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This is a research paper examining the influence of parents and peers on juvenile delinquency
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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 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.
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
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.
Feeny 8
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).
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 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
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 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.
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 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
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 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
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 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 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
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 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.
Feeny 18
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
Feeny 19
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
Feeny 20
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.
Feeny 21
References
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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
Feeny 24
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
Feeny 25
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
Feeny 27