Parents, Peers, and Juvenile Delinquency By Jed Feeny SOC 429 December 7, 2011
Feeny 1
Parents, Peers, and Juvenile Delinquency
Abstract By utilizing the 1980 National Youth Survey, I analyze the relationship between the attachment with parents and juvenile delinquency. Following Hirschi’s social control theory, I treat parents as barriers to delinquency and anticipate that adolescents who are strongly influenced by their parents commit fewer criminal offenses. My hypotheses for examining this association between parental attachment and delinquency are the following: (1) adolescents who are strongly influenced by their parents are less likely to commit delinquent acts and (2) adolescents are less likely to commit delinquent acts if their parents strongly disapprove of such behaviors. In addition to this relationship, I examine the association between peer influence and juvenile delinquency. In accordance with Sutherland’s differential association theory, I treat peers (friends) as instigators to delinquency and expect that adolescents who are strongly influenced by their peers are more likely to commit criminal offenses. My hypotheses for this peer attachment are the following: (1) adolescents who are strongly influenced by their peers are more likely to commit delinquent acts and (2) adolescents are more likely to commit delinquent acts if their peers strongly approve of such behaviors. The findings suggest that an increase in parental attachment and disapproval, as well as an increase in peer disapproval contribute to lower levels of marijuana use. Higher levels of peer disapproval result in lower frequencies of major theft. An increase in peer disapproval and an increase in parental attachment correlate with lower levels of violence. However, the findings also show that peer influence is positively correlated with higher levels of violence. Social control theory was substantiated when examining the relationship between parental attachment and marijuana use, as well as parental attachment and violence. Differential association theory was only supported by the relationship between peer attachment and violence. Feeny 2
Introduction Adolescents, especially males, are prone to delinquent behavior in their mid to late teens. This is a common occurrence that has been observed at different points of history and in different parts of the world. It is an important issue to address because young adults may acquire criminal records that will prevent them from being hired for certain jobs. The findings of this research can help parents determine more effective ways wa ys in minimizing the delinquency of their children. The purpose of this study is to determine if there is an association between the strength of parents’ influence and the frequency of delinquent behavior by their children. With regards to the
parent-child relationship, the research will also examine the association between the frequency of delinquent behavior committed by juveniles and the approval/disapproval of their parents toward such actions. According to Hirschi’s social control theory, parents act as a barrier against the deviant influences of peers. A main tenant of this theory is that parental attachment and delinquency are inversely related. Parental attachment refers to the social ties adolescents form with their parents. A positive parent-child attachment means that the child is less likely to engage in delinquent acts in order to preserve the relationship (Rankin and Kern 1994). A weak parentchild attachment increases the likelihood that the adolescent will commit criminal offenses because he or she is less sensitive to his or her parents’ opinions (Rankin and Kern 1994). Assuming that a child has a strong attachment to their parents and that their parents strongly disapprove of delinquent behavior, the child is less likely to commit such behavior. Parents exhibit an almost universal disapproval of delinquent behavior. Another purpose of this study is to determine if there is an association between the strength of peer influence and the frequency of delinquent offending by juveniles. The research will also analyze the relationship between the amount of delinquent behavior committed by juveniles and the approval/disapproval of their peers (friends) towards that behavior. According Feeny 3
to Sutherland’s differential association theory, peers act as instigators of delinquency. A major
tenant of this theory is that criminal c riminal behavior is learned through social interaction with others. On theoretical grounds, it is sensible to believe that increased interaction with potential instigators of deviance is likely to result in more juvenile delinquency.
Literature Review Two major influential figures, Hirschi and Sutherland, have emerged in the field of research on juvenile delinquency. Hirschi’s (1969) social control theor y emphasizes the
influence of parents and family in reducing delinquency. He attributes delinquent behavior to inadequate external constraints on adolescents. Parents serve as barriers to delinquency, while peers are thought of as instigators (Warr 1993). Sutherlands’ (1947) differential association
theory states that criminal behavior is learned learn ed through interaction with delinquent peers. Like Hirschi, he regards peers as instigators of delinquency. Differential association theory also speculates that deviant behavior is a consequence of attitudes that favor the violation of the law (Warr and Stafford 1991). Based on these two theories, it can be said that strong parental influence negatively correlates with juvenile delinquency. According to Warr (1993), children who spend more time with their parents are less likely to commit delinquent behavior. By spending more time with parents, children have less time to spend with deviant peers. Warr’s (1993) findings suggest that peer influence can be
reduced and even prevented p revented if adolescents spend the majority of their time with their family. Hirschi writes that children who spend most of their time with their parents are “less likely to get into situations in which delinquent acts are possible (2002: 88).” Family transitions from single parent households to two-parent households may result in reduced family time and lead to higher rates of delinquency (Schroeder et al. 2010). Feeny 4
Another result of increased time between parents and children is that it strengthens the parental attachment between the two parties (Warr 1993). The research suggests that parental attachment and delinquent peers are negatively correlated (Liu 2003, Rankin and Kern 1994, Schroeder et al. 2010, Warr 1993). Children who have strong attachments to their parents are less likely to form friendships with delinquent peers (Warr 1993). Consequently, these children have a lower chance of engaging in delinquency. Children who live in non-intact, or broken, homes have weaker parental attachment and are more likely to commit criminal offenses (Schroeder et al. 2010). According to Warr (1993), children with strong parental attachments are more likely likel y to internalize their parents’ moral inhibitions, which serve as an obstacle to p eer influence. Hirschi (1969) argues that parents may be “psychologically “ps ychologically present” even when adolescents are in the
company of delinquent peers. Schroeder et al. (2010) finds that strong attachment between children and parents prior to a family transition can diminish levels of delinquency. These researchers also conclude that family formation is detrimental to adolescents who have weak parental attachment prior to the transition. Families that transition from single-parent to twoparent households may experience shifts in parental attachment, which result in increased levels of deviance (Schroeder et al. 2010). Rankin and Kern’s (1994) results are inconsistent with Hirschi’s (1969) hypothesis. Hirschi states that there should be no correlation between single -
parent homes and delinquency as long as the child is strongly attached to the custodial parent, but Rankin and Kern (1994) found that single-parent homes and delinquency are positively related, regardless of the relationship with the custodial parent. Adolescents who are strongly attached to their parents are somewhat less likely to use drugs than adolescents who have weak attachments (Bahr et al. 2005). Contrary to most research, Warr’s (1993) findings suggest that
the attachment to parents has no direct effect on delinquency. Parental attachment is also ineffective at counterbalancing the influence of delinquent friends. He concludes that parental Feeny 5
attachment indirectly affects delinquency by affecting the kinds of friends that adolescents have. A strong parental attachment inhibits the formation of delinquent friendships from occurring in the first place (Warr 1993). Research shows that children from non-intact homes exhibit higher rates of delinquency than children from intact homes (Schroeder et al. 2010). Children in blended households (cohabitating families or step-families) also show higher rates o f delinquency than children in intact or single-parent homes (Schroeder et al. 2010). According to Schroeder et al. (2010), adolescents who lived in a two-parent household in the first wave of the NYS show lower levels of delinquency than those who lived in single-parent homes during the same wave. Adolescents who experienced a family formation between the first and third waves of the NYS display a significant increase in delinquency (Schroeder et al. 2010). Family dissolution does not necessarily result in criminal offending by adolescents (Schroeder et al. 2010). The transition from a single-parent family to a blended or cohabitation household has been strongly correlated with delinquent offending (Schroeder et al. 2010). Rankin and Kern (1994) contend that the number of parental attachments is the most significant factor for delinquency. Their research suggests that a strong attachment to both parents is more likely to result in less delinquency than a strong attachment to only one parent (Rankin and Kern 1994). However, strong attachment to a second parent does not necessarily divide the likelihood of committing offenses in half (Rankin and Kern 1994). Single parent homes are associated with delinquent behavior because there is only one parental attachment (Rankin and Kern 1994). Many researchers find a significant relationship between weak parental supervision and high delinquency (Fischer 1983). Children in non-intact homes are more likely to commit delinquent acts, partly due to less parental supervision (Schroeder et. al 2010). Glueck and Glueck (1970) find that maternal supervision is a significant factor in juvenile delinquency. delinquenc y. Feeny 6
Stanfield (1966) finds that poor paternal supervision is associated with high delinquency when peer activity is high. However, consistent discipline and supervision by the father is correlated with low delinquency regardless of peer group activity. In Wilson’s (1980) study of low
socioeconomic families in Britain, he finds that relaxed supervision is significantly associated with increased delinquency. Wilson (1980) also finds that the delinquency rate in families where parental supervision is weak is over seven times that of families in which there is strict supervision. According to Hirschi (1969), children are less likely to commit delinquent activities if they believe that their parents are aware of their actions. In Jensen’s (1972) study of 1588 high hi gh
school males in California, he finds a significant negative relationship between parental supervision and self-reported delinquency. West and Farrington (1973) find that poorly supervised boys are more likely to become delinquent than “average” supervised boys.
According to Aseltine (1995), parental supervision is weakly related to delinquency and marijuana use. His research provides little support for control theories of deviance and he goes so far as to say that constraints are not influential. Parental monitoring has a strong inverse relationship for marijuana and illicit drugs use, but a weaker inverse relationship with cigarette use (Bahr et al. 2005). Adolescents that are closely monitored by parents are less likely to have friends who use drugs (Bahr et al. 2005). In general, parental supervision weakens as adolescents mature (Liu 2003). Adolescents may intentionally seek to acquire non-delinquent friends in order to avoid parental disapproval (Warr 1993). Liu (2003) suggests that the loss of parental approval may be enough to deter delinquency even under intense peer pressure. The anticipated disapproval of parents decreases the influence of delinquent peers (Liu 2003). Despite the fact that parents’ influence weakens as children mature, parents are still able to dissuade children from committing illegal behavior. Parental disapproval is more powerful pow erful than disapproval from coworkers (Liu Feeny 7
2003). Adolescents who have parents that are more tolerant of drug use are more likely to have friends who use drugs (Bahr et al. 2005). In contrast to these findings, though, according to Zhang and Zhang (2004), parental disapproval is not significantly related to juvenile delinquency when conducting multivariate analyses. One of the most consistent findings of delinquency research is that the more delinquent friends an adolescent has, the more likely he or she is to commit delinquent acts (Akers et al. S utherland’s differential association theory contends that 1979, Elliott et al. 1985, Jensen 1972). Sutherland’s
peer influence is a major causal factor on juvenile delinquency. Deviant behavior is a consequence of attitudes that favor the violation of the law. These attitudes are acquired through the close social interaction with peers pe ers (Warr and Stafford 1991). Research by b y Warr and Stafford (1991) suggest that while it is true that peers’ attitudes affect delinquenc y, peers’ behavior are much more influential. When peers’ behavior and attitudes are inconsistent, the behavior appears
to override the attitudes of peers. According to Warr and Stafford (1991), delinquency delinquenc y is not so much the result of acquired attitudes from peers as it is the consequence of imitation and group p eers have a strong influence on adolescents’ pressures to conform. Bahr et al. (2005) verify that peers
decisions to use drugs. According to Warr (1993), most adolescents will have at least some delinquent friends by the time they reach their mid-teens. He suspects that the immediate pressure of peer influence is so powerful that adolescents can only overcome it by avoiding delinquent peers entirely. Aseltine’s (1995) research suggests that friends are the primary source of influence on youths’ behavior. The variable that has the strongest correlation with delinquency
is the number of friends that a youth has. According to Braithwaite (1989:87), shaming by significant others should be “more potent than shaming by an impersonal state.” Most people are more concer ned ned about the regard
in which they are held by their peers rather than those working in the criminal justice system. Feeny 8
There are different ways in which delinquency delinquenc y disapproval is conceptualized. Sutherland’s
differential association theory conceptualizes delinquency disapproval as attitudes from peers and parents (Warr and Stafford 1991). According to Warr and Stafford (1991), peer delinquency disapproval is significantly and negatively related to juvenile delinquency. Akers et al. (1979) find that positive reinforcement of delinquent behavior beha vior from peers contributes to drug and alcohol use. Krohn et al. (1985) find that positive reinforcement from peers is s ignificantly associated with adolescent smoking. Heimer and Matsueda (1994) predict that adolescent perceptions of disapproval from parents and peers will significantly reduce their delinquency. However, they find that only perceptions of parental disapproval have a significant effect on delinquency. Their results show that perceptions of peer disapproval are not significantly related to delinquency (Heimer and Matsueda 1994). Zhang and Zhang (2004) find that peer disapproval is negatively correlated with criminal offending. Wright and Younts (2009) analyze the relationship between race and crime by using data from several waves of the National Youth Survey. They find that single-parent families, lowered education attainment, and crime-ridden neighborhoods increase criminal offending of African Americans relative to White respondents. However, these researchers also find that increased religiosity, strong family ties, and lowered alcohol use are associated with low criminal offending by African Americans. For this study, stud y, I will use race as a control variable. I will determine if there is an association between race and juvenile delinquency. According to Warr (2006), the effects of age on self-reported delinquency are largely insignificant when peer influence is controlled. He does find that once delinquent friends are ea rly friends, acquired, they are not quickly lost. Warr’s main finding is that recent, rather than early
have the greatest effect on delinquency. Hirschi and Gottfredson contend that the age distribution of crime cannot accurately be measured by any variables in criminology (Warr 2006:35). Feeny 9
However, Farrington (1986) and Steffensmeier et al. (1989) find that most self-reported criminal offenses tend to peak in the middle-to-late teens and decline shortly after. With regards to marijuana use, Warr (2006) finds that at age 11, 95% of respondents report that none of their friends have smoked marijuana. At age 16, that number decreases to 40%. At age 18, only 25% of respondents report that none of their friends have smoked marijuana. The decline from each age group is about 10% per year (Warr 2006). For this study, age will be used as a control variable. I will examine the relationship between age a ge and several criminal offenses. According to Mears, Ploeger, and Warr (1998), males are significantly more likely than females to have delinquent friends. Males also appear to be more strongly influenced by delinquent peers than females. This research suggests that the moral judgments of females are apparently sufficient enough to reduce and even entirely negate the impact of delinquent peers. Although males are more affected than females, both are influenced by delinquent friends to some degree (Mears, Ploeger, and Warr 1998). Giordano’s Gio rdano’s (1978) research suggests that for
some females, delinquency is a consequence of exposure to delinquent males. She finds that girls who spend time in mixed-sex groups are more likely to engage in delinquency than those who participate in same-sex groups. Warr (1996) finds that females are more likely than males to report that the instigator of their delinquent group is of the opposite sex. For this study sex will be a control variable. I will look to determine if an association exists between one’s sex and their
level of juvenile delinquency.
Hypotheses For my research, I will explore the nature of the relationship between the strength of parental influence and juvenile delinquency. I will also determine if there is an association between parental approval/disapproval and juvenile delinquency. As a control variable, I will Feeny 10
analyze the relationship between the strength of peer influence and juvenile delinquency. Additionally, I will examine the association between peer approval/disapproval and juvenile delinquency. Based on the literature review, I have constructed four hypotheses for associations that I expect to see. In exploring the nature between juvenile delinquency and parental influence/attachment, I hypothesize: (1) adolescents who are strongly influenced by their parents are less likely to commit delinquent acts and (2) adolescents are less likely to commit delinquent acts if their parents strongly disapprove of such behaviors. In exploring the nature between juvenile delinquency and peer influence/attachment, I predict (1) adolescents who are strongly influenced by their peers are more likely to commit delinquent acts and (2) adolescents are more likely to commit delinquent acts if their peers strongly approve of such behaviors. My other control variables include sex, age, and race. Based on the literature, I expect to find that males commit more delinquency that females. The literature suggests that adolescents commit more delinquent acts in their middle-to-late teen years followed by a substantial decline when they reach their early twenties. In accordance with the literature, I predict that race will be related juvenile delinquency.
Data and Measures This research utilizes data from the 1980 National Youth Survey (Wave V), a longitudinal study of self-reported delinquent and criminal behavior in the United States. The NYS is a five-year study of a national probability sample. For this wave, youth were interviewed in 1981 about events that occurred in the calendar year of 1980. The sample consists of 1,725 respondents, of which 918 were male and 807 female. The respondent’s ages ranged from 15 to
21. The unit of analysis for this study was individuals. The NYS was collected through the interviews of approximately 1,700 youths from more than 100 communities around the country. Feeny 11
Self-reported surveys are an unofficial source of crime data that provide criminologists with a method for collecting data without having to depend on government resources. In these types of surveys, criminologists ask respondents about their own criminal behavior during a specific time period. In the case of the NYS, respondents report on their criminality in the last year. Self-report surveys usually focus on youths because their information is more readily available through records from schools, detention courts, and correctional facilities. Youths are also far more likely than adults to report their own illegal behaviors. While self-report surveys provide valuable information, they are not witho ut problems. The data in these types of surveys is not always reliable. Some respondents may lie about their illegal acts and criminal involvement because they are reluctant to confess these offenses to strangers. Many people may ma y also forget, misunderstand, or misidentify their participation in criminal behaviors. Self-report surveys often do not take into account the most active and serious criminal offenders. Many of the surveys utilize college student populations where only a small number of serious crimes actually occur. Incarcerated youths are usually more delinquent than even the most serious offenders found in self-reported surveys. These flaws have inspired some criminologists to develop methods to validate the findings from self-report surveys. Checks for reliability and validity hav e led some researchers to conclude that self-report surveys do not have insurmountable concerns and can still provide criminologists with a variety of data for making generalizations about the nature and extent of crime in the United States. Self-report surveys often find a prevalence of less serious crimes being committed by respondents. These would include stealing small sums of money and using alcohol. Self-report surveys provide researchers with less obvious information for populations within the United States and have added to our awareness of the real extent of crime. SelfFeeny 12
reported research also provides clear evidence of race, ethnic, and gender bias in the processing of suspects. Self-reported studies provide reasonable estimates of less serious crimes, particularly for drug offenses. The NYS extensively asks youths about their use of specific types of drugs. These drugs vary from less serious types, such as marijuana, to hard drugs, including cocaine and heroin. Self-reports of criminal activity are able to quantify the actual amount of crime that people commit. However, the accuracy may be limited because people may be dishonest, forgetful, or have trouble understanding the questions. It is also unlikely that people who commit serious crimes, such as rape and murder, would voluntarily vo luntarily tell others about their criminal acts for fear of being arrested. Ultimately, only the offender o ffender can tell the exact number of offenses he or she has committed regardless of what his or her criminal records show. According to Hirschi’s social control theory, adolescents are less likely to commit
deviance if they have strong ties to their parents (Warr 1993). I operationalize parental attachment by using variable 122, Y-5 118. This variable asks “How much have your parents influenced what you’ve thought and done?” Respondents select an answer on a Likert scale
ranging from 1-Very little to 5-A great deal. I also operationalize the reaction of parents to specific delinquent acts, including marijuana use, use , committing theft of something worth more than $50, and hitting someone. Variable 275, Y5-271 asks “How would your parents react if you used marijuana or hashish?” Variable 276, Y5 -272 asks “How would your parents react if you stole something worth more than $50?” Variable 277, Y5-273 asks “How would your parents react if you hit or threatened to hit someone without any reason?” For variables va riables that asked respondents for their parents’ reactions, answers range on a Likert scale from 1-Strongly
Approve to 5-Strongly Disapprove. These independent variables were used to operational the concept, parental attachment. Feeny 13
Frequency of marijuana use is log transformed as “MarijuanaUseLN”. It is constructed using variable 571, Y5-568. For this variable the questionnaire asks “How many times in the last year have you used marijuana ma rijuana or hashish?” Respondents answer by providing the best estimate of
the exact number of times they used marijuana or hashish from Christmas of 1979 to Christmas of 1980. The frequency of theft of something greater than $50 is log transformed as “MajorTheftLN.” It utilizes variable 448, Y5-444. For this variable, the questionnaire asks “How
many times in the last year have you stolen or tried to steal something worth more than $50?” Respondents answer on an interval scale that ranges from 0 to 20. The frequency of committing violence is recoded as “ViolenceLN.” It includes variables 466, 472, 488, 490, and 492 which
were combined into an additive index. Variable 466 asks for the frequency of attacking someone “with the idea of seriously hurting or killing him or her.” Variable 472 asks for the frequency frequenc y of the respondents’ participation in gang fights. Variable 488 asks for the frequency in which the respondent “hit or threatened to hit a teacher or other adult at school.” Variable 490 asks the
respondent for the number of times in the last year that they hit or threatened to hit one of their parents. Variable 492 asks for the frequency in which the respondent “hit or threatened to hit other students.” According to Sutherland’s (1974) differential association theory, friends are potential
instigators to delinquency. Adolescents learn to commit delinquent behavior by socially interacting with peers. Theoretically, youth who have strong attachments to peers are more likely to commit delinquency. To measure the attachment to peers, I include several control variables of peer influence. Variable 35, Y5-35 asks respondents “How much have your friends influenced what you’ve thought and done?” The answers range on a Likert scale from 1-Very Little to 5-A
Great Deal. Three other variables measure the reactions of close friends if the respondent commits specific delinquent acts. As is the case for the parental reactions, these variables Feeny 14
measure the reaction of friends if the respondent used marijuana, stole something worth more than $50, or committed a violent act. The answers for these three variables range on a Likert scale from 1-Very Little to 5-A Great Deal. Variable Variab le 284, Y5-280 asks respondents “How would your close friends react if you used marijuana or hashish?” Variable 285, Y5-281 asks
respondents how their close friends would react if they stole something worth more than $50. Variable 286, Y5-282 asks respondents “How would your close friends react if you hit or threatened to hit someone without any reason?”
For my research I log transformed three dependent variables. These variables include the logged frequency of marijuana use, the logged frequency of theft of something greater than $50, and the logged frequency of committing violence. All of these dependent variables were log transformed to meet the ordinary least squares assumption that the dependent variable is normally distributed. This was achieved by adding a constant of 0.5 to the raw values and then transforming with the natural log My other control variables include sex, age, and race. Based on the literature, males are more likely than females to commit delinquency and engage in violent behavior (Mears, Ploeger, and Warr 1998). For my research, sex is coded as 1-Males and 2-Females. Farrington (1986) and Steffensmeier et al. (1989) find that most self-reported s elf-reported criminal offenses tend to peak in the middle-to-late teens and decline shortly after. Age is an interval level measure and ranges from 15-21. According to Wright and Younts (2009), African Americans and inner-city youths are more likely to commit delinquent acts relative to Whites. The race measure, African American, was coded as 0-Non-African 0 -Non-African American and 1-African American. With regard to our delinquent behavior of interest, on average these respondents used marijuana nearly 31 and a half times in the last year, stole something worth over $50 about one tenth of one time, and hit someone or was involved in a gang fight one and a half times. The Feeny 15
average age of the respondents in this sample was about 18. The respondents’ ages ranged from 15 to 21. The sample was approximately 53% male and 47% female. Of the 1,725 respondents for which data are available, 1,361 1,36 1 were “Anglo.” The sample was an accurate reflection of the
proportions of ethnic groups in the United States. The average influence of parents on the youth in this sample was 4.01 on a scale from 1 to 5, with 1 being “Very little” and 5 being “A great deal.” On the same scale, the average influence of friends on the youth in this sample was 3.16, significantly lower than the influence of parents. On average, respondents indicated that their parents were generally more influential than their friends. The average reactions of parents and friends to potential delinquent acts that the youth might commit range from 1 to 5, with one being “Strongly approve” and 5 being “Strongly disapprove.” For marijuana use, major theft, and violence, respondents indicated on average that
their parents would more strongly disapprove of their delinquent behaviors than their peers. The largest gap between parent and friend disapproval occurred with regards to marijuana use. For this behavior, the mean reaction of parents was 4.50, compared to only 3.61 for friends. To test my hypothesis, I use Ordinary Least Squares (OLS) multiple regression. This statistical technique measures the association between the independent and dependent variables. This type of analysis is appropriate for my research because I am using interval level dependent variables.
Results The first model analyzed the dependent variable “MarijuanaUseLN.” The adjusted R square shows the amount of variance in the dependent variable that is explained by the independent variables. Here the adjusted R square for MarijuanaUseLN is .449 – that is, “44.9% Feeny 16
of the logged marijuana use is explained by the variables: parents’ reaction to marijuana use, peers’ reaction to marijuana use, parents’ general influence, peers’ general influence, sex, age, and African American.”
Table 2 displays the coefficients estimated from the OLS analyses of these models and reveals the relationship and statistical significance between the dependent variables and the independent variables. This table shows us that the unstandardized coefficient B for parents’
reaction to marijuana use (Y5-271) is -.649 and is statistically significant with a p value < .05. The parents’ reaction to marijuana use is negatively and statistically significantly related to the
logged marijuana frequency as hypothesized. With a one unit increase in parents’ disapproval, the logged marijuana frequency decreases by .649. As parental disapproval of marijuana use increases, the frequency of marijuana use by respondents decreases. The unstandardized coefficient B for peers’ reaction to marijuana use (Y5-280) is -1.039
and also statistically significant. The peers’ reaction to marijuana use is negatively and statistically significantly related to the logged marijuana frequenc y. With a one unit increase in peers’ disapproval, the logged marijuana frequency decreases by 1.039. As peer disapproval of
marijuana use increases, the frequency of marijuana use by the respondent decreases. The unstandardized coefficient B for parents’ general influence on respondents (Y5-118)
is -.177 – again, statistically significant in the hypothesized direction. The parents’ general influence in 1980 is negatively ne gatively and statistically significantly related to the logged marijuana frequency. With a one unit un it increase in parents’ general influence, the logged marijuana frequency decreases by .177. As parents’ general influence over the respondent increases, the
frequency of marijuana use by the respondent decreases. The unstandardized coefficient B for sex of respondents is -.234, which is negatively and statistically significantly related to the logged marijuana frequency. With a one unit increase in Feeny 17
sex of respondents, the logged marijuana frequency decreases by .234. Males are more likely to use marijuana than females. The unstandardized coefficient B for African Americans (AA) is -.309. The dummy measure for African Americans is negatively and statistically significantly related to the logged marijuana frequency. African Americans are less likely to report using marijuana than nonAfrican Americans. The standardized coefficient Beta explains which independent variable accounts for the va riable. For marijuana use, peers’ reaction to marijuana use greatest variance of the dependent variable.
has the largest absolute value Beta at -.518. Parents’ reaction to marijuana use was -.199. Therefore, in 1980, peers’ reaction to marijuana use is a stronger predictor o f marijuana use by respondents than parents’ reaction to marijuana use.
The second model analyzed the dependent variable “MajorTheftLN” (grand larceny). Here the adjusted R square for MajorTheftLN is .096 – meaning “9.6% of logged grand larceny larcen y, is explained by the variables: parents’ reaction to grand larceny, peers’ reaction to grand larceny, parents’ general influence, peers’ general influence, sex, age, and African American.”
Table 3 displays the coefficients estimated from the OLS analyses of these models. This table shows us that the unstandardized coefficient B for p eers’ reaction to grand larceny (Y5-
281) is -.136 and is statistically significant with a p value < .05. The peers’ r eaction eaction to grand larceny is negatively and statistically significantly related to the logged major theft frequenc y as pe ers’ disapproval, the logged major theft frequency hypothesized. With a one unit increase in peers’
decreases by .136. As peer disapproval of major theft increases, the frequency of major theft by respondents decreases. Consequently, as peer approval of major theft increases, the frequency of major theft by respondents increases.
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The unstandardized coefficient B for age of respondents is -.008 and is also statistically significant at the .1 level. The age of respondents is negatively and statistically significantly related to the logged major theft frequency. With a one year increase in age, the logged major theft frequency decreases by .008. As age increases, the frequency of major theft by respondents decreases. For major theft, peers’ reaction to major theft has the largest absolute value Beta at -.322. Parents’ reaction to major theft was not statistically significant . Therefore, in 1980, peers’
reaction to major theft was a stronger s tronger predictor of major theft frequency than any an y other independent variable used in the model. The third model analyzed the dependent variable “ViolenceLN.” Here the adjusted R square for ViolenceLN is .178 – that is, “17.8% of the logged violence is explained by the variables: parents’ reaction to violence, peers’ reaction to violence, parents’ general influence, peers’ general influence, sex, age, and African American.”
Table 4 displays the coefficients estimated from the OLS analyses of these models. This table shows us that the unstandardized coefficient B for p eers’ reaction to violence (Y5-282) is -
.376 and is statistically significant with a p value < .05. The peers’ reaction to violence is negatively and statistically significantly related to the logged violence frequency as hypothesized. With a one unit increase in peers’ disapproval, the logged violence frequency decreases by .376. As peer disapproval of violence increases, the frequency of violence by respondents decreases. By the same token, as peer approval of violence increases, the frequency of violence by respondents increases. The unstandardized coefficient B for parents’ gener al al influence (Y5-118) is -.044 and is
also statistically significant at the .1 level. The parents’ general influence is negatively and statistically significantly related to the logged violence frequency as hypothesized. With a one Feeny 19
unit increase in parent’s general influence, the lo gged violence frequency decreases by .044. As parents’ general influence increases, the frequency of violence committed by respondents
decreases. The unstandardized coefficient B for peers’ general influence (Y5 -35) is .048 and also
statistically significant. The peers’ general influence is positively and statistically significantly related to the logged violence frequency as hypothesized by differential association theory. With a one unit increase in peers’ pe ers’ general influence, the logged violence frequency increases by .048. As peers’ general influence increases, the frequency of violence committed by respondents
increases. The unstandardized coefficient B for sex of respondents is -.297. This is negatively and statistically significantly related to the logged violence frequency. With a one unit increase in sex of respondent, the logged violence frequency decreases by .297. Males are more likely to commit violence than females. The unstandardized coefficient B for age of respondents is -.070 and also statistically significant. The age of respondents is negatively and statistically significantly related to the logged violence frequency. With a one unit increase in age, the logged violence frequency decreases by .070. As age increases, the frequency of violence by respondents decreases. For violence, peers’ reaction to violence has the largest absolute value Beta at -.303. Parents’ reaction to violence was not statistically significant. Therefore, in 1980, peers’ reaction
to violence is a stronger predictor of violence by respondents than any other independent variable used in this model.
Conclusion
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This study sets out to compare the relationship of parental attachment and influence on juvenile delinquency relative to other variables. My research utilizes both social control and differential association theory to see which has greater support based on this sample. The findings show more support for differential association th eory than social control theory. I find that peer influence and attachment is a stronger predictor of juvenile delinquency than parental influence and attachment. These results support social control theory and substantiate the belief that stronger parental attachment and influence are correlated with lower levels of delinquency. Table 2 shows that both parental influence and parental disapproval are negatively correlated with marijuana use. Table 4 shows that the relationship between violence and parental disapproval is negative as well. I find that higher peer disapproval is correlated with lower levels of juvenile delinquency. delinquenc y. Table 2 shows that as peer disapproval increases, marijuana use decreases. According to Table 3, an increase in peer disapproval is also correlated with lower levels of major theft. Table 4 shows that stronger peer disapproval is correlated with lower levels of violence. However, Table 4 also shows that as peer influence increases, violence increases. This was the only finding that supported differential association theory. These findings expand on our knowledge and understanding of the relationship between parents, peers, and juvenile delinquency. This study confirms that stronger parental influence and attachment are associated with lower levels of juvenile delinquency. However, the relationship between peer influence and delinquency is less straightforward. Although parents may be wary of the individuals that their adolescents spend time with, adolescents are less likely to commit delinquent acts if their peers strongly disapprove of such behaviors. Parents may want to examine the influence of peers on their children if they are prone to violent behavior. Feeny 21
References Akers et al. 1979. “Social Learning and Deviant Behavior: A Specific Test of a General Theory.” American Sociological Review. 44(4):636-655. Aseltine, Robert. 1995. “A Reconsideration of Parental and Peer Influences on Adolescent Deviance.” Journal of Health and Social Behavior . 36(2):103-121. Bahr, Stephen J., John P. Hoffman, and Xiaoyan Yang. 2005. “Parental and Peer Influences on the Risk of Adolescent Drug Use.” The Journal of Primary Prevention. 26(6):529-551. Braithwaite, John. 1989. Crime, Shame and Reintegration. New York, NY: Cambridge University Press. Elliott et al. 1985. Explaining delinquency and drug us. Beverly Hills, CA: Sage Publications. Farrington, David P. 1986. “Age and Crime.” Crime and Justice. 7:189-250. Fischer, Donald G. 1983. “Parental Supervision and Delinquency.” Perceptual and Motor Skills. 40:635-640. Giordano, Peggy C. 1978. “Girls, Guys and Gangs: The Changing Social Context of Female Delinquency.” The Journal of Criminal Law and Criminology. 69(1):126-132. Glueck, Eleanor and Sheldon Glueck. 1970. Toward a typology of juvenile offenders: implications for therapy and prevention. New York, NY: Grune and Stratton. Heimer, Karen and R. L. Matsueda. 1994. “Role-Taking, Role-Commitment, and Delinquency: A Theory of Differential Social Control.” American Sociological Review. 59(3):365-390. Hewitt, John D. and Robert M. Regoli. 2009. Exploring Criminal Justice: The Essentials. London, UK: Jones and Bartlett Publishers. Hirschi, Travis. 2002. Causes of delinquency. Berkeley, CA: Transaction Publishers. Jensen, Gary F. 1972. “Parents, “P arents, Peers, and Delinquent Action: A Test of the th e Differential Association Perspective.” American Journal of Sociology. 78(3):562-575. Kern, Roger and Joseph H. Rankin. 1994. “Parental Attachments and Delinquency.” Criminology. 32(4):495-515. Krohn et al. 1985. “Social Learning Theory and Adolescent Cigarette Smoking: A Longitudinal Study.” Social Problems. 32(5):455-473. Liu, R. 2003. "The Moderating Effects of Internal and Perceived External Sanction Threats on the Relationship between Deviant Peer Associations and Criminal Offending." Western Criminology Review 4(3) Mears et al. 1998. “Explaining the Gender Gap in Delinquency: Peer Influence and Moral Evaluations of Behavior.” Journal of Research in Crime and Delinquency. 35(3):251266. Schroeder, R. D., A. K. Osgood and M. J. Oghia. 2010. “Family Transitions and Juvenile Delinquency.” Sociological Inquiry. 80:579 – 604. 604. Stanfield, R. 1966. “Interaction of Family Variables and Gang Variables in the Etiology of Delinquency.” Social Problems. 4:411-417. Steffensmeier et al. 1989. “Age and the distribution of crime.” American Journal of Sociology. 94(4):803-831. Feeny 22
Sutherland, Edwin Hardin. 1974. Criminology 9th ed . Philadelphia, PA: Lippincott. Warr, Mark. 1993. “Age, Peers, and Delinquency.” Criminology. 31(1):17-40. Warr, Mark. 1993. “Parents, Peers, and Delinquency.” Social Forces. 72(3):43-59. Warr, Mark. 1996. “Organization and Instigation in Delinquent Groups.” Criminology. 34(1):1137. Warr, M. and Mark Stafford. 1991. “The Influence Of Delinquent Peers: What They Think Or What They Do?” Criminology. 29(4):851 – 866. 866. West, Donald J. and David P. Farrington. 1973. Who becomes delinquent? Portsmouth, NH: Heinemann Educational Wilson, H. 1980. “Parental Supervision: A Neglected Aspect of Delinquency.” British Journal of Criminology. 20(3):203-235. Wright, Bradley R. E. and C. Wesley Younts. 2009. “Reconsidering the Relationship between Race and Crime.” Journal of Research in Crime and Delinquency. 46(3):327-352. Zhang, Lening and Sheldon Zhang. 2004. “Reintegrative Shaming and Predatory Delinquency.” Journal of Research in Crime and Delinquency. 41(4):433-453.
Feeny 23
Table 1. Descriptive Statistics
Use of marijuana Parents’ reaction to marijuana use (Y5-271) Peers’ reaction to marijuana use (Y5-280) Theft > $50 Parents’ reaction to theft > $50 (Y5-272) Peers’ reaction to theft > $50 (Y5-281) Violence Parents’ reaction to violence (Y5273) Peers’ reaction to violence (Y5282) Parents’ influence on respondent (Y5-118) Peers’ influence on respondent (Y5-35) Sex (Y5-1) AA Valid N listwise
N
Minimum
Maximum
Mean
1494
0
999
31.476
Std. Deviation 94.013
1493
2
5
4.50
.658
1491
1
5
3.61
1.037
1494 1494
0 2
20 5
.1138 4.75
1.061 .446
1491
1
5
4.23
.749
1494 1493
0 2
642 5
1.485 4.42
16.982 .557
1491
1
5
4.00
.740
1263
1
5
4.01
1.025
1383
1
5
3.16
1.109
1725 1725 1184
1 0
2 1
1.47 .151
.499 .358
Feeny 24
Table 2. OLS Regression Parameter Coefficients Coefficients for Predictors of Marijuana Use (Log Transformed) T
Sig.
-.199
-7.948
.000**
-1.039
-.518
-20.104
.000**
-.177
-.088
-3.778
.000**
.057
.031
1.349
.178
Y5-1: Sex
-.234
-.057
-2.616
.009**
Y5-6: Age
.000
.000
.015
.988
AA: African
-.309
-.052
-2.422
.016**
Y5-271: Parents’
Unstandardized
Standardized
Coefficient B
Coefficient Beta
-.649
reaction Y5-280: Peers’ reaction Y5-118: Parents’ general influence Y5-35: Peers’ general influence
American Note: **p<.05; *p<.1; one-tailed test
MarijuanaUseLN
Adjusted R square .449
Feeny 25
Table 3. OLS Regression Parameter Coefficients Coefficients for Predictors of Major Theft (Log Transformed) T
Sig.
.049
1.597
.111
-.136
-.322
-10.148 -10.148
.000**
-.012
-.041
-1.363
.173
.010
.036
1.240
.215
Y5-1: Sex
-.005
-.008
-.270
.787
Y5-6: Age
-.008
-.048
-1.720
.086*
AA: African
-.036
-.040
-1.426
.154
Y5-272: Parents’
Unstandardized
Standardized
Coefficient B
Coefficient Beta
.035
reaction Y5-281: Peers’ reaction Y5-118: Parents’ general influence Y5-35: Peers’ general influence
American Note: **p<.05; *p<.1; one-tailed test MajorTheftLN
Adjusted R square .096
Feeny 26
Table 4. OLS Regression Parameter Parameter Coefficients for Predictors of Violence (Log Transformed) T
Sig.
-.022
-.719
.472
-.376
-.303
-9.633
.000**
-.044
-.049
-1.721
.086*
.048
.057
2.054
.040**
Y5-1: Sex
-.297
-.161
-5.878
.000**
Y5-6: Age
-.070
-.144
-5.338
.000**
AA: African
.067
.025
.960
.337
Y5-273: Parents’
Unstandardized
Standardized
Coefficient B
Coefficient Beta
-.036
reaction Y5-282: Peers’ reaction Y5-118: Parents’ general influence Y5-35: Peers’ general influence
American Note: **p<.05; *p<.1; one-tailed test ViolenceLN
Adjusted R square .178
Feeny 27
