PREDICTORS OF EARLY ADULTHOOD DEPRESSION AND ANGER

In refining the symbolic interaction theory, Erving Goffman developed a dramaturgical perspective in which societal interactions are viewed as individuals reacting differently to different settings rather than everyone performing standardized interactions. This perspective values how specific contexts inform and alter how individuals behave. Lack of social control and self-control allows and promotes deviant behavior such as drug use, depression, and trouble in school.

“Self-control” refers to individuals’ abilities to exercise restraint or control over their feelings, emotions, and reactions. Gottfredson and Hirschi 1990 asserted that self-control develops early in life and is usually fully established by age 8 or 10. Socialization implemented by caregivers, peers, and social institutions, such as schools, faith-based organizations, and extracurricular activities, shape an individual’s cognitive choices and control personal urges. In the absence of these resources, which function as positive influences, children are less likely to learn to defer or inhibit self-gratification Vazsonyi & Huang, 2010.

“Deviance” refers to actions or behaviors that violate expectations, including formal rules (such as laws) and informal social norms. “Delinquency” refers to predispositions to commit crimes; deviance is a different matter that does not revolve around the law, making it more to do with convention.

In adolescence, deviance might be measured by school-related variables, such as academic achievement, along with individual actions such as theft, drug use, and sexual promiscuity. In young adulthood, deviance might manifest itself through illegal activity, such as drug use and whether the individual has ever spent time in jail or been homeless. It is important to note that these indicators measure the same underlying behavior of deviance, even though they differ in the specific criteria they indicate.

For the purposes of this study, “social control” is understood as the control over an individual’s behavior through public opinion, legal force, and social and religious organizations operating predominantly with the interest of society as a whole.

THEORETICAL PERSPECTIVES

Social Control Theory
Social control theory is based on the notion that when individuals are involved in group social activities, they believe in a sense of higher social norm. Individuals are less likely to exhibit deviant behavior. In order to prevent individuals from engaging in delinquent behavior, the involvement in non-delinquent groups and having attachments to social contexts is stressed. These relations allow for the belief in more encompassing social norms Powell, Perreira, & Harris, 2010.

Social control is meant to be an informal means of maintaining public order by fostering conformity and compliance to rules and norms. The mechanisms of social control are nearly invisible to the average citizen and are hardly ever questioned due to the fact that they are frequently cross-cultural. The social control process clearly differs from self-control due to the internalization of norms and values, as well as from the use of sanctions.

Symbolic Interaction Theory
Symbolic interactionism examines how personal interactions relate to the constructions of society and the concept of one’s self. The work of George Herbert Mead argues that meaning is created through interactions Gould, 2009. Once the meaning of the interaction is agreed upon, it becomes a social reality Gould, 2009. The connection between society and experience is negotiated by an individual’s interactions, such as language choice, because it gives meaning to the world. Language is an example of a way in which individuals exchange symbols to provide new meaning.

Individuals’ socially constructed meaning derives from interactions that guide their behaviors, which can be understood as a form of social control. Due to the fact that society and individuals cannot be separated, individuals are continuously being pushed, pulled, created, and recreated by society and social forces. Nonetheless, there remains individual agency to negotiate relationships within society. This creates a tension between personal identity and society’s perception of individual value, thus forming a fluid definition of one’s worth. When an individual defines a situation as real, he or she consequently perceives it as real.

Literature Review
This section of the study will introduce all of the major concepts and ideas that serve as a basis for the current study and describe their inadequacies as they pertain to the topic. This research extends from a series of key findings relating deviance to the growth and development of individuals over time. The literature most pertinent to the perspective and direction of this project is summarized below. The concepts introduced by control theory and social bonding theory, as modified by self-control theory, are discussed through how they relate to deviance being caused by individuals’ abilities to exercise restraint or control over their feelings, emotions, and reactions. The unique path my research plans to incorporate is how symbolic interactionism interprets personal interactions as they relate to constructs of society and the individual’s construct and concept of self. The connection between society and experience is negotiated by an individual’s interactions shown through self-control.

One study found that, contrary to popular belief, the type of households inhabited by adolescents was not a significant predictor of delinquency Mack, Leiber, Featherstone, & Monserud, 2007. The connection of Hirschi’s 1969 social control theory with the social bonding theory is meant to explain delinquency as a result of the lack of strong conventional family attachments in an individual’s life, emphasizing that it is not the number of connections but the quality of the interaction between parent and child Mack, 2007. This allows for quality positive attachments in relationships to be observed alongside different social groups and setting attributes that conduct of the individual Goffman, 1959.

When adolescents have a low level of quality attachment, they are more inclined to be involved in deviant behavior Mack et al., 2007. Parents play an integral role in the socialization process; it’s shown through the increase in delinquency of non-intact households. With children who engage in good relationships with their parents and have quality peer relationships, delinquent behavior is less prevalent Mack et al., 2007. The relationships function as a form of social control to motivate them to operate and create the adolescents’ identity within the norms of society. The questions selected for my research will reflect the attachments absent in adolescence by looking at depression, drug use, trouble in school, and violence. These areas are intended to show how adolescents lacking in quality attachments have deviant and delinquent relationships.

Negative adolescent effects are categorized as anything that leads to increased deviance Mason, Hitch, & Spoth, 2009. The effects are characterized as depression and homelessness, substance use, and peer deviance as interrelated characteristics that shape adolescent relationships, rather than being independent from one another Mason et al., 2009. Based on the criteria used, my statistical analysis will look at depression, homelessness, violence, and juvenile delinquency. The negative effects promote deviance and delinquency by preventing individuals from upholding constructive relationships with conventional peers and causing peers who lack positive social groups to seek out deviant peers Mason, 2009. The relationship between these factors is the basis for the questions chosen from Add Health to determine the deviant behavior in adolescence and into early adulthood. Peer relationships are important because they are the means in which socialization occurs most frequently. Depression, homelessness, violence, low academic achievement, and juvenile delinquency prevent individuals from maintaining constructive relationships with conventional peers and encourage seeking out deviant groups. Based on the literature, the regression analysis of violence interaction, depression, and anger and hostility in early adulthood is intended to show the relationship with anger, depression, and drug use.

The social controls and bonding theory previously established by Hirschi 1969 will be examined alongside the theory that deviance is a function of an individual’s ability to exhibit self-control Longshore, Chang, Hsieh, and Messina, 2004. This adds an additional dimension to the understanding of deviance by looking at the individual’s ability to exhibit self-control. In contrast with social control theory, based on an individual’s quality of attachment with society, the focus is on an individual’s ability to execute self-control. This parallels Goffman’s concept that an individual’s performance is based on the choice to enact behaviors that exhibit desired characteristics.

Delinquent participants with low self-control have a greater number of peers who consume drugs and possess weaker conventional bonds and moral beliefs Longshore et al., 2004. These factors contributed to substance use: involvement in an unconventional lifestyle, moral beliefs, religious commitment, and association with substance-using peers Longshore et al., 2004. While no one path led directly to substance abuse, the combination of substance-using peers and low self-esteem or flaccid moral beliefs did significantly correlate with substance use Longshore et al., 2004. An individual’s amount of self-control is reflected in the peer group they chose to surround themselves with and the deviant actions in which they participated with the given audience. This information has led to my inclusion of deviance later in life, rather than focusing only on early adolescence. Deviant peers in young adulthood could foster deviant actions later in life.

The association between extracurricular activities and deviance among adolescents depends more on micro-level contextual factors meaning the relationships, identities, and norms within specific activities Guest & McRee, 2009. This is where deviance is taught and reinforced. This then creates a feedback loop that increases the likelihood of negative effects. The process limits individuals’ opportunities to develop healthy, socially acceptable relationships, thereby causing individuals to seek out like-minded peers who participate in and promote deviant behaviors Mason, 2009. In an individual’s chosen group, deviant behavior will allow him/her to gain social status and esteem. Extracurricular activities are where actions are taught and reinforced. When deviance is the behavior being reinforced, it causes individuals to seek out like-minded peers who will accept this type of behavior.

Gottfredson and Hirschi’s 1990 view of being impulsive and lacking the ability to plan for the future is the definition of lacking self-control. Originally, the explanation was that self-control develops during the first decade of life and remains stable Vazsonyi & Huang, 2010. The findings most pertinent to this research are statistical results showing that, while self-control is developed within the first decade of life, self-control continues to grow over time Vazsonyi et al., 2010. It was also found that the deviant trajectory declines over time Vazsonyiet al, 2010. This shows that positive socialization has a positive nonlinear impact on how self-control is developed, which can explain and predict why self-control measurements of children differ. These conclusions hold true for different ethnic and racial groups, youth and adults in different countries, and among diverse genders and socioeconomic strata.

METHOD

Working with the Department of Human Development at Virginia Polytechnic Institute under the supervision of Dr. Mark Benson and Graduate Research assistant Caitlin Faas, I was able to develop this research project through the use of the public data set from the National Longitudinal Study of Adolescent Health (Add Health). The data from the original Add Health study was based on a nationally representative sample of sixty schools stratified by region, school type, ethnicity, and size. The first wave of data was gathered from seventh to twelfth grade students so that there were equal numbers of students from each grade level. This population was surveyed three additional times after the initial interview.

For the purposes of this project I used the public data set (N = 6,504) with no qualifiers. The questions I selected in Wave I were related to adolescent deviance. The Wave IV questions were based on deviance in young adults in order to see if the behavior continued. This was done by examining the questions that measured school-related variables, along with individual actions such as legal problems, emotions, drug use, and sexual promiscuity in Wave I and then following the answers into Wave IV. The questions I selected from the Wave I codebook were based on the Benson, Faas, and Kaestle (under review) division of the original questions. They had previously divided the question asked of the participants into 30 scales based on similar areas. The analysis of the questions’ descriptive variables, correlations, and linear regressions were conducted with JMP, a computer program developed by SAS Institute to perform simple and complex statistical analyses.

Independent Variables- Wave I
Minor juvenile delinquency. This scale’s amount of delinquency was determined by using eight items from Wave I (α = .78) that were self-reported. Item statements included, “How often did you steal something worth more than $50?” and “How often did you deliberately damage property that did not belong to you?” Responses included (0) never to (3) five or more times, ranging from 0-24.

Major juvenile delinquency. In this scale, the amount of delinquency was determined by using seven items from Wave I (α = .73) that were self-reported. Item statements included, “How often did you run away from home?” and “How often did you get into a serious physical fight?” Responses included (0) never to (3) five or more times, ranging from 0-21.

Violence and exposure. The construct of violence and exposure consisted of eight items that adolescents self-reported from Wave I. Adolescents were asked to report “how often each of the following things happen.” Item statements included “Someone pulled a knife or gun on you” and “You were jumped.” Responses included (0) never to (2) more than twice, ranging from 0-16 (α = .75).

Drug use. Within this scale, the amount of drug use was determined by using three items from Wave I (α = .69) that were self-reported. Item statements included, “Have you ever tried marijuana?” and “Have you ever tried cigarette smoking, even just one or two puffs?” Responses included (0) never have tried to (3) all tried, ranging from 0-3.

Depression. The construct of the depression measure consisted of nine items that adolescents self-reported by stating “how often each of the following things is true during that past week.” Item statements included, “You thought your life had been a failure.” and “You were jumped.” Responses included (1) never or rarely to (4) most of the time or all the time, ranging from 9-36 (α = .84).

Trouble in school. The amount of trouble in school was determined by using four items from Wave I (α = .76) that were self-reported. Adolescents answered items based on “since school started this year/during that past year, how often have you had trouble” in the selected items. Item statements included, “getting along with your teacher.” and “getting your homework done.” Responses include (0) no troubles in school to (4) everyday, ranging from 0-16.

Perceived hassle of birth control. In this scale, the perceived hassle of birth control was determined by using six items from Wave I (α = .83) that were self reported. Item statements included, “It takes too much planning ahead of time to have birth control on hand when you’re going to have sex.” and “Using birth control is morally wrong.” Responses ranged from (1) strongly disagree to (5) strongly agree, ranging from 6-30.

Dependent Variables-Wave IV
Depression. The construct of the depression measure consisted of nine items that in young adulthood were self-reported. Item statements included, “In the last 30 days, how often have you felt that difficulties were piling up so high that you could not overcome them?” and “(During the past seven days:) You enjoyed life.” Responses included (0) never or rarely to (3) most of the time or all the time, ranging from 0-28 (α = .81).

Anger and hostility. This scaled the amount of anger and hostility within the individuals’ life and was determined by using four items from Wave IV (α = .76) that were self reported. Item statements included, “I get angry easily.” Responses included (1) strongly disagree to (5) strongly agree, ranging from 4-20.

Violence involvement. The construct of Violence Involvement consisted of five items that were self-reported from Wave IV. Young adults stated “How often each of the following things happen,” Item statements included, “Someone pulled a knife or gun on you.” and “Someone slapped, hit, choked, or kicked you.” Responses were either (0) no or (1) yes, ranging from 0-16 (α = .94).

Risk of drinking. The final question in young adulthood examined drinking behaviors by asking “How often have you been under the influence of alcohol when you could have gotten yourself or others hurt, or put yourself or others at risk, including unprotected sex?” The responses in Wave IV were either (0) never, (1) one time, or (2) more than one time.

RESULTS

The initial data analysis began with the descriptive statistics of each of the scales (Table 1). This table included mean, standard deviation, range, skewness, kurtosis, and alpha value. The participants of this study had a gender distribution of 52% women. Ethnic distribution was 66% white, 25% African–American, 4% Asian, and 7% other (percentages may total less than a hundred due to subgroups not included). Within the Wave I and Deviance section the scales had relatively low means within their ranges. This is reflected in the skewness of the graphs. In Minor Juvenile Delinquency, Major Juvenile Delinquency, and Violence and Exposure, the means of the scales were low in relation to their respective ranges. The graph of the distributions of these questions all show a positive skewness, where the right tail is longer and the mass of the distribution is concentrated on the left of the figure. Wave I Psychosocial Functioning have a mean that is more centrally located within its respective ranges. The Wave IV variables followed the same sort of trend in Wave I with a positive skewness.

The next part of the analysis was the creation of a correlation table (Table 2). This table looked at each of the variables and how they relate to one another, positively or negatively. There is a unique clumping of high correlations between Wave I Minor Juvenile Delinquency, Major Juvenile Delinquency, Violence and Exposure, and Drug Use. The previously stated independent variables are highly positively correlated to each other. There is also a modest positive correlation with the Trouble in School scale and Minor Juvenile Delinquency, Major Juvenile Delinquency, Violence and Exposure, Drug Use, and Depression. Depression in adolescence and depression as a young adult also demonstrate a high positive correlation.

Three regression tables have been created in order to examine how three Wave IV variables, Violence Involvement (Table 3), Depression (Table 4) and Anger and Hostility (Table 5), can be predicted by using the independent variables from Wave I. Within my graph there are dummy variables, such as gender and ethnicity, which take the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.

Violence Involvement had no statistically significant results. This lack of results was due to the correlations being were very low compared to other Wave IV scales, such as Depression and Anger.

Controlling for gender and ethnicity for Depression (Table 4) the independent variables from Wave I with the largest coefficient size are Depression, Trouble in School, and Hassle of Birth Control. This is the size of the effect these variables have on Wave IV Depression. The indicated standard error is low showing that the regression coefficient has strong precision. Figure 1 shows the means for the scale Wave IV Depression compared with Wave I Depression and Trouble in School since those were statistically significant in Table 3. Figure 1 describes the relations of these variables. There is a greater amount of depression in young adulthood for both genders. Wave I Depression gender differences occur with higher female means in Wave I and Wave IV. However, there is also a steep drop off at the end. With men there is more of an increase in mean value of Trouble in School along with higher means in Wave IV Depression.

Controlling for gender and ethnicity for Anger (Table 5) the independent variables from Wave I with the largest coefficient size are Major Juvenile Deviance, Depression, and Trouble in School. The indicated standard error is low meaning that the regression coefficient has strong precision. Figure 2 shows the means for the scale Wave IV Anger and Hostility compared with Wave I Depression, and Trouble in School since those were statistically significant in Table 5. Figure 2 describes the relations of these variables, showing that males Wave IV Anger decreases as it relates to an increase in Wave I Depression while with women there is a steady increase. However, for both genders, as Trouble in School increases there is also an increase in Wave IV Anger. Both genders have a large dip with Wave IV Anger and then another large spike.

DISCUSSION

Society constantly attempts to extinguish deviant and delinquent behaviors for its own well-being. As adolescents become young adults, they have more social control placed on them by society’s expectations. In this context, “social control” is understood as the control over an individual’s behavior through public opinion, legal force, and social and religious organizations that operate with the interest of society as a whole coming first.

This study has found significant correlations between Wave I and Wave IV scales. The scales being used are considered to exemplify deviance in adolescents and young adults. In this study, the correlations and regression lines show how deviant behavior, such as depression and anger in adolescence, persist into young adulthood.

There is also an increase in the amount of self-control from adolescence to young adulthood. “Self-control” refers to individuals’ abilities to exercise restraint or control over their feelings, emotions, and reactions. Inconsideration for social control and a lack of self-control are measured in this study through minor and major juvenile delinquency, drug use, depression, violence and exposure, and trouble in school. In this study, mean values of the independent variables in young adulthood were lower than means in adolescence. The findings from this study imply that deviance decreases in young adulthood, consistent with the theory.

While there are expectations of more responsibility from young adults than youth, there is also a portion of youths who continue their deviant behavior, such as depression, violence, and anger. This continuation can be explained by the fact that an individual can gain status and esteem from certain social groups through deviant behavior. Delinquent participants with low self-control have a larger number of peers who consume drugs as well as weaker conventional bonds and moral beliefs Longshore et al., 2004. These factors contribute to substance use: involvement in an unconventional lifestyle, moral beliefs, religious commitment, and association with substance using peers Longshore et al., 2004. This positive reinforcement thereby encourages deviance into young adulthood. For adolescents for whom deviance does not persist, there is quality connection with positive models of societal expectation.

Minor and major delinquency was not significantly correlated with violence in young adulthood, demonstrating the discontinuation of deviant behavior over time. This may be due to the fact that the minor and major delinquency scales were measured by questions relating to legal crimes, such as theft and vandalism. The violence scale measured events such as witnessing and/or participating in violent acts like stabbing, shooting, and/or assault. Minor and major delinquency and violence in adolescence differed in the severity of the actions being included.

Regression results show that adolescent depression and trouble in school are positively related to depression and anger in young adulthood. When separated by gender, there is a stronger relationship with depression in adolescence and young adulthood for both males and females. However, trouble in school is less of a predictor for depression in males in early adulthood. Predictors of aggression in young adulthood, when separated by gender, show equally strong relationships with depression and trouble in school in adolescence. The main difference is that there is a steady increase in the relationship between the amount of depression in adolescent women and the amount of anger in young adulthood. This shows that individuals who did not feel the social control placed on them to perform well in school early in life were more likely to feel angry and depressed later in life. The findings from this study imply that deviance decreases in young adulthood, consistent with the theory.

This study shows a unique pattern of how the majority of deviant adolescents tend to grow out of such behavior. A future implication of this study is that society’s view of deviance during adolescence as a terminal sentence could be transformed. This would allow deviance to be seen as a growth process of youth. In conjunction with this study it would behoove society to find a way to discover ways to facilitate the growth process in individuals to whom the natural growth out of deviance does not occur.

LIMITATIONS

Considering that I was using secondary data, there were restraints on the type of survey questions that were asked of the participants. Some areas of interest that could have been included are financial responsibility and family responsibility, because alternate literature indicated them as explanations of deviant adult behavior. Since the data was representative of the national population, it would be unwise to generalize these conclusions to subpopulations where the national representation is not present, such as in urban cities. Since the secondary data was nationally representative, studying solely minority populations would have resulted in a low number of participants. While my results show a national trend, it would be interesting to compare the results to individuals who are repeat offenders or who have been career criminals since this population has more deviance. Also, since large amounts of data were available, it is possible that all the possible variables were not taken into account.

This study showed how depression and trouble in school as adolescents is positively related to depression and anger as a young adult. These patterns in deviant behavior can be further used through the application of self-regulation theories. Future studies could examine Add Health data regarding personality and self-regulatory behaviors of participants who had exhibited deviant trends.

This project originally proposed that minor and major delinquency as well as violence would predict deviant behavior in young adulthood. However, this study found that adolescent depression is a more important indicator of anger, violence, and depression in early adulthood.

Depression in adolescence should not be taken lightly because of the strong correlation between depression and violence in early adulthood. Depression in adolescence has grounds for further investigation.

REFERENCES

Benson, M. J., Faas, C. S., & Kaestle, C. E. (under review). Thirty adolescent measures: Reliability and validity data from a longitudinal study on contexts, assets, and risks. Manuscript under review.

Goffman, E. (1959). The Presentation of Self in Everyday Life. Garden City, N.Y.: Anchor Books.

Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Stanford, CA: Stanford University Press.

Gould, M. (2009). Culture, Personality, and Emotion in George Herbert Mead: A Critique of Empiricism in Cultural Sociology. Sociological Theory, 27, 435-448. DOI:10.1111/j.1467- 9558.2009.01357.x

Guest, A. M., & McRee, N. (2009). A school-level analysis of adolescent extracurricular activity, delinquency, and depression: The importance of situational context. Journal of Youth and Adolescence, 38, 51- 62. doi: [10.1007/s10964-008-9279-6](#http://link.springer.com/article/10.1007%2Fs10964-008-9279-6)

Harris, K. M., Halpern C.T., Whitsel E., Hussey J., Tabor J., Entzel P., and J.R. Udry. (2009). The National Longitudinal Study of Adolescent Health: Research Design [WWW document]. URL: [http:// www.cpc.unc.edu/projects/addhealth/design](http:// www.cpc.unc.edu/projects/addhealth/design)

Hirschi, T. (1969). Causes of delinquency. Berkeley: University of California Press.

Hoffman, J. P., & Dufur, M. J. (2008). Family and school capital effects on delinquency: Substitutes or complements? Sociological Perspectives, 51, 29-62 doi:[10.1525/sop.2008.51.1.29](#http://spx.sagepub.com/content/51/1/29)

Longshore, D., Chang, E., Hsieh, S., & Messina, N. (2004). Self-control and social bonds: A combined control perspective on deviance Crime & Deliquency, 50, 542-564. doi: 10.1177/001112870326068

Mack, K. Y., Leiber, M. J., Featherstone, R. A., & Monserud, M. A. (2007). Reassessing the family-delinquency association: Do family type, family processes, and economic factors make a difference?. Journal of Criminal Justice, 35, 51-67. doi: [10.1016/j.jcrimjus.2006.11.015](#http://www.sciencedirect.com/science/article/pii/S0047235206001437)

Mason, W., Hitch, J. E., & Spoth, R. L. (2009). Longitudinal relations among negative affect, substance use, and peer deviance during the transition from middle to late adolescence. Substance Use & Misuse, 44, 1142-1159. doi: [10.1080/10826080802495211](#http://www.tandfonline.com/doi/abs/10.1080/10826080802495211?journalCode=isum20#.VjD63rxVhBc)

McGloin, J., & Shermer, L. (2009). Self-Control and Deviant Peer Network Structure. Journal of Research in Crime & Delinquency, 46, 35-72. doi: 10.1177/002242780832658

Newman, G. R. (1975). A theory of deviance removal. British Journal of Sociology 26, 203-217.

Powell, D., Perreira, K. M., & Harris, K. (2010). Trajectories of delinquency from adolescence to adulthood. Youth & Society, 41, 475-502. doi: [10.1177/0044118X09338503](#http://yas.sagepub.com/content/41/4/475)

Rawls, A. (1989). Language, self, and social order: A reformulation of Goffman and Sacks. Human Studies, 12, 147-172.

Vazsonyi, A. T., & Huang, L. (2010). Where self-control comes from: On the development of self-control and its relationship to deviance over time. Developmental Psychology, 46, 245-257. doi: [10.1037/a0016538](#http://psycnet.apa.org/journals/dev/46/1/245)

TABLES & FIGURES

Variables M SD Min-Max Skewness Kurtosis α
Wave One and Deviance            
Minor juvenile delinquency 2.71 3.40 0-24 2.05 5.13 .78
Major juvenile delinquency 1.38 2.33 0-21 2.81 10.54 .73
Violence & Exposure 1.05 1.90 0-16 2.85 10.43 .75
Psychosocial Functional Deviance            
Drug use 1.37 1.14 0-3 0.13 -1.39 .69
Depression 12.56 3.90 9-33 1.71 3.53 .84
Trouble In School 4.16 2.92 0-16 0.96 0.98 .69
Perceived hassle of birth control 12.35 4.89 6-30 0.77 0.56 .83
Wave Four and Deviance            
Depression 5.89 4.34 0-28 1.25 2.05 .81
Angry & Hostility 10.21 2.90 4-20 .44 .03 .76
Violence & Exposure 0.72 1.57 0-5 2.10 2.83 .94
Drinking put yourself at risk 1.08 0.92 0-2 -0.16 -1.81 -

Table 1: Descriptive Statistics (N=6,504)

Correlations: (N=6,504)   *p < .01. **p < .001.
Variables 1 2 3 4 5 6 7 8 9 10 11
   Wave I  
1. Minor juvenile delin. -  
2. Major juvenile delin. .55** -  
3. Violence & Exposure .37** .68** -  
4. Drug use .41** .32** .26** -  
5. Depression .20** .19** .16** .22** -  
6. Trouble In School .36** .33** .28** .29** .29** -  
7. Hassle of birth control .09** .17** .13** -.01** .10** .13** -  
   Wave IV  
8. Depression .10** .13** .11** .08** .30** .17** .10** -  
9. Angry & Hostility .09** .12** .09** .10** .17** .13** .06 .39** -  
10. Violence & Exposure .03 .04* .04** .02 .04* .04* .02 .07** .05** -  
11. Risk of Drinking .18** .08** .29** .11** .03** .13** -.00** .11** .04** -.00** -

Table 2

* p ** p<.001.> a White ethnicity is the reference group
Dependent Variable Anger
Variable B SE B B
Gender (Ref: Male) -.05 .03 -.03
African Americana -.12 .07 -.07
Asiana -.06 .09 .01
Other Ethnicitya -.04 .08 .01
Minor JD .00 .01 .00
Minor JD -.01 .02 -.01
Violence .05 .02 .06
Drug Use .01 .02 .01
Depression .01 .01 .12
Trouble in School .01 .01 .01
Hassle of birth control .01 .01 .01

Table 3: Linear Regression of Adolescent Variables on Violence Interaction in Young Adulthood (n=6,504)

* p ** p<.001.> a White ethnicity is the reference group
Dependent Variable Depression
Variable B SE B B
Gender (Ref: Male) -.34 .07 -.08**
African Americana -.37 .07 .08**
Asiana -.09 .18 -.01
Other Ethnicitya -.09 .14 -.01
Minor JD -.01 .02 -.01
Minor JD .07 .04 .04
Violence .05 .04 .02
Drug Use -.04 .06 -.01
Depression .32 .02 .30**
Trouble in School .01 .03 .07**
Hassle of birth control .05 .01 .06**

Table 4: Linear Regression of Adolescent Variables on Depression in Young Adulthood (N=6,504)

* p ** p<.001.> a White ethnicity is the reference group
Dependent Variable Depression
Variable B SE B B
Gender (Ref: Male) -.34 .07 -.08**
African Americana -.37 .07 .08**
Asiana -.09 .18 -.01
Other Ethnicitya -.09 .14 -.01
Minor JD -.01 .02 -.01
Minor JD .07 .04 .04
Violence .05 .04 .02
Drug Use -.04 .06 -.01
Depression .32 .02 .30**
Trouble in School .01 .03 .07**
Hassle of birth control .05 .01 .06**

Table 5: Linear Regression of Adolescent Variables on Anger & Hostility in Young Adulthood (N=6,504)

Figure 1: Wave IV Depression vs. Wave I Depression & Trouble in School (N=6,504)

Figure 1: Wave IV Depression vs. Wave I Depression & Trouble in School (N=6,504)

Figure 2: Wave IV Anger vs. Wave I Depression & Trouble in School (N=6,504)

Figure 2: Wave IV Anger vs. Wave I Depression & Trouble in School (N=6,504)


Amanda Griffin is a Senior from Alexandria, Virginia majoring in Psychology with a minor in International Studies. She would like to thank her advisor Dr. Mark Benson, Human Development, for his assistance on this article. After graduation Amanda seeks to attend graduate school for Social Work and Human Development.

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from twenty-three other federal agencies and foundations. Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website http://www.cpc.unc.edu/addhealth. No direct support was received from grant P01-HD31921 for this analysis.