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dissertation entitled

RELATIONSHIP AMONG MOTOR SKILL DEVELOPMENT,
AEROBIC CAPACITY, BODY COMPOSITION, AND
PERCEIVED COMPETENCE OF FOURTH GRADE SCHOOL
CHILDREN

presented by

Sheila Kathleen Kelly

has been accepted towards fulﬁllment
of the requirements for the

PhD. degree in Kinesiologi

 

 

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RELATIONSHIP AMONG MOTOR SKILL DEVELOPMENT, AEROBIC
CAPACITY, BODY COMPOSITION, AND PERCEIVED COMPETENCE
OF FOURTH GRADE SCHOOL CHILDREN
By

Sheila Kathleen Kelly

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Kinesiology

2010

ABSTRACT
RELATIONSHIP AMONG MOTOR SKILL DEVELOPMENT, AEROBIC
CAPACITY, BODY COMPOSITION, AND PERCEIVED COMPETENCE
OF FOURTH GRADE SCHOOL CHILDREN
By
Sheila Kathleen Kelly
A few important potential barriers to participation in physical activity that

have been identiﬁed are the lack of motor skills, low ﬁtness levels, and low
perceived competence of Children and adolescents (Hands, Parker, & Larkin,
2002). If these barriers are reduced and children and adolescents have positive
physical activity experiences while young, youth may be more likely to not only
become physically active, but maintain physical activity levels throughout the
lifespan (Dennison, Straus, Mellits, & Chamey, 1988; Taylor, Blair, Cummings,
Wun, & Malina, 1999). There is limited evidence examining the interrelationships
among these three variables. Therefore, the purpose of this study was to
examine the relationship among fundamental motor skill development (of both
Iocomotor and object-control skills), health-related ﬁtness level (measured by
aerobic capacity and body composition), and perceived competence (measured
by subscaleS/domains) of fourth grade students. Participants in this study were
137 fourth grade children (67 males and 70 females) from three schools. Using
two assessments from the FITNESSGRAM (Cooper Institute for Aerobic

Research, 2007), the participants took part in the PACER to measure their

aerobic capacity, and their height and weight measurements were taken to

determine their body mass index (BMI) as the measure of body composition.
The Test of Gross Motor Development-2 (TGMD-2; Ulrich, 2000) was
administered to assess the Iocomotor and object-control fundamental motor Skill
performance of the participants on 12 skills. Participants’ perceived competence
in Six domains was calculated from scores on the Self-Perception Proﬁle for
Children (SPPC; Harter, 1985). According to FITNESSGRAM guidelines, 29.5%
of participants fell below the standards for aerobic capacity and 29% were
considered at an unhealthy weight. Mean TGMD-2 and SPPC scores of the
participants were high. Stepwise regression results indicated the most Signiﬁcant
predictor variables in various tests were aerobic capacity, object-control skill
performance, and the SPPC academic, athletic, and physical appearance
domains. Two revised ﬁgures (for boys and girls) of the model proposed by
Stodden et al. (2008) are introduced for fourth grade students to include the
results from this study and potential relationships to physical activity. Although
more research is needed for the relationship among these three variables, these
ﬁndings indicate that children and adolescents should maintain a healthy BMI,
increase their aerobic capacity, and engage in fundamental motor skill
development (especially object-control Skill development) at a young age.
Parents, teachers, and coaches Should encourage this behavior as well as
focusing on enhancing the Children’s and adolescents’ competence in different

areas (particularly academic and athletic).

Copyright by
SHEILA KELLY
2010

ACKNOWLEDGEMENTS

It is my pleasure to thank those who made this dissertation possible. I
would not have been able to complete this dissertation without the guidance of
my committee members and love and support from my family, boyfriend, and
good friends. Without you all, this experience would not have been possible.

I would like to express my sincere appreciation to my advisor, Dr. Crystal
Branta, for her excellent guidance and support throughout my entire doctoral
program, especially during the dissertation process. I would also like to thank
Dr. Joe Eisenmann, Dr. Marty Ewing, and Dr. Kathy Stansbury for all their help,
guidance, and feedback throughout this process. I am truly lucky and fortunate
to have worked with such a talented and knowledgeable committee who
generously gave their time and expertise to better my work. They all forced me
to grow as a student, researcher, writer, and thinker, and for that I am grateful.

A special thank you goes to my father, Jim Kelly, and in loving memory of
my mother, Julie Kelly. They instilled in me a value of physical activity and a
healthy lifestyle throughout my youth that I keep with me today, as well as the
desire to pass my knowledge onto others. Furthermore, I am extremely
appreciative of their encouragement to follow my dreams, the opportunities they
gave me, and my father’s everlasting support especially throughout the pursuit of
my doctoral degree. Maybe now he will stop telling people his daughter teaches

bowling at MSU! To my brilliant Grandpie Kelly, who had to drop out of school at

a young age to work to support his family, thank you for your strong work ethic
which was passed down through my dad and made me even more appreciative
of my educational opportunities and the chance to ﬁnd my true passion. As Nana
Kelly predicted when l was a little girl, “She’s going to be a teacher somedayl”...
She was right.

To my brothers Mikey and Timmy, thank you for always being there with
“big brother” advice to keep me motivated and for always believing in me. To
Hector, thank you for being my “calm within the storm” during the stressful times
while I was writing my dissertation. Your understanding, patience,

encouragement, and inspiration this past year helped more than you know.

vi

TABLE OF CONTENTS

LIST OF TABLES ........................................................................... ix
LIST OF FIGURES ......................................................................... x
CHAPTER 1
INTRODUCTION ........................................................................... 1
Motor Skill Development of Children ......................................... 3
Health-Related Fitness Levels of Children ................................. 5
Perceived Competence of Children .......................................... 6
Justiﬁcation for the Study ....................................................... 7
Pilot Study ........................................................................... 9
Purpose .............................................................................. 1 1
Hypotheses ......................................................................... 1 1
Deﬁnition of Terms ................................................................ 13
CHAPTER 2
REVIEW OF LITERATURE .............................................................. 16
Physical Activity Levels in Children and Adolescents .................... 16
Age—related trends during childhood and adolescence ......... 16
Factors that inﬂuence physical activity levels in children
and adolescents ........................................................... 18
Beneﬁts of physical activity ............................................. 19
Pediatric Obesity .................................................................. 21
Body mass index (BMI) as a body composition measurement
to determine overweight/obesity ...................................... 21
Prevalence of overweight and obesity in children and
adolescents ................................................................ 23
Consequences of childhood obesity ................................. 23
Gender & Race/Ethnicity differences in obesity and physical
activity ....................................................................... 26
Health-related Physical Fitness Levels of Children and
Adolescents ......................................................................... 30
Cardiovascular ﬁtness level and assessment ..................... 32
Body composition ......................................................... 33
Muscular strength/endurance & ﬂexibility ﬁtness levels ......... 35
Motor Skill Development of Children ......................................... 35
Importance of motor skill development .............................. 35
Assessment of motor skill/motor performance .................... 38
Relationship between Fundamental Motor Skill Development!
Level and Fitness Level of Children .......................................... 4O

vii

Psychological Factors ............................................................ 41
Psychological assessment: Self-Perception Proﬁle for

Children (SPPC) .......................................................... 44
Psychological Aspects related to Motor Skill Development ............. 46
Summary of Review of Literature ............................................. 48
Purpose of Study .................................................................. 49

CHAPTER 3

METHOD ..................................................................................... 50
Participants ......................................................................... 50
Measures ............................................................................ 51

FTG PACER and BMI ................................................... 51

Test of Gross-Motor Development-2 (TGMD—Z) .................. 52

Self-Perception Proﬁle for Children (SPPC) ....................... 53
Procedures .......................................................................... 54

FTG PACER ............................................................... 57

BMI ........................................................................... 58

TGMD—2 ..................................................................... 59

SPPC ........................................................................ 60
Data Analysis ....................................................................... 61

CHAPTER 4
, RESULTS .................................................................................... 63
Descriptive Statistics ............................................ . ................ 63
Partial Correlations ............................................................... 70
Stepwise Regression ............................................................. 75
CHAPTER 5
DISCUSSION ................................................................................ 84
Strengths of the Study ............................................................ 94
Limitations ........................................................................... 95
Implications for Future Research .............................................. 99
Conclusion .......................................................................... 101
APPENDICES ............................................................................... 103
Letter to Parents ................................................................... 104
Parental Consent Form ........................................................... 107
Participant Assent Form ......................................................... 111
REFERENCES ............................................................................... 113

viii

LIST OF TABLES

TABLE 1
CDC Weight Status Category by BMI-for—age Percentiles of Children

and Adolescents ............................................................................ 22
TABLE 2

Physical Descriptive Characteristics of the Sample ............................... 64
TABLE 3

Test of Gross Motor Development-2 Descriptive Characteristics of the
Sample ........................................................................................ 66
TABLE 4

SPPC Domains & V02 Max Descriptive Characteristics of the Sample ...... 69
TABLE 5

Partial Correlation Results Controlling for Age with All Subjects ............... 72
TABLE 6

Partial Correlation Results Controlling for Age — Boys ............................ 73
TABLE 7

Partial Correlation Results Controlling for Age - Girls ............................ 74
TABLE 8

Stepwise Regression Results — All Participants .................................... 80
TABLE 9

Stepwise Regression Results - Boys ................................................. 82
TABLE 10

Stepwise Regression Results - Girls .................................................. 83

LIST OF FIGURES

FIGURE 1
Developmental Mechanisms Inﬂuencing Physical Activity Trajectories
of Children (Stodden et al., 2008) ...................................................... 4

FIGURE 2
Revised Stodden et al. (2008) Model for Fourth Grade Boys ................... 93

FIGURE 3
Revised Stodden et al. (2008) Model for Fourth Grade Boys ................... 93

CHAPTER ONE
Introduction

Inadequate physical activity in children is a health-related concern as it is
one of the main contributors to childhood obesity (Fox, 2004; Goran, Reynolds, &
Lindquist, 1999; Hills, King, & Armstrong, 2007; Reilly & McDowell, 2003). The
most recent estimates indicate that 35.5% of children ages 6 to 11 are
overweight and 19.6% are considered obese (Ogden, Carroll, Curtin, Lamb, &
Flegal, 2010). These rates have nearly tripled in the past few decades (Ogden,
Carroll, Curtin, Lamb, & Flegal, 2010). Although the increase has been minimal
in the last few years, there is still a need to focus on reducing these rates given
the relatively high prevalence rates and adverse consequences. Given the
importance of physical activity in reducing obesity (and for general health,
development, and well-being of the Child), examining the determinants to.
participation in physical activity is an important area of research. A few important
potential barriers that have been identiﬁed are the lack of motor skills, low health-
related ﬁtness levels, and low perceived competence of children and adolescents
(Hands, Parker, & Larkin, 2002). If these barriers are reduced and Children and
adolescents have positive physical activity experiences while young, physically
active youth may be more likely to maintain physical activity levels throughout the
lifespan (Dennison, Straus, Mellits, & Chamey, 1988; Taylor, Blair, Cummings,

Wun, & Malina, 1999).

There are numerous beneﬁts of an active lifestyle (Surgeon General
Report, 1996; Strong et al., 2005). In children, regular physical activity and
appropriate nutrition are necessary for normal growth and development of
physical ﬁtness, which includes body composition (Strong et al., 2005; Thomas &
Thomas, 2008). Lack of activity is a concern because people who are physically
inactive may incur health problems such as becoming overweight or obese which
increase one’s risk of many diseases and health conditions (CDC, 2009).
Childhood obesity is associated with a range of physical, social, and
psychological consequences, including poor self-esteem, depression, and social
isolation (Daniels, Jacobson, McCrindle, Eckel, & Sanner, 2009; Jackson,
Mannix, Faga, & McDonald, 2005).

One major reason for encouraging children to be physically active at a
younger age is the implications for future physical activity involvement and health
beneﬁts. Youth who are inactive as children and adolescents are more likely to
grow up to be sedentary adults than youth who are active (Corbin, Pangrazi, &
Le Masurier, 2004). However, the magnitude of these ﬁndings is weak
(Zimmermann—Sloutskis, Wanner, Zimmerman, & Martin, 2010), and additional
evidence has identiﬁed a genetic component linking physically active adults to
more physically active children (Teran-Garcia, Rankinen, & Bouchard, 2008).
Lack of physical activity may contribute to childhood obesity, which is the

foremost predictor of obesity in adolescence (Salbe et al., 2000). In turn, obese

children have a higher tendency to become overweight adults (Saxena,
Borzekowski, & Rickert, 2002).

Many factors explain a child’s participation in physical activity, which may
inﬂuence the child’s ability to achieve and maintain a healthy weight. One way to
approach understanding the determinants of physical activity is by examining the
model proposed by Stodden and colleagues (2008; Figure 1). The four main
components (motor skill competence, perceived motor competence, health-
related ﬁtness, and physical activity) in the inner square of the model are all
interrelated and lead to the risk of obesity of children.

Motor Skill Development of Children

Motor skill competence in this model refers to proﬁciency in common
fundamental motor skills, which include both Iocomotor and object control skill
development (Stodden et al., 2008). From birth through childhood individuals
experience the development of human movement; and as they grow and mature
into adolescents, they continue to reﬁne and practice skills Ieamed at younger
ages depending on the activities they Choose. In general, younger children will
demonstrate less advanced movement pattems for fundamental motor skills than
older children, but there is variability in the skill level at each age (Thomas,
Thomas, & Williams, 2008). Clark and Metcalfe (2002) hypothesized a
“mountain of motor development” in which fundamental motor skills must ﬁrst be
Ieamed before individuals can progress into context-Speciﬁc skills or skillful

movements at higher levels of the mountain. Age was often used as a general

 

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marker of performance and development; however, age does not cause a child to
perform motor skills at a certain level and not all children at any given age will
demonstrate the same level of motor skill development (Thomas, Thomas, &
Williams, 2008). The Test of Gross Motor Development-2 (TGMD—2; Ulrich,
2000) was used in this study to identify the motor skill performance level of the
participants on a variety of Iocomotor and object-control skills. Stodden et al.
(2008) suggested that young children’s activity might drive their development of
motor Skill competence, and that the relationship between motor skill
competence and physical activity will strengthen over time. However, there are
other variables in this relationship to consider as well.
Health-Related Fitness Levels of Children

Stodden et al. (2008) identiﬁed health-related ﬁtness as a possible
mediator in the relationship between motor skill competence and physical
activity. Therefore, motor skill competence could inﬂuence health-related ﬁtness,
which may then inﬂuence physical activity, and vice versa. Although children
learn fundamental motor Skills in early childhood (2 to 5 years of age), it is not
until middle childhood that they demonstrate the intermediate to high levels of
motor Skill competence (Stodden et al., 2008). Therefore, Stodden et al. (2008)
suggested that at this point the increased levels of motor skill development
should correspond with increased physical activity levels, greater health-related
ﬁtness, and higher performance scores. Based on a pilot study (discussed later

in this chapter), the two components of health-related ﬁtness which were

examined in this study are aerobic capacity and body mass index (as a measure
of body fatness).
Perceived Competence of Children

Perceived competence was considered an important factor to examine in
the fourth grade, when children are typically ages nine or ten. Children’s
judgments of their competence in the motor domain are not always accurate
compared to their actual motor competence (Stodden et al., 2008). However,
during mid—childhood, individuals have higher levels of cognitive development
and their perceived motor skill competence is more likely to reﬂect their actual
motor skill competence (Harter, 1999). At this point less-skilled Children will have
lower perceived competence and more-skilled children will have higher perceived
competence (Stodden et al., 2008). Stodden et al. (2008) only identiﬁed
perceived motor competence in their model, but there may be other areas of
perceived competence (e.g., academic, physical appearance, athletic, social
acceptance) that relate to the other variables previously discussed. Therefore,
the Self-Perception Proﬁle for Children (SPPC; Harter, 1985) was used in this
study to identify how self-perceptions in different domains of a child’s life
contribute to the model proposed by Stodden et al. (2008). The SPPC has been
broken into six subscales (or domains): (a) academic competence; (b)
social/peer acceptance; (c) athletic competence; (d) physical appearance; (e)
behavioral conduct; and (f) global self-worth. Although not all of the six

subscales are linked to the factors in the model (Stodden et al., 2008), all

questions from the SPPC were included in the perceived competence
assessment. In fourth grade, children may still ﬁnd it difﬁcult to differentiate
between the subdomains and determine in what areas they feel more competent.
In addition, the subscales are highly correlated, and the entire SPPC does not
take much longer to complete than if only selected subscales were included in
the study. Therefore, all subscales were kept in the SPPC to examine not only
the factors predicted to be related to the other variables in the model, but also
those factors that are not apparent in the current literature for exploratory
reasons.
Justiﬁcation for the Study

Past studies have examined the associations between health-related
_ ﬁtness levels and motor Skill development (Hume et al., 2008; Okely, Booth, &
Chey, 2004; Okely, Booth, & Patterson, 2001 b), health-related ﬁtness levels and
psychological factors (Davison & Birch, 2001; Strauss, 2000), and motor skill
development and psychological factors (Okely, Booth, & Chey, 2004; Bunker,
1991; Ulrich, 1987). However, to my knowledge no published studies have
examined the interrelationships among these three variables. Although the
levels of competence of ﬁtness and motor skills have been examined, an
individual’s perceived competence may be different from his or her actual
competence levels. If the perceived competence levels are accurate with actual
levels of competence, whether the competence is high or low may ultimately

inﬂuence physical activity levels. For example, research has shown that children

with higher perceived competence and actual competence levels are more likely
to have higher physical activity levels than children with lower perceived
competence (Barnett, Morgan, van Beurden, & Beard, 2008; Bois, Sarrazin,
Bmstad, Trouilloud, & Cury, 2005). With the lack of physical activity playing a
large role in the current childhood obesity epidemic, the potential factors and
psychological repercussions that inadequate physical activity may cause must be
identiﬁed.

In fourth grade, most children are ages 9 to 11. Most basic movement
patterns are established from ages 2 to 10 (Bunker, 1991 ). Therefore,
fundamental motor skills have been Ieamed by children in fourth grade, but the
children have not yet reached their peak proﬁciency for motor skill development
of all the fundamental Iocomotor and object—control skills. The majority of
children have also not begun puberty, which causes dynamic growth and
development that would inﬂuence performance on ﬁtness tests, motor skill
assessment, and results on psychological batteries. In addition, due to cognitive
development increases, the perceived competence of children is more accurate
compared to their actual competence (Stodden et al., 2008). Overall, this is a
crucial time to instill a healthy lifestyle in the children’s lives, it not before,
because overweight and obesity in youth has been shown to start as early as

infancy (Ogden et al., 2010).

Pilot Study

Recently, a pilot study was conducted to examine the relationship among
motor Skill development, health-related ﬁtness, and perceived competence.
Speciﬁcally, the purpose of the pilot study was to address the gaps in the
literature (described in the justiﬁcation for the current study) and investigate the
relationship between stage of motor skill development and health-related ﬁtness
in children. The role of perceived competence across the six subscales (i.e.,
academic competence, social acceptance, athletic competence, physical
appearance, behavioral conduct, and global self-worth) was also addressed, and
the overall relationship between motor skill development, health-related ﬁtness,
and perceived competence was to be identiﬁed. Speciﬁc questions were asked
including, what is the relationship between motor skill level and ﬁtness? What is
the relationship between motor skill levels and perceived competence? What is
the relationship between ﬁtness and perceived competence? Does a gender
difference exist among the relationships of motor skill development, health-
related ﬁtness, and perceived competence? What is the relationship among
motor skill level, ﬁtness, and perceived competence? Participants included 147
students (63 males, 84 females).

Results showed that scores from the TGMD-2 and SPPC were relatively
high, and scores from the FITNESSGRAM/ACTIVITYGRAM (hereafter referred
to as FTG) covered a broad range based on the skill performed. Overall,

participants who scored higher on motor skills also had higher levels of physical

ﬁtness and higher perceived competence. Participants who scored highest on
perceived competence subscales scored highest on the FTG tests, compared to
those participants in the moderate and low perceived competence groups.
Fundamental motor skills scores and ﬁtness levels were also higher for those
participants with lower BMls compared to participants with higher BMIS. Males
had higher scores than females on aerobic capacity measured by the PACER
(Progressive Aerobic Cardiovascular Endurance Run), object-control skills on the
TGMD-2, and in three subscales on the SPPC (i.e., athletic competence, global
self-worth competence, and peer acceptance competence). Females scored
higher than males on the SPPC behavioral competence subscale, Iocomotor
skills on the TGMD-2, and on three FTG tests (i.e., left leg sit-and-reach, trunk
lift, and curl up). i

This study was beneﬁcial and showed feasibility as a starting point to the
current proposed study, as it allowed for testing of the TGMD-2 and Harter’s
SPPC in a fourth grade sample. Both measurements were feasible in the school
setting, and issues that arose in the data collection were addressed in the
methodology of the current study. The FTG is already a commonly used test
battery in fourth grade. In the pilot study, FTG scores for each participant were
retrieved from the physical education teacher, which was a limitation since the
.testing had been done that year but not at the time of the TGMD-2 and Harter’s
SPPC collection. Therefore, all data collection in the current study occurred

within six weeks to control for changes that could occur throughout a longer

10

period of time. The pilot study results also revealed a subset of signiﬁcant
variables within the FTG, and therefore, only aerobic capacity (PACER) and body
composition (BMI) were included as ﬁtness components in the current study,
rather than all tests included in the FTG.
Purpose

The purpose of this study was to examine the relationship among
fundamental motor skill development (of both Iocomotor and object-control Skills),
health-related ﬁtness level (measured by aerobic capacity and body
composition), and perceived competence (measured by subscales/domains) of
fourth grade students. In addition, any differences between males and females
were addressed. Although the races/ethnicities of the individual participants
were not attainable, general race/ethnicity information was collected from the
schools to relate to the variable for exploratory purposes.
Hypotheses

The following hypotheses were developed for the study:

1. a. BMI, aerobic capacity, Iocomotor and object-control skill
performance of participants will account for a signiﬁcant percentage of
the variance in athletic and physical appearance perceived
competence.

b. BMI, aerobic capacity, Iocomotor and object-control skill

performance of participants will not account for a signiﬁcant

11

percentage of variance in the academic competence, peer acceptance,
behavioral conduct, and global self-worth.

2. a. BMI and Iocomotor skill performance of participants will account for
a signiﬁcant percentage of the variance in aerobic capacity.

b. Object-control skill performance of participants will not account for a
signiﬁcant percentage of the variance in aerobic capacity.

3. a. Aerobic capacity, Iocomotor skill performance, object-control skill
performance, and the athletic and physical appearance perceived
competence of participants will account for a signiﬁcant percentage of
the variance in body mass index.

b. Object-control skill performance and the academic competence,
peer acceptance, behavioral conduct, and global self-worth of
participants will not account for a signiﬁcant percentage of the variance
in body mass index.

4. a. BMI, aerobic capacity, and the athletic and physical appearance
perceived competence of participants will account for a signiﬁcant
percentage of locomotor skill performance.

b. The academic competence, peer acceptance, behavioral conduct,
and global self-worth of participants will not account for a signiﬁcant
percentage of Iocomotor skill performance.

5. a. BMI, aerobic capacity, and the athletic and physical appearance

12

perceived competence of participants will account for a signiﬁcant
percentage of object-control skill performance.
b. The academic competence, peer acceptance, behavioral conduct,
and global self-worth of participants will not account for a signiﬁcant
percentage of object-control skill performance.

Deﬁnition of Terms

0 Meg: males and females ages 6 to 11. However, Malina (2004)
states the range of adolescence for girls is ages 8 to 19, and for boys
is ages 10 to 22 based on the onset of puberty to maturity. Therefore,
some children in the proposed study may be transitioning into
adolescence.

. FITIﬂESSGRAM/ACTIVITYGRAM Healthy Fitness _Z_one (HFg): the
range of ﬁtness scores associated with good health based on scientiﬁc
information (Welk 8 Meredith, 2008).

. FHLVESSGRAM/ACTIVITYGRAM “Needs Improvement” scores:
scores above or below the HFZ. Efforts are needed to bring the score
into the HFZ (Welk & Meredith, 2008).

. Ovenrveight: Body mass index (BMI) between the 85th and 95th age-
and sex-speciﬁc percentiles according to the CDC (2009). A child or
adolescent may also have an unhealthy body weight if his or her body

composition score is above the FTG HFZ, as determined using the

13

FTG cutoff points although the FTG does not distinguish between
overweight and obese.

M: BMI greater than or equal to the 95th age- and sex-speciﬁc
percentile according to the CDC (2009). A child or adolescent may
also have an unhealthy body weight if his or her body composition
score is above the FTG HFZ, as determined using the FTG cutoff
points although the FTG does not distinguish between ovenrveight and
obese.

Perceived Competence: individuals’ perceptions of their competencies
or abilities in speciﬁc domains (Harter, 1982). Unless a speciﬁc
“perceived competence” is explicitly stated (e.g., perceived motor
competence), “perceived competence” is a general term including
different domains of perceived competence.

Physical Activity: any body movement produced by the skeletal
muscles that results in a substantial increase over the resting energy
expenditure (Bouchard & Shephard, 1994).

m: a form of physical activity that involves competition (Bouchard &
Shephard, 1994).

Exercise: a form of leisure-time physical activity that is usually
performed on a repeated basis over an extended period of time with a
speciﬁc external objective such as the improvement of ﬁtness, physical

performance, or health (Bouchard & Shephard, 1994).

14

o ﬁeglth-RelatedL Fitness: a state characterized by (a) an ability to
perform daily activities with vigor and (b) demonstration of traits and
capacities that are associated with a low risk of premature
development of hypokinetic diseases and conditions (Bouchard &
Shephard, 1994). The speciﬁc components and examples of

subcomponents are discussed in the next chapter.

15

CHAPTER TWO
Review of Literature
This review of literature examines the current research about physical
activity, speciﬁcally relating to motor skill development, health-related ﬁtness, and
perceived competence. An overview of physical activity levels in children and
adolescents will ﬁrst be given. Although data on physical activity levels of youth
were not collected in this study, this overview will show the importance and
relationship of physical activity to the variables included in the study. In addition,
information related to gender and race/ethnicity has also been included as that
additional information about the children was collected. After the initial overview
of physical activity and pediatric obesity, each variable (i.e., health-related
ﬁtness, motor skill development, and psychological factors) has been introduced
independently, and then the research describing the relationships between the
factors have been discussed. Finally, the purpose of this study was stated.
Physical Activity Levels in Children and Adolescents
Age-related Trends during Childhood and Adolescence. Currently, physical
activity levels among children have been shown to be moderate to low in relation
to the recommended activity levels for children. Strong et al. (2005)
recommended that all school-age youth should participate daily in 60 minutes or
more of moderate to vigorous physical activity that is developmentally
appropriate, enjoyable, and involves a variety of activities. This amount of

activity could accrue throughout the day including physical activities during

16

physical education, recess, intramural sports, before and after school programs,
and personal exercise or play (Strong et al., 2005).

In general, children’s levels of physical activity are higher relative to adults’
physical activity levels, but these levels continue to decrease as children enter
adolescence. Bradley, McMurray, Harrell, and Deng (2000) found that the
activity levels of boys and girls decreased each year between third and tenth
grade. The Youth Risk Behavior Survey (YRBS) showed that only 45% of United
States youth ages 14 to 18 years (typically the ages adolescents are in high
school) participate in moderate-intensity physical activity for 30 minutes on more
than two days per week, and only 65% reported participating in vigorous-intensity
physical activity for 20 minutes on three or more days per week (Lohman, Going,
& Metcalfe, 2004). Due to this concem, one of the ten leading health indicators
for the Healthy People 2010 objectives is physical activity (Crespo, 2005).
Although many studies have reported physical activity levels of children and
adolescents, one major limitation in the comparisons between studies is the
measurement tool used. Methods to collect physical activity data range from
those used in larger scale studies, such as self-reporting physical activity, that
are not always reliable and valid, to more accurate measures, such as the use of
accelerometers or pedometers. Troiano et al. (2008) compared the different
measures of physical activity and found that in a nationally representative health
survey, the accelerometer data were qualitatively consistent with the self-report

data. Males were more active than females and the level of physical activity

17

decreased with age, especially during adolescence (Troiano et al., 2008).
However, differences arose when comparing adherence to recommended levels
of physical activity, in which the self-reported data showed participants claimed
higher levels of physical activity than the actual levels measured by
accelerometer data (Troiano et al., 2008). Therefore, more objective means of
measuring physical activity should be used whenever possible.

Factors that inﬂuence physical activity levels in children and adolescents.
Various factors contribute to the challenge of getting youth to engage in physical
activity, Sport, and exercise, and to explain the reasons why they participate or
Choose not to participate in physical activity. Weiss, Corbin, and Pangrazi (2000)
suggested three motives about why children and adolescents continue and
sustain exercise: (a) they want to develop and demonstrate physical
competence, such as athletic skills, physical ﬁtness, and physical appearance;
(b) they want to gain peer acceptance and support including friendships, peer
group acceptance, and approval, reinforcement, and encouragement by
signiﬁcant adults (parents, teachers, coaches); and (c) their positive experiences
related to physical activity are maximized and their negative experiences related
to physical activity are minimized because of the fun derived from participation.
Whatever a child’s reason for participating, it is beneﬁcial for him or her to get

involved at a young age, and for those experiences to be as positive as possible.

18

Beneﬁts of physical activity. Encouraging a healthy lifestyle and regular physical
activity can inﬂuence a person’s future behavior. Inactive youth are more likely to
be sedentary adults compared to youth who are active (Corbin, Pangrazi, & Le
Masurier, 2004); however, tracking of physical activity is difﬁcult to measure and
relationships are low to moderate. Studies of adolescents and adults have found
that those who had positive and enjoyable experiences with exercise while they
were younger were more likely to continue to exercise as they got older (Hands,
Parker, & Larkin, 2002). Therefore, children should be introduced to a healthy
lifestyle at a young age, and elementary school is a crucial time to begin teaching
the importance of physical activity, which can lead to both physical and
psychological beneﬁts.

Regular participation in physical activity has many health beneﬁts for
children and adolescents. Strong and colleagues (2005) were part of an expert
panel which reviewed the current research regarding the inﬂuence of physical
activity on health and behavioral outcomes in children and adolescents ages 6 to
18 years. They concluded that physical activity decreased adiposity among
overweight individuals, may have a positive effect on high-density lipoprotein
cholesterol IeVels (HDL-C), triglyceride levels and skeletal health, may reduce
high blood pressure among hypertensive adolescents, leads to greater upper
body muscular endurance, and shows better levels of aerobic ﬁtness and
improved mental health and academic performance in youth (Strong et al., 2005).

Nelson and Gordon-Larsen (2006) found that participation in a range of physical

19

activity-related behaviors, particularly those which included parental
sports/exercise involvement, was associated with positive adolescent risk proﬁles
including reduced participation in activities with health risk behaviors and
enhanced positive health outcomes such as higher self—esteem and academic
performance.

The type of physical activity youth participate in is important to their
participation and the beneﬁts that result from physical activity. Most
preadolescent Children ﬁnd periods of deﬁned exercise boring or punitive (Barlow
& Dietz, 1998). Non-structured moderate intensity exercise seems to contribute
to most of the disease- prevention goals and health-promoting beneﬁts (Sothem,
Loftin, Suskind, Udall, & Blecker, 1999). For young children, unstructured
outdoor play with friends is often vigorous, and children can also reach this high
level of physical activity by engaging in organized sports, as long as they are
active in the game and not sitting on the bench (Barlow & Dietz, 1998).
Therefore, children Should be encouraged to become involved in both informal
“play” activities and formal organized sports, and physical education should be
structured in a way that promotes this idea as well. Berkey and colleagues
(2003) found that Speciﬁcally for 10- to 15-year—old girls and overweight boys,
increasing total recreational physical activity over one year was associated with a
relative BMI decline. Although contributions about individual and group results in

the literature are beneﬁcial, Flegal and Troiano (2000) suggested seeking to

20

 

understand what factors are causing increases in BMI in the population as a
whole as opposed to comparing obese and non-obese individuals.

Pediatric Obesity
Body mass index (BMI) as a body composition measurement to determine
overweight/obesity. The body mass index (BMI) is a common measure
expressing the ratio of weight-to-height. It provides an indication of the
appropriateness of a child’s weight relative to height, but does not estimate the

percentage of fat (Cooper Institute for Aerobic Research, 2007). BMI is found by
computing the following formula: weight (kg) / height squared (m2), and it

changes from infancy through childhood to adolescence.
The Centers for Disease Control and Prevention (CDC, 2009) deﬁnes

overweight and obesity using age- and sex-speciﬁc BMI percentiles. An adult 4

who has a BMI between 25 and 29 kg/m2 is considered overweight, while an

adult who has a BMI of 30 kg/m2 or higher is considered obese. For children. and

adolescents, high BMI scores are also referred to as ovenrveight and obese.
Unlike BMI of adults, the distribution of BMI changes with age as weight and
height distributions change, and therefore, calculations for children and
adolescents take into account age-speciﬁc body fat ﬂuctuations and
developmental differences between boys and girls, as speciﬁc BMI-for-age
calculations are used (Barlow & the Expert Committee, 2007; Deﬁning and
Diagnosing Obesity, 2005). BMI-for-age is plotted on a growth chart which

determines in which percentile a child or adolescent’s score falls. According to a

21

report which included over 300 studies related to the assessment of child and
adolescent ovenrveight and obesity, the CDC 2000 growth charts provide the best
reference data available for the growth of US children (Krebs et al., 2007). The
CDC has charts for boys and girls from birth to age 20 for BMI, height, and
weight percentiles (CDC, 2009). Data on White, Black, and Mexican American
children and adolescents in the United States was used to develop the CDC BMI-
for-age growth charts (Guo, Wu, Chumlea, & Roche, 2002). The weight status
category as determined by the BMI-for-age percentiles for children and
adolescents is shown in Table 1.

Table 1

CDC weight status category by BMI-for-age percentiles of children and
adolescents ,

 

Weight Status Category Percentile Range

Underweight Less than the 5th percentile

Healthy Weight 5th percentile to less than the 85th percentile
Overweight 85th percentile to less than the 95th percentile
Obese Equal or greater than the 95th percentile

The CDC changed this terminology in 2005 from “at-risk for overweight” if the
BMI of the child/adolescent fell between the 85th and 95th percentile, and
“overweight” if the BMI of the Child/adolescent was equal or greater than the 95th
percentile. This Change resulted from the seriousness, urgency, and medical
nature of childhood obesity, and the need to take action on the issue (Krebs

et al., 2007).

22

Fm"

The American Academy of Pediatrics recommends that physicians
calculate and plot BMI-for-age once a year for all children and adolescents and
monitor Change to assess those that are ovenrveight or obese (Bariow & the
Expert Committee, 2007). A committee of pediatric obesity experts
recommended that children with a BMI greater than or equal to the 85th percentile
(with complications of obesity) or greater than or equal to the 95th percentile (with
or without complications of obesity), undergo evaluation and possible treatment
and that treatment begins early, involves the family, and includes permanent
changes (Barlow & the Expert Committee, 2007).

Prevalence of overweight and obesity in children and adolescents. The
childhood obesity rates have continued to rise over the years, and although the
percentages have not increased drastically over the past couple years, 19.6% of
children ages 6 to 11 and 18.1% of adolescents ages 12 to 19 were still
considered obese in 2006, and even more are overweight (Ogden, Carroll,
Curtin, Lamb, & Flegal, 2010). These levels are still a concern for the health and
well-being of children and adolescents.

Consequences of childhood obesity. A child or adolescent with a high BMI
percentile on the CDC BMI-for-age growth charts has a high risk of being
ovenrveight or obese at 35 years of age, and the risk increases with age (Guo,
Wu, Chumlea, & Roche, 2002). Dwyer and colleagues (1998) found that the
strongest predictor of overweight and overfatness among 11-year-olds was being

ovenrveight at age 9, and Salbe et al. (2002) found this result for 5- to 10-year-

23

olds as well. Although the risk of being ovenrveight or obese is less in children
than adults, research shows children diagnosed with obesity at seven years of
age will have an elevated relative risk, of about three, of becoming obese in
adulthood (Wickramasinghe et al., 2005). Therefore, the younger children can
confront any overweight/obese issues, the better off they will be in the future.

Physical inactivity may cause health problems and a child who is
ovenrveight or obese has an increased risk of many diseases and health
conditions. These consequences can be Classiﬁed into short-term or long-term.
Short-terrn consequences that occur in many obese youth include hypertension,
dyslipidemia (for example, high total cholesterol of high levels of triglycerides),
type 2 diabetes, sleep disturbances such as sleep apnea, respiratory problems,
and adverse effects on growth (CDC, 2009). Many overweight or obese children
also face immediate; psychological effects such as low self-esteem or negative
body image. Possible long-tenn factors, which do not occur until later in life,
include increased risk of coronary heart disease, stroke, gallbladder disease,
osteoarthritis, high cholesterol, orthopedic problems (e.g., bowed legs, stress
fractures, bone deformities), and some cancers such as endometrial, breast,
prostate, and colon (Black, 2004; CDC, 2009).

Childhood obesity has also been found to result in glucose abnormalities
leading to type 2 diabetes (Saxena, Borzekowski, & Rickert, 2002). Heavier
children are at greater risk for type 2 diabetes and for higher levels of fasting

glucose and insulin related to body fatness, physical inactivity, and low ﬁtness

24

levels (Lohman, Going, & Metcalfe, 2004). The insulin resistance caused by
obesity can cause what was once termed adult-onset diabetes. However, with
the dramatic increase in adult-onset diabetes in children, it has been renamed
Type 2 diabetes, and is one of the most publicized consequences of the
childhood obesity epidemic. The American Diabetes Association estimates that
one in three children born after the year 2000 will develop diabetes before
reaching age 50 (Glendening, 2005). One of the ways to combat Type 2
diabetes is by increasing physical activity to help lower overweight and obesity
levels.

Various studies have also examined the long and short-tenn psychosocial
consequences of childhood obesity. These consequences include negative self-
image, decreased self-esteem, eating disorders, and lower health-related quality
of life (Strauss, 2000; Davison & Birch, 2001). Obese Children may also face
rejection and discrimination from other children and adults, including teachers,
and tend to experience more failure and have poor interpersonal relationships
(Black, 2004). However, not all studies show psychosocial consequences due to
obesity. Swallen, Reither, Haas, and Meier (2005) investigated the health-
related quality of life of adolescents using the National Longitudinal Study of
Adolescent Health (a nationally representative sample of adolescents in grades 7
to 12) and found that although obesity in adolescence was linked to a poor
physical quality of life, the obese adolescents did not have poorer emotional,

school, or social functioning.

25

Gender & Race/Ethnicity differences in obesity and physical activity. Gender and
race/ethnicity may be factors that contribute to whether or not a child is
ovenrveight or obese. Certain ethnic groups may face unique sets of factors for
becoming ovenrveight or obese (Haas et al., 2003). In addition, the differences
in gender and race/ethnicity may also contribute to the physical activity levels or
certain barriers to physical activity of individuals.

Gender differences have been commonly studied in the childhood obesity
and physical activity literature. Various studies have reported more overweight
males than females (Celi et al., 2003; Dwyer, Allison, & Makin,1998, and Ogden,
Carroll, Curtin, Lamb, & Flegal, 2010). However, Celi et al. (2003) found that
although the overweight rates were different, obesity rates were similar between
males and females, and Pena Reyes et al. (2001) found that the prevalence of
obesity was greater in boys than girls.

According to the most recent CDC NHANES data (2003-2006) based on
the CDC sex-and-age speciﬁc body mass index (BMI) greater than or equal to
the 95th percentile indicating obesity, there is a difference in the percentages of
obese children 6— to 11-years-old based on race/ethnicity and gender. These
numbers are based on the children who had a BMI in the 95th percentile or higher
on the CDC growth Chart. For non-Hispanic White children, 11.9% of boys and
12.0% of girls were obese. The percentage for obese non-Hispanic Black
children equaled 17.6% of boys and 22.1% of girls. For Mexican American

children, 27.3% of boys and 19.6% of girls were obese. This number continues

26

to grow for most groups among adolescents ages 12 to 19. The following
percentages for adolescents also show the most recent CDC NHANES data
(2003—2006) according to the same standards to determine obesity. For non-
Hispanic White children, 17.3% of boys and 14.5% of girls were obese. The
percentage for obese non-Hispanic Black Children was 18.5% of boys and 27.7%
of girls. For Mexican American children, 22.1% of boys and 19.9% of girls were
obese.

In other smaller studies, varied results were found related to race/ethnicity
and gender trends for ovenrveight/obesity. The obesity rates among minority
children exceed the obesity rates among White children (Saxena, Borzekowski, &
Rickert, 2002). Dwyer et al. (1998) found that the prevalence of ovenrveight and
triceps skinfold thickness was greater among African American children than
among White children. Black adolescent females are almost twice as likely as
White adolescent females to be overweight (Saxena, Borzekowski, & Rickert,
2002). Haas et al. (2003) found that for children ages 6 to 11, boys were more
ovenrveight than girls, and Latinos and Blacks had a greater likelihood of being
overweight. For adolescents ages 12-17, boys were more overweight than girls,
and Latinos and Asian/Paciﬁc Islanders had higher prevalence of overweight
(Haas et al., 2003). Thorpe et al. (2004) also found a high rate of overweight
among Hispanic children, particularly Hispanic boys. Mexican-American children
and adolescents have increased rates of obesity, insulin, resistance, and type 2

diabetes than non-Hispanic White youth (Gomez, Johnson, Selva, & Salis, 2004).

27

Overall, in general boys are more likely to be ovenrveight or obese than girls
(especially in childhood), and African American, Mexican-American, Latino,
Hispanic, and Asian/Paciﬁc Islander children and adolescents have a higher
overweight/obesity prevalence than White youth. Some researchers hypothesize
that these differences may be due to lifestyle, acculturation, and cultural beliefs
and practices (Haas et al., 2003).

Race/ethnicity and gender differences in youth are also seen in levels of
physical activity and inactivity. There are various reasons for physical activity
level differences between males and females. One study showed that boys were
Signiﬁcantly more active than girls across all age groups for children aged 7- to
14-years, and for both boys and girls, the most active groups were 10-year-olds
(Raustorp, Pangrazi, & Stahle, 2004). In a study examining ovenrveight children,
Zabinski et al. (2003) found that overweight girls reported higher body-related
barriers to physical activity than overweight boys and indicated body
consciousness and concern about others seeing their bodies while being active
as the most common type of barrier to physical activity.

Gender differences have also been seen in physical activity intensity
levels. Participation in physical activities, particulariy the more vigorous
activities, is generally lower in females than in males (Hands, Parker, & Larkin,
2002). Robinson and Thomas (2004) also found that girls participated in more
low-intensity physical activity, but boys participated in more high-intensity

physical activity than did girls. Andersen et al. (1998) supported that giris tended

28

 

to participate less in vigorous activity than boys, and added that as girls get older
there is a steady decline in physical activity; however, as boys get older the
percent who participate in vigorous activity increases. Kohl and Hobbs (1998)
believe these differences are related to the development of motor skills, body
composition during growth, maturation levels and socialization toward sport and
physical activity.

Girls in the United States are at a high risk for inactivity, which may be the
cause of the statistics seen today regarding obese or ovenrveight females. In
1970, only one out of every 21 girls was obese or overweight; today, one out of
every six females is obese or overweight (National Center for Health Statistics,
2002). Cardiovascular disease is also the number one cause of death among all
American women (44.6% of all deaths), and the death rate is 69% higher for
African American women than for White women (American Heart Association,
2003).

Rates of inactivity have been found to be highest among minority youth,
especially females (Saxena, Borzekowski, & Rickert, 2002). Anderson et al.
(1998) identiﬁed that non-Hispanic Black and Mexican American children aged 8-
to16-years were less likely to participate in vigorous physical activity than non-
Hispanic Whites. Overall, according to the Youth Behavioral Risk Surveillance
System (YRBSS; Grunbaum et al., 2004), 33.4% of students in grades 9 through
12 did not participate in sufﬁcient physical activity. Insufﬁcient participation was

higher among Black females (50.4%), Hispanic females (42.6%), and White

29

 

females (37.5%) compared with Black males (31.8%), Hispanic males (30.3%),
and White males (24.8%). By comparing these percentages to the percentages
of overweight and obese youth, there is clearly a connection in the statistics
between overweight and obesity, and physical activity levels.

Cultural differences may also inﬂuence participation in physical activity.
Yan and McCullagh (2004) investigated the differences in participatory motivation
in physical activities among Chinese, American-bom Chinese, and American
children and adolescents ages 12 to 16. They found that American children and
adolescents participate in sports or physical activities for competition and
improving skills, Chinese children and adolescents participate because of social
afﬁliation and wellness, and American-bom Chinese children and adolescents
participate because of travel, equipment use, and having fun (Yan & McCullagh,
2004)

Health-related Physical Fitness Levels of Children and Adolescents

Many deﬁnitions for ﬁtness exist. For the purpose of this study, the health-
related ﬁtness as deﬁned by Bouchard and Shephard (1994) will be used. It is a
state characterized by an ability to perform daily activities with vigor, and a
demonstration of traits and capacities that are associated with a low risk of
premature development of hypokinetic diseases and conditions (Bouchard &
Shephard, 1994). ~

One aspect of improving the physical activity of children is improving

health-related physical ﬁtness levels. Beneﬁts of ﬁtness programs for children

30

include: (a) an increase in their willingness to become more physically active due
to a possible increase in physical ability; (b) improvements in the ability to self-
regulate their physical activity levels when children participate in supervised
ﬁtness programs; and (c) the development of positive attitudes toward physical
activity and ﬁtness during Childhood affecting their level of ﬁtness during
adulthood (Simons-Morton, Parcel, O’Hara, Blair, & Pate, 1988).

Bouchard and Shephard (1994) break down the components of health-
related physical ﬁtness into the following: morphological components, muscular
components, motor components, cardioreSpiratory components, and metabolic
ﬁtness components. There are various ways to test these areas. Some common
assessments to measure these components include BMI (morphological
component), muscular strength and endurance tests (muscular component),
agility, speed of movement, and motor coordination (motor component), and
submaximal exercise capacity (cardioreSpiratory component). With the exception
of metabolic component, the FTG is one assessment of these components for
children and adolescents.

The FTG is a widely-used comprehensive health-related ﬁtness and
activity assessment and computerized reporting system, comprised of six major
ﬁtness areas with multiple performance task options for most areas to measure
all components of physical ﬁtness (Corbin & Pangrazi, 2008). The speciﬁc
health-related physical ﬁtness components assessed by the FTG test battery

include aerobic capacity, abdominal strength and endurance, upper body

31

strength and endurance, trunk extensor strength and ﬂexibility, ﬂexibility, and
body composition. For the purpose of this study, the aerobic capacity and body
composition components will be assessed.

Cardiovascular Fitness Level and Assessment. The assessment for
cardiovascular ﬁtness used by the FTG is the Aerobic Capacity Measurement.
This measurement is used as opposed to other terms that are often used
interchangeably (e.g., cardiovascular ﬁtness, cardiovascular endurance,
cardioreSpiratory endurance, aerobic ﬁtness, maximal aerobic power, aerobic
work capacity, physical work capacity) because it refers to a functional

(physiological) capacity. The ﬁeld tests that are used to measure this functional
capacity are validated compared to V02 max tests measured in a laboratory

setting and the functional capacity is of most interest in relation to health
(Cureton & Plowman, 2008). The three FTG test options for this measurement
are the PACER, the one-mile um, and the walk test. For the purpose of this
study, the PACER will be used because it is a fun alternative to distance run
tests, and it is appropriate for this age group (Cureton & Plowman, 2008). The
pilot study showed the feasibility of conducting the PACER in an indoor school
setting. The one-mile run or one-mile walk tests will not be used because the
participants may get bored and there may not be an appropriate facility for the
test (because running or walking outside may not be an option depending on the
weather). In addition, the one-mile run makes it very clear which students are

slower than others (as they are the last to ﬁnish), which may affect a child

32

 

psychologically. Students who are the last to ﬁnish during the PACER test are
the students who perform better than those students who drop out of the test
earlier due to fatigue. Barkoukis, Thogersen-Ntoumanis, Ntoumanis, & Nikitaras
(2007) recommend that physical education teachers provide opportunities for all
students to achieve and feel able in order to foster intrinsic interest and
enjoyment. Because this testing will take place with children and in a physical
education setting, it is important that a positive motivational climate is created or
maintained.

Body Composition. Methods for estimating body composition in children
and adolescents include undenNater/hydrostatic weighing, Bod Pod, DEXA,
anthropometry (skinfold measurement), bioelectrical impedance, and BMI. BMI
is a simple, accurate and valid measure of fatness in childhood and adolescence
(Dietz & Bellizzi, 1999). The American Academy of Pediatrics Expert Committee
on obesity evaluation and treatment suggests BMI be used as the tool for the
screening and classiﬁcation of childhood obesity (Barlow & the Expert
Committee, 2007), and the International Obesity Task Force supports the use of
BMI to assess fatness in children and adolescents (Dietz 8 Bellizzi, 1999). BMI
shows a strong correlation to skinfold thickness in Children (Rowland, 1990) and
to hydrostatic densitometry (Revicki & Israel, 1986).

The two options recommended by the FTG to assess body composition
are skinfold measurements and BMI, because the laboratory method is not

practical for use in the school setting. Laboratory methods require facilities with

33

materials such as hydrostatic weighing equipment or a Bod Pod, which is
uncommon in elementary, middle, and high schools. It is advantageous to use
BMI because it is convenient, less expensive, not intmsive, and easy to
calculate. The BMI and skinfolds HFZ ranges correspond to 25% fat for boys
and 32% fat for girls, and are used in schools throughout the country to
encourage health-related ﬁtness (Lohman, Going & Metcalfe, 2004). BMI is the
test selected for use by most schools, usually because teachers do not have
sufﬁcient training and experience in skinfold measurement. BMI is also easier to
calculate with acceptable accuracy than skinfold measurements (Raustrop,
Pangrazi, & Stahle, 2004). Although the 5.6% prediction error may make BMI
less effective in identifying moderately ovenrveight children (Lohman & Going,
1998), Pietrobelli et al. (1998) found BMI as a way to measure fatness in groups
of children and adolescents, but cautioned about interpreting results when
comparing BMI across age groups or predicting a speciﬁc individual’s body fat.
While the CDC classiﬁes children and adolescents into percentiles
according to their BMI-for-age to determine ovenrveight and obesity trends, the
FTG identiﬁes three categories related to BMI of youth aged 5 to 17. BMI scores
falling within the HFZ are indicative of a healthy level of body composition. A
BMI score that falls within the Needs Improvement range is above the HFZ and
indicates that a child or adolescent weighs too much for his or her height. A BMI
score that falls within the Very Lean range is below the HFZ and indicates that

the child or adolescent’s weight is too light for his or her height.

34

The BMI HFZ ranges may provide a better indication of body composition
than height and weight charts (such as those provided by the CDC). The charts
show percentiles that plot the distribution of BMI at a given age and can be used
to identify children who are ovenrveight, but they may not be overfat (Lohman &
Falls, 2006). BMI based on the HFZ charts responds to the concern of a more
muscular child. A child with more lean muscle mass will have a higher BMI
based on growth charts that may classify him or her as falsely overweight when
in reality, does not indicate an unhealthy level of fat. Therefore, a high BMI could
be made up either by excess adipose tissue or by muscle hypertrophy, and the
opposite is also true (Wickramasinghe et al., 2005).

Muscular Strength/Endurance & Flexibility Fitness Levels. The three
remaining components of physical ﬁtness are also measured in the FI'G. These
component assessments include testing for abdominal strength and endurance,
upper-body strength and endurance, trunk extensor strength and ﬂexibility, and
another ﬂexibility test. However, due to the lack of signiﬁcant results from these
tests in the pilot study (discussed below), these components will not be tested as
part of this study.

Motor Skill Development of Children
Importance of Motor Skill Development. A child’s development of fundamental
motor skills is important at a young age. Strong et al. (2005) concluded that
during the preschool and early school ages general movement activities develop

movement patterns and skills, and after that occurs and Skills improve, health,

35

ﬁtness, and behavioral components of physical activities increase in importance.
Fisher and colleagues (2005) tested preschool children and found that there was
a signiﬁcant but weak relationship between the habitual physical activity and
fundamental movement skills of the participants. The mastery of fundamental
motor skills may be an important factor in preventing unhealthy weight gain
among children and adolescents (Okely, Booth, & Chey, 2004). Motor skill
interventions at a young age may help improve fundamental motor skills and
thereby increase physical activity levels. One such intervention was conducted
with disadvantaged preschool children and results showed signiﬁcantly greater
improvements in fundamental motor skills (both Iocomotor and object-control)
from pre- to post-intervention, as compared to the control group (Goodway &
Branta, 2003).

Participation in sport and physical activity in general may have a positive
inﬂuence on the fundamental motor skill level of children and adolescents as they
get older as well. Ulrich (1987) found that children in grades K through four
involved in organized sports performed selected movement ability tasks better
than nonparticipants. Houwen, Hartman, and Visscher (2008) also found a
positive correlation between physical activity and gross motor skill performance
of children ages six to twelve. Thomas and French (1985) found that prior to
puberty, physical activity and motor performance differences between boys and

girls are minimal. A greater variability exists among boys and among girls, rather

36

than between boys and girls, with most skill differences dependent on practice,
opportunity, and interest (Thomas, Thomas, & Williams, 2008).

Fundamental motor skills are critical to participation in most physical
activities because they are necessary for the behavioral competencies required
for participation (Okely, Booth, & Chey, 2004). These skills are the basic building
blocks for more advanced movements (Clark & Metcalfe, 2002), and by providing
children with opportunities to explore these movements, it may help children
learn the principles that underlie all sports (Bunker, 1991). For example, children
must learn how to kick before they can participate in soccer, and in order to play
basketball they need to learn basic fundamental motor skills such as jumping.
Comparisons of children with high and low motor competence Show differences
in participation in moderate to vigorous activities (Hands, Parker, & Larkin, 2002).

The development of motor skills also has implications for the future
physical activity participation of a child or adolescent. Booth and colleagues
(1997) identiﬁed low motor skill level as a major barrier to participation in sport.
Oftentimes children drop out of sport as they get older, and one reason is
because they lack the skill level to sufﬁciently play a game successfully (Hands,
Parker, & Larkin, 2002). In a study examining the relationship of physical activity
to fundamental movement skills among adolescents in grades eight and ten,
Okely, Booth, and Patterson (2001a) found that fundamental movement skills
(run, vertical jump, catch, overhand throw, forehand strike, and kick) are

signiﬁcantly associated with adolescents’ participation in organized physical

37

activity (but not nonorganized physical activity). The movement skills
signiﬁcantly predicted time in organized physical activity; however, they only
accounted for 3% of the total variation.

Duncan (1997) found that failure to develop a range of fundamental motor
skills at a young age makes it more difﬁcult to begin physical activities and sport
later in life. Adolescents and adults who are not competent in speciﬁc
movements ﬁnd it hard to learn new ways to move their bodies, not only because
of the physical demands, but also because of the fear of appearing awkward and
unskilled, leading to embarrassment. However, improved fundamental motor
skill proﬁciency may enhance a child’s motivation to be physically active through
improved self-esteem and enjoyment of physical activity, in addition to improved
skills (Okely, Booth, & Chey, 2004).

Assessment of motor skill/mater performance. Various instm ments exist to
assess fundamental motor skill performance. These instruments may be process
assessments or product assessments. Process assessments, such as the Test

. of Gross Motor Development-2nd Edition (TGMD-2; Ulrich, 2000) or the Get
Skilled: Get Active process-oriented motor skill assessment tool (New South
Wales Department of Education and Training, 2000), measure how the skills are
performed. Product assessments, such as the Bruininks-Oseretsky Test of
Motor Proﬁciency (Bruininks, 1978) or The Movement Assessment Battery for
Children (M-ABC; Henderson & Sugden, 1992) quantify the skill performance by

the skill execution outcome, such as time, distance, or successful attempts.

38

These two types of measurements will determine the physical competencies of
youth; however, only the process assessments can identify the speciﬁc skill
components that need improvement (Ulrich, 2000).

The TGMD—2 (Ulrich, 2000) will be the process-assessment used in the
current study because it is a well-validated, standardized test to measure the
fundamental motor skill performance of children between the ages of 3 and 10
years. Children are qualitatively assessed on their performance for both
Iocomotor skills and object-control skills. The Iocomotor skills are running,
galloping, hopping, leaping, horizontal jumping, and sliding. The object-control
skills include striking a stationary ball, stationary dribbling, catching, kicking,
overhand throwing, and underhand rolling. Children receive a score for each skill
based on performance criteria (3 to 5 criteria, depending on the skill). A criterion
is scored with a 1 or 0 to indicate its presence or absence. Children demonstrate
each skill twice, resulting in a raw score for that skill between 0 and 8 points with
48 being the highest total possible raw score for both the locomotor and object-
control skills. The raw scores can be converted into standardized scores per age
group.

One concern with using process assessments to identify problem skill
features is the challenge of creating a clear scoring and assessment system
(Barnett et al., 2009). This challenge becomes even more difﬁcult when multiple
people are raters for the fundamental motor skills. Therefore, it is critical that

each rater be trained and that inter-rater objectivity is tested.

39

Relationship between Fundamental Motor Skill Development/Level and Fitness
Level of Children
Until recently, the relationship between motor skills and physical activity
and ﬁtness levels of children has not been closely examined, but recent studies
are showing the important connection between these variables. Stodden et al.
(2008) argued that the “degree of motor skill competence is a critically important,
yet underestimated, causal mechanism partially responsible for the health-risk
behavior of physical inactivity” (p. 302), and they emphasize that much of the
physical activity research is focused on the measurement, ignoring the Ieaming
that must occur in order to move and be physically active.
Various studies have shown a relationship between youth fundamental

motor skill development/level and different ﬁtness components. According to a
study (Okely, Booth, & Chey, 2004) examining cross-sectional data of 4,363
children and adolescents in grades 4, 6, 8, and 10, body composition (as
determined by BMI and waist circumference) was found to be inversely related to
only Iocomotor skill proﬁciency; it was unrelated to object-control skill proﬁciency.
Therefore, the heavier children and adolescents performed the fundamental
Iocomotor skills more poorly than the less heavy ones; yet body composition had
no inﬂuence on the children and adolescents’ performance on the fundamental
object-control skills. Malina et al. (1995) also studied the association between

body composition (using skinfold measurements) and ﬁve motor performance

40

items of girls ages 7 to 17 years. He found that as adiposity increased, balance
speed, power, and strength decreased.

Another group of researchers examined whether weight status inﬂuenced
the association among children’s fundamental movement skills and physical
activity (Hume et al., 2008). While a cause-and-effect relationship could not be
tested with the design of the study, results revealed correlations between
physical activity and motor skill proﬁciency, but no interaction between those two
variables and weight status (Hume et al., 2008).

A relationship has also been shown between cardioreSpiratory endurance
and fundamental motor skill proﬁciency. Okely, Booth, and Patterson (2001b)
examined this relationship with adolescents in eighth grade and tenth grade
testing both Iocomotor (run and jump) and object-control (catch, throw, kick, and
strike) skills related to cardioreSpiratory endurance measured using the PACER.
They found a signiﬁcant relationship between the number of laps measuring
cardioreSpiratory endurance and each fundamental motor skill (Okely, Booth, &
Patterson, 2001b). In addition, gender differences were revealed. Boys had
higher levels of cardioreSpiratory endurance and were more competent than girls
on all fundamental motor skills except the vertical jump (Okely, Booth, &
Patterson, 2001 b). .

Psychological Factors
Psychological factors can both inﬂuence ﬁtness levels, motor Skill

development, and participation in sport, exercise, and physical activity and be

41

inﬂuenced by these variables. There are many terms related to the self that are
sometimes used interchangeably. Therefore, it is important these terms be
deﬁned as related to the proposed study.

Self-perception and self-concept are closely related. According to Horn
(2004, p. 102), self-perceptions are “individuals’ beliefs, perceptions, attitudes,
thoughts, and feelings about themselves in general or about their abilities, skills,
competencies, characteristics, and behaviors,” while self-concept is “a relatively
stable assessment or description of the self in terms of personal characteristics,
attributes, and abilities.” Horn (2004) explained the latter is the descriptive
component of the self (i.e., who am I; what am I; what kind of person am I; what
are my strengths and weaknesses?) Davison and Birch (2001) noted that
. overweight children experience low self-concept across a number of domains of
self-concept. In their study examining the relationship between weight status and
self-concept in a sample of preschool-aged giris, they found that as early as age
5 years, lower self-concept is noted among girls with higher weight status
(Davison & Birch, 2001), although Klesges et al. (1992) found that low self-
esteem is not characteristic of obese preschool children.

Self-esteem (or self-worth) is “a relatively stable evaluation or judgment of
the overall self” (Horn, 2004, p. 102). Compared to self-concept, Horn (2004)
explained self-esteem as the evaluative component of the self (i.e., how much do
I value the person I am, the abilities I have, the traits and characteristics that are

part of me?) One potential long-term beneﬁt for participating in sports activities is

42

self-esteem (NLSCY, 2001). Data from the NLSCY (2001) showed that 16% of
youth who had rarely or never participated in sports reported low levels of self-
esteem, four times higher than those who had always participated. Strauss
(2000) chose to examine this data to identify trends from childhood to
adolescence. He found that although no signiﬁcant differences among 9 to 10-
year—old obese and nonobese children in academic and global self-esteem
scores were found among either gender or ethnic group, over the four year
period after this time, differences emerged in gender and ethnicity related to
weight status. Obese Hispanic and White females showed signiﬁcantly lower
levels of global self-esteem compared to their nonobese counterparts, and there
were mild decreases in self-esteem in obese boys compared to nonobese boys.
Low self-esteem may then lead to other consequences, linking back to obesity
and continuing the cycle. Abernathy, Webster, and Verrneulen (2002) found that
low self-esteem of adolescents was associated with low self-mastery, not being
happy and interested in life, less physical activity, and not reporting health as
excellent.

Perceived competence (or perceived ability) is “the individuals’
perceptions of their competencies or abilities in speciﬁc domains” (Horn, 2004, p.
103). According to Horn (2004), this construct is perceived to be less global (i.e.,
they: are more typically measured in reference to speciﬁc achievement domains)
and relatively less stable - especially as they ﬂuctuate over time and across

achievement domains. One problem in using the measurement of self-esteem is

43

that unidimensional or global self-esteem does not capture the speciﬁc sources
from which self-worth is derived, in particular, body esteem or perception of
physical appearance (Franklin, Denyer, Steinbeck, Caterson, 8. Hill, 2006).

The perceived competence of the individual may relate to certain domains.
For example, children who are more physically or athletically competent (e.g.,
believing that they are good at sports and learn new physical activities easily)
typically have higher physical activity levels (Davison, Downs, & Birch, 2006).
Therefore, they are more likely to have higher ﬁtness levels and are less likely to
be ovenrveight or obese.

Two additional terms are often used in lieu of some of the terms above;
however, they are quite different. Self-conﬁdence is “the degree of certainty
individuals possess about their ability to be successful” (Horn, 2004, p. 103). In a
more situational setting, self-efﬁcacy is the belief that one can successfully
execute a speciﬁc activity in order to obtain a certain outcome (Bandura, 1986).
It is consistently an important predictor of physical activity in children and adults
regardless of race (Crespo, 2005).

Psychological Assessment: Self-Perception Profile for Children (SPPC). Due to
the connections between perceived competence and other concepts related to
the self (e.g., self-esteem, self-conﬁdence, self-efﬁcacy), this measure will be
used as the psychological component of this study in order to identify how the
competence in the different domains is affected by ﬁtness levels and motor skill

development. There are many instruments to measure psychological

44

components discussed in this review. For the purpose of this study, the Self-
Perception Proﬁle for Children (SPPC) will be used in order to measure the
participants’ competence in different domains as opposed to general
psychological factors (e.g., overall self-esteem) or situational factors (e.g., self-
efﬁcacy).

The SPPC measures children’s perceptions of themselves. It consists of
36-items using a Likert scale to assess perceived competence in ﬁve domains
(academic competence, social acceptance, athletic competence, physical
appearance, behavioral conduct) and a sixth domain of global self-worth. The
athletic and academic competence scales directly measure children’s judgments
of their competency, while the remaining scales measure children’s self-
adequacy, rather than competence at actual skills (Harter, 1985). The subscales
have six questions each which are scored 1 to 4, with 1 and 2 indicating low-
perceived competence and 3 and 4 indicating high-perceived competence. The
SPPC speciﬁcally has been chosen because it is intended for children from ages
8 to 14. The SPPC takes approximately 15 minutes to complete, so it will also be
practical to use in this study.

Furthermore, psychometric testing has shown that it is signiﬁcantly less
inﬂuenced by socially desirable answers compared with other measures of self-
esteem, which is most likely due to the way the survey is formatted (Harter,
1985). For each question, the child responds to the two contrasting statements.

For example, one question in the physical appearance domain is, “Some kids are

45

happy with their height and weight BUT Other kids wish their height or weight
were different.” Once the child chooses one of the statements, he or she then
answers whether the statement is “a little like me” or “a lot like me.” This process
allows researchers to evaluate the prevalence of children who have high versus
low perceived competence in the different domains. An example of a question
from the academic domain is, “Some kids feel that they are very good at their
school work BUT Other kids wony about whether they can do the school work
assigned to them.” In the peer acceptance domain, one question is, “Some kids
ﬁnd it hard to make friends BUT For other kids it’s pretty easy.” An example of a
question from the athletic domain is, “Some kids do very well at all kinds of sports
BUT Others don’t feel that they are very good when it comes to sports.” In the
behavioral conduct domain, one question is, “Some kids often do not like the way
they behave BUT Other kids usually like the way they behave.” And ﬁnally, an
example from the global self-worth domain is, “Some kids like the kind of person
they are BUT Other kids often wish they were someone else.”

Psychological Aspects related to Motor Skill Development in Children

Relationships have been identiﬁed in the literature between two of the

three variables, but not the relationship among the three. The ﬁnal relationship
between two variables is between motor skill development and psychological
aspects. Children gain self-conﬁdence and self-esteem as a result of successful
experiences, particularly in the motor domain (Bunker, 1991), and improved

proﬁciency of fundamental motor skills may improve perceived competence and

46

self-esteem (Ulrich, 1987). Furthermore, the improved proﬁciency of
fundamental motor skills may also enhance motivation to be physically active
through improved sail-esteem and enjoyment of physical activity, in addition to
improved skills (Okely, Booth, & Chey, 2004). Hill (2009) agrees with the
psychological benefrts of improved skills. In addition, he argues that access to
sport participation during the elementary school years is critical because children
who develop physical skills in those activities tend to have a higher perceived
competence (Hill, 2009), which is a major reason why children continue to
participate in speciﬁc physical activities and are motivated to be physically active
(Hutchinson & Mercier, 2004). Thomas, Thomas, and Williams (2008) found this
relationship is also evidenced in the other direction; maintaining motivation to
continue participation and practice is essential to skill development and future
physical activity as well. Overall, the research using Harter's SPPC has shown
an association between childhood overweight and obesity and some, but not all,
of the six subscales. Franklin, Denyer, Steinbeck, Caterson, and Hill (2006)
found obese children had signiﬁcantly lowered perceived athletic competence,
physical appearance, and global self-worth than their normal weight peers, with
lower scores in these domains in giris than in boys. In addition, obese girls also
had reduced perceived social acceptance, but no changes were seen in this
domain for boys or in academic competence or behavioral conduct for both boys

and girls (Franklin et al., 2006).

47

Summary of Review of Literature

This review of literature examined the current research about physical
activity, speciﬁcally relating to motor skill development, health-related ﬁtness, and
perceived competence. Physical activity levels of children and adolescents have
been a key component in the childhood obesity literature, due to its implications
in contributing to developing and maintaining a healthy lifestyle for youth, and the
negative health psychosocial consequences that may emerge from physical
inactivity and obesity.

Gender and race/ethnicity may be factors that contribute to the body
composition and physical activity levels of children or adolescents. Although
there are trends in the literature, mixed results that still remain in the literature
prove this area in the childhood obesity and physical activity research is one that
needs to continue to be examined.

Three factors that may also contribute to the obesity level and physical
activity participation of children and adolescents are the health-related physical
ﬁtness, motor skill performance, and perceived competence of youth. Research
has shown the importance of developing health-related physical ﬁtness,
maintaining a healthy body composition, Ieaming fundamental Iocomotor and
object-control skills and performing them at a developmentally appropriate level,
and the inﬂuence of perceived competence in different areas of one’s life. The
current literature examines the relationship between ﬁtness and motor skill

development, between ﬁtness and perceived competence, and between motor

48

skill development and perceived competence, but little is known about the
relationship among the three variables.
Purpose of Study

There is plenty of evidence to show the importance of the three variables
in the study and how they relate to the childhood obesity epidemic and the lack of
physical activity of children and adolescents. However, this study focuses on the
gap in the research examining the relationship among health-related ﬁtness
levels, motor skill performance, and perceived competence.

The pilot study discussed in the introduction revealed results that sparked
future investigation. Therefore, the purpose of this study was to examine the
relationship among fundamental motor skill development (of both Iocomotor and
object-control skills), health-related ﬁtness level (measured by aerobic capacity
and body composition), and perceived competence (measured by
subscales/domains) of fourth grade students. In addition, any differences
between males and females were addressed. Although the races/ethnicities of
the individual participants were not attainable, general race/ethnicity information

was collected from the schools to relate to the variable for exploratory purposes.

49

CHAPTER THREE
Method

Participants

Participants in this study were fourth grade students at three elementary
schools in Michigan. Students in the fourth grade at School A were Caucasian
(94%), Asian (3%), and Hispanic (3%), at School 8 were Caucasian (86%),
Asian/Paciﬁc Islander (8%), African American (4%), and Hispanic (2%), and at
School C were Caucasian (60%), Asian (28%), and African American and
Hispanic (12% combined). Socioeconomic status of the participants was
determined by students who received free and reduced lunches at the schools,
or by the demographic data from the website of the school. At School B, 10% of
students received free and reduced lunches, and at School C, less than 10
students (17%) were considered economically disadvantaged. This information
was not available from School A. Because of the homogeneous sample
(predominately middle to upper class, Caucasian students), differences in
race/ethnicity and socioeconomic status were not addressed in this study.

There were a total of 221 fourth grade children (66 at School A, 92 at
School B, and 63 at School C) enrolled at the schools. Total participants
included 137 fourth grade children (62% of the total number of fourth graders
enrolled at all schools), consisting of 67 males and 70 females. There were 33
participants from School A (13 males and 20 females), 51 participants from

School B (25 males and 26 females), and 53 participants from School C (29

50

males and 24 females). All students in attendance on the days of the
measurements and testing with completed parental consent forms and assent
forms were included in the study. On the ﬁrst day of data collection, students
without parental consent forms were informed they would still be able to
participate during the next data collection day if they brought back their
completed form. Additional data collection days were added in order to collect
missing data from participants who were absent during data collection days or
turned in their parental consent forms late. One student from School B was
excluded from the study because he was absent on the days the PACER, height
and weight, and SPPC information were collected, and was absent again during
the ﬁnal make-up day. Therefore, he had only motor skill data and the
relationship with the other variables was not able to be asseSsed.
Measures
FTG PACER and BMI

Two assessments from the FTG test battery were used: the Progressive
Aerobic Cardiovascular Endurance Run (PACER) to measure aerobic capacity
and the body mass index (BMI) as the measure of body composition. The
PACER is a multi-stage, 20-Meter test set to music; therefore, the FTG 20-Meter
PACER CD was used. The music allows a fun alternative to distance run tests
(e.g., one-mile run) for an aerobic capacity test. The objective is for the
participants to run as long as possible back and forth across a 20-meter distance

at a speciﬁed pace that gets faster each minute. During the ﬁrst minute, the 20-

51

meter version allows 9 seconds to run the distance, and the lap time decreases
by approximately one-half second at each successive level, which occurs every
minute. By progressively running faster, the children begin with a wann-up and
are able to pace themselves effectively as the time to complete the lap
decreases, until the participants can no longer complete two successive laps.
The PACER is a valid and reliable test for children; reliability of the test ranges
from 0.84 to 0.93 (Leger et al., 1988; Liu, Plowman, & Looney, 1992; & Mahar et
al., 1997), and validity of the test ranges from 0.69 to 0.87 (Boreham, Paliczka, &
Nichols, 1990; Leger et al., 1988; Liu, Plowman, & Looney, 1992; Mahoney,
1992; Van Mechelen, Hlobil, & Kemper, 1986).

The second component tested from the FTG was body mass index (BMI)
as the measure of adiposity. In order to calculate BMI, standing height and
weight are obtained using standard anthropometric procedures (Malina, 2004) as
described below. Participants are asked to remove their shoes and any heavy
clothing (e.g., jackets, sweatshirts) before being measured. Height is measured
with the participants standing in a standard erect posture (Malina, 2004). In this
study, height was measured to the nearest 0.1 cm using a portable stadiometer
(Seca Road Rod). Body mass was measured to the nearest 0.1 kg using a
calibrated strain gauge scale (Lifesource MD).

Test of Gross Motor Development-2 (TGMD-2)
The TGMD—2 includes 12 gross motor Skills that are subdivided into two

skill areas: Iocomotor (run, gallop, hop, leap, jump, and slide) and object-control

52

(two-hand strike, stationary bounce, catch, kick, overhand throw, and underhand
roll). A demonstration was provided prior to the participants performing each of
the skills at stations in the school gymnasium while being videotaped. The
researcher scored all the participants’ motor skill levels by watching the
videotapes, with assistance from another researcher for School A. Both
researchers scored the motor Skill levels separately and then compared their
scores for School A. If any discrepancies existed, the researchers reviewed the
video as needed to discuss the participant’s performance until a decision was
reached for the score. The scorers were trained by an expert in TGMD-2
assessment. Inter-rater reliability (r = 0.69) between the TGMD-2 expert and the
primary researcher was attained for this investigation.

Self-Perception Proﬁle for Children (SPPC)

The SPPC was administered to the participants in each fourth grade
classroom or during part of the physical education class. This measure is a 36
item, 4 point Likert scale survey which consists of 6 questions from each of the
domains/subscales (i.e., academic, peer acceptance, athletic, physical
appearance, behavioral conduct, and global self-worth). Children are instructed
to circle the phrase that best describes them, and then they are asked to decide
if the phrase they chose is “really true” or “sort of true” for them, checking the
appropriate box next to the statement. Scores can range from 1 to 4 for each
item, and various items are reverse scored. A score of 4 indicates “really true”

for the higher perceived competence, 3 indicates “sort of true” for the higher

53

perceived competence, 2 indicates “sort of true” for the lower perceived
competence, and 1 indicates “really true” for lower perceived competence.
Therefore, scores OH and 2 indicated low perceived competence, and scores of
3 and 4 indicated a high perceived competence. Reliability and validity of this
measure have been tested in many studies and was used in the pilot study
previous to this one. According to Harter (1985), subscale internal reliabilities
range from 0.71 to 0.84. Researchers have found high internal reliability (r = .73-
.86; Harter 1982; Harter, 1985), although Shevlin, Adamson, & Collins, 2003)
found that the reliability estimates over four administration times within one year
ranged from 0.53 to 0.77 in subjects ages 8 to 10, with an increase from the ﬁrst
to last administration for all subscales except for behavioral conduct.
Procedures

The researcher visited the principals and physical education teachers at
School A and School B in early December 2009 to discuss the data collection
process, answer any questions, and ask for input. School C was not added until
February 2010 when not enough participants had been recruited from Schools A
and B. Then the researcher met with the principal at School C and received
approval from the superintendent of the school district to proceed with data
collection. All procedures were approved by the Michigan State University
Institutional Review Board (IRB). Once IRB approval was obtained, approved
consent forms were sent home to all the parents of the fourth graders at all three

schools in the students’ weekly folders asking parents to return the completed

54

form by the ﬁrst day of data collection it they wanted their child to participate in
the study. Overall percentages for race/ethnicity of the fourth graders were also
provided by school administrators. Parental consent forms were collected by the
physical education teachers or classroom teachers at the schools. Written and
verbal participant assent was obtained on the ﬁrst day of data collection in each
class for participants with completed parental consent forms. The researchers
read and explained the assent form verbally to the participants and answered
any questions.

All data collection took place over a six-week time period (February to
March). The time frame was extended from a three-week schedule due to the
addition of a third school, fourth grade ﬁeld trips, and time conﬂicts in physical
education classes. There were 22 to 25 students in each class at both schools.
This length of time for data collection in each class was determined by needed
time indicated in the manuals of the measures being used in the study, and from
experience during the pilot study. The planned time proved to be an adequate
amount of time for testing.

On the ﬁrst day of data collection, all participants completed the Iocomotor
skill testing. All skills were videotaped to allow for careful analyses and scoring
at a later time. Three skills were performed at each station. Running, hopping,
and jumping were performed at one station, while galloping, sliding, and leaping
were performed at the other. On the second day of data collection, all

participants completed the object-control testing. Striking, dribbling, and

55

underhand rolling were performed at one station, while kicking, catching, and
throwing were performed at the other. The students who did not have a
completed parental consent form were still able to participate during the skill
testing; however, they were not videotaped. During the third day of’data
collection, the participants completed the PACER as a group. All students were
allowed to participate in this activity, but only the scores of participants with
completed parental consent forms were recorded. After the PACER, the
researcher took height and weight measurements individually while the physical
education teacher had the students involved in another activity, except for at
School A where the graduate research assistant took height and weight
measurements on another day. Additional days of data collection were added to
collect data for all variables for as many participants as possible.

Research assistants included graduate and undergraduate students who
helped with set-up, clean-up, recording PACER testing information, and
recording the TGMD-2 data using video cameras. The research team consisted
of six graduate students and twelve undergraduate students, as well as the
physical education teacher and physical education intern at School C. The goal
number of participants was reached; therefore, no additional parental consent
forms were sent home and no additional days were added for data collection

after the ﬁnal follow-up days.

56

F TG PACER

The PACER was administered using the established FTG PACER
protocols (Cooper Institute for Aerobic Research, 2007). The testing took place
in the gym at the schools, and cones and tape were used to mark off the 20-
meter distance. Students were familiar with the task because the physical
education teachers allowed the students to practice the test beforehand in a
previous class, and at School B the students were familiar with this test before
the practice previous to data collection. The researcher explained the test and
they were also allowed to listen to the directions on the CD and run a few
minutes of the actual test before performing the test. Participants performed the
test as a group (all beginning at the same time), and continued until they failed to
reach the line before the beep for the second time. The number of laps was

recorded by the researcher and research assistants;- Scores were also

converted to estimated VO2 Max (ml/kg/min), dependent on the participant’s age

and gender, using the equation: estimated V02 max = 31.025 + (3.238 * Max
speed) - (3.248 * age) + (.1536 * max speed * age) from the SAS Growth
Program for the CDC Growth Charts (CDC Growth Chart Training, 2009). The

FITNESSGRAM standards for the Healthy Fitness Zone (HFZ) for the PACER
tests include V02 max scores between 42 and 52 mI/kg/min (Cooper Institute for
Aerobic Research, 2007). Each participant was classiﬁed as “Below the Healthy

Fitness Zone (HFZ)” or “In or Above the HFZ” according to the FITNESSGRAM

standards for the PACER HFZ for males and females.
57

BMI

Standing height and weight measurements were obtained using standard
anthropometric procedures (Malina, 2004). Measurements were taken by a
graduate research assistant at School A, and by the researcher at Schools B and
C. Measurements were taken in the equipment rooms which were connected to
the physical education gyms at the schools. Participants were measured
individually (without other participants present in the equipment room) to ensure
privacy and ensure measurements remained conﬁdential. During the height
measurements, they were asked to look straight ahead in order to maintain an
erect posture while having their height measured, and were asked to step on the
scale and look straight ahead so they would not see their weight. They also
stepped on the scale backwards (facing away from the display) in order to ensure
they would not see their weight. Measurements were recorded without
verbalizing.

BMI measurements were calculated for each participant using the formula:

BMI = weight (kg) l height squared (m2). Each participant was classiﬁed as

“Below the Healthy Fitness Zone (HFZ)”, “In the HFZ”, or “Above the HFZ”
according to the FITNESSGRAM standards for the BMI HFZ for males and
females. In addition, participants were also classiﬁed into one of four groups
based on the CDC (2009) age-sex speciﬁc BMI percentiles: (a) undenrveight (BMI
S 5th percentile); (b) normal weight (5"1 < BMI < 85th percentile); (c) overweight

(BMI a 85th and < 95th percentile); or (d) obese (BMI 2 95th percentile).

58

Percentiles were determined using a SAS Growth Program for the CDC Growth
Charts (CDC Growth Chart Training, 2009).
TGMD-2

The TGMD-2 was administered using standard protocols (Ulrich, 2002).
The researcher provided a list of equipment needed to administer the TGMD—2 to
each physical education teacher, and brought any necessary items the physical
education teacher did not have or did not want to provide. Each participant was
given a randomly assigned number, then after lining up in numerical order, they
were split into two groups. There was one group at each station (2 stations total
for the locomotor skills, and 2 stations total for the object-control skills), and each
station was comprised of three skills. The researcher and research assistants
demonstrated the skills, and the participants had the opportunity to practice the
skill one to two times before each skill was performed twice on video to be
scored. Video cameras were positioned in the middle of the gymnasium facing
the stations situated on opposite sides of the gymnasium, and re-focused or
moved slightly as needed to videotape participants for each skill adequately. All
participants were videotaped performing each skill (in numerical order) during
both trials by the researcher or research assistants, and the researchers scored
each participant’s performance in the skills after reviewing the recordings. Each
participant’s skill performance was evaluated on qualitative performance criteria
(3 to 5 criteria, depending on the skill). For each trial, the participant received a

score of 1 if the criterion was present, or a 0 if it was absent.

59

The raw scores on the TGMD-2 were added for both trials of all Iocomotor
and object control skills. Therefore, for each skill there is a possible score
ranging from 0 to 6, 0 to 8, or 0 to 10 depending on the number of performance
criteria. Then, all the scores from the locomotor skills were added together, and
all the scores from the object-control skills were added together. For both the
Iocomotor and object control skills (two separate raw scores), the highest
possible raw score for each is 48 points.

SPPC

The SPPC was administered either in the classroom or during the
participants’ physical education period using standard protocols (Harter, 1985).
The researcher administered the SPPC in all classes. This procedure involved
the researcher explaining the questionnaire, reviewing a sample question, and
reading aloud the questions, asking the participants to follow along and mark
their answers accordingly, and answering any questions from the participants.
Participants were given an additional piece of paper to cover their answers and in
order to keep them from working ahead.

Participant scores from all 36 items on the SPPC were entered into an
Excel spreadsheet and appropriate questions were reverse-scored. The scores
were then calculated for each of the six subscales. Participants who chose not to
answer speciﬁc questions on the survey were only excluded from the particular
subscales in which they left blank answers. Participants with all complete

answers for each subscale were included in the data analyses.

60

Data Analysis

All data were entered into the Statistical Package for the Social Sciences
(SPSS) computer program and checked twice to ensure accurate data entry by
the researcher. Exploratory data analysis was conducted to identify any outliers.
No outliers were identiﬁed in the data. All participants fell within 4 standard
deviations with the exception of the object-control motor skill scores, which is to
be expected in fourth grade when there is a larger variability in the object-control
skill competency of children.

Descriptive statistics for participants’ scores on FITNESSGRAM, TGMD-2
and SPPC variables were computed. The means, standard deviations, and
ranges of all variables were calculated and also separated by gender.
Frequencies and percentages of participants meeting the FTG HFZ and Needs
Improvement category were also calculated, as well as CDC ovenrveight and

obese percentiles. Partial correlations (controlling for age) were calculated to
determine the relationships between BMI, V02 Max, Locomotor Raw Score,

Object-Control Raw Score, and all six SPPC subscales individually.

Linear regression analyses were used to test the hypotheses for the study.
Both backward regression and stepwise regression analyses were conducted to
determine if there was a difference between the tests. Each hypothesis was
analyzed using both backward and stepwise linear regression. The analyses
were also run with both the dataset including all participants, and the dataset

including only those participants with complete data. Results reported include all

61

participants in the dataset and the regression analyses are the results from the

stepwise linear regression results.

62

CHAPTER FOUR
Results
Descriptive Statistics
Descriptive statistics were conducted including all the subjects who
participated in any portion of the testing in the dataset. Then, the descriptive
statistics were conducted again to see if any differences existed between all

subjects and only those who had complete data for all testing (e.g., all skills in
the TGMD-2, BMI, V02 max, and all questions on the SPPC). The total number

of participants decreased from 134 to 112; therefore, 22 participants were
deleted from the dataset. However, even with these participants removed from
the dataset, no signiﬁcant differences existed between those with and without
complete data for the descriptive results, correlations, and regression analyses.
Therefore, all participants who participated in any portion of the, testing were
included for the remainder of the results presented.

Table 2 shows the physical descriptive characteristics for the total sample
(and separated by gender) including the mean, standard deviation, and range for
age, height, weight, and BMI. BMI ranged from 12.79 to 31.17 kg/ m2.
Independent t-tests revealed no Signiﬁcant difference in the mean BMI between
boys and girls (p = 0.607). The percentage of participants who were considered
underweight, in the BMI HFZ, ovenrveight, and obese according to the CDC

classiﬁcations (CDC, 2009) are also presented in Table 2.

63

Table 2

Physical Descriptive Characteristics of the Sample

 

 

Physical characteristics Male Female Total

Age (yrs) n=137 10.1 (0.42) 10.0 (0.31) 10.0 (0.37)
9-11 9-11 9-11

Height (cm) n=135 143.4 (5.83) 141.9 (6.56) 142.6 (6.23)

1282-1585 1292-1569 1282-1585
Weight (kg) n=135 37.1 (7.81) 36.9 (8.40) 37.0 (8.08)
24.5-69.0 24.3-65.2 24.3-69.0

BMI (kg/m2) n=135 17.9 (3.05) 18.2 (3.15) 18.1 (3.09)
13-31 13-31 13-31

% undenrveight* 5.9% 3.0% 4.4%

% in the FTG HFZ 69.1% 71.7% 70.4%

% overweight" 16.2% 13.4% 14.8%

% obese* 8.8% 11.9% 10.4%

 

Note. Age, Height, Weight, and BMI values are Mean (Standard Deviation) with

the range below.

*According to the CDI BMI Percentiles (CDC, 2009)

64

The SAS Growth Program for the CDC Growth Charts (CDC Growth Chart
Training, 2009) was used to determine the mean (m) height percentile (68th
percentile), mean (m) weight percentile (63rd percentile), and mean (m) BMI
percentile (58th percentile). When comparing the individual BMI percentile results
from the SAS Growth Program for the CDC Growth Charts (CDC Growth Chart
Training, 2009) of the participants to the CDC percentiles, results showed that 6
participants (4%) were classiﬁed as undenrveight (4 boys/6%, 2 girls/3%), 95
participants (71%) fell within the HFZ (47 boys/69%, 48 girls/71%), 20
participants (15%) were classiﬁed as ovenrveight (11 boys/16%, 9 girls/14%), and
14 participants (10%) were classiﬁed as obese (6 boys/9%, 8 girls/12%).

Each of the motor skills for the Test of Gross Motor Development-2
(TGMD—2) and the overall Iocomotor and object-control descriptive statistics are
presented in Table 3. These scores revealed that participants had slightly higher
mean scores on the object-control skills (m = 41.7 :I: 4.81) versus Iocomotor skill
scores (m = 41.11 3.40). Similar results were shown between boys and girls.
Independent t-tests revealed the mean scores for Iocomotor skills were not
signiﬁcantly different between boys and girls (p = 0.616), however, the mean
scores for the object-control skills of boys were Signiﬁcantly higher (p = 0.000),

than the mean scores for girls.

65

Table 3

Test of Gross Motor De velopment-2 Descriptive Characteristics of the Sample

 

 

Locomotor Skills n = 131 Male Female Total
Run 7.7 (0.79) 7.7 (0.78) 7.7 (0.79)
4-8 4-8 4-8
Gallop 6.1 (1.31) 6.4 (1.12) 6.3 (1.22)
3—8 4-8 3-8
Hop 8.8 (1.43) 8.8 (1.24) 8.8 (1.33)
5-10 5-10 5-10
Leap 5.1 (0.88) 5.1 (0.87) 5.1 (0.87)
4-6 3-6 3-6
Jump 6.0 (2.00) 9.0 (1.39) 6.0 (1.71)
0-8 2-8 0-8
Slide 7.2 (1.03) 7.2 (1.05) 7.2 (1.04)
4-8 4-8 4-8
Locomotor raw score 41.0 (3.70) 41.3 (3.12) 41.1 (3.40)
27-46 34-47 27-47

 

Note. Values are Mean (Standard Deviation) with the range below.

66

Table 3 (continued)

Test of Gross Motor Development-2 Descriptive Characteristics of the Sample

 

 

Object-Control Skills n = 134 Male Female Total
Strike 8.9 (1.21) 8.3 (1.62) 8.6 (1.46)
6-10 4-10 4-10
Dribble 6.6 (1.75) 5.8 (1.94) 6.2 (1.89)
0-8 1-8 0-8
Catch 5.8 (0.56) 5.8 (0.51) 5.8 (0.54)
3-6 4-6 3—6
Kick 7.5 (0.77) 7.2 (0.87) 7.3 (0.84)
5-8 5-8 5-8
Throw 7.8 (0.93) 7.0 (1.53) 7.2 (1.33)
2-8 2-8 2-8
Roll 6.9 (1.56) 6.5 (1.46) 7.0 (1.52)
2-8 2-8 2-8
Object-control raw score 43.5 (4.50) 40.5 (4.65) 42.0 (4.81)
19-48 27-48 19-48

 

Note. Values are Mean (Standard Deviation) with the range below.

67

Table 4 shows the descriptive statistics for the Self-Perception Proﬁle for
Children (only those participants with completed subscales for each of the six

domains: i.e., academic, peer acceptance, athletic, physical appearance,
behavioral conduct, and global self-worth), and estimated V02 max. The mean

of the SPPC domain scores ranged from 3.1 to 3.3 on a scale of 1 to 4, with
48.4% to 64.6% of participants having a score greater than 3.0 for the six
domains (academic 53.1%, peer acceptance 48.4%, athletic 55.6%, physical
appearance 58.3%, behavioral conduct 64.6%, and global self-worth 63.4% with
scores greater than 3.0). These results Show that many of the participants have
a fairly high perceived competence in most domains. Independent t-tests
revealed that the only signiﬁcant difference in the mean scores between boys
and girls in all six SPPC domains was in the behavioral conduct domain, in which
girls had signiﬁcant higher scores than boys (p = 0.002).

Estimated V02 max values of the participants ranged from 36.9 to 53.5

mI/kg/min. According to the FITNESSGRAM standards for the Healthy Fitness
Zone (HFZ) for the PACER test, 29.5% of the participants fell below

FITNESSGRAM standards for this test. The independent t-test revealed that

boys had a Signiﬁcantly higher mean V02 max than girls (p = 0.004).

68

Table 4

SPPC Domains & VO2 Max Descriptive Characteristics of the Sample

 

 

 

 

SPPC Domains Male Female Total
Academic n=128 3.1 (0.70) 3.1 (0.59) 3.1 (0.64)
1-4 2-4 1-4
Peer Acceptance n=120 3.2 (0.62) 3.0 (0.75) 3.1 (0.69)
2-4 1-4 1-4
Athletic n=126 3.1 (0.74) 3.0 (0.66) 3.1 (0.70)
1-4 1-4 1-4
Physical Appearance n=126 3.1 (0.72) 3.2 (0.62) 3.2 (0.67)
2-4 1-4 1-4
Behavioral Conduct n=127 3.1 (0.56) 3.4 (0.63) 3.3 (0.62)
2-4 1-4 1-4
Global Self-Worth n=123 3.3 (0.56) 3.3 (0.65) 3.3 (0.61)
2-4 1-4 1-4
Estimated VO2 Max
V02 Max (kg/ml/min) n=132 45.4 (3.53) 43.7 (2.88) 44.5 (3.31)
37-53 39-53

37-53

 

Note. Values are Mean (Standard Deviation) with the range below.

69

Partial Correlations

Both bivariate and partial correlation analyses were conducted to
determine if age was a factor in the correlation results. Bivariate correlation
results for all participants (not controlling for age) showed various signiﬁcant
correlations at both the 0.01 and 0.05 levels, and did not change signiﬁcantly

when recalculated controlling for age, using partial correlations. Therefore,
results shown in Table 5 are the partial correlations for BMI, V02 max, Iocomotor

skill performance, object-control skill performance, and all 6 SPPC domains (i.e.,
academic, peer acceptance, athletic, physical appearance, behavioral conduct,
and global self-worth), in order to control for any inﬂuence of

age. The only correlations that were signiﬁcant in the partial correlation

results that were not signiﬁcant in the bivariate correlation results were object-
control skills and the SPPC behavioral conduct domain, and the SPPC athletic
domain and the SPPC global self-worth domain. All correlation results include
participants with data from any of the testing, not those participants with only

complete data for all variables. Overall, BMI was negatively correlated with the

majority of the variables, but only signiﬁcantly with V02 max r(109) = -0.292,

p < .01 and the academic domain r(109) = -0.283, p < .01. V02 max was also

signiﬁcantly positively correlated with Iocomotor skill scores r(109) = 0.256,
p < .01, object-control skills r(109) = 0.408, p < .01, and the peer acceptance
perceived competence r( 109) = 0.229, p < .05, athletic perceived competence

r(109) = 0.245, p < .01, physical appearance perceived competence r(109) =
70

0.227, p < .05 and global self-worth r(109) = 0.207, p < .05. Locomotor skill
scores were signiﬁcantly positively correlated with object-control skills r(109) =
0.243, p < .01, and object-control skills were also positively correlated with the
athletic domain r(109) = 0.229, p < .05. The academic domain was signiﬁcantly
correlated with all of the other SPPC domains. All of the other SPPC domains
were signiﬁcantly correlated with each other, except for the peer and behavioral
conduct domain, the athletic domain and the behavioral conduct domain, the
physical appearance domain and the behavioral conduct domain, and the athletic
domain and the global self-worth domain. Correlations according to gender

showed similar results (Table 6 for boys and Table 7 for girls).

71

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Stepwise Regression

Stepwise regression analyses were conducted to determine the signiﬁcant
predictor variables for Iocomotor skills, object-control skills, BMI, V02 max, and

all six of the SPPC domains. Complete stepwise regression results are
presented in Table 8. Stepwise regression results for boys and girls are shown
in Tables 9 and 10, respectively.

The ﬁrst hypothesis stated that (a) BMI, aerobic capacity, Iocomotor and
object-control skill performance of participants would account for a signiﬁcant
percentage of the variance in athletic and physical appearance perceived
competence, but (b) would not account for a signiﬁcant percentage of variance in
the academic competence, peer acceptance, behavioral conduct, and global self-

worth. This hypothesis was partially supported. When each of the SPPC
domains was used as the criterion variable and BMI, V02 max, Iocomotor skills

and object-control skills were the predictor variables in the models, none of the
domains that emerged with predictor variables accounted for more than 10% of
the variance. Only object-control skill performance was a signiﬁcant predictor of
athletic perceived competence [adjusted R2 = 0.061, F(1, 121) = 8.844, p = .004],

and object-control skill performance and V02 max were the signiﬁcant predictors

for physical appearance perceived competence [adjusted R2 = 0.083, F(2, 115) =
6.211, p = .003]. Results supported part (b) of the hypothesis, with these four

predictor variables accounting for 4.8% to 8.9% of the variance in the academic,

75

peer acceptance, and global self-worth domains, while no signiﬁcant predictors

emerged for the behavioral conduct domain.
The gender differences revealed that V02 max, object-control skill

performance, and Iocomotor skill performance were more signiﬁcant predictors of
the SPPC domains for boys than for girls, particularly in the physical appearance

and behavioral conduct domains. For boys, object-control skill performance and

V02 max were signiﬁcant predictors of physical appearance perceived

competence [adjusted R2 = 0.202, F(2, 58) = 8.321, p = .001], and V02 max and

Iocomotor skill performance were signiﬁcant predictors in the behavioral conduct
domain [adjusted R2 = 0.134, F(2, 58) = 5.491, p = .007]. For girls, the only
predictor variables that emerged were in the academic and athletic domains.
BMI was a signiﬁcant predictor of academic perceived competence [adjusted
R2 = 0.078, F(1, 63) = 6.333, p =' .014], and Iocomotor skill performance was a
signiﬁcant predictor for athletic perceived competence [adjusted R2 = 0.073,
F(1, 62) = 5.869, p = .018]. No predictor variables emerged for the other SPPC
domains.

The second hypothesis stated that (a) BMI and Iocomotor skill
performance of participants would account for a signiﬁcant percentage of the
variance in aerobic capacity, but (b) object-control skill performance of
participants would not account for a signiﬁcant percentage of the variance in

aerobic capacity. Again, results partially supported the hypothesis, showing the

largest predictors of V02 max scores were object-control skills, BMI, and physical
76

appearance perceived competence [adjusted R2 = 0.245, F(3, 111) = 12.983, p =

.000]. When only Iocomotor and object-control skills were used as the predictor
variables, object-control skills were the signiﬁcant predictor of V02 max scores

[adjusted R2 = 0.148, F(1, 127) = 23.076, p = .000]. Physical appearance
perceived competence and object-control skill performance were the signiﬁcant
predictor variables for boys [adjusted R2 = 0.204, F(2, 55) = 8.067, p = .001], and
neither object-control nor Iocomotor skill performance were signiﬁcant predictor
variables when only those two variables were entered into the model. For girls,

BMI, object-control and Iocomotor skill performance were signiﬁcant predictor
variables of v02 max [adjusted R2 = 0.340, F(3, 55) = 10.449, p = .000], and both

object-control and Iocomotor skill performance were signiﬁcant predictor
variables when only those two were entered into the model [adjusted R2 = 0.274,
F(2, 64) = 13.079, p = .000].

The third hypothesis stated that (a) aerobic capacity, Iocomotor skill
performance, and the athletic and physical appearance perceived competence of
participants would account for a signiﬁcant percentage of the variance in BMI, but
(b) object-control skill performance, the academic competence, peer acceptance,

behavioral conduct, and global self-worth of participants would not inﬂuence the
variance in BMI. Only V02 max, academic perceived competence, and athletic

perceived competence were the signiﬁcant predictors of BMI scores [adjusted R2
= 0.158, F(3, 111) = 7.967, p = .000]. For boys, only academic perceived

competence was a signiﬁcant predictor variable of BMI [adjusted R2 = 0.066, F(1,

77

55) = 4.861, p = .032]. For girls, V02 max and academic perceived competence

were signiﬁcant predictor variables of BMI [adjusted R2 = 0.146, F(2, 55) = 5.717,
p = .006].

The fourth hypothesis stated that (a) BMI, aerobic capacity, and the
athletic and physical appearance perceived competence of participants would
account for a signiﬁcant percentage of locomotor skill performance, but (b) the
academic competence, peer acceptance, behavioral conduct, and global self-
worth of participants would not account for a signiﬁcant percentage of locomotor
skill performance. There was not strong support for this hypothesis, as V02 max
was the only signiﬁcant predictor for Iocomotor skill performance [adjusted R2 =
0.056, F(1, 112) = 7.655, p = .007]. Again, V02 max was a signiﬁcant predictor
forlocomotor skill performance even more so for girls [adjusted R2 = 0.134, F(1,
56) =“9.634, p = .003, but no signiﬁcant predictors emerged for Iocomotor skill
performance for boys.

The ﬁfth hypothesis stated (a) BMI, aerobic capacity, and the athletic and
physical appearance perceived competence of participants would account for a
signiﬁcant percentage of object-control skill performance, but (b) the academic
competence, peer acceptance, behavioral conduct, and global self-worth of
participants would not account for a signiﬁcant percentage of object-control skill

performance. This hypothesis is more strongly supported than the last
hypothesis as V02 max and the athletic perceived competence and physical

appearance perceived competence accounted for a much higher variance for
78

object-control skill performance [adjusted R2 = 0.206, F(3, 111) = 10.616, p =
.000] than the locomotor skill performance. The same variables were signiﬁcant
predictors along with peer acceptance perceived competence for object-control

skill performance for boys [adjusted R2 = 0.305, F(4, 55) = 7.025, p = .000]. Only
V02 max was a signiﬁcant predictor variable for object-control skill performance

for girls [adjusted R2 = 0.200, F(1, 55) = 14.786, p = .000].

79

 

 

 

 

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83

CHAPTER FIVE
Discussion

Stodden et al. (2008) have proposed a model that includes four main
components (motor skill competence, perceived motor competence, health-
related ﬁtness, and physical activity), which are interrelated and may ultimately
lead to the risk of obesity of children. This study explored aspects of this model
and expanded the perceived motor competence variable to different domains of
perceived competence. The overall purpose of this study was to examine the
relationship among fundamental motor skill development (of both Iocomotor and
object-control skills), health-related ﬁtness level (measured by aerobic capacity
and body composition), and perceived competence (measured by
subscales/domains) of fourth grade male and female students.

Due to the complex relationships amongst the variables, stepwise
regression analyses were conducted to determine which variables predicted a
signiﬁcant percentage of the variance of other variables. Overall, a small percent
of the variance was explained for any variable; thus, additional factors (e.g.,
genetics, social inﬂuence, practice, opportunity, environment) contribute to motor
skill development, health-related ﬁtness levels, and perceived competence of
youth. These factors will be discussed throughout this chapter.

Object-control skill performance consistently emerged as a signiﬁcant
predictor of the dependent variables. In the total sample, object-control skill

performance was a signiﬁcant predictor for athletic perceived competence

84

(adjusted R2 = 0.023), physical appearance perceived competence (adjusted R2
= 0.046) and V02 max (adjusted R2 = 0.137). The results were similar for boys.
ln girls, object-control skill performance predicted even more of the variance for
V02 max than for the total sample. These ﬁndings are in contrast to previous

research which has linked Iocomotor skill performance with aerobic capacity and
BMI more so than object-control skill performance (Hands, 2008; Okely, Booth, &
Chey, 2004). Only Iocomotor skill performance was a signiﬁcant predictor for
athletic perceived competence in girls. The inﬂuence of object-control skill
development on athletic perceived competence is not surprising since the ability
to control implements such as bats, balls, or gloves is an important aspect of
many sports (e.g., baseball, softball, basketball). In early to middle childhood,
children usually acquire more competitive behaviors and begin to use social
comparison to peers as a way of judging their competence (Weiss & Stuntz,
2004). Such comparisons may inﬂuence the importance of the athletic domain
(and the peer acceptance domain which was also a signiﬁcant predictor). Youth
sport is becoming more specialized and children are often expected to perform at
a high level at young ages. In turn, there are motor skill, sociological, and
psychological consequences related to sport specialization (Wiersma, 2000).
These consequences could result in a lowered perceived athletic competence.
However, children can clearly distinguish between their abilities in each of the six
domains of the SPPC by middle to late childhood (ages 8 to 11; Hom, 2004) and

have more realistic evaluations of the self (Harter, 1982). Therefore, actual and

85

perceived competences are more similar to each other than they were in early
childhood.

Boys also had a signiﬁcantly higher mean object-control skill performance
score than girls, while there was no difference in the mean Iocomotor skill
performance score. These ﬁndings are somewhat supported by the current
literature. Researchers have reported that the difference between boys’ and
girls’ performance of motor skills is minimal before puberty (Thomas & French,
1985). In contrast, Hume et al. (2008) found that more 9-12 year old boys
achieved mastery/near mastery in object-control skills compared to same age
girls, which supports the ﬁndings from the current study. Boys may have
signiﬁcantly higher scores on object-control skills because many of the organized
sports in which they engage involve object-control skills.

Gender differences in motor performance in elementary school children
may be largely socialized by parents (Thomas & French, 1985). In addition, the
lack of opportunities and the low expectations for a girl’s performance as
compared to boy’s in a skill such as throwing may have negative consequences
for females as they enter puberty (Thomas & Thomas, 2008). Sports that require
more vigorous movements and a greater use of space are often considered
masculine and often require objects to be manipulated; however, girls possess
the physical capabilities to perform well in all kinds of movement activities
(Duncan, 1993). The choice of organized physical activity (whether the child’s

choice or not) may also contribute to the gender difference in object-control skill

86

and lack of gender difference in Iocomotor skills. Children participate in
organized physical activity for a number of reasons including social inﬂuence,
sport availability and opportunity for boys and girls, and motivation, among other
factors. Barnett, van Beurden, Morgan, Brooks, and Beard (2008) found that the
most reported organized sport activities in summer and winter for boys ages 8 to
12 in Australia were football, soccer, hockey, baseball, basketball, cricket, and
squash. For girls ages 8 to 12, the favorites were netball, soccer, hockey, dance,
aerobics, swimming, and football. In this particular study, the most popular
activities for boys were ones that all required object-control skills and various
Iocomotor skills (Barnett et al., 2008). Girls participate in some sports that do not
require object-control (e.g., swimming, dance, aerobics) as well as some sports
that require object-control skills (Barnett et al., 2008). Girls might not get as
much practice with object-control skills, therefore, and the mean differences in
performance may increase over time.

Fundamental motor skill development in childhood has been shown to be
an important facet for encouraging physical activity and preventing and treating
childhood obesity by increasing actual and perceived physical competence of
children (NSW Department of Health, 2003). According to the results from the
current study, it may be beneﬁcial to focus more on object-control skill
development than Iocomotor skill development in middle childhood. By doing so,
children’s feelings of perceived competence in the athletic and physical

appearance domains may improve. In addition, object-control skills are

87

signiﬁcantly correlated with aerobic capacity not only in childhood (Frey 8r Chow,
2006), but object-control proﬁciency in childhood is also associated with
adolescent cardioreSpiratory ﬁtness (Barnett et al., 2008). Fundamental motor
skill development in the primary school years is important in promoting
adolescent and long-term ﬁtness (Barnett et al., 2008). Seefeldt and
Haubenstricker’s (1982) research on the age at which sixty percent of boys and
girls perform at a speciﬁc developmental level for both Iocomotor and object-
control skills supports this idea as well. In middle childhood, children have
typically reached the highest developmental level for most Iocomotor skills (e.g.,
mnning) that are needed for playing sports/games that require object-control.
The Iocomotor skills in which they have not reached the highest developmental
level (e.g., long jumping, hopping on one leg) are not as important to excel in to
participate in most sports/games. Thelen and Ulrich (1991) use dynamical
systems theory to explain that new forms in behavior emerge from the
cooperative interactions of multiple components within a task context. The
component parts interact among themselves and also with the environment in
order to cause movement patterns, control, and coordination (Payne & Isaacs,
2008). Therefore, it may be beneﬁcial in Stodden’s model (2008) to partial the
motor competence inﬂuence into Iocomotor development early in childhood
(when the locomotor component is more important than object-control skills) and
object-control development during the middle to later childhood ages (when the

object-control component is more important than Iocomotor skills).

88

Another interesting ﬁnding in this study was that although various
predictors of BMI emerged, only academic perceived competence was a
signiﬁcant predictor of BMI. Research has shown a negative association
between obesity/high BMI and academic performance of children and
adolescents (Datar, Sturm, & Magnabosco, 2004; Kristjansson, Sigfusdottir, &
Allegrante, 2010; Sabia, 2007; Schwimmer, Bunlvinkle, & Vami, 2003). If children
are performing better on schoolwork, their academic perceived competence will
likely increase (Wagner & Phillips, 1992). However, until recently, little evidence
existed suggesting a cause and effect relationship between obesity and
academic performance. Cho, Lambert, Kim, and Kim (2009) found that poor
school performance increases the risks of adolescents becoming overweight,
which in turn causes poor school performance. The current study supports this
relationship as well; when academic perceived competence was the dependent
variable, BMI was a signiﬁcant predictor. Results from a study examining the
effect of a school-based obesity prevention intervention on weight and academic
performance among low income children found that the children participating in
the 2-year intervention had higher math and reading scores and weight
decreases than the control group (Hollar et al., 2010). In addition, increasing
academic performance may be especially important for females as they enter
adulthood. Alatupa et al. (2010) found that low grade point averages of students
in early and middle adolescence may be a risk factor of adulthood obesity, but

only among women. In contrast, Franklin et al. (2006) found that obesity typically

89

does not impact academic achievement in grades 5 and 6 (sample age range
9.2-13.7 years, m = 11.3 years).

Due to the lack of cause and effect relationships in the literature (as well
as many possibilities for why overweight may inﬂuence academic performance),
more research should be conducted examining the BMI and academic
competence/perceived academic competence area to determine how and why
this relationship may or may not exist. Among the ﬁrst of the researchers to
investigate the relationship, Ratey (2008) identiﬁed that exercise increases brain
derived neurotropic factor (BDNF) levels in the brain, a key element in cognitive
function. Spirduso, Poon, and Chodzko-Zajko (2007) proposed that potential
mediators between physical activity and cognition (i.e., Ieaming, retrieval,
attention, executive function, problem solving, and information processing speed)
include sleep effectiveness, energy/fatigue, nutrition, mental health and certain
disease states. Therefore, if children are more physically active and regularly
exercise, they are more likely to sleep better, have more energy, have higher
self-efﬁcacy, and are less likely to have diseases such as Type 2 diabetes. This
impact will lead to better concentration/attention, lower absentee levels, and
overall, an increased ability to learn, improving academic performance.

Although most of the participants fell within the FT G HFZ for BMI or
normal weight category, there were still children who were considered oven/veight
or obese. The most recent national estimates indicate that 35.5% of children

ages 6 to 11 are overweight and 19.6% are considered obese (Ogden, Carroll,

90

Curtin, Lamb, 8. Flegal, 2010). In the current study, 14.8% of the participants
were overweight and 10.4% were obese. For exploratory purposes, descriptive
statistics for aerobic capacity, motor skill performance, and perceived
competence were compared for the overweight and obese group to the normal

weight subjects. Results showed that the ovenrveight and obese participants had
a lower mean V02 max (43.3 v. 44.5 kg/ml/min), Iocomotor skill performance

(40.1 v. 41.1), object-control skill performance (40.5 v. 42.0), and perceived
competence in the academic (2.9 v. 3.1), peer acceptance (3.0 v. 3.1), physical
appearance (3.1 v. 3.2), and global self-worth (3.2 v. 3.3) domains. The means
of the two groups for the athletic and behavioral conduct perceived competence
domains were similar. Additional analyses were not conducted due to the small
sample size. However, these preliminary results show that the overweight and .
obese population of children and adolescents is an important group to investigate
and more interventions should be administered in schools for both the students
and their parents.

Overall, the ﬁndings support various components of the model proposed
by Stodden et al. (2008). Speciﬁcally, actual motor performance, health-related
ﬁtness (as measured by aerobic capacity and BMI), and perceived competence
(in the academic, athletic, and physical appearance domains) emerged as the
signiﬁcant predictors. Therefore, perceived competence in the model should
perhaps consider the academic, athletic, and physical appearance domains and

not just generic perceived motor competence. Likewise, the perceived

91

competences and health-related ﬁtness variables may be more than mediators to
physical activity participation; they may directly inﬂuence skill outcomes. If
children have higher perceived competence in different areas, have higher
ﬁtness levels, and have lower BMls, they may be more likely to be physical
active. Therefore, obesity is also probably a signiﬁcant factor of the main part of
the model and should be included within those relationships as well. In the model
proposed by Stodden et al. (2008), the risk of obesity is the primary outcome of
the interrelationships among these variables that feeds back into the model. Due
to the gender differences found in the current study, two separate models should
also be created for boys and girls in middle to late childhood. Figures 2 and 3
reﬂect proposed models for boys and girls, respectively, based on ﬁndings from
the current study.

These two models show that some variables are bi-directional
relationships (depicted by an arrow on each end of the line), while others are only
a one-way relationship (depicted by a line ending in an arrow). The three dashed
lines from each general variable (i.e., motor skill performance, perceived
competence, and health-related ﬁtness) to physical activity are showing that
there is a possible relationship. Unfortunately, physical activity was not
measured in this study. In addition, note that the ﬁgures are different for boys
and girls and are speciﬁc to fourth grade children. In younger children the

relationships may be different. For example, Iocomotor skill performance may

92

Figure 2

Revised Stodden et al. (2008) Model for Fourth Grade Boys

 

Perceived
Competence

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Academic <
>Athletic

 

Physical Appearance
A

 

 

A

 

Motor Skill Development

 

Locomotor

 

 

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Fitness

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Aerobic Capacity
BMI

 

 

 

J

 

 

Figure 3

Revised Stodden et al. (2008) Model for Fourth Grade Girls

 

Perceived
Competence

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q

 

 

Athletic
Physical Appearance

 

Academic ‘—_‘

 

 

 

Motor Skill Development

 

 

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93

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ﬂ

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have been a more signiﬁcant predictor because children typically Ieam and
become more proﬁcient in most of these skills at a younger age. Perceived
competence in the different domains may also have been different as younger
children do not have as accurate actual competence related to their perceived
competence.

These models should also include potential mediators such as race/
ethnicity, socioeconomic status, genetics, social inﬂuence, practice, opportunity,
and environment. The general importance of these variables was discussed in
relation to physical activity throughout the review of literature and in this chapter.
Strengths of the Study

There were three main strengths in this study. First, although previous
research has examined the relationships between ﬁtness and motor skills, motor
skills and perceived competence, and ﬁtness and perceived competence, few
studies have simultaneously considered these three sets of variables. Secondly,
the same trained and experienced researcher analyzed all the videos of the
participants performing the locomotor and object-control skills in the TGMD-2 to
ensure consistency of the scoring. Barnett and colleagues (2009) explained that
during observation in a ﬁeld setting, such as the one used in this study, multiple
raters may assess fundamental motor skill proﬁciency of the participants without
compalison to an expert rating. The overall reliability of the raters is important,
though. Videotaping all the skills eliminated the need for multiple raters and

assessment of the performances during the ﬁeld test. The researcher’s scoring

94

was compared to an expert’s scoring, therefore increasing the overall reliability of
the TGMD-2 in the study.

Third, while BMI may not be the best measure of body composition, direct
assessment of height and weight of the participants is a strength as opposed to
using self-reported data. Elgar, Roberts, Tudor-Smith, and Moore (2005) stated
that self-report bias is not always accurate for predicting ovenrveight and obesity
of adolescents and actual and perceived body size contribute to underreporting
body weight. Jansen and colleagues (2006) agree that self-reported height and
weight of children led to an underestimation of BMI and, therefore, an
underestimation of the prevalence of overweight. In ﬁeld settings, BMI is the
most practical method of determining body composition. It is convenient, less
expensive than laboratory measures, not intrusive, and easy to calculate.

Therefore, BMI should be incorporated where meaningful to study questions.
Limitations

Several limitations may inﬂuence the results of this study. The sample of
fourth grade children was not diverse with regards to race/ethnicity and
socioeconomic status. Participants were primarily Caucasian and from middle to
upper class families. Race/ethnicity may play a role in body composition, ﬁtness,
motor skill performance, and perceived competence. Youth from low
socioeconomic status families may be less active than those from middle or high
socioeconomic status families, therefore inﬂuencing ﬁtness levels and motor skill

performance (Sallis, Zakalian, Hovell, & Hofstetter, 1996). For children from low-

95

income families, physical education may be their only opportunity to practice and
acquire fundamental motor skills (Thomas, Thomas, & Williams, 2008). For
example, children from higher SES environments may have access to private
lessons, more choices of movement activities, or ﬁnancial means to enroll in high
cost activities that impact skill development. Therefore, these relationships
should be examined in a more diverse sample.

The participants were from three schools chosen by convenience.
Randomly selected schools would have made the results stronger. However, the
support of the principal, physical education teacher, and, in one case, approval of
the superintendent were needed beforeeven distributing parental consent forms.
These requirements made choosing schools at random a challenge. Because
the participants were from three schools, there were three different physical
education teachers and one physical education intern involved with the classes.
Experience of the instructors in physical education classes may greatly inﬂuence
a child’s motor skill development, ﬁtness levels, and perceived competence. In
addition, physical education classes may vary in time provided for physical
education, quality of the curriculum, and the emphasis placed on physical activity
and motor skill development. Robinson and Goodway (2009) found that
signiﬁcant motor development gains are obtained from well-designed and
developmentally appropriate motor skill interventions regardless of instructional
climate. Other researchers have found the teacher’s role in providing feedback

and reinforcement is important as well (Bunker, 1991), especially when using

96

mastery climate instructional approaches (Robinson, Rudisill, & Goodway, 2009).
Thomas and Thomas (2008) add that the curriculum in elementary school should
begin with fundamental skills, and then build to transitional skills.

The physical education teachers at these three schools were all certiﬁed in
physical education, taught a curricula which included a focus on motor skills, and
emphasized the importance of physical activity. One physical education teacher
even said before the children performed a particular skill, “They should be good
at this one; they just practiced it last week!” Physical education time
requirements for these three schools were twice a week for 35-40 minutes per
class. In schools with less required physical education time, inexperienced
physical education teachers, classroom teachers who teach physical education,
or a poorly constructed curriculum results, may have been different. 8

Physical activity outside of school may account for some of the positive
results and should be considered in future research. Many students were
discussing playing sports outside of school and involvement in physical activity
with their families and friends. However, this information was not captured
systematically.

The time of data collection during the school year may be a factor,
especially ﬁtness tests. Children improve on ﬁtness tests from fall to the spring
because of growth and development, but also because of practice from the
physical education classes (Thomas & Thomas, 2008). Because the data

collection occurred in February to March, scores might have been different than if

97

testing had occurred in early fall, depending on the physical activity levels of
participants during the summer vacation. For example, Butterﬁeld, Lehnhard,
Mason, McCormick (2008) found that regardless of age, sex, BMI, or sports
participation, the PACER scores of the children signiﬁcantly increased during the
school year, decreased over the summer, and returned to the original slope the
following year. Participants from some classes were also more familiar with the
PACER test measuring aerobic capacity than participants in other classes, and
therefore, that experience could have affected the results.

The teacher involvement in parental consent form distribution and
collection may have inﬂuenced the completion of parental consent forms of the
participants. All three physical education teachers involved in this study were
experienced and enthusiastic about physical activity and providing the children
with the skills needed for a healthy lifestyle. However, the return rate (84%) for
parental consent forms was the highest from the physical education teacher who
was in full support of the study and encouraged the parents to allow their children
to participate. The other two physical education teachers did not put as much
emphasis on participation, and the return rates for Schools A and B were 50%
and 57%, respectively. The classroom teachers who were more interested in the
study and the implications of the results also seemed to promote participation in
their classrooms and more parental consent forms were received from the

students in their classes.

98

BMI is not the best measure of body composition because it is only a
measure of the relationship between height and weight and does not account for
weight from muscle as opposed to fat. It is not as effective in identifying
moderately overweight children as other methods of measuring body composition
since it does not account for muscle mass (Lohman & Going, 1998). However,
BMI is one of the two options of body composition tests used in the
FITNESSGRAM, and is often used in ﬁeld settings such as elementary schools.
Research comparing BMI with other body composition tests of children has
shown that BMI offered a reasonable measure to assess body fat in children and
adolescents and that the standards used to identify overweight and obesity in

children and adolescents should agree with the standards used to identify grade
1 and grade 2 overweight (BMI of 25 kg/m2 and 30 kg/m2, respectively) in adults

(Dietz & Bellizzi, 1999; Pietrobelli et al., 1998). In addition, recent systematic
reviews are supportive of current guidelines that recommend percentile-based
cut-off points relative to national reference data to deﬁne obesity for children and
adolescents (Reilly, 2010).
Implications for Future Research

This study has shown the importance of the relationships among ﬁtness,
motor skill performance, and perceived competence. These relationships should
continue to be investigated in order to determine how best to help youth excel in
these areas and overall increase physical activity participation and decrease

childhood obesity. There are many implications for future research.

99

A more diverse sample should be used when conducting a study with
these variables. Different races/ethnicities should be included in the sample, as
well as children from a lower socioeconomic status. This study was conducted in
Michigan; therefore, replicating this study in other areas of the United States and
also in other countries would be helpful to determine any differences. Goodway,
Robinson, and Crowe (2010) found that boys outperformed girls on both
Iocomotor and object-control skill performance in the midwestem and
southwestern regions, and children in the midwestem regions had better
Iocomotor skills than those children in other regions. Therefore, geographic
region may also have implications for motor skill development.

Future research should also examine the other variables, such as physical
activity, in the model proposed by Stodden and colleagues (2008). Mixed results
have been found for the relationship between physical activity and motor skill
performance. Fisher et al. (2005) found that fundamental motor skills (15 tasks
based on the Movement Assessment Battery) of preschool children were
signiﬁcantly associated with their habitual physical activity (time spent in
moderate-to-vigorous physical activity and total physical activity), but the
association between the two variables was weak (r = 0.18 for the time spent in
moderate-to-vigorous physical activity measurement and r = 0.10 for the total
physical activity measurement). Okely, Booth, and Patterson (2001) found a
similar relationship when examining the fundamental motor skills and physical

activity of adolescents.

100

Additional factors that may inﬂuence these variables, such as social
inﬂuence, the effects of practice, environment, and opportunities because the
activities youth participate in outside of school will inﬂuence aerobic capacity,
body composition, motor skill performance, and perceived competence, should
be examined. Okely, Booth, and Patterson (2001) and Ulrich (1987) found that
adolescents in grades 8 and 10 and children in grades K through 4, respectively,
who performed better on motor skills spent more time in organized physical
activity. The amount of time children spend practicing within organized or
recreational activities will make a difference in performance levels as well.
Before puberty, poor performance for both boys and girls is largely due to lack of
practice rather than growth and development factors (Thomas & Thomas, 2008).

This study included experienced and well-educated physical education
teachers; therefore, it would be interesting to include participants who receive
physical education instruction from classroom teachers who are not trained in
physical education. Physical education classes should be taught by certiﬁed
physical education teachers or, in elementary school, at least classroom teachers
who have received special training in physical ﬁtness education (Simons-Morton,
1988). The motor skills and ﬁtness levels of children who do not receive
adequate and developmentally appropriate instruction may suffer othenlvise.

Conclusion
“The present study adds to the knowledge base concerning the importance

of motor skill performance, ﬁtness levels, and perceived competence of children

101

and adolescents. More research is needed to determine the relationship of these
variables in other populations and the inﬂuence of these variables on physical
activity levels and childhood obesity. However, results from this study show
children and adolescents should strive for a healthy BMl, increase their aerobic
capacity, and engage in fundamental motor skill development (especially object-
control skill development) at a young age. Parents, teachers, and coaches
should encourage this behavior as well as focusing on enhancing the children
and adolescents’ academic and athletic competence because at this age, the
actual and perceived competence is similar. Speciﬁcally, relationships in Figures
2 and 3 should be considered for boys and girls in order to encourage

recommended levels of physical activity participation.

102

APPENDICES

103

APPENDIX A

Letter to Parents

104

Cover Letter for Parents
January 15, 2010
Dear Parents:

We are entering a research endeavor with individuals in the Department of
Kinesiology at Michigan State University. This research will beneﬁt the students
by providing important information on the children’s motor skill development,
physical activity behaviors, health-related ﬁtness, and feelings of self-
competence. The data will help the researchers analyze the proposed link
between motor skill development, physical activity, self-competence, and health-
related ﬁtness. These variables are important to consider for the overall health
and well-being of children and youth. The data also will provide — with
information that will help her assess the effectiveness of the physical education
program.

The study has been approved by the Institutional Review Board at
Michigan State University indicating that the procedures are safe and that the
rights of human subjects have been protected. All relevant school policies will be
followed. The children will spend about 15-30 minutes ﬁlling out a questionnaire;
they will spend physical education class time performing a running test and basic

Skills such as jumping, skipping, hopping, running, and catching. All students will
b articipate in the running and motor skill activities as part of the physical
education class period, but they will not be videotaped or have their scores

recorded unless they have completed parental consent forms. Height and weight

105

measurements will also be taken behind a portable screen in the gym.
Participants will be measured individually to ensure conﬁdentiality and will be
asked to step on the scale facing away from the digital display so they will not
see their weight. Measurements will be recorded without verbalizing. -
will oversee the classes, while the researchers will score the performances of the
children. The motor skills will be videotaped and scored later for efﬁciency.
Participants will also be asked to wear a device that measures physical activity
for one week; this device is worn on the upper arm under the participant’s
clothing and is small and unobtmsive. Participation is voluntary and children may
withdraw from the study at any time.

We fully support this joint endeavor and ask that you consider providing
consent for your child to participate by signing the enclosed form and having your
son/daughter return it to the classroom teacher. Please contact Sheila Kelly or

Kyle Morrison, the MSU doctoral students conducting this study for their

 

dissertation, if you have questions at kellyshe@msu.edu or -;

morri310@msu.edu or —.

Sincerely,

Principal Physical Education Teacher

106

APPENDIX B

Parental Consent Form

107

Parental Consent Form

Project Title: The relationship among motor skill development, physical activity,
aerobic capacity, body composition, and perceived competence of fourth grade
school children.

Your child’s school has agreed to take part in a research study being conducted
by Sheila Kelly and Kyle Morrison, both doctoral students, under the supervision
of Dr. Crystal Branta from the Department of Kinesiology at Michigan State
University. The purpose of this study is to investigate the relationship between
fundamental motor skill level, physical activity, health—related ﬁtness, and
perceived competence to determine how these factors may interact to inﬂuence
healthy activity of children. Only children in fourth grade will be included.
Students who are not capable of fundamental motor skills due to physical
disability will not be able to participate.

Research studies have both beneﬁts and risks of participation. The beneﬁts of
this research include: understanding the relationship between motor skill
development and ﬁtness of children, determining if a child’s self-competence is
inﬂuenced by skill and ﬁtness, and providing data to improve physical education
at your child’s elementary school. General results from this study (as a group, not
individual results) will be given to the principal, the physical education teacher,
and any interested parents. The risks are minimal, but include potentially raising
the child’s awareness of their competencies related to others. All instruments
have been validated and used with hundreds of children without experiencing
any of the potential risks.

Participation in this study will involve a survey, which will take 15-30 minutes in
the classroom as a group to complete. Questions will focus on your child’s
perceived competence related to school, sports, social interactions, physical
appearance, and behavioral conduct. Participation will also include a
fundamental motor test assessing basic Iocomotor skills and object-control skills,
a running test, and height and weight measurements. This testing will take
during physical education class periods. One physical education class period
(30-40 minutes) will involve testing Iocomotor skills (run, gallop, hop, leap,
horizontal jump), one class period (30-40 minutes) will involve testing object-
control skills (striking a stationary ball, stationary dribble, catch, kick, overhand
throw, underhand roll), and part of one class period (less than 30 minutes) will
involve the running test to measure aerobic capacity and taking height/weight
measurements. We plan to videotape the motor tests for efﬁciency and score the
tests later. Your child will also be asked to wear an activity monitor that measures
physical activity for one week; this device is worn on the upper arm under the
clothing and is unobtrusive and the size of an mp3 player (iPod). This activity
monitor is not to be worn during water activities including showers. These

108

fundamental Iocomotor and object-control skills listed above and the mnning test
will be part of regular physical education classroom activities, but we are
requesting permission to record and use this data for research purposes. If you
do not sign the consent form, your child’s height and weight will not be taken or
recorded, he/she will not receive an armband to measure physical activity, and
he/she will not complete the survey portion of the study. Students who do not
have completed parental consent forms or who do not give assent will be asked
to read or do other work during class when the survey is given.

Responses to the survey and results to motor skills test and physical activity
assessment will remain conﬁdential. No one except the investigators and the
Institutional Review Board will have access to these responses. Results will be
based on the answers given by all participants as a group, insuring conﬁdentiality
to individual responses. Your child’s conﬁdentiality will be protected to the
maximum extent allowable bylaw. Written and electronic records will be kept in
the primary investigator’s locked ﬁle cabinet and in a password-protected
computer ﬁle for three years following the ﬁnal completion of the study and then
destroyed.

Although the running test and motor skill activities are common in a physical
education setting, please be aware of the university policy. If your child is injured
as a result of their participation in this research project, Michigan State University
will assist you in obtaining emergency care, if necessary, for your child’s
research related injuries. If you have insurance for medical care, your insurance
carrier will be billed in the ordinary manner. As with any medical insurance, any
costs that are not covered or in excess of what are paid by your insurance,
including deductibles, will be your responsibility. The University's policy is not to
provide ﬁnancial compensation for lost wages, disability, pain or discomfort,
unless required by law to do so. This does not mean that you are giving up any
legal rights you may have. If you have concerns or questions about this study,
such as scientiﬁc issues, how to do any part of it, or to report an injury, please
contact Sheila Kell at or by e-mail at kellyshe@msu.edu, Kyle
Morrison at or morri310@msu.edu, or the primary investigator Dr.
Crystal Branta at or by e-mail at cbranta@msu.edu. You may
contact any of us by regular mail at: 134 IM Circle, Dept. of Kinesiology, MSU,
East Lansing, MI 48824.

 
  
 
 

Your child’s participation in this study would be greatly appreciated. However,
please know that participation is voluntary and he or she may withdraw from
participation at any time without penalty. Furthermore, he or she may refuse to
answer speciﬁc questions on the survey or elect not to participate in a ﬁtness or
motor skill test if your child feels uncomfortable, and still be part of the study. If
you have any questions or concerns about your role and rights as the parent of a
research participant, would like to obtain information or offer input, or would like

109

to register a complaint about this research study, you may contact, anonymously
if you wish, the Michigan State University Human Research Protection Program

at 517-355-2180, FAX 517-432-4503, or e-mail irb@msu.edu, or regular mail at:
207 Olds Hall, MSU, East Lansing, MI 48824.

Thank you for your time and cooperation,

Your signature below indicates that you DO wish for your child to participate in
this study.

 

 

Parent’s Signature Date

I grant permission for the motor skills testing to be videotaped.

 

 

Parent’s Signature Date

 

Child’s Name (Please Print)

110

APPENDIX C

Participant Assent Form

111

Assent Form

Project Title: The relationship among motor skill development, physical activity,
aerobic capacity, body composition, and perceived competence of fourth grade
school children.

Your principal and teachers have agreed to take part in a research study being
conducted by Sheila Kelly and Kyle Morrison, students from Michigan State
University. The purpose of this study is to look at your motor skill level, physical
activity behaviors, physical ﬁtness, and feelings about your abilities.

If you want to participate in this study you will take a survey about your feelings
about school, sports, social interactions, physical appearance, and behavioral
conduct. Participation will also include a running test, height and weight
measurements, and fundamental motor skill tests. One PE class (30-40 minutes)
will involve testing Iocomotor skills (run, gallop, hop, leap, horizontal jump), one
PE class (30-40 minutes) will involve testing object-control skills (striking a
stationary ball, stationary dribble, catch, kick, overhand throw, underhand roll),
and part of one PE class (less than 30 minutes) will involve the running test and
taking height/weight measurements. You will participate in the running and
motor skill activities in PE class, but if you do not agree we will not write down or
videotape your tests. If you do not want to take the survey, you will read or do
other work while your classmates take the survey. You will also be asked to
Wear a small armband that measures your physical activity for one week. If you
do not want to wear the armband or have your height or weight measurements
taken, you can say no.

No one except the MSU researchers will see your responses and scores. Your
principal, teachers, and classmates will not see any of your responses or scores.

Your participation in this study would be really helpful, but you can choose if you
want to participate in the study or not. You may also decide you do not want to
participate at any time, or you can decide not to participate in certain tests or
answer certain questions at any time without anyone getting mad. If you have
questions about this, please talk to one of the Michigan State students. If you
wish to participate, please follow the directions of the leader and complete the
form.

Sign below if you agree to be videotaped and participate in the study.

 

 

Participant’s Signature Date

112

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113

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