University of Southern California Dissertations and Theses

Factors contributing to self control for incarcerated youth

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Factors contributing to self control for incarcerated youth

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Content FACTORS CONTRIBUTING TO SELF CONTROL FOR INCARCERATED YOUTH

by

Trancita Winquist

A Dissertation Submitted to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2010

Copyright 2010 Trancita Winquist

ii

ACKNOWLEDGEMENTS

“I tell you, whatever you ask for in prayer, believe that you have received it,
and it will be yours.‖
Mark 11:24

It is with great pride that I acknowledge all those who have helped me along in
this incredible journey. I owe my thanks to many who have helped in making this all
possible. First, to my husband Jim and sons Kamakana and Nainoa, thank you for giving
me the time to accomplish this goal and for all your love and understanding. To my
mom, you have been an inspiration to me in all my difficult times.
My thanks extends to August Suehiro, Ellen Schroeder, Rene Iwamoto, Debbie
Heyler, and all the teachers and staff at Olomana School for keeping me going and
believing in me even when I felt discouraged. In addition, thank you to the
administration and staff members at the Hawaii Youth Correctional Facility for their
willingness to help me.
To my friends in my Hawaii 2007 Cohort and USC professors, you were all
instrumental in expanding my perspective on education and you continued to challenge
me to look beyond my own experiences. A special thanks to my dissertation committee
Dr. Dominic Brewer, Dr. Melora Sundt, and Dr. Louise Wolcott for agreeing to help me
with all those draft rewrites. Also, my gratitude goes out to Dr. Dennis Hocevar who
helped me in unscrambling my data analysis.
Finally, and most importantly, I give praise to God who I know was there with me
even when I felt like giving up. All that I have accomplished would not have been
possible without the love from Jesus Christ.

iii

Table of Contents
Acknowledgements ii
List of Tables v
List of Figures vi
Abstract vii
Chapter 1: Introduction 1
Background of the Problem 3
Statement of the Problem 8
Purpose of the Study 9
Research Questions 10
Significance of the Study 12
Limitations and Delimitations 13
Definitions 14
Organization of the Study 16

Chapter 2: Literature Review 17
Self Regulation 19
Self Perception 26
Family Relations 28
Significant Other 30
Correctional Setting 31
Costs Associated with Youth Incarceration 35

Chapter 3: Methodology 38
Subjects 39
Instrumentation 40
Setting 44
Research Design 45
Data Analysis 46
Strengths and Limitations 47

Chapter 4: Findings 49
Descriptive Data 51
Statistic and Data Analysis 58

Chapter 5: Conclusions and Recommendations 75
Discussion of Findings for Research Question 1 77
Discussion of Findings for Research Question 2 81
Recommendations for Practice 83
Limitations of the Study 84
Directions for Future Research 86

iv

References 88

Appendices:
Appendix A: Consent to Review Data 96
Appendix B: IRB Approval Letter 97
Appendix C: Mean, Standard Deviation, & T-Test Scores for 98
Part Hawaiian & Non-Hawaiian Groups
Appendix D: Mean, Standard Deviation, & T-Test Scores for 99
SPED & Non-SPED Groups
Appendix E: Mean, Standard Deviation, & T-Test Scores for 100
Mother & Other Groups
Appendix F: Mean, Standard Deviation, & T-Test Scores for 101
Violent & Non-Violent Groups

v

List of Tables
Table 1: Description of Self-Regulation Studies 18
Table 2: Hypotheses with Literature 33
Table 3: Research Questions with Grasmick et al. Scale 39
& Facility Indicators
Table 4: Description of Subjects: Age & Number of Years in School 47
Table 5: Demographic of Subjects by District 47
Table 6: Description of Youths’ Ethnicity 48
Table 7: Percent of Youth by Disability and Age 49
Table 8: Significant Other in Youths’ Household 50
Table 9: Percent of Youth by Age and Previous High Risk Encounter(s) 51
Table 10: Percentage of Youth by Age and Offense 52
Table 11: Mean and Standard Deviation for Independent 55
Self Control Scale

Table 12: Grasmick et al. Scale Results by Individual Mean & Section 59
Mean & Age
Table 13: Comparison of Mean & Standard Deviation between 60
Ethnicity Variable
Table 14: Summary of One-Way ANOVA on Impulsivity for 61
MO & NM Groups
Table 15: Comparison of Mean & Standard Deviation between 62
Significant Other
Table 16: Summary of One-Way ANOVA on Temper for ZO & TO Groups 63

vi

List of Figures
Figure 1: Boekaerts Three-Layer Model of Self-Regulated Learning 22
Figure 2: One-Way Design Using Error Bars to Represent Age Group 57

vii

ABSTRACT
This study was conducted to examine characteristics contributing to high self
control for incarcerated youth. Subjects include fifty youth (8 females and 42 males)
ages 14 through 18 incarcerated for at least 60 days. Data on subjects’ responses from a
validated measure (Grasmick et. al. Scale, 1993) and data from historical records, STAR
reading and facility level movement at the Hawaii Youth Correctional Facility (HYCF),
were closely analyzed to provide accurate findings. The researcher used descriptive,
correlational, and secondary data analysis to conduct this non-experimental quantitative
study.
Measurement models of comparison (through the use of t-tests) and correlational
analysis (through the use of Spearman’s Rho) to examine youth self control and the
relationship to level movement and academic accomplishment by incarcerated youth at
HYCF was implemented. The quantitative design is aligned to research on self-
regulation (Bandura, 1989), specifically self control, and the outcome measures were
aligned to determine the impact self control of youth had on youth success within HYCF.
All data included in this study was collected within one semester (from September 1,
2009 through December 1, 2009) and was used to answer both research questions of this
study.

1

CHAPTER ONE

INTRODUCTION
According to the U.S. Department of Justice (2007), 7.2 million people were in
jail or prison, on probation, or on parole in 2006 and by mid-2006, nearly 1.6 million
people were held under the jurisdictions of state and federal prisons. In addition to these
adult statistics, over 1.2 million juveniles were either in jail or prison, on probation, or on
parole based on data from the Office of Juvenile Justice and Delinquency Prevention
(2005). Although data collected on crime may provide an overview of its impact across
the United States, an unknown percentage of crime incidents go unreported (Shakelton,
1994). According to Bronskill (1996), many victims of crimes do not report it to
authorities because they fear revenge or because they believe that they will not be taken
seriously. Therefore, it is likely that crimes, including those committed by juveniles, are
underestimates of unknown proportion.
The history of juvenile justice in the United States stems back to the early 1900s,
or the Progressive-era, when the rights of women were being fought over, with
campaigns against child labor and against the abuses of big businesses. Among the initial
social philosophies of this period was the belief that the state was in charge of intervening
in children’s social well-being and family structures in order to save them from being
delinquent (Wolcott, 2001). By the 1930s the context of the American childhood
experience had changed with the rise of child guidance and child experts and the phase in
which adolescents who committed crimes were imprisoned with adults, shifted to a
period of more rehabilitative models where the intention of the state was to help rather
than to punish juveniles (Hawes, 1997).

2

For years our society has debated over how to best address the needs of
incarcerated youth as well as what environment is best suited for them. Today, the
facilities that hold many of incarcerated youth are most often barren of opportunities to
socialize. In his work, Bandura (1989) discusses how human behavior is multi-faceted
and argues that the environment must be included as causal factors in development.
Furthermore, Bandura understood that in order for individuals to overcome conflict and
obstacles, they needed social supports. Although in comparison to a century ago, many
may presently assert that rehabilitation is the key to helping incarcerated youth,
educational programs in youth correctional facilities continue to be overshadowed by
punitive models of discipline including isolation. When exploring alternatives to youth
incarceration, many profess to support rehabilitation models but the inconsistency of fully
adopting these models, or what Festinger (1962) refers to as dissonance, is apparent
based on the overuse of punitive models in juvenile corrections (Blombert & Lucken,
2000).
With regard to education, research by Piaget and Cook (1952) suggests
understanding that human interaction is necessary and individuals cannot compose
meaning alone. Moreover, our understanding is developed through those relationships
that are most meaningful. Youth who have opportunities to interact appropriately with
one another in a classroom setting by talking and exchanging ideas my discover
inconsistencies in their own understanding that they may not have discovered alone
(Blankstein, Cole, & Houston, 2007; Easton, 2008). This type of student interaction, also
known as a form of ―student engagement‖ (Blankstein, Cole, & Houston, 2007; Easton,
2008; Kolb, Boyatzis, & Mainemelis 1999), is particularly important for youth in

3

incarcerated settings as this kind of modeling of appropriate interaction can lead to
learning (P. Leone, personal communication, December 11, 2007).
It is apparent that educational programs within correctional facilities may be
instrumental in helping empower youth to succeed in society (Foley, 2001). Education is
often viewed as the answer to the problems plaguing marginalized youth who either have
a history of cognitive or emotional challenges. Furthermore, quality education in
correctional facilities may be imperative for an auspicious transitional plan back into the
community for these youth. Although literature on the over-representation of special
education students within incarcerated settings is abundant (McQuin, Rutherford, Leone,
Osher, & Poirier, 2005), literature investigating self-directed learning and self regulation,
particularly in the area of self control, within youth incarcerated settings is limited.
Background of the Problem
In an effort to prevent juvenile delinquency and enhance the juvenile justice
system in the United States, Congress enacted the Juvenile Justice and Delinquency
Prevention (JJDP) Act in 1974. According to the Office of Juvenile Justice and
Delinquency Prevention (2005), attention should be given to the development of
prevention programs along with the implementation of intervention programs aimed at
helping juveniles develop socially appropriate behaviors. Youth who enter the juvenile
justice system come with a variety of interconnected social, emotional, behavioral, and
academic needs. Many have been impacted by poverty, drug abuse, and exposure to
violence. Those juveniles who exhibit maladaptive behaviors are labeled in many ways
(e.g., socially maladjusted, delinquents, at risk, antisocial). Once these juveniles enter the
juvenile justice system, the challenges they must overcome are magnified.

4

Gottfredson and Hirschi (1990) points to maladaptive behaviors as a product of
those who lack self control: criminal acts are consequently committed by those with low
self control. Gottfredson and Hirschi (1990) also proposed that a lack of self control is
perpetuated in childhood by parents who do not acknowledge, correct, and punish a
child’s deviant behavior. Moreover, confidence of an inverse relationship between self-
control and crime or maladaptive behaviors is widely held (Pratt & Cullen, 2000).
Therefore, it becomes imperative that juveniles in the juvenile justice system develop and
practice self control as they will be forced to face more stringent challenges within an
institutional setting that not only require adherence to regulations, but also positive,
productive engagement in order to maximize all educational opportunities. Among the
major challenges for incarcerated youth are programming issues, supports that help
youth, factors to promote knowledge construction, and issues dealing with behavior
changes.
Program Issues
Although most juvenile delinquents in our country today are placed on probation
and are not committed, many reside at either private or state-run correctional institutions
where the educational programming for these youth can vary tremendously based on the
organizational structure (P. Leone, personal communication, August 15, 2008). The
emphasis of organizational structures is especially important when examining institutions
were these structures dominate self-contained populations. Research by Ogbu and
Simmons (1998) and Salazar (2005) present the notion that when a lack organizational
culture exists and youth tensions rise, these youth will tend to rely on their peer groups
for support. Ogbu’s work expands on the role of dominant groups in relation to voluntary

5

and involuntary groupings. The struggle between ―The System‖ and ―Community
Forces‖ as Ogbu describes is identified as a plight for minority grouping, but the
community forces concepts he produces can also be seen within adolescent development
as well (1998).
Along with the tensions that exist in correctional institutions, a common problem
associated with most incarcerated institutions is that of overcrowding. Overcrowding in a
correctional facility can be categorized as facilities with more wards than beds (U.S.
Department of Justice, 2009). Inmates who arrive with a lack self control skills can
encounter further negative experiences within a correctional institution that is
overcrowded. In a 2004 census of juvenile facilities across the country, nearly 15% of
juvenile offenders were held in facilities that had fewer beds than residents (U.S.
Department of Justice, 2009).
In addition to the spread of infectious diseases due to overcrowding in closed
confinements (Hoge et al., 1994; Mendell et al., 2002), the issue of mental health
concerns within juvenile correction facilities may also be problematic. In the U.S.,
approximately70% of the incarcerated population has a diagnosed mental illness
(Skowyra & Cocozza, 2006; Teplin, Abram, McClelland, Dulcan, & Mericle, 2002).
Furthermore, Skowyra and Cocozza (2006) argue that nearly 80% of those incarcerated
youth diagnosed with one mental health illness not only may meet eligibility criteria for
special education, but may also meet the criteria for a second mental illness diagnosis as
well.

6

Supports for Youth
According to the Office of Juvenile Justice and Delinquency Prevention (OJJDP),
correctional facilities fall into the residential category of the Model Programs Guide
(2005). Approximately 3,600 youth correctional facilities with over 100,000 incarcerated
youth exists in the United States on any given day (Sickmund, 2002). Skowyra and
Cocozza (2006) contend that many of these facilities lack resources to adequately address
all the needs of the youth they serve. However, reform models in juvenile justice, such as
the Model Programs Guide, examine the state by state efforts to change the quality of life
for juveniles and their families prior to incarceration (Olgetree, 2008). Structure and
consistency within the family dynamics although difficult and at times elusive, may be
linked to educational success, positive self-conceptions, and stronger work habits
(Steinberg, Lamborn, Dornbusch, & Darling, 1992).
In addition to rehabilitative programming supports such as counseling and
recreation, an emphasis on effective educational programming that provide a wide range
of educational opportunities, together with basic reading and computation skill
instruction, special education supports, high school equivalency programs, and vocational
training (Foley, 2001).
Promotion of Knowledge Construction
As education moves from a teacher-centered to student-centered approach to
instruction, increasing accountability is placed on the learner for their learning. In their
research, Sungur and Tekkaya (2006) contend factors that help students become
independent learners correlate to an increase in academic learning. Furthermore, students
who initiate tasks and set goals while utilizing appropriate strategies to achieve their

7

goals ultimately regulate their learning and achieve at higher levels (Sungur & Tekkaya,
2006). Unfortunately, incarcerated students do not fall into this category but rather are
plagued with many other challenges like being illiterate or marginally literate along with
experiencing school failure and retention (Quinn, Rutherford, Leone, Osher, & Poirier,
2005).
According to Foley (2001), youth in incarcerated settings have histories of high
rates of grade retention and academic failure along with academic functioning between
the fifth and ninth grade levels and it is imperative that educational programs consider
possible General Equivalency Diploma (GED) along with options that provide for
tracking to career pathways. In addition, approximately 43% of juveniles in incarcerated
facilities do not return to school or continue their education following their release
(Foley, 2001). Of those students released from incarcerated facilities, only 1.6% actually
complete with a high school diploma (Haberman & Quinn, 1986).
Behavior Change
The need that every student wishes to belong, and that misbehavior is a student’s
way of seeking a sense of belonging if one does not exist, is the underlying assumption of
the social model of Rudolf Dreikurs (Wolfgang, 1995). According to Dreikurs, people
are social beings and all human behavior is purposeful and directed toward social goals.
A person’s misbehavior is the result of faulty reasoning on how to gain social recognition
(Wolfgang, 1995). Research in social cognitive theory reveals that not only is learning

8

achieved through observation, but learning is also an internal mental process that may be
reflected in the behavior of the learner (Bandura, 1989).
According to Forrest, Tambor, Riley, Ensminger, and Starfield (1999), in order
for behavioral changes to happen for incarcerated youth, supports that attend to their
basic needs as well as their antisocial behaviors need to be addressed. Supports for youth
in incarcerated settings can include modeling appropriate ways to deal with and resolve
interpersonal conflicts through pro-social strategies such as self control.
Statement of the Problem
According to the Office of Juvenile Justice and Delinquency Prevention,
retributive models of incarceration are problematic not only because these models rely
heavily on punishment and isolation, but also because these models do not foster
knowledge construction as a social process (Ajzen, 1991; Bandura, 1989; Kolb, Boyatzis,
& Mainemelis, 2001). Society is often faced with the challenge of dealing with
marginalized youth who have low self control skills. In an effort to minimize pathways
to crime, researchers have studied the factors contributing to youth maladaptive behaviors
which often connect to low self control (Deibert, 2005; Evans, Owens, & Marsh, 2005;
Goff & Goddard, 1999). Once these youth enter the Juvenile Justice System, correctional
facilities are tasked with developing more work readiness opportunities for them, but
simply infusing vocational programming into the learning environment of incarcerated
youth when those students are not ready to engage socially about shared tasks or about
their challenges can create a system of failure (Foley, 2001).
More research in how youth are supported in an institutional environment,
particularly in the area of programming, must be explored. Programs that foster the

9

inclusion of family supports as part of the ongoing rehabilitation model may be
particularly beneficial for youth (Ogbu & Simmons, 1998; Ogletree, 2008). Most
important, the ways in which students interact, develop, and utilize self regulation skills
to navigate while incarcerated may be significant in determining their overall success in
life (Gottfredson & Hirschi, 1990; Haberman & Quinn, 1986).
Purpose of the Study

To conceptualize the significance of self-control and the impact it has on
incarcerated youth, the researcher drew on two fundamental theoretical frameworks. The
first theoretical framework, and much-used learning model (Bandura, 1989), emphasizes a
merge of ideas from behaviorism, cognitive psychology, and motivation into a social
cognitive theory that rely on three variables (environment, person, and behavior) which
equally influence one another. The Bandura model builds on the Zimmerman (1986)
model of self-regulation and self-perception. The second framework claims that resources
allocated to training and education is costly and should be viewed as an investment
(Becker, 1964). Human capital model (Becker, 1964) includes factors within the
cognitive processes that are significant to consider when examining marginalized
populations such as incarcerated youth particularly in the area of literacy and the
acquisition of vocational skills.
This study examined the importance of self control and the impact it has on
student success within the setting of the Hawaii Youth Correctional Facility (HYCF).
Youth facility level movement along with academic indicators reported in
Multidisciplinary Team (MDT) meetings (including STAR Reading scores) was
examined to determine the extent to which self control affects students’ success. First,

10

the researcher examined existing youth records and intake processing data indicating how
students within HYCF assess their own levels of self control as indicated in the
Grasmick, Tittle, Bursik, and Arneklev (1993) Low Self Control Scale. Second, the
researcher compared the Grasmick et al. (1993) scale scores with success indicators used
both by the facility and school. Finally, the researcher explored the premise that students
who possess high levels of self control were more successful in the HYCF setting
compared to those who did not. The data collected may be used to identify youth, upon
entry to school, who may be predisposed to low self-regulatory behaviors as well as those
youth who may have high self-regulatory skills and if those skills translate into successful
transitioning into community programs.
Research Questions
The following research questions were addressed in this study:
1. What characteristics contribute to self control for incarcerated youth?
2. Is there a correlation between youth self control (impulsivity, risk-seeking, and
temper) and outcomes (HYCF Level Movement and STAR Reading scores)
within a youth correctional facility?

11

Hypotheses
The following research hypotheses were tested in this study:
1. There is no difference in self control (impulsivity, risk seeking, or temper)
between age groups for incarcerated youth.
2. There is no difference in self control (impulsivity, risk seeking, or temper)
between part-Hawaiian and non-Hawaiian incarcerated youth.
3. There is no difference in self control (impulsivity, risk seeking, or temper)
between special education and non-special education eligible incarcerated
youth.
4. There is no difference in self control (impulsivity, risk seeking, or temper)
between incarcerated youth who identified having a mother as the most
significant other in their lives and those who do not.
5. There is no difference in self control (impulsivity, risk seeking, or temper)
between violent youth offenders and non-violent youth offenders.
6. There is no difference in self control (impulsivity, risk seeking, or temper)
between incarcerated youth who had less than three high risk encounters
and those who had three or more high risk encounters.
7. There is no correlation between low temper scores and high level
movement or STAR reading scores.
8. There is no correlation between low impulsivity scores and high level
movement or STAR reading scores.
9. There is no correlation between low risk seeking scores and high level
movement or STAR reading scores.

12

Significance of the Study
The aim of this study was to augment the existing body of research on youth self
control in general and increase the body of knowledge regarding incarcerated youth in
particular. Two reasons differentiate this study from previous research. First, research
exploring the relationship between self regulation and incarcerated youth can expand the
range of theories that focus on understanding the condition that distinguishes criminals
from non-criminals in childhood and onto adult life. Second, research valuing the
perspectives of incarcerated youth and how they access their level of self control is
significant in providing evidence to validate effective programming. A noteworthy
implication of this study is that it offers additional insight of incarcerated youth by
examining the influences of self regulation particularly characteristics that may contribute
to it. By determining the correlation between youth self control and the measurable
success indicators within an incarcerated setting, data can be used to explore proactive
program interventions that decrease the overrepresentation of youth incarceration that
exists today.
Data from this study may also be used as a tool for transitional services by
identifying youth who may report low self control and therefore, may require more
intensive supports prior to reintegration into the community. As youth enter the HYCF,
an intake process begins and data is collected. Youth who have not been identified with
low levels of self control stand a higher chance of failure compared to youth who have
supports in place to help with this transition period. Similarly, data collected from youth
with high self control prior to exiting the facility can be used to determine the

13

effectiveness of the overall facility programs as well as additional resources to help that
youth succeed beyond their period of incarceration.
Currently little data is collected and analyzed in the area of youth self control, but
the researcher proposes to explore if a fundamental relationship between self control and
student success within an incarcerated setting exists and therefore, the data examined is
useful for the diagnostic approach being proposed.
Limitations and Delimitations

In reviewing the limitations of this study, one limitation is that all participants are
incarcerated youth in a residential facility, which will be referred to as the Hawaii Youth
Correctional Facility (HYCF), for youth offenders who are adjudicated to the only youth
correctional facility in Hawaii. The majority of these youth are males thereby possibly
limiting some educational opportunities for parody for the females. Each youth has been
committed for a period at the HYCF facility and the transiency rate is high. The terms of
the youths’ commitment vary depending on their involvement in delinquent offenses and
may pose challenges in collecting accurate longitudinal data. In addition, there is a high
rate of recidivism among the incarcerated youth at HYCF and therefore, the data for the
purposes of this study must be carefully examined to avoid duplication. The nature of
strict confidentiality for youth who are wards of the state limited the researcher’s access
to rich perceptual data in the form of personal interviews.

14

Definitions
This section offers definitions of concepts and terms relevant to incarcerated
youth in the Hawaii Youth Correctional Facility.
Self Control is especially difficult to define because of the many and diverse
interpretations. Gottfredson and Hirschi (1990) describe self control as the act of
controlling impulses that would otherwise lead to overindulgence or immediate
gratification. Furthermore, self control theory as defined by Gottfredson and Hirschi
asserts that impulses relating to self control tend to by constant over time. Other
formulations of self control such as ―self-perception‖ and ―self-regulation‖ add to the
knowledge of not only controlling behavior, but the knowledge of having the ability to
learn independently with the motivation to do so (Bandura, 1989; Silverman & Ragusa,
1992; Zimmerman & Pons, 1986).
Multi-disciplinary Team (MDT) is an internal team of professionals that assists
the youth in adapting to the facility environment, aids in accommodating the needs of the
youth, supports the youth in meeting academic goals, and facilitates exploration of
pathways for the youth’s transition back into the community. Participants in the MDT
consist of the youth, a Youth Correctional Officer (YCO), their assigned facility social
worker, a mental health worker, and a school representative. MDT meetings are
conducted for every youth on a 30-day cycle but may be more frequent depending on the
needs of the youth.
Level System is classified into five different levels and is used for programming
purposes. All youth may earn up to 10 points per day based on the combination of
adherence to their MDT plan as well as completion of their daily responsibilies. Once a

15

youth enters the facility he or she is automatically placed into ―orientation‖ status and
once an intake meeting is conducted, usually within 48 hours, the youth is placed on
orientation level status. The levels are as follows:
(1) Orientation Level= 0–70 points, (2) Level One= 71–280 points, (3) Level Two= 281–
540 points, (4) Level Three= 541–780 points, and (5) Level Four= 781 points or more.
Based on a youth’s 30-day MDT meeting review, a youth’s level may go up, down, or
stay at the same level.

16

Organization of the Study
The theoretical framework for this study, both social cognitive theory and human
capital theory are presented in Chapter 2 along with literature associated with both
theories. Next, Chapter 3 provides the methodology used in this study particularly the
variables and two types of analyses that are used to test the research questions and
hypotheses for this study. Chapter 4 supplies the results of the study along with answers
to both research questions. Finally, Chapter 5 concludes with a discussion of the
findings, some limitations of the research with suggestions for further research, and
implications for programming and policy.

17

CHAPTER TWO

LITERATURE REVIEW
On any given day, an estimated 93,000 youth are held in residential correctional
facilities across the country (Office of Juvenile Justice and Delinquency Prevention,
2005). Research shows a greater need for systems of prevention, deterrence, and
rehabilitation for youth offenders in contrast to incarceration (Austin, Johnson, &
Weitzer, 2005). Compelling evidence suggests that in order for youth to be successful,
they must take an active role and adopt strategies and mental processes, such as self
regulation or self control, which will deliberately engage them in learning and performing
better (Delisi, Hochstetler, & Murphy, 2003; Dembo & Eaton, 2000; Young, 2005;
Zimmerman, 1986). According to self control theory (Gottfredson & Hirschi, 1990),
those with low self control are at higher risk of engaging in criminal activities versus
those with high self control. In addition, in their validation of the Grasmick et al. scale
(1993), Delisi, Hochstetler, and Murphy (2003) indicated that self control—particularly
in the domains of impulsivity, risk taking, and temper—offered higher degrees of
significance supporting Gottfredson and Hirschi’s theory.
The purpose of this study was to uncover possible variables contributing to high
self control, with particular attention in the areas of impulsivity, risk taking, and temper,
among youth who are incarcerated. Success for youth in incarcerated settings can be
defined as the possession of constructive decision-making skills that lead to readiness for
community re-entry (Evans, Brown, & Killian, 2002). Moreover, closer examination that
identifies whether or not incarcerated youth can perceive characteristics contributing to

18

their own self control may contribute to facilitating pathways that lead to their transition
back into the community.
The first theoretical framework used to address the first research question in this
study is Bandura’s social cognitive model (1989) of self regulation and goal-directed
behavior. The researcher followed the assumption in Bandura’s model that reciprocal
influences among behavior, personal, and environmental factors directly impacts each
other and this can lead to success or failure for the individual. Moreover, the lack of
supports for healthy personal development, along with poor environmental supports, may
contribute to maladaptive behaviors and an overall increase in low self control (Bandura &
McDonald, 1963). The second framework, human capital model (Becker, 1964), offers an
important area within the cognitive processes to be considered when examining
marginalized populations such as incarcerated youth. Although a major focus of the
human capital model is on the importance of training in relation to occupational wage
differentials, this study will specifically draw on the area of the human capital model that
focuses on the acquisition of literacy and vocational skills. This area of focus will be used
to address the second research question for this study.
The literature in this section is organized into three main sections. The first
section will present literature associated with self regulation and the connection it has to
self control. Next, literature on self-perception is provided to emphasize how
metacognition influences the regulatory process particularly as it relates to self control
theory. The final section in this chapter provides literature on family relations, importance
of a significant other, the correctional setting, and cost associated with youth
incarceration.

19

Self Regulation
Numerous studies exist on self regulation. According to Zimmerman and Pons
(1986), self regulation refers to ―actions directed at acquiring information or skills that
involve agency, purpose (goals), and instrumentality self-perceptions be a learner‖ (p.
615). Kopp (1982) defined self regulation as the ability to; follow requests; to initiate,
postpone, or terminate actions based on situational conditions; and to monitor actions in
educational and social settings. Furthermore, Kopp believed that the self regulation was
a higher form of self control. It involved the ability to use an array of rules to guide
behavior according to standards and expectations. Most important was the principle that
growth of cognitive skills needed for self control and self regulation occurred gradually
throughout the preschool years (Kopp, 1982).
From the six self regulation studies reviewed in this section, an array of
participant age levels, ranging from 4-year-olds through adulthood existed. Two of the
studies that examined intrinsic conditions such as motivation and mood that did not show
significant effects on self regulation compared to the other four studies. Silverman and
Ragusa (1992) showed some of the most influential findings in their research with early
childhood development particularly with early maternal socialization experiences.
In their study of 69 four-year-olds, Silverman and Ragusa (1992) discuss the
impact that child rearing plays on self regulation and how mother–child interaction can
be a powerful influence on the ability for the child to develop self regulation skills.
Identifying the qualitative factors effecting the mother–child interaction for incarcerated
youth holds promise in driving rehabilitation initiatives. The question of whether
mother–child interaction has occurred, or has been absent, for incarcerated youth may be

20

an area to be further explored particularly in how this interaction has promoted self
regulation for these youth.

21

Table 1. Description of Self Regulation Studies

Citation Purpose Participants Instrument Findings

Pintrich & Motivation, self 173 youth Motivated Intrinsic value had no
DeGroot, 1990 regulation, & academic (100 girls, 73 Strategies for direct influence on
performance. boys) Learning performance but did
M=12.6 years (MSLQ) impact self regulation.

Zimmerman & Discusses use of self 80 youth Interview Self-regulated learning
Pons, 1986 regulation strategies (random measures proved best
during class, for selection) predictor of standardized
homework, and study M=15 years achievement scores.
time.

Sungur & Examines effectiveness 61 youth MSLQ Problem based learning
Tekkaya, 2006 of problem-based (22 girls, 39 Questionnaire learning enhanced self
learning and traditional boys) regulation skills.
instruction on students’ M=16 years for
self regulation. experimental
group, M= 16.5
years for control
group.

Young, 2005 Discusses use of self 257 college MSLQ Application-oriented
regulation strategies undergraduates Questionnaire experience delivered by
during class, for enthusiastic teacher with
homework, and high interaction and
study time. feedback increases use of
self regulated learning
strategies.

Slverman & Examines whether 69 children Yale Negative maternal inter-
Ragusa, 1992 self regulation at age 4 (35 boys, Children’s action predicted criterion
could be predicted from 34 girls) Inventory behaviors in the child.
child and maternal Maternal behavior is a
measures obtained contributor to the develop-
from when the children ment of self regulation.
were 24 months old.

22

The six studies included in Table 1 cover an array of participant age levels,
ranging from four-years-olds on up through adulthood. Two of the studies that examined
intrinsic conditions such as motivation and mood did not show significant effects on self
regulation compared to the other four studies. Silverman and Ragusa (1992) present
some of the most important findings on early childhood development particularly with
early maternal socialization experiences. In their research, of 69 four-year-olds,
Silverman and Ragusa (1992) point to the impact that child rearing plays on self
regulation and how mother-child interaction can be a powerful influence on the ability for
the child to develop self regulation skills. Identifying the qualitative factors of the
mother-child interaction that may influence increases in self regulation for incarcerated
youth holds promise in driving rehabilitation initiatives. The question of how mother–
child interaction has or has not occurred for incarcerated youth may be an area to be
explored further particularly in how this interaction has promoted self regulation.
The picture that learning is enhanced by student self regulation emerges from
research by Zimmerman and Pons (1986), Sungur and Tekkaya (2006), and Young
(2005). Specifically, the study by Zimmerman and Pons (1986) showed that 91% of
students in the sample could be correctly identified into predictor groups of high and low
achievement based on their degree of self regulation. Although Sungura and Tekkaya
(2006) were able to validate the existing literature relating to the hypothesis that tasks
with high interest value for youth produced increases in the expression of self-regulatory
strategies, the use of zero-order correlations to explore the association between
motivation and learning strategies indicated no statistically significance between the two.

23

To support the role of environment influences youth in the area of delaying
gratification, research by Mahrer (1956) was able to show that by varying the expectation
for delayed reinforcements, with other factors being the same, second and third grade
male subjects could produce a higher degree of self regulation. Mahrer’s findings
indicated that the prospect for self regulation depended on the social factor that served as
a prompt for the expectancy levels of delaying gratification. Mahrer inferred that
subjects’ perceptions of the social factors in connection to the existence or non-existence
of delay reinforcements affected the subjects’ willingness to delay gratification.
To expand on the notion of self control and the area of delaying gratification
among children, Mischel and Ebbesen (1970) developed a theory based on the
metacognitive process that examined wait time and goal-directed behavior using
perceptual focusing or meditation strategies. In their research, Mischel and Ebbesen
predicted that subjects who were provided rewards for exhibiting self control should be
able to sustain self control longer being that the rewards would be more desirable than
misbehaving. Contrary to their predictions, the results of their study indicated that
exposure to any rewards negatively affected the ability for children to delay gratification
and that subjects in their study group who were not exposed to any rewards had a higher
rate of self control compared to those exposed to rewards. The researchers concluded
conditions that lowered the subjects’ concentration to a delayed reward, distracted the
subjects by internal or external activity from the delay of that reward which resulted in
the subjects becoming frustrated and causing the subjects to be less likely to continue
their goal-directed waiting.

24

Bandura (1986) understood that social efficacy was the result of an ongoing and
reciprocal interaction between cognitive, behavioral, and environmental activities. In
order for individuals to learn from their behavior, they needed to give specific attention to
their behavior. This understanding differs from early work by Festinger (1957) by
acknowledging that learning is a social process. Bandura (1986) saw the inter-
dependence between person, behavior, and environment. In one of his earlier studies,
Bandura and McDonald (1963) examined the dynamics between person, behavior, and
environment. The experimental design of Bandura and McDonald’s (1963) study
provided a strong quantitative construct for investigating the cause-and-effect
relationship. Through a three step process the researchers conducted a pre-assessment of
moral responses from their participants followed by an experimental treatment and a post
treatment measurement of subjective and objective moral responses. The researchers
concluded that children of all ages showed discriminative banks of moral judgment based
on environmental reinforcements.
Another model conceptualizing student self regulation is presented as in the
Boekaerts (1999) three-layered model of self regulated learning (see Figure 1). Boekaerts’
model captures the depth to which cognitive and metacognition supports self regulation.
Furthermore, similar to that of Bandura’s model emphasizing the reciprocal causation
between environment, behavior, and person variables; Boekaerts’ model relies on choice
of cognitive strategies, use of metacognition, and learning, and choice of goals and
resources in order to achieve self regulated learning.

25

Figure 1. Boekaerts Three-layered Model of Self-regulated Learning

Although Boekaerts (1999) acknowledges different constructs of the self-
regulated learning process, she proposes that cognitive and affective processes operate
synchronously from information processing. Thus, self-regulated learning is influenced
by those affective traits of metacognition competence (being proactive, resilient to
failure, self-actualized, goal-oriented).
In summary, use of self regulation helped to provide a basis for later
manifestation in the topic of self control by helping students organize their cognitive
processes using affective processes such as attitudes and beliefs as change agents. What
Regulation of
the self
Regulation of
learning process
Regulation of
processing modes
Choice of goals & resources
Choice of cognitive
strategies
Use of metacognition
to direct learning
Self regulated learning

26

is unclear is how to facilitate self regulation in the population of non-traditional students
such as those youth who are incarcerated.
Self Perception
One of the fundamental theories in the study of attitudes and beliefs comes from
Leon Festinger’s theory of cognitive dissonance. According to Festinger (1957), people
are often faced with dissonance in what he describes as holding two contrasting ideas
simultaneously. In his work, Festinger (1957) argues that people are inherently
motivated to reduce dissonance and argues that the cause of dissonance occurs when
these ideas ultimately conflict with fundamental elements of self-concept. Festinger’s
theory of cognitive dissonance purports that dissonance is a result from the
disconnectedness between one’s beliefs and the inconsistent overt behaviors (Festinger,
1957).
In contradiction of the Festinger theory of dissonance, Bem (1967) advanced the
hypothesis that changes in our attitudes result from a change in behavior the notion that
―seeing is believing‖. In his theory of self-perception, Bem argued that a person’s
attitudes and beliefs are most determined by self-observation (Bothamley, 2002). Bem
refuted Festinger’s dissonance theory of how attitudes change by explaining that direct
observation rather than contrasts in perceived information caused changes in mindset.
In his analysis, Bem (1967) examined cognitive dissonance studies and
determined that by using self-perception analysis or making self-observations about
attitudes and beliefs, the reduction of dissonance occurs. Bem’s research deduced from
the data that a person’s self-perception is a result of the mind concluding that the
behavior is the overt marker of an attitude. Thus, Bem’s theory is diametrically in

27

contrast to Festinger’s model that proposes that attitudes resulting from cognitive
dissonance drive behaviors. Furthermore, by evaluating the research data-gathering
techniques of Festinger’s earlier studies, Bem (1967) provided a divergent interpretation
of the data that resulted in his self-perception theory on how his subjects looked at their
own behaviors that resulted in an increase in metacognitive awareness.
The significance of metacognition, or the ability for individuals to reflect on their
own understandings and beliefs about their cognitive process, is paramount in learning
(Ormrod, 2008). Moreover, not only is research in the area of metacognition and how it
influences regulatory processes significant (Pintrich & DeGroot, 1990; Dembo & Eaton,
2000; Zimmerman, 1986) but this same research also adds to understanding the factors
that influence efficacy of learning which include a student’s perception of the expected
success in completing the task, the value of the learning task, and the emotions connected
to the task. Through this form of reflection or metacognition, one can ―learn‖ from their
own behavior. Thus, the level of the student’s self regulation skills is dependent on the
student’s motivation to use metacognition. The notion that one can learn from his or her
behavior assumes that the learner took some time to reflect and therefore, self control
should exist on the part of the learner.
In summary, the research articles on self-perception reveal several important
findings. In the research articles examined, the characteristics of self-perception
included: (1) Bem’s examination of cognitive dissonance studies and how using self-
perception analysis reduces dissonance thereby increasing self control in individuals, (2)
Pintrich and DeGroot (1990); Dembo and Eaton (2000); Zimmerman (1986); Mischel
and Ebbesen (1970); research in the area of metacognition and how it influences

28

regulatory processes that parallel Self Control Theory, and (3) Mahrer (1956) and
Bandura’s main tenet in his Social Cognitive Theory (1986) of the significant
interdependence between the environment, person, and behavior and how that supports
the idea that as children grow, they strive at directing and monitoring their own
behaviors. Moreover, the literature presented in this section offers a structure to address
the first research question as presented in Chapter 4. Although the research articles
describe factors that may contribute to self control, little research exists to describe how
self-perception influences youth who are incarcerated.
Family Relations
Most educators agree that parenting shapes both child and adolescent
development in significant ways. According to Jacobson and Rowe (1999) genetic
factors account for more than half of the correlations between family and school
connectedness. In their examination of a behavioral genetic study by the National
Longitudinal Study of Adolescent Health of 2,302 adolescent sibling pairs, Jacobson and
Rowe (1999) was able to use genetically derived data to calculate the genetic and
environmental factors related to the covariation between family and school environments
and adolescent mood.
Although research in early childhood development highlights the important role
parents play, Rowe (1994) and Harris (1995) both argue that in many cases, parents play
a less pivotal role in the behavior and personality of their children. Contemporary
research in parenting shows that representation of heritable traits relies strongly on
experience, parental behavior, and age-related considerations in the child. It is this
combination of factors that contemporary researchers use to define the parenting roles in

29

a broader context than simply how families live (Collins, Maccoby, Steinberg,
Hetherington, & Bornstein, 2000).
Research revealing correlations between parenting behavior and student
achievement also can be significant in understanding the important impact parents have
on their children. Silverman and Ragusa (1992) found that not only did the lack of
having a maternal figure negativity impact child self regulation, but in their study of 69
children, correlations between compliance and performance on tasks were also clinically
significant dependent variables. Although their study was restricted to the study of 4-
year-olds, they were still able to determine through longitudinal data that maternal
behavior is a contributor to the development of self regulation (Silverman & Ragusa,
1992).
Contrary to Jacobson and Rowe (1999) and Harris (1995) supportive parents are a
vital element contributing to resiliency that is related to positive child and adolescent well
being (DeBaryshe, Yuen, Nakamura, & Stern, 2006). Furthermore when parents,
regardless of socioeconomic factors, are involved, students demonstrate positive
behaviors and attitudes and their academic achievement increases (Kamehameha Schools,
March 2000). Parent involvement in education consists of home-based activities such as
help with homework and reinforcing reading and supporting school attendance and
supporting school-based activities such as parent-teacher conferences, open house, and
volunteering (Margolis, 2005).
In summary the importance of parents in child development is indeed significant
(DeBaryshe, Yuen, Nakamura, & Stern, 2006; Kamehameha Schools, 2000; Silverman &
Ragusa, 1992). Although extensive research exists to support this notion, relatively little

30

quantitative data exists regarding how parents’ behavior shapes adolescent ability for self
control particularly among incarcerated youth.
A Significant Other
A large body of research indicates that adolescent youth are more likely to
succeed when they have at least one significant positive adult in their lives. A seminal
1955 study regarding this research was the Kauai Longitudinal Study by Werner and
Smith (1992). In their 30-year study of 505 individuals, Werner and her team monitored
the impact of a range of biological and psychosocial risk factors, protective factors and
traumatic life experiences on the development of these individuals—from birth, in
infancy, early and middle childhood, late adolescences, and adulthood. One of three in
Werner and Smith’s study experienced at least one of the following conditions, prenatal
stress, chronic poverty, were raised by parents with little formal education, and lived in
disorganized families. One-third of the study participants experiencing any of these
conditions were also marred with alcoholism or mental illness in their family and two of
three in this vulnerable group experienced at least four or more of these risk factors
before the age of two. Werner and Smith were able to identify two predominate
protective factors (latent variables) correlating with high successful adult adaptation. The
first was having social competence and independence as a toddler and the second was
having competent parental and caregiving styles as a child with emphasis on having a
mother.
Drawing upon the Werner and Smith’s study, Todis, Bullis, Waintrup, Schult, and
D’Ambrosio (2001) employed an ethnographic life history approach in their study of 25
incarcerated adolescents. They discovered that many participants did have a significant

31

connection with at least one adult while incarcerated. Youth who are incarcerated can
greatly increase their chances of not reoffending once released if they are supported with
connections to a family structure that fosters boundaries and responsibilities (Dembo,
Ramirez-Garnica, Rollie, & Schmeidler, 2000). However, this proviso has a caveat as
documented in the Forst, Fagan, and Vivona (1989) study. They argued that although
social workers in juvenile facilities are significant figures in facilitating information of
youth needs and goals to key personnel including the court system, adult relationships for
youth outside of the facility are more often detrimental because those adults closest to the
youth are often law-violators themselves.
In summary, Werner and Smith’s 1955 study established a vital source of data
pertaining child development from infancy on up through adulthood as well as risk
factors associated with negative developmental outcomes. Although there is significant
research in the area of resiliency, there is much to be learned about the process by which
protective factors are established that afford vulnerable youth a break away from
childhood and adolescent adversity. This is particularly true when it comes to
determining whether incarcerated youth have an internal locus of control that may be
bolstered by encouragement or guidance from at least one significant other.
Correctional Setting
One basic principle of rational action is that humans learn from their errors and
therefore have greater guidance over their own futures. This has not always been the case
regarding those within our penal system in our country. A founding piece of literature on
the condition of prisons dates back to the nineteenth

century were systemic abuses of
prisoners were rampant throughout Europe (Kropotkin, 1887). According to Kropotkin

32

(1887) those detained in prisons are less adapted for life in society and very few prisons
operate in raising the intellectual and moral faculties rendering that person ―better‖ than
before he entered. Interestingly, although Kropotkin examined prison life in the mid-
1800s, many of the problems he addressed in his research are still evident in correctional
systems around our country today.
The change in some prison research post-1900 is evident in the socialization
patterns found in prisons and the process by which inmates adopted the norms and values
that created an inmate subculture (Blomberg & Lucken, 2000). Understanding the
adjustment of inmate to prison subculture is an important area of research in correctional
systems (Hand & Lebo, 1954; Wolfgang, 1960).
In a study of 116 delinquent youth, Hand and Lebo (1954) used a quarantine
period to determine a technique for identifying boys who could not be predicted to
conform immediately to incarcerated life. Hand and Lebo used a three by three chi
square comparison of the California Test of Personality test scores and an institutional
adjustment index (IAI) to determine if there was a relationship between the two for a
period of 30 days or more. Although confinements such as 30 days or more may be
considered ―harsh‖ for the purposes of research gathering, the delinquent youths in the
study were provided with counseling and close observation by various institutional
officers during that period. Hand and Lebo were able to determine that overcrowding
was a variable to the IAI and to some extent may have impacted students during the
period of quarantine. The researchers also found that low scores on the California test
were obtained by participants with high IAI’s (poorly adjusted boys), whereas high
scores on the California test were obtained by boys with low IAI’s (well adjusted boys).

33

Consequently, California test scores in the middle array of the group test were gathered
by boys with central IAI scores.
Other than the issue of overcrowding, there is little quantitative data regarding
correctional operations. In one report on correctional systems, six key elements were
identified by the California Corrections Policy Development (2000), as essential to an
effective correctional system. These elements included the following:
1. Integration, collaboration, and coordination is apparent,
2. A structure of balanced funding were needs are addressed and sustained,
3. Clear, consistent sentencing laws that reflect the crime, the offender, and
appropriate punishment options, and resources,
4. Identification system for substance abusers, treatment and training options to
address substance abuse issues,
5. Awareness of responsibility to participate in crime and delinquency prevention,
6. Builds relationships within the facility and with community supporters to address
positive change.
Correctional management is clearly seen as an important mechanism in linking
the implementation of a clear philosophy about corrections, supports of a strong
managerial force, and the overall corrections operations (Diiulio, 1992; Wright, 1994).
The culture in a correctional facility varies depending on the institution and the
relationship between the residents and those who work within these institutions.
Changing policies and shifting philosophies regarding corrections has created a tussle
between conservative custodial attitudes and rehabilitative models in correctional
institutions (Crouch & Alpert, 1980). The degree to which rehabilitation has the support

34

among the correctional employees within a facility is a crucial question. One group of
officials with the greatest authority within an incarcerated setting are the youth officers
assigned to supervise incarcerated youth, however; relatively little research about their
personal experiences and attitudes toward punishment has been conducted (Jacobs &
Retsky, 1977; Jurik, 1985).
Following the Juvenile Justice and Delinquency Prevention Act of 1974, the
environmental quality of confinement in juvenile correctional facilities has been closely
examined sparking scrutiny on the effectiveness of public and versus private management
(Bayer & Pozen, 2003). According to the Office of Juvenile Justice and Delinquency
Prevention (2005), nearly every state offers a combination of both public and private
facilities that secure its incarcerated youth. However, Hawaii is one of the few states in
which all of its committed juveniles is, at some point, placed in state-run secured facility
(Office of Juvenile Justice and Delinquency Prevention, 2005).
Educators have pointed extensively to the home as the biggest influence effecting
student success. However, research by Salazar (1997) indicates that the issue is more
about access to networks that tap into paths of success determined by the dominate
culture. According to Salazar (1997) although youth are systemically surrounded in
familial and school-based networks that offer institutional support, youth who are
economically depressed and who may be ethnically segregated experience connections
that may be life-altering and even problematic. Expanding on Salazar’s social capital
framework is the notion of ―costs‖ and the monetary value associated with saving a high-
risk youth (Cohen, 1998; Rose & Clear, 1998).

35

In their work, Rose and Clear argue that an overreliance on incarceration as a
formal control hinders the ability for communities to cultivate other forms of control
because they are at the cost of weakened family and community structures. More
specifically, the side effects of policies proposed to combat crime by controlling
individual criminals may aggravate problems that lead to crime in the first place.
Costs Associated with Youth Incarceration
According to Cohen (1998), the ideal cost–benefit analysis of a high risk program
would track participants and a group of matched controls from the time of the
intervention throughout their lifetime. Cohen estimates potential benefits from ―saving‖
high risk youths by estimating the lifetime costs associated with a typical career criminal.
Because of the absence of controlled experimental data on the number of career
criminals, Cohen’s study examined what number of career criminals must be prevented in
order for a program to ―pay for itself‖. Based on his study, Cohen estimated that the
typical career criminal causes $1.3 to $1.5 million and a high-school dropout causes
$243,000 to $388,000 in external costs.
In her review of 20 studies relating to the examination of academic characteristics
of incarcerated juvenile delinquents, Foley (2001) found that incarcerated youth had
significant problems in both intellectually and academically. Assessments of academic
performance exposed the functioning of incarcerated youth to be significantly lower than
that of their non-incarcerated counterparts. Foley pointed to the following features that
were well noted across the studies in her research: (1) A viable assessment system based
on valid research, (2) an array of relevant curricular options, and (3) highly efficient and
rigorous instructional strategies. Common threads in the academic programs in

36

correctional settings included both voluntary and involuntary participation in the school,
ability level groupings, curriculum ranging from basic skills instruction to postsecondary
education options, educational assessments including computer-based testing for reading
placement, and varying degrees of attention youth qualifying for special education
services.
In summary, the research presented by Bandura and others emphasize the
interdependence of person, environment, and behavior. However, all juveniles in the
correction system in Hawaii are in locked facilities and often have very few opportunities
to engage in socializing with others outside the facility. In addition, correctional
institutions that make good use of research in the area of understanding the culture and
subcultures within a correctional facility are more likely to be those institutions that
benefit individuals within it (Blomberg & Lucken, 2000; Hand & Lebo, 1954; Jurik,
1985; Wolfgang, 1960). Although the intention of correctional institutions should be to
increase intellectual and moral faculties rendering that person ―better‖ than before he
entered, this is not always the case. Whereas some research exists in the area of
understanding the correctional structure, and the impact of the subcultures within it, more
research like that of Hand and Lebo (1954) is needed to predict the degree of adjustment
by incarcerated youth, particularly in the area of how self control can positively influence
them to succeed within a correctional setting. Table 2 presents an overview of this
chapter by way of identifying the research questions and hypotheses driving this study
together with an overview of the literature supporting why the research questions are
important.

37

Table 2. Hypotheses with Literature

Hypothesis What Literature Says
H
1
- Age

Bandura, 1959- Main tenet that people learn by observing others
and as youth grow, they strive at directing and monitoring their
own behaviors.

Gottfredson & Hirschi, 1990- Theorized that self control remains
stable over time and counters ―life course‖ research that views
crime as age related.

H
2
- Ethnicity Blomberg & Lucken, 2000- Identified patterns found in prisons
by which inmates adopted behavioral norms and values created
an inmate subculture particularly among ethnicities.

H
3
- Special Education

Foley, 2000- Found that school failure was common among
incarcerated youth.

Todis, Bullis, Wainthrup, Schultz, & D’Ambrosio, 2001- Argue
that youth with disabilities who exhibit maladaptive behaviors
have serious impairment in their abilities to perform successfully
in society.

H
4
- Significant Other

Werner & Smith, 1992- Identified two protective factors
associated with successful adult adaptation, (1) having social
competence and independence as a toddler and (2) having
competent parental and caregiving styles as a child with
emphasis on having a mother.

H
5
- Offenses Leading to
Incarceration

Gottfredson & Hirschi, 1990- Found that those committing
crimes and maladaptive behaviors as youth through adulthood
had exhibited conduct problems early in life.

H
6
- Exposure to High Risk
Experience

Dembo & Schmeidler, 2003- Found a large number of juvenile
offenders were victims of neglect or abuse, more than 20% had
extensive mental health problems that exceeded the clinical
range, and many had high rates of overlapping involvement in
both violent and non-violent crimes.

H
7
- Temper and Facility Success

Boekaerts, 1999- Argued that the choice of cognitive strategies,
use of metacognitive knowledge, and choice of goals and
resources are necessary for self regulation.

H
8
- Impulsivity and Facility
Success

Silverman & Ragusa, 1992- Found correlations between
compliance and performance on tasks.

Hand & Lebo, 1954- Found that overcrowding can be a
significant variable in youth incarcerated facilities.

H
9
- Risk Seeking and Facility
Success

Zimmerman, 1986- Argued that self regulation proved the
number one predictor of student achievement scores.

38

CHAPTER THREE

METHODOLOGY

Researchers have shown that self control is necessary in order for learning to take
place (Bandura, 1989; Foley, 2001; Zimmerman, 1986). Self regulated learning,
including the use of metacognition skills to direct one’s learning, and choice of goals,
must exist in order for student achievement to occur (Boekaerts, 1999). According to
Caldwell, Rudolph, Troop-Gordon, and Kim (2004), youth tend to perform in ways
which reflect their views about themselves and those who possess positive self-
perceptions are more apt to succeed physically, socially, and academically.
Unfortunately, little research exists identifying what prompts self control, or the lack of
it, among incarcerated youth.
The purpose of this study is to examine the construct of self control to determine
what characteristics contribute to high levels of self control among incarcerated youth
and if there is a correlation between youth who possess high self control and success
outcomes within a correctional facility. The researcher followed a quantitative non-
experimental research design using descriptive, correlational, and secondary data analysis
study.
This chapter provides an overview of the methodology that was used in this study.
Included with the purpose of the study is a description of the setting, background of the
incarcerated youth whose data were examined, description of the self control instrument,
the research design, the data collection procedures, and the data analysis methodologies.
The researcher used inferential data analyses to examine the construct of self control
particularly with variables such as age, ethnicity, special education eligibility, identified

39

significant other, and previous high-risk encounters. Included with the purpose of the
study is a description of the instrumentation, setting, the study participants, the survey
inventory, and the research design that describes the data collection procedures and data
analysis methodologies. The chapter concludes with study strengths and limitations.
The researcher examined levels of self control as reported by youth as well as
success indicators for youth incarcerated at the Hawaii Youth Correctional Facility
(HYCF). Indicators such as student write ups and time-out referrals along with academic
indicators such as Multidisciplinary Team meeting reports were examined to determine
measures of student success for incarcerated youth at HYCF. The researcher attempted
to investigate the premise that youth with high self control appear to get better grades and
be more successful (Wolfe & Johnson, 1995).
Subjects
Youth at the Hawaii Youth Correctional Facility (HYCF) are incarcerated for
serious law violations, flagrant and extreme disregard of school attendance, conduct, and
program non-compliance. The typical youth is between 14 and 18, part-Hawaiian,
functioning in the 25th percentile academically, and at least one year behind in grade
placement. In addition, approximately 60 to 85% of these youth are eligible for special
education services (Office of Youth Services, 2005).
This study examined data from incarcerated youth at the Hawaii Youth
Correctional Facility who ranged in age from 15 through 18 and originated from
throughout the State of Hawaii. The length of stay for youth in the Hawaii Youth
Correctional Facility ranged from approximately 30 days to a maximum of 3 years. In
order for youth to be considered as subjects for this study the criteria included (1)

40

sentencing (or remaining days of sentencing) of more than 60 days; (2) non-completion
of high school diploma requirements according to the Hawaii Department of Education;
(3) completion of intake Grasmick et al. Scale Survey; completion of intake Pertinent
Information form; (4) completion of at least one Multi-Disciplinary Team meeting, and
(5) completion of STAR reading assessment test within first 10 days of attending school
setting.
The initial group of subjects was 83 youth. However, 33 youth were excluded
from this study. Twelve youth had less than 60 days remaining on their sentences and an
additional 21 youth completed the Hawaii Department of Education diploma
requirements, thereby leaving a total of 50 subjects who met qualifying criteria for this
study.
Instrumentation
In July 2009, the transition counselor at the Hawaii Youth Correctional Facility
(HYCF) aimed to find a prompt assessment that would help gauge the affect of youth
entering HYCF. In determining the best instrument, the researcher provided the
transition counselor with data from Peterson and Seligman’s work and their analysis of
self control and self regulation models (2004). The Grasmick et al. Low Self control
Scale (1993) appeared to have good psychometric properties, face validity, measures in
more diverse behavioral spheres, and a high capacity to produce significant results
(Peterson & Seligman, 2004). Therefore, the transition counselor, with the support of the
facility, chose to utilize the Grasmick et al. Scale (1993).
The Grasmick et al. Scale was developed to test the core empirical research of
Gottfredson and Hirschi (1990), General Theory of Crime. In their research, Gottfredson

41

and Hirschi (1990) argue that individuals with low self control make high-risk choices
that may be a contributing factor to the cause of crime. The Grasmick et al. Scale
provides data on six key areas of low self control (impulsivity, insensitivity, preference
for easy tasks, and preference for physical tasks, temper control, and risk-taking). This
instrument consists of 24 questions, four questions in each of the six key areas covering
low self control. For each of the 24 questions, a four-point Likert Scale containing no
mid-point will be used that would force the subject to make a choice.
From September 2009 through December 2009, data were taken from the
transition counselor at HYCF (primary source) regarding youth responses to their
Grasmick et al. Scale. Each youth was identified by a coded number system. The
researcher examined the data from the Intake Welcome Process that was already in place
within the facility that provided orientation information for all new youth as a process
fulfilling one of the requirements of a provision response to a Memorandum of
Agreement between the Hawaii Youth Correctional Facility and the United States
Department of Justice.
The data examined were collected and kept by the transition counselor. The
transition counselor provided the researcher with a data file that was sequentially
numbered so that the researcher was able to sort the information without losing the
integrity of the data. The researcher requested that the counselor strip all identifying
information thereby assuring that the researcher would not be able to identify exactly
which youth was associated with specific responses. The data source from the
counselors, stripped of all identifying information was considered the secondary source
data. In addition, the Hawaii Youth Correctional Facility also provided the researcher

42

access to confidential youth records that were stripped of any identifying data also coded
to align with Grasmick et al. Scale data.
Barlow (1991) confirmed six components of low self control and argued that once
these components are established in childhood they remain constant throughout the life of
the individual. The six components include: (1) risk seeking behaviors, (2) self
centeredness, (3) preference of simple versus complex tasks, (4) impulsivity, (5) physical
activities, and (6) temper. Using items from the Grasmick et al. Scale, the following
Table 3 identified the research questions: (1) What characteristics contribute to student
self control for incarcerated youth? (2) Is there a correlation between youth self control
and success outcomes for youth within a youth correctional facility?

43

Table 3. Research Questions with Grasmick et al. Scale & Facility Indicators

Research Questions Indicators

What characteristics contribute
to youth self control in an
incarcerated setting?

 Self-Centeredness (Items 21-24)

 Simple versus complex tasks
(Items 9-12)

 Physical Activities (Items 1-4)

Is there a correlation between
youth self control (impulsivity,
risk-seeking, and temper) and
outcomes (HYCF level
movement and STAR reading
scores) within a youth
correctional facility?

 Temper (Items 21-24)

 Impulsivity (Questions 13-16)

 Risk Seeking (Items 5-8)

 Support through program level
movement/Multi disciplinary Team
reports

 Support through STAR Reading Scores

44

Setting
In 1951, Act 54 established the names of the facility known in Hawaii as the
Koolau Boys Home and Kawailoa Girls Home. Act 212, which followed Act 54, called
for the consolidation of both homes under a single administrator. Under the State of
Hawaii Government Reorganization Act of 1959 (Statehood) the administration of the
boys and girls home was transferred to the Department of Social Services. The names of
the homes were changed to the Hawaii Youth Correctional Facility (HYCF) as a branch
of the Hawaii Corrections Division, Department of Social Services and Housing.
The Hawaii Youth Correctional Facility (HYCF) is the only facility in the state of
Hawaii for incarcerated male and female youth offenders who are adjudicated for a
period of at least 60 days. The facility uses Olomana School, a public alternative school,
to service the students’ academic as well as behavioral needs. Olomana School continues
under the administration of both a principal and vice principal. All staff role groups at
the school are represented by collective bargaining agents (HGEA, HSTA, & UPW). The
school is held accountable to align the course offerings to the same Hawaii State Content
and Performance standards and benchmarks as all other schools in the Hawaii State
Department of Education and must strive to meet the benchmarks of the No Child Left
Behind Act. The school is an agent that strives to mediate school success to accelerate
credit recoupment to assist students with promotion or a high school diploma.
In addition to a high school diploma, youth at HYCF are also afforded vocational
education opportunities as well as a General Equivalence Diploma (GED) program. All
servicing efforts at HYCF comply with established security rules and regulations that

45

apply to facility and school personnel as well as to individual youth whose movements
are limited by security control levels and infrequently by court decree.
Research Design
Using data from youth responses to the Grasmick et al. Scale and youth records
provided by the facility, the researcher presented the data for this study by following
comparative research methods identified by Bollen, Entwisle, and Alderson (1993),
which are as follows: Do the findings of the study demonstrate the importance of having
explicit measurement models before analyzing the measures? Are the indicators clearly
aligned to outcome measures? And, are the data analyses aligned to the research
questions? In this chapter, the researcher provides evidence of the questions above in the
research methodology used. Statistical calculations for this study were conducted using
Excel 2007, SISA Binomial online t-test software (Uitenbroek, 1997), and Statistics
Software version 1.1.23-r-5 (Wessa, 2010).
By determining the mean and standard deviation for each of the items on the
Grasmick et al. Scale, the researcher was able to do further analysis by groupings to
determine the standard error of mean (SEM) for a sampling distribution of means. This
quantitative study used measurement models of comparison (through the use of t-tests)
and correlational analysis (through the use of Spearman’s Rho) to examine youth self
control and the relationship to level movement and academic accomplishment by
incarcerated youth at the Hawaii Youth Correctional Facility (HYCF). The quantitative
design is aligned to research on self-regulation (Bandura, 1989), specifically self control,
and the outcome measures were aligned to determine the impact self control of youth had
on youth success within HYCF. This study involved examining data already collected

46

from incarcerated youth at HYCF. All data included in this study was collected within
one semester (from September 1, 2009 through December 1, 2009) and was used to
answer both research questions of this study.
Data Analysis
T-test for independent means was used to compare groupings to address research
question one. Six t-tests were conducted using continuous scaled dependent variable of
self-control and the categorical independent variables of age, ethnicity, special education
eligibility, identified significant other, infractions resulting in incarceration, and previous
high-risk encounters.
To address research question two, the researcher referred to the findings in work
by Delisi, Hochstetler, and Murphy (2003) in which they refer to the categories of
temper, impulsivity, and risk seeking categories as having the most differential predictive
power among the subscales of the Grasmick et al. Scale. The researcher then used
Spearman’s Rank-Order Correlation to determine the relationship between temper,
impulsivity, and risk seeking with facility success indicators of youth level system
movement and STAR Reading scores.
Following the gathering of all data, the researcher first organized the data into
descriptive tables representing the demographic composition of the youth in this study.
Next, the researcher analyzed mean and standard deviation scores for all items of the
Grasmick et al. Scale and then determined the relationship between incarcerated youth
whose scores fell into the low range on the Grasmick Scale and the data used both by the
youth facility for level movements and monthly Multi-Disciplinary Team (MDT)
outcomes.

47

To test for the difference between facility level movement, STAR reading scores,
and Grasmick et al. Scale scores, Spearman Rank-Order correlation coefficient was
conducted. In addition, the researcher used an analysis of variance (or ANOVA) to
determine the correlations between the participant survey responses and the indicators of
program level movement and weekly school points. The researcher aimed to examine the
relationship between Grasmick Scale scores with facility level movement and weekly
point scores. The dependent variables were facility level movements and weekly school
points while the independent variable was self control identified through the Grasmick et
al. Scale responses.
Strengths and Limitations
Two significant strengths were identified in this study. The first strength was in
the validity and reliability of the instrument selected for this study. The Grasmick et al.
Scale was previously administered in studies with incarcerated populations. Therefore,
the Grasmick et al. Scale instrument allowed the researcher to draw defensible, or valid,
conclusions about the characteristics of the participants in the study. The second strength
of the study was in the setting. The Hawaii Youth Correctional Facility (HYCF) is the
only facility in the state servicing incarcerated youth; therefore, the researcher did not
need to be concerned with surveying participants who may be scattered over a large
geographic even though the participants originated from different parts of the State.
One limitation to this study was that the participants are all incarcerated youth.
The researcher was able to obtain approval from institutional review board (IRB) for this
study because it was deemed to be a study based on secondary source data and the
researcher adhered to strict guidelines specifically involving prisoners. A second

48

limitation involved the high transiency of youth based on their varying lengths of stay, or
sentences, at HYCF. The length of stay may have led to irregular sampling intervals
which resulted in no available data for a post Grasmick et al. Scale scores.

49

CHAPTER FOUR

FINDINGS

This chapter provides an analysis and description of data from 50 incarcerated
youth at the Hawaii Youth Correctional Facility (HYCF) during the fall of 2009. The
purpose of this study was to determine what characteristics contributed to high self
control for these incarcerated youth and to determine if there was a correlation between
self control and success outcomes within a correctional facility for youth. The results in
this chapter was obtained from an analysis of the HYCF Intake Process and Multi-
Disciplinary Team (MDT) data, which provides a brief description of all youth offenders
as well as their aptitude upon entry.
Results from this study are presented in three sections of descriptive analyses and
concludes with the analyses of research questions and hypotheses stated in Chapter 1.
The first section identifies youth descriptive highlights such as age, county origin,
predominant ethnicity, special education eligibility, significant other, previous
encounters, and offense(s) resulting in incarceration. The second section focuses on
research question one and the variables contributing to self-control for incarcerated
youth. The third section addresses research question two and examines correlations
between youth self control and success outcomes while incarcerated. Both sections two
and three used multivariable analysis representing a sufficient set of statistics.
The following research questions were formulated to evaluate descriptive data
during the fall of 2009 on youth incarcerated at the Hawaii Youth Correctional Facility:

50

1. What characteristics contribute to self control for incarcerated youth?
2. Is there a correlation between youth self control (impulsivity, risk-seeking, and
temper) and outcomes (HYCF level movement and STAR reading scores)
within a youth correctional facility?
The research hypotheses for this study were as follows:
Hypothesis 1: There is no difference in self control (impulsivity, risk seeking, or
temper) between age groups for incarcerated youth.
Hypothesis 2: There is no difference in self control (impulsivity, risk seeking, or
temper) between part-Hawaiian and non-Hawaiian incarcerated youth.
Hypothesis 3: There is no difference in self control (impulsivity, risk seeking, or
temper) between special education and non-special education eligible incarcerated
youth.
Hypothesis 4: There is no difference in self control (impulsivity, risk seeking, or
temper) between incarcerated youth who identified having a mother as the most
significant other in their lives and those who do not.
Hypothesis 5: There is no difference in self control (impulsivity, risk seeking, or
temper) between violent youth offenders and non-violent youth offenders.
Hypothesis 6: There is no difference in self control (impulsivity, risk seeking, or
temper) between incarcerated youth who had less than three high risk encounters
and those who had three or more high risk encounters.
Hypothesis 7: There is no correlation between low temper scores and high level
movement or STAR reading scores.

51

Hypothesis 8: There is no correlation between low impulsivity scores and high
level movement or STAR reading scores
Hypothesis 9: There is no correlation between low risk seeking scores and high
level movement or STAR reading scores.
Descriptive Data

Between September 1 and December 1 of 2009, 83 youth were incarcerated at the
Hawaii Youth Correctional Facility. These youth originated from all four counties in the
State of Hawaii. From this pool of eighty-three incarcerated youth, subjects for this study
was selected based on the following criteria; sentencing (or remaining days of
sentencing) of more than 60 days; non-completion of high school diploma requirements
according to the Hawaii Department of Education; completion of intake Grasmick et al.
Scale Survey; completion of intake Pertinent Information form; completion of at least one
Multi-Disciplinary Team meeting, and completion of STAR reading assessment test
within first 10 days of attending school setting. A total of 33 youth were excluded from
being subjects of this study. Twelve youth had less than 60 days remaining on their
sentences and an additional 21 youth completed the Hawaii Department of Education
diploma requirements, thereby leaving a total of 50 subjects who met qualifying criteria
for this study.
A total of fifty youth (N=50) met the eligibility requirements for this study.
Forty-four percent (22 youth) were incarcerated at least one other time. The fifty youth
consisted of eight females (16%) and 42 males (84%). The following six tables (4-10)
represent the demographic overview of these 50 youth. Existing data on subjects’ age and
the number of years spent in public school in Hawaii is described by mean and range.

52

Table 4. Description of Subjects: Age and Number of Years in Public School
in Hawaii

Variable Mean Range

Age 16 14-18
No. of Years in Public School 10 7-12

As shown in Table 4, the mean average for the youth subjects was 16, with a
range of 14 to 18 years of age with a mean of 10 years in public school.
Being that the Hawaii Youth Correctional Facility is the only one of its kind in
Hawaii, Table 5 presents a demographic overview of youths by their originating counties
and districts. The subjects in this study originated from each of the four counties
(Honolulu, Maui, Kauai, and Hawaii) representing eight districts (Honolulu, Leeward,
Central, Maui, Kona, Windward, Hilo, and Kauai). Thirty-four percent (17 youth) were
from Honolulu district and this group represented the largest concentration of the
subjects. Fourteen percent (7 youth) were from the Leeward district.
Table 5. Demographic of Subjects by District

District No. of Students Percentage
Honolulu 17 34%
Leeward 7 14%
Central 6 12%
Maui 6 12%
Kona 4 8%
Windward 4 8%
Hilo 3 6%
Kauai 3 6%

53

Thirty-four percent (17 youth) were from Honolulu district and this group
represented the largest concentration of the subjects. Fourteen percent (7 youth) were
from the Leeward district. Both Central and Maui districts were represented by 12% (6
youth). Both Kona and Windward districts were represented by 8% (4 youth). Both Hilo
and Kauai districts were represented by 6% (3 youth). There were five youth (10%) who
identified themselves as being homeless prior to incarceration.
The ethnicity of the youth subjects were identified from the facility Pertinent
Information form upon youths’ intake process (see Table 6).
Table 6. Description of Youths’ Ethnicity

Predominate Ethnicity No. of Students Percentage

Part Hawaiian 19 38%
Caucasian 5 10%
Samoan 5 10%
Filipino 5 10%
Micronesian 4 8%
Portuguese 3 6%
Hispanic 2 4%
Puerto Rican 2 4%
Japanese 2 4%
African American 1 2%
American Indian 1 2%
Laotian 1 2%

The majority of youth incarcerated during the time of this study were Part
Hawaiian while a small percentage (18% or 9 youth) represented Hispanic, Asian,
African American, American Indian, and Laotian.

54

The majority of youth were identified as being non-disabled (ND). Thirty-four
percent (18 youth) were identified as eligible for special education services. The youths’
disabilities included Emotional/Behavioral Disabilities (ED), Specific Learning
Disabilities (SLD), Mental Retardation (MR), and Other Health Impairments (OHI).
Table 7. Percent of Youth by Disability and Age

14 15 16 17 18 Total
ND 8% 10% 22% 26% 0 66%
ED 2% 4% 2% 6% 2% 16%
SLD 0 0 6% 0 2% 8%
MR 0 0 0 2% 0 2%
OHI 0 4% 0 4% 0 8%
Total: 10% 18% 30% 38% 4%

Sixteen percent (8 youth) of the 50 subjects were youth with Emotional/
Behavioral disabilities while youth with Mental Retardation represented only 2% (1
youth) of the 50 subjects.
An overview of the most significant other in the youths’ lives was examined by
the researcher. Eighty-eight percent (44 youth) were identified as having one or both
parents in their household. Twelve percent (6 youth) were identified as not having either
a mother or father in their household. The significant other in the youths’ household was
most frequently their mother, as represented by 52% (26 youth). Fourteen percent (7
youth) identified their father as the most significant other in their household. Twenty-two
percent (11 youth) identified both mother and father as being the most significant other in

55

their household. Eight percent (4 youth) was represented by Child Protective Services
and the remaining 4% (2 youth) had a grandmother and an uncle as their significant other.
Table 8. Significant Other in Youths’ Household

Parent/Guardian No. of Youth Percentage
Mother 26 52%
Both Parents 11 22%
Father 7 14%
Child Protective Services 4 8%
Grandmother 1 2%
Uncle 1 2%

Data on youths’ histories indicated an array of high risk encounters. According to
the HYCF Pertinent Intake forms, categories of ―high risk‖ included one or more
exposures to the following: psychiatric interventions, sexual abuse, alcohol, illicit drugs,
assault (physical abuse), gangs, and pregnancy. Ninety-six percent (48 youth) in this
study had exposure to one of more of these ―high risk‖ encounters.
Of the 48 youth, 83% (40 youth) had a history of having more than one high risk
encounter. Analysis of youth by age and previous encounters showed that all ages were
represented in the categories of alcohol use, illicit drug use, and assaultive behaviors.
The most frequent high risk encounter was assaultive behaviors. The following groups
engaged in the high risk behaviors of assault: 80% of the participants of 14-year-olds,
slightly less than 45% of 15- year-olds, half of the 16-year-olds, slightly less than 68% of
17-year-olds, and half of 18-year-olds. The second most frequent high risk behavior
resulted in psychiatric interventions. The following groups were in this cluster: 60% of

56

14-year-olds, slightly less than 45% of 15-year-olds, slightly less than 75% of 16-year-
olds, and half of the 17-year-olds. The most infrequent high risk encounter was
pregnancy, as indicated by one 16-year-old youth. Additionally, nearly 17% of the males
in this study (7 youth) had fathered at least one child. The second most infrequent high
risk encounter by age was sexual abuse by 15-year-olds and psychiatric interventions by
18-year-olds (see Table 9).
Table 9. Percent of Youth by Age and Previous High Risk Encounter(s)

AGE 14 15 16 17 18 ______
No. of Youth 5 9 16 18 2 (N=50)

*PSYCH. INT. 60% <45% <69% 50% 0
*SEXUAL 40% 0 25% <6% 50%
*ALCOHOL <7% <34% <13% <28% 100%
*DRUG USAGE 40% <23% <44% <34% 100%
*ASSAULTIVE 80% <45% 50% <67% 50%
*GANG MEMBER 20% 0 <13% <6% 50%
*PREGNANCY 0 0 6% 0 0
UNDETERMINED 20% 0 0 <6% 0
* High risk indicator according to Hawaii Youth Correctional Facility Pertinent Form

Youth offenses were categorized into those sentenced for violent crimes, those
sentenced for property crimes, and public health crimes. Fifty-four percent (27 youth)
were committed for violent crimes, 32% (16 youth) were committed for property crimes,
and 14% (7 youth) were committed for public health crimes. The violent crimes ranged
from aggravated assault, robbery, kidnapping, to sex assault. The property crimes ranged

57

from theft, burglary, to criminal property damage. Public health crimes included
prostitution, indecent encounter, and probation violation (see Table 10).
Table 10. Percentage of Youth by Age and Offense

AGE 14 15 16 17 18 ______
No. of Youth 5 9 16 18 2 (N=50)
Violent Crimes

Sex Assault 20% 0 6% 0 0
Aggravated Assault ** 40% 0 0 0 0
Aggravated Assault * 20% 0 20% 0 0
Aggravated Assault 20% 0 12% 17% 0
Kidnapping ** 0 0 6% 0 0

Property Crimes

Robbery * 0 11% 0 5% 50%
Robbery 0 34% 6% 22% 50%
Burglary 0 11% 0 12% 0
Theft 0 11% 20% 17% 0
Motor Vehicle Theft 0 11% 6% 0 0
Criminal Property Damage 0 11% 12% 12% 0

Public Health Crimes

Prostitution 0 0 0 5% 0
Indecent Encounter 0 0 0 5% 0
Probation Violation 0 11% 12% 5% 0

** Two other infractions
* One other infraction

Data showed that all 14 year-old youth in this study were sentenced for violent crime
offenses and both 18-year-old youths were sentenced for property crimes. Eight-nine
percent of the 15 year-old youth (8) and 68% of the 17-year olds (12 youth) were
sentenced for property crimes. A total of 28 youth were incarcerated for violent crimes
compared to 22 youth incarcerated for non-violent crimes (property and health).

58

Statistic and Data Analysis
Statistical calculations for this section were analyzed using Excel 2007, SISA
Binomial online t-test software by Uitenbroek (1997), and Statistics Software version
1.1.23-r-5 by Wessa (2010). Applicable descriptive and correlational statistical analyses were
conducted in this study examining the subscale groupings of impulsivity, risk seeking, and
temper.
A descriptive statistical analysis using t-tests performed on age, ethnicity, special
education eligibility, significant other, previous infractions leading to incarceration.
When the culminating t-tests is large (<.05), the null hypothesis of independence is
rejected. Commonly, if the probability or p-value is small (>.05), the hypothesis of
independence is rejected. Contingent on these numbers, an interpretation of an
association between variables can be made for the population groups included in this
study. The results are provided below in the following sections.
Research Question #1
What characteristics contribute to self control for incarcerated youth?

The researcher analyzed youths’ responses to the Grasmick et al. scale that is
categorized into six distinct sections of self control. Responses to the Grasmick et al.
scale statements ranged from ―agree strongly,‖ ―agree somewhat,‖ ―disagree somewhat,‖
or ―disagree strongly‖ (score 4 through 1 respectively) for each item. A low response
score equated to high youth self control.
A composite of subscale analysis was performed to strengthen the reliability for
further item by item tests described in this chapter (see Table 11). The researcher aimed
to use the data analyzed to make appropriate and meaningful inferences that would lead

59

to a validation of work done for this study. Once a general idea of subscale comparison
scores was examined, scores from the categories showing the lowest mean (indicating the
areas of highest youth self control) were further analyzed to determine if any statistically
significant findings could be discovered.
Subscale data indicated the mean to be the lowest in the category of impulsivity;
however the temper category had the closest standard deviation. In addition, the category
of score physical activity produced the strongest agreement responses as reflected by the
largest mean compared to all the other categories.

60

Table 11. Mean and Standard Deviations for Independent Self Control Scale
Items (4= strong self control: 1=low self control)

Item Item
Mean
Item
SD

1. If I had a choice, I would almost always rather do something physical than
something mental.
2.86

0.81
Physical
Activities
2. I almost always feel better when I am on the move than when I am sitting and
thinking. 3.00

0.70
3. I like to get out and do things more than I like to read or contemplate ideas.
2.84

0.79
4. I seem to have more energy and a greater need for activity than most other people
my age. 2.88

0.85
5. I like to test myself every now and then by doing something a little risky.
2.90

0.68
Risk Seeking
6. Sometimes I will take a risk just for the fun of it.
2.82

0.85
7. I sometimes find it exciting to do things for which I might get in trouble.
2.74

0.85
8. Excitement and adventure are more important to me than security.
2.80

0.73
9. I frequently try to avoid projects that I know will be difficult.
2.72

0.67
Simple Tasks
10. When things get complicated, I tend to quit or withdraw.
2.76

0.85
11. The things in life which are easiest to do bring me the most pleasure.
2.70

0.79
12. I dislike really hard tasks that stretch my abilities to the limit.
2.86

0.76
13. I often act on the spur of the moment without stopping to think.
2.72

0.67
Impulsivity
14. I don’t devote much thought and effort to preparing for the future.
2.66

0.72
15. I often do whatever brings me pleasure here and now, even at the cost of some
distant goal. 2.82

0.69
16. I’m more concerned with what happens to me in the short run than in the long run.
2.76

0.80
17. I lose my temper pretty easily.
2.78

0.58
Self -
Centered
18. Often, when I’m angry at people I feel more like hurting them than talking to them
about why I am angry. 2.84

0.79
19. When I’m really angry, other people better stay away from me.
2.82

0.66
20. When I have a serious disagreement with someone, it’s usually hard for me to talk
calmly about it without getting upset. 2.96

0.70
21. I try to look out for myself first, even if it means making things difficult for others.
2.82

0.72
Temper
22. I’m not very sympathetic to other people when they are having problems.
2.84

0.74
23. If things I do upset people, it’s their problem not mine. 2.84 0.71
24. I will try to get the things I want even when I know it’s causing problems for others. 2.74 0.69

61

Age and Self Control Variable
The first hypothesis stated, ―There is a difference in self control (impulsivity, risk
seeking, or temper) between age groups for incarcerated youth.‖ To determine if age and
self control were related, and to what extent age differences mattered in relation to self
control, a one way ANOVA was conducted by age for 14, 15, 16, and 17-year- olds.
Youth responses in the category of ―self-centered‖ were most significant. The
category of self-centered consisted of items 17-20. The data from item 17 indicated an F-
value of 4.36 with a significance of .009 (p). The F-value of 4.18 and significance of
.011 (p) was the result for item 18. The analysis of item 20 indicated and the F-value of
4.95 with a significance of .005 (p). The item 18 data showed no statistical significance.
Although the category of physical activity had the highest mean (2.89) of all six
categories, the standard deviation range (.70-.85) for this section indicated a larger range
of youth responses. A confined standard deviation (.68) with a mean of 2.85 was found
for the category of self-centered. Both categories of risk seeking and impulsivity had the
same standard deviation (.77) with the mean of 2.81 and 2.74 respectively.

62

Figure 2. One-Way Design Using Error Bars to Represent Age Group
Grasmick et. al. Scale Responses

N=5 N=2

A comparison of responses for all 24 Grasmick et al. scale items in Figure 2
indicated 14- year-olds (Group A) with a mean of 2.57 and a 95% confidence interval for
M: 2.47 through 2.67 with a standard deviation of 0.31. The mean of 15-year-olds
(Group B) was 2.83 and a 95% confidence interval for M: 2.74 through 2.93 with a
standard deviation of 0.242. Seventeen year olds (Group D) showed a mean of 3.03 with
a 95% confidence interval for M: 2.93 through 3.12 and a standard deviation of 0.16.

63

The mean of Group E was 3.19 and a 95% confidence interval for M: 3.09 through 3.28
with a standard deviation of 0.29. Table 12 indicates the independent variable of self
control and age are related. As age increases self control decreases.
A one-way ANOVA between the two highest Grasmick et al. Scale composite
mean score categories (physical activities and impulsivity) indicated an increase in low
self control responses as age increased in all age groups except for the age Group C (16
year-olds) with the mean of 2.58, a 95% confidence interval for M: 2.48 through 2.67,
and the standard deviation of 0.11. Higher scores indicate lower self control. Although
Group A (14 year-olds), Group B (15 year-olds), Group D (17 year-olds) and Group E
(18 year-olds) all showed incremental increases in mean scores as age increased, the
ANOVA scores failed to show statistically significant findings to support the first
hypothesis ―There is a difference in self control (impulsivity, risk seeking, or temper)
between age groups for incarcerated youth.‖ Therefore the null hypothesis was not
rejected.

64

Table 12. Grasmick et al. Scale Results by Individual Mean and Section Mean
and Age

Item

Mean

SD

Section
Mean
14-yr-
old
Mean
15-yr-
old
Mean
16-yr-
old
Mean
17-yr-
old
Mean
18-
yr-
old
Mean
1 2.86 .80

2.99

2.60 3.11 2.43 3.11 3.50
2 3.00 .69 3.20 3.33 2.68 3.11 3.50
3 2.84 .79 2.60 3.00 2.63 3.27 3.50
4 2.88 .84 2.20 3.33 2.63 3.27 3.00
5 2.90 .67

2.82

3.00 3.00 2.38 3.05 3.50
6 2.82 .84 2.40 3.00 2.81 2.94 3.50
7 2.74 .85 2.60 2.88 2.75 2.61 3.00
8 2.80 .72 2.40 2.66 2.60 3.05 2.50
9 2.72 .67

2.74

2.20 2.66 2.63 3.00 3.00
10 2.76 .84 2.20 2.33 2.60 3.22 3.00
11 2.70 .78 2.60 2.66 2.50 3.00 3.00
12 2.86 .75 3.00 2.77 2.50 3.11 3.00
13 2.72 .67

2.79

2.60 2.66 2.50 3.00 3.00
14 2.66 .71 2.20 2.77 2.43 2.77 3.00
15 2.82 .69 2.20 3.11 2.63 2.94 3.00
16 2.76 .79 3.00 2.77 2.43 2.94 3.00
17 2.78 .58

2.88

2.40 2.77 2.50 3.05 3.50
18 2.84 .79 2.20 2.66 2.56 3.16 3.50
19 2.82 .66 2.60 3.00 2.50 3.00 3.50
20 2.96 .69 2.40 3.00 2.56 3.33 3.50
21 2.82 .71

2.82

2.80 2.66 2.63 3.05 3.00
22 2.84 .73 3.00 2.77 2.68 2.88 3.00
23 2.84 .71 3.00 2.55 2.75 2.83 3.50
24 2.74 .69 2.40 2.66 2.50 2.94 3.00

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Ethnicity as a Self Control Variable
To verify if ethnicity was a factor contributing to self control for incarcerated
youth, a t-test was used to determine if the means between two independent samples were
statistically different (see Table 13). Because the majority of youth in the study were
predominately part-Hawaiian, and the population size of the other predominate ethnicities
were slight; a t- test was conducted between part-Hawaiian (PH) and non-Hawaiian (NH)
groups. The second hypothesis stated, ―There is a difference in self control (impulsivity,
risk seeking, or temper) between part-Hawaiian and non-Hawaiian incarcerated youth.‖
The t-tests yielded the most noteworthy finding in the category of impulsivity,
specifically in items 13 through 16.
The t-tests indicated the PH and NH groups differed on their view of preparing for
the future (t (33) =2.18, p<.05) and on what happens to them in the ―short run rather than
the long run‖ (t (32) =2.07, p<.05). A statistical difference was found in the PH group
particularly in their view of themselves as less impulsive by devoting more ―thought and
effort in preparing for their futures‖ and in being more concerned with what happens to
them in the long run as compared to their non-Hawaiian counterparts. Therefore, the
second hypothesis ―There is a difference in self control (impulsivity, risk seeking, or
temper) between part-Hawaiian and non-Hawaiian incarcerated youth‖ was accepted. No
additional statistically significant differences between the PH and NH groups were
supported statistically (see Appendix C).

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Table 13. Impulsivity Means & Standard Deviations by Ethnicity Variable

Variable PH (N=19) NH (N=31) Test Statistic
Item

M SD M SD t p df
13 2.47 .99 2.77 .67 1.67 .25 4.8
14 *2.14 .85 *2.65 .71 2.18 .03 33
15 2.46 .89 2.90 .60 1.90 .06 4.8
16 *2.35 1.01 *2.71 .82 2.07 .04 32

Note: *Statistically significant at the p<.05 level

Special Education Eligibility as a Self Control Variable
No significant findings were noted in the subscale categories of impulsivity, risk
seeking or temper and therefore, the third hypothesis was rejected as t-test scores between
special education and non-special education eligible incarcerated youth failed to yield
statistically significant findings (see Appendix D).
Significant Other as a Self Control Variable
Similar findings to the ethnicity variable were apparent in the area of impulsivity
for youth who had a mother (MO) as their most significant other factor (see Table 14).
The largest representation identifying mother as most significant other was 26. Ten
youth identified someone other than a mother (NM) as the most significant in their lives.
Youth who identified both parents were omitted from this analysis to avoid redundancy
(N=10). The population of those other than MO and NM were not included in this
analysis due to their small size (N=4).

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Table 14. Summary of One-Way ANOVA on Impulsivity for MO and NM
Groups

SOURCE ______SS df MS _F___ P
Between groups 2.281 1 2.281 4.369 0.042
Within groups 25.058 48 0.522
___________ ______ ___
Total 27.338 49

T-test for item 14 indicated the MO group as less impulsive and viewed
themselves as putting forth more ―effort in preparing for the future‖ (t (36)= -2.06, p<.05)
compared to the group not identifying a mother (NM) as their significant other.
Therefore, the fourth hypothesis stating, ―There is a difference in self control
(impulsivity, risk seeking, or temper) between incarcerated youth who identified having a
mother as the most significant other in their lives and those who do not‖ was accepted.
Responses to item 15 indicated the MO group viewed themselves as less likely to obtain
pleasure at the cost of some distant goal (t (33) =3.48, p<.05). Within the MO and NM
youth groups, T-tests indicated no other significant difference (see Appendix E).
Table 15. Comparison of Mean & Standard Deviations between Significant
Other Variable for Self Control

Variable MO (N=26) NM (N=13) Test Statistic
Item

M SD M SD t p df
13 2.73 0.72 2.77 .67 .03 .86 38
14 *2.58 0.86 *2.65 .71 -2.06 .04 36
15 *2.62 0.64 *2.90 .60 -3.48 .001 33
16 2.65 0.94 2.71 .82 .04 .85 38

Note: *Statistically significant at the p<.05 level

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Infractions Resulting in Incarceration as a Self Control Variable
Due to the small population sizes for some infractions youth were categorized into
one of two groups, violent offenders (VO) and non-violent offenders (NVO) that
included those who committed property or public health crimes (see Appendix F). Youth
who fell into both groups were omitted (N=3).
The fifth hypothesis stated, ―There is a difference in self control (impulsivity, risk
seeking, or temper) between violent youth offenders and non-violent youth offenders.‖ T-
test results revealed significant difference in the category of physical activities and risk
seeking, particularly in items 4 and 6 respectively. The NVO group had ―a greater need
for activity‖ than the VO group (t (33) = -2.14, p<.05). The NVO group also had a
greater need to ―take a risk just for the fun of it‖ compared to the VO group (t (33) = -
2.51, p<.05). Therefore, the fifth hypothesis was accepted being that the non-violent
offender group yielded a statistically significant difference in the category of risk seeking
compared to the violent offender group. T-Tests on the remaining categories and items
showed no significant (<.05) difference between the two groups.
Previous High-Risk Encounters as a Self Control Variable
The sixth hypothesis stated, ―There is a difference in self control (impulsivity, risk
seeking, or temper) between incarcerated youth who had less than three high risk
encounters and those who had three or more high risk encounters.‖ The mean scores
according to the number of previous high-risk encounters was examined (see Appendix
F). Furthermore, ANOVA results between ZO group (N=15; zero to one encounter), TO
group (N=20; two encounters), and TH group (n=15; 3-4 encounters) was conducted.

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Findings in the category of temper showed that not only did the average mean
scores increase as the number of high-risk encounters increased, but also youth with more
than three high-risk encounters had a statistically significant low self control when
agreeing that if they ―upset people, it’s their problem not mine.‖ Therefore, the sixth
hypothesis stating ―There is a difference in self control (impulsivity, risk seeking, or
temper) between incarcerated youth who had less than three high risk encounters and
those who had three or more high risk encounters‖ was accepted. No other statistically
significant findings were discovered in the other categories.

Table 16. Summary of One-Way ANOVA on Temper for ZO and TO Groups

SOURCE ______SS df MS _F___ P
Between groups 3.089 2 1.544 3.361 0.043
Within groups 21.600 47 0.460
___________ ______ ___
Total 24.688 49

Based on the statistically significant findings from t-tests conducted for this study
along with hypotheses one through six, the following findings were determined in
answering research question one:
1. Age was not a characteristic contributing to self control (impulsivity, risk
seeking, or temper),
2. Non Hawaiians had higher impulsivity,
3. Special education eligibility was not a characteristic contributing to self
control (impulsivity, risk seeking, or temper),
4. Not identifying a mother as a significant other was a characteristic relating to
higher impulsivity,

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5. Non- violent offenders reported greater risk taking than violent offenders,
6. A high number of high risk encounters (3 or more) was associated with higher
temper.
Research Question #2
Is there a correlation between youth self control (impulsivity, risk-seeking, and temper)
and outcomes (HYCF level movement and STAR reading scores) within a youth
correctional facility?
Following an analysis of the means and standard deviations relating to the first
research question, the researcher noted some interesting trends in the mean and standard
deviation scores that supported existing research by Delisi, Hochstetler, and Murphy
(2003). Considering that the Hawaii Youth Correctional Facility uses two main outcome
indices to determine youth success (STAR Reading scores and facility level movement
promotion) and based on the research by Delisi, Hochstetler, and Murphy (2003) which
indicated that subscale composite items in self control showed temper, impulsivity, and
risk seeking to be the most significant categories, the correlations between self control
and STAR reading and facility level movement were examined. To address the second
research question, Spearman Rho correlation tests were conducted on these three subscale
categories with STAR reading scores and youth level movement.
The first self control variable of temper was compared to both level movement
and STAR Reading scores. The second self control variable of impulsivity was compared
to both level movement and STAR Reading scores. The third self control variable of risk
seeking was compared to both level movement and STAR Reading scores. A low score

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in temper, impulsivity, and risk seeking equated to high youth self control. An alpha
level of .05 was used for all statistical tests.
Relationship between Temper Scores and Youth Level Movement
Fifty youth responses addressing temper (M=2.78, SD=.58) and youth level
movement at the Hawaii Youth Correctional Facility (M=1.02, SD=1.77) were analyzed.
Hypothesis seven stated, ―There is a correlation between low temper scores and high
level movement or STAR Reading scores.‖ A Spearman’s r data analysis revealed a
weak correlation (p >.05), r= .08 or r
2=
.0064 between the two variables. The data
indicated that this correlation was not significant. Therefore, hypothesis seven was
rejected and the null hypothesis was not rejected.
Relationship between Temper Scores and STAR Reading
Responses to item 17 addressing temper (M=2.78, SD=.58) and STAR reading by
grade equivalency scores (M=5.99, SD= 2.69) were analyzed. A Spearman’s r data
analysis revealed a weak correlation, r= -.03 between the two variables as p=.86. STAR
reading scores were not related to temper scores thereby confirming the rejection of
hypothesis seven.

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Relationship between Impulsivity Scores and Youth Level Movement
Data addressing impulsivity showed (M=2.72, SD=.67) for item 13 and youth
level movement (higher level leads to quicker transition to community programming) at
the Hawaii Youth Correctional Facility (M=1.02, SD=1.77) was analyzed. Hypothesis
eight stated, ―There is a correlation between low impulsivity scores and high level
movement or STAR Reading scores.‖ Further analysis indicated using Spearman’s r
revealed a moderate correlation, r= .28 and between the two variables p=.004 indicating
this is not a chance occurrence. T-test for the significance of the coefficient= 2.07 (df=
48). Youth who met level movement requirements reported higher levels of self control
in the area of impulsivity thereby supporting the hypothesis that a relationship exists
between low impulsivity scores and higher level movement by incarcerated youth.
Relationship between Impulsivity Scores and STAR Reading
Impulsivity scores from item 13 (M=2.72, SD=.67) and data addressing STAR
reading by grade equivalency scores (M=5.99, SD= 2.69) was evaluated. A Spearman’s r
data analysis revealed a weak correlation, r=-.05 or r
2
=.10 and between the two variables
p=.62 indicating this was a chance finding. T-test for the significance of the coefficient=
-.39 (df= 48). There a low chance that low impulsivity scores influenced STAR Reading
scores. The data analysis failed to yield any other significant findings between
impulsivity and STAR Reading scores.
Relationship between Risk Seeking Scores and Youth Level Movement
Data addressing risk seeking (M=2.90, SD=.68) from item 5 and youth level
movement at the Hawaii Youth Correctional Facility (M=1.02, SD=1.77) was analyzed.
A Spearman’s r data analysis revealed a weak correlation, r= -.37 and between the two

73

variables p= .35. T-test for the significance of the coefficient= -2.69 (df= 48). Youth who
met level movement requirements still reported low levels of self control in the area of
risk seeking. No significant findings were noted in any of the subscale categories.
Relationship between Risk Seeking Scores and STAR Reading
Item 5 data addressing risk seeking (M=2.90, SD=.68) and STAR reading by
grade equivalency scores (M=5.99, SD= 2.69) was reviewed. A Spearman’s r data
analysis showed a weak correlation, r= -.33 or r
2
= -.18 between the two variables p= .22.
T-test for the significance of the coefficient= -2.45 (df= 48). Youth with high STAR
Reading scores still reported low levels of self control in the area of risk seeking. There
were no significant findings noted in any of the subscale categories leading to the
rejection of hypothesis nine.
Based on the findings from Spearman’s Rho Correlation tests conducted along
with hypotheses seven through nine, the following finding was determined in answering
research question two: A correlation between low impulsivity scores and high facility
level movement existed.
Summary of Findings
In summary, extensive data analyses of youth responses to the Grasmick et al.
scale led the researcher to discover that the theoretical model of self control as a
dependent or independent variable was difficult. Despite these issues, answers to the first
research question point to the following: (1) although increase in age yielded some
interesting findings they were not enough to draw significant conclusions, indicating
increase in age was a factor contributing to low self control, (2) Non Hawaiians had
higher impulsivity, (3) Special Education eligibility was not a factor contributing to low

74

self control in any of the subscale categories (4) Not identifying a mother as a significant
other was a characteristic relating to higher impulsivity, (5) Non-violent offenders
reported greater risk taking than violent offenders, and (6) A high number of high risk
encounters (3 or more) was associated with higher temper.
Despite an exhaustive analysis using Spearman’s Rho Correlation test between
self control variables and facility success outcomes, such as STAR reading scores and
facility level movement increases, the only significant finding was in the relationship
between impulsivity and level movement (r=.28). All other tests to answer the second
research question failed to provide statistically significant correlations between facility
outcomes and youth self control composite categories of temper, impulsivity, and risk
seeking.

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CHAPTER FIVE

CONCLUSIONS AND RECOMMENDATIONS

Chapter 4 tested the hypotheses that there are differences in self control in
comparison to several variables. Results of those tests led answering two research
questions in this study. Test results supported four of the six hypotheses relating to the
first discussion question. Higher degrees of self control were found in youth who had one
or more of the following attributes: (1) were part-Hawaiian, (2) had a mother as
significant other, (3) were violent offenders, and (4) had less than three high risk
encounters. Chapter 4 also tested the hypotheses that there are correlations between three
forms of self control (temper, impulsivity, and risk seeking) and facility level movements
or STAR Reading Scores. Those results led to answering the second research question in
this study. Data analysis from those results supported one of the three hypotheses in that
section. Higher degrees of self control (as reported through low impulsivity scores) were
found in youth who successfully advanced in the level system at the Hawaii Youth
Correctional Facility (HYCF). As a next step, this chapter provides a discussion focused
on evaluating and interpreting the implications of the findings in Chapter 4.
The goals of this study were to contribute to the body of literature on incarcerated
youth and to provide greater clarity on the factors leading to self control for incarcerated
youth. Research indicates that students who are independent learners, and manifest self
control, have more success in academic learning (Sungur & Tekkaya, 2006). In addition,
students who initiate tasks and set goals while using appropriate strategies to achieve
their goals ultimately regulate their learning and perform at higher levels (Bandura, 1989;
Zimmerman, 1986). Research showed that individuals with low self control are not only

76

prone to be involved in criminal activity but are also prone to be unsuccessful in school,
at work, and in relationships (Gottfredson & Hirschi, 1990). In order to better serve
youth in correctional facilities, educators and researchers must understand the dynamics
of what may contribute to instances of low self control among youth within this
population. The researcher attempted to determine in this study how levels of self control
may contribute to success for youth within the facility. The methodology of quantitative
analysis was used to examine data to help the researcher answer the research questions
for this study. By identifying what factors add to low student levels of self control, as
reported by the youth in this study, the researcher hoped to contribute meaningful
findings to the purpose of constructing practical applications for remediation of youth for
educators both within incarcerated settings and within the community.
Despite the research presented in this study, little research exists to describe how
self-control influences youth who are incarcerated. Youth who are incarcerated have
little experience in regulating their behaviors and are often plagued with many other
challenges like being illiterate or marginally literate along with experiencing school
failure and retention (Quinn, Rutherford, Leone, Osher, & Poirier, 2005). The purpose of
this correlation quantitative study was to examine what factors contributed to youth self
control particularly for incarcerated youth and to determine if a relationship exists
between youth who possessed high self control and success outcomes such as increase in
program level movement and STAR reading scores.
This study describes the range of reported self control levels by incarcerated
youth along with records indicating current educational and performance data along with
previous data some of which leading up to incarceration. This study provides an

77

important role in terms of data from this somewhat uncharted population. What
characteristics contribute to self control for incarcerated youth? Is there a correlation
between youth self-control and outcomes within a youth correctional facility? These
questions were the driving force behind this study.
Discussion of Findings for Research Question 1

Research Question 1 compared the differences in the frequency of self control
across six variables via ANOVA tests. Results of the ANOVA tests were varied and
were shaped by the groupings in this study.
In examining the participant sample as a whole, scores on the Grasmick, et. al.
scale (scores from 0 to 4) presented one ironic finding. Despite all other variables, the
majority of youth in this study viewed themselves as having high self control in the area
of impulsivity (M= 2.74, SD= .07) as compared to any of the other subscale categories on
the scale. This was an interesting finding because descriptive data obtained through the
review of facility intake records indicated nearly 90% of the youth in the study were
found guilty of violent and/or property crimes. Based on the main tenet of Gottfredson
and Hirschi (1990) general theory of crime, self control is the main predictor of
delinquency relating to criminal behaviors. The interpretation of this finding may, some
ways, support work by Samenow (1984). According to Samenow, those who break laws
and consistently engage in criminal behaviors have a vastly different way of thinking.
Criminals, as Samenow refers, are mercurial. Their attitudes toward others and views on
situations depend on whether it serves them. Another interpretation may be that youth
who viewed themselves as having high self control in the area of impulsivity felt that
entering into HYCF (the period in which data and scale scores were obtained) required

78

that they adhere to certain conditions including compliance. With either interpretation,
further exploration on if this trend is consistent with other subjects and if this finding can
be replicated is needed.
A startling finding was revealed in the data relating to self control and age.
Despite the rejection of this hypothesis, overall t-test scores indicated that maturation was
not necessarily a factor contributing to the way participants viewed themselves in the area
of self control. This finding was fairly consistent in the t-tests conducted. What was
surprising was that this finding contradicts Piaget’s cognitive development theory (Piaget
& Cook, 1952). According to his theory, Piaget believed major brain changes take place
in children when they are 2 years old, again around 6 or 7, and then in puberty which may
extend in the early 20s. During each of these operational stages, new abilities should
arise lending to an increase in reflective and sophisticated thought (Ormrod, 2008).
Findings relating to age and its relationship to self control were more closely supported
by Gottfredson and Hirschi (1990). In their work, the researchers argue that age is not a
dominate predictor of crime since self control with age generally remains fixed over time.
Further research refuting or confirming this finding in this study is necessary as it will
have a direct impact on the current belief that as youth get older, they should make better
decisions and not repeat bad patterns of behavior.
An interesting finding was in the area of self control and ethnicity. Despite the
fact that the only ethnicity explored in t-tests was with those identified as being part-
Hawaiian and those who were not (due to small sample sizes), data was consistent in this
area particularly in the self control items relating to impulsivity. Part-Hawaiian youth
viewed themselves as having more self control in planning for the future and goal setting

79

as compared to youth who were not identified as being Hawaiian. Caution is given here
especially without further research to confirm this finding. Many programs for native
Hawaiian rely on empirical research to benefit this population and threats to the internal
validity of this finding should be tested.
Unexpected was the analysis relating to data in the category of special education
eligibility and self control. Research into the overrepresentation of special education
students in the juvenile justice system is not new or sparse. Of the 36% of special
education youth in this study, no statistically significant finding was uncovered in
relation to this population and any of the dimensions of self control. This finding may be
interpreted in one of two ways. One interpretation could be due to federal oversight of
the Hawaii Youth Correctional Facility (HYCF) beginning in 2006 and the impact it has
had on insuring that all youth with disabilities receive educational and mental health
services in accordance with federal Individuals with Disabilities Education Act (IDEA)
laws. In 2005, the Department of Justice (DOJ) responded to complaints stemming from
accusations of abuses of youth at HYCF by staff members. A Memorandum of
Agreement (MOA) between HYCF, the Department of Education (DOE), and the
Department of Health (DOH) consisted of provisions to address alarming issues
regarding the safety and security of youth while at HYCF. A national expert in the field
of special education was assigned to oversee provisions in the MOA specifically dealing
provisions relating to education and since then, all provisions relating to education have
met substantial compliance. A second interpretation contributing to the rejection of this
hypothesis could be due to the fact that out of the 34% if special education youth in the
study, only two students were eligible under the category of Other Health Impairment

80

(OHI). Under OHI, a qualifying criteria is those diagnosed with attention deficit
hyperactivity disorder also known as ADHD.
Affirming the significance of family, particularly the importance of a maternal
figure, was the data resulting supporting hypothesis four. Similar to the findings on
ethnicity, youth who identified having a mother as their most significant other, viewed
themselves as being less impulsive than their counterparts (t (36)= -2.06, p<.05).
Although this supports work by Werner and Smith, (1992) and Silverman and Ragusa
(1992), further research is warranted to determine the impact on the self control for
incarcerated youth who have fathers as the most significant person in their life.
A salient finding from this study was the lack of predictive power in identifying
youth who had low levels of self control prior to incarceration. Youth who were non-
violent offenders viewed themselves as having less self control than the violent offenders
in this study. Research on the trajectory of youth participation in criminal behaviors
revealed that early participation and adjudication led to an increase (within 42 months of
initial incident) of more violent offenses (Dembo, Ramirez-Garnica, Rollie, &
Schmeidler, 2000). Although this trajectory may predict the outcome of non-violent
offenders, it does not provide insight as to why the violent offenders in this study viewed
themselves as having more self control than their counterparts. Another interpretation
follows the model that youth who engage in criminal behaviors often view themselves as
victims which thereby leads to negative emotions forcing the youth to justify their
behavior as a effect of provocation (Daley & Onwuegbuzie, 2004). In addition, the more
negative encounters these youth experience, the more likely they are to believe they are
victims, and the more likely they are to justify more violent behaviors (Daley &

81

Onwuegbuzie, 2004). Further investigation is needed in this area so that detection and
intervention is may help deter youth from engaging in more violent offenses.
Unsurprising were the findings comparing number of previous high risk
encounters with self control. Youth who experienced more than three high risk
encounters (psychiatric intervention, sex abuse, drug abuse, physical abuse, gang
involvement and or pregnancy) viewed themselves as having much less self control than
their peers.
Discussion of Findings for Research Question 2
Surprisingly, the quantitative data collected for this study provided little insight
into the relationships between self control and facility success outcomes which determine
youth transition into the community.
The quantitative analysis using Spearman Rho correlations offered only a weak
correlation between impulsivity and facility level movement. Realizing that a number of
other factors can influence facility level movement by youth, this finding by itself was
not too surprising. However, the most significant finding of the correlational analysis
was the lack of statistical significance between high self control (an assumed attribute
leading to success) and high STAR reading scores. In order for students to master the
knowledge and skills that make high performance levels possible, students must have self
control (Zimmerman & Pons, 1986). But upon further examination of data showing
STAR reading scores, of the 12% of youth who had above average reading scores (10.0
Grade Equivalency through Post-High Equivalency), only one youth had overall mean
scores in temper and impulsivity that fell into the high self-control range. Evidently, high
literacy skills in reading are not purely dependent on self-control. But the crucial

82

question of how self control may impact other success outcomes at HYCF requires
further exploration.
Correlation of youth self control responses and correctional facility success
outcomes addressing research question two presented minimal findings. The indicators
of increase in facility level movement and grade level STAR Reading scores were
compared with the variables of temper, impulsivity, and risk-seeking scores. The only
statistically significant result in the Spearman Rank Order correlation tests was between
facility level movement increase and impulsivity. Not surprising was the finding that
youth who met facility level increase requirements also reported high levels of self
control in the area of impulsivity.
Finally, because facility level movement program was one of the main outcomes
measuring success of youth in this study. Further examination and possible refinement of
what constitutes an increase in level movement may be beneficial. Youth in the study
who successfully achieved level increases still reported low levels of self control that led
the researcher to believe that any changes in behavior for these youth were only
temporary and superficial. Programming within the correctional facility to address
problem solving methods aimed at increasing youth levels of self control may be
beneficial.

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Recommendations for Practice
The importance of early detection of offender characteristics, such as the lack of
self control, cannot be underestimated in order to move beyond the focus of crime
causation. If the mission in juvenile justice is to provide effective forms of correction,
then empirical research identifying how youth in this population think and how they
process information is necessary in order to reduce the overrepresentation of youth in
correctional facilities.
The process of this dissertation has revealed that although Hawaii is a unique
state, isolated from the rest of the country, this geographic restriction is not evident in the
research relating to characteristics of youth particularly those incarcerated.
Disproportionate minority commitments can commonly be found in youth facilities is and
it crosses over state lines. More is needed to learn how these systems have responded to
the needs of incarcerated youth. By creating a system of collecting and analyzing
aggregate data, early interventions targeting youth in this novel group can be
implemented.
In terms of training, data in this study supports the notion of expanding the
function of the multidisciplinary teams at the Hawaii Youth Correctional Facility
(HYCF) to create internal collaborative teams focused on sharing and discussion new
trends in positive behavior reinforcement. Furthermore, members in these teams could
share their expertise and build more mentoring opportunities for the youth within
HYCF.

84

In concluding the analysis of this study, it is important to mention that there may
be noteworthy considerations for future directions or research on predicting youth with
low levels of self control particularly for youth who are incarcerated. Bandura’s social
cognitive theory (1989) stresses the important relationship between environment, person,
and behavior and how that relationship is necessary not just for learning but for self
regulation. However, youth who are incarcerated lack opportunities to practice
appropriate socialization skill that are crucial to being a contributing member of society.
Limitations of the Study
Replication. The high transient rate among incarcerated population can be a
challenge in itself. The collection of data from this unique population is magnified
because of policies to ensure confidentiality. Although recurrent tests on theories are
expected, these tests can rarely be replicated with the same measures and variables.
Therefore, the reliability and validity of these tests should be open to skepticism
particularly with regards to the self assessments of incarcerated youth populations.
Methods. Although a major strength of this quantitative study was the access the
researcher had to historical youth records, as well as thorough completion of self control
survey data, more contextual information is needed from this population to better
understand the results of all the data collected. Interviews with the youth would have
provided more insight into possible relationships between their lack of self control and
conditions that led these youth to becoming marginalized.
The analysis and research findings in this study were obtained via t-tests and
Spearman’s Rank-Order Correlation tests, which only revealed connections and
associations, hence no information about why the connections happened, were available.

85

The researcher would have been able to provide more insights if observations of youth
behaviors were conducted.
Gender Equity. Few females were represented in this study and research in the
area of gender by Gottfredson and Hirschi (1990) describe the disparity connected with
socialization for children by gender and the consequential degrees of self control that is
established. The small representation of females resulted in the omission of gender as a
variable to be explored in this study. In addition, less youth of non-ethnic minority were
represented in this study and may warrant further comparative research particularly
among females.
Setting. This study focused on the population of one setting and therefore, the
findings should not be generalized to all state-run facilities. A state with more facilities
and more resources may have provided more implications from the findings.
Furthermore qualitative data such as interviews from correctional officers who spend the
most time with this population of study would have provided more information on
possible root-causes for those youth with low self control.

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Directions for Future Research
Ironically, a common response to youth who violate rules (often those with low self
control) include less social interactions, fewer opportunities to participate in activities,
and less access to vocational training. Therefore, future research on positive behavior
supports particularly focused on practicing appropriate social skills at an early age is
crucial. Based on the Department of Justice (DOJ) oversight starting in 2006, youth at
the Hawaii Correctional Facility (HYCF) have been experiencing the effects of a shift in
philosophy of being more restrictive to one of understanding the needs and related
experiences of youth have encountered academic and social failure.
Future studies may expound on this study by investigating: (1) The role of a
significant other such as a father figure in developing short term and long term goal
setting to increase youth self control, (2) The implication of special education eligibility
particularly through Individualized Education Program objectives developed to enhance
youth self control particularly in incarcerated settings, (3) Longitudinal studies on the
impact of infractions leading to incarceration and the effect of high risk encounters on
self control for incarcerated youth, and (4) Longitudinal designs and interventions based
on these findings with a pre-test and post-test of STAR reading score progress and
correlation to youth self control within incarcerated settings.

87

Sadly, many indications predicting potential involvement in crime are evident in
schools across the country today. Youth who struggle both socially and academically are
known to be at greater risk for crime as their successful counterparts (Foley, 2001).
Youth who drop out of school have a higher propensity to engage in criminal activities
(Hawkins, 1982). Youth who lack parental involvement are more likely to become
involved in the juvenile justice system (Warner & Smith, 1992). The question now is,
―So what do we do with this knowledge?”

88

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Appendix A:
Consent to Release of Information

97

Appendix B:
IRB Approval Letter

98

Appendix C:
Mean, Standard Deviation, & T-Test Scores for Part Hawaiian
& Non Hawaiian Groups

Note: *Statistically significant at the p<.05 level

99

Appendix D:
Mean, Standard Deviation, & T-Test for SPED and Non-SPED Groups

Note: *Statistically significant at the p<.05 level

100

Appendix E:
Mean, Standard Deviation, & T-Test for Mother and Other Groups

Note: *Statistically significant at the p<.05 level

101

Appendix F:
Mean, Standard Deviation, & T-Test for Violent and Non-Violent Offender
Groups

Note: *Statistically significant at the p<.05 level

Abstract (if available)

Abstract This study was conducted to examine characteristics contributing to high self control for incarcerated youth. Subjects include fifty youth (8 females and 42 males) ages 14 through 18 incarcerated for at least 60 days. Data on subjects’ responses from a validated measure (Grasmick et. al. Scale, 1993) and data from historical records, STAR reading and facility level movement at the Hawaii Youth Correctional Facility (HYCF), were closely analyzed to provide accurate findings. The researcher used descriptive, correlational, and secondary data analysis to conduct this non-experimental quantitative study.

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Creator Winquist, Trancita (author)

Core Title Factors contributing to self control for incarcerated youth

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/24/2010

Defense Date 03/04/2010

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Grasmick scale,Hawaii Youth Correctional Facility,HYCF,incarcerated youth,infractions leading to incarceration,juvenile corrections,juvenile justice,Native Hawaiian,OAI-PMH Harvest,self control characteristics,self perception,significant other,Special Education,STAR reading

Place Name Hawaii (states)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Brewer, Dominic J. (committee chair), Sundt, Melora A. (committee member), Wolcott, Louise (committee member)

Creator Email tinawinquist@yahoo.com,winquist@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3215

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