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Parents, Peers, and Juvenile Delinquency By Jed Feeny SOC 429 December 7, 2011 Feeny 1

Parents, Peers, and Juvenile Delinquency

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This is a research paper examining the influence of parents and peers on juvenile delinquency

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Page 1: Parents, Peers, and Juvenile Delinquency

Parents, Peers, and Juvenile Delinquency

By Jed Feeny

SOC 429

December 7, 2011

Feeny 1

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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.

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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 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 parent-

child 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

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to Sutherland’s differential association theory, peers act as instigators of delinquency. A major

tenant of this theory is that criminal 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 theory 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 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 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).

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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 to

internalize their parents’ moral inhibitions, which serve as an obstacle to peer influence. Hirschi

(1969) argues that parents may be “psychologically 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 two-

parent 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

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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 of 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.

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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

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 than disapproval from coworkers (Liu

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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.

1979, Elliott et al. 1985, Jensen 1972). Sutherland’s differential association theory contends that

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 (Warr and Stafford 1991). Research by Warr and Stafford

(1991) suggest that while it is true that peers’ attitudes affect delinquency, 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 is not so

much the result of acquired attitudes from peers as it is the consequence of imitation and group

pressures to conform. Bahr et al. (2005) verify that peers have a strong influence on adolescents’

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 concerned about the regard

in which they are held by their peers rather than those working in the criminal justice system.

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There are different ways in which delinquency 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 from peers contributes to drug and

alcohol use. Krohn et al. (1985) find that positive reinforcement from peers is significantly

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, 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

acquired, they are not quickly lost. Warr’s main finding is that recent, rather than early friends,

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).

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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 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 (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

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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.

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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 without 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 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 have 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. Self-

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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 tell others about their criminal acts

for fear of being arrested. Ultimately, only the offender 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, 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 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.

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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 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 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

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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 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 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 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

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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 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%

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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 frequency. 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 and statistically significantly related to the logged marijuana

frequency. With a one unit 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

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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 non-

African Americans.

The standardized coefficient Beta explains which independent variable accounts for the

greatest variance of the dependent variable. For marijuana use, peers’ reaction to marijuana use

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 of 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

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 peers’ reaction to grand larceny (Y5-

281) is -.136 and is statistically significant with a p value < .05. The peers’ reaction to grand

larceny is negatively and statistically significantly related to the logged major theft frequency as

hypothesized. With a one unit increase in peers’ disapproval, the logged major theft frequency

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 predictor of major theft frequency than any 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 peers’ 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’ general 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

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unit increase in parent’s general influence, the logged 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’ 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 theory 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.

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.

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References

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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:

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London, UK: Jones and Bartlett Publishers.Hirschi, Travis. 2002. Causes of delinquency. Berkeley, CA: Transaction Publishers.Jensen, Gary F. 1972. “Parents, Peers, and Delinquent Action: A Test of the Differential

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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):11-

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Table 1. Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

Use of marijuana

1494 0 999 31.476 94.013

Parents’ reaction to

marijuana use (Y5-271)

1493 2 5 4.50 .658

Peers’ reaction to

marijuana use (Y5-280)

1491 1 5 3.61 1.037

Theft > $50 1494 0 20 .1138 1.061Parents’

reaction to theft > $50(Y5-272)

1494 2 5 4.75 .446

Peers’ reaction to theft > $50(Y5-281)

1491 1 5 4.23 .749

Violence 1494 0 642 1.485 16.982Parents’

reaction to violence (Y5-

273)

1493 2 5 4.42 .557

Peers’ reaction to

violence (Y5-282)

1491 1 5 4.00 .740

Parents’ influence on respondent (Y5-118)

1263 1 5 4.01 1.025

Peers’ influence on respondent

(Y5-35)

1383 1 5 3.16 1.109

Sex (Y5-1) 1725 1 2 1.47 .499AA 1725 0 1 .151 .358

Valid N listwise

1184

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Table 2. OLS Regression Parameter Coefficients for Predictors of Marijuana Use (Log Transformed)

Unstandardized

Coefficient B

Standardized

Coefficient Beta

T Sig.

Y5-271: Parents’

reaction

-.649 -.199 -7.948 .000**

Y5-280: Peers’

reaction

-1.039 -.518 -20.104 .000**

Y5-118: Parents’

general influence

-.177 -.088 -3.778 .000**

Y5-35: Peers’

general influence

.057 .031 1.349 .178

Y5-1: Sex -.234 -.057 -2.616 .009**

Y5-6: Age .000 .000 .015 .988

AA: African

American

-.309 -.052 -2.422 .016**

Note: **p<.05; *p<.1; one-tailed test

Adjusted R squareMarijuanaUseLN .449

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Table 3. OLS Regression Parameter Coefficients for Predictors of Major Theft (Log Transformed)

Unstandardized

Coefficient B

Standardized

Coefficient Beta

T Sig.

Y5-272: Parents’

reaction

.035 .049 1.597 .111

Y5-281: Peers’

reaction

-.136 -.322 -10.148 .000**

Y5-118: Parents’

general influence

-.012 -.041 -1.363 .173

Y5-35: Peers’

general influence

.010 .036 1.240 .215

Y5-1: Sex -.005 -.008 -.270 .787

Y5-6: Age -.008 -.048 -1.720 .086*

AA: African

American

-.036 -.040 -1.426 .154

Note: **p<.05; *p<.1; one-tailed test

Adjusted R squareMajorTheftLN .096

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Table 4. OLS Regression Parameter Coefficients for Predictors of Violence (Log Transformed)

Unstandardized

Coefficient B

Standardized

Coefficient Beta

T Sig.

Y5-273: Parents’

reaction

-.036 -.022 -.719 .472

Y5-282: Peers’

reaction

-.376 -.303 -9.633 .000**

Y5-118: Parents’

general influence

-.044 -.049 -1.721 .086*

Y5-35: Peers’

general influence

.048 .057 2.054 .040**

Y5-1: Sex -.297 -.161 -5.878 .000**

Y5-6: Age -.070 -.144 -5.338 .000**

AA: African

American

.067 .025 .960 .337

Note: **p<.05; *p<.1; one-tailed test

Adjusted R squareViolenceLN .178

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