ArticlePDF Available

A longitudinal test of the effects of parenting and the stability of self-control: Negative evidence for the General Theory of Crime



This study investigates two core propositions of Gottfredson and Hirschi's (1990) general theory of crime. Using longitudinal data collected on approximately 750 African American children and their primary caregivers, we first examine whether self-control fully mediates the effect of parenting on delinquency. Consistent with the general theory, we find that low self-control is positively associated with involvement in delinquency. Counter to Gottfredson and Hirschi's proposition, we find that self-control only partially attenuates the negative effect of parental efficacy on delinquency. Next, we assess the theory's hypothesis that between-individual levels of self-control are stable. Finding substantial instability in self-control across the two waves, we explore whether social factors can explicate these changes in self-control. The four social relationships we incorporate (improvements in parenting, attachment to teachers, association with pro-social peers, and association with deviant peers) explain a substantial portion of the changes in self-control. We then discuss the implications of these findings for the general theory of crime.
University of Georgia
KEYWORDS: self-control, authoritative parenting, delinquency, stability,
change, peers
This study investigates two core propositions of Gottfredson and
Hirschi’s (1990) general theory of crime. Using longitudinal data
collected on approximately 750 African American children and their
primary caregivers, we first examine whether self-control fully mediates
the effect of parenting on delinquency. Consistent with the general
theory, we find that low self-control is positively associated with
involvement in delinquency. Counter to Gottfredson and Hirschi’s
proposition, we find that self-control only partially attenuates the
negative effect of parental efficacy on delinquency. Next, we assess the
theory’s hypothesis that between-individual levels of self-control are
* This research was supported by the National Institute of Mental Health (MH48165,
MH62669) and the Center for Disease Control (029136-02). Additional funding for
this project was provided by the National Institute on Drug Abuse, the National
Institute on Alcohol Abuse and Alcoholism, and the Iowa Agriculture and Home
Economics Experiment Station (Project #3320). An earlier version of this paper
was presented at the 2005 American Society of Criminology conference in Toronto,
Canada. We wish to thank Mark Cooney, Denise Gottfredson, and two anonymous
reviewers for their comments and suggestions that improved the manuscript. We
extend a special thanks to Tanja Link for insightful critiques on several drafts of
this paper. Please direct correspondence to: Callie Harbin Burt, Department of
Sociology, University of Georgia, 114 Baldwin Hall; Athens, GA, 30601;
stable. Finding substantial instability in self-control across the two
waves, we explore whether social factors can explicate these changes in
self-control. The four social relationships we incorporate (improve-
ments in parenting, attachment to teachers, association with pro-social
peers, and association with deviant peers) explain a substantial portion
of the changes in self-control. We then discuss the implications of these
findings for the general theory of crime.
Proclaiming an explanation of all crimes at all times, Gottfredson and
Hirschi (1990) proposed the general theory of low self-control. This
theory, which is grounded in the classical view of human nature, assumes
that criminal motivation is evenly distributed; all humans are self-
interested actors seeking pleasure, and crime is a universally desirable way
of pursuing self-interest. The basic thrust of the theory is that the absence
of self-control leads to crime. A convincing body of evidence has
accumulated in support of its central tenet that low self-control is related
to a range of criminal behaviors (for example, Pratt and Cullen, 2000).
Indeed, the consistently strong support has led scholars to conclude that
“its relationship to delinquent involvement is a ‘fact’ for which extant
theories must take account” (Unnever, Pratt, and Cullen, 2003: 483).
According to the general theory, criminality, or the propensity to
engage in crime, is an inverse function of self-control (Gottfredson and
Hirschi, 1990). Effective parenting during the first 6 to 8 years of life
produces self-control. Effective parenting consists of monitoring a child’s
behavior, recognizing deviant behavior when it occurs, and punishing bad
behavior. Individuals can be hierarchically ranked according to their levels
of self-control, and after the first 10 years of life, these between-individual
rankings of self-control remain stable. Whereas Gottfredson and Hirschi
(1990) ascribe a central role to parenting practices in the development of
self-control, they propose, as Unnever and colleagues expressed it (2003:
472), that parental influence “is exerted through the narrow conduit of
The general theory proposes that this stable criminal propensity, low
self-control, accounts for all variation by sex, race, and culture in crime
rates and “explains all crime, at all times, and, for that matter many forms
of behavior that are not sanctioned by the state” (Gottfredson and
Hirschi, 1990: 177). Moreover, they also claim that self-control renders the
apparent causal relationship between social factors—such as weak
attachment to parents, associating with deviant peers, and disliking
school—and crime spurious. In the words of Gottfredson and Hirschi
(1990: 251), the causal factors in traditional explanations of crime are
manifestations of self-control and thus, “events without causal
An impressive amount of empirical attention has focused on the
relationship between self-control and crime. On the other hand, much is
still unknown about the empirical adequacy of the theory. Indeed, two of
its most distinctive and controversial propositions, the irrelevance of
family processes after the formative years and the stability of between-
individual rankings in self-control, have been largely neglected in
empirical tests (for exceptions, see Gibbs, Giever, and Martin, 1998; Hay,
2001; Perrone et al., 2004; Turner and Piquero, 2002; Unnever, Pratt, and
Cullen, 2003). This neglect is due in part to sample limitations, including
the use of older respondents, the absence of measures of parenting
practices or self-control, and the dearth of longitudinal examinations that
examine these relationships over time (Unnever, Pratt, and Cullen, 2003).
A primary goal of this study is to contribute to this literature by
examining Gottfredson and Hirschi’s (1990) proposition that self-control
fully mediates the effect of parenting on crime. Drawing on Hay’s (2001)
work as well as on the extensive psychological literature on parenting
practices, we conceptualize parental efficacy as authoritative parenting.
The constellation of parenting practices that Baumrind (1966, 1991, 1996)
identified and labeled as authoritative parenting emphasizes caregiver
warmth and support as well as monitoring and consistent discipline. We
examine the mediating effects of self-control on the relationship between
authoritative parenting and delinquency using contemporaneous measures
of these constructs. We also assess the influence of improvements or
deteriorations in these constructs over time, controlling for initial levels.
Moreover, although relatively few studies have investigated the tenet
that self-control fully mediates the effects of family processes on crime,
even fewer have examined the stability of self-control within the general
theory’s framework. The second aim of this study, then, is to test the
theory’s stability postulate, which asserts that between-individual rankings
of self-control should remain stable after age 10 (Turner and Piquero,
2002). Although the theory allows for a cohort’s overall level of self-
control to increase, it does not allow for decreases or changes in individual
rankings. We assess this proposition by examining between-individual
levels of self-control across a 2-year span. Self-control may be less stable
than the theorists would have us believe. If so, Gottfredson and Hirschi’s
assertions that rely on stability may require modification, and an
additional inquiry may be desirable to explain these changes adequately.
This study, then, addresses these gaps in the self-control theory
literature by examining two core and controversial propositions. First, we
test the proposition that the influence of parenting on delinquency is
exerted through self-control. Next, we assay the theory’s proposition that
between-individual levels of self-control remain stable after the first
decade of life. Findings from the paucity of studies that have examined
these tenets of the general theory provide mixed evidence. In part, the
inconclusive findings seem to be due to methodological problems,
particularly inconsistencies in the operationalization of key constructs
(Akers and Sellers, 2004; Tittle and Botchkovar, 2005). The present
analyses are distinctive in several respects and attempt to overcome the
limitations of previous work by: employing a sample of African American
youth subsequent to the age at which self-control rankings are said to be
fixed, incorporating multiple facets of parenting from different sources,
and examining the postulated relationships across time.
In the following sections we will review relevant theoretical and
empirical work. We then will analyze the two propositions of self-control
theory using data from the Family and Community Health Study, a sample
of African American children and their primary caregivers in Georgia and
Iowa (Simons, Simons, and Wallace, 2004). This population was chosen for
study because systematic investigations of developmental processes of
African American children of this age are rare.
Roughly 15 years ago, Gottfredson and Hirschi boldly presented the
theory of self-control. Defining crime as “acts of force and fraud
undertaken in the pursuit of self-interest,” they contend that the vast
majority of offenses are trivial, unspecialized, and involve little or no
planning (1990: 15). The cause of crime is traced to low self-control. Self-
control is formed at an early age through effective child rearing. In
contrast to those with higher levels of self-control, the behavioral choices
for individuals suffering from low self-control are governed by short-term
rationality (Hirschi and Gottfredson, 1993). This restricted time and
person frame of reference is reflected in the elements of low self-control,
which include immediate and easy gratification of desires, inability to
appreciate long-term consequences, and lack of perseverance in achieving
goals (Gottfredson and Hirschi, 1990: 89–90).
No doubt due in part to the debate sparked by the general theory,
empirical assessments are plentiful, and support for its central premise, an
inverse relationship between self-control and deviant behavior, is
consistent (see Pratt and Cullen, 2000). Research has found that low self-
control is significantly related to crime and analogous behaviors (for
example, Arneklev et al., 1993; Gibbs and Giever, 1995; LaGrange and
Silverman, 1999; Tremblay et al., 1995). In their meta-analysis, Pratt and
Cullen (2000: 952) noted that the influence of self-control does indeed
appear to be “general” and its effect size qualifies it as “one of the
strongest known correlates of crime.”
Gottfredson and Hirschi (1990) maintain that effective parenting is the
major cause of self-control. Driven by affection for the child, effective
parenting during a child’s first 6 to 8 years leads to a general orientation
that increases the probability of restrained or socially appropriate
responses throughout life. The three components of effective parenting
are monitoring or tracking the child’s behavior, recognizing deviant
behavior when it occurs, and consistently punishing deviant behavior
(1990: 97–98). Gottfredson and Hirschi assert that parenting practices that
satisfy these three conditions are necessary and sufficient to socialize
children and instill self-control.
Instructively, numerous psychological studies on child development
have consistently documented that a broad range of parenting factors are
crucial to the positive outcomes of children (for example, Gray and
Steinberg, 1999). In particular, caregivers who are responsive to their
children’s needs, who permit children to be active participants in the
establishment of rules, and who engage in inductive reasoning when
disciplining their children are more likely to have children who are
assertive, independent, friendly, and cooperative (Amato and Fowler,
2002; Brody and Flor, 1997; Dornbusch et al., 1987; Steinberg, Elmen, and
Mounts, 1989; Steinberg et al., 1992; Steinberg et al., 1991). Identified by
Baumrind (1966), this combination of supportive, inductive parenting
practices is known as authoritative parenting. Research has shown that
caregiver warmth, support, and involvement are necessary for the
successful development of self-control (Berscheid, 1986; Rankin and Kern,
1994; The NICHD Early Child Care Research Network, 1998; Wills,
Mariani, and Filer, 1996). This research demonstrates that child-rearing
practices based on power assertion and control without guidance and
support actually foster weak self-control (Belsky, Woodworth, and Crynic,
1996; Crockenberg and Litman, 1991; Power and Chapieski, 1986).
Drawing on the extensive literature on parenting styles, Hay (2001)
assessed whether Baumrind’s (1966, 1991, 1996) theory of authoritative
parenting, improved the explanation of self-control beyond the theory’s
conception of effective parenting. He found that it did. In fact,
incorporating the additional parenting factors tripled the explained
variance in self-control and lead the author to conclude that self-control
theory’s conceptualization of effective parenting was unduly narrow.
Based on Hay’s findings and the extensive literature on authoritative
parenting, we believe that there is good reason to modify the theory’s
conception of effective parenting to incorporate caregiver warmth,
support, reasoning, and consistent nonphysical discipline.
An important corollary proposition in self-control theory concerns the
role of parenting after early childhood. Gottfredson and Hirschi (1990)
view effective parenting as a distal cause of criminal behavior, in that its
effect on crime should operate solely through self-control. That is, self-
control theory maintains that once levels of self-control are developed and
fixed within individuals (around ages 8 to 10), parental efficacy should
play no role in explaining criminal behavior.
Despite the theory’s emphasis on the essential role of parenting during
a child’s formative years and its alleged irrelevance after age 10,
sociological research has only begun to assess the empirical adequacy of
these propositions. To our knowledge, only six published studies have
subjected the theory’s parenting arguments to empirical scrutiny (Feldman
and Weinberger, 1994; Gibbs, Giever, and Martin, 1998; Hay, 2001;
Perrone et al., 2004; Polakowski, 1994; Unnever, Pratt, and Cullen, 2003).
For the most part, these efforts indicate that the effect of parenting on
crime is at least to some extent mediated by self-control (Hay, 2001;
Unnever, Pratt, and Cullen, 2003).
A key facet of Gottfredson and Hirschi’s theory is the stability
postulate (1990: 107). Indeed, this aspect of the theory has sparked the
greatest controversy and perhaps most sharply distinguishes it from other
sociological theories of crime.1 In effect, this postulate asserts that self-
control rankings between individuals remain constant across time. After
age 10 those who failed to develop adequate self-control will not be able
to control their impulses over the life span. Well-behaved children become
good adolescents and good adults; bad children are doomed “to remain a
source of concern to their parents, teachers, and eventually to the criminal
justice system” (Hirschi and Gottfredson, 2001: 90). Subsequent to the
formative years, self-control theory posits that shifts in parenting practices,
life events, or criminal justice interventions have neither a positive nor a
negative effect on individuals’ relative standings in criminal propensity.
Although many scholars, such as Laub and Sampson (2003; Sampson
and Laub, 1993; see also Nagin and Paternoster, 1993), have examined the
stability of criminal behavior, only two studies purportedly testing the
general theory of crime have explored the stability postulate using
measures of self-control. Arneklev and colleagues (1999) measured the
1. For an informative debate on stability versus change, see Hirschi and Gottfredson
(1995) and Sampson and Laub (1995). For a commentary on this debate, see Cohen
and Vila (1996) in the following volume.
self-reported levels of self-control in a convenience sample of college
students in a two-wave test-retest study. The researchers found that the
overall self-control construct remained relatively stable, though their test
only captured the short period of 4 months. In a more recent and rigorous
study, Turner and Piquero (2002) explored the stability hypothesis using
behavioral and attitudinal measures of self-control in a national
probability sample. Although reporting only moderate stability in the
correlations of self-control over time (ranging from 0.33 to 0.68), the
authors found that self-control differences between offenders and
nonoffenders remained significantly different across six of seven waves of
data. Further analyses led Turner and Piquero to conclude: “It is apparent
that these findings neither consistently support nor refute Gottfredson and
Hirschi’s stability postulate” (2002: 467).
In contrast to Gottfredson and Hirschi’s (1990) strict stability postulate,
psychological research points to a more dynamic view of self-control.
Researchers examining the stability of individual differences in self-
control report finding moderate stability over time. For example,
Tremblay et al. (1995) found that teacher ratings of children’s self-control
at age 6 correlated at r = .43 with teacher ratings and at r = .30 with mother
ratings 4 years later when the children were age ten. In another
longitudinal study, Murphy and colleagues (1999) reported considerable
stability in groups of children observed when they were 6 to 8 years old
and assessed again 4 years later (when they were 10 to 12). Rank-order
correlations between baseline and follow-up parental reports of inhibitory
control and behavioral self-control were .63 and .41, respectively (Murphy
et al., 1999). Finally, in one of the few large-scale longitudinal assessments
of self-control, Raffaelli, Crockett, and Shen (2005) examined the stability
of individual differences at three points across an 8-year period using the
National Longitudinal Survey of Youth. They reported significant
correlations between self-control scores between times 1 and 2 (r = .50)
and between times 2 and 3 (r = .49), and concluded that individual
differences in self-control were “fairly stable” across the observation
period (69). The relevance of Raffaelli and associates’ (1999) study for
Gottfredson and Hirschi’s theory is vitiated by the fact that the children
were only 4 to 5 years old at the baseline interviews and 12 to 13 at the
third interview. On the other hand, the magnitude of the stability
correlations actually decreased slightly contrary to the researchers’
expectations and the general theory’s assertions of increasing stability
after middle childhood.
Research suggests, then, that the stability of self-control is analogous to
personality traits such as neuroticism, negative affectivity, and IQ (Caspi,
Roberts, and Shiner, 2005; Johnson, McGue, and Krueger, 2005).
Summarizing the extensive research on self-control, Strayhorn writes,
“self-control is a stable enough trait that it makes sense to talk about an
individual’s generalized self-control and to set goals for increasing it. On
the other hand, self-control is not so stable that hope of altering it should
be abandoned” (2002: 10). These studies have established not only that
within-individual levels and between-individual rankings change over
time, but also that individual and environmental factors operate
simultaneously to effect these changes in levels of self-control (for
example, Baumeister, Heatherton, and Tice, 1994; Caspi, Roberts, and
Shiner, 2005).
Consistent with this idea and previous research, Baumeister and
colleagues (Baumeister, Heatherton, and Tice, 1994; Baumeister and
Exline, 1999; Muraven, Tice, and Baumeister, 1998) have elaborated the
strength model of self-control, which contends that self-control operates
like a muscle. They argue that changing social and material reinforcements
and their importance within the goal hierarchies of individuals influence
how much effort is expended in utilizing available self-regulatory skills,
which in turn strengthens or weakens the self-control “muscle” (Higgins
and Spiegel, 2004; Schmeichel and Baumeister, 2004).
The strength model of self-control has two central features. First, just as
muscle strength is depleted after prolonged or intense use, exertion makes
self-control tired and diminishes its power. On the other hand, just as a
muscle is fatigued in the short run but strengthened in the long run by
exercise, so self-control may be strengthened by exercise and practice
(Baumeister, 2002; Baumeister, Muraven, and Tice, 2000). Longitudinal
research has supported both features of the strength model (for example,
Baumeister, Heatherton, and Tice, 1994; Mischel, Cantor, and Feldman,
1996; Muraven, Baumeister, and Tice, 1999; Vohs, Baumeister, and
Ciarocco, 2005).
Gottfredson and Hirschi contend that self-control is the main causal
agent not only of crime but also of a range of analogous behaviors and life
outcomes (1990: 154–68). According to the theory, self-control has social
consequences that shape the ability to form social bonds and succeed in
social institutions. Thus, opposing the axiomatic stance of sociological
criminology, Gottfredson and Hirschi deny that salient life events or social
factors, such as associating with deviant peers, weak attachment to
conventional activities, or failing in school, have any causal significance.
Instead, they assert that such social interactional constructs are associated
with crime because all are manifestations of low self-control. The theory
predicts that low self-control is the cause of impaired social relations,
affiliation with deviant others, and school failure and eliminates any
relationship between these factors and crime. Importantly, this hypothesis
relies heavily on the assertion that self-control is stable before the age at
which many of these social behaviors are possible (Gottfredson and
Hirschi, 1990).
Research testing this social consequences hypothesis has been largely
consistent with the theory (Pratt and Cullen, 2000). In the most rigorous
examination of this facet of the theory to date, Evans and colleagues note
that their findings in support of the theory, using a cross-sectional sample
of white adults residing in a Midwestern city, “must be interpreted with
caution because their causal implications are not clear” (1997: 493).
Insofar as the present study discredits the stability postulate (substantial
changes in individuals’ self-control are found) the possibility of reverse
causal ordering (social consequences influence individuals’ levels of self-
control) is plausible. In keeping with the strength model of self-control,
the so-called social consequences and improvements in parenting may
alter individuals’ levels and rankings of self-control.
Therefore, if the between-individual levels of self-control change
substantially across the two waves, we will conduct an exploratory analysis
and consider the influence of four social factors on changes in levels of
self-control. Three of these factors—improvements in parenting,
involvement with pro-social peers, and attachment to teachers—are
expected to increase individual levels of self-control. Associating with
deviant peers, on the other hand, is hypothesized to decrease self-control.
Participating in risky or illegal acts at the urging of one’s peers offers
immediate rewards (for example, positive peer reinforcement, avoidance
of conflict) and may contribute to an escalation in behaviors that involve
discounting the risks of undesirable outcomes while pursuing a more
desirable outcome. From this perspective, individuals’ associates may
influence the weighing of costs and benefits, or exacerbate an already
biased ability to accurately foresee and evaluate the distal consequences of
actions, and thereby contribute to an increase in risk taking.
In the present study, two propositions from Gottfredson and Hirschi’s
(1990) theory will be tested using two waves of data from the Family and
Community Health Study (FACHS), a longitudinal, multisite investigation
of neighborhood and family effects on health and development. Most
research on the effects of contextual factors on African American parents
and children has centered on families living in the impoverished inner core
of large metropolitan areas. This focus does not acknowledge the diversity
of African American families and the variety of communities in which
they live. The FACHS was designed to identify neighborhood and family
processes that contribute to school-age African American children’s
development in families living in a wide variety of community settings
outside the inner-city core. Each family included a child who was in the
fifth grade at the time of recruitment. Interviews were conducted with the
target child, his or her primary caregiver, and a secondary caregiver when
one was present in the home. This data set is well suited for this
investigation. To date, few tests of self-control theory have focused on
African American adolescents (for an exception, see Vazsonyi and
Crosswhite, 2004); thus, the theory’s empirical adequacy among this
population remains unclear. Moreover, the study collects detailed
information on parenting practices from both the target children and their
primary caregivers.2 Additionally, the age of the children in the sample (10
to 12 at wave 1 and 12 to 14 at wave 2) provides an opportunity to assess
the stability of self-control subsequent to the formative years when the
theory allows for changes in between-individual levels.
The FACHS sample consists of several hundred African American
families living in Georgia and Iowa. Families were recruited from
neighborhoods that varied in demographic characteristics, specifically,
racial composition (percentage African American) and economic level
(percentage of families with children living below the poverty line). Using
1990 census data, block groups (BGs) were identified in both Iowa and
Georgia in which the proportion of African American families was high
enough to make recruitment economically practical (10 percent or higher),
and in which the proportion of families with children living below the
poverty line ranged from 10 to 100 percent. Using these criteria, 259 were
identified (115 in Georgia and 144 in Iowa). The study families were
recruited from these BGs.
Recruitment strategies differed in Georgia and Iowa. In Georgia,
sampling procedures were similar to those used in earlier investigations of
African American families (Brody and Flor, 1997). Block groups in
Georgia came from locations such as south Atlanta, the Stone Mountain
area, Athens, and several small towns and cities in the north central
portion of the state. Within each BG, community members were hired to
serve as liaisons between the University of Georgia researchers and the
communities. The liaisons compiled rosters of children who met the
sampling criteria. In addition to their own direct knowledge, the liaisons
2. Past research has established that both parents and children have biased
perspectives on family processes (Furhman et al., 1989; Olson, 1977). In an effort to
increase the validity of the measure of ineffective parenting, primary caregiver self-
reports and child reports will be used.
used information from parents, schools, churches, youth groups, and other
community organizations to compile the rosters.
In Iowa, all block groups that met the study criteria were in two
communities: Waterloo/Cedar Falls, with a metropolitan population of
approximately 120,000, and the Des Moines metropolitan area, with a
population of approximately 350,000. Families with African American
children within the age criterion were identified through the public
schools, which provided the names and addresses of all African American
students in the fifth grade.
In both Georgia and Iowa, families were randomly selected from these
rosters and contacted to determine their interest in participating in the
project. Families who declined participation were removed from the
rosters and other families were randomly selected until the required
number of families from each BG had been recruited. Most families were
recruited by telephone. However, after repeated unsuccessful attempts to
make telephone contact, or if a potential participant did not have a
telephone, a staff member attempted to make face-to-face contact. If the
potential participant was no longer at the address, we asked neighbors for
information regarding the new address.
To evaluate the variability and representativeness of the neighborhoods
included in our sample, we compared census tracts included in the FACHS
sample with those in Georgia and Iowa that were not included. No
significant differences were found in Iowa. For Georgia, average and
median family incomes were somewhat lower among the tracts in the
study than in those excluded. Further analysis showed this to be a result of
the study sample having an under-representation of high-income census
tracts (that is, $45,000 or higher in 1990). However, the FACHS sample
includes a large number of both lower- and middle-class census tracts.
Existing research on community effects shows that the greatest contrasts
are between poor and middle-income communities (Jencks and Mayer,
1990). We believe our sampling strategy yielded a relatively representative
set of communities with sufficient variability on economic status to allow
significant relations between community characteristics and outcome
variables to be detected.
Two waves of data were collected from the Georgia and Iowa families
using identical research procedures (for further details on the sampling
procedure, see Simons et al., 2005). The first wave was collected in 1998
and the second in 2000. At wave 1, the participants were 867 African
American children (400 boys and 467 girls, 462 in Iowa and 405 in
Georgia) and their primary caregivers. The children were 10 to 12 years
old (mean of 10.5 years) at wave 1. A primary caregiver was defined as a
person living in the same household and responsible for the majority of
the child’s care. Most (84 percent) of the primary caregivers were the
target child’s biological mother (6 percent were the father, 6 percent were
the grandmother). Their age ranged from 23 to 80 (mean of 37.1 years).
They reported an average of 4.5 children living in their homes. The
primary caregivers’ education ranged from less than high school (19
percent) to advanced graduate degrees (3 percent). The mode was a high
school degree (41 percent). Ninety-two percent identified themselves as
African American. Seventy-one percent were employed full or part-time,
15 percent were unemployed, 6 percent were disabled, and 5 percent were
full-time homemakers. Median income for the families was $20,803. There
was no significant difference in income or education of the primary
caregiver between the Iowa and Georgia subsamples.
At wave 2, interviews were completed by 779 of the children and their
caregivers, a response rate of 89 percent. Analyses indicated that the
families who did not participate at wave 2 did not differ significantly from
those who did with regard to caregiver income and education or child’s
age, gender, school performance, delinquency, or self-control. Complete
data were available for 754 children and their caregivers.
Low self-control. The general theory asserts that individuals with low
self-control can be characterized as “impulsive, insensitive, physical (as
opposed to mental), risk-taking, short-sighted, and nonverbal”
(Gottfredson and Hirschi, 1990: 90). Following the theory’s description of
the nature of low self-control, thirty-nine items that assess whether the
respondents desire immediate gratification, are easily frustrated, are
physical versus contemplative, verbal, impatient, and have a preference for
risk were identified. Instructively, Gottfredson and Hirschi (1990: 91) treat
self-control as a single unidimensional latent trait. That is, they expect
these characteristics to come together in the same people and to comprise
a stable construct (see also Burton et al., 1998; Grasmick et al., 1993). The
measures of self-control were generated by summing the responses across
the thirty-nine items at wave 1 and again at wave 2.3 The resulting measure
closely matches Gottfredson and Hirschi’s nominal definitions of low self-
control and is analogous to the operational definition of the frequently
3. Factor analysis was undertaken with items in the self-control measure. Although
previous research (see Arneklev et al., 1993; Grasmick et al., 1993; Wood,
Pfefferbaum, and Arnkelev, 1993) has identified through factor analysis separate
factors within the trait of self-control, our analysis of the items failed to identify
distinct, theoretically coherent factors (see also Brownfield and Sorenson, 1993).
used Grasmick et al. (1993) scale.4 Confidence in the internal consistency
of the scale was given by the estimated reliability coefficients in both
waves ( = .88 and = .89, respectively). Scale items have been coded so
that high scores indicate low self-control and are listed in appendix A.
Delinquency. This construct was measured using child self-reports on
the conduct disorder section of the Diagnostic Interview Schedule for
Children, Version 4 (DISC-IV). The DISC-IV covers Diagnostic
Statistical Manual-IV (DSM-IV; American Psychiatric Association, 1994)
as well as International Classification of Disease-9 criteria for diagnoses.
The DISC was developed over a 15-year period of research on thousands
of children and parents and has demonstrated reliability and validity
(Schaffer et al., 1993). Version IV became available in 1995 and represents
a modest revision of the DISC-III based on findings from the MECA
study (Schaffer et al., 1993). The conduct disorder section contains a series
of questions about how often during the preceding year the respondent
engaged in twenty-six deviant acts such as shoplifting, physical assault,
lying, setting fires, cruelty to animals, vandalism, burglary, and robbery.
Although these items vary in seriousness, Gottfredson and Hirschi (1990)
consider the effects of self-control to be general across crimes. Thus, they
question the validity and usefulness of narrow measures of various types
of crime and favor scales that include a variety of offenses. The conduct
disorder section can be used to generate symptom counts (number of
different acts committed) or diagnoses. Symptom counts were used in this
study. The maximum score of 26 corresponds to a subject responding that
he or she engaged in all of the different acts. Not surprisingly, no
respondent reported engaging in all of the acts; the maximum delinquency
scores were 15 and 19 at waves 1 and 2, respectively. Intuitively,
respondents who indicated no involvement in the deviant activities
received a score of 0. Coefficient alpha for the twenty-six-item
delinquency instrument was above .90 at both waves 1 and 2.
Regression models for dependent variables that represent counts of
some phenomena are more appropriate than ordinary least squares
regression (OLS) due to inherent problems in the latter model.5 Given
that the measure of delinquency represents counts of engagement in the
4. The instrument designed by Grasmick et al. (1993) has been used in several studies,
which have provided strong reliability and validity support for the scale (for
example, Nagin and Paternoster, 1993).
5. First, OLS regression assumes that the dependent variable is continuous, whereas
count data is inherently discrete. Additionally, count dependent variables are by
definition truncated at zero, as unequivocally, negative counts are not possible.
And, last, count dependent variables invariably have highly skewed, nonsymmetric
distributions; this violates the OLS assumption that the error terms approximate a
normal distribution (Allison, 1999; Long, 1997; Long and Freese, 2003).
behaviors, the ability of self-control to fully mediate the effect of parenting
practices on delinquency is estimated with negative binomial regression
models using Stata 8.0 (Long, 1997).6
Parenting practices. Gottfredson and Hirschi state that “effective
punishment by the parent or major caregiver therefore usually entails
nothing more than explicit disapproval of unwanted behavior” (1990: 100).
Research on parenting practices and child development, however, evinces
that parental efficacy is a function not only of control but also of
responsiveness (for example, Baumeister, Heatherton, and Tice, 1994;
Baumrind, 1966); that is, parents of children with high self-control are
nurturant and demanding (Strayhorn, 2002). As noted earlier, this style of
child rearing is labeled authoritative parenting and subsumes the general
theory’s narrower concept of effective parenting.
Research has established that effective parents monitor their child’s
behavior, use inductive reasoning to explain rules, positively reinforce
desirable behavior, and are consistent in their use of nonharsh discipline in
the context of a warm and supportive relationship (see Simons, Simons,
and Wallace, 2004). The items for the scale were adapted from the
parenting instrument developed for the Iowa Youth and Families Project
and demonstrated high validity and reliability (Conger et al., 1992). For
example, research has shown that parent and child reports both correlate
with each other and with observers’ ratings (Conger et al., 1992; Simons
and Associates, 1996) and predict various dimensions of children’s
behavior across a several-year period (Simons et al., 2001). In addition,
feedback from the focus groups prior to data collection indicated that
6. There are a variety of models that deal with characteristics of count outcomes. The
most basic model is the Poisson regression model, on which the negative binomial
regression model (NBRM) and related count models are based (Long, 1997). With
this model the probability of a count is estimated by a Poisson distribution, where
the mean of the distribution is a function of the independe nt variables. The Poisson
process presupposes that the events are independent. To put a nother way, if an
event occurs, it does not affect the probability of the event occurring in the future
(Allison, 1999). The model has the requirement that the conditional mean of the
outcome is equal to the conditional variance; an assumption known as
equidispersion. This model is rarely used in practice due to this equidispersion
requirement, which is routinely violated in most applications. If the model is fitted
to an outcome with overdispersion, while slopes will not be affected, the standard
errors will be biased downward, leading to spuriously large z-values (Long, 1997).
The NBRM was developed to deal with this problem, and while the Possion model
and the NBRM have the same mean structure, the NBRM introduces unobserved
heterogeneity allowing for overdispersion (Long and Freese, 2003). In the
following models predicting delinquency, the overdispersion parameter is
significant (indicating a dependent variable with a distribution incorporating many
zero values and large positive skews); thus, we report the negative binomial results.
these items are meaningful to African American parents and capture what
they consider the important aspects of parenting.
Primary caregivers completed twenty-one questions about their
parenting practices. Five questions focused on monitoring, six concerned
consistency of discipline, five focused on inductive reasoning, four asked
about problem solving, and two involved positive reinforcement. The
response format for all of these items ranged from 1 (always) to 4 (never).
Negatively worded items were recoded so that higher scores on all items
indicated superior parenting. These items were summed to create
caregivers’ reports of authoritative parenting. Coefficient alpha for the
primary caregiver instrument was .74 at wave 1 and .77 at wave 2.
These same items were reworded so that the target child could use the
same scale to rate the primary caregiver’s parenting behavior. The child-
report measure of parenting also included nine items concerning parental
warmth and fourteen items about harsh parenting. These items were also
recoded so that higher scores on all items indicated superior parenting and
were combined. Alpha reliability for the 45-item child-report measure was
approximately .90 at both waves.
In an effort to increase the validity of the measure of quality of
parenting and avert the problem of shared method variance,7 primary
caregiver self-reports and child reports about the caregiver’s parenting
were standardized and summed to form a composite measure of
authoritative parenting at each wave. Scale items are listed in appendix B.
Increase deviant peer affiliation. The children self-reported their
affiliation with deviant peers using an instrument adapted from the
National Youth Survey (Elliott, Huizinga, and Menard, 1989). They were
asked how many of their close friends (1 = none, 3 = half, 5 = all) had
engaged in each of nineteen delinquent acts. The acts varied from
relatively minor offenses such as skipping school to more serious
violations such as stealing something worth more than $25. The responses
to the items were summed to obtain a total score on the extent to which
the respondents’ friends engage in deviant behavior at each wave.
Coefficient alpha for the scale was roughly .90 for both waves. The
7. Much of previous work assessing patterns of relations found between parenting
practices, self-control, and delinquency employs measures from a common
source—“the primary pitfall of method variance” (Gray and Steinberg, 1999: 586).
This methodological weakness raises the possibility that these associations are
spurious. Overall perceptions of well-being (affected by levels of self-control) may
slant adolescents’ descriptions of themselves as well as their parents—causing well-
adjusted youth to provide generally positive characterizations and maladjusted
teens to cast everything in a negative light. We minimize this possibility by
employing measures from both the target children and their primary caregivers.
measure of deviant peers at wave 1 was subtracted from the measure at
wave 2 to generate the measure of increase in deviant peer affiliation.
Increase pro-social peer affiliation. This measure captures the change in
the target children’s pro-social peers from wave 1 to wave 2. In both
waves, the children answered nine items regarding the extent to which
their friends positively reinforce conforming behavior. The children
reported how (1 = tell me to stop, 2 = do nothing, 3 = encourage me to do
it again) their close friends would respond to nine pro-social behaviors,
such as “if you saved money to go to college,” “if you helped at home by
spending money you have earned on food, clothing, or rent for the
family,” and “if you worked hard to get good grades in school.” The
responses were summed such that higher scores indicate greater
association with pro-social peers; alpha reliability for the measure was .82
at wave 2 and .78 at wave 1. Last, we subtracted the pro-social peers scale
from wave 1 from its wave 2 counterpart to create the variable increase in
pro-social peer affiliation.
Increase attachment to teachers. The change in attachment to teachers
was measured by subtracting the respondent’s score on a three-item scale
reported by the target children in wave 1 from the same measure at wave
2. The children were asked how much they agreed or disagreed (1 =
strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree) with three
statements: “you feel very close to at least one of your teachers,” “you get
along well with your teachers,” and “your teachers think you are a good
student.” The responses were summed with higher scores indicating
greater attachment; coefficient alpha was .65 and .61 at waves 1 and 2,
Control variables. Consistent with previous research on self-control
theory, controls for age and sex are included in all analyses (Baron, 2003;
Hay, 2001; LaGrange and Silverman, 1999). Age was measured as a
continuous variable in years, and sex was coded 1 for males and 0 for
Table 1 presents the means, standard deviations, and correlation matrix
for the study variables. At the zero-order, there are significant associations
between most of the study variables. Table 1 suggests that self-control is
moderately stable between individuals. The rank-order correlation, which
tracks the degree to which people change ordinal position over time
(Clarke and Clarke, 1984), is .48 between low self-control at wave 1 and
wave 2 (p< .001). Low self-control is significantly related to all of the
study variables with the exception of sex and age (p< .01).
Table 1. Correlation Matrix for Study Variables (n = 754)
Mean SD 1 2 3 4 5 6 7 8 9 10
1. Low self-control
29.78 11.61
2. Low self-control
30.27 11.31 .48
3. Authoritative parenting
-.04 5.78 -.38
4. Authoritative parenting
.04 5.98 -.20
5. Delinquency
1.63 2.48 .35
6. Delinquency
2.86 3.14 .25
7. Sex (1= Male) .47 .50 .04 .02 -.08
-.06 .18
8. Age
11.03 .68 .08 .08 .01 -.08 -.08 .13
9. Deviant peers
4.33 4.69 .24
.01 .14
10. Prosocial peers
14.98 2.97 -.10
-.03 -.26
11. Attachment to teachers
6.35 1.73 -.18
-.01 -.10
Before turning to the results, it is worth noting that we replicated Hay’s
(2001) analysis to examine whether authoritative parenting substantially
improved the explanation of self-control in our data. The results (not
shown) indicated that authoritative parenting more than doubled the
explained variance in self-control at wave 1, from .08 to .20.8 Having
duplicated Hay’s (2001) finding, we assessed Gottfredson and Hirschi’s
prediction that the influence of parental efficacy (authoritative parenting)
on delinquent participation is completely mediated by low self-control.9
Tables 2 and 3 present a series of negative binomial regression models10
examining the mediating effects of self-control contemporaneously at
wave 1 as well as longitudinally with autoregressive models.11 Wave 1
8. Results of this analysis are available upon request.
9. Although downplayed in later versions of the theory (see Hirschi and Gottfredson
1993, 2001), opportunity factors are noted as influences on the specific behavioral
manifestations of self-control. Insofar as authoritative parenting is measuring
opportunity factors, which is plausible given that monitoring is one of the six scales
that comprise the measure, we would not expect the parenting measure to be fully
mediated by self-control. Hirschi and Gottfredson (1993; Hirschi, 1994), however,
downplay this possibility, arguing that for adolescents the opportunity to engage in
illegal activities is “limitless.” That said, if the measure of authoritative parenting at
wave 1 has an effect on the change in delinquency from wave 1 to wave 2, this
argument is moot. Opportunity factors at wave 2 are not affected by parental
monitoring at wave 1. In addition, the models were re-analyzed incorporating
monitoring at wave 2 and a modified version of the improvement in parenting
variable, which was calculated by taking the difference of the authoritative
parenting measures that did not incl ude monitoring. These results were roughly
equivalent (in both substantive content and significance levels) to the ones shown.
These results are available upon request.
10. For each distribution, the variance greatly exceeds the mean. Moreover, for all
models presented in table 5, we reject the null hypothesis (at p< .001) that the
residual variance parameter is 0, thus establishing that a negative binomial model
fits the data better than a Poisson model would (Long, 1997).
11. Given the advantages of autoregressive models (for example, capturing the
longitudinal link between constructs, attenuating the risk of e ndogenous bias), the
reader may be perplexed by our presentation of contemporaneous models along
with the longitudinal estimations. Although we believe the results from the
autoregressive models are more robust, the cross-sectional models strengthen the
conclusions that can be drawn for a couple of reasons. First and most important, a
longitudinal estimate is not a flawless pa nacea for the problems of cross-sectional
models. Some scholars contend that valid conclusions about parenting behaviors
can be derived only from cross-sectional analyses. For children at the life-stage of
those in our sample, the 2-year interval between waves could involve drastic
changes in outl ook, includi ng puberty, experiences, peer relations, parenting,
among other things. Relations that exist among contemporaneous measures could
be lost in the life that happened between waves. Moreover, Gottfredson and
measures are used in models 1 and 2 (table 2). The third and fourth
models assess the change in delinquency from wave 1 to 2 (table 3). In
these models, delinquency at wave 2 is regressed on delinquency,
authoritative parenting, and self-control at wave 1, the increases in
authoritative parenting (improvements in parenting) and increases in low
self-control (decreases in self-control) from wave 1 to wave 2, and the
controls for age and sex. The variables increase in self-control and increase
in authoritative parenting were created with the simple arithmetic process
of subtracting wave 1 self-control from wave 2 self-control and
authoritative parenting at wave 1 from its counterpart at wave 2,
respectively. This allows for a straightforward assessment of the influence
of improved or deteriorated parenting and self-control, while averting
multicollinearity between the repeated measures. For each model in tables
2 and 3, the first column displays the exponentiated unstandardized
coefficient with asterisks indicating the significance level, standard errors
are located in parentheses in the second, and the third column of each
model (%StdX) displays the percent change in the expected count for a
standard deviation increase net of other variables in the model.
Table 2. Negative Binomial Models Regressing Delinquency on Authoritative
Parenting and Low Self-Control at Wave 1 (n=754)
Outcome Variable: DelinquencyW1
Independent Variables Model 1 Model 2
e^ba SE %StdXbe^ba SE %StdXb
Sex (1= Male) 1.73*** (0.11) 31.5 1.77*** (0.10) 32.8
Age 1.40*** (0.06) 34.3 1.31*** (0.06) 26.7
Authoritative parenting W1 .92*** (0.01) -37.7 .95*** (0.01) -24.7
Low self-control W1 1.04*** (0.01) 53.1
LR test of = 0 621.96*** 468.28***
Chi-square 113.10*** 158.15***
a This column reports the exponentiated beta; also denoted as µ, it is the factor
change in the expected count for a unit increase in the independent variable, net of
other independent variables.
b This column presents the percentage change in the expected count for a standard
deviation increase in the independent variable, all other variables held constant.
Hirschi criticize longitudinal researchers for numerous reasons, including their
being “as likely as not to miss what we would consider the crucial period of life,
taking up their longitudi nal studies after the crucial differences in level of self-
control have been established” (1990: 229, emphasis in original). For these reasons,
we believe that a consistent result across contemporaneous and longitudinal models
augments the conclusions that could be drawn from either one of the two alone.
Across all of the models in tables 2 and 3, the control variables played a
similar role in the estimations. Being male and older were both associated
with a higher expected count of delinquency. Although the controls were
more strongly related to delinquency at wave 1 than wave 2, the
magnitude of their effects was not noticeably affected by the inclusion of
low self-control in the models. In model 1, the coefficient for authoritative
parenting is statistically significant in the expected direction. As predicted,
parental efficacy is negatively associated with delinquency in the first
wave, net of other factors (p< .01).
Table 3. Negative Binomial Models Regressing Delinquency on Authoritative
Parenting and Low Self-Control across Waves (n=754)
Outcome Variable: DelinquencyW2
Independent Variables Model 3 Model 4
e^ba SE %StdXbe^ba SE %StdXb
DelinquencyW1 1.13*** (0.02) 35.7 1.11*** (0.02) 30.5
Sex (1 = Male) 1.17* (0.07) 8.3 1.16* (0.07) 7.8
Age 1.09* (0.04) 8.0 1.09* (0.04) 7.6
Authoritative parentingW1 .94*** (0.01) -30.0 0.95*** (0.01) -24.9
Increase authoritative parentingW2 .94*** (0.01) -28.1 0.95*** (0.01) -25.0
Low self-controlW1 1.02*** (0.00) 21.3
Increase low self-controlW2 1.07*** (0.01) 23.7
LR test of = 0 348.20*** 304.41***
Chi-square 192.87*** 213.84***
a This column reports the exponentiated beta; also denoted as µ, it is the factor change
in the expected count for a unit increase in the independent variable, net of other
independent variables.
b This column presents the percentage change in the expected count for a standard
deviation increase in the independent variable, all other variables held constant.
Consistent with the general theory, model 2 reveals that low self-control
has a strong, statistically significant influence on delinquency. Holding
other variables constant, a standard deviation increase in low self-control
increases the expected count of delinquency by more than 50 percent.
According to Gottfredson and Hirschi (1990), self-control should fully
mediate the effect of parenting on delinquency. The results presented in
model 2 reveal partial support for their position. On the one hand, the
effect of authoritative parenting on delinquency is reduced by almost 35
percent. On the other hand, a standard deviation increase in authoritative
parenting directly decreases the expected count of delinquency by 24.7
percent (p< .001). Thus, contrary to the hypothesis that parenting
influences delinquency only through the narrow conduit of self-control,
authoritative parenting directly decreases the expected count of
delinquency, above its indirect effect on self-control at wave 1 when the
children are ages 10 to 12.
Turning to the results of the autoregressive models assessing the change
in delinquency across the two waves, model 3 reveals the enduring and
proximal effects of parental efficacy on delinquency. Authoritative
parenting at wave 1 as well as the increase in authoritative parenting at
wave 2 significantly reduce delinquency (p< .001). As shown in the fourth
column of model 3, the combined influence of authoritative parenting and
the increase in authoritative parenting on the change in delinquency is
larger than the influence of delinquency at wave 1 on wave 2 delinquency,
holding other factors constant. Standard deviation increases in the
measures of authoritative parenting significantly decrease the expected
count of delinquency by 30.0 percent and 28.1 percent compared to 35.7
percent for past delinquency. Turning to the fourth model, we can see that
low self-control once again has a significant positive effect on the change
in delinquency. Both low self-control at wave 1 and the increase in low
self-control significantly increase involvement in delinquency (b= .02 and
b= .063, respectively; p< .001). In contrast to Gottfredson and Hirschi’s
mediation hypothesis, however, wave 1 parenting and change measures of
authoritative parenting significantly diminish the expected count of
delinquency, even with self-control in the model. The coefficient for the
increase in authoritative parenting, for example, is mediated by less than
16 percent. These results suggest that a key proposition in Gottfredson
and Hirschi’s (1990) theory, specifically that parenting is a distal cause of
crime and that its effect should operate solely through self-control, does
not hold for these youth.
Gottfredson and Hirschi (1990) are clear in their assertions that
although within-individual levels of self-control may increase over time,
these levels should not decrease, and between-individual levels or rankings
on self-control should remain constant. We assessed this prediction in two
ways. First, we created quartiles of self-control at each wave. Group 1, for
example, is comprised of the individuals with the lowest 25 percent of the
scores on the low self-control measure (individuals with the highest self-
control), and group 4 consists of the individuals who scored above the 75th
percentile on the low self-control scale (individuals with the lowest self-
Next, we cross-tabulated these quartiles by wave. This basic method of
comparison provides a useful starting point for assessing the stability of
self-control across this relatively short period (2 years), when, according to
Gottfredson and Hirschi (1990), individual rankings of self-control should
already be set in stone. Although Gottfredson and Hirschi maintain that
individuals’ rankings on self-control should remain stable after ages 8 to
10, this assessment allows individuals to increase or decrease in their
relative rankings as long as they do so within their group of roughly 195
other individuals. Only those who move out of their groups are counted as
having changed in their levels of self-control. If the preponderance of
these adolescents remains in the same group at wave 2 as predicted by the
general theory, the theory’s claims of stability remain contested but are
supported.12 On the other hand, a finding that a substantial number of
individuals change groupings during the 2-year period is inconsistent with
the stability postulate. This is especially true given the conservative nature
of the test; recall that the children were between 10 to 12 years of age at
wave 1 and 12 to 14 at wave 2. Table 4 displays the results of the cross-
tabulation of the groups of self-control; wave 1 quartiles are displayed in
the rows, and wave 2 groups are listed in the columns.
Table 4. Examining the Between-Group Stability of Self-Control
Four Quartiles of Low Self-Control, Wave 2
Four Quartiles of Low
Self-Control, Wave 1 1 2 3 4 Totals
Self-control group 1a 90 60 39 13
44.6 29.7 19.3 6.4 202
Self-control group 2 56 52 48 29
30.3 28.1 26.0 15.7 187
Self-control group 3 38 42 62 53
18.5 21.5 31.8 27.2 195
Self-control group 4b 13 33 43 83
7.6 19.2 25.0 48.3
Total Frequency 197 187 192 178
Key = frequency/row%
a Group with highest 25 percent of self-control
b Group with lowest 25 percent of self-control
Note: Row percentages may not add to 100.0 due to rounding.
12. This paper’s test of the stability is relatively conservative given the only 2-year gap
between measures; therefore, a finding of stability will support self-control theory
but does not address the contentious issue of long-term stability.
As displayed on the diagonal, fewer than half of the adolescents
remained in the same group across the two waves. Not surprisingly, more
individuals in the highest and lowest groups of self-control in wave 1
remained in their groups at wave 2. Every group, however, experienced
major changes in individual members. That is, individuals’ rankings in self-
control were substantially altered between the two waves. Looking at the
group with the highest self-control in the first wave (the top left corner of
the table), more than 25 percent of those individuals moved to one of the
two groups with the lowest self-control at wave 2. At the other end of the
hierarchy of individual levels of self-control, approximately 7.6 percent of
those in the group with the lowest levels at wave 1 moved to the group
with the highest levels of self-control at wave 2. Instructively, groups 2 and
3 experienced lower stability than groups 1 and 4. Approximately 45
percent of those with the highest and lowest levels of self-control
remained in their respective groups; in contrast, only one-third of those in
the groups with the middle 50 percent of self-control remained in the same
group across the 2 years.
Although straightforward, the quartile comparison is problematic in
several ways.13 First, the boundaries between the four different groups are
arbitrary. More important, changes in groupings are affected not only by
the amount of change but also by the location of the individual within the
groups. That is, individuals near the boundaries of the quartiles may not
have experienced much change. To address these limitations and to gauge
the extent of movement both up and down the hierarchy of self-control,
we ranked the individuals in their levels of self-control at both waves and
examined the differences in ranking calculated by subtracting the youths’
wave 1 ranks from their rank at wave 2.
Analogous to the quartile comparison, the comparison of the rankings
across waves reveals substantial vacillation in between-individual rankings
in self-control. Youths on average moved 175 positions, in either direction,
in their ranking. Illustrating the extent of change, one female youth
accomplished the greatest decrease in rank moving from among the
highest in low self-control (number 729) at wave 1 to one of the lowest
ranks (24; only 23 individuals had higher self-control) just two years later.
In the other direction, the greatest increase in low self-control rank was
observed for a male who was ranked 8 out of 754 in the first wave and 731
at wave 2. We also examined the number and percent of individuals who
moved more than one standard deviation in rankings. Fifty-two percent, or
386 individuals, moved more than one standard deviation (142 ranks),
while slightly more than 21 percent moved more than two standard
deviations (moving up or down approximately 286 positions and over 38
13. Many thanks to the anonymous reviewer for pointing out these limitations.
percent of the sample). Finally, we examined the number and percent of
youths who increased or decreased fewer than seventy-five positions,
which is less than 10 percent of the sample. The comparison revealed that
only 231 individuals, or 31 percent of the sample, remained within seventy-
five positions of their wave 1 rank in self-control at wave 2.
The results presented in table 4 and the comparison of self-control
rankings across the two waves fail to support Gottfredson and Hirschi’s
(1990) strict stability postulate. Instead, these findings are consonant with
much of the psychological research on the stability of personality traits and
suggest that shifts in individual rankings of self-control are not the
exception, but the norm. Having discovered substantial changes in between-
individual rankings in self-control, we turn to investigating whether social
factors help explain within-individual changes in self-control. The following
analysis was conducted to assess whether parenting and social bonds to
conventional and unconventional individuals can shed light on changes in
self-control. Following the strength model of self-control (Baumeister,
Heatherton, and Tice, 1994), we predict that they can.
To predict the change in self-control, low self-control at wave 2 was
regressed on low self-control at wave 1 using ordinary least squares
regression. OLS regression was employed because the dependent variable
is continuous and normally distributed.14 In the first model, authoritative
parenting at wave 1 and the improvement in authoritative parenting were
used to predict and explain the changes in individual levels. Increases
deviant peers, pro-social peers, and attachment to teachers from wave 1 to
wave 2 were incorporated in model 2. Gottfredson and Hirschi (1990)
argue that these social factors are consequences of, and thus exert no
causal influence on, self-control. Although we cannot rule out reverse
causal ordering, controlling for wave 1 self-control and using change
scores diminishes the possibility that the causal path flows nonreciprocally
from self-control to social consequences.
The results displayed in table 5 indicate that parenting, deviant peers,
pro-social peers, and attachment to teachers are all independently and
significantly associated with changes in low self-control in the expected
directions. Model 1 provides evidence that improvements in parenting
strengthen self-control net of the effects of low self-control, authoritative
14. Skewness tests of low self-control at waves 1 and 2 indicate that neither measure is
significantly different from normality in skew (p > .25). In each model the first
column presents the unstandardized coefficient with asterisks indicating
significance, and the standard error and standardized coefficient are displayed in
the second and t hird columns, respectively.
parenting at wave 1, child’s age, and sex. Indeed, a standard deviation
improvement has a greater effect on the adolescents’ self-control when
they are aged 12 to 14 (at wave 2), than the measure of authoritative
parenting at wave 1 ( = -.30 compared to = -.27; p < .000).
Table 5. OLS Regressions Predicting the Change in Low Self-Control
Outcome Variable: Low Self-Control w2
Model 1 Model 2
Independent Variables bSE Std. bSE Std.
Low self-controlw1 .44*** (.04) .44 .46*** (.03) .46
Age .28 (.41) .02 .07 (.42) .01
Sex (1= Male) .74 (.71) .03 1.08 (.74) .05
Authoritative parenting w1 -.55*** (.07) -.27 -.52*** (.08) -.26
Increase in authoritative parenting w2 -.63*** (.07) -.30 -.48*** (.08) -.23
Increase deviant peers w2 .45
*** (.08) .19
Increase pro-social peers w2 -.25** (.09) -.08
Increase attachment to teachers w2 -.50*** (.17) -.10
Constant 13.67** (5.18) 14.73*** (4.96)
Adjusted R-square .34 .40
*p < .05; ** p < .01; *** p < .001; two-tailed tests.
Model 2 shows that increases in deviant peers, pro-social peers, and
attachment to teachers are significantly associated with the changes in low
self-control. As predicted, increases in attachment to teachers and
involvement with pro-social peers are associated with decreases in low
self-control, and affiliation with deviant peers is related to escalations in
low self-control. Moreover, authoritative parenting and the improvement
in authoritative parenting remain significantly associated with decreases in
low self-control (p< .001). Demonstrating the strength of the effects of
parenting after the formative years, the combined influence of a standard
deviation increase in both parenting measures exerts a greater effect on
low self-control at wave 2 than individuals’ self-control at wave 1. Thus,
both facets of this exploratory investigation yield significant and
substantively interesting results; social relationships and parenting explain
a substantial portion of the changes in individual levels of self-control.
These findings contrast starkly with Gottfredson and Hirschi’s (1990)
assertions that after the first 10 years of life parenting has no effect on
levels of self-control. In addition, the significant effects of deviant peers
and attachment to teachers suggests that social relationships with others
(conventional and unconventional) are not merely social consequences but
are associated with changes in self-control.
Gottfredson and Hirschi’s (1990) general theory challenged many
beliefs in the field, among them that social experiences beyond childhood
matter, and instigated a wealth of research on its clearly stated
propositions. In this study, we have examined two of these propositions
using longitudinal data from African American children and their primary
caregivers. Although the data certainly have weaknesses, the age of the
children and the two waves of data allowed for an examination of
understudied facets of self-control theory. Three important findings
emerged from this analysis, and they are briefly discussed below. This is
followed by a consideration of what these findings, as well as those from
other tests of self-control theory, suggest about the adequacy of the theory
and the modifications it may require to continue to play a central role in
criminological theory and research.
Gottfredson and Hirschi (1990) ascribe to parental child-rearing
practices a primary role in the development of self-control. According to
the general theory, however, parental efficacy should only affect
delinquency vis-à-vis its effects on self-control. In the present study, we
examined this claim. Consistent with the theory, lower self-control at wave
1 was strongly related to higher counts of delinquency measured
synchronously. Contrary to the general theory, however, authoritative
parenting continued to have a negative, direct effect on delinquency. In
addition, wave 1 and 2 predictors were used to assess wave 2 delinquency,
controlling for wave 1 delinquency. As before, low self-control
significantly augmented the expected count of delinquency, and parental
efficacy directly influenced delinquency. Specifically, authoritative
parenting as well as improvements in authoritative parenting, as reported
by both the children and primary caregivers, substantially lowered
involvement in delinquency, even after controlling for self-control.
Notably, Hirschi and Gottfredson (1993; see also 2000) have criticized
empirical tests of their theory based on attitudinal measures of self-
control, including the frequently used self-control scale that Grasmick and
colleagues (1993) developed. Despite the close match between most
nonbehavioral measures and the theory’s nominal definition of low self-
control, Hirschi and Gottfredson (1993) contend that the best measures of
low self-control are behaviorally based measures of previous acts
indicating low self-control. Although we utilized an attitudinal measure of
self-control in this study, the models assessing the change in delinquency
can be interpreted in an alternate way. Delinquency at wave 1 may be
considered a behavioral measure of self-control. Thus, strengthening these
findings, caregiver authoritative parenting and the change in parenting
significantly decrease delinquent participation, net of behavioral and
attitudinal measures of low self-control.
Assessing Gottfredson and Hirschi’s (1990) stability postulate was the
second goal of this study. Our results suggest that the assumption of
stability in between-individual rankings in self-control after age 10 is
unsound. Creating quartiles of self-control, we gave the stability postulate
a great chance of success. Individuals were allowed to change positions, as
long as they did so within their group of roughly 195 individuals, and
stability was assessed over a short span of 2 years. Despite the
conservative nature of this test, fewer than half of the individuals in the
study remained in the same self-control group at wave 2 as in wave 1. In
addition, we examined between-individual stability by comparing
individuals’ ranks at each wave. This comparison evinced that the changes
of low self-control are not simply an artifact of artificial thresholds or
ceiling effects, as changes in rankings occurred throughout the
distribution. Stated bluntly, self-control is not as stable as the theory
The final question we asked was whether changes in parenting and
social relationships explain a portion of the changes in self-control.
Consistent with the strength model of self-control (for example,
Baumeister, Heatherton, and Tice, 1994), the investigation into the
influence of social factors on levels of criminal propensity revealed
significant effects in the expected direction. Improvements in authoritative
parenting as well as increases in pro-social peers and attachment to
teachers were associated with decreases in low self-control.
Simultaneously, changes in deviant peer association predicted increases in
individuals’ low self-control. The influence of these social relationships on
self-control in the second wave occurred despite controls for earlier
parenting and self-control and explained a substantial portion of the
The rank-order stability in self-control reported in our study (r = .48) is
lower than might be expected, particularly given that the study covers only
2 years. Our findings, however, are consonant with existing research on
continuity and change in personality traits (for example, Caspi, Roberts,
and Shiner, 2005). For example, in their meta-analysis of the rank order
stability of personality traits, Fraley and Roberts (2005) found that test-
retest correlations increased from .41 in childhood to .55 at age 30 and
reached a plateau of .70 between ages 50 to 70, after increasing linearly
with time (see also Roberts and DelVecchio, 2000).
An additional concern with the evidence of (in)stability presented here
may arise from our use of a cognitive, self-report measure of self-control.
We would expect to find greater stability using a behavioral measure,
which is the preferred measure of Gottfredson and Hirschi (1990). Such an
approach, however, suffers from two related problems. The first is the
extensively debated issue of tautology (for example, Akers, 1991).
Predicting delinquency from past delinquency provides neither a satisfying
explanation nor a contribution to knowledge on the etiology of crime.
Second, and more important, delinquency measures of self-control lack
validity. At the present state of criminological knowledge, past
delinquency may indicate low self-control, but is just as likely to indicate,
for example, an aggressive, hostile view of relationships (Dodge, 1980,
1986), negative emotionality (Agnew, 1992; Agnew et al., 2002), or
definitions favorable to deviant behavior (Akers, 1977). In sum, we
disagree with scholars who believe that until “the measurement issue has
been solved,” research on the general theory is a “waste of time!”
(Marcus, 2004: 49). Rather, we believe there is much to be gained in
continuing to evaluate the general theory, even against the backdrop of a
measurement debate.
Although contradicting Gottfredson and Hirschi’s hypothesis, the
finding that self-control is malleable and responsive to social interactional
influences is good news. Rather than having to adjudge between being
optimistic or realistic, this study suggests that individuals manifesting low
self-control are not necessarily doomed to a present-oriented life with
concomitant social consequences and baggage. To be sure, although
change in between-individual rankings was the rule, approximate stability
was not exceptional. For example, almost 32 percent (231) of the children
in our sample remained within seventy-five positions of their initial rank in
self-control at wave 2. In regards to stability, then, the present results
concur with low self-control theory’s recognition of between-individual
stability, but also suggest that a general theory must attend to the
empirical reality of change.
Low self-control theory has earned commendation for its parsimony,
logical consistency, scope, and clearly stated propositions (Akers and
Sellers, 2004; Tittle, 1995). Research has demonstrated that low self-
control is consistently associated with deviant behavior, in a variety of
contexts, with a multitude of samples, and in competition with other
dominant theories (Akers and Sellers, 2004; Pratt and Cullen, 2000).
Recently scholars have examined facets of the theory beyond the low self-
control—crime-deviance relationship. In general, this research neither
consistently refutes nor supports low self-control theory. In the present
research, evidence was brought to bear on two propositions of the general
Overall, this study diverges from Gottfredson and Hirschi’s (1990)
formulae. It does not, however, suggest that the theory is unsound, nor
does it question the significance of self-control as a cause of delinquent
behavior. Notably, our study can be added to the voluminous list of
empirical evidence confirming the robust relationship between self-control
and delinquency. Gottfredson and Hirschi’s logical, parsimonious theory
encourages rigorous testing, thereby facilitating the identification aspects
of the explicans in need of refinement. In addition, their immodest claims
for the theory almost certainly set it up for criticism. Nonetheless, our
results, combined with those of various other studies, indicate that the
theory’s stance requires softening, and the propositions need to be
qualified (for example, Evans et al., 1997; Hay, 2001; Wright and Beaver,
2005; Unnever, Pratt, and Cullen, 2003).
We found that parental behavior influences an individual’s risk for
delinquency in more ways than simply through its impact on self-control.
Future research might therefore examine other factors that account for the
relationship between quality of parenting and delinquency. Other theories
have identified various psychosocial mechanisms whereby parenting
influences the probability of delinquency. Agnew’s general strain theory
(1992) and Colvin’s (2000) coercion theory both posit that poor parenting
generates anger in the child and that this emotional state increases the
chance of delinquency. A hostile view of relationships is the mediating
mechanism in Dodge’s (1980, 1986) biased attribution model. Dodge
contends that antisocial youth hold the view that people cannot be trusted
and thus adopt a confrontational style of interaction that leads to
aggression and delinquency. In short, it is important that future research
attend to the often overlooked, but important, processes through which
quality of parenting influences delinquency.
The findings of instability of individual rankings of self-control pose a
particular problem for the theory. Gottfredson and Hirschi’s (1990;
Hirschi, 2004; Hirschi and Gottfredson, 1993) assumption that between-
individual levels of self-control remain fixed after age 10 lies at the heart
of their theoretical scheme. The stability postulate also guides their
emphasis on parenting in early childhood and the irrelevance of social
Our results indicate that low self-control is neither solely an outcome of
parental control in the early years nor stable and insensitive to social
influences after age 10. It appears that the theory’s model is almost
certainly misspecified, if not incomplete. Apparently, low self-control is a
condition that can be improved through appropriate intervention and
social experiences. An important next step, insofar as the findings are
replicated with other samples and methods, is to identify specific factors
that catalyze or contribute to changes in self-control and to better
understand the processes through which this change occurs. The strength
model of self-control provides a compelling premise from which this
investigation might proceed. Instructively, this model has been largely
supported with experimental research; thus, its empirical adequacy in
nonexperimental settings and to criminal samples, for example, is not
known (but see Vohs, Baumeister, and Ciarocco, 2005). Longitudinal
studies are needed to examine these issues and investigate extensions of
the theory.
Sampson and Laub’s (1993) informal theory of social control provides
additional footing from which future work on temporal changes in
individuals’ levels in self-control may advance. Laub and Sampson (2003)
acknowledge that causation and selection models are not mutually
exclusive and recognize the tendency towards stability as well as the
possibility of change. Emphasizing the gradual buildup of investments and
disadvantage that tend to accrue over time, these scholars have focused
their attention on the impact of adult social bonds. Our findings indicate
that the development and modification of social bonds (informal social
controls) in adolescence may be important contributors to changes.
Notably, the changes in external factors contribute to variations in internal
controls. Giordano, Cernkovich, and Rudolph’s (2002) theory of cognitive
transformations, which is compatible with Sampson and Laub’s theory,
specifies the psychosocial mechanisms relating changes in social bonds to
cognitive and behavioral modifications. This recent specification of the
interplay between the individual and the social may prove valuable in
understanding the changes in self-control over the life course.
Interestingly, we found that individuals ranked in the middle 50 percent
of self-control changed groups more frequently than those in the highest
and lowest groups. It may be that those with intermediate levels of self-
control are more receptive to environmental catalysts, such as deviant
peers or attachment to parents and teachers, that influence the costs and
benefits of risk-taking behaviors and delayed gratification. Although
several pathways exist for future research to take, our results underscore
the importance of developing and investigating a theoretical framework
that recognizes stability of individuals’ behavior and personality while
acknowledging change processes.
Our contention that the general theory requires modification must be
tempered in light of various limitations associated with the study. Two
weaknesses, in particular, should be mentioned. First, the general theory
states that individual rankings of self-control depend on parenting
practices during a child’s first 8 years. The initial measures of parenting
were collected when the children were between ages 10 and 12. Although
our sample is younger than previous studies of Gottfredson and Hirschi’s
parenting postulate and incorporates measures of parenting from both the
target children and their caregivers, it might be that earlier manifestations
of low self-control influenced parenting. Such reciprocal parent–child
effects are well documented in the literature (see, for example, Stewart et
al., 2002). In addition, research on Gottfredson and Hirschi’s parenting
theses has assumed the temporal stability of child-rearing practices (Gibbs,
Giever, and Martin, 1998; Hay, 2001; Unnever, Pratt, and Cullen, 2003; but
see Feldman and Weinberger, 1994). Our findings not only suggest that
this assumption is questionable, but also that the changes in authoritative
parenting directly influenced levels of self-control and delinquency. It is
critical that future work investigate parenting and self-control with a
longitudinal sample of young children.
Second, these analyses were based on two waves of data with children
who were, at most, 5 years removed from the time the theory contends
between-individual rankings of self-control are fixed. It may be that levels
of self-control are set later than Gottfredson and Hirschi (1990) suggest,
though research suggests this alternate explanation is unlikely (see, for
example, Baumeister and Vohs, 2004). Similarly, the magnitude of change
and the influence of social factors on individuals’ levels of self-control may
attenuate as individuals move through adolescence into adulthood. It
would therefore be beneficial to track this sample and others across the
life course.
An additional caveat concerns this study’s generalizability; all of the
respondents were African Americans. Although it is not clear why this
would be the case, it is possible that the theoretical processes that account
for the development, stability, change, and manifestations of self-control
differ by racial-ethnic group. Moreover, this study focused on families
living in small cities in Iowa and Georgia, and the sample was therefore
not nationally representative. It is critical to replicate these analyses using
ethnically and geographically diverse samples.
Notwithstanding these limitations, these findings represent a useful
contribution to the body of empirical literature testing Gottfredson and
Hirschi’s theory. Despite the general theory’s strengths, this study
indicates that extensions and modifications of the theory are required if
the theory is to correspond to empirical reality. Clearly, more research on
the postulates addressed in this work is called for. Given the current
debate over stability and change, criminological theory would benefit from
an understanding of how variability in environments and specific social
factors influence within-individual levels of self-control over time.
Agnew, Robert. 1992. Foundation for a general strain theory of crime and
delinquency. Criminology 30:47–88.
Agnew, Robert, Timothy Brezina, John Paul Wright, and Francis T.
Cullen. 2002. Strain, personality traits, and delinquency: Extending
general strain theory. Criminology 40:43–72.
Akers, Ronald L. 1977. Deviant Behavior: A Social Learning Approach.
Belmont, CA: Wadsworth.
Akers, Ronald L. 1991. Self-control as a general theory of crime, review
essay. Journal of Quantitative Criminology 7:202–11.
Akers, Ronald L., and Christine S. Sellers. 2004. Criminological Theories:
Introduction, Evaluation, and Application. Los Angeles, CA: Roxbury.
Allison, Paul D. 1999. Multiple Regression. Thousand Oaks, CA: Sage
Amato, Paul R., and Frieda Fowler. 2002. Parenting practices, child
adjustment, and diversity. Journal of Marriage and Family 64:703–16.
American Psychiatric Association. 1994. Diagnostic and Statistical Manual
of Mental Disorders. Washington, DC: American Psychiatric
Arneklev, Bruce J., Harold G. Grasmick, Charles R. Tittle, and Robert J.
Bursik, Jr. 1993. Low self-control and imprudent behavior. Journal of
Quantitative Criminology 9:225–47.
Arneklev, Bruce J., Harold G. Grasmick, Charles R. Tittle, and Robert J.
Bursik, Jr. 1999. Evaluating the unidimensionality and invariance of
‘low self-control’. Journal of Quantitative Criminology 15:307–31.
Baron, Stephen W. 2003. Self-control, social consequences, and criminal
behavior: Street youth and the general theory of crime. Journal of
Research in Crime and Delinquency 40:403–35.
Baumeister, Roy F. 2002. Ego depletion and self-control failure: An
energy model of the self’s executive function. Self and Identity 1:129-36.
Baumeister, Roy F., and Julie Juola Exline. 1999. Virtue, personality, and
social relations: Self-control as the moral muscle. Journal of Personality
Baumeister, Roy F., and Kathleen D. Vohs. 2004. Handbook of Self-
Regulation: Research, Theory, and Applications. New York: Guilford
Baumeister, Roy F., Todd F. Heatherton, and Dianne M. Tice. 1994.
Losing Control: How and Why People Fail at Self-Regulation. San
Diego, CA: Academic Press.
Baumeister, Roy F., Mark Muraven, and Dianne M. Tice. 2000. Ego
depletion: A resource model of volition, self-regulation, and controlled
processes. Social Cognition 18:130–50.
Baumrind, Diana. 1966. Effects of authoritative parental control on child
behavior. Child Development 37:887–907.
Baumrind, Diana. 1991. The influence of parenting style on adolescent
competence and substance use. Journal of Early Adolescence 11:56–95.
Baumrind, Diana. 1996. Parenting: The discipline controversy revisited.
Family Relations 45:405–14.
Belsky, Jay, Sharon Woodworth, and Keith Crynic. 1996. Trouble in the
second year: Three questions about family interaction. Child
Development 67:556–78.
Berscheid, Ellen. 1986. Emotional experience in close relationships: Some
implications for child development. In Relationships and Development,
eds. Willard W. Hartup and Zick Rubin. Hillsdale, NJ: Lawrence
Erlbaum Associates.
Brody, Gene H., and Douglas L. Flor. 1997. Maternal psychological func-
tioning, family processes, and child adjustment in rural, single-parent,
African American families. Developmental Psychology 33:1000–11.
Brownfield, David, and Ann Marie Sorenson. 1993. Self-control and
juvenile delinquency: Theoretical issues and an empirical assessment of
selected elements of a general theory of crime. Deviant Behavior 4:243-
Burton, Velmer S., Francis T. Cullen, T. David Evans, Leanne Fiftal
Alarid, and R. Gregory Dunaway. 1998. Gender, self-control, and
crime. Journal of Research in Crime and Delinquency 35:123–47.
Caspi, Avshalom, Brent W. Roberts, and Rebecca L. Shiner. 2005.
Personality development: Stability and change. Annual Review of
Psychology 56:453–84.
Clarke, A.D.B., and A. M. Clarke. 1984. Constancy and change in the
growth of human characteristics. Journal of Child Psychology and
Psychiatry 25:191–210.
Cohen, Lawrence E., and Bryan J. Vila. 1996. Self-control and social
control: An exposition of the Gottfredson-Hirschi/Sampson-Laub
debate. Studies on Crime and Crime Prevention 5:125–50.
Colvin, Mark. 2000. Crime and Coercion: An Integrated Theory of Chronic
Criminality. New York: St. Martin’s Press.
Conger, Rand D., Glen H. Elder, Frederick O. Lorenz, Ronald L. Simons,
and Leslie B. Whitbeck. 1992. A family process model of economic
hardship and influences on adjustment of early adolescent boys. Child
Development 63:526–41.
Crockenberg, Susan, and Cindy Litman. 1991. Effects of maternal
employment on maternal and two-year-old child behavior. Child
Development 62:930–53.
Dodge, Kenneth A. 1980. Social cognition and children’s aggressive
behavior. Child Development 51:162–70.
Dodge, Kenneth A. 1986. Social Competence in Children. Chicago:
University of Chicago Press.
Dornbusch, Sanford M., Philip L. Ritter, P. Herbert Liederman, Donald F.
Roberts, and Michael J. Fraleigh. 1987. The relation of parenting style
to adolescent school performance. Child Development 58:1244–257.
Elliott, Delbert. S., David. Huizinga, and Scott Menard. 1989. Multiple
Problem Youth: Delinquency, Substance Use, and Mental Health
Problems. New York: Springer-Verlag.
Evans, T. David, Francis T. Cullen, Velmer S. Burton, R. Gregory
Dunaway, and Michael L. Benson. 1997. The social consequences of
self-control: Testing the general theory of crime. Criminology 35:475–
Feldman, S. Shirley, and Daniel A. Weinberger. 1994. Self-restraint as a
mediator of family influences on boys’ delinquent behavior: A
longitudinal study. Child Development 65:195–211.
Fraley, R. Chris, and Brent W. Roberts. 2005. Patterns of continuity: A
dynamic model for conceptualizing the stability of individual
differences in psychological constructs across the life course.
Psychological Review 112:60–74.
Furman, Wyndol, Lauren Jones, Duane Buhrmester, and Tama Adler.
1989. Children’s, parents’, and observers’ perspectives on sibling
relationships. In Sibling Interaction across Cultures: Theoretical and
Methodological Issues, ed. R. G. Zukow. New York: Springer-Verlag.
Gibbs, John J., and Dennis Giever. 1995. Self-control and its
manifestations among university students: An emprical assessment of
Gottfredson and Hirschi’s general theory. Justice Quarterly 12:231–55.
Gibbs, John J., Dennis Giever, and J. S. Martin. 1998. Parental
management and self-control: An empirical test of Gottfredson and
Hirschi’s general theory. Journal of Research in Crime and Delinquency
Giordano, Peggy C., Stephen A. Cernkovich, and Jennifer L. Rudolph.
2002. Gender, crime, and desistance: Toward a theory of cognitive
transformation. American Journal of Sociology 107:990–1064.
Gottfredson, Michael R., and Travis Hirschi. 1990. A General Theory of
Crime. Palo Alto, CA: Stanford University Press.
Grasmick, Harold G., Charles R. Tittle, Robert J. Bursik, Jr., and Bruce J.
Arneklev. 1993. Testing the core implications of Gottfredson and
Hirschi’s general theory of crime. Journal of Research in Crime and
Delinquency 30:5–29.
Gray, Marjory Roberts, and Laurence Steinberg. 1999. Unpacking
authoritative parenting: Reassessing a multidimensional construct.
Journal of Marriage and the Family 61:574–87.
Hay, Carter. 2001. Parenting, self-control, and delinquency: A test of self-
control theory. Criminology 39:707–36.
Higgins, E. Tory, and Scott Spiegel. 2004. Promotion and prevention
strategies for self-regulation: A motivated cognition perspective. In
Self-Regulation: Theory, Research, and Applications, eds. R. F.
Baumeister and K. D. Vohs. New York: The Guilford Press.
Hirschi, Travis. 1994. Family structure and crime. In When Families
Fail...The Social Costs, ed. Bryce L. Christensen. Lanham, MD:
Rowman and Littlefield.
Hirschi, Travis. 2004. Self-control and crime. In The Handbook of Self-
Regulation: Theory, Research, and Applications, eds. R. E. Baumeister
and K. D. Vohs. New York: Guilford Press.
Hirschi, Travis, and Michael R. Gottfredson. 1993. Commentary: Testing
the general theory of crime. Journal of Research in Crime and
Delinquency 30:47–54.
Hirschi, Travis, and Michael R. Gottfredson. 1995. Control theory and the
life-course perspective. Studies on Crime and Crime Prevention 4:131–
Hirschi, Travis, and Michael R. Gottfredson. 2000. In defense of self-
control. Theoretical Criminology 4:55–69.
Hirschi, Travis, and Michael R. Gottfredson. 2001. Self-control theory. In
Explaining Criminals and Crime, eds. Raymond. Paternoster and Ronet
Bachman. Los Angeles: Roxbury Press.
Jencks, Christopher, and S. E. Mayer. 1990. The social consequences of
growing up in a poor neighborhood. In Adolescents at Risk: Medical
and Social Perspectives, eds. David E. Rogers and Eli Ginzberg.
Boulder, CO: Westview Press.
Johnson, Wendy, Matt McGue, and Robert F. Krueger. 2005. Personality
stability in late adulthood: A behavioral genetic analysis. Journal of
Personality 73:523–52.
LaGrange, Teresa C., and Robert A. Silverman. 1999. Low self-control
and opportunity: Testing the general theory of crime as an explanation
for gender differences in delinquency. Criminology 37:41–72.
Laub, John H., and Robert J. Sampson. 2003. Shared Beginnings,
Divergent Lives: Delinquent Boys at Age 70. Boston, MA: Harvard
University Press.
Long, J. Scott. 1997. Regression Models for Categorical and Limited
Dependent Variables. Thousand Oaks, CA: Sage Publications.
Long, J. Scott, and Jeremy Freese. 2003. Regression Models for Categorical
Dependent Variables Using Stata, rev. ed. College Station, TX: Stata
Marcus, Bernd. 2004. Self-control in the general theory of crime:
Theoretical implications of a measurement problem. Theoretical
Criminology 8:33-55.
Mischel, Walter, Nancy Cantor, and S. Shirley Feldman. 1996. Principles
of self-regulation: The nature of will-power and self-control. In Social
Psychology: Handbook of Basic Principles, eds. E. T. Higgins and A.
W. Kruglanski. New York: The Guilford Press.
Muraven, Mark, Roy F. Baumeister, and Dianne M. Tice. 1999.
Longitudinal improvement of self-regulation through practice: Building
self-control through repeated exercise. Journal of Social Psychology
Muraven, Mark, Dianne M. Tice, and Roy F. Baumeister. 1998. Self-
control as a limited resource: Regulatory depletion patterns. Journal of
Personality and Social Psychology 74:774–89.
Murphy, Bridget C., Nancy Eisenberg, Richard A. Fabes, Stephanie
Shepard, and Ivanna K. Guthrie. 1999. Consistency and change in
children’s emotionality and regulation: A longitudinal study. Merrill-
Palmer Quarterly 45:413–44.
Nagin, Daniel S., and Raymond Paternoster. 1993. Enduring individual
differences and rational choice theories of crime. Law and Society
Review 27:467–96.
Olson, D.H.L. 1977. Insiders’ and outsiders’ views of relationships:
Research studies. In Close Relationships: Perspectives on the Meaning
of Intimacy, eds. George Levinger and Harold L. Rausch. Amherst:
University of Massachusetts Press.
Patterson, Gerald R., John B. Reid, and Thomas J. Dishion. 1992.
Antisocial Boys. Eugene, OR: Castilia.
Perrone, Dina, Christopher J. Sullivan, Travis C. Pratt, and Satenik
Margaryan. 2004. Parental efficacy, self-control, and delinquency: A
test of a general theory of crime on a nationally representative sample
of youth. International Journal of Offender Therapy and Comparative
Criminology 48:298–312.
Polakowski, Michael. 1994. Linking self- and social control with deviance:
Illuminating the structure underlying a general theory of crime and its
relation to deviant activity. Journal of Quantitative Criminology 10:41–
Power, Thomas G., and M. Lynn Chapieski. 1986. Child-rearing and
impulse control in toddlers: A naturalistic investigation. Developmental
Psychology 22:271–75.
Pratt, Travis C., and Francis T. Cullen. 2000. The empirical status of
Gottfredson and Hirschi’s general theory of crime: A meta-analysis.
Criminology 38:931–64.
Raffaelli, Marcela, Lisa J. Crockett, and Yuh Ling Shen. 2005.
Developmental stability and change in self-regulation from childhood
to adolescence. The Journal of Genetic Psychology 166:54–75.
Rankin, Joseph H., and Roger Kern. 1994. Parental attachments and
delinquency. Criminology 32:495–515.
Roberts, Brent W., and Wendy F. DelVecchio. 2000. The rank-order
consistency of personality traits from childhood to old age: A
quantitative review of longitudinal studies. Psychological Bulletin
Sampson, Robert J., and John H. Laub. 1993. Crime in the Making:
Pathways and Turning Points Through Life. Cambridge, MA: Harvard
University Press.
Sampson, Robert J., and John H. Laub. 1995. Understanding variability in
lives through time: Contributions of life-course criminology. Studies on
Crime and Crime Prevention 4:143–58.
Schaffer, David, Prudence Fisher, John D. Piacentini, C. Keith Conners,
Mary Schwab-Stone, Patricia Cohen, and Darrell Regier. 1993. The
Diagnostic Interview Schedule for Children-Revised Version (DISC-
R): Preparation, field testing, inter-rater reliability, and acceptability.
Journal of the American Academy of Child and Adolescent Psychiatry
Schmeichel, Brandon J., and Roy F. Baumeister. 2004. Self-regulatory
strength. In Self-Regulation: Theory, Research, and Applications, eds. R.
F. Baumeister and K. D. Vohs. New York: The Guilford Press.
Simons, Ronald L., and Associates. 1996. Understanding Differences
between Divorced and Two-Parent Families. Thousand Oaks, CA: Sage
Simons, Ronald L., Leslie Gordon Simons, and Lora Ebert Wallace. 2004.
Families, Delinquency, and Crime: Linking Society’s Most Fundamental
Social Institution to Antisocial Behavior. Los Angeles, CA: Roxbury.
Simons, Ronald L., Wei Chao, Rand D. Conger, and Glen H. Elder. 2001.
Quality of parenting as mediator of the effect of childhood defiance on
adolescent friendship choices and delinquency: A growth curve
analysis. Journal of Marriage and the Family 63:63–79.
Simons, Ronald L., Leslie Gordon Simons, Callie Harbin Burt, Gene H.
Brody, and Carolyn Cutrona. 2005. Collective efficacy, authoritative
parenting, and delinquency: A longitudinal test of a model integrating
community- and family-level processes. Criminology 43:989–1030.
Steinberg, Laurence, J. D. Elmen, and Nina Mounts. 1989. Authoritative
parenting, psychosocial maturity, and academic success in adolescents.
Child Development 60:1424-436.
Steinberg, Laurence, Susie D. Lamborn, Sanford M. Dornbusch, and
Nancy Darling. 1992. Impact of parenting practices on adolescent
achievement: Authoritative parenting, school involvement, and
encouragement to succeed. Child Development 63:1266–281.
Steinberg, Laurence, Nina Mounts, Susie D. Lamborn, and Sanford M.
Dornbusch. 1991. Authoritative parenting and adolescent adjustment
across various ecological niches. Journal of Research on Adolescence
Stewart, Eric A., Ronald L. Simons, Rand D. Conger, and C. Scaramella.
2002. Beyond the interactional relationship between delinquency and
parenting practices: The contribution of legal sanctions. Journal of
Research in Crime and Delinquency 39:36–59.
Strayhorn, Joseph M., Jr. 2002. Self-control: Theory and research. Journal
of the American Academy of Child & Adolescent Psychiatry 41:7–16.
The NICHD, Early Child Care Research Network. 1998. Early child care
and self-control, compliance, and problem behavior at twenty-four and
thirty-six months. Child Development 69:1145–170.
Tittle, Charles R. 1995. Control Balance: Toward a General Theory of
Deviance. Boulder, CO: Westview Press.
Tittle, Charles R., and Ekaterina V. Botchkovar. 2005. Self-control,
criminal motivation and deterrence: An investigation using Russian
respondents. Criminology 43:307–54.
Trembley, Richard E., Bernard Boulerice, L. Arnseneault, and Marianne
Junger Niscale. 1995. Does low self-control during childhood explain
the association between delinquency and accidents in early
adolescence? Criminal Behaviour and Mental Health 5:439–51.
Turner, Michael G., and Alex R. Piquero. 2002. The stability of self-
control. Journal of Criminal Justice 30:457–71.
Unnever, James D., Travis C. Pratt, and Francis T. Cullen. 2003. Parental
management, ADHD, and delinquent involvement: Reassessing
Gottfredson and Hirschi’s general theory. Justice Quarterly 20:471–500.
Vazsonyi, Alexander T., and Jennifer M. Crosswhite. 2004. A test of
Gottfredson and Hirschi’s general theory of crime in African American
adolescents. Journal of Research in Crime and Delinquency 41:407–32.
Vohs, Kathleen D., Roy E. Baumeister, and Natalie J. Ciarocco. 2005.
Self-regulation and self-presentation: Regulatory resource depletion
impairs impression management and effortful self-presentation depletes
regulatory resources. Journal of Personality and Social Psychology
Wills, Thomas Ashby, John Mariani, and Marnie Filer. 1996. The role of
family and peer relationships in adolescent substance use. In Handbook
of Social Support and the Family, eds. G. R. Pierce, B. R. Sarason, and
I. G. Sarason. New York: Plenum Press.
Wood, Peter B., Betty Pfefferbaum, and Bruce J. Arnkelev. 1993. Risk-
taking and self-control: Social psychological correlates of delinquency.
Journal of Crime and Justice 16:111–30.
Wright, John Paul, and Kevin Beaver. 2005. Do parents matter in creating
self-control in their children? A genetically informed test of
Gottfredson and Hirschi’s theory of low self-control. Criminology
Callie Harbin Burt is a doctoral candidate in the Department of
Sociology at the University of Georgia. Her research interests include
criminological theory, research methodologies, and links between family
and community processes and crime. In other current projects, she
examines the role of gender in delinquency and tests an elaboration of
Blackian legal theory. Callie has received awards from the American
Society of Criminology and the American Sociological Association for her
research as a graduate student.
Ronald L. Simons is Distinguished Professor of Research in the
Department of Sociology and research fellow in the Institute for
Behavioral Research at the University of Georgia. His research examines
the manner in which community factors, family interaction, and peer
processes combine to influence psychological adjustment and antisocial
behavior across the life course. He has published widely including
Families, Delinquency, and Crime: Linking Society’s Most Basic Institution
to Antisocial Behavior, co-authored with Leslie Simons and Lora Wallace,
Roxbury Press, 2004.
Leslie Gordon Simons is assistant professor of child and family
development at the University of Georgia. Her research investigates the
effect of family structure, parenting practices, community processes, and
religion on adolescent outcomes such as conduct problems, depression,
and risky sexual behaviors.
Here are some things that people may say about themselves. Please tell
me if the statement is not at all true, somewhat true, or very true for you.
1. You could do something most people would consider dangerous like
driving a car fast.
2. You would prefer doing something dangerous rather than sitting
3. You enjoy taking risks.
4. You would enjoy fast driving.
5. You would do almost anything for a dare.
6. Life with no danger would be dull for you.
7. When you promise to do something, people can count on you to do it.*
8. You can deliberately calm down when you are excited or “wound up”.*
9. When you ask a question, you often jump to something else before
getting an answer.
10. You stick with what you’re doing until you’ve finished with it.*
11. You have to have everything right away.
12. When you have to wait in line, you do it patiently.*
13. You usually sit still in class.*
14. You have to be reminded several times to do things.
15. You have a lot of accidents.
16. You would rather have a small gift today than a large gift tomorrow.
17. You bother other students when they’re trying to work.
18. You are easily distracted from your schoolwork.
19. You could be described as careless.
20. You like to switch from one thing to another.
21. If you find that something is really difficult, you get frustrated and quit.
22. You usually think before you act.*
23. You prefer to concentrate on one thing at a time.*
24. You can’t stay still for long.
25. You move around a lot.
26. If you have to stay in one place for a long time, you get very restless.
27. Even when you are supposed to sit still, you get very fidgety after a few
28. You keep working at a task until it is finished.*
29. Once you are involved in a task, nothing can distract you from it.*
30. You stay with an activity for a long time.*
31. You get upset easily.
32. You often feel frustrated.
33. When things don’t go right, you can get pretty upset.
34. You often get irritated at things.
35. You never seem to stop moving.
36. You often have days when you find it difficult to do your schoolwork.
37. You like to switch from one thing to another.
38. You never seem to be in the same place for long.
39. You are usually a “calm person” and don’t get upset easily.*
* Items reverse coded in scoring.
† These items were adapted from various sources, including the Kendall-Wilcox
inventory (Kendall and Williams, 1982; Wills, Vaccaro, and McNamara, 1994), the
inventory of Eysenck and Eysenck (1977), the Dimensions of Temperament
Survey (Windle and Lerner, 1986), and the EAS Inventory (Buss and Plomin,
In the past 12 months when you and your [PC name] have spent time
talking or doing things together, how often did your PC:
1. Help you do something that was important to you?*
2. Let you know he_she really cares about you?*
3. Listen carefully to your point of view?*
4. Act supportive and understanding toward you?*
5. Act loving and affectionate toward you?*
6. Have a good laugh with you about something that was funny?*
7. Let you know that he_she appreciates you, your ideas or the things you
8. Tell you he_she loves you?*
9. Understand the way you feel about things?*
1. Get angry at you?
2. Get so mad at you that he_she broke or threw things?
3. Shout or yell at you because he_she was mad at you?
4. Threaten to hurt you physically?
5. Criticize you or your ideas?
6. Push, grab, hit, or shove you?
7. Argue with you whenever you disagree about something?
8. Slap or hit you with his_her hands?
9. Strike you with an object?
10. Boss you around a lot?
11. Throw things at you?
12. Insult or swear at you?
13. Tell you he_she is right and you are wrong about things.
14. Give you a lecture about how you should behave?
1. How often does your [PC name] know what you do after school?*
2. How often does your [PC name] know where you are and what you are
3. How often does your [PC name] know how well you are doing in
4. How often does your [PC name] know if you do something wrong?*
5. How often can you do whatever you want after school without your
[PC name] knowing what you are doing?
1. How often would you be disciplined at home if your [PC name] knew
you broke a school rule?*
2. When your [PC name] asks you to do something and you don’t do it
right away, how often does he_she discipline you?*
3. When your [PC name] tells you to stop doing something and you don’t
stop, how often does he_she discipline you?*
4. When you do something wrong and your [PC name] decides on a type
of discipline, how often can you get out of it?
5. How often does your [PC name] discipline you for something at one
time and then at other times not discipline you for the same thing?*
6. When your [PC name] disciplines you, how often does the type of
discipline you get depend on his_her mood?
1. How often does your [PC name] ask what you think before deciding on
family matters that involve you?*
2. How often does your [PC name] give you reasons for his_her
3. How often does your [PC name] ask you what you think before making
a decision about you?*
4. When you don’t understand why your [PC name] makes a rule for you
to follow how often does he_she explain the reason?*
5. How often does your [PC name] discipline you by reasoning,
explaining, or talking to you?*
1. On a weekly basis, how often do you and your [PC name] have serious
2. How often do the same problems between you and your [PC name]
come up again and again and never seem to get solved?
3. When you and your [PC name] have a problem, how often can the two
of you figure out how to deal with it?
4. How often do you talk to your [PC name] about things that bother
1. How often does your [PC name] give you a reward like money, or
something you would like, when you get good grades, do your chores,
or something like that?*
2. When you do something your [PC name] likes or approves of, how
often does he_she let you know he_she is pleased about it?*
† The items presented are taken from the target children surveys; unless otherwise
noted, the same items were reworded for the primary caregivers. The reworded
questions are not presented due to brevity concerns.
*Items reverse coded in scoring.
**The items in these subscales were only included in the target children’s
... Based on multiple meta-analyses, there is consistent support for the positive association between low self-control and deviance (De Ridder et al. 2012;Duckworth and Kern 2011;Vazsonyi et al. 2017). Research findings, however, are more nuanced regarding the relevance of parenting for developing child self-control Chapple et al. 2010;Meldrum 2008;Wright and Beaver 2005) and the relative stability of self-control (Burt et al. 2006;Hay and Forrest, 2006;Forrest et al. 2019). ...
... While few studies testing self-control theory have included explicit measures of parental attachment toward children as predictive of later parenting practices and subsequent self-control, many more have investigated the influence of parenting practices, often measured as a composite of different aspects, on self-control (Botchkovar et al. 2015;Burt et al. 2006;Hay 2001; see also a review by Cullen et al. 2008). For instance, Vazsonyi and Huang (2010) analyzed self-control trajectories in a sample of 1,155 children who participated in the NICHD SECCYD over 6 years, beginning at 4.5 years of age and ending at 10.5 years of age. ...
... While Gottfredson and Hirschi (1990) were explicit in their definitions of effective child rearing, few studies have successfully incorporated distinct measures of attachment, monitoring/supervision, and clear and consistent discipline. As many of the items used to measure parenting constructs are often highly correlated, global measures often have been employed (Botchkovar, et al. 2015;Burt et al. 2006;Hay 2001Perrone et al. 2004). It remains unclear as to how global versus separate measures of attachment, monitoring, and disciplinary practices, for example, may impact the estimation of parenting effects on child self-control. ...
Full-text available
Purpose: Research surrounding the intergenerational transmission of self-control has expanded recently. Yet, findings are mixed, and key limitations regarding the inclusion of distinct measures of parental attachment toward children and parenting practices within a longitudinal framework remain. We seek to address these limitations by providing a longitudinal test of serial mediation linking maternal low self-control, maternal attachment toward children, maternal parenting practices, and adolescent low self-control. Methods: We employed structural equation modeling to examine direct and indirect effects between maternal low self-control measured when children were six months-old, maternal attachment toward children measured when target children were seven years old, maternal parenting practices assessed when children were twelve years-old, and adolescent low self-control when children were fifteen years old. Results: Findings partially support assertions from self-control theory in that maternal low self-control was positively related to later adolescent low self-control indirectly via maternal attachment toward children and, in turn, maternal parenting practices. However, direct associations between maternal low self-control and maternal parenting practices and, even more, between maternal low self-control and adolescent low self-control, were also observed. Limitations and implications of our findings are discussed.
... (Glaser, 1964 (Gottfredson & Hirschi, 1990). In mehreren Studien konnte die Grundannahme der General Theory of Crime, wonach kriminelles Verhalten durch eine Interaktion zwischen geringer Selbstkontrolle und der Gelegenheit zu kriminellem Verhalten entsteht, bestätigt werden (Burt, Simons & Simons, 2006;DeLisi & Vaughn, 2008;Grasmick et al., 1993;Pratt & Cullen, 2000;Siegfried & Woessner, 2016). ...
... Theoretisch und empirisch wurden die Annahmen der General Theory of Crime von Gottfredson und Hirschi (1990) (Piquero & Bouffard, 2007). Auch die von Gottfredson und Hirschi (1990) (Pratt & Cullen, 2000) und eine einmal entwickelte geringe Selbstkontrolle instabiler und durch spätere soziale Einflüsse und Beziehungen beeinflussbarer ist, als in der General Theory of Crime angenommen (Burt et al., 2006). ...
... Darüber hinaus existieren empirische Hinweise, dass der Einfluss der Möglichkeit zu kriminellem Verhalten von Gottfredson und Hirschi (1990) Selbstkontrolle hin zu deviantem Verhalten konnte nicht durchgängig empirisch belegt werden (Burt et al., 2006;Siegfried & Woessner, 2016 (Hirschi, 2004). Die in der ursprünglichen Theorie beschriebene Selbstkontrolle wird mit dem in der modifizierten Theorie postulierten Konzept sozialer Kontrolle mitunter als nahezu deckungsgleich erachtet (Ward, Boman & Jones, 2015 (Ward et al., 2015). ...
Mitgefangen. Seltener im Fokus der Aufmerksamkeit, aber oftmals von einer Haftstrafe in ähnlichem Ausmaß betroffen wie Inhaftierte selbst, sind deren Partnerinnen. Aus unterschiedlichen Blickwinkeln und unter Rückgriff auf Erkenntnisse der Rechts-, Entwicklungs- und Partnerschaftspsychologie beleuchtet diese Studie Licht- und Schattenseiten, die die Inhaftierung des Lebenspartners für Frauen mit sich bringt. Um die Umstände dieser sehr außergewöhnlichen Lebens- und Beziehungssituation abzubilden, kommen neben validierten Fragebogeninstrumenten stichprobenspezifische und für diese Studie konzipierte Fragebögen zum Einsatz, die faktoren- und reliabilitätsanalytisch geprüft werden und sich als tauglich für den intendierten Zweck erweisen. Das psychische Belastungserleben, die Lebenszufriedenheit und die Partnerschaftszufriedenheit stellen die Kriteriumsvariablen regressionsanalytisch geprüfter Hypothesen dar, zeigen sich teilweise durch das Ausmaß erlebter negativer Haftfolgen ungünstig beeinflusst, bedingen sich mitunter aber auch gegenseitig. Dass das Ausmaß einiger abträglicher Effekte auf die verwendeten Kriteriumsvariablen durch verschiedene Ressourcen und Bewältigungsmodi tendenziell abgeschwächt werden kann, belegen durchgeführte Interaktionsanalysen. Nach einer kritischen Diskussion der Einschränkungen der Fragebogenstudie kommen im Rahmen qualitativer Interviews betroffene Personen zu Wort, deren Berichte das breite Spektrum von Herausforderungen, aber auch förderlichen Entwicklungen im Kontext der Inhaftierung ihres Partners bzw. ihrer Partnerin verdeutlichen.
... An extensive number of studies have examined the effect of low self-control on crime and delinquency, and some researchers have turned their attention to the stability purported to be characteristic of low self-control (Gottfredson & Hirschi, 1990). Previous researchers have noted mixed support for the supposition that low self-control remains stable across a person's lifecourse (Burt, Simons, & Simons, 2006;Hay & Forrest, 2006;Na & Paternoster, 2012;Turner & Piquero, 2002). ...
... However, by late adolescence both Anderson (1999) and Gottfredson & Hirschi (1990) have suggested that street code adherence and low self-control should be fairly stable. Despite these theorists suggestions, previous research on street code adherence has provided evidence that decreases in street code adherence is more common in late adolescence than Anderson suggested Moule et al., 2015), and prior investigations have provided mixed support for the stability of low self-control (Burt, Simons, & Simons, 2006;Hay & Forrest, 2006;Na & Paternoster, 2012;Turner & Piquero, 2002). No prior research has examined the relative stability of street code adherence and low self-control and their reciprocal effects on each other over time. ...
Full-text available
The code of the street and low self-control are prominent theories of crime. However, there is no research that examines if these criminogenic dispositions inform each other over time. We utilize the G.R.E.A.T. data to analyze the development of street code adherence and low selfcontrol longitudinally. We find a portion of the stability associated with street code adherence and low self-control to be a product of measurement, as evidenced by correlating error terms across waves. Additionally, we find low self-control to be related to increases in street code adherence especially in later waves and, to a lesser extent, we show effects of street code adherence on subsequent levels of low selfcontrol. We also discuss results from analyses split by race, gender, and neighborhood type. We discuss the theoretical implications of our findings and argue for the development and utility of a broad measure of criminal propensity.
... Although the general theory of crime originally proposed that self-control was established early in life and that levels of self-control remained relatively stable throughout one's life (Gottfredson & Hirschi, 1990), recent research has provided evidence for within-individual variability in selfcontrol over time (Burt et al., 2006;Hay & Forrest, 2006;Higgins et al., 2009;Ray et al., 2013). In addition, changing circumstances (e.g., parental socialization, exposure to prosocial, or deviant peers) may explain changes in self-control in adolescence (Burt et al., 2006;Hay & Forrest, 2006;Ray et al., 2013). ...
... Although the general theory of crime originally proposed that self-control was established early in life and that levels of self-control remained relatively stable throughout one's life (Gottfredson & Hirschi, 1990), recent research has provided evidence for within-individual variability in selfcontrol over time (Burt et al., 2006;Hay & Forrest, 2006;Higgins et al., 2009;Ray et al., 2013). In addition, changing circumstances (e.g., parental socialization, exposure to prosocial, or deviant peers) may explain changes in self-control in adolescence (Burt et al., 2006;Hay & Forrest, 2006;Ray et al., 2013). Thus, if self-control is related to offending, and individuals' self-control can improve, then it remains possible that improvements in self-control or related characteristics could be related to decreased risk of offending. ...
The goal of the current study was to investigate the relationships between observer-rated skills related to emotional and cognitive regulation post-admission and pre-release in a secure facility and official records of juvenile felony recidivism up to 1 year after release. Data came from a sample of 599 youth in a residential facility in Washington state (84% male; 38% White). Latent change score models indicated that both initial level of emotional regulation skills and improvement in emotion regulation skills while incarcerated were significantly related to lower recidivism. This pattern of findings remained when controlling for length of stay, among other covariates. Follow-up analyses indicated that the results for emotion regulation skills might be driven primarily by monitoring internal and external triggers. Additional research should investigate the connection between emotion regulation skills and juvenile recidivism, with a special focus on trigger monitoring and how to improve those skills.
... This section reviews research on the possibility that peers influence one another's impulsivity and uses the framework of our conceptual path model to explore the potential consequences for individual delinquency. Early research examining the development of self-control centered on the family (e.g., Burt et al. 2006;Hay and Forrest 2006), consistent with Gottfredson and Hirschi's (1990) position emphasizing the role of parents. During adolescence, however, the amount of time spent with parents decreases, as adolescents spend more time with their peers (Felson and Gottfredson 1984;Larson and Richards 1991;Larson et al. 1996), and this increased exposure may provide peers sufficient opportunity to become a meaningful influence on personality characteristics such as impulsivity, represented as path A in Fig. 1. ...
Full-text available
Objectives Drawing on criminological research about peer delinquency and self-control, we employ a network perspective to identify the potential paths linking impulsivity, peers, and delinquency. We systematically integrate relevant processes into a set of dynamic network models that evaluate these interconnected pathways. Methods Our analyses use data from more than 14,000 students in Pennsylvania and Iowa collected from the evaluation of the PROSPER partnership model. We estimate longitudinal social network models to disentangle the paths through which impulsivity and delinquency are linked in adolescent friendship networks. Results We find evidence of both peer influence and homophilic selection for both impulsivity and delinquency. Further, results indicate that peer impulsivity is linked to individual delinquent behavior through peer influence on delinquency, but not on impulsivity. Finally, the results suggest that impulsivity moderates both influence and selection processes, as adolescents with higher levels of impulsivity are more likely to select delinquent peers but less likely to change their behavior due to peers. Conclusions In sum, this study offers a more holistic framework and stronger theoretical tests than similar studies of the past. Our results illustrate the need to consider the simultaneous network processes related to peers, impulsivity, and delinquency. Further, our findings reveal that a large dataset with ample statistical power is a valuable advantage for detecting the selection processes that shape friendship networks.
... Again, few studies have tackled the full complement and complexity of these theoretical predictions, for the previously noted reasons, but have instead focused mostly or exclusively on the rank-order stability (between individual differences) issue of self-control, for instance, (Beaver & Wright, 2007;Coyne & Wright, 2014;Diamond, 2016;Jo, 2015;Yun & Walsh, 2011) or have conflated the between and within individual difference changes over time, or have erroneously interpreted theory as predicting no additional changes at all in self-control during the second decade of life and beyond. Some of this work has provided evidence supporting rank-order stability (Arneklev et al., 1998;Coyne et al., 2015;Diamond et al., 2015;Hay & Forrest, 2006;Ray et al., 2013;Turner & Piquero, 2002), while work has not (Burt et al., 2006(Burt et al., , 2014Meinert & Reinecke, 2018;Mitchell & MacKenzie, 2006;Na & Paternoster, 2012;Winfree, et al., 2006). ...
Full-text available
The current investigation tested changes in low self-control and the developmental links between parenting and the developmental course of self-control. It was hypothesized that (1) low self-control would change over time (within individual changes); (2) parenting would negatively predict both the intercept and slope of low self-control during childhood; (3) parenting would negatively predict only the intercept during early and late adolescence. Self-report data from the Korean Children and Youth Panel Survey (KCYPS) were used, from the (1) first-grade elementary school panel (childhood; N = 2342), (2) the fourth-grade elementary school panel (early adolescence; N = 2378), and the (3) first-grade junior high school panel (late adolescence; N = 2351). Second-order latent growth curve models provided support that low self-control decreased over time. Findings also partially supported hypothesis 2, as parenting negatively predicted the intercept of low self-control, not the slope. Finally, they supported hypothesis 3, as a significant negative parenting effect predicted the low self-control intercept during both early and late adolescence. The current study contributes to research on the link between positive parenting and low self-control development, tested across three distinct developmental periods or age groups and by studying these questions among Korean youth.
... While self-control is established by parental management around early childhood (around the ages of 8 to 10) and can be stabilized as individuals mature, the social learning process continually changes human nature. However, the stability of low self-control has been contested (Arneklev, Cochran, and Gainey 1998;Beaver et al. 2008;Burt et al., 2006;Meinert and Reinecke 2018;Winfree et al. 2006). These studies suggested that parental influences over time are constantly relevant to the change in the level of low self-control. ...
... First, if one were to assume self-control is time stable, as Gottfredson and Hirschi (1990) suggest, our hybrid fixed effects methodology would rule this explanation out, as estimates cannot be biased by time invariant factors. Second, if one were to question whether self-control is time-stable (e.g., Burt et al., 2006;Hay and Forrest, 2006;Na and Paternoster, 2012), we also included a measure of self-control within our sensitivity analysis (Appendix F) -suggesting this construct is also not a source of omitted variable bias. ...
Research evaluating the relationship between work and crime has paid little attention to behavior in the workplace. We evaluate four hypotheses regarding the work-crime relationship: (1) Employment and crime are negatively related, (2) Employment displaces offending from the street to the workplace, (3) Work offending emboldens street offending, and (4) Work offending has no association with street offending. Drawing on longitudinal data from a high-risk sample of young adults from The Pathways to Desistance study, we use hybrid fixed effects models with measures of street property offending and workplace property offending to test the hypotheses. Our findings indicate a positive association between work property offending and street property offending with the inclusion of fixed effects. Findings also provide evidence that job quality moderates this relationship. We elaborate on the role of workplace behavior in the broader work-crime relationship and explore the mechanisms underlying the associations we identify.
... We also call on future research to explore the interdependence of individuals and their social environment and their impact on tourism victimization. While traditional criminological explanations tend to focus on individual characteristics to help understand the risks of victimization, there is evidence that the characteristics of individuals and the characteristics of social environments are both important correlates of crime and victimization (Burt et al., 2006;Doherty, 2006;Hay & Forrest, 2008;Moffitt, 1993;Nagin & Paternoster, 1993;Sampson et al., 2006;Wright et al., 2001). ...
Full-text available
There is a dearth of research examining criminal victimization among tourists and travelers. Additionally, with the exception of the routine activities framework, none of the leading criminological perspectives have been applied to study tourism victimization. In this paper, we apply a dominant criminological perspective, self-control theory, and an emerging perspective on tourist personality inventory, the Jackson Tourist Personality Inventory, to examine risks of victimization among a sample of tourists. We also assess whether the adventurer tourist personality inventory influences risks of victimization beyond an individual’s self-control. Employing three categories of victimization – personal victimization, property victimization, and other victimization – we found low self-control predicted two types of victimization (property victimization and other victimization) while the adventurer tourist personality type was a significant predictor of one type of victimization (property victimization). We also uncovered that the characteristics of an adventurer tourist were not related to victimization risks after a tourist’s self-control has been taken into consideration. Finally, we found that under conditions of very low self-control, the adventurer tourist measure was related to property victimization. Theoretical implications and suggestions for future research are discussed.
... 90 Gibbs y Giever (1995); Cochran et al. (1998); Gibbs et al. (1998); Vazsonyi et al. (2001). 91 Polakowski (1994); Pratt y Cullen (2000); Pratt et al. (2004); Burt et al. (2006); Schreck et al. (2006). 92 Gottfredson y Hirschi (1987). ...
“La composición del crimen: Una aproximación analítica” introduce los principales conceptos, teorías y evidencias sobre el estudio del crimen, invitando a toda persona interesada a adentrarse en este apasionante ámbito de estudio. El reto que nos planteamos en este libro es presentar una visión analítica sobre el fenómeno criminal. Nos preguntamos qué elementos componen el crimen, cada crimen, sin los cuales el mismo no tiene lugar. Del mismo modo que se puede descomponer un coche en sus partes mecánicas, o un ser humano en un conjunto de elementos biológicos, también se puede descomponer el crimen en tres elementos fundamentales: el agresor, el objeto del crimen y la ausencia de un “guardián capaz”. Este libro sintetiza el principal saber científico sobre cada uno de estos elementos que componen el evento criminal. Después de leer este libro, el lector será capaz de desarrollar una visión analítica sobre el crimen, desgranando el mismo en sus componentes fundamentales, e incluso proponer medidas para su prevención y control. “21st Century criminology has seen the emergence of a “new crime science.” It combines both rigorous empirical research and practical theories that predict the distribution of crime and provide guidance in how to respond effectively. This book summarizes the findings of the new crime science and their implications for society.” (Wesley G. Skogan, Foreword) “Este libro es de lo más fresco e interesante que le ha sucedido recientemente al panorama académico de la criminología en español […] el autor logra tanto condensar analíticamente el principal saber científico existente hoy sobre el crimen, su estructura y componentes, como transmitirlo al lector de forma sencilla e incluso amena.” (Fernando Miró Llinares, Prólogo)
A major contribution to the field of crime/deviance, this volume by noted criminologist Charles R. Tittle puts forth an integrated theory of deviance?control balance. Its central premise is that the total amount of control people are subjected to, relative to the control they can exercise, will affect the probability and type of their deviant behavior.In developing control balance, Tittle critically reviews other general theories such as anomie, Marxian conflict, social control, differential association/social learning, labelling, and routine activities and offers reasons why those theories are insufficient. Using real-world examples to illustrate his argument, he contends that deviance results from the convergence of four variables, each of which represents an interactive nexus of several inputs, including most prominently a control imbalance. The variables are predisposition, motivation, opportunity, and constraint. Control balance theory also explains six basic types of deviance, ranging from predation, defiance, and submissiveness on one end of a control ratio continuum to exploitation, plunder, and decadence on the other.Tittle conceives of control balance as a continuation, or temporary culmination, of the collective efforts of crime/deviance scholars who have gone before, presenting it as a vehicle for trying to achieve a fully adequate general theory of deviance.
1 Introduction.- 2 The Demographic Distribution of Delinquency and ADM Problems.- 3 Prevalence and General Offending/Use Patterns: The Joint Occurrence of Delinquent Behavior and ADM Problems.- 4 Age, Period, and Cohort Effects.- 5 Developmental Patterns.- 6 The Etiology of Delinquency and ADM Problems.- 7 Prediction of Delinquent and ADM Behavior from Other Delinquent and ADM Behavior.- 8 Summary and Implications.- References.- Appendix A Frequency of Alcohol Use.- Appendix B Mental Health Measures.- Appendix C Prevalence and Offending/Use Rates for Multiple Problem Types.- Appendix D Annual Transition Matrices for Problem Behavior Types.- Author Index.
To evaluate child-care effects on young children's self-control, compliance, and problem behavior, children enrolled in the NICHD Study of Early Child Care were tested and observed in the laboratory and in child care at 24 and 36 months, and mothers and caregivers completed questionnaires. Indicators of child-care quantity, quality, stability, type, and age of entry, along with measures of family background, mothering, and child characteristics obtained through the first 3 years of life were used to predict 2 and 3 year child functioning. Results revealed (1) mothering to be a stronger and more consistent predictor of child outcomes than child care; (2) little evidence that early, extensive, and continuous care was related to problematic child behavior, in contrast to results from earlier work; (3) that among the child-care predictors, child-care quality was the most consistent predictor of child functioning, although limited variance could be explained by any (or all) child-care variables; and (4) that virtually none of the anticipated interactions among child-care factors or between them and family or child measures proved significant.
We propose a family process model that links economic stress in family life to prosocial and problematic adolescent adjustment. Employing a sample of 205 seventh-grade boys aged 12 to 14 years (M = 12.7) and living in intact families in the rural Midwest, the theoretical constructs in the model were measured using both trained observer and family member reports. In general, results were consistent with the proposed model. Objective economic conditions such as per capita income and unstable work were related to parents' emotional status and behaviors through their perceptions of increased economic pressures such as the inability to pay monthly bills. These pressures were associated with depression and demoralization for both parents, which was related to marital conflict and disruptions in skillful parenting. Disrupted parenting mediated the relations between the earlier steps in the stress process and adolescent adjustment. The emotions and behaviors of both mothers and fathers were almost equally affected by financial difficulties, and disruptions in each parent's child-rearing behaviors had adverse consequences for adolescent development.