model as a whole, which included extroversion, peer deviance and age, was a strong predictor of participant deviance. A two-way ANOVA showed that there was a significant main effect for peer deviance. Researchers concluded that while other factors contributed to deviance, peer groups were especially influential in participant deviance. These results have implications for how deviance can be dealt with and prevented.

INTRODUCTION
The issue of peer pressure is one of great interest in the psychological field. In Eric Erikson’s Theory of Identity vs. Identity Confusion, the psychological conflict of adolescence in this developmental stage is reviewed (Berk, 2004, p. 382). According to Erikson, individuals in this stage become more susceptible to peer pressure, due to the shift in emotional dependence from parents to peers (Wall, Power, Arbona, 1993, p. 404).This study takes Erikson’s theory a step further, by examining peer influence on deviant behavior and how an individual’s tendency toward deviance is influenced by several conceptual variables. In addition to how deviant behavior is influenced by the presence or absence of a peer group, the effects of age, gender, individual personality, and peer morality on deviance will also be examined. The results of this study will provide a better understanding of the factors that influence negative behavior, thus shining light on possible routes that could be used to avoid deviance. Past research shows that peer influence has emerged over the last 50 years to be the chief source of values and behavioral influence in adolescence, replacing the influence of adults. Along with this new trend has come a rise in antisocial behavior (Neufeld & Mate, 2005, p.10-11). Although the level of deviance from peer group to peer group varies, the negative actions of one member in a group will increase the probability of other members taking part in similar behaviors. Affiliation with deviant peers predicts delinquent behavior more strongly than community, school, or family characteristics (Gifford-Smith, Dodge, Dishion, & McCord, 2005, p. 255-56). Research has also found relationships between deviance and other factors. Studies have shown young adolescents to be more susceptible to peer influence than are younger children or those in late adolescence (Pruitt, 1999, p. 10). An increase in susceptibility is seen between grades five and eight, followed by a linear decline as older adolescents develop a sense of autonomy from their peers. Another factor, gender, shows females depending more on parents for behavioral cues and reporting less likelihood of conforming to antisocial peer pressure (Wall et al., p. 404-05). While women display relative interdependence, such as close friendships, men tend to show more collective interdependence, as in group alliances, making them more susceptible to pressures from these groups (Gabriel & Gardner, 1999, p. 642). Research reveals that an individual’s level of extroversion is a predictor of deviance as well. In a study of substance use in Taiwan, it was found that higher extroversion scores acted as a predictor of adolescents’ substance use (Kuo, Yang, Soong, & Chen, 2002, p.36). Also a factor in deviance is the likelihood of the individuals peer group to partake in deviant behavior. A previous study found an individual’s drug use to be highly correlated with peers who encourage drug use (Oetting & Beauvais, 1987, p.211). A different perspective by Pruitt (1999) shows that positive peer pressure can also have a strong effect, and that even adolescents that are highly susceptible are more likely to be influenced by positive or neutral behavior, rather than antisocial behavior (p. 82). Also, while pressure from peer groups is undoubtedly influential, most teens choose friends that share common views about behaviors such as drinking or drug use. Pruitt states that “the ‘good kid’ who falls in with the bad crowd is the exception, not the rule (p. 37).”These studies and findings lend direction to the predicted findings in this research, on the relationships between deviant behavior and peer influence, age, gender, personality, and peer group deviance levels of the participants. For a two by two study (group vs. alone, and deviant peers vs. non-deviant peers) it is hypothesized that when participants are randomly assigned to two conditions, one in which they will read a scenario where they were in a group and one in which they will read a scenario where they are alone, there will be a main effect between the group vs. alone conditions as well as a main effect for the engagement of deviant behavior for a person’s rating of their group of peers as being deviant or non-deviant. No significant interaction is predicted. Also it is believed that the likelihood of engaging in deviant behavior when in a group will be positively correlated with extroversion, higher deviance of peers, being in a group, and will be negatively correlated with age. For this study, an internet based experiment will be administered to participants, with a majority of college aged students, in which scenarios manipulating the social environment will be presented. Participant will then answer questions as to how they would react to specific temptations in the given environment. Also, a multiple regression will be run in order to determine correlations between deviance and other factors. Variables under consideration include the participant’s age, gender, individual personality (predispositions toward introversion or extraversion), the likelihood of the individual’s own peer group to participate in deviant behaviors, and the social environment (specifically, the presence or absence of a peer group). We will manipulate the participant’s environment through hypothetical scenarios. The observation of these variables will further past research by showing insight into the impact of positive peer pressure and the effects of peer pressure on individuals moving out of the adolescent stage. Also, by using a multiple regression, the research will explain the influence a more complex interaction of the variables has on deviance.


METHOD
Participants The participants were volunteers invited to complete the experiment online. Both males (M= 63) and females (F= 67) between the ages of 18 and 26 responded. The majority of the participants invited were Caucasian college students. The participants were not given any incentive to complete the survey.MaterialsResearchers used a web based survey to measure peer influence on deviance. Qualtrics was the survey software used in this experiment. A variation of the Myers-Briggs Type Indicator was used as a scale to measure levels of introversion and extroversion. Likert scales were used for the remaining questions regarding the deviance of the participants and the deviance of the participants’ peer groups. ProceduresResearchers used the social networking websites www.facebook.com and www.myspace.com, as well as the instant messaging server American On-Line Instant Messenger (AIM) as the method to administer the survey online. Participants were asked to click on a link to a survey consent form (www.users.muohio.edu/thomasc6/consent.htm). When participants clicked on the aforementioned link they were directed to an online consent form that only told them they were being asked about their reactions to different hypothetical situations, so as not to bias the survey results. When the students accepted the consent form, they were randomly assigned to one of two different situations. If assigned to the first group, the participant was asked to imagine a hypothetical situation in which he went into a party alone and found alcohol that was not his. Then the participant was asked what he would do in the situation. If assigned to the second group, the participant was asked to imagine a hypothetical situation in which she and a group of friends went to a party, and found some alcohol that did not belong to anyone in the group. Then the participant was asked if she would take the alcohol. After this scenario, both sets of participants were asked to answer some other questions about age, introversion or extroversion, and deviance. The complete list of questions appears in Table 1 in the appendix. When the survey was completed the participants were directed to a debriefing form, where they were told the full purpose of the experiment (that the experiment was actually to test peer influence on social deviance) and were asked not to tell the details of the experiment to other possible participants.


RESULTS
The level of significance, used for all tests, was á = .05. An internal consistency analysis showed that the data had low reliability, Cronbach’s á = .41. A bivariate correlation ran for first order relationships revealed a significant relationship between deviance of participants’ peers and the likelihood of participants to engage in deviant behavior, r = .61, p < .05. No other significant relationships were shown (see Table 2). It was hypothesized that the likelihood of engaging in deviant behavior will be positively correlated with extroversion, age, and higher deviance of peers in combination. After running a multiple regression, the data showed the model as a whole to be a significant predictor of deviance, r = .60, F(3, 123) = 22.72, p < .05. 35.7% of the total variance was accounted for by the model. However, only deviance of peer groups was shown to be a significant predictor above and beyond the model, t = 8.09, p < .05. No other variables were significant predictors (see Table 3). For a two by two design (group vs. alone, and deviant peers vs. non-deviant peers) it was hypothesized that when participants are randomly assigned to two conditions there will be a main effect for the group conditions and deviance of peers, but that there would be no interaction between the two. Using a two-way analysis of variance (ANOVA) the data showed that there was no main effect between the group (M = -.06, SD = .11) or alone (M = -.05, SD = .11) conditions, F(1, 125) = .00, p > .05. Using a 1-5 scale with 1 indicating highest deviance of peers and 5 indicating lowest deviance of peers, it was shown that there was a main effect between deviant peers (M = -.52, SD = .12) and non-deviant peers (M = .41, SD = .11), F(1, 125) = 34.11, p < .05. No significant interaction was found, F(1, 125) = .00, p > .05 (see Figure 1 for summary).


DISCUSSION
When evaluating the results of the statistical analyses, support for the correlational hypothesis was only found for first order relationships in the positive relationship between the deviance levels of the participants’ peer groups and their own levels of deviant behavior. This means that as peer group’s deviance increases so does the deviance of an individual. This supports findings of previous research which stated that affiliation with deviant peers predicts delinquent behavior more strongly than community, school, or family (Gifford-Smith et al., 2005). Results may not have shown a significant relationship with age like previous research, because our sample included only participants in late adolescence and early adulthood, and previous research found a linear decline in susceptibility as older adolescents develop a sense of autonomy (Wall et al., 1993). Other studies that used predominately younger adolescents showed susceptibility to peer pressure to be highest in this age group, most likely causing them to be more deviant when their peers are deviant (Pruitt, 1999). Results failed to support previous research that found higher extroversion scores to act as a predictor of adolescents’ substance use (Kuo et al., 2002). Also, the results of the multiple regression further supported the correlational hypothesis by showing the model as a whole to be significant, meaning that when extroversion, peer deviance, and age are considered simultaneously they can be useful in predicting the likelihood that an individual will engage in deviant behavior. However, only deviance of peer groups was shown to be a significant predictor above and beyond the model. The results of this study only supported the experimental hypothesis partially. The findings did not show a main effect for the presence or absence of others, meaning that regardless of whether an individual was in a group or was alone, their likelihood of engaging in deviant behavior did not differ significantly. Consistent with the hypothesis, no significant interaction was found, meaning that the level of peer deviance was not dependent on whether or not the participant was in a group or alone, and vice versa. Also consistent, a main effect was found for deviant and non-deviant peer groups, meaning that the likelihood of an individual engaging in deviant behavior is significantly different depending on whether the affiliated peer group is deviant or non-deviant. This parallels a previous study that found an individual’s drug use to be strongly correlated with peers who encourage drug use (Oetting & Beauvais, 1987). The results of the current study, which showed that participants in the non-deviant peer group exhibited a significantly lower likelihood to engage in deviant behavior, also support a prior, alternative perspective that positive peer pressure can have a strong effect (Pruitt, 1999). The results of this study however were limited by several factors. Because invitations and alerts to the study were not sent out to a very diverse group, results cannot be generalized to the entire population. The age range (18-26 years of age) only included participants in late adolescence, limiting comparisons to previous literature, which dealt mainly with earlier adolescence. Because deviance of peers was not manipulated, but instead reported by participants, it cannot be concluded that deviance of peers causes an individual’s likelihood to engage in deviant behavior, but can only be concluded that the two are correlated. Also, many participants did not complete the survey in its entirety, the survey, being web based, used self report and may not have sufficiently primed participants, the internal consistency was low, and the definition of deviance itself may be subject to variation. These results have implications for how deviance can be dealt with and prevented. Because the study showed a strong positive relationship between the deviance of an individual and the deviance of peer groups, it is clear that it is important to choose peer groups wisely and it is important for parents to be aware of potential influences on their children. Also, because these results showed a possible cause of deviance, they may help those who work with deviant adolescents and young adults by leading them to more effective methods. There are also many variations that could be run to increase the external validity of this study. Results could differ between cultures or regions of the country or the world. It is also possible that running this study with test subjects of different races, ages or socio-economic statuses could produce more gerneralizable findings.


REFERENCES
Berk, L. E. (2004). Development Throughout the Lifespan (3rd ed.). Boston: Allyn and Bacon.

Gabriel, S. & Gardner, W. L. (1999). Are There “His” and “Hers” Types of Interdependence? The Implications of Gender Differences in Collective Versus Relational Interdependence for Affect, Behavior, and Cognition. Journal of Personality and Social Psychology 77(3), 642-655.

Gifford-Smith, M., Dodge, K. A., Dishion, T. J., & McCord, J. (2004). Peer Influence in Children and Adolescents: Crossing the Bridge from Developmental to Intervention Science. Journal of Abnormal Psychology 33(3), 255-265.

Kuo, P., Yang, H., Soong, W., & Chen, W. J. (2002). Substance use among adolescents in Taiwan: associated personality traits, incompetence, and behavioral/emotional problems. Drug and Alcohol Dependence 67, 27-39.

Neufeld, G., & Mate, G. (2005). Hold On to Your Kids. New York: Ballantine Books.

Oetting, E. R., & Beauvais, F. (1987). Peer Cluster Theory, Socialization Characteristics, and Adolescent Drug Use: A Path Analysis. Journal of Counseling Psychology 34(2), 205-213.

Pruitt, D. B. (Ed.). (1999). Your Adolescent. New York: Harper Collins.

Wall, J. A., Power, T. G., & Arbona, C. (1993). Susceptibility to Antisocial Peer Pressure and Its Relation to Acculturation in Mexican-American Adolescents. Journal of Adolescent Research 8(4), 403-418.


APPENDIX
 Table 1     It is the weekend! There are parties all over campus that are open to the public. You are walking by yourself and you come across a house party. There are a lot of people inside and it seems as if anyone can go in. How likely would it be for you to go into the house and join the party?	It is the weekend! There are parties all over campus that are open to the public. You are walking with a group of friends and you come across a house party. There are a lot of people inside and it seems as if anyone can go in. How likely would it be for you and your friends to go into the house and join the party?Assuming that you decide to go into the house, what is the likelihood that you would engage in a conversation with someone who you have not met before?	Assuming that you and your friends decide to go into the house, what is the likelihood that you would engage in a conversation with someone who you have not met before?You make your way to the kitchen, and no one from the party is there. In the kitchen is a case of beer that apparently someone bought for only their consumption. Not knowing anyone at the party, how likely would you be to take a beer from the case?	You and your friends make your way to the kitchen, and no one from the party is there. In the kitchen is a case of beer that apparently someone bought for only their consumption. Not knowing anyone else at the party, how likely would you and each of your friends be to take a beer from the case?How old are you?Gender?If your friends were alone in the aforementioned scenario, how likely do you think they would be to take a beer from the case in the kitchen?When you go out on the weekends, how likely is your peer group to choose activities that break rules?When responding to the following four questions, identify how well these characteristics describe you.

I tend to act first, and think/reflect later:I regularly require an amount of "private time" to recharge my batteries:Usually open to and motivated by the outside world of people and things:I prefer one-to-one communication and relationships:

Table 2 Correlations Age Zscore: The mean of the extroversion/introversion variables Zscore: Likelihood of taking beer from case Zscore: The mean of the deviance of participant`s friendsAge Pearson Correlation 1 .030 -.029 .054 Sig. (2-tailed) .736 .746 .544 N 130 127 130 129Zscore: The mean of the extroversion/introversion variables Pearson Correlation .030 1 .120 .163 Sig. (2-tailed) .736 .177 .068 N 127 127 127 127Zscore: Likelihood of taking beer from case Pearson Correlation -.029 .120 1 .607(**) Sig. (2-tailed) .746 .177 .000 N 130 127 130 129Zscore: The mean of the deviance of participant`s friends Pearson Correlation .054 .163 .607(**) 1 Sig. (2-tailed) .544 .068 .000 N 129 127 129 129** Correlation is significant at the 0.01 level (2-tailed).

Table 3 Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .897 1.142 .786 .433 Zscore: The mean of the extroversion/introversion variables .025 .073 .025 .347 .729 Zscore: The mean of the deviance of participant`s friends .596 .074 .595 8.086 .000 Age -.044 .056 -.057 -.782 .436a Dependent Variable: Zscore: Likelihood of taking beer from case

Figure 1

Submitted 5/9/2007 6:37:14 PM
Last Edited 5/9/2007 6:46:02 PM
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