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This is to certify that the

dissertation entitled

THR RELATIONSHIP BETWEEN LEISURE LIFESTYLE AND RISK: NATIVE

AMERICAN YOUTH AND ALTERNATIVE SCHOOL STUDENTS

presented by

Stephen R. Yanni

has been accepted towards fulﬁllment
of the requirements for

Ph. D- degreein Park. Recreation and
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THE RELATIONSHIP BETWEEN LEISURE LIFESTYLE AND RISK: NATIVE

AMERICAN YOUTH AND ALTERNATIVE SCHOOL STUDENTS

By

Stephen R. Yanni

A DISSERTATION
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Department of Park, Recreation, and Tourism Resources

2001

ABSTRACT
THE RELATIONSHIP BETWEEN LEISURE LIFESTYLE AND RISK: NATIVE
AMERICAN YOUTH AND ALTERNATIVE SCHOOL STUDENTS
By

Stephen R. Yanni

If recreation practitioners are to provide effective youth risk prevention
programs and obtain the necessary resources for such programs, the
relationship between leisure lifestyle and the behaviors and Choices associated
with risk must be fully understood. This study was designed to: 1) examine
leisure lifestyle (leisure boredom and leisure participation patterns) and risk, and
2) to explore the relationship between leisure lifestyle and risk among Native
American youth attending regular schools and white and Native American
students in alternative school students. I

The subjects for this study were 63 youth from the Bay Mills Indian
community located in upper Michigan attending regular schools and 38 students
attending the Sault Ste. Marie, Michigan Alternative Education Center. Data were
collected in May and June 2000 in a group interview format. Instruments used
were the Adolescent Leisure Time Activity Scale (ALTAS), the Leisure Boredom
Scale, an Indicator of Risk Scale, and a demographic questionnaire.

The key ﬁndings of this study were: 1) Native American youth from Bay
Mills had signiﬁcantly higher rates of participation in organized leisure activities,

organized sport activities, activities at home, and self-directed leisure activities

while the alternative school students had signiﬁcantly higher total risk and leisure
boredom scores; 2) leisure variables explained 23.8% of the variance in total risk
for the entire sample; 3) increased unsupervised socialization with friends,
decreased organized leisure activity, decreased activities at home, and increased
leisure boredom were found to contribute signiﬁcantly to increased total risk for
the whole sample; and 4) leisure variables predicted group membership as either
youth from Bay Mills or students from the alternative school with accuracy rates

of 82.5% and 84.2% respectively.

ACKNOWLEDGEMENTS

WIthout the encouragement, guidance, and understanding of members of
my family this project would never have been considered, let alone completed.

To my wife Hedy, and my Children Brandon, Caleb, and Rachel; were it
not for the belief that all of the time spent away from you working on this project
would ultimately beneﬁt all of “us” I would not have found the motivation and
discipline to carry on thank you.

My mother and father provided a foundation from my earliest days which
was built on love, hard work, wisdom, and selﬂessness, these same building
blocks were also provided to my wife, and later to myself by my wife’s parents.
To both sets of parents thank you.

To my brothers and sisters by blood and by marriage who quietly provided
encouragement and assistance to my wife and myself thank you.

To Gary Deuman, his staff, and students at the Sault Ste. Marie
Alternative Education Center; I thoroughly enjoyed the time I spent working with
you. Thank you for welcoming me into your world during my data collection.

WIthout the support of the Bay Mills Indian Community this project would
have been doomed. To the members of the Executive Council and the young
people who participated in the data collection, I say Chi Migwetch.

To my colleagues at the Bay Mills Indian Community and Lake Superior
State University who assisted with the collection of data, and playfully but

effectively pushed me to completion of this project thank you. In particular I

would like to thank Dr. R. Lee Gardiner, you picked me up by the bootstraps
many times when l was ready to throw in the towel; without your expertise, and
kind friendship this project would not have been completed thank you.

To Dr. Charles Nelson, my major advisor at Michigan State University,
thank you for your brilliance, patience, and friendship. My journey to completion
of this project was a complex and unique one; with every twist in the path you
urged me forward and displayed an unwavering conﬁdence in my abilities.

To Dr. Joe Fridgen, Dr. Don Holecek, and Dr. George Cornell who
provided time and guidance as members of my dissertation committee, your
assistance was greatly needed and appreciated.

To God the Father who gave me the Skills, support, and opportunities to

be involved in a project such as this thank you.

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION ............................................................................ 1
STATEMENT OF THE PROBLEM .............................................................................. 3
PURPOSE OF THE STUDY ...................................................................................... 4
NEED FOR THE STUDY .......................................................................................... 5
DELIMITATIONS .................................................................................................... 5
LIMITATIONS ........................................................................................................ 6
DEFINITION OF TERMS .......................................................................................... 7
HYPOTHESES ...................................................................................................... 8

CHAPTER TWO: LITERATURE REVIEW ......................................................... 12
LEISURE LIFESTYLE ............................................................................................ 12
ADOLESCENT LEISURE LIFESTYLE AND INDICATORS OF RISK ................................. 14
YOUTH AND RISK BEHAVIORS .............................................................................. 34
LEISURE LIFESTYLE AND NATIVE AMERICANS ....................................................... 38
LITERATURE REVIEW SUMMARY .......................................................................... 42

CHAPTER THREE: METHODOLOGY ............................................................... 45
SUBJECTS ......................................................................................................... 45
INSTRUMENTS .................................................................................................... 50
ARRANGEMENTS FOR DATA COLLECTION ............................................................. 52
DATA COLLECTION TECHNIQUES ......................................................................... 55
ANALYSIS OF DATA ............................................................................................ 59
MULTIVARIATE AND UNIVARIATE ANALYSES RESULTS ............................................ 73
REGRESSION ANALYSES RESULTS ...................................................................... 77

CHAPTER 5: DISCUSSION ............................................................................... 84
SUMMARY OF KEY FINDINGS ............................................................................... 84
EXPLANATION FOR FINDINGS AND INTEGRATION WITH PAST LITERATURE ................ 85
IMPLICATIONS AND RECOMMENDATIONS ............................................................... 91

APPENDIX A ...................................................................................................... 96
ADOLESCENT LEISURE TIME ACTIVITY SCALE (ALTAS) ........................................ 96

APPENDIX B .................................................................................................... 101
LEISURE BOREDOM SCALE ......................................................................................... 101

APPENDIX C .................................................................................................... 109
INDICATORS OF RISK SCALE .............................................................................. 109

APPENDIX D .................................................................................................... 112
DEMOGRAPHIC QUESTIONNAIRE ........................................................................ 112

APPENDIX E .................................................................................................... 114

vi

PARENT/GUARDIAN INFORMED CONSENT FORM ................................................. 114

APPENDIX F ..................................................................................................... 117
SUBJECT INFORMED CONSENT FORM ................................................................ 117
APPENDIX G .................................................................................................... 120
REQUEST TO BAY MILLS INDIAN COMMUNITY EXECUTIVE COUNCIL ...................... 120
APPENDIX H .................................................................................................... 122
TRIBAL COUNCIL APPROVAL OF RESEARCH ........................................................ 122
APPENDIX I ...................................................................................................... 124
BAY MILLS POTENTIAL SUBJECT MAILING COVER LETTER ................................... 124
APPENDIX J ..................................................................................................... 127
ALTAS SCORE FORM ...................................................................................... 127
APPENDIX K .................................................................................................... 129
LEISURE BOREDOM SCALE SCORE FORM ........................................................... 129
APPENDIX L ..................................................................................................... 131
RISK BEHAVIOR SCALE SCORE FORM ................................................................ 131
TOTAL: ............................................................................................. 132
BIBLIOGRAPHY ............................................................................................... 133

vii

Chapter 1: Introduction

One of the greatest Challenges of our time is to understand the factors
involved in inﬂuencing the lifestyles of our youth. Some young people live
according to the rules; they are successful in school, they abide by the laws of
the land, they are able to stay Clear Of drugs and alcohol, their personal Choices
promote health rather than disease, and Ultimately they become successful,
productive members of society. Conversely we have “youth-at-risk” whose lives
may take a decidedly different route. This route is characterized by conﬂict,
rebellion, violence, substance abuse, academic failure, sexual promiscuity, and
other behaviors which tend to reduce their chances of becoming successful,
productive members of society.

Many factors have been linked to the development of at-risk youth. These
include economic status, family Characteristics, gang affiliations, racial and
cultural afﬁliations, religious afﬁliations, extracurricular pursuits, birth order,
gender, personality, leisure lifestyle, and various pathological conditions have all
been examined for their contributions to the development of risk amongst youth.
This study looked at leisure lifestyle as a potential factor in shaping the lives of
young people.

Many in the recreation profession have made the argument that it is far
less expensive to facilitate positive leisure lifestyles amongst youth than it is to
rehabilitate them after they have been transformed to youth-in—trouble. “For as

long as recreation has been institutionalized as a public service, it has been

argued by the ﬁeld’s evangelists that it can be an effective tool for alleviating
delinquency and crime” (Crompton, 1993, p. 4).

Leisure time pursuits of young people are an important factor in
determining the type of lifestyle an individual will pursue. For better or worse,
“leisure can contribute in a positive way to maintenance of a healthy, vigorous
lifestyle; on the other hand, it can detract from one’s well-being in a signiﬁcant
manner” (Edginton, Jordan, DeGraff & Edginton, 1998, p. 13).

Evidence of the beneﬁts of investments in leisure-based prevention
programs for youth is growing. Schultz et. al. (1995) point out, if an at-risk youth
prevention program prevents only one in every 178 individuals from detention in
a state-run facility, the prevention program will be cost effective. While such
analysis is encouraging, those who seek resources for youth prevention
programs ﬁnd that recreation programs often are not an allowable expenditure
from many potential funding sources, such as state-level substance abuse
prevention programs. Many of these prevention funding sources target youth at
high risk, such as Native American youth and Alternative School students.

Concerning risk and minorities, the leisure-related literature does provide
some information regarding the relationship between delinquency and risk
amongst Mexican American, African American, and white youth; however, there
is a void in the literature concerning leisure lifestyle and delinquency or risk

amongst Native American youth.

This investigation is designed to assess leisure lifestyle and at-risk
behaviors of Native American youth and alternative school students, and then to

examine the relationship between risk and leisure lifestyle.

Statement of the Problem

Many communities, including those that are predominantly Native
American, turn to leisure service professionals for help in preventing at-risk
lifestyles among their younger members. However, these practitioners are
currently without the beneﬁt of a signiﬁcant body of research concerning the
relationship between leisure lifestyle and at-risk behaviors for Native American
youth.

The lack of literature concerning Native Americans and leisure is partly
due to the demographic realities. In Michigan, Native Americans comprise
roughly 0.6% of the state’s total population. There are portions of the state
however, with a signiﬁcantly higher proportion of Native Americans. In Chippewa
County, in Michigan’s Eastern Upper Peninsula, Native Americans are 11.0% of
the county’s population. (Hembroff, Cornell, & Hamlin, 1999)

There is a Signiﬁcant body of literature that examines the beneﬁts of
leisure, and the leisure lifestyles of white, African-American, and Mexican-
American adolescents, but there is an obvious gap in the literature speciﬁc to
Native Americans. There is also a gap in the delinquency research, which has
ignored leisure activity as a contributing factor (Agnew and Petersen, 1989). The

review of literature found in Chapter two of this study will suggest that Native

American youth as a group are more likely to be Classiﬁed as at-risk than their
non-Native counterparts; a reality that further highlights the need to understand
factors related to risk, including leisure lifestyle.

This study was designed to: 1) examine leisure lifestyle (leisure boredom
' and leisure participation patterns) and risk, and to explore the relationship
between leisure lifestyle and risk among Native American youth attending regular
schools and alternative school students; and 2) examine data from instruments

used for potential predictive abilities and relationships.

Purpose of the Study

If recreation practitioners are to provide truly effective youth prevention
programs, and obtain the necessary resources for such programs, the
relationship between leisure lifestyle, behaviors, and Choices associated with risk
must be fully understood. Furthermore, it is necessary to understand if youth
from differing cultural and racial groups show similar relationships between
leisure lifestyle and indicators of risk. This avoids the potentially false assumption
that all youth are impacted equally by similar prevention programs which focus
on leisure. It is also important to obtain current knowledge of leisure practices
amongst our youth, and to determine if those practices are consistent across risk

indicators, and racial/cultural boundaries.

Need for the Study

Leisure service providers who work with Native American youth and
at-risk youth must be better equipped to offer services which are likely to be
effective in preventing at-risk lifestyles. Currently little is known of the
relationship between leisure behaviors of Native American youth and at-risk
behaviors. Additionally, if strong relationships between leisure lifestyle and
indicators of risk are found, it may become important to explore the predictive

value of leisure lifestyle assessments.

Delimitations

This study was delimited to:

1. Currently enrolled (second semester 2000) students in the Sault Ste.
Marie, Michigan Area Alternative Education Center and registered
members of the Bay Mills Indian Community between the ages of
twelve and nineteen years living in Chippewa County.

2. Leisure lifestyle was assessed using the Adolescent Leisure Time
Activity Scale (ALTAS) (Yin, Katims, and Zapata, 1999) and the
Leisure Boredom Scale (lso-Ahola & Weissinger, 1990)

3. Indicators of risk were assessed from student responses to questions
pertaining to delinquent acts derived from Yin et al. (1999)

4. Demographic variables were assessed using student responses to
researcher developed items concerning gender, grade in school, age,

and race (Native American or non-Native American)

5. The data were collected between in May and June 2000.

6. The data were analyzed using SYSTAT 5.04.

Limitations

Limitations inﬂuencing the results of this study were:

1. The Native American youth who participated in this study were
overwhelmingly members of one tribe, the Bay Mills Indian Community.
Standards for membership in tribal communities vary, thus leading to
concerns regarding the ability of the Native American subjects in this
study to represent all Native American students.

2. Some of the Native American students in this study may be more
integrated into the dominant society than tribal members of more rural
or western tribal communities. This may also limit the generalizability of
the results of this study.

3. The ﬁnancial success of native enterprises of the Sault Ste. Marie
Tribe of Chippewa Indians and the Bay Mills Indian Community has led
to the development of extensive recreational facilities and programs for
tribal youth. This may limit the generalizability of the results of this
study to all tribal youth.

4. Non-response bias speciﬁc to the variables related to risk and leisure
lifestyle was not measured; this may limit the generalizability of the

results of this study.

Deﬁnition of Terms

For consistency of interpretation the following terms are deﬁned:

Risk:

Leisure Boredom:

Leisure:

For the purposes of this research project, risk will be
represented by the following indicators: belonging to a gang,
carrying a weapon, criminal activity, participation in tagging
(gang logos being painted in public places),

staying out late without parental permission, abusive
language directed to teachers or parents, substance use,
poor academic performance, and poor self-reported health

and physical ﬁtness (Yin, Katims, and Zapata, 1999)

The subjective perception that available leisure experiences
are not sufﬁcient to instrumentally satisfy needs for optimal
arousal. Perceptions of leisure as boredom are associated
with negative affect and can be manifested as beliefs that
available leisure resources are not sufﬁciently frequent,
involving, exciting, varied or novel. (Iso-Ahola and Crowley,

1991,p.262)

Discretionary time.

Leisure Lifestyle: A combination of self-reported level of leisure boredom, and

current free-time activity participation.

Native American: A member in full standing of a federally recognized tribe.

Youth: For the purposes of this research project, youth are to be
deﬁned as those between twelve and nineteen years of age

at the time of data collection.

Hypotheses

The literature review completed for this study and the personal
experiences of the author as a director of recreation and health promotion for a
Native American community have led to the development of the hypotheses
presented below.

Hypotheses are offered for leisure lifestyle and risk data comparing the
groups of Bay Mills youth (all attending regular schools) and alternative school

students.

1. Subjects who were students in the alternative school will have higher total
risk scores than youth from Bay Mills who were students in regular
schools. The above hypothesis is based on the risk behavior data from the
1998 Centers for Disease Control (CDC) Alternative School Risk Behavior
Survey and the information provided by Gary Deuman, director Of the

Sault Ste. Marie Alternative Education Center. Both of these sources

indicated that students in alternative education programs are involved in
risk behavior at higher rates than students in regular schools.

Alternative school students will have higher scores for participation in
unsupervised socialization with friends than Bay Mills youth whom were
students in regular school. Yin, Katims, and Zapata (1996) found that
increased socialization with friends led to increased illegal substance use,
and Agnew and Petersen (1989) found that leisure activities with peers
had a positive relationship with both total and serious delinquency. Since it
is expected that the alternative school students will have higher rates of
total risk, it is expected based upon the above two sources that alternative
school students will also have higher rates of involvement in unsupervised
socialization with friends.

Bay Mills youth will have higher scores for: 1) organized Sports activities,
2) organized leisure activities, 3) activities at home, and 4) self-directed
leisure activities than alternative school students. Since only one of the
ﬁve typologies of leisure (unsupervised socialization with friends) has
been associated with higher rates of risk behaviors (Yin et. al, 1996), and
Bay Mills youth are expected to have lower risk scores than the alternative
school students; it is therefore expected that Bay Mills youth will have
higher rates of participation in the other four typologies of leisure activities.
It is expected that alternative school students will have higher total risk
scores (as was supported above), and Caldwell (1995) found that

increased boredom leads to increased delinquency. Therefore, it is

hypothesized that alternative school students will have higher leisure
boredom scores than youth from Bay Mills who were students in regular
schools.

Agnew and Petersen (1989) found that leisure variables explained six
percent of the variance in total and minor delinquency and four percent of
the variance in serious delinquency. It is expected that leisure lifestyle in
the current study will explain at least six percent of the variance in total
risk scores for all subjects.

Based on the results of Yin et. al, (1999) and Caldwell (1995) it is
expected that for Bay Mills youth unsupervised socialization with friends,
organized leisure activities, organized sport activities, activities at home
and leisure boredom will all contribute signiﬁcantly to a prediction of total
risk.

Based on the results of Yin et. al, (1999) and Caldwell (1995) it is
expected that for Bay Mills youth participation in self-directed leisure
activities will not be a signiﬁcant variable in the prediction of total risk.
Based on the results of Yin et. al, (1999) and Caldwell (1995) it is
expected that for alternative school students unsupervised socialization
with friends, leisure boredom, organized leisure activities, organized sport
activities, and activities at home will all contribute Signiﬁcantly to a
prediction of total risk.

Based on the results of Yin et. al, (1999) and Caldwell (1995) it is

expected that for alternative school students participation in self-directed

1O

10.

leisure activities will not be a signiﬁcant variable in the prediction of total
risk.

It is hypothesized that accuracy of predicting group membership as either
Bay Mills youth or alternative school student based on leisure lifestyle will
be greater than Chance.

Although it will be shown in the literature review that Native
American youth and alternative school students are at greater risk than
youth in general in the United States; it is the author’s belief that the
alternative school students in the current study will Show greater levels of
at-risk behaviors than the youth from Bay Mills (see hypothesis two).

If the alternative school students and the youth from Bay Mills do
differ on levels of at-risk behaviors, it is expected that Since leisure may be
a signiﬁcant factor in understanding delinquency (Agnew and Petersen,
1989), predicting group membership based on leisure variables should be
successful.

This hypothesis is also based on information concerning the leisure
habits of the alternative school students provided to the author by Gary
Deuman, director of the Sault Ste. Marie Alternative Education Center. (G.

Deuman, personal communication, May, 2000)

11

Chapter Two : Literature Review

This study was designed to: 1) examine leisure lifestyle (leisure boredom
and leisure participation patterns) and risk, and to explore the relationship
between leisure lifestyle and risk among Native American youth attending regular
schools and alternative school students; and 2) examine data from instruments
used for potential predictive abilities and relationships.

The literature related to 1) leisure lifestyle, 2) adolescent leisure lifestyle
and indicators of risk, 3) Native Americans and risk, and 4) leisure and Native

Americans will be reviewed in this Chapter.

Leisure Lifestyle

As the elements of leisure lifestyle are explored, the term leisure must ﬁrst
be examined. The term leisure has commanded a signiﬁcant amount of attention
over the centuries, as philosophers, social scientists, religious theorists, and
leisure professionals have attempted to create the universally applicable
deﬁnition of this term. As a result many theories of leisure have been discussed,
including leisure as activity, leisure as a state of mind, leisure as a symbol of
social status, the anti-utilitarian view of leisure, and leisure as a holistic concept
(Edginton, et. al., 1998). The most widely accepted view of leisure in today's
society is that leisure is some form of free time, time to do as you please
(Bammel and Bammel, 1992). Shivers and DeLiSle (1997) support the notion of

leisure as free time, “the concept of leisure as time free of obligations is the most

12

effective and meaningful deﬁnition yet proposed. Instead of encrusting leisure
with restrictive consequences and hedging it with certain values, activities, or
partial time references, the free-time deﬁnition is theoretically sound and
unambiguous” (p. 93).

Deﬁning leisure as free time provides a simple, tidy understanding of the
term leisure in isolation, but falls short in developing a thorough understanding of
the leisure experience or leisure lifestyle. It is in exploring the lifestyles and
experiences associated with leisure that the practitioner would beneﬁt the most.

The state of mind view of leisure lends itself most readily to an
understanding and measurement of leisure experience or lifestyle, “under the
state of mind view, we would be more concerned with creating environments and
utilizing leadership strategies that will maximize feelings and perceptions that
have been denoted as typifying leisure” (WM and Ellis, 1989. P. 3).

Central to the state of mind view Of the leisure experience are the
concepts of competence, control, intrinsic motivation and freedom (WM and Ellis,
1989). Edginton et. al. (1998) support this notion by offering the following four
similar central factors: freedom, perceived competence, intrinsic motivation, and
positive affect.

Peterson and Stumbo (2000) assist in developing an understanding of the
concept of leisure experience or lifestyle, “leisure lifestyle is the day-to-day
behavioral expression of one’s leisure-related attitudes, awareness, and activities

revealed within the context and composite of the total life experience” (p. 7).

13

The issue of boredom related to leisure or free time is often studied (lso-
Ahola and Crowley, 1991; lso-Ahola and Weissinger, 1987; Shaw, Kleiber, and
Caldwell 1996; Caldwell 1995) as an important factor in understanding leisure
lifestyle. Boredom is reported to be a factor in determining participation patterns
as well as how leisure lifestyle plays a role in other important life Choices and
behaviors.

In summary, in order to understand leisure as an isolated term, one must
consider the notion of leisure as free time; but, in order to develop a more
thorough awareness of leisure as it relates to the life experience, one must look
at, freedom, motivation, constraints, attitudes, boredom, competence, control,

and activity choices as they relate to free time.

Adolescent Leisure Lifestyle and Indicators of Risk

This section of chapter two reviews literature examining the relationship
between leisure lifestyle and various indicators of risk amongst adolescents.
Leisure lifestyle is measured primarily by looking at current participation patterns
and leisure boredom.

Yin, Katims, and Zapata (1996) surveyed 1190 sixth and seventh grade
Mexican-American students from four middle schools in a South Texas
metropolitan area for the purposes of: 1) investigating the typology of after-
school-activities engaged in by a group of economically deprived and
academically at-risk Mexican-American middle school students, 2) examining the

relationship between the types of after-school activities and substance use, and

14

3) identifying factors that may act as mediators in the relationship between after-
SChool activities and the use of alcohol and marijuana. Of the 1190 students
surveyed in this study 573 were male and 617 female. Researcher-developed
surveys were administered by trained undergraduate students in the classrooms
of the subjects; these surveys gathered information concerning use of alcohol
and drugs in the last thirty days, availability of alcohol and marijuana, friend’s use
of substances, and an after-school activity survey. The after-school activity
survey asked students to indicate which of the eleven activities listed they
participated in most often, second most often, and third most often; only the
activities participated in “most Often” were used in the analysis.
Following a method used by others (Agnew and Petersen, 1994) this
study summarized after-school, or leisure activities by placing each activity in a
category of activities. Three categories of activities were deﬁned:
Type I: peer socialization activities that provide youth opportunities to
interact freely without supervision,
Type II: organized activities that are structured to provide recreation and
Challenge to participants usually under adult supervision, and
Type I ll: activities that youth engage in at home under the direct or indirect
supervision of adults, with limited opportunities to interact with
peers. (Yin, et. al., 1996, p. 49)
VVIII'I respect to use of alcohol and marijuana, the subjects of this study
reported higher use than national averages. Participation in after-school activity

tYPOlogies found type I (socializing in unsupervised settings) to be the most

15

frequently reported (41.2%), followed by type II (home-based activities) at 40%,
and type III (organized activities) being the least often reported at 18.1%. Male
verses female participation differences showed that males were more likely to
socialize with friends in unsupervised settings and organized activities, while
females were more likely to participate in home-based activities. Analysis
indicated that substance use increased as socialization with peers in
unsupervised settings (type I) increased as compared to the other two typologies;
this trend was consistent across the genders. This study used only three
typologies to summarize after-school activities; this may not be enough
categories to examine the wider issue of leisure activities rather than after-school
activities.

Yin, Katims, and Zapata (1999) completed another study focusing on
leisure and delinquency that provided much of the framework for the current
study. There were three purposes identiﬁed for this study:

1. To develop a typology of leisure time activities using the Adolescent
Leisure Time Activity Scale (ALTAS) developed by the authors for the
study;

2. To explore the relationship of this leisure typology and delinquency
among Mexican American adolescents; and

3. To explore the effect of gender on participation in leisure activities and
its mediating role on the relationship between leisure activity and

delinquency. (Yin et. al., 1999, p. 172)

16

The subjects for this study included 2651 Mexican American students from
a school district in south, central Texas; males represented 51% of the subjects.
The mean age of the subjects was 14.6, with 36.9% from grade eight, 36.1%
from grade nine, and 26.9% from grade ten. The three instruments used included
the ALTAS, a self-report delinquency scale, and a questionnaire seeking
demographic information. The ALTAS was developed by the authors based upon
leisure activity scales developed by Agnew and Petersen (1989), Kelly (1996),
Yu (1980), and Yin et al. ( 1996). The development and subsequent evaluation of
the ALTAS as a means of assessing leisure time activities was one of the
objectives of this research.

The ALTAS included 24 leisure activities. In it subjects were asked to
indicate their participation in the 24 activities after school or on weekends and to
respond whether participation was usually, sometimes, or never. The 24 leisure
activities were associated with one of ﬁve typologies of leisure: 1) unsupervised

socialization with friends, 2) organized leisure activities, 3) organized sport
activities, 4) activities at home, and 5) self-directed leisure activities.

The delinquency scale developed for the study asked students to respond

“yes” or “no” to questions pertaining to nine delinquent acts in which they had
engaged during the past year. The nine delinquent acts included: 1) belonging to
a gang, 2) carrying a weapon (knife/gun) to school, 3) Charged with a crime/went
to court for a felony Charge, 4) did “tagging” (tagging is marking territory with a
9309’s or group’s colors/logo), 5) stayed out late without permission/left home

without parents knowing, 6) cussed out loud at a teacher/used bad language to

17

parents, 7) smoked marijuana at least once in last 30 days, 8) was drunk (had 5
or more drinks on one occasion) at least once in last two weeks, and 9) averaged
“D” or less at school in last year.

Data were collected in the classrooms of the subjects during the Spring of
1995, with a response rate of 89%. To control for standardized administration
and readability, university students were trained to administer the survey and
they read the survey to the students in English. Subjects were instructed to follow
along with the research assistant who read the questions and the multiple Choice
response Options out loud. School personnel were asked to leave the classrooms
during test administration so as not to inﬂuence subject responses. Subjects
were each paid $1.00 for their participation.

Data were analyzed in the follows ways. A chi-square was performed on
each activity item to assess possible differential associations with student
gender. The relationship between leisure time activities and delinquent behavior
was examined by conducting a univariate one-way F-test on each aggregate
dimension score of the ALTAS, and the nine delinquency indices were used as
criterion variables. Exploratory and conﬁrmatory factor analysis were performed
to determine the construct validity of the ALTAS. (Yin et. al, 1999) The results Of
this study are extensive, and will be summarized here in point form.

1. Males reported Signiﬁcantly more involvement than females in six of the nine

delinquent behaviors.

18

. Delinquency is signiﬁcantly associated with increased participation in
unsupervised socialization with friends and less frequent participation in
organized leisure activities, organized Sport activities, and activities at home.
. Participation in self-directed leisure activities was not related to any
delinquency index.

. Most of the relationships between leisure activities and delinquency were
consistent across gender; however participation in organized sport activities
had a signiﬁcant positive correlation with male use of marijuana.

. Males had better school performance in association with participation in
organized leisure activities, organized sport activities, and activities at home.
Males left home at night without permission less often in association with
participation in organized leisure activities and sport activities.

. The ATLAS was shown to be a valid instrument for assessing typologies of
adolescent leisure time activities. (Yin et. al, 1999)

A study by WIdmer, Ellis, and Trunnell (1996) also focused on developing

an instrument that might allow a greater understanding of the relationship

between leisure and delinquency amongst youth. The purpose of their study was

to develop an instrument to measure the ethical component of recreation and

leisure behavior that can be used to distinguish between high and low risk

adolescents. The instrument being developed was the Adolescent Ethical

Behavior in Leisure Scale (AEBLS). This scale was based on an interpretation of

the ethical system presented in Aristotelian philosophy. Variables related to

Aristotelian philosophy such as intellectual activity, creative activity, meaningful

19

relationships, and moral behavior were identiﬁed and used in the study to

establish construct and criterion validity and inferences that can be made from

scores on the AEBLS. Many of these variables are of interest due to their
similarity to the current study’s focus on leisure lifestyle and indicators of risk
amongst youth.

WIdmer et. al, (1996) tested the following hypotheses:

1. The AEBLS mean of the low risk group will be signiﬁcantly greater than
the AEBLS score of the high risk group.

2. A signiﬁcant, negative correlation will be found between the AEBLS and
school bonding. School bonding is explained to be the Choice to stay in
high school, continue one’s education, and an interest in learning; this
would be termed retention in most of the literature.

3. A signiﬁcant, negative relationship will be found between the AEBLS and
leisure boredom.

4. A signiﬁcant correlation will not be found between the AEBLS and gender.

5. A signiﬁcant correlation will not be found between the AEBLS and race.

6. A signiﬁcant, positive relationship will be found between the AEBLS
scores and evaluation of cortical recreation activities (involving cognitive
skills).

7. A signiﬁcant, negative relationship will be found between the AEBLS
scores and evaluation of sensory recreation activities.

The last two hypotheses were included in this review although they do

20

not relate to the current study; the results review will not include a discussion of
these two hypotheses

Two studies were conducted investigating construct and criterion related
evidence of validity of the AEBLS. The ﬁrst study addressed the hypotheses of
interest to the current study, examining the relationship between the AEBLS
scores and leisure boredom, substance use, school bonding, race, and gender.
(WIdmer et. al, 1996) The developed AEBLS contained sixty-two items
representing Aristotelian ethical leisure behavior. The Leisure Boredom Scale
(lso-Ahola and Weissinger, 1990) was used, as well as a set of questions related
to school bonding, a questionnaire about substance abuse, and a list of
questions concerning demographics. (WIdmer et. al, 1996)

The subjects for this study included a sample of 346 high school aged
adolescents from agencies serving high risk (n=145) and low risk youth (n=201)
from Northern California and Utah. The participants in the ﬁrst study were
between twelve and nineteen years of age (mean=16.1). The low risk group was
comprised of 111 males and 90 females while the high-risk group was made up
of 91 males and 49 females. Fifteen percent of the low risk and 33 percent of the
high risk group were racial minorities. (WIdmer et. al, 1996) Unfortunately, for this
study speciﬁc information regarding the racial minorities was not provided.

The results of the ﬁrst study produced an alpha reliability estimate Of .90
for the AEBLS and .86 for the Leisure Boredom Scale, respectively. Findings of
signiﬁcance were a positive correlation between AEBLS scores and school

bonding and negative correlations between scores on the AEBLS and substance

21

use and leisure boredom. The relationships between scores on the AEBLS and
race and gender were found to be nonsigniﬁcant. (\Mdmer et. al, 1996)

One of the most extensive studies published in recent times exploring the
relationship between leisure and delinquency amongst youth is the work
completed by Agnew and Petersen, (1989). Agnew and Petersen drew heavily
from theories of criminologists attempting to explain the relationship between
leisure and delinquency. Three theories are discussed as being “of the most
inﬂuential” (p. 333), they are social control theory, subcultural deviance theory,
and strain theory. The following eight hypotheses were tested in this study:

The researchers expected to ﬁnd:

1. a negative relationship between delinquency and time spent in pleasurable
organized leisure activities

2. a positive relationship between delinquency and time spent in unsupervised
peer-oriented social activities

3. a negative relationship between time spent in liked activities and delinquency

4. a negative relationship between delinquency and the amount of time spent in
liked leisure activities with parents

5. a positive relationship between delinquency and the amount of time spent in
leisure activities with peers

6. a negative relationship between delinquency and the amount of time Spent in
pleasurable leisure activities

7. a positive relationship between delinquency and the amount of time spent in

disliked leisure activities

22

8. the relationship between delinquency and certain categories of leisure
activities will be conditioned by the extent to which the leisure activity is liked
(Agnew and Petersen, 1989, pp. 335-337)

One-hour interviews were conducted in the homes of 600 adolescents from
the metropolitan Atlanta area. The subjects were white students attending grades
9-12 in 21 public high schools; the authors report that the subjects were from a
prosperous sample area and generally came from well educated families. The
variable of leisure for this study was measured in a way which differs from most
other studies of leisure. Rather than creating a list of leisure activities and
instructing subjects to Check those that they participate in, the authors of this
study deﬁned leisure as any activity so deﬁned by the respondent. In response to
this understanding of the meaning of leisure, respondents were initially asked to
answer the following open-ended question, “what are your favorite ways of
spending your free time. Up to ﬁve responses were recorded for this item in order
to capture a range of leisure activities; in all 265 activities were named with
almost half the sample being unable to list more than four activities. The activities
listed in response to the initial question were then Classiﬁed into one of the
following ten categories:

1. organized activities (eg. drill team, band, school newspaper, cheerleader,
scouts, Church activities, school homework)

2. social activities (eg. dating, parties, telephone conversations, visiting friends,

play with friends)

23

3. hanging out/loaﬁng (e.g. do nothing, sit around, pleasure driving, hang around
house)

4. passive entertainment (e.g. listening to records, reading, radio, TV, movies,
concerts, sporting events)

5. housework activities (eg. baby-sit, Cleaning, mow lawn, house work, yard
work)

6. sports competitive (e.g. baseball, football, basketball, tennis) Includes both
supervised and unsupervised competitive Sports activities

7. sports noncompetitive (e.g. bike riding, horseback riding, roller skating,
swimming, jogging, boating) Includes both supervised and unsupervised
noncompetitive sports activities

8. games/crafts/hobbies (e.g. embroidering, sewing, model building, Chess,
cooking)

9. music/art (eg. as a performer or active participant - includes dancing, playing
guitar, playing piano, drawing, painting, and photography)

10. other activities (eg. travel, go to beach, visit parks)

The above list seems to omit the speciﬁc category of outdoor recreation, and
it separates sports based on competitiveness only, rather than competitiveness
and level of structure or adult supervision (eg. the pick up basketball game at the
gym verses varsity high school basketball). Other questions asked of subjects in
this study included: 1) with whom did you spend most of this leisure time?
(Options — parents, friends, alone); 2) how frequently do you do these leisure

activities?; and list up to three activities you least enjoy doing. The responses to

24

the “least enjoy doing” item were Classiﬁed according to the ten categories listed
earlier. The variable of delinquency was measured using an adapted self-report
scale that included 19 delinquent acts:

1. hurt somebody badly

steal something worth less than $50

use knife or gun to get something

steal car

serious ﬁghting

steal something worth more than $50

set ﬁre to property

get something through a threat

PPNBBPPN

run away from home

1 0. hit instructor or supervisor

1 1 . hit father

12. steal expensive part of a car

13. hit mother

14. trespass

15. argue or ﬁght with parents

16. damage school property on purpose
17. steal from store

18.take part in a gang ﬁght

19.steal inexpensive part of a car

25

The above items were weighted and three measures of delinquency were
obtained, total amount of delinquency, serious delinquency, and minor
delinquency. The authors also experimented with alternative versions of the
above measure of delinquency, including an unweighted version that produced
essentially the same results. A summary of the results of this study follows:

1. Leisure variables explained roughly six percent of the variance of total and
minor delinquency and four percent of serious delinquency (this data would
indicate that leisure variables played a minimal role in explaining
delinquency);

2. The data suggest that leisure may be a factor (although a minimal one) in
understanding delinquency;

3. Leisure activities are negatively associated with total and serious
delinquency;

4. Hanging out is positively associated with total and serious delinquency while
social activities are positively associated with total and minor delinquency;

5. Passive entertainment and noncompetitive sports had a signiﬁcant negative
relationship to delinquency;

6. Time spent in leisure activities with peers has a positive relationship with both
total and serious delinquency;

7. Time spent in pleasurable leisure activities with parents is unrelated to
delinquency;

8- The hypothesis predicting a negative relationship between delinquency and

time spent In favorite leisure activities was not supported;

26

9. The hypothesis predicting a relationship between delinquency and the total
and relative amount of free time spent in least favorite activities was not
supponed;

10. Delinquency is positively related to the amount of time spent in least favorite

leisure activities with parents. (Agnew and Petersen, 1989)

A study by Caldwell (1995) examined the relationship between youth who
appeared alienated in their leisure time to health compromising, or at-risk
behaviors. Leisure alienation is explained to be a combination of leisure boredom
and rejection of adult structure during leisure. A total of 2756 students in four
high schools located in the southeastern United States completed self-
administered questionnaires for this study during the spring of 1994. The closed
ended questionnaire included standardized items from 1) Youth Risk Behavior
Survey (Centers for Disease Control), 2) Proﬁles of Student Life (Search
Institute), and the Leisure Experience Battery for Adolescents (LEBA). The health
indices included smoking, drinking, suicide, vomiting on purpose, and
depression; leisure participation behaviors measured were participation in Clubs,
going out for fun, and sports involvement in and outside school. Three item
measurers for boredom and rejection of adult structure were used to determine
leisure alienation. Questions focusing on adolescent use of leisure as a reaction
to, or rejection of adult structure were also included.

Leisure alienation was found to be a Signiﬁcant feeling amongst respondents,
as 8-9% of the high school students expressed boredom with their free time and

15% aCtively used leisure to reject adult structure. Adolescents who reported

27

boredom, or who rejected adult structure, were signiﬁcantly more likely to smoke
Cigarettes, abuse alcohol, vomit on purpose, attempt suicide, and be depressed.
An analysis of gender-based differences showed that females who express
boredom in leisure were signiﬁcantly less likely to participate In Clubs or
organizations, go out in the evenings for fun or recreation, or to participate in
teams at school as compared to males. Lower participation in teams at school
was the only Signiﬁcant difference among females who reject adult structure
verses those who do not. Amongst the male subjects, those who were bored with
their free time were signiﬁcantly less likely to participate on teams outside of
school; among the males who reject adult structure, there were no leisure
participation differences. (Caldwell, 1995)

Bergin (1992) investigated the reciprocal relationship of high school students’
school activities and their leisure activities and motivations. The following four
research questions formed the foundation of his study:

1. “Do leisure activities and motivation predict in-school achievement?"
2. “Is student academic achievement related to intense participation in

sports, academic leisure activities, and other leisure activities in different

ways?”

3. “Does school inﬂuence leisure activities by creating continuing
motivation?”

4. “ls continuing motivation positively related to achievement, intrinsic

intellectual motivation, leisure activities, and self-efﬁcacy? “‘(Bergin, 1992,

D. 228)

28

A convenience sample from social studies Classes from two San
Francisco bay area high schools produced 159 subjects. Included in the 159
subjects were 74 males and 85 females. Although ethnicity was not a variable in
this study, subjects were asked to self-report their ethnic afﬁliation. Only 4 of the
subjects reported their ethnicity as Native American; reinforcing the need for a
study focusing on the Native American population. Instruments for this study
included a leisure activity questionnaire that asked students to indicate how
much time per week they spent in each of 43 leisure activities, a subset of
academic leisure activities was developed which focussed on identifying leisure
activities which had obvious academic value. The Intrinsic Intellectual Motivation
Scale, Self-Efﬁcacy Scale, and an open-ended format concerning potential post
secondary education were employed. Academic achievement was measured by
computing GPA’S and continuing motivation was measured through private
interviews with 66 of the subjects. Continuing motivation was described as school
activities generating interests that are pursued in leisure time activities. (Bergin,
1992) Reliability and validity data were provided only for the Intrinsic Intellectual
Motivation Scale.

Bergin’s (1992) results demonstrated that leisure activities are related to
academic achievement, although the relationship was modest; the total number
of academic leisure activities correlated most strongly with GPA (r = .17). Of the
individual leisure activities, two correlated signiﬁcantly with overall GPA, learning
about current events (r = .31) and school-based music lessons (r = .31).

Interestingly students who worked (paid jobs) did not differ in GPA from those

29

who did not work. For students who did work, time on the job correlated
negatively (r = - .40) with GPA. Students who intensely pursued only high school
sports were lower in intrinsic intellectual motivation than students with non-sport
interests. This becomes important in that intrinsic intellectual motivation was a
Signiﬁcant correlate of school achievement. Lastly, Bergin reported that
continuing motivation (school generated interests being pursued in leisure) was
low.

The hypothesis that adolescent substance abusers are more likely to
experience leisure as boredom than non-substance abusers was the focus of a
study by Iso-Ahola and Crowley (1991). This study is important to the current
study in that it further substantiates the predictive validity of the Leisure Boredom
Scale.

Two groups of subjects were utilized for this study; a group of substance
abusers and a control group of non-substance abusers. The 39 subjects in the
substance abusers group all met the criteria for the diagnosis of psychoactive
substance abuse as deﬁned by the American Psychiatric Association’s DSM III-
R. Of the 39 substance abusers, 19 were patients in a private psychiatric hospital
and 20 were outpatients in a substance abuse treatment program at another
psychiatric institute. The substance abuse group was made up of 21 males and
18 females representing a variety of socioeconomic levels, family structures, and
ethnic backgrounds. The age range of the substance abusers was from 15 — 18
years with a mean age of 16.6. VWth regard to ethnic background, only one

subject from this group reported ethnicity as Native American. The control group

30

of 81 non-substance abusing adolescents were 45 male and 34 female students
at a private school from a variety of ethnic groups, socioeconomic levels, and
family systems. None of the subjects in the control group reported being Native
American. The age range of the non-substance abusers was from 15 — 18 years
with a mean age of 16.1. (Iso-Ahola and Crowley, 1991) Since both groups of
subjects in this study were nonprobability samples the external reliability and
validity of this study may be limited.

Leisure boredom was assessed using the Leisure Boredom Scale (lso-
Ahola and Weissinger, 1990). WIth reliability reported in the mid eighties, this
scale consists of 16 items to which the subjects responds on a 1 — 5 (strongly
disagree to strongly agree) scale. Leisure participation in a variety of activities
was self-reported; activities included those done at home and away from home
either individually or with family and friends. As a validity check for the dependent
variable, subjects were asked to indicate their frequency of drug and alcohol use,
both alone and with friends on a 0 — 4 (never to very often) scale. Subjects were
also asked to report gender, age, race, and family makeup. Socioeconomic
status was determined by considering parental employment status. The
instruments were self-administered to both groups of subjects in supervised
settings (Iso-Ahola and Crowley, 1991). '

The validity Check for the dependent variable produced the expected
results; the two groups (substance abusers and non-substance abusers) did
indeed differ signiﬁcantly in self-reported frequency of drug and alcohol use. The

ﬁndings regarding substance abuse and boredom showed signiﬁcant difference

31

between the means of the two groups of subjects; the substance abusers were
signiﬁcantly more bored with leisure than non-substance abusers.

Somewhat surprisingly, the overall leisure participation frequency for the
substance abusers was signiﬁcantly higher than the non-substance abusers.
More speciﬁcally, frequency of participation in ten activities differed signiﬁcantly
between the two groups. The substance abusers participated more frequently in
football, baseball, gymnastics, skateboarding, roller-skating, going to concerts,
and going for a drive, while the non-substance abusers were signiﬁcantly more
likely to participate in reading, tennis, and going to movies. (Iso-Ahola and
Crowley, 1991) These ﬁndings may suggest that the substance abusers have an
overall higher need for excitement, activity, and stimulation, and when these are
not met through leisure activities, they seek substances to produce the desired
effects. The ﬁndings of this study also supported the predictive validity of the
Leisure Boredom Scale, “for behaviors such as lethargy, drug and alcohol abuse,
vandalism and other leisure-related problematic conditions” (lso-Ahola and
Crowley, 1991, p. 269).

Any review of the literature concerning adolescent risk factors and leisure
lifestyle must look at the literature speciﬁc to sport and indicators of risk. Segrave
(1983) undertook an extensive review of the research concerning sport and
delinquency; he concluded that, “the research reviewed clearly shows a negative
relationship between participation in sport and juvenile delinquency” (Seg rave,

1983, p. 197). The study by Landers and Landers (1978) will be reviewed here to

32

 

represent the literature examining the relationship between sport and adolescent
delinquency.

The purpose of the Landers and Landers (1978) study was to assess the
relationship between extracurricular activity participation and delinquent acts.
This ex-post-facto study collected data from senior directories of a high school
located in a small northeastern town. Based on the activities listed for each
student in the directories, students were placed into one of four groups, 1) athlete
only (n = 113), 2) service only (n = 118), 3) athlete and service (n = 170), and 4)
neither — no athletics or service activity (n = 120). Court records were used to
determine the total number of misdemeanor and felony offenses for each of the
four groups of students. Determining the occupation of the major wage earner of
each student’s family controlled for socioeconomic status (Landers and Landers,
1978)

It was found that the socioeconomic scores of the four groups of students
did not differ signiﬁcantly, and that there is a signiﬁcant association between
delinquent acts and extracurricular participation. Of the 87 total delinquent acts
identiﬁed, only 10 were felony convictions, and these all involved students in the
“neither" category. The “service only” and “athlete only” groups were essentially
the same in frequency of delinquent acts. Students in the “neither” category had
higher incidences of delinquent behaviors than students who were in “athlete
only”, and “service activities only,” or both athletics and service (Landers and

Landers, 1978).

33

Although this research included males only and is now somewhat dated,
its ﬁndings do represent the majority of the literature in this area as evidenced by

Segrave’s (1983) review of research related to this topic.

Youth and Risk Behaviors

There is evidence that Native Americans, and in particular Native
American youth, and alternative school students are at greater risk than youth in
general, making it important to understand the factors leading to increased risk
amongst Native American youth and alternative school students. This section
will present some of this evidence.

The following information was taken from the Michigan Pre-Conference
report to the White House Conference on Indian Education. (Dunham-Martell &
Van Alstine, 1997)

Compared to a white Child, a Michigan Indian Child is:

o 4.5 times more likely to live in poverty

. 4.4 times more likely to have no phone In the home

. 3.5 times more likely to live in a home with no furnace

. 2.2 times more likely to live with parents who have no car

0 2.2 times more likely to have four or more siblings

o 4.5 times more likely to live in a single parent household living in poverty

0 4.5 times more likely to have a mother (if married), who married young (17 —

19 years of age)

34

. an Indian Child’s mother probably does not have a job, and she has a greater
likelihood of having no husband and being unemployed

. an Indian child’s family has 4.6 times the possibility of being on public
assistance and is 1.6 times more likely to live in a rented home
The following information was taken from Changing America: Indicators of

Social and Economic Well-Being by Race and Hispanic Origin (1998) for the

President's Initiative on Race:

. according to the 1990 census data, the median family income of American
Indians was lower than that of blacks, which was lower than that of Hispanics
and white, non-Hispanics

. according to the 1990 census, the poverty rate for American Indians was the
highest among the ﬁve racial and ethnic groups

0 according to the 1990 census, American Indian Children had a poverty rate
second only to that of black Children
0 in general, blacks fare worse than any other group, and American Indians and
Hispanics are often disadvantaged in health status relative to whites
- among persons 18 to 34 years of age, smoking rates for America Indians are
higher than those of all other groups
° American Indians face much higher death rates due to suicides and
unintentional injuries than any other group, and also face higher than average
homicide rates
' Between 1983 and 1995 infant mortality rates for American Indians were

Second only to those of Blacks

35

According to the Kids Count in Michigan 1996 Data Book, the 1994-1995
dropout rate for the Brimley Schools (the school attended by the majority of the
Bay Mills youth living in Chippewa County) was 8.6%. This compares with a
dropout rate for the 1999-2000 school year among 16-18 year olds from Bay
Mills of 24%. (C. Adair, personal communication, June 2000)

Perhaps the best indicator of risk amongst Native American youth comes
from the Youth Risk Behavior Study undertaken by the Bureau of Indian Affairs
(1997). This study, which was also conducted in 1994, used an instrument, the
Youth Risk Behavior Survey, developed by the Center for Disease Control (CDC)
for their national survey conducted every two years in over 100 selected high
schools throughout the United States. The Bureau of Indian Affairs (BIA) felt
compelled to replicate the CDC’S efforts with strictly American Indian students

due to the fact that “American Indians are too small a sample nationally to be
statistically reliable." (BIA, 1997, p.2)
The subjects for the 1997 BIA study were 5,606 high school students
(from a total population of 7,780) attending BIA funded schools, including some
in Michigan. Of the 57 BIA funded schools with grades 9-12, 54 participated in
this study (BIA, 1997).
Table 1 presents youth risk behaviors data (as percentages) from the
1997 BIA Youth Risk Behavior Study, the CDC’S 1998 National Alternative High
School Youth Risk Behavior Survey (CDC , 1998), and the CDC’C 1999 National

Youth Risk Behavior Survey (CDC, 1999)-

36

Table 1

National At-risk Youth Behavior Results

 

 

Risk Behavior BIA (1997) Alternative Schools Nationwide Youth
(1998) (1997)
Carried a weapon 25.4% 32.9% 17.3%
Considered suicide 22% 15.7% (attempted) 19.3%
Physical ﬁght on 20.9% 14.2%
school property
Lifetime Cigarette use 84.9% 70.4%
Current Cigarette use 64.2% 64.1% 34.8%
Frequent cigarette use 30.5% 16.8%
Lifetime alcohol use 84.9% 81%
Current alcohol use 53.5% 64.5% 50%
Episodic heavy 42.6% 49.8% 31.5%
drinking
Current marijuana use 52.3% 53% 26.7%
Current cocaine use 10% 15.3% 4%
Lifetime inhalant use 29.4% 14.6%
Ever had sexual 63.3% 87.8% 49.9%
intercourse
Ever had four or more 24.6% 50.4% 16.2%
sexual partners
Currently sexually 40.4% 68.5% 36.3%
active
Played in school team 52.85 55.1%
Sports
Participate in vigorous 57.4% 46.8% 64.7%
Physical activity
Thought they were 35.2% 25.5% 30%

m

37

Leisure Lifestyle and Native Americans

“Traditionally, recreational or competitive sport and recreation activity have
always been important elements within Aboriginal communities. Before the
colonization of Canada, the Aboriginal people held activities at traditional
gatherings, which were not only ceremonies, but also inter-tribal skills
competitions such as bone games, leg wrestling, lacrosse, snow snake, hand
game, and a moccasin game. Many times these competitions were seen as
alternatives to tribal conﬂicts or combats” (Ontario Aboriginal Recreation Council,
1994).

As has been pointed out throughout the current review of literature, very
little attention has been paid to the impact of leisure lifestyle on Native
Americans. This section will present the limited information found in the literature
aimed at examining the leisure lifestyle of the indigenous peoples of North
America.

In the fall of 1993, the Ontario Ministry of Culture, Tourism and Recreation
- Recreation Policy Branch and the Ontario Aboriginal Recreation Council
formed a partnership for the purpose of studying the current state of recreation

V for Ontario’s Aboriginal peoples. The purpose of the resultant survey was to
obtain a snap Shot of the status of recreation in the Aboriginal communities,
(Henhawk, 1994) Some of the speciﬁc elements examined by the survey were:
1- leadership proﬁle of Aboriginal people working/volunteering in recreation;

2- beneﬁts of recreation to Aboriginal people;

3. evaluation of recreation opportunities, gaps and issues;

38

4. strengths and weaknesses in aboriginal recreation programs; and
5. barriers and opportunities for recreation development in aboriginal
communities. (Henhawk, 1994)
In all, 56 Aboriginal communities were invited to participate in the study;
twenty-one (37.5%) communities completed and returned the survey.
The results of this survey indicated:

1. that the majority of Aboriginal communities classify their recreation programs
and/or services to be either fair or poor;

2. the ﬁve top ranking barriers to recreation were: 1) lack of funding, 2) lack of
staff, 3) lack of facilities, 4) lack of volunteers, and 5) poor organization and
lack of structure of recreation programs;

3. for the majority of Aboriginal communities, professional recreation staff,
recreation departments and volunteer committees were non-existent;

4. Aboriginal people currently participate in a limited range of team and
individual activities depending on the opportunities they have access to;

5. Aboriginal people participate in sport and recreation for a variety of reasons
including social beneﬁts, competition, exercise and personal growth;

6. on reserve communities generally have few recreation facilities located within
the community itself and those facilities usually are in poor condition;

7. cultural beneﬁts are a signiﬁcant reason for participating in large sporting

events;

39

8. Aboriginal communities unanimously agree that recreation services should
be made a priority and that recreation is very important to an individual’s
health and to their community; and

9. the aboriginal communities unanimously agree that sport and recreation
programming for youth is important as a means to teach constructive use of
spare time, preventative measures to drug and/or alcohol abuse, provide an
opportunity for social interaction and to build self-esteem. (Henhawk, 1994)

Caution must be used when considering the above results; the motivation
to respond to the survey may have been the desire to justify higher levels of
funding for recreational programming. It is also important to note that Aboriginal,
or Native American communities can be as varied as non-Native communities; it
would be a mistake to take the above results and generalize them to all Native
American communities.

The purpose of a doctoral dissertation by Van Der Wal (1988) was to
determine if recreation, sports or competitive activities affected age-grade
displacement and academic achievement of elementary and secondary Indian (in
this case Native Canadian) students. A case study approach was instituted for
this study; this approach “was necessary in that scientiﬁc control and
experimental groups and population samples were not possible at the time” (Van
Der Wal, 1988, pp. 31-32). Since standardized tests were utilized in this study
contemporary school environments were chosen as data collection sites since

thejsta ndardized tests could only be administered in formal education situations.

40

The ﬁrst of the two case study sites was the Marieval Community
Education Center which was located approximately 10 miles due east from the
city of Regina, Saskatchewan on Indian Reserve 73. The Marieval case study
site sample included 63 high school students who were attending full time during
the 1983-84 academic year. This sample included students who were of Plains
Cree, Saulteaux, Sioux, and Assiniboine cultural background. The second case
study site was on the campus of the University of Saskatchewan located in the
city of Saskatoon, which hosted the Indian Track and Field Championships in
1984. Participants at this event came from all areas of the province of
Saskatchewan. The Saskatoon case study site involved 267 Indian student
participants whose ages ranged for 9-23 years and grades 4-12 were
represented.

Provincial and tribal records were used in both case study sites to
establish tribal afﬁliation and to verify ages of the subjects. The standardized
instrument used to assess academic achievement was the Canadian Test of
Basic Skills (C.T.B.S.) High School/Multilevel Edition/levels 15-18, form 5. This
instrument was used “to provide comprehensive High School measurement of
growth and academic achievement in the fundamental skills: listening,

vocabulary, reading, word analysis, language, work-study and mathematics”
(Van Der Wal, 1988, p. 41). The C.T.B.S. is the Canadian version of the Iowa
Test of Basic Skills and is widely used in Canada. For the Marieval case study
site, sports and recreation program participants were compared with non-

PaﬂiCipants. For the Saskatoon site, the track and ﬁeld participants were

41

compared with the total Saskatchewan Indian population, which was provided by
Indian Affairs 1983-84 Provincial Roll.

The results of this study indicated that Indian students who participated in
sports and recreation programs were not signiﬁcantly more age-grade displaced
than those students who were not participants in sports and recreation programs.
It was also shown that Indian students who participated in sports and recreation
programs generally did not have signiﬁcantly different academic achievement
age-grade means than those students who were non-participants, with the
exception of one grade twelve situation where the sports participants had

signiﬁcantly higher overall academic scores. (Van Der Wal, 1988).

Literature Review Summary

The reported relationship between leisure boredom and delinquency
(Wldmer et. al, 1996; Caldwell, 1995), and speciﬁcally substance abuse (lso-
Ahola & Crowley, 1991 ) is consistent and well supported. The greater the level of
leisure boredom, the higher the incidence of delinquent behaviors.

The relationship between delinquency and participation in leisure activities
varies based upon the typology of the leisure activity. In general a negative
relationship between participation in sport and delinquency is found. (Segrave,
1983; Landers & Landers, 1978) Leisure that involves unsupervised interaction
with peers is strongly associated with higher rates of delinquency and appears to
be consistent across genders. (Agnew & Petersen, 1989; Yin, Katims & Zapata,

1996)

42

Most of the relationships between leisure activities and delinquency were
shown to be consistent across genders. Exceptions included male participation in
organized sports having a signiﬁcant positive affect on increased marijuana use
(Yin, Katims & Zapata, 1999); males had better school performance in
association with participation in organized leisure activities, organized sport
activities, and activities at home. (Yin, Katims & Zapata, 1999)

The impact of leisure lifestyle on academic performance seems to be less
clear. Bergin (1992) reported a modest relationship between leisure activities and
academic achievement. Van Der Wal (1988) reported no relationship between
participation in sports and recreation programs and indicators of academic
success amongst Native American youth. Bergin (1992) also reported that
students who intensely pursued only high school sports during their leisure were
lower in intrinsic motivation for academics than students with non-sports

interests. Wrdmer et. al, (1996) found a signiﬁcant correlation between ethical
behavior in leisure and school retention.

As was pointed out in the introductory chapter and the literature review,
there is an obvious lack of research concerning the leisure lifestyle of Native
Americans. The literature does however clearly indicate that Native American
youth experience increased levels of risk compared to youth in general (Dunha-

Martell & Van Alstine, 1997; B.l.A., 1997). Henhawk (1994) reports that
Aboriginal peoples, as do those from most communities, value leisure and fully
understand the potential beneﬁts of leisure and recreation on the health of the

individual and the well being of their communities. The lack of qualiﬁed

43

recreation/leisure professionals working in Aboriginal communities is reported as

a barrier to organized, successful recreational programming. (Henhawk, 1994)

44

Chapter Three: Methodology

At this point the author would like to make it known that the original focus
of this study was to compare Native American and non-Native American high
school-aged youth attending the same high school on the variables of leisure
lifestyle and risk. Access to sufﬁcient numbers of high school students was
initially approved by public school administrators only to be denied later by a high
school principal. The result of the last minute denial of access to the high school
students was the inclusion of the Bay Mills youth and Alternative School students

in the current study.

Subjects

The population for this study included two mutually exclusive groups, 1)
students enrolled in the Sault Ste. Marie, Michigan Alternative Education Center
during the Spring semester 2000, and 2) all registered members of the Bay Mills
Indian Community between twelve and nineteen years of age living in Chippewa

County (Michigan).

Sault Ste. Marie Alternative Education Center

 

Background

The Sault Ste. Marie Public School system serves 3,120 students in one

Hi9h School, one Middle School, six Elementary Schools, one Vocational

45

Technical Career Center, and one Alternative High School. The Sault Schools
are one of only twenty districts in Michigan to be totally K-12 accredited with the
North central Association of Schools and Colleges (1998-1999 Annual Education
Report, Sault Ste. Marie Area Public Schools).

Of the persons 20 years of age and older in the Sault Schools service
area 3,115 had 12th grade or less/no diploma, 4,790 were high school graduates,
3,958 had some college/no bachelor degree, and 1,675 had a bachelor degree or
higher (1989-1990 School District Data Book).

Of the total persons living in the Sault Schools service area none lived in
Urban-Inside Urbanized Areas, 14,689 lived in Urban-Outside Urbanized Areas,
200 lived in Rural-Farm Areas, and 4,445 lived in Rural-Non-farm areas (1989-
1990 School District Data Book).

The median household income for the service area was $21 ,965 compared to
the state of Michigan household median of $31,020. Based on income in 1989,
15,167 persons lived above the poverty level and 3,120 lived below the poverty
level (1989—1990 School District Data Book). The High School drop out rate in
1997 was 6.7% (1998-99 Annual Education Report, Sault Ste. Marie Public
Schools).

The following information regarding the Sault Ste. Marie Alternative Education

Center was provided in writing by Gary Deuman, the center’s director in
response to written questions from the researcher.

Question #1: Where geographically do your students come from?

46

The center is operated by the Sault Area Public Schools; the student’s
parents must reside in the Sault School district if the student is under eighteen.
The center also takes about 6-8 school of choice students.

Question #2: How does a student initially become enrolled at the alternative
school and for what reasons?

The students who are sixteen or older can self refer; students under sixteen
and at least fourteen must be referred by a secondary school. Most students are

referred by the sending school for either behavior or attendance problems. Self-

 

referred students are there mainly because they couldn’t or wouldn’t follow the
more restrictive rules of the high school.

Question #3: In general, what characteristics do your students share which
may set them apart from other students?

The students seem to have difﬁculty with authority, whether it is the rules are
too restrictive or with actual authority ﬁgures. They tend to however, have an
ability to relate to at least one adult who shows interest in them and who displays
consistent expectations of their behaviors. Many of the students engage in some
sort of addictive behavior including smoking.

Question #4: How does the environment and approach to teaching differ at

the altemative school compared to the main campus of the high school?

The alternative is smaller and everybody tends to know each other and what

goes on. There are fewer opportunities for extra activities. The classes are

Shorter and the students can take more classes. I think the teachers have an

47

ability to accommodate a wide variety of abilities and motivation among students.
They cannot rely on homework, as we generally do not assign homework.

Question #5: During the period of time when we were collecting data, (for the
cunent dissertation project) how many total students would have been attending
your school?

Approximately sixty students were in attendance. (G. Deuman, personal
communication, May, 2000)

The following information from the CDC (1998) supports the above
description of the alternative school and its students, “Alternative high schools
serve approximately 280,000 students nationwide who are at risk for falling or
dropping out of regular high school or who have been expelled from regular high
school because of illegal activity or behavior problems." (p. 3)

Summarv Statistics

Of the sixty (60) students attending the Alternative Education Center at the
time of data collection thirty-eight (38) completed the research instruments; this
represents a response rate of 63.3 %. The mean age for the subjects from the
Alternative School was 16.4 years; the minimum age was 13 and the maximum
was 20. There were 15 (39.5%) males and 23 (60.5%) females with 20 (52.6%)
tribal members and 18 (47.4%) who were non-tribal. None of the tribal members

were members of the Bay Mills Indian Community.

48

Youth of the Bay Milljs Indian Community
Background
The Bay Mills Indian Community (BMIC) is located approximately 15 miles

west/southwest of Sault Ste. Marie, Michigan in Chippewa County. The BMIC
was one of the original four reservations established in Michigan with the
passage of the Indian Reorganization Act of 1934. The BMIC has a total of 1269
tribal members, with 564 living within reservation boundaries or elsewhere in
Chippewa County (Overall Economic Development Plan, 1999-2000). It should
be noted that as this research was being conducted the BMIC was experiencing
a substantial period of growth and tribal enrollment numbers were changing on a
daily basis.

The majority of the school-aged children of the BMIC living on or near the
reservation attend the Brimley Area Public Schools and account for 53% of the
total enrollment of the Brimley Schools. All of the subjects from Bay Mills were

attending regular, public school.

Summary Statistics

From the initial mailing list of 112 potential subjects, a total of sixty-three (63)
young people completed the study instruments for a response rate of 56.3%. The
mean age of the subjects from Bay Mills was 15.3 years; the minimum age was
12 and the maximum was 19. There were 34 (54%) males and 29 (46%)

females. All of the subjects from Bay Mills were tribal members.

49

ac

Lilli

a“);

Instruments

Leisure lifestyle for this study was represented by self-reported recreation
participation patterns and self-reported boredom during leisure. Recreation
participation patterns were measured using a slightly modiﬁed version (Appendix
A) of the Adolescent Leisure Time Activity Scale (ALTAS) developed by Yin et
al., (1999). The original scale included 24 leisure activities that were taken from
leisure activity scales by Agnew and Petersen (1989), Kelly (1996), Yu (1980),
and Yin et al. (1996) - as reported in Yin et al. (1999). Students were asked if
they usually, sometimes, or never participated in the individual leisure activities
after school and/or on weekends. The ALTAS includes ﬁve typologies of leisure,
1) unsupervised socialization with friends, 2) organized leisure activities, 3)
organized sport activities, 4) activities at home, and 5) self-directed leisure
activities (Yin et al., 1999). Each of the 24 individual leisure activities is classiﬁed
under one of the ﬁve typologies of leisure. The typologies of leisure then become
the units of concern for analytic purposes. Exploratory and conﬁrmatory factor
analysis were conducted on the ALTAS by Yin et al. (1999) to provide support for
the ALTAS as a valid and reliable instrument. The results of this analysis
supported the ALTAS as an acceptable research instrument.

Leisure boredom was assessed using the Leisure Boredom Scale (lso-
Ahola and Weissinger, 1990). A copy of this scale is included as Appendix B.
The Leisure Boredom Scale was utilized due to the reported correlations
between this scale and other scales measuring important constructs of leisure

lifestyle. These include the Intrinsic Leisure Motivation Scale, Leisure

50

Satisfaction, the Leisure Ethic Scale, Frequency of Leisure participation,
Perceived Social Competence Scale, and the Self as Entertainment Scale (lso-
Ahola and Weissinger, 1990). The results of three separate studies by lso-Ahola
and Weissinger provide support for the reliability and validity of the Leisure
Boredom Scale (1990). The scale itself includes 16 items to which subjects
respond on a ﬁve-point Likert scale. Items 2, 4, 7, 8, 9, 12, 13, and 16 utilize
reverse coding. (lso-thla and Weissinger, 1990).

Indicators of risk were assessed using a slightly modiﬁed version of the
Self-reported Delinquent Acts questionnaire by Yin et al., (1999). A copy of the
modiﬁed version used for the current study is included as Appendix C. Segrave
(1983) supports the use of self-report tests to measure indicators of risk or
delinquent acts, “several self-report tests have provided favorable results when
compared against such checks as ofﬁcial records, lie detectors, and the word of
informants" (p. 188). Additionally, “after an extensive analysis of self-report
methodology in delinquency research, Hardt and Peterson-Hardt concluded that
the procedure yielded accurate results and can make an important contribution to
etiological studies of delinquent behavior” (as cited in Segrave, 1983).

The three instruments described above were combined into a packet
along with a separate page developed for the current study that included items

concerning age, gender, grade in school, and tribal afﬁliation (Appendix D).

51

Th:
one
ma"
cont

Alter;

Arrangements for Data Collection
Application was made to the Michigan State University Committee on
Research Involving Human Subjects (UCRIHS) for the approval of this research

project. Approval from UCRIHS was received on May 9, 2000.

Alternative Education Center

The initial step in the process of arranging for data collection was a
request to the Assistant Superintendent of Schools for the Sault Ste. Marie Public
Schools to collect data at the Sault Ste. Marie Alternative Education Center. This
request was initially made via a telephone conversation that was followed up with
a mailing providing details regarding purpose, instruments, consent, and other
speciﬁcs of the study. The Assistant Superintendent subsequently approved the
request for data collection and recommendations for further meetings with school
ofﬁcials were made.

On April 17, 2000 the researcher met with Dr. Cathy Tibbett, Director of
Academic Services for the Sault Ste. Marie Public Schools. The purposes of this
meeting were to present the study purpose and design to Dr. Tibbett and to
initiate planning for the actual data collection at the Sault Ste. Marie Alternative
Education Center. As a result of this meeting numerous concerns were raised.
These concerns included the supervision of students being asked to move from
one room to another in the school, students who do not have informed consent
may not be in the room with subjects during the data collection, assurance of
conﬁdentiality of subjects and their responses, and the need to meet with the

Alternative Education Center Director and ultimately the teachers to get them “on

52

 

YT

boar During this meeting the researcher was also provided with numerous
sources of information about the Sault Ste. Marie Schools and its students and
service area.

The researcher met with Gary Deuman, Director of the Alternative
Education Center on May 8, 2000 to make arrangements for data collection.
During the meeting the researcher visited each classroom and explained the
project to the teachers and students. Students were made aware of the steps
they needed to take in order to participate in the study. At this time
parent/guardian informed consent forms (Appendix E) were distributed to all
students under the age of eighteen and participant informed consent forms
(Appendix F) were handed out to all students. It was further explained to students
that when they returned the completed consent form(s) to Mr. Deuman, they
would receive a soda and that all students who participated in the study would be
eligible to win one of three $50.00 gift certiﬁcates from a local clothing store.

Additional copies of the informed consent forms were left with Mr. Deuman
to distribute to students who misplaced their forms. Mr. Deuman and the school
staff checked with students for a period of one week to remind them to bring in
the completed consent form(s). Mr. Deuman maintained a list whereby he was
able to keep track of which students had returned the required completed
consent form(s). In some cases the school made phone calls to
parents/guardians who then came to the school and completed informed consent

forms.

53

 

Dates for the collection of data were set up for Tuesday, May 23 and

Thursday, May 25, 2000.

Bay Mills lndijap Cornrnurm

On May 18, 2000 the researcher submitted a letter (Appendix G) to the
Executive Council of the Bay Mills Indian Community requesting permission to
invite all tribal youth between the ages of thirteen and nineteen to participate in
this study. The tribal council at their regularly scheduled meeting on Monday,
May 22, 2000 approved the researcher’s request (Appendix H). Even though the
researcher did not request it, the tribal council also approved an incentive of
$50.00 for each tribal youth who participated in the study.

A list of names and addresses of all tribal youth of the Bay Mills Indian
Community between the ages of thirteen and nineteen (N = 112) residing in
Chippewa County was requested from the Tribal Enrollment ofﬁce. All youth
included on this list were mailed a cover letter (Appendix I) and consent forms on
May 6, 2000. The purposes of the cover letter were to introduce the young
people to the purpose of the study, to explain the informed consent requirements,
to introduce the conﬁdential and voluntary nature of the study, to explain the
$50.00 incentive approved by the Executive Council, and to provide directions for
participation in the study. The cover letter and consent forms were also sent as
an attachment in an email sent to all employees of the Bay Mills Indian
Community, many of whom are parents or guardians of the potential study

participants.

54

The cover letter sent to the youth directed them to attend one of two
sessions, Monday, June 12 or Saturday, June 17, 2000 at the Waishkey Center
in the Bay Mills Indian Community. One weekday and one weekend date were
chosen to provide the greatest amount of opportunity to accommodate various
youth work and activity schedules. The Waishkey Center houses the
community’s Recreation and Health Promotion Department of which the
researcher is the Director, as well as a large meeting room with enough tables
and chairs to accommodate the youth who would be participating in the study.

The researcher made arrangements for two adult employees of the
Department of Recreation and Health Promotion to assist with room supervision
during each data collection session. One of the room assistants has a Ph.D. and

is therefore familiar with the conditions required for data collection of this nature.

Data Collection Techniques
§_a_ult Ste Maje Alternative Education Center

On two separate occasions (May 23 and May 25, 2000) the researcher
visited the Alternative Education Center for the purpose of administering the
research instruments. Two separate dates were chosen due to the high daily
absentee rates at the school.

On the ﬁrst occasion the researcher with the assistance of the center’s
director identiﬁed which students were present that day for whom completed
parent/guardian informed consent forms and/or participant informed consent

forms had been received. All of these students were then asked to gather in one

55

classroom. One teacher was present in the classroom during the data collection

to ensure an orderly classroom environment. The researcher then double-

checked that only students for whom completed informed consent forms were on
ﬁle were present in the room.

Once it was determined that all students present were cleared to participate in
the study the researcher explained the format of the data collection and
reiterated the voluntary and conﬁdential nature of the study. Participants were
reminded that only if they completed the instruments would they be eligible for
the drawing, and that they would be asked to leave the room if they were
disruptive or were not proceeding in the manner described by the researcher.

At this point the researcher distributed writing instruments and described the
following procedures:

1. After the questionnaires were handed out participants were not to begin
reading the directions until the researcher began reading them out loud.

2. After the directions for each portion of the questionnaire packet were read an
opportunity for participants to ask questions would be provided.

3. After the opportunity to ask questions had passed, the researcher would
begin reading out loud each item of the questionnaires. After the item was
read participants would be given an opportunity to ask questions about that
item. Participants were asked not to respond to an item until they understood
all words in the item and the overall nature of each item completely. The

researcher would then proceed to the next item.

56

Al
59

Wt

Dar

date

4. Participants are to keep their eyes on their own questionnaires and are to
refrain from talking to one another.

5. Participants were asked to answer each item as honestly and accurately as
possible keeping in mind that their name would never be associated with their
responses.

At this point the researcher read out loud the directions followed by each item
until the questionnaire packet was completed. Completed questionnaires were
gathered by the researcher, placed in an envelope and then sealed. The date
and location of the administration was indicated on the outside of the envelope.
Each student then printed their name on a small piece of paper that was placed
in a separate envelope for the purpose of the drawing for the gift certiﬁcates. The
envelopes containing the responses and names for the drawing were kept
separate from one another at all times.

Participants were then thanked for their participation and were dismissed to
their respective classrooms.

The procedures for data collection on the second administration at the
Alternative Education Center were identical to those described above. After the
second administration all participants were asked to come to one classroom and
witness the drawing for the gift certiﬁcates.

In the opinion of the researcher and the teacher present, the students
participated in the study in a very well behaved and serious manner during both

data collection sessions. It was not necessary to ask any of the participants to

57

leave the room for reasons of inappropriate behavior, talking, or not complying

with the stated procedures.

Bay Mills InderCommunihl

The collection of data for the two sessions at the Bay Mills Indian Community
were both conducted in the following manner.

All youth who arrived for the purpose of participating in the study were asked
to line up in the hall way leading to the meeting room. One by one the young
people entered the room where their names were checked against the tribal
enrollment list and they were asked for their completed consent form(s). If they
were not on the enrollment list they were asked to leave and if they did not have
completed consent forms they were given another copy of the forms and asked
to attend the next session with the consent forms completed.

Once all of the qualiﬁed youth were in the meeting room and seated the
researcher provided instructions in a manner that was identical to those
discussed earlier with the Alternative Education groups. The instructions were
followed by the actual administration of the research instruments in a manner
that was once again identical to the procedure described earlier with the
Alternative Education groups.

After the administration was completed all instruments were placed in an
envelope which was sealed with the date and location noted on the outside of the
envelope. Participants were then asked to record their names and addresses on

a sheet of paper for the purpose of requesting their $50.00 incentive from the

58

 

tribal accounting department. These names and addresses were at all times kept
separate from the completed research instruments.

As was the case with the Alternative Education students, the participants from
Bay Mills, in the opinion of the researcher and assistants, behaved in a very
respectful and serious manner.

The completed consent forms from each administration at the Alternative
Education Center and Bay Mills were placed in sealed envelopes and retained by

the researcher in his ofﬁce.

Analysis of Data
l__strument Scorinq

In order to assure control and accuracy each completed questionnaire
packet was numbered from 1 to 101. Scoring forms were then used to calculate
leisure boredom scores, total risk scores, and leisure typology scores for each
subject.

Each item on the Adolescent Leisure Time Activity Scale (ALTAS) was
scored one (1) for a response of “never”, two (2) for “sometimes”, and three (3)
for “usually”. The score for each individual item was then included in the
appropriate leisure typology and a cumulative score for each of the ﬁve
typologies was calculated. The scoring form for the ALTAS is included as

Appendix J.

59

The leisure boredom score for each subject was calculated by summing
the responses from each 5-point likert item on the Leisure Boredom Scale. Items
2,4,7,8,9,13, and 16 were reverse scored and once again a score sheet
(Appendix K) was developed and used by the researcher.

Each item on the Indicators of Risk Scale was scored one (1) for “no”
responses and two (2) for “yes” responses. A scoring sheet was utilized
(Appendix L) and items ten (10) and (12) were reverse scored. Each risk item
was summed to calculate the total risk scores. Gender, Bay Mills tribal

membership, and school afﬁliation were also noted.

Data Analysis

Initially histograms were developed for the variables of 1) ﬁve typologies of
leisure, 2) total risk, and 3) leisure boredom. The purpose of the histograms was
to visually inspect the data to determine the normalcy of the distribution for all
subjects involved in this study. Statistical tests of normality are available but the
visual inspection of a histogram is considered the most revealing means of
becoming familiar with the characteristics of a distribution. (StatSoft Electronic
Textbook, 2000) This step was important since subsequent statistical tests
assumed normalcy of the distribution; although, most tests are quite robust with
regard to violations of this assumption. (StatSoft Electronic Textbook, 2000)

Additional descriptive statistics were then calculated for the primary
categorical and dependent variables. The descriptive statistics (mean, standard

deviation, and standard error) provided the researcher with an initial awareness

60

of the data and provided the foundational knowledge necessary for more
advanced analyses.

Multivariate measures of association were calculated to determine if
differences existed between the categorical variables of gender (Bay Mills only)
and school afﬁliation (Bay Mills youth and alternative school) on the dependent
variables. The multivariate tests were used as an omnibus test of signiﬁcance to
determine if further analyses were warranted. Of the four most commonly used
multivariate measures wilk’s lambda was chosen as it is considered the most
easily interpreted. (StatSoft Electronic Textbook, 2000)

As a follow up or “post hoc” test of signiﬁcance univariate F tests were
calculated to identify which of the dependent variables was contributing to any
differences found in the multivariate analyses. (StatSoft Electronic Textbook,
2000)

ANOVA was used rather than the simple t-test because with ANOVA it is
possible to test each factor while controlling all others, making ANOVA more
statistically powerful than the simple t-test. Another advantage of ANOVA over
the t-test is that ANOVA allows for detection of interaction effects between
variables and therefore, the ability to test more complex hypotheses about reality.
(StatSoft Electronic Textbook, 2000)

Assumptions for ANOVA include normality of the distribution and
homogeneity of variances. It is also assumed that the dependent variable is

measured on at least an interval scale. (StatSoft Electronic Textbook, 2000) The

61

F-statistic is remarkably robust to deviations from normality and homogeneity of
variances. (StatSoft Electronic Textbook, 2000)

Regression analyses were calculated to learn more about the relationships
between the categorical variables and the dependent or predictor variables. In
the social and naturalsciences multiple regression procedures are widely used in
research. In general multiple regression allows the researcher to ask, “what is the
best predictor of...”. (StatSoft Electronic Textbook, 2000) Speciﬁcally, multiple
regression was used to determine the variance in total risk explained by leisure
lifestyle and the degree to which each of the leisure variables was related to the
dependent variable of total risk.

The assumptions for regression analysis focus on the issues of linearity,
normalcy of the distribution and redundancy or multicollinearity of the predictor
variables. (StatSoft Electronic Textbook, 2000) In practice the assumption of
linearity can virtually never be conﬁrmed; fortunately regression procedures are
not greatly affected by minor deviations from this assumption. (StatSoft
Electronic Textbook, 2000) The assumption of normalcy of the distribution was
examined with histograms. Multicollinearity issues were considered by examining

tolerance levels, eigenvalues, or condition indices. (Vlﬁlkinson, L., 1990)

62

Chapter Four: Results

This chapter presents the results of the statistical analyses. The ﬁrst
results presented are the descriptive statistics, followed by multivariate analysis,
univariate analysis, and regression analysis.

The variables included for analysis were: 1) Bay Mills youth or Alternative
School student (categorical), 2) leisure boredom score and score for each of the
ﬁve typologies of leisure (independent), and 3) total risk score (dependent).

Data were analyzed with the software programs SYSTAT 5.04 and Microsoft

Excel 97. Graphs were created with Microsoft Excel 97 and SPSS 10 Standard

Version.

63

Descriptive Statistics Results

Histograms are presented for all subjects on each of the variables for the
purpose of determining if the data approximate a normal distribution.

The statistical analyses tools used throughout this chapter assume that
the data being analyzed approximate a normal distribution; thus the need create
and visually inspect these histograms.

Figure 1. Unsupervised Socialization with Friends

30

.. Z \

lo \
5 Std. Dev= 1.77
Mean 2 11.9

0 N = 101.00

7.0 3.0 9.0 1070 1170 1270 13:0 1450 1570

 

 

 

 

 

 

 

 

 

 

 

Frequencies

 

Scores

A visual inspection of Figure 1 indicates that the normalcy is present for

the variable unsupervised socialization with friends for all subjects.

64

Figure 2. Organized Sport Activities

40

 

30

 

 

 

 

20
Std. Dev = 1.84

,, / _,
Mean = 4.8

 

 

 

 

 

 

 

 

Frequencies

 

Scores

A visual inspection of Figure 2 indicates that the data is skewed. This is
not surprising given the expected lack of organized sport activity participation by

the alternative school students.

65

Figure 3. Activities at Home

 

 

 

 

 

 

 

 

 

 

 

30
20
10
(D
.9
O
5 Std. Dev . 1.42
a. 3 ‘ Moan - 8.8
3.: 0 N - 101.00

 

6.0 7.0 8.0 9.0 1070 1170 1270

Scores

A visual inspection of Figure 3 indicates that the normalcy is present for

the variable activities at home for all subjects.

Figure 4. Organized Leisure Activities

40

 

30
20 \

10

 

 

 

 

 

 

 

 

 

 

 

Frequencies

Std. Dev = 2.59
Mean = 13.4
—_l E N = 101.00

8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0

 

Scores

66

A visual inspection of Figure 4 indicates that the normalcy is present for

the variable organized leisure activities for all subjects.

Figure 5. Self-directed Leisure Activities

20

10

Frequencies

 

 

 

 

 

 

 

 

 

0.0 8.0 10.0 12.0 1470

Scores

Std. Dev ’- 1.83

Mean = 9.3
N - 101.00

A visual inspection of Figure 5 indicates that the normalcy is present for

the variable self-directed leisure activities for all subjects.

67

Figure 6. Leisure Boredom

 

 

 

 

 

 

 

 

 

 

 

 

 

30

20

10
g \
g , , \ Std. Dev = 8.00
8- \ Mean = 38.8
E 0 .4 N = 101.00

 

 

 

2070 2570 350 3670 450 4570 515 5570 6070

Scores

A visual inspection of Figure 6 indicates that the normalcy is present for

the variable leisure boredom for all subjects.

Figure 7. Total Risk

 

 

 

 

 

 

 

 

 

 

30

20

‘l

10
ID
.9
U
5 Std. Dev = 2.95
3' ‘ Mean = 18.4
E 0 < N = 101.00

 

- i

14.0 16.0 1670 250 2270 2470 2670

Scores

68

A visual inspection of Figure 7 indicates that the normalcy is present, and
the curve appears to be bi-modal, for the variable total risk for all subjects.

The above histograms (ﬁgures 1-7) indicate that for six of the seven
variables the shape of the distribution approximates a normal distribution. This
provides evidence that assumptions concerning normalcy of the distributions are
not being violated for statistical analyses.

Means, standard errors, and ranges for alternative school students and all
youth from Bay Mills are presented for the following variables:

1. ﬁve typologies of leisure (unsupervised socialization with friends, organized
leisure activities, organized sport activities, activities at home, and self-
directed leisure activities)

2. total risk score

3. leisure boredom score

Descriptive statistics were utilized ﬁrst to assist with identifying general
tendencies and differences. This initial analysis was valuable for the purposes of
developing an overall awareness of the data and determining which further
statistical analyses may be warranted.

Implications of Tables 2, 3, 4, and 5 and along with Figure 8 will be
summarized after Figure 8 is presented.

It is of no beneﬁt to compare scores from the ﬁve typologies of leisure to
one another. They represent sums from individual activities, and the typologies
do not have equal numbers of activities available for scoring. It is useful however,

to compare scores between the groups being analyzed.

69

Table 2
Means. Standard Errog, and Ranqes for Bav Mills Youth for the Five Tvoologies

of Leisure (n = 63)

 

 

Unsupervised Organized Organized Activities Self-directed
Socialization Leisure Sport At Homed Leisure
with Friends‘ Activitiesb Activitiesc Activitiese
Mean 11.87 14.43 5.38 9.25 9.84
Range 8-15 9-21 3-9 7-12 7-14
(Min/Max.)
Standard .24 .28 .24 .17 .22
Error

 

Note. Minimum score for each variable indicating no participation:

“' unsupervised socialization with friends (5)
b organized leisure activities (8)

° organized sport activities (3)

d activities at home (4)

° self-directed leisure activities (5)

70

Table 3

Means Standard Errors. and Ranges for Alternative School Students for the Five

 

Typolggies of Leisure (n = 38)

 

 

Unsupervised Organized Organized Activities Self-directed
Socialization Leisure Sport At Home‘1 Leisure
with Friends“ Activities” Activities“ Activities"
Mean 11.92 11.71 3.79 8.05 8.39
Range 7-14 8-17 3-7 6-11 5-12
(Min/Max.)
Standard .26 .36 .20 .21 .25
Error

 

Note. Minimum score for each variable indicating no participation:

unsupervised socialization with friends (5)
organized leisure activities (8)

organized sport activities (3)

activities at home (4)

self-directed leisure activities (5)

a
b
C
a
e
Table 4

Means, Standard Errorsg and Ranges for Bay Mills Youth for Leisure Boredom

and Total Risk (n = 63)

 

Leisure Boredom“ Total RiskD

 

Mean 37.54 17.38
Range (Min/Max.) 19 - 60 14 - 23
Standard Error .99 .34

 

Note. Minimum possible score for each variable:

a leisure boredom (16), higher scores indicate higher boredom

b total risk score of (14) indicates absence of risk indicators, higher scores
indicate higher risk

71

Table 5

Means, Standard Errors, and Ranges for Alternative School Students for Leisure

Boredom and Total Risk (n = 38)

 

 

Leisure Boredom' Total W
Mean 40.87 20.18
Range (Min/Max.) 28 - 55 15 - 24
Standard Error 1.27 .42

 

Note. Minimum possible score for each variable:
' leisure boredom (16), higher scores indicate higher boredom
b total risk score of (14) indicates absence of risk indicators, higher scores

indicate higher risk

Figure 8. Means for ﬁve typologies of leisure, total risk, and leisure boredom

scales comparing Bay Mills youth and alternative school students.

 

 

Figure 9. Altematlve School Students and Youth from Bay Mills: Means Compared

45

4O

35»

30

25»

20-

 

     

 

 

 

 

0 i ‘ M _'." .....
Unsupervised ' . . .. .
. . . Org Organized Sports Actrvmes at Self-directed . {
red
Socialization wrth Leisure Activities Activities Home Leisure Activities Total RISk Bo cm

A Friend: , I
llArtamauve School I 11.92 I 11.71 3.79 9.05 8.39 l 20.13 l 40.37 I

Eggurarschoor I 11.97 I 14.43 5.36 9.25 9.64 L 17.38 I 37.54

 

 

 

Tables 2, 3, 4, and 5, and Figure 8 show that the Bay Mills youth were

more involved in organized leisure activities, organized sport activities, activities

72

 

for

y0L

var

the

Mu.

at home, and self-directed leisure activities; while alternative school students had
higher scores for total risk and leisure boredom. There appears to be no
difference between youth from Bay Mills and alternative school students’ scores
for the variable unsupervised socialization with friends.

Tables 2, 3, 4, and 5, and Figure 8 provide initial evidence that Bay Mills
youth and alternative school students differ on six of the seven independent
variables depicted. These differences warrant further analyses aimed at testing
the signiﬁcance of these differences and the relationships between the variables.

Results of multivariate and univariate analyses are presented next.

Multivariate and Univariate Analyses Results

Multivariate analysis of variance results are now presented to determine if
differences seen earlier in leisure variables between the two groups of subjects

are signiﬁcant.

Table 6
Multivariate Analysis of Variance for Bav Mills Youth and Alternative School

Students for Leigre Lifestyle (Five Tvpoloqies of Leisure and Leisure Boredom)

 

 

 

F-statistic 13.75
DF 6, 94
Prob 0.000‘
*g < .05

73

The multivariate test results shown in Table 6 indicate that there is a
statistically signiﬁcant difference between Bay Mills youth and Alternative School
students for leisure lifestyle.

Univariate F-test results are now presented to identify which of the

variables are contributing to the signiﬁcant difference found in Table 6.

Table 7
Unigriate Analysis of Variance for Independent Variables Comparing BayMills

Youth and Alternative School Students

 

11l
"0

Variable SS DF

 

Unsupervised Socialization with Friends 0.055 1 0.017 0.895

 

Organized Leisure Activity 175.112 1 35.147 0.000*
Organized Sport Activity 279.173 1 21.290 0000*
Activities at Home 34.208 1 20.179 0.000"
Self-directed Leisure Activity 49.597 1 17.320 0000*
Leisure Boredom 262.641 1 4.240 0042*
*p < .05

As denoted by the asterisks (*) in Table 7 there are statistically signiﬁcant
differences at the .05 level of signiﬁcance between Bay Mills youth and
alternative school students for the variables organized leisure activity, organized
sport activities, activities at home, self-directed leisure activity, and leisure
boredom.

The results of Table 7 combined the information contained in Figure 8

indicate that the youth from Bay Mills are more likely than the alternative school

74

(n

students to participate in organized leisure activity, organized sports activity,
activities at home, and self-directed leisure activity; while the alternative school
students show signiﬁcantly greater levels of leisure boredom than the Bay Mills
youth.

Hypothesis two of the current study suggested that alternative school
students would have higher rates of participation in unsupervised socialization
with friends than the youth from Bay Mills. This hypothesis was rejected by the
data.

Hypothesis three of the current study predicted higher rates of
participation in 1) organized sports activity, 2) organized leisure activity, 3)
activities at home, and 4) self-directed leisure for the Bay Mills youth than for the
alternative school students. These four components of hypothesis three were
supported by the data.

Hypothesis four of the current study predicted higher rates of leisure
boredom for the alternative school students compared to the Bay Mills youth; this
hypothesis was supported by the data.

It was hypothesized that there would be categorical differences for the
dependent variable total risk. Univariate F-test results are now presented

comparing Bay Mills youth and alternative school students for total risk.

75

 

Table 8

Univgriate Analysis of Variance for Bav Mills Youth and Alternative School

Students for Total Risk

 

Variable SS DF F P

 

Total Risk 186.264 1 26.937 0.000"

 

*g < .05

As denoted by the asterisk (*) in Table 8 there is a statistically signiﬁcant
difference between Bay Mills youth and alternative school students for the
variable total risk.

Table 8 combined with the information contained in Figure 8 indicate that
the alternative school students have signiﬁcantly higher total risk scores than the

youth from Bay Mills; therefore hypothesis one is accepted.

76

 

QU

ids

Regression Analyses Results

Hypotheses ﬁve through nine of the current study were concerned with
quantifying the amount of variance in total risk explained by leisure lifestyle and
identifying which of the leisure lifestyle variables are contributing signiﬁcantly to
the explained variance in total risk.

Hypothesis ten of the current study suggested that leisure lifestyle will be
able to predict group membership as either Bay Mils youth or alternative school
student with a level of accuracy that is greater than chance.

Regression analyses will allow the researcher to arrive at conclusions

regarding these hypotheses.

77

Table 9
Multiple Regression Analysis for all SubLects with Total Risk as the Dependent
Variable and Leisure Lifestyle (Five Typologies of Leisure and Leisure Boredom)

Q the lndegendent Variables

N = 101, multiple R = 0.532, Squared Multiple R = 0.283, Adjusted Squared Multiple R = .238,
Standard Error of the Estimate = 2.576

 

 

Variable Coefﬁcient Std Std Tolerance T P (2 tail)
Error Coef

Unsupervised 0.484 0.155 0.289 0.882 3.1 13 0.002*

Socialization with

Fnends

Organized Leisure -0.265 0.114 -0.0232 0.770 -2.335 0022*

Activity

Organized Sport 0043 0.173 -0.027 0.655 -0.249 0.804

Activity

Activities at Home -0.61 1 0.209 -0.294 0.749 -2.917 0.004*

Self-directed 0.016 0.150 0.010 0.882 0.107 0.915

Leisure Activity

Leisure Boredom 0.106 0.036 0.287 0.81 1 2.965 0.004"

 

*p < .05

According to Table 9, 23.8% of the variance in total risk is accounted for

by leisure lifestyle. As the coefﬁcients indicate, for the signiﬁcant variables the

direction of the relationships is logical and consistent with expectations.

Hypothesis ﬁve predicted that leisure lifestyle in the current study would

explain at least six percent of the variance in total risk for all subjects. With an

adjusted squared multiple R of .238 in table 9, hypothesis ﬁve is accepted.

78

Table 10

Regression Analysis for Bay Mills Youth with Total Risk as the Dependent
Variable and Leisure Lifesgle (Five Typologies of Leisure and Leisure Boredom)

as the Independent Variables

 

N = 63, multiple R = 0.469. Squared Multiple R = 0.220, Adjusted Squared Multiple R = .137,
Standard Error of the Estimate = 2.472

 

 

Variable Coefﬁcient Std Std Tolerance T P (2 tail)
Error Coef

Unsupervised 0.394 0.188 0.277 0.799 2.095 0.041“

Socialization with

Fnends

Organized Leisure 0.021 0.151 0.017 0.869 0.137 0.891

Activity

Organized Sport -0.084 0.190 -0.060 0.760 -0.440 0.661

Activity

Activities at Home 0491 0.274 -0.244 0.756 -1.794 0.078

Self-directed 0.245 0.189 0.162 0.887 1 .295 0.201

Leisure Activity

Leisure Boredom 0.129 0.045 0.382 0.799 2.891 0.005*

 

*p < .05

Table 10 suggests that 13.7% of the variance in total risk is accounted for
by leisure lifestyle. Of the six variables included in leisure lifestyle, the variables
unsupervised socialization with friends and leisure boredom contributed
signiﬁcantly to the prediction of total risk and were positively associated with total

risk for youth from Bay Mills.

79

Hypothesis six predicted that for youth from Bay Mills unsupervised
socialization with friends, organized leisure activities, organized sport activities,
activities at home, and leisure boredom would be signiﬁcant predictors of total
risk. Based on the data presented in Table 10 hypothesis six is rejected.

It was predicted in hypothesis seven that for Bay Mills youth participation
in self-directed leisure activities would not be a signiﬁcant predictor of total risk.

Based on the information presented in Table 10 hypothesis six is accepted.

80

Table 11

ﬁgression Analysis for Alternative School Students with Total Risk as the

Dependent Variable and Leisure Lifestyle (Five Typologies of Leisure and

 

Leisure Boredom) as the Independent Variables

N = 38, multiple R = 0.421, Squared Multiple R = 0.177, Adjusted Squared Multiple R = .018,

Standard Error of the Estimate = 2.554

 

 

Variable Coefﬁcient Std Std Tolerance T P (2 tall)
Error Coef

Unsupervised 0.386 0.285 0.240 0.847 1 .354 0.185

Socialization with

Fnends

Organized Leisure -0.488 0.216 -0.424 0.751 -2.257 0.031“

Activity

Organized Sport 0.397 0.386 0.190 0.779 1.031 0.311

Activity

Activities at Home -0149 0.374 -0.074 0.780 -0.399 0.692

Self-directed 0.089 0.290 0.054 0.850 0.307 0.761

Leisure Activity

Leisure Boredom 0.046 0.057 0.140 0.872 0.800 0.430

 

*9 < .05

Table 11 suggests that 1.8% of the variance in total risk is accounted for

by leisure lifestyle. Of the six variables included as representing leisure lifestyle

only the variable organized leisure activity contributes signiﬁcantly toward the

prediction of total risk for the alternative school students.

Hypothesis eight of the current study predicted that for the alternative

school students unsupervised socialization with friends, leisure boredom,

organized leisure activity, organized sport activity, and activities at home would

81

all contribute signiﬁcantly to the prediction of total risk. The data presented in
Table 11 do not support this hypothesis.

It was predicted in hypothesis nine that self-directed leisure activity would
not contribute in a signiﬁcant way to the prediction of total risk for the alternative
school students. This hypothesis was supported by the data presented in Table

11.

Table 12

Discriminant Analysis Predicting Group Membership between Bay Mills Youth
and Alternative School Students Based on the Independent Variables Organized
Leisure Activity. Orgﬂized Sport Activity, Activities at Home. Self-directed

Leisure Activity. and Leisure Boredom

 

Accuracy of Group Membership Prediction between Bay Mills Youth and
Alternative School Students

 

Bay Mills Youth 82.5%
Alternative School 84.2%

 

Note. The independent variables used for this analysis were found to differ signiﬁcantly between
the Bay Mills youth and the alternative school students in the univariate analysis presented in
Table 7

Table 12 indicates that with far greater accuracy than chance, leisure
lifestyle variables were able to predict membership as either youth from Bay Mills
or alternative school student.

Hypothesis ten suggested that leisure lifestyle variables would predict

group membership as either Bay Mills youth or alternative school student at a

82

accuracy level greater than chance. This hypothesis was supported by the data

in Table 12.

83

Chapter 5: Discussion

Summary of Key Findlngs
Following is a summary in list form of the key ﬁndings from chapter four:

1. Bay Mills youth had significantly higher rates of participation than the
alternative school students in organized leisure activities, organized sport
activities, activities at home, and self-directed leisure activities;

2. The alternative school students had signiﬁcantly higher total risk and leisure
boredom scores than the youth from Bay Mills;

3. When all subjects (Bay Mills youth and alternative school students) were
considered leisure variables explained 23.8% of the variance in total risk. The
leisure lifestyle variables found to be signiﬁcant in explaining the variance in
total risk for all subjects were unsupervised socialization with friends,
organized leisure activity, activities at home, and leisure boredom;

4. When Bay Mills youth were considered separately, leisure variables explained
13.7% of the variance in total risk ;

5. When the Alternative School students were considered separately, leisure
variables explained only 1.8% of the variance in total risk;

6. For youth from Bay Mills, unsupervised socialization with friends and leisure
boredom were the leisure variables contributing signiﬁcantly toward a
prediction of total risk. Increased participation in unsupervised socialization
with friends led to increased total risk scores and higher leisure boredom

scores led to higher total risk scores;

84

7. For the alternative school students, organized leisure activity was the only
leisure variable contributing signiﬁcantly toward a prediction of total risk.
Decreased participation in organized leisure activities led to increased total
risk;

8. Leisure variables were very useful in predicting group membership as either
Bay Mills youth (82.5% accuracy) or alternative school students (84.2%

accuracy);

Explanation for Findings and Integration with Past Literature

Hypotlﬁis 1

It was apparent from the CDC Youth Risk Behavior Survey Results that
alternative school students in general display higher rates of delinquent activity
than regular school students do. (CDC, 1999) Gary Deuman, director of the
Alternative Education center in Sault Ste. Marie also provided support for the
notion that the alternative school students would show higher rates of delinquent
activity than the regular school students would. (G. Deuman, personal
communication, May, 2000) In the case of the current research, the regular
school students were all Bay Mills youth, and evidence was provided in chapter
two indicating that Native American children are at greater risk than non-Native
American children.

It was primarily the personal experience of the researcher and the fact that

approximately ﬁfty percent of the students at the alternative school were Native

85

American that led to the hypothesis that the alternative school students would
have higher total risk scores than the Bay Mills youth, as was supported by the
data.

A reality to consider when reﬂecting on the total risk scores from the Bay
Mills youth, is the researcher’s belief, based on nearly four years of experience
working in the Native American community involved in this study, that ofﬁcial
consequences of law violations by youth may go unreported more often than is

the case outside of the Native American community.

typothesis 2

It was expected that since alternative school students would have higher
total risk scores they would have higher rates of participation in unsupervised
socialization with friends than the Bay Mills youth. This was the relationship
found in Yin et. al, 1999, Yin et. al, 1996 and Agnew and Petersen, 1989.

In the current study, no difference was found between alternative school
students and Bay Mills youth for participation in unsupervised socialization with
friends; even though, as was discussed earlier, alternative school students had
higher scores for total risk. The similarities between the Bay Mills youth and
alternative school students with respect to racial make-up may in part explain the
lack of difference in participation in unsupervised socialization with friends. It also

may be a risk factor both groups share.

86

Hypothesis 3

It was hypothesized that the youth from Bay Mills would have higher rates
of participation than alternative school students in 1) organized sport activities, 2)
organized leisure activities, 3) activities at home, and 4) self-directed leisure
activities based on the results of Yin et. al, 1999 and the knowledge of the
researcher. These expected results were supported by the data.

Yin et. al, 1999 found that delinquency is signiﬁcantly associated with less
frequent participation in organized leisure and sport activities and activities at
home. Here again the higher expected total risk scores for the alternative school
students motivated the hypothesized leisure participation results.

Alternative school students are not eligible, according to Gary Deuman,
director of the Sault Alternative Education Center to participate in high school
sports, nor does the alternative school offer intramural activities for its students.
(G. Deuman, personal communication, May, 2000) The regular school students
were all members of the Bay Mills Indian Community. They have access to many
organized sports and leisure opportunities offered by the community’s
Department of Recreation and Health Promotion. These include gymnastics,
boxing, year-round outdoor recreation programs, arts and crafts, organized
sports leagues, and after-school programming. Within the city of Sault Ste. Marie,
where most of the alternative school students live, there is a serious lack of
organized sport and leisure opportunities for teenagers outside of the High

School’s main campus.

87

It is therefore not surprising that alternative school students showed lower
rates of participation in four of the ﬁve typologies of leisure than the Bay Mills

youth.

Hypothesis 4

The hypothesis that alternative school students would have higher leisure
boredom scores than the Bay Mills youth was supported by the data.

This ﬁnding supports earlier research by lso-Ahola and Crowley (1991)
and Caldwell (1995) showing positive relationships between leisure boredom
scores and delinquency and indicators of risk amongst youth.

Given the ﬁndings for hypothesis three, where alternative school students
showed less participation in four of the ﬁve typologies of leisure, it is not

surprising that they show higher level of boredom during their leisure time.

Hypothesis 5

Hypothesis ﬁve was based on the ﬁndings of Agnew and Petersen (1989).
This was the only research reviewed that attempted to quantify the variance in
total risk explained by leisure behavior. They found that leisure variables
explained roughly six percent of the variance in total and minor delinquency and
four percent of the variance in serious delinquency. Although the amount of
explained variance in delinquency is not large in absolute terms, it is impressive
given that complete models of delinquency considering family, school, peer, and
other variables rarely explain more than twenty-ﬁve to thirty percent of the

vanance.

88

In light of the information provided in the above paragraph the results of
the current study where leisure lifestyle explained roughly twenty-four percent of
the variance in total risk for all subjects seems impressive. Explaining this result
may be a formidable task, and one that will likely require more research.

Possible explanations include differences in the way risk and leisure was
measured in the two studies. Agnew and Petersen (1989) did not include items
regarding sexual activity or academic performance in their risk scale, nor did they
include a leisure boredom score as part their leisure variables as did the current
study. The differences in the ﬁndings between the two studies may also be a
product of subject variations. Agnew and Petersen (1989) surveyed white,
middle-class students from the Metropolitan Atlanta area; it is possible that
leisure lifestyle is a greater predictor of risk for Native Americans and alternative
school students than it is for white students, or for lower socioeconomic classes
than for higher ones.

For the populations included in the current study it is suggested that
leisure choices are inﬂuential and associated with participation in negative risky
behaviors. Conversely, positive leisure choices are clearly associated with a

lower incidence of negative risky behavior.

Hypothesis 6
Based on the ﬁndings of Yin et. al, (1999) and Caldwell (1995) it was

expected that the leisure variables unsupervised socialization with friends,

organized leisure activities, organized sport activities, activities at home, and

89

leisure boredom would all contribute signiﬁcantly toward a prediction of total risk
for youth from Bay Mills. In the current study unsupervised socialization with
friends and leisure boredom were found to contribute signiﬁcantly towards this

prediction and explained 14% of the variance in total risk.

Hypothesis 7
Based on the ﬁndings of Yin et. al, (1999) and Caldwell (1995) it was

expected that the leisure variable participation in self-directed leisure activity
would not contribute signiﬁcantly toward a prediction of total risk for youth from

Bay Mills. In the current study this hypothesis was supported.

Hypothesis 8

Based on the ﬁndings of Yin et. al, (1999) and Caldwell (1995) it was
expected that the leisure variables unsupervised socialization with friends,
organized leisure activities, organized sport activities, activities at home, and
leisure boredom would all contribute signiﬁcantly toward a prediction of total risk
for alternative school students. In the current study only organized leisure activity
was found to contribute signiﬁcantly towards this prediction. This group had little
variation in these independent variables which may have limited their association

with total risk scores.

Hypothesis 9
Based on the ﬁndings of Yin et. al, (1999) and Caldwell (1995) it was

expected that the leisure variable, participation in self-directed leisure activity,

90

would not contribute signiﬁcantly toward a prediction of total risk for students

from the alternative school. In the current study this hypothesis was supported.

Hymthesis 10

In the current study leisure variables predicted group membership as
either youth from Bay Mills or alternative school student with accuracy rates of
82.5% (Bay Mills) and 84.2% (alternative school). Hypothesis ten predicted
accuracy prediction levels greater than chance and was supported by the data.

The alternative school students scored signiﬁcantly higher than the youth
from Bay Mills on total risk and signiﬁcant differences were found between the
two groups for ﬁve of the six leisure variables measured.

The ﬁndings for hypothesis ten supports past research ﬁndings (Widmer,
Ellis, & Trunnell, 1996, Agnew & Petersen, 1989, Yin et. al, 1999) showing

relationships between leisure variables and at-risk behaviors amongst youth.

lmplicatlons and Recommendations

Prggrgmmatic lmplicgtions and Recommendations

Leisure lifestyle as represented in the current study (participation patterns
and leisure boredom) appears to play a major role in explaining levels of at-risk
behaviors for Native American adolescents and alternative school students when
both groups were considered together for analyses. By combining a robust

measure of leisure participation trends (ALTAS) and a proven measure of leisure

91

boredom, the current study was able to explain far more variance in delinquency
than previous work using either leisure boredom scores or leisure participation
patterns, but rarely both.

The ﬁndings that considered all subjects in the current study suggest that
the leisure variables unsupervised socialization with friends, organized leisure
activity, activities at home and leisure boredom all contribute signiﬁcantly to the
relationship between leisure lifestyle and at-risk behaviors. Efforts aimed at
reducing unsupervised socialization with friends and leisure boredom while
increasing organized leisure activities and activities at home should be
successful at reducing at-risk behaviors. The net result would be less
unsupervised time with friends, more time at home with parental or adult
supervision, and more time engaged in organized leisure activities. The
increased participation in organized leisure activity and activities at home should
help in reducing leisure boredom.

Analyses in the current study which separated the Bay Mills youth from
the alternative school students suggested that increasing organized leisure
activity for the alternative school students would be most helpful in reducing
delinquent behaviors. The most effective strategy for the Bay Mills youth would
be to reduce unsupervised socialization with friends and leisure boredom while
increasing activities at home.

It must be considered that leisure boredom as an individual leisure
variable has been shown to correlate highly with leisure repertoire, leisure ethic,

work ethic, leisure awareness, leisure constraints, and self-motivation. (Iso-Ahola

92

& Weissinger, 1987) The signiﬁcant impact of leisure boredom on at-risk
behavior in the current study supports the assertion by lso-Ahola 8. Weissinger
(1987) that leisure education and counseling programs should be effective in
reducing at-risk behaviors amongst youth.

Elementary and secondary school physical education classes might
consider teaching more lifetime leisure skills, rather than developing sport
speciﬁc skills in competitive environments. Doing so may increase perceived
leisure conﬁdence and increase the positive leisure repertoire amongst all
students, not only those who excel in athletics.

The non-proﬁt sector (i.e. Boy’s and Girls Clubs, Scouts, etc.) should also
be looked to for recreation programming for underserved youth, such as the
alternative school students in the current study.

The results of this study should be useful in justifying increased use of
organized recreation programs as a prevention tool in grant applications and
local recreation department budget requests.

Alternative education programs would be well served by providing
organized leisure programs for their students as well as leisure counseling and

leisure education programs.

Research Recommendations
The current study produced some signiﬁcant ﬁnding for two groups of
young people who have not been the target of leisure researchers in the past.

Since this study included heretofore little studied subjects, further studies should

93

be completed using larger samples from different Indian communities and
alternative education programs in order to build upon the generalizability of these
results.

The current study brought together two instruments to measure leisure
lifestyle in a way that should be further explored. Combining the leisure boredom
score with the typologies of leisure participation created a very powerful measure
of leisure lifestyle among these young people. More studies should be
undertaken using this understanding of leisure lifestyle; the result may be a
greater appreciation for the importance of leisure in explaining at-risk behaviors.

Further research should be conducted to determine if the relationship
between leisure lifestyle and at-risk behaviors is consistent amongst young
people from varying socioeconomic groups, cultural backgrounds, geographic
locations, and family circumstances.

The amount of variance in total risk explained by leisure variables in the
current study was considerable (23.8%) when both subject groups were
considered together. When subject groups were analyzed separately the amount
of variance explained by leisure variables dropped considerably; speciﬁcally the
amount of variance explained was 13.7% for the Bay Mills youth and 1.8% for the
alternative school students. Further research investigating these differences is
warranted.

It would be of beneﬁt to examine if the inﬂuence of leisure lifestyle on

delinquent behavior varies with changes in age. For example, is leisure lifestyle

94

more important as a means of prevention at earlier ages, and at what age is
leisure lifestyle no longer a signiﬁcant factor in explaining delinquent behavior.
Future research should attempt to track a group of young people,
monitoring their leisure lifestyle and participation in delinquent behaviors. It would
be helpful to monitor young people from varied racial and economic groups. By
entering as many variables as possible into the equation, including leisure,
academic success, socioeconomic status etc., it may be possible to create a
“proﬁle” that seems to lead to success and one that seems to lead to
delinquency. It would then be of interest to determine if the above noted “proﬁle”

differs amongst various racial and socioeconomic groups.

95

Appendix A

Adolescent Leisure Time Activity Scale (AL TAS)

96

Adolescent Leisure Time Activity Scale

The purpose of the following questionnaire is to ﬁnd out which activities you
participate in during your leisure time; leisure time is free time you have after
school and/or on weekends. For each activity listed, indicate with a checkmark
how often you participate in that activity, usually, sometimes, or never.

Thank you.

1.

Riding a bike, roller skating/bladlng, skate boarding, skiing, sledding,
or snow boarding

usually sometimes never

Flshlng (non- commercial) or hunting

usually sometimes never

Participating in band, school clubs, yearbook, or cheerleadlng

usually sometimes never

Participating In activities at community youth/recreation centers

usually sometimes never

Hanging out or driving around with friends

usually sometimes never

Hanging around my house with friends

usually sometimes never

Partying with friends and visiting with friends

usually sometimes never

97

10.

11.

12.

13.

14.

15.

Talking to friends on the phone

usually sometimes never

Watching television or listening to music at home

usually sometimes never
Helping around the house (watching your younger brothers or
sisters, doing yard work or other chores)

usually sometimes never
Playing varsity, junior varsity sports, orjunlor high sports organized
by school

usually sometimes never
Participating In after-school sports or recreational activities
organized by your school

usually sometimes never
Playing sports (e.g. local league, church league, recreation center)
that is supervised by adults or coaches

usually sometimes never
Playing sports In the neighborhood, snowmobiling, jet-skiing, or
four wheeling without adult supervision

usually sometimes never

Playing computer or video games at home

usually sometimes never

98

16.

17.

18.

19.

20.

21.

22.

23.

24.

Playing a musical instrument, taking dance lessons, or
drawing/painting

usually sometimes never
Going to malls/shopping centers (going to movies, playing video
games, walking around, shopping)

usually sometimes never

Going to local parks/beaches with friends

usually sometimes never

Doing homework or class projects at home

usually sometimes never

Doing activities with a church group

usually sometimes never

Attending traditional (Native American) ceremonies

usually sometimes never

Doing crafts or hobbies (chess, model building, or collecting stamps)

usually sometimes never
Working at a part time job
usually sometimes never

Doing volunteer work

usually sometimes never

99

25. Babysitting or doing yard work for neighbors

usually sometimes never

100

Appendix B

Leisure Boredom Scale

101

Lelsure Boredom Scale (lso-Ahola and Weissinger, 1990)

Instructions: The statements listed below are intended to ﬁnd out how you feel
about your leisure time. Just respond to each statement as it applies to your
leisure time. By leisure time, we mean free time you have after school and/or on

the weekends.

Please respond to each of the following 16 statements. You do this by circling the
number that shows how much you agree or disagree with the statement. For
example, by circling a 5, you are showing that you Strongly Agree with the
statement as it applies to your leisure time. Please use the scale below to

respond to each statement

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

1. For me, leisure time just drags on and on.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

102

During my leisure time, I become highly involved in what I do.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

Lelsure time Is boring.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

If I could retire now with a comfortable income, I would have plenty
of exciting things to do for the rest of my life.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

103

During my leisure time, I feel like I’m just “spinning my wheels.”

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

In my leisure time, I usually don’t like what I’m doing, but I don’t
know what else to do.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

104

Lelsure time gets me aroused and going.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

Leisure experiences are an Important part of my quality of life.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

I am excited about leisure time.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

105

 

10.

11.

12.

In my leisure time, I want to do something, but I don’t know what to
do.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

I waste too much of my leisure time sleeping.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

I like to try new leisure activities that I have never tried before.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

106

13.

14.

15.

I am very active during my leisure time.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

Lelsure time activities do not excite me.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

I do not have many leisure skills.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

107

16.

During my leisure time, I almost always have something to do.

1 = Strongly Disagree

2 = Disagree
3 = Neutral
4 = Agree

5 = Strongly Agree

108

Appendix C

Indicators of Risk Scale

109

Indicators of Risk Scale

Please check yes or no to the following questions:

1.

Have you belonged to gang in the last year?

yes no
Have you carried a weapon (knife/gun) to school in the last
year?

yes no

Were you charged with a crime or went to court for a felony
charge in the last year?

yes no

Have you done “tagging” in the last year?

yes no

Did you stay out late without permission or left home
without your parents knowing in the last year?

yes no

Have you cussed out loud at a teacher or used bad
language to parents in the last year?

yes no

Have you smoked marijuana 1-2 times in the last 30 days?

yes no

110

10.

11.

12.

13.

14.

Have you been drunk (had 5 or more drinks on one
occasion) at least once in the last two months?

yes no

Have you averaged “D” or less at school in the last year?

yes no

Do you plan on attending college or university after high
school?

yes no

Have you engaged willingly in sexual activity in the last
year?

yes no

Would you consider yourself to currently be a healthy,
physically fit person?

yes no

Have you smoked more than one cigarette per day over the
past two weeks?

yes no

Have you done “huffing” 1-2 times in the last two weeks?

yes no

111

Appendix D

Demographic Questionnaire

112

Dear student,

Respond to the following statements and requests for
information as honestly and accurately as you can. This
information will remain conﬁdential; in other words, your name
will never be associated with the information you provide. The
researcher is not interested in your individual responses, but
rather the responses of all students when added together. Your
information is extremely valuable, and your cooperation is

greatly appreciated.
Your Age: Current Grade in School:
Gender: (Check one) Male Female

Are You A Registered Member of An Indian Tribe/Community?
(check one)
Yes No

If yes, please indicate which tribe you are a member of:

 

113

Appendix E

Parent/Guardian Informed Consent Form

114

Research Study: Parent/Guardian Informed Consent Form

Participation of your son or daughter in the study explained below is being
sought. All students at the Sault Ste. Marie Alternative High School will be given
the opportunity to participate in this study. The participation of your son or
daughter is very important to the overall success of this project. All students who
participate in the study will be entered into a drawing for gift certiﬁcates from a
local clothing store. Please review the following information. You indicate your
consent by signing below and sending this form back to school with your son or
daughter.

Project Title: Examining the Relationship Between Leisure Lifestyle
And Indicators of Risk of Youth and the Mediating Effects of
Gender and Race on this Relationship.

The purpose of this study is to examine the free time activity patterns of youth
and the impact of these free time activity patterns on indicators of risk. The
inﬂuence of race/culture and gender on the relationship between free time activity
patterns and indicators of risk will also be examined. The results of this study will
be helpful in understanding which free time activity choices seem to lead to risk
and those which seem to lead to indications of success. The results of this study
will beneﬁt all students by identifying interventions and programming that provide
them with the most beneﬁt.

Procedures

Three separate surveys will be completed by all high school students at the Sault
Ste. Marie Alternative High School for whom consent has been received. The
surveys will be administered in the classroom with the classroom teachers .
present. The time required for each student to complete the surveys is one hour.
The researcher will be going into the school for two or three days to ensure that
all consenting students are given the opportunity to participate in the study.

Voluntary/Conﬁdential Participation

The participation of all students in this study is completely voluntary. The
decision not to participate, or to withdraw from the study at any time, will involve
no penalty or loss of beneﬁts to which the student is otherwise entitled. All
information obtained from the students will be treated with strict conﬁdence on
the part of the investigator. Students will not be identiﬁed in any report of
research ﬁndings. The privacy of all students will be protected to the
maximum extent allowable by law.

115

Questions/Concerns
If you have any questions or concerns regarding participation of your
son/daughter in this project, please contact the following:

David E. Wright, Chair

University Committee on Research Involving Human Subjects
Michigan State University

(517) 355-2180

By signing this consent form, you indicate an understanding of the information
presented above and grant permission for the student identiﬁed below to
participate in this study.

Name of Student (Please print):

 

 

 

Signature of Parent/Guardian Date

Thank You,

Steve Yanni, Ph.D. Candidate
604 Johnston St.

Sault Ste. Marie, MI
632-8659

116

Appendix F

Subject Informed Consent Form

117

Research Study: Subject Informed Consent Form

Your participation in the study explained below is being sought. All students at
the Sault Ste. Marie Alternative High School will be given the opportunity to
participate in this study. All students who participate in the study will be entered
into a drawing for gift certiﬁcates from a local clothing store. Your participation is
very important to the overall success of this project. Please review the following
information. You indicate your consent by signing below.

Project Title: Examining the Relationship Between Leisure Lifestyle
And Indicators of Risk of Youth and the Mediating Effects of
Gender and Race on this Relationship.

The purpose of this study is to examine the free time activity patterns of youth
and the impact of these free time activity patterns on indicators of risk. The
inﬂuence of race/culture and gender on the relationship between free time activity
patterns and indicators of risk will also be examined. The results of this study will
be helpful in understanding which free time activity choices seem to lead to risk
and those which seem to lead to indications of success. The results of this study
will beneﬁt all students by identifying interventions and programming that provide
them with the most beneﬁt.

Procedures

Three separate surveys will be completed by all high school students at the Sault
Ste. Marie Alternative High School for whom consent has been received. The
surveys will be administered in the classroom with the classroom teachers
present. The time required for each student to complete the surveys is one hour.
The researcher will be going into the school for two or three days to ensure that
all consenting students are given the opportunity to participate in the study.

Voluntary/Confidential Participation

The participation of all students in this study is completely voluntary. The
decision not to participate, or to withdraw from the study at any time, will involve
no penalty or loss of beneﬁts to which the student is othenrvise entitled. All
information obtained from the students will be treated with strict conﬁdence on
the part of the investigator. Students will not be identiﬁed in any report of
research ﬁndings. The privacy of all students will be protected to the
maximum extent allowable bylaw.

118

Questions/Concerns
If you have any questions or concerns regarding participation of your
son/daughter in this project, please contact the following:

David E. Wright, Chair

University Committee on Research Involving Human Subjects
Michigan State University

(517) 355-2180

By signing this consent form, you indicate an understanding of the information
presented above and grant permission for the student identiﬁed below to
participate in this study.

Name of Student (Please print):

 

 

 

Signature of Parent/Guardian Date

Thank You,

Steve Yanni, Ph.D. Candidate
604 Johnston St.

Sault Ste. Marie, Ml
632-8659

119

Appendix G

Request to Bay Mills Indian Community Executive Council

120

5-1 8-00

To: Bay Mills Indian Community Executive Council
From: Steve Yanni
Re: Research Project

 

As many of you are aware I am closing in on the ﬁnal stages of my doctoral dissertation.
The topic of my research is examining the relationship between leisure lifestyle and
indicators of risk amongst youth and the impact of race and gender on this relationship. I

I am most interested in the results of this research speciﬁc to our own youth. The
information gained could be very helpful in identifying interventions that seem to be
effective and also in supporting grant applications from our Department of Recreation
and Health Promotion.

My initial plan was to use the Brimley and Sault High Schools as the forum for the data
collection; the data collection involves the administration of three questionnaires that
require about an hour to complete. The schools, with the exception of the Alternative
School in the Sault have been less than accommodating. Rather than ﬁght with the
schools and strain relations I thought that I would administer the surveys within the
community. Speciﬁcally I would administer the surveys to all Bay Mills Tribal members
who are currently enrolled in high school for whom consent has been provided.
Research protocol requires parental/guardian consent for all research participants 17
years of age and younger; each participant regardless of age must also provide their
own consent to participate. My plans for administering the surveys would be to mail all of
our high school students (tribal only) the consent forms and a cover letter inviting them
to come to the Waishkey Center on a predetermined date to complete the surveys. A
pizza dinner would also be provided after the surveys had been completed. It may take
some follow-up phone calls and subsequent meeting times to collect the data from as
many of our young people as possible.

 

I am also administering the surveys at the Alternative School in the Sault.

The research project has been approved by the University Committee on Research
Involving Human Subjects at Michigan State University as well as my dissertation
committee from MSU. l have included a copy of the questionnaires and the informed
consent forms to be used with this project.

Would the Executive Council be willing to approve of this research involving Tribal
members who are currently enrolled in high school?

Respectfully,

Steve Yanni

121

Appendix H

Tribal Council Approval of Research

122

BAY MILLS EXECUTIVE COUNCIL
Meeting Minutes
May 22, 2000

PRESENT: Jeff Parker, President, L. John Lufkins, Vice-President, Terry
Carrick, Secretary, Allyn Cameron, Treasurer, Mickey Parish, Councilperson

Meeting called to order at 1:40 pm.
AGENDA The council reviewed the agenda and made additions.

INTRODUCTION - Shawn Kintigh introduced Becky Brown who will be her
replacement for Mental Health Intake Worker for the tribe.

 

APPROVALQF M_AY 81h ME_ETIN§ MINUTES h

Mickey Parish motioned to approve the May 8th meeting minutes, seconded by
Terry Carrick. Motion carried 4 for 0 opposed 1 abstaining.

EMINISTRATIVE REPORTS
Mark Solberg - General Manacg

Mark commented that the reports he receives from Greg are very useful. He
reported on the slot revenue for April 2000, including allocating food costs,
promotions, etc. He said that revenue has declined which is attributed to 37%
loss of Canadian customers. He updated the council on the opening, the stafﬁng,
and the shuttle service.

NEW BUSINESS
Request from Steve Yanni for a Research Project

Jeff said that Steve had talked to him about the possibility of doing a research
project for his dissertation that would involve tribal kids. He tried to work with
Brimley Schools but could not get access to talk to any of the students. He has
questionnaires that will take approximately an hour to complete and he would like
to reward the kids that participate in the surveys with a gift not to exceed $50.00.
It will be for approximately 56 students. Jeff said this information would be
available for funding purposes in the future. Allyn Cameron motioned to support
Steve Yanni's dissertation efforts and also to support it ﬁnancially. Motion carried
4 for 0 opposed I abstaining.

123

Appendix I

Bay Mills Potential Subject Mailing Cover Letter

124

6-6-00

To: All youth of the Bay Mills Indian Community born between 1981 and 1987
From: Steve Yanni, Director - Department of Recreation and Health Promotion
Re: Research Project

 

I am asking for your assistance in providing some information for a research
project I am working on. The Bay Mills executive council has approved my
gathering information from the youth of the community.

The purpose of the study is to examine the relationship between leisure lifestyle
and indicators of risk in youth. In other words, is there a link between what you
do during your free time and indicators of risk that you may or may not be
involved with. The results of this study will be very helpful for us in planning
activities for you, and all of our youth that seem to be beneﬁcial for everyone in
the long run.

The way you can be of assistance is to ﬁll out a survey that takes about 40
minutes to complete. All youth will be completing the same survey. The results of
the survey are managed to ensure the highest level of conﬁdentiality; your name
is not requested and will never be associated with your answers to the survey
questions. Participation in this study is completely voluntary.

Out of appreciation for your participation in this study, the executive council has
approved an incentive of $50.00 to each young person who completes the
survey. I have a list from tribal enrollment of all youth born between 1981 and
1987.

WHAT TO DO TO PARTICIPATE IN THE STUDY:

1. If you are 17 years of age or younger you must have your parent/guardian
read and complete the enclosed informed consent form.

2. Come to the Bay Mills Waishkey Center (Gym) on 9113 of the following dates
(with the parental/guardian consent form signed if under 18). If you are under
3 and you do not have the consent form completed and with you, you will not
be allowed to participate in the study. Please be on time for the session you
choose.

 

Date 1: Monday, June 12th at 5:00 PM
Date 2: Saturday, June 17th at 10:00 AM

125

_E:ach youth attends one session only. You may choose which
session you will attend;

If you or your parents/guardians have any questions or concerns please call
me at 248-3241 ext. 3115.
Thank You,

Steve Yanni

126

Appendix J

AL TAS Score Form

127

ALTAS Score Sheet

Subject #

K_e¥
usually = 3; sometimes = 2;

Unsupervised Socialization with Friends
#5
#6
#7
#17 __
#18 _

Total:

Organized Leisure Activities
#3 _

#4
#16
#20
#21
#23
#24
#25

Total:

Organized Sport Activities
#11 _
#12 _
#13 _

Total:

Activities at Home
#8 _

#9 __

#10 __

#19 _

Total:

128

never = 1

Self-Directed Leisure Activities
#1 _

#2 _

#14 __

#15 _

#22 _

Total:

Appendix K

Leisure Boredom Scale Score Form

129

Leisure Boredom Scale Score Sheet

Subject #

1. 1 2 3 4 5
2. 5 4 3 2 1
3 1 2 3 4 5
4 5 4 3 2 1
5 1 2 3 4 5
6 1 2 3 4 5
7 5 4 3 2 1
8. 5 4 3 2 1
9 5 4 3 2 1
10. 1 2 3 4 5
11. 1 2 3 4 5
12. 5 4 3 2 1
13. 5 4 3 2 1
14. 1 2 3 4 5
15. 1 2 3 4 5
16. 5 4 3 2 1

Total Score:

130

Appendix L

Risk Behavior Scale Score Form

131

Indicators of Risk Score Sheet

 

Subject #
13 N2
1. Gang 2 1
2. Weapon 2 1
3. Crime/Court 2 1
4. Tagging 2 1
5. Out Late Without 2 1
Permission

6. Bad Language 2 1
7. Marijuana 2 1
8. Drunk 2 1
9. D or Less in School 2 1
10. College Plans 1 2
1 1. Sexual Activity 2 1
12. Healthy/Fit 1 2
13. Cigarettes 2 1
14. Hufﬁng 2 1

Total:

132

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