1. UNIVERSITY OF WISCONSIN-LA CROSSE
Graduate Studies
INTERPERSONAL PREDICTORS OF ADOLESCENTS’ PHYSICAL ACTIVITY
BEHAVIOR IN PHYSICAL EDUCATION
A Manuscript Style Thesis Submitted in Partial Fulfillment of the Requirements for the
Degree of Master of Science in Exercise and Sport Science-Physical Education Teaching
Christopher M. Kear
College of Science and Health
Adventure Education
August, 2014

2. INTERPERSONAL PREDICTORS OF ADOLESCENTS’ PHYSICAL ACTIVITY
BEHAVIOR IN PHYSICAL EDUCATION
By Christopher Kear
We recommend acceptance of this thesis in partial fulfillment of the candidate’s
requirements for the degree of Master of Science in Exercise and Sport Science: Physical
Education Teaching-Adventure Education Emphasis.
The candidate has completed the oral defense of the thesis.
_________________________________
Jooyeon Jin, Ph.D.
Thesis Committee Chairperson
__________
Date
_________________________________
Teri Hepler, Ph.D.
Thesis Committee Member
__________
Date
_________________________________
Alessandro Quartiroli, Ph.D.
Thesis Committee Member
__________
Date
Thesis accepted
_________________________________
Steven Simpson, Ph.D.
Graduate Studies Director
__________
Date

3. iii
ABSTRACT
Kear, C.M. Interpersonal predictors of adolescents’ physical activity behavior in physical
education. MS in Exercise and Sport Science-Physical Education Teaching, Adventure
Education emphasis, August 2014, 58pp. (J. Jin)
Adolescents are not adequately physically active within physical education (PE) to gain
health benefits. The Theory of Triadic Influence (TTI) has been used in many fields to
change human behavior, but it has not been used in PE to change physical activity (PA)
behavior. The purpose of the study was to examine the capability of the extended TTI’s
social stream to predict adolescents’ PA in a PE setting. Participants (N=71) were 14-16
years old adolescents at a High school in state of Wisconsin. Paper-and-pencil
questionnaires were used to assess the TTI-based interpersonal PA predictors. Following
this survey, an Actigraph GT3X+ accelerometer was worn on the participant’s hip to
monitor his/her PA levels during five consecutive PE lessons. Participants played flag
football each day for the duration of the PE lesson. The results showed that TTI’s social
constructs predicted adolescents’ PA intentions, but not their PA levels. Future study
should consider possible additional mediators and/or moderators to predict adolescents’’
PA behavior in a PE class.

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ACKNOWLEDGEMENTS
The author would like to acknowledge the support of his friends and family. In
addition thanks to be given to the committee members of this thesis Jeff Steffen,
Alessandro Quartiroli and Teri Hepler. A thanks to Holmen High School, the teachers
and students who took part in the study for their cooperation, help and support throughout
the period of time for testing. Finally special thanks to Dr. Jooyeon Jin, Assistant
Professor at the University of Wisconsin- La Crosse, who provided guidance and support
throughout this thesis.

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TABLE OF CONTENTS
PAGE
INTRODUCTION………………………………………………………..................... 1
Figure 1. Extended social/normative stream of the TTI………………………... 6
Hypothesis……………………………………………………………………… 6
Delimitations……………………………………………………………………. 7
Limitations……………………………………………………………………… 7
Operational Definitions………………………………………………………… 8
METHOD…………………………………………………………………………….. 9
Participants……………………………………………………………………... 9
Instruments……………………………………………………………………... 9
Survey Questionnaire………………………………………………………
Social Situation………………………………………………………..
Interpersonal Bonding………………………………………………....
Others Behavior and Attitude…………………………………………
Perceived Norms………………………………………………………
Motivation to Comply…………………………………………………
Social Normative Believes…………………………………………….
Goal Intention………………………………………………………....
Implementation Intention……………………………………………...
Accelerometers……………………………………………………………..
Procedures……………………………………………………………………….
9
11
12
12
12
12
13
13
13
13
14
Analysis………………………………………………………………………… 15

6. vi
RESULTS…………………………………………………………………………….. 16
Figure 2. Participants’ daily physical activity participation……………………. 17
DISCUSSION………………………………………………………………………… 21
CONCLUSION……………………………………………………………………….. 25
REFERNCES…………………………………………………………………………. 26
APPENDICES………………………………………………………………………... 32
APPENDIX A: Survey Instrument…………………………………………….. 33
APPENDIX B: Review of the Literature………………………………………. 36

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LIST OF TABLES
TABLE PAGE
1. Internal consistencies of TTI constructs pilot studies…………………………... 11
2. Descriptive statistics and internal consistencies of TTI constructs…………….. 17
3. Inter-correlations of the study variables………………………………………... 17

8. 1
INTRODUCTION
Regular physical activity (PA) participation for adolescents has been considered
to be critical, as it is closely associated with numerous health benefits, such as decreasing
adiposity and increasing self-esteem, as well as contributing to bone strength and skeletal
development (Strong, et al., 2005; US Department of Health and Human Services, 2008).
In addition, being physically active during adolescence establishes healthy lifestyle
patterns that will reduce health problems (e.g., chronic diseases) in later life (Barnekow-
Bergkvist, Heinberg, Janlert, Jansson, 2008; Ducan, Duncan, Strycker & Chaumeton,
2007; Mummery, Spence, & Hudec, 2000). The American Physical Activity Guideline
(U.S. Department of Health and Human Services, 2008) requires that all adolescents
should participate in moderate to vigorous PA at least 60 minutes each day, however
many adolescents are not physically active and not meeting the guideline (Maturo &
Cunningham, 2013). While there are numerous factors to determine adolescents’ PA
behavior, understanding their social context is one of important key aspects for
promoting their PA (Davidson, 2004; Dishman, Salis, & Orenstein, 1985; Fein,
Plotnikoff, Wild, & Spence, 2004; Maturo & Cunningham, 2013).
Social context refers to the immediate physical and social setting in which people
live or in which something happens or develops (Barnett & Casper, 2001). Social
influences on PA can occur throughout life (Springer, Kelder, & Hoelscher, 2006).
Family, teachers and friends are major social agents who significantly influence youths’
PA behavior. For example, an adolescent may not be physically active if his/her parents

9. 2
are not able to afford the equipment to play the sport that he/she wants to participate in or
don’t have the means of transport to get to practices and games. Similarly, if a physical
education (PE) teacher does not emphasize the importance of PA and does not provide
adequate PA opportunities, the students are more likely not to be physically active in and
outside of the PE class. In addition, peer influence of adolescents should be investigated
equally, as both childhood and adolescence are formative periods when friends are a
primary point of reference (Adler & Adler, 2008).
Many studies have shown that interpersonal influences of parents, siblings, PE
teachers, and peers are all positively associated with PA levels of adolescents with and
without related mediators (Fein., et al, 2004). Ornelas, Perreira, and Ayala (2007) showed
that parents had a significant influence on adolescent’s PA through their longitudinal
study. Davison (2004) showed that middle school girls and boys who were in the high
active group reported significantly higher levels of paternal logistic maternal logistic,
family, peer and sibling support than in the low active group. A logistic is used for
predicting the outcome of a categorical dependent variable based on one or more
predictor variables (Bishop, 2006). Edwardson, Gorely, Pearson and Atkin (2013)
revealed a significant direct effect of peer’s social support on adolescents’ after-school
PA. Hagger et al. (2009) showed support from PE teachers had a significant effect on
motivation within the PE context, but also on autonomous motivation outside of school,
which in turn affects leisure time PA. Research in PE classes indicates that the teacher is
a critical agent of enhancing student’s motivation and promoting a particular class
environment (Biddle and Mutrie, 2008).
Despite these relationships between social and interpersonal aspects and

10. 3
adolescents’ PA, the findings have been inconclusive (Dowda, Pate, Sallis, et al. 2007;
Edwardson & Gorely, 2010; Edwardson, et al., 2013; Gillander & Hammarstrom, 2002;
Ferreira et al., 2006 & Lopes, Gabbard, & Rodrigues, 2013). For instance, Lytle,
Erickson, Sirard, Barr-Anderson and Story (2010) and Sallis, Prochaska, and Taylor
(2000) found no link between peer influence and PA.
There might be two possible reasons to explain the mixed results. First, effects of
interpersonal factors on PA might be different during different segments of the day.
Namely, PE teachers might affect adolescents’ PA mostly during PE classes, whereas
parents and siblings might influence mostly after or before school. However, many
studies focused on overall daily PA (Edwardson et al., 2013). Further research efforts
concentrating on a specific segment of the day are necessary. Second, not many studies
have used a specific theoretical framework to understand the influence of the social
context on adolescents’ PA behavior. According to the Treasury Board of Canada
Secretariat (2014), a theoretical based approach allows conclusions to be drawn and helps
focus on new data collections and in areas with considerable gaps. Thus, it is essential to
employ a sound theoretical model, such as the Theory of Triadic Influence, to
systematically understand the interpersonal factors, which will guide effective
interventions.
The Theory of Triadic Influence (TTI) is a powerful theory that has been used to
explain human behavior, such as smoking, substance use, diet and PA (Flay, Snyder &
Petraitis, 2009; Leatherdale & Burkhalter, 2012). The TTI is an integrative theory that
proposes variables can be arranged in different streams of influences, levels of causation,
and degrees of causation. The three streams consist of intrapersonal, social/normative,

11. 4
and cultural/attitudinal streams to explain human behavior, but only the social/normative
stream will be employed in this study.
The social/normative stream begins with social situation that is largely out of
control of an individual (Flay et al., 2009). Social situation is considered
ultimate/underlying level characteristics of one’s immediate surroundings, such as overall
family PA behavior. It flows through strength of the interpersonal bonds with immediate
role models (e.g., father, mother, siblings, teachers, and friends) and relevant behaviors
(e.g. leisure-time PA) of the role models. This flow continues through motivation to
comply with the role models and perceived norms, which are perceptions of behavior
(e.g., moderate to vigorous leisure-time PA) that the role models are encouraging. These
four constructs are considered distal/predisposing influences. The stream then flows to
social normative beliefs, which is the perceptions of social pressures to engage in a
specific behavior (e.g., moderate to vigorous PA in PE classes) and this directly leads to
the intention. The social normative beliefs and the intentions are proximal/immediate
factors that finally predict outcome behavior (e.g., moderate to vigorous PA in PE
classes).
The TTI theorizes that human behavior is a result of a combination and interaction
of intrapersonal, social, and environmental influences (Leatherdale & Burkhalter, 2012).
The TTI provides a meta-theoretical orientation that proposes higher-order descriptions
and explanations of health related behaviors, presenting a detailed ecological approach to
health behavior change, and suggests that an increased focus on distal and ultimate levels
of influence will produce greater and more sustainable health promotion (Flay et al.,
2009). There have been a plethora of studies where the TTI has been used in different

12. 5
behaviors among adolescents. For instance, Brickeret al., (2009), Ertas (2006), and
Grenard et al. (2005) investigated the prevalence and determinants of cigarette smoking
behavior in adolescents. Sieving, et al., (2006) used the TTI to examine friends’
influences on adolescents’ sexual behavior. Peters, et al. (2009) and Wiefferink et al.,
(2006) examined health related behaviors and their possible consequences for school
health interventions in adolescents using the TTI. Wind et al. (2006) studied correlates of
dietary behavior among adolescents based on the TTI. However, the TTI has rarely been
applied in PA domain.
In addition, there is a need to extend the TTI by including implementation
intention. The TTI proposes intentions as a unidimensional construct, but there are two
different types of intentions, goal intentions and implementation intentions. Goal
intention (i.e., TTI’s intentions) is concerned with intentions to perform behavior and
focus on the outcome, whereas implementation intention is concerned with plans as to
when, how, and how often the goal intention will be translated into behavior and focuses
on the process of achieving the goal (Gollwitzer, 1993). From accumulated research on
implementation intentions, Roberts, et al., (2010) revealed that implementation intentions
mediate the relationship between goal intentions and PA in adolescents. However, this
mediation framework has rarely been examined in PE settings (Jin & Yun, 2013).
Based on the extended social stream of the TTI (see Figure 1), it is postulated that
the predictors mediate the relationship between the ultimate predictor (social situation)
and PA behavior. The purpose of the study is to examine the capability of the extended
TTI’s social stream to predict adolescents’ PA in a PE setting.

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Figure 1. Extended social/normative stream of the TTI
Hypothesis:
To achieve the study purpose, the following hypotheses will be tested.
1. The influence of social situation on social normative beliefs will be mediated by
interpersonal bonding, other’s behavior and attitudes, motivation to comply, and
perceived norms.
2. The influence of interpersonal bonding, other’s behavior and attitudes, motivation to

14. 7
comply, and perceived norms on goal intentions will be mediated by social normative
beliefs.
3. The influence of social normative beliefs on implementation intentions will be
mediated by goal intentions.
4. The implementation intentions will mediate the relationship between goal intentions
and PA behavior.
5. The affective sub-stream (interpersonal bonding and motivation to comply) of female
participants will explain social normative beliefs stronger than male participants.
6. The cognitive sub-stream (other’s behavior and attitudes and perceived norms) of
male participants will explain social normative beliefs stronger than female
participants.
Assumptions:
1. The Theory of Triadic Influence explains PA behavior.
2. Instruments are reliable and valid, which include the questionnaires to measure the
TTI social constructs and the GT3X+ accelerometers to measure PA levels.
Delimitations:
1. The number of participants
2. Geographical region
3. High school students
Limitations:
1. Time constraints as this study collects data for a set time period, in the spring of 2014.
2. The types of activity the adolescents are partaking in their physical education settings.
3. Convenience sampling method

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Operational Definitions:
1. Physical Activity: Any bodily movement produces by the contraction of skeletal
muscle that increases energy expenditure above a basal level (US Department of
Health and Human Services, 2008).
2. Social Influence: Change in an individual’s thoughts, feelings, attitudes, or behaviours
that results from interaction with another individual or a group (Rashotte, 2009).
3. Social Situation: Ultimate-level characteristics of one’s immediate social surroundings
that are largely outside the control of the person (Flay, Snyder, & Petraitis, 2009).
4. Interpersonal bonding: Strength of the interpersonal bonds with immediate role models
(Flay, Snyder, & Petraitis, 2009).
5. Others’ behaviour and attitudes: Relevant behaviors and attitudes of the role models
(Flay, Snyder, & Petraitis, 2009).
6. Motivation to comply: Motivation to comply with the role models (Flay, Snyder, &
Petraitis, 2009).
7. Perceived Norms: Perceptions of what behavior the role models are encouraging (Flay,
Snyder, & Petraitis, 2009).
8. Social Normative Beliefs: Perceptions of social pressures to engage in a specific
behavior (Flay, Snyder, & Petraitis, 2009).
9. Goal intentions: An individual’s willingness to perform behavior and focus on the
outcome (Gollwitzer, 1993).
10. Implementation intentions: An individual’s wiliness to plan as to when, where, and
how the goal intention will be translated into behavior and focuses on the process of
achieving the goal (Gollwitzer, 1993).

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METHOD
Participants
A total of 71 students (male=56%; mean age=14.72) from a high school
conveniently selected in La Crosse County, Wisconsin participated in this study. Initially,
120 students were invited, but only 84 students decided to take part in this study and the
final sample was reduced to 71 participants due to several reasons, including (a) not
getting parental consent, (b) not signing the student assent form, (c) injured during the
study, and (d) absent for three or more days. A majority of participants were Caucasian
(82%) and had GPA between 3.5-4 (52%). All assent and consent forms were collected
from the student participants and their parents prior to data collection.
Instruments
The data was collected in two different ways: (a) paper-and-pencil questionnaires
to collect students’ social constructs and (b) an accelerometer to collect students’ PA.
Survey Questionnaires
Paper-and-pencil survey questionnaires, including 41 items assessing TTI social
constructs and demographic information were developed. Measures for social constructs
include social situation at ultimate level; interpersonal bonding, other’s behavior and
attitudes, perceived norms, and motivation to comply at distal level; social normative
beliefs, goal intentions, and implementation intentions at proximal level. Content-related
validity evidence of the questionnaires was evaluated with four steps based on the
recommendation of Yun and Ulrich (2002). A guideline, including operational definitions

17. 10
of theoretical constructs, was developed to help content experts to make judgments. Next,
a panel of judges was organized with three experts who have academic and practical
background in exercise psychology, physical activity, and physical education. These
experts were asked to evaluate content relevance of the questionnaires. After the review
is completed, directions, expressions, and wordings in each section will be revised based
on feedback and suggestions of the panel of judges.
According to previous studies (Kodish, Kulinna, Martin, Pangrazi, & Darst, 2006;
Martin, McCaughtry, & Shen, 2009), the phrase “breathe hard or feel tired” was used as a
descriptor to indicate specific PA behavior that this study is investigating.
Three pilot studies were conducted to ensure suitability and comprehensibility of
the questionnaire items. First pilot study (n=43) was conducted at Tomah High School
the Physical Activity Predictors Assessment questionnaire was administered to all
students. The completed questionnaires were collected and then analyzed to test internal
consistencies of TTI constructs. After the results were analyzed the questionnaire was
altered based on the analysis. Changes included, alterations to the wording to make it
easier to understand and formatting changes. Following the alterations a second pilot
study was conducted on the University of Wisconsin- La Crosse Women’s Soccer team
(n=28), again just the Physical Activity Predictors Assessment questionnaire was
administered. The players were asked to critique the questionnaire and suggest changes to
be made. Again the results were analyzed to test internal consistencies. The analysis
showed that another pilot study was needed. Therefore a third pilot study was conducted
on the Aquinas High School Girls Soccer team (n=26), after the results were analyzed,
the decision was made that all constructs were consistent therefore the questionnaire was

18. 11
a valid measurement tool for the study. Internal consistencies of the three pilot studies are
presented in Table 1. The reliability ranges varied through the three pilot studies. For
example, the goal inattention’s reliability was consistent, but social normative belief’s
reliability was fluctuated. However, the researcher decided to precede the primary data
collection as the last pilot study showed acceptable reliability estimates for all study
constructs.
Table 1. Internal consistencies of TTI constructs pilot studies
Cronbach’s Alpha
Pilot 1 Pilot 2 Pilot 3
Social Situation .75 .52 .77
Interpersonal Bonding .55 .48 .54
Others Behavior and Attitudes .78 .80 .86
Perceived Norms .79 .56 .85
Motivation to Comply .89 .80 .88
Social Normative Beliefs .76 .27 .68
Goal Intention .96 .95 .95
Implementation Intention .97 .88 .96
Social Situation. Three items were developed to assess students’ PA support
from family as a social situation variable adapted from scales of Davison (2004). An
example item will be “Physical activity is central to our family life.” A 5-point Likert-
type scale ranging from ‘Strongly Disagree’ to ‘Strongly Agree’ was employed.

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Interpersonal bonding. Five items were developed to assess students’ strength of
relationships with father, mothers, siblings, friends and a PE teacher adapted from scales
of Bavarian et al. (2013). An example item will be “How would you rate the strength of
relationship with your father.” A 5-point Likert-type scale ranging from ‘Very weak’ to
Very Strong’ was employed.
Other’s behavior and attitudes. Fifteen items were developed to assess other’s
behavior and attitudes that influence participants’ PA through the same five major social
agents, which are father, mother, siblings, peers and PE teachers adapted from scales of
Davison (2004). An example item will be “My friends often play a sport or do something
active.” A 5-point Likert-type scale ranging from ‘Strongly Disagree’ to Strongly Agree’
was employed.
Perceived norms. Five items were developed to assess students’ perceptions of
PA behavior of the same five role models encouraging, adapted from scales of Martin et
al. (2009). The target PA behavior was specified by including the phrase “breathe hard or
feel tired.” An example item will be “My mother believes that it is important that I
participate in physical activity that makes me breathe hard or feel tired.” A 5-point
Likert-type scale ranging from ‘Strongly Disagree’ to ‘Strongly Agree’ was employed.
Motivation to comply. Five items were developed to assess students’ motivation
to comply with the five social agents or not, adapted from scales of Martin et al. (2009).
The phrase “breath hard or feel tired” was included in the items to specify PA behavior.
An example item will be “How important is it to you that your friends believe you should
participate in physical activity that makes you breathe hard or feel tired?” A 5-point
Likert-type scale ranging from ‘Not important at all’ to ‘Very important’ was employed.

20. 13
Social normative beliefs. There were two items developed to assess students’
perceptions of social pressures to engage in PA, adapted from scales of Bavarian et al.
(2013). The target PA behavior was more specified using the phrase “breath hard or feel
tired during PE”. An example item will be “What proportion of students at this high
school do you believe do PA that makes them breathe hard or feel tired during PE?” A 5-
point Likert-type scale ranging from ‘0-10%’ to ‘More than 75%’ was employed.
Goal intentions. There were three items developed to assess students’ goal
intentions to be active, adapted from scales of Kodish et al. (2006). PA was specified by
using the descriptor “breathe hard or feel tired during PE”. An example item will be “I
plan to do physical activity that makes me breathe hard or feel tired during PE” A 5-point
Likert-type scale ranging from ‘Definitely false’ to ‘Definitely True’ was employed.
Implementation intentions. Three items were developed to assess students’
extent to which they had formed a detailed plan regarding when, how, and how often to
do PA, adapted from scale of Roberts et al. (2010). The phrase “breathe hard or feel tired
during PE” was used to specifically assess PA. An example would be “During PE”, I
have made a detailed plan regarding how often to do physical activity that makes me
breathe hard or feel tired. A 5-point Likert-type scale ranging from ‘Definitely false’ to
‘Definitely True’ was employed.
Accelerometers
GT3X+ accelerometer (Actigraph, Pensacola, FL) were used to objectively assess
students’ PA in PE classes. According to Loprinzi, & Cardinal (2011), accelerometers
record the frequency and magnitude of the body’s acceleration during movement. The
acceleration signal from the accelerometer is digitized and generates an “activity count”

21. 14
and the counts are then summed over a set period of time. Many studies support that
GT3X+ accelerometers are reliable and valid to assess PA (Robusto & Trost, 2012) and it
has been used in a variety of ways for adolescents. For instance, Zhu and Chen (2013)
used the GT3X+ to monitor daily PA levels of senior high school students. Donatienne
and Frazer (2009) examined associations between adolescents’ school travel PA, school
travel mode and neighborhood walkability using the GT3X+. In addition, Kirschner,
(2012) used the GT3X+ to investigate energy expenditure and PA intensity for
adolescents.
Procedures
Once the IRB was approved, consent and assent was gained to participate in the
study. This study adopted a two-wave prospective design. In the first wave, the
participants completed the questionnaires during PE classes. The researcher provided a
brief introduction and necessary directions about the questionnaires. PE teachers
supported the survey administration process. The researcher provided any additional
assistance to better comprehend the survey questions if needed. After the survey
administration was completed, the researcher provided an orientation for each student to
explain the accelerometer, including how the device is operated and how to wear it.
Along with the consent process, the permission to conduct the study was obtained from
PE teachers of the participants.
In the second wave one week after the survey administration, participants were
asked to wear accelerometers for four PE classes. A 4-day monitoring was based on the
recommendation of Janz, Witt, and Mahoney, (1995). A researcher was present at all
times to collect the data. Each participant was assigned an identification number that

22. 15
corresponds to the number on his/her accelerometer and asked to place monitor on his/her
waist during the entire class time (e.g., 50 minutes). The accelerometers was given to the
students individually when PE teachers are taking roll, and students returned the device to
the researchers at the end of each class. The number they have been assigned was
recorded by their name on a class list, and the researcher kept the numbers for records.
Analysis
A series of multiple regressions was used to test all six hypotheses. Based on the
recommendation of Baron and Kenny (1986), the following four-step approach was
employed to test hypotheses 1-4: (a) estimate the total effect between a predictor variable
and an outcome variable, (b) estimate the indirect effect between the predictor variable
and a mediator, (c) estimate the indirect effect between the mediator and the outcome
variable, controlling for the predictor variable, and (d) estimate the direct effect between
the predictor and outcome variables, controlling for the mediator. If the direct effect was
zero, it was considered a complete mediation. If the direct effect was not zero, but
reduced compared to the total effect, it was considered a partial mediation.
To test hypothesis 5 and 6, several regressions were conducted separately.
Regressions for hypothesis 5 included (a) interpersonal bonding  motivation to comply,
(b) motivation to comply  social normative norms, and (c) interpersonal bonding +
motivation to comply  social normative beliefs. In the same manner, regression for
hypotheses 6 included (a) other’s behavior and attitudes  perceived norms, (b)
perceived norms  social normative beliefs, and (c) other’s behavior and attitudes +
perceived norms  social normative beliefs. Each outcome variable was regressed onto

23. 16
the predictor variable with gender (0 = Male and 1 = Female) and the predictor variable ×
gender interaction, respectively.

24. 17
RESULTS
The average of percent of time spent in MVPA was 9.6% (SD=5.48) ranged from
2.2% to 37.3%. A majority of participants (59%) reported that they participate 2-3 hours
PA daily (see Figure 2). Team sports (52%) were the most popular type of activity and
adventure/outdoor (24%) and individual activities (22%) were the next. Approximately,
half of participants (55%) were affiliated with a school club and one third of participants
(34%) described that their general health was very good, followed by good (31%), fair
(18%), excellent (15%), and poor (1%). Descriptive statistics and internal consistencies
of TTI social constructs are illustrated in Table 2 and inter-correlations of the study
variables are presented in Table 3.
Figure 2. Amount of daily physical activity participation of the study participants
0%
10%
20%
30%
40%
50%
60%
70%
0-1 h 2-3 h 4-5 h 6+ h

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Table 2. Descriptive statistics and internal consistencies of TTI constructs
Mean
Standard
Deviation
Cronbach’s
Alpha
Social Situation 3.72 .64 .82
Interpersonal Bonding 3.87 .60 .60
Others Behavior and Attitudes 3.32 .70 .91
Perceived Norms 3.61 .81 .82
Motivation to Comply 3.28 .96 .85
Social Normative Beliefs 3.70 .72 .36
Goal Intention 4.08 .77 .91
Implementation Intention 3.17 .93 .94
Table 3. Inter-correlations of the study variables
1 2 3 4 5 6 7 8 9
1 1.0
2 .44* 1.0
3 .49* .41* 1.0
4 .35* .32* .72* 1.0
5 .36* .32* .53* .73* 1.0
6 .46* .10 .39* .41* .26* 1.0
7 .36* .21 .38* .41* .42* .30* 1.0
8 .27* .28* .15 .22 .31* .28* .53* 1.0
9 .18 .04 .02 .05 .04 .01 .20 -.02 1.0
Note. 1=Social Situation; 2=Interpersonal Bonding; 3= Other’s Behavior and Attitude; 4
Perceived Norms; 5= Motivation to Comply; 6= Social Normative Beliefs; 7= Goal Intention; 8=
Implementation Intention.
Hypothesis 1, 2, 3, and 4 were tested through the 4-step mediation analyses using
multiple regressions. It was revealed that interpersonal bonding, other’s behaviors and
attitudes, motivation to comply and perceived norms partially mediate the relationship
between social situation and social normative beliefs. The effect of social situation on
social normative beliefs was reduced from β=.52 (total effect; P<.001) to β=.41 (direct

26. 19
effect; P<.05) when controlling for interpersonal bonding, other’s behavioral and
attitudes, motivation to comply and perceived norms. Albeit the small mediation effect,
this finding supports hypothesis 1 demonstrating that effect of ultimate cause (social
situation) on proximal predictor (i.e., social normative beliefs) is mediated by distal
influence (i.e., interpersonal bonding, other’s behavior and attitudes, motivation to
comply, and perceived norms).
There was mediation effect of social normative beliefs between distal predictors
(i.e., interpersonal bonding, other’s behavior and attitudes, motivation to comply, and
perceived norms) and goal intention. The total effect was β=.14 (p<.001) and the direct
effect was β=.12 (p<.001) after controlling for social normative beliefs. Despite the small
mediation effect, the finding supports hypothesis 2 demonstrating that effect of distal
predictors on goal intention is mediated by the proximal predictor (i.e., social normative
beliefs). The influence of social normative beliefs on implementation intentions was
mediated by goal intentions, β=.36 (total effect; p<.05) to β=.18 (direct effect; p>.05),
when controlling for implementation intention. Thus, there was a mediation effect of goal
intention on the relationship of social normative beliefs and implementation intention to
support hypothesis 3. There was no mediation effect of implementation intentions
between goal intentions and PA behavior and hypothesis 4 was not supported.
In terms of hypothesis 5 and 6, there was no evidence to show the affective sub-
stream (interpersonal bonding and motivation to comply) of female participants explain
social normative beliefs stronger than male participants (i.e., the interaction effect was
not significant). However, the interaction term of male × cognitive sub-stream (β = -.27,
p<.05) significantly moderated the effect of the cognitive sub-stream (other’s behavior

27. 20
and attitudes + perceived norms) on social normative beliefs after accounting for the
gender and the cognitive sub-stream. This finding indicated that the cognitive sub-stream
of female participants explain social normative beliefs stronger than male participants,
which is opposite to hypothesis 6.

28. 21
DISCUSSION
The purpose of the study was to examine the capability of the TTI’s extended
social constructs to predict adolescents’ PA in a PE setting. To achieve the study purpose,
the following six hypotheses were tested: (1) the distal influences (interpersonal bonding,
others’ behavior and attitudes, motivation to comply, and perceived norms) will mediate
the relationship of social situation and social normative beliefs; (2) the social normative
beliefs will mediate the relationship of the distal influences and goal intentions; (3) the
goal intentions will mediate the relationship of social normative beliefs and
implementation intentions; (4) the implementation intentions will mediate the
relationship of goal intentions and PA behavior; (5) the affective sub-stream
(interpersonal bonding and motivation to comply) of female participants will explain the
social normative beliefs stronger than male participants; (6) the cognitive sub-stream
(other’s behavior and attitudes and perceived norms) of male participants will explain the
social normative beliefs stronger than female participants.
It was found that the distal influences (interpersonal bonding, other’s behavior
and attitudes, motivation to comply, and perceived norms) mediated the relationship
between the ultimate cause (i.e., social situation) and the social normative beliefs. To the
author’s knowledge, there is no direct literature in agreement with this finding, but many
studies found that these distal influences are strong predictors of adolescents’ physical
activity. For instance, Wenthe, Janz and Levy (2010) showed that family support was the
strongest predictor of leisure-time MVPA levels in adolescents. In addition, Trost, Sallis,

29. 22
Pate, Freedson, Taylor and Dowda (2003) revealed that parental capacity was critical to
provide instrumental and motivational support for PA of adolescents. Future research is
necessary to better understand and confirm the mediating role of distal influences for
adolescents.
In terms of hypothesis 2, it was shown that social normative beliefs mediated the
relationship between the distal influences and goal intentions. Because TTI is based on
many behavioral/explanatory theories, there are many similar findings in literature. For
instance, previous studies using theory of reasoned action (TRA) and theory of planed
behavior (TPB) have consistently demonstrated that subjective norm explains goal
intentions, which in turn predict PA behavior. Trost, Saunders, and Ward (2002) found
youth’s leisure-time MVPA was significantly predicted by subjective norm (calculated by
multiplying normative beliefs and motivation to comply) in both TRA and TPB.
Although the theoretical structure is slightly different between TTI and TRA/TPB, this
finding indicates social normative belief is an important predictor of adolescent’s PA
levels in both leisure-time and PE settings.
For hypothesis 3, the goal intentions appeared to be a significant mediator
between social normative beliefs and implementation intentions. In agreement with this
finding, Jin and Yun (2014) showed that adolescents’ goal intentions to be active
mediated the relationship of subjective norm (normative beliefs × motivation to comply)
and implementation intentions in a school physical education environment. This finding
indicates that physical educators should provide quality PE lessons, so that students can
appropriately and effectively plan how, when, and how often to be active during PE
classes. Although the TTI doesn’t have implementation intentions as one of it’s

30. 23
constructs, TTI researchers may consider adding it to the theory to better understand and
eventually promote physical activity for adolescents in future studies.
Hypothesis 4 was not supported. Implementation intention is a self-regulatory
strategy of successful goal pursuit (Duckworth, Grant & Loew, 2011), and numerous
studies found implementation intention is one of immediate predictors of PA behavior
(Belanger-Gravel, Godin, & Amireault, 2013). Nonetheless, there was no significance
mediation effect of implementation intentions between goal intentions and PA in
adolescents. There might be several potential reasons to explain this insignificant effect
of implementation intentions as a mediator. First, a PE teacher plans, teaches, and adjusts
his/her lessons and thus his/her students may have a lack of controllability to be active
during PE lessons. In other words, students are not given much freedom to perform their
own PA as they are told what to do by the modules they are taught. Second, different
lesson plans and environmental factors may affect students’ PA levels although the
content is the same across different classes. For example, if the lesson cannot be
completed outside due to the weather, alternative ways to deliver the same content will
vary. Third, different gender ratios in a PE class may influence the effect of intentions on
PA levels. For instance, if there are more boys than girls in a PE class, the girls may be
less likely willing to be active. Thus, additional mediators and/or moderators should be
considered between implementation intentions and PA levels of adolescents to further
understand the complex relationship between intentions and PA behavior during PE.
There was no evidence to support hypothesis 5 testing the affective sub-stream of
female students predicts social normative beliefs stronger than male students. Cash
(2011) and Groan (2008) showed adolescent girls’ body dissatisfaction was a key issue

31. 24
with interpersonal bonding. In addition, Hanna and Bond (2006) found that mothers’
emotional support was key for female adolescents’ behavior. However, this result
indicates that gender is not an actual moderator between the affective distal influences
(i.e., interpersonal bonding and motivation to comply) and social normative beliefs to be
physically active during PE. It might be possible that the physical educators equally treat
students regardless of gender (e.g., same amount of teacher feedback is given to both
male and female students), but a selection bias might exist on this result, due to the
convenience sampling method (i.e., the selected school might have high quality PE).
Hypothesis 6 was supported, but in an opposite way. According to Van der Horst
et al. (2007), perceived benefits and attitudes are strong correlates of youth PA behavior.
Also, Li, Lannotti, Haynie, Perlus and Simons-Morton (2014) found that perceived peer
PA behavior and parental support were associated with both internal and external
motivation for adolescents’ PA participation. Based on the literature, it was hypothesized
that gender moderates the relationship and specifically the effect of cognitive sub-stream
on social normative beliefs is stronger for males than females. However, it was revealed
that the cognitive sub-stream of female participants explained social normative beliefs
stronger than male participants. This opposite finding might be explained by the unique
context of PE. Traditionally, it has been known that PE participation of female students
dramatically declines compared to male students during adolescence. Female students
recognize physical characteristics and appearance (e.g., being overweight and obese that
is common reason for teasing among peers) more seriously than male students (Salvy,
Coelho, Kieffer & Epstein, 2007; Salvy et al., 2008). Particularly, overweight youth are
perceived more negatively and less accepted by peers than are normal weight youth (Bell

32. 25
& Morgan, 2000 & Zeller, Reiter-Purtill & Ramey, 2008). Thus, the unique school
environment where others’ attitudes and behaviors are more exposed than out of school
should take into consideration when TTI is applied into educational settings (e.g., a PE
class), especially for the affective and cognitive concepts.
The potential bias with this study may be minimal since the data was collected
over several days to gather reliable PA levels; the PE teachers had a set of the same
curriculum and lesson plans to follow in the same school environment. Furthermore, all
student participants took part in the same sport content (i.e., flag football) during the data
collection period. Several limitations should be acknowledged as well. The sample size of
this study was relatively small. The results would be more significant if the sample size
was larger. Another limitation to the study was that each teacher has different teaching
style. Although the same sport was taught there might be some variations with each
lesson.
Future studies may examine different schools in both rural and urban areas using
the same sport or activity being taught in each school and also may think about
comparing different sport or activity modules within one school, to identify why or if one
produces lower levels of moderate to vigorous PA. This will allow module changes or
changes to teaching styles to produce the most PA. Furthermore, comparing different
school years to see which has the least amount of PA that will allow more focus on that
year to change the teaching style to better promote PA. Another potential research
direction could be using different times of the school year. For example, researchers
would use the start, middle and end of the school year to monitor and identify changes in
PA levels throughout the year.

33. 26
A greater depth and understanding for the use of the TTI must be obtained,
particularly when it is applied to PA in PE environment. Future validation study would be
necessary to develop a more reliable and valid TTI measure that can be used in PE
classes.

34. 27
CONCLUSION
In sum, the study results showed that interpersonal predictors of the TTI have an
effect on adolescents PA levels during PE. Despite a lack of PA research using the TTI in
PE, this study indicates the TTI is capable of understanding social predictors of
adolescents’ PA behavior. However, future research is warranted to further understand
effects of TTI’s interpersonal predictors on adolescents’ PA behavior in PE. Future
research endeavors may explain the insignificant mediation effect of implementation
intentions between the goal intention and the PA behavior in this population.

35. 28
REFERENCES
Adler, P. A., & Adler, P. (2008). Peer Power: Preadolescent Culture and Identity. New
Brunswick; NJ: Rutgers University Press.
Araujo-Soares, V., McIntyre, T., & Sniehotta, F. F. (2008). Predicting changes in
physical activity among adolescents: the role of self efficacy, intention, action
planning and coping planning. Health Education Research, 1, (28), 13.9-24.1
Barnekow-Bergkvist, M., Hedberg, G., Janlert, U., Jansson, E. (2008). Physical activity
pattern in men and women at the ages of 16 and 34 and development of physical
activity from adolescence to adulthood. Scandinavian Journal of Medicine &
Science in Sports and Exercise, 40, (1), 181-188.
Barnett, E., & Casper, M. (2001). A Definition of “Social Environment”, American
Journal of Public Health, Vol. 91, No. 3
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic and statistical considerations.
Journal of Personality and Social Psychology, 51, 1173-1182.
Belanger-Gravel, A., Godin, G., & Amireault, S. (2013). A meta-analytic review of the
effect of implementation intentions on physical activity. Health Psychology
Review, 7, (1), 23-54.
Biddle, S, J, H., & Mutrie, N. (2008). Psychology of Physical Activity: Determinants,
well-being and interventions. Routledge, 1-419.
Bishop, C, M. (2006). In the terminology of statistics, this model is known as logistic
regression, although it should be emphasized that this is a model for classification
rather than regression. Pattern Recognition and Machine Learning. Springer,
p. 205.
Bricker, J, B., Rajan, K, B., Zalewski, M., Andersen, R., Ramey, M., & Peterson, A, V.
(2009). Psychological and Social Risk Factors in Adolescent Smoking
Transitions: A Population-Based Longitudinal Study.
Bavarian, N., Flay, B. R., Ketcham, P. L., & Smit, E. (2013). Development and
psychometric properties of a theory-guided prescription stimulant misuse
questionnaire for college students. Substance Use & Misuse, 48, 457-469.

36. 29
Davison, K, K. (2004). Activity-Related Support From Parents, Peers, and Siblings and
Adolescents’ Physical Activity: Are There Gender Differences? Journal of
Physical Activity and Health, 1, 363-376.
Donatienne, A., & Frazer, C. (2009). Associations between Adolescents’ School Travel-
Physical Activity, School Travel Mode, and Neighborhood Qalkability, Pp. 1-91.
Dowda, M., Pate, R. R., Sallis, J. F., et al. (2007). Agreement between student- reported
and proxy-reported physical activity questionnaires. Journal of Pediatric Exercise
Sciences, 19, (3), 310-318.
Driver, S. (2007). Psychometric properties and analysis of the physical activity social
influence scale for adults with traumatic brain injuries. Adapted Physical Activity
Quarterly, 24, 160-177.
Driver, S. (2008). Development of a conceptual model to predict physical activity
participation in adults with brain injuries. Adapted Physical Activity Quarterly,
25, 289-307.
Duckworth, A, L., Grant, H., Loew, B. (2011). Self-regulation strategies improve self-
discipline in adolescents: benefits of mental contrasting and implementation
intentions, 31. 1.
Duncan, S, C., Duncan, T, E., Strycker, L, A., Chaumeton, N, R. (2007). A Cohort-
Sequential Latent Growth Model of Physical Activity from the ages 12-17 Years.
Annals of Behavioral Medicine, 33, (1), 80-89.
Edwardson, C.L., & Gorely, T. (2010). Parental influences on different types and
intensities of physical activity in youth: A systematic review. Psychology of Sport
and Exercise, 11,(6), 522-535.
Edwardson, C.L., Gorely, T., Pearson, N., & Atkin, A. (2013). Sources of activity-related
social support and adolescents’ objectively measured after-schaool and weekend
physical activity: Gender and age differences. Journal of Physical Activity and
Health, 10, 1153-1158.
Ertas, N. (2006). Factors associated with stages of cigarette smoking among Turkish
Youth. European Journal of Public Health, 17, (2), 155-161.
Ferreira, I., va der Horst K., Wendel-Vos, W., Kremers, S., van Lenthe, F. J., Brug, J.
(2006). Environmental correlates of physical activity in youth: A review and
update. Obesity Reviews, 8, 129-154.
Flay, B. R., & Petraitis, J. (1994). The theory of triadic influence: A new Theory of
health behavior with implications for preventive interventions. Advances in
Medical Sociology, 4, 19-44.

37. 30
Flay, B. R., Snyder, F., & Petraitis, J. (2009). The Theory of Triadic Influence. In R. J.
DiClemente, M. C. Kegler & R. A. Crosby (Eds.), Emerging Theories in Health
Promotion Practice and Research (Second ed., pp. 451-510). New York: Jossey-
Bass.
Fein, A. J., Plotnikoff, C., Wild, C., & Spence, J. (2004). Perceived Environment and
Physical Activity in Youth. International Journal of Behavioral Medicine, 11, (3),
135-142.
Gillander, G. K., Hammarstrom, A. (2002). Can school-related factors predict future
health behavior among young adolescents? Public Health, 116 (1), 22–9.
Goffman, E. (1964). The Neglected Situation. American Anthropological Association.6,
(66), 133-136.
Gollwitzer, P.M. (1993). Goal achievement: The role of intentions. European Review of
Social Psychology, 4, 141-185.
Grenard, J. L., Guo, Q., Jasuja, G. K., Unger, J. B., Chou, C. P., Gallaher, P. E., Sun, P.,
Palmer, P., & Johnson, A. (2005). Influences affecting adolescent smoking
behavior in China. Nicotine & Tobacco Research, 8, (2), 245-255.
Hagger, M., Chartzisarantis, N.L.D., Hein, V., Soos, I., Karsai, I, Lintunen, T., &
Leemans, S. (2009). Teacher, Peer, and parent autonomy support in physical
education and leisure-time physical activity: A trans-contextual model of
motivation in four nations. Psychology and Health, 24, (6), 689-711.
Janz, K. F., Witt, J., & Mahoney, L. T. (1995). The stability of children’s physical
activity measured by accelerometry and self-report. Journal of Medicine &
Science in Sport & Exercise, 27, 1326-1332.
Jin. J., & Yun, J. (2013). Three frameworks to predict physical activity behavior in
middle school inclusive physical education: A multilevel analysis. Adapted
Physical Activity Quarterly, 30, 254-270.
Jin. J., & Yun, J. (2014). Adolescents’ physical activity predictors within the context of
inclusive physical education: An integrative model approach. Manuscript
submitted for publication.
Kirschner, M. M. (2012). Assessment of Energy Ependiture and Physical Activity
Intensity Through Simultaneous Use Of Heart Rate Monitoring and
Accelerometry. pp. 1-103.

38. 31
Kodish, S., Hodges-Kulinna, P., Martin, J., Pangrazi., & Darst, P. (2006). Determinants
of physical activity in an inclusive setting. Adapted Physical Activity Quarterly,
23, 390-409.
Leatherdale, S.T., Burkhalter, R. (2012). The substance use profile of Canadian youth:
exploring the prevalence of alcohol, drug and tobacco use by gender and grade.
Journal of Addictive Behavior, 37, 318–322.
Lopes, V, P., Gabbard, C, & Rodrigues, L, P. (2013). Physical Activity in Adolescents:
Examining Influence of the Best friend Dyad, 52, 752-756.
Martin, J. J., McCaughtry, N., & Shen, B. (2009). Physical activity and fitness in inner
city Hispanic American children. Hispanic Health Care International, 7, (1), 21-
29.
Maturo, C. C., & Cunningham, S.A. (2013). Influence of friends on children’s physical
activity: A review. American Journal of Public Health, 103 (7), e23-e38.
Mummery, W, K., Spence, J. C., & Hued, J. C. (2000). Understanding physical activity
intention in Canadian school children and youth: An application of theory of
planned behavior. Research Quarterly for Exercise and Sport, 71, (2), 116-124.
Ornelas, I, J., Perreira, K, M., Ayala, G, X. (2007). Parental influences on adolescent
physical activity: a longitudinal study. International Journal of Behavioral
Nutrition and Physical Activity. 4:3
Patterson, R, E., Kristal, A, R., & White, E. (1996). Do Beliefs, Knowledge and
Perceived Norms about Diet and Cancer Predict Dietary Change? American
Journal of Public Health, 86, (10), 1394-1400.
Patnode, C, D., Lytle, L, A., Erickson, D, J., Sirard, J, R., Barr-Anderson, D., Story, M.
(2010). The relative influence of demographic, individual, social and
environmental factors on physical activity among boys and girls. International
Journal of Behavioral Nutrition and Physical activity. 7:79.
Peters, L, W, H., Wiefferink, C, H., Hoekstra, F., Buijs, G, J., ten Dam, G, T., &
Paulussen, T, G, W, M. (2009). A revirew of similarities between domain-specific
determinants of four health behaviors among adolescents. Journal of Health
Education Research, 24, (2),198-223.
Rashotte, L, S. (2009). Social Influence in The Concise Blackwell Encyclopedia of
Sociology, George Ritzer and J. Michael Ryan eds. Oxford: Blackwell Publishing.
Roberts, V., Maddison, R., Magnusson, J., & Prapavessis, H. (2010). Adolescent physical
activity: Does implementation intention have a role? Journal of Physical Activity
and Health, 7, 497-507.

39. 32
Robusto, K. M., & Trost, S. G. (2014). Comparison of three generations of ActiGraphTM
activity monitors in children and adolescents. Journal of Sports Sciences, 30 (13),
1429-1435.
Roberts, V., Maddison, R., Magnusson, J., & Prapavessis, H. (2010). Adolescent physical
activity: Does implementation intention have a role? Journal of Physical Activity
and Health, 7, 497-507.
Sallis, J, F., Prochaska, J, J., & Taylor, W, C. (2000). A review of correlates of physical
activity of children and adolescents. Official Journal of the American College of
Sports Medicine, 963-975.
Sieviing, R. E., Eisenberg, M. E., Pettingell, S., and Skay, C. (2006). Friends’ influence
on adolescents’ first sexual intercourse. Perspectives on Sexual and Reproductive
Health, 38, (1), 13-19.
Springer, A., Kelder, S., & Hoelscher, D. (2006). Social support, physical activity and
sedentary behavior among 6th grade girls: a cross- sectional study. International
Journal of Behavior Nutrition Physical Activity, 3,8.
Steinberg, L., & Monahan, K.C. (2007). Age differences in resistance to peer influence.
Developmental Psychology, 43, 1531-1543.
Strong, W. B., Malina, R. M., Blimkie, C. J. R., Daniels, S.R., Dishman, R. K., Gutin, B.,
et al. (2005). Evidence based physical activity for school aged youth. Journal of
Pediatrics, 146, 732-737.
Theeboom, M., De Knop, P., & Weiss, M. R. (1995). Motivational climate, psychosocial
responses, and motor skill development in children’s sport: A field based-
intervention study. Journal of Sport & Exercise Psychology, 17, 294-311.
Treasury Board of Canada Secretariat. (2014). Theory-Based Approaches to Evaluation:
Concepts and Practices.
Trost, S. Saunders, R., & Ward, D. (2002). Determinants of physical activity in middle
school children. American Journal of Health Behavior, 26, (2), 95-102.
U.S. Department of Health and Human Services. (2008). Physical Activity Guidelines for
Americans. Washington, DC: U.S. Department of Health and Human Services.
Voorhees, C, C., Murray, D., Welk, G., Birnbaum, A., Ribisl, K, M., Johnson, C, C., et
al. (2005). The role of peer social network factors and physical activity in
adolescent girls. [Electronic version]. American Journal of Health Behavior, 29,
183-190.

40. 33
Wenthe, P, J., Janz, K, F., Kevy, S, M. (2010). Gender Similarities and Differences in
Factors Associated with Adolescent Moderate-Vigorous Physical Activity.
National Institutes of Health, 21, (3), 291-304.
Wind. M., deBourdeaudhuij, I., teVelde, S.J., Sandvik, C., Klepp, K. I., et al. (2006).
Correlates of fruit and vegetable consumption among 11-year-old Belgian-
Flemish and Dutch school children. Journal of Nutrition Education and Behavior,
38, (4), 211-221.
Wiefferink, C, H., Peters, L., Hoekstra, F., ten Dam, G, T., Buijs, G, J., & Paulussen, T,
G, W, M. (2006).Clustering of Health-Related Behaviors and Their Determinants:
Possible Consequences for School Health Interventions. Journal of Prevention
Science, 7, (2) 127-149.
Woodard, M, C., & Berry, M, J. (2001). Enhancing Adherence to Prescribed Exercise:
Structured Behavioral Interventions in Clinical Exercise Programs. Journal of
Cardiopulmonary Rehabilitation, 21, 201-209.
Yun, J., & Ulrich, D. (2002). Estimating measurement validity: A tutorial. Adapted
Physical Activity Quarterly, 19, 32-47.
Yun, J., & Shapiro, D.R. (2004). A quantitative approach to movement skill assessment
for children with mental retardation. Adapted Physical Activity Quarterly, 21,
269-280.
Zhu, L., Chen, P. (2013). Research on Monitoring the Daily Physical Activity of Senior
High School Boys in Huangzhou by Using Triaxial Accelerometer (GT3X~+).
Journal of Guangzhou Sport University

41. APPENDIX A
SURVEY INSTRUMENT

42. 35
Appendix A: A Survey Instrument

43. 36
D.#Perceived#norms#
! ! Strongly)
Disagree)
Disagree) Neutral) Agree) Strongly)
Agree)
1! My!Father!believes!that!it!is!important!that!I!participate!in!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
2! My!Mother!believes!that!it!is!important!that!I!participate!in!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
3! My!Sibling!believes!that!it!is!important!that!I!participate!in!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
4! My!friends!believe!that!it!is!important!that!I!participate!in!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
5! My!PE)teacher!believes!that!it!is!important!that!I!participate!in!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
!
E.#Motivation#comply#
! ! Not)at)all)
Important)
Somewhat)
Important)
Neutral) Important) Very)
Important)
1! How!important!is!it!to!you!that!your!Father!believes!you!
should!participate!in!physical!activity!that!makes!you!breathe!
hard!or!feel!tired?!!!
! ! ! ! !
2! How!important!is!it!to!you!that!your!Mother!believes!you!
should!participate!in!physical!activity!that!makes!you!breathe!
hard!or!feel!tired?!!!
! ! ! ! !
3! How!important!is!it!to!you!that!your!Sibling!believes!you!
should!participate!in!physical!activity!that!makes!you!breathe!
hard!or!feel!tired?!!!
! ! ! ! !
4! How!important!is!it!to!you!that!your!friends!believe!you!should!
participate!in!physical!activity!that!makes!you!breathe!hard!or!
feel!tired?!!!
! ! ! ! !
5! How!important!is!it!to!you!that!your!PE)teacher!believes!you!
should!participate!in!physical!activity!that!makes!you!breathe!
hard!or!feel!tired?!!!
! ! ! ! !
!
F.#Social#normative#beliefs#
! ! 0B10%) 11B25%) 26B50%) 51B75%) More)
than)75%)
1! What!proportion!of!students)at)this)high)school!do!you!
believe!do!physical!activity!that!make!them!breathe!hard!or!feel!
tired!during)PE?!
! ! ! ! !
2! What!proportion!of!your)close)friends!do!you!believe!are!
physically!active!during)PE?!
! ! ! ! !
!
G.#Goal#intentions#
! ! Definitely)
False)
False) Neutral) True) Definitely)
True)
1! I!plan!to!do!physical!activity!that!makes!me!breathe!hard!or!feel!
tired!during)PE.!
! ! ! ! !
2! I!will!try!to!do!physical!activity!that!makes!me!breathe!hard!or!
feel!tired!during!PE.!
! ! ! ! !
3! I!have!decided!to!do!physical!activity!that!makes!me!breathe!
hard!or!feel!tired!during)PE.!!!!!!!
! ! ! ! !
) )
H.#Implementation#intentions#
! ! Definitely)
False)
False) Neutral) True) Definitely)
True)
1! During)PE,!I!have!made!a!detailed!plan!regarding!WHEN!
(intro,!fitness,!game,!etc.)!to!do!physical!activity!that!makes!me!
breathe!hard!or!feel!tired.!!!!!!
! ! ! ! !
2! During)PE,!I!have!made!a!detailed!plan!regarding!HOW!to!do!
physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !
3! During)PE,!I!have!made!a!detailed!plan!regarding!HOW)OFTEN!
to!do!physical!activity!that!makes!me!breathe!hard!or!feel!tired.!
! ! ! ! !

44. 37
I.#Demographic#information#
Your)survey)is)not)complete!)Thank)you)for)your)time!)

45. APPENDIX B
REVIEW OF LITERATURE

46. 39
Quality physical activity experiences are those that prompt commitment and
adherence to active living, as well as those that facilitate outcomes such as moral
development, motor competence, positive self- perceptions, and positive affect (Smith,
2002). Investigating social experiences in physical activity with peers can be looked at in
many different intricacies. Therefore a literature review is warranted in order to gain
deeper knowledge and understanding on the impact of peers in physical activity. This
review focuses on (a) physical activity levels in children and adolescents, (b) physical
activity and peer influence and (c) the theory of triadic influence.
Physical Activity levels in children and adolescents
Physical activity is defined as any bodily movement produced by the contraction
of skeletal muscle that increases energy expenditure above a basal level. (US Department
of Health and Human Services, 2008). There is a growing concern about inadequate
physical activity levels among adolescents. According to the World Health Organization
(WHO), (2003) physical inactivity greatly contributes to medical costs; it is estimated
$75 billion in the USA in the year 2000 alone. Progressively leisure time for children and
adolescents has become more sedentary with the development of video games, television,
and computers. However physical activity behaviors adopted during adolescence are
likely to be maintained in adulthood (Telma, Yang, Laakso, 1997). Another study by
Kahn, Huang, Gillman, Field, Austin, Colditz and Frazier (2008) s examines patterns and
determinant of physical activity in U.S adolescents. Results showed that decline in
physical activity appeared to be steepest between the ages of 13 and 18, generally greater
for males rather than females.

47. 40
The Physical activity guidelines for Americans (2008) suggest that children and
adolescents should focus on the main types of activity: aerobic, muscle strengthening and
bone strengthening. It is stressed that all three are as important if health benefits are to be
maximized. Being active aerobically include activities such as walking, hopping,
skipping, and swimming, these activities increase cardiovascular fitness. Muscle
strengthening implies overloading muscle groups. This can be achieved in a variety of
ways, from climbing trees to lifting weights in a weight room. Bone strengthening
activities; produce force that is applied to the bones, that promotes bone growth and
strength. This can be produced by playing sports such as basketball, soccer and general
exercise by running and jumping for the daily recommendation of 60 minutes a day.
Benefits of physical activity. Although literature on the benefits of physical
activity in children and adolescents has been less extensive than with adults, health
related benefits associated with regular physical activity participation for children and
adolescents have been demonstrated through scientific research.
Physical Activity Guidelines for Americans Summary (2008); advocates there are
many health benefits to physical activity in children, adolescents and adults. Bone
strengthening is one effect of regular physical activity. Weight baring exercises promotes
bone growth and strength, examples for children include, walking, jumping. For
adolescents this will include activities such as weight lifting, running and jumping jacks.
Physical activity has many benefits that include; lower blood pressure, and
decreased adiposity (Strong, et al., 2005) Physical Activity Guideline for Americans
(Center for Disease Control and Prevention [CDC], 2008) stated many effects regular
physical activity improves. These include improvements of cardio-respiratory and

48. 41
muscular fitness, improvements of bone health, improvements of cardiovascular and
metabolic health and favorable body composition. Benefits of physical activity can be
categorized into two different categories physical and psychological.
Physical activity is also closely linked with psychological benefits such as higher
levels of self-esteem (Dietz, 1998; Sääkslahti, et al., 2004; Steinberg & Monahan, 2009).
Similarly many studies have provided strong evidence that physical activity is an
effective strategy for managing depression (Babyak, et al., 2000; Mather, et al., 2002).
Valois et al. reported that physical activity participation for youth was associated with
decreased depression, increased self-esteem, decreased anger, decreased psychological
stress, lower levels of mental health problems and increases in quality of life satisfaction.
Physical activity is closely linked with psychological benefits (Valois, Umstattd, Zullig,
& Paxton, 2008).
To summarize participation in physical activity has a significant role in promoting
a child’s holistic growth, development learning and wellbeing (Gallahue & Ozmun,
2002). The next sub section will exemplify obesity rates in children and adolescents,
along with current statistics.
Current data on obesity rates in children and adolescents. According to the
World Health Organization (2004), it is estimated that 10% of school children, between 5
and 17 years old are overweight or obese. There are several definitions of obesity and
overweight. The World Health Organization (WHO, 2011) defines ‘overweight’ and
‘obesity’ as abnormal or excessive fat accumulation that may impair health. The
worldwide prevalence of infantile and juvenile obesity has progressively increased in
recent decades, from 4.2% in 1990 to 6.7% in 2010 (Onis, Blössner &Borghi 2010). The

49. 42
percentage of children aged 6–11 years in the United States who were obese almost
tripled from 7% in 1980 to nearly 18% in 2010. Similarly, the percentage of adolescents
aged 12–19 years who were obese increased from 5% to 18% over the same period. In
2010, more than one third of children and adolescents were overweight or obese (Ogden,
Carroll, Kit, Flegal, 2012; National Center for Health Statistics, 2012). The Wisconsin
State Nutrition, Physical Activity, and Obesity Profile (2010), show 14.0% of adolescents
were overweight (≥ 85th and < 95th percentiles for BMI by age and sex, based on
reference data) and 9.3% were obese (≥95th percentile BMI by age and sex, based on
reference data) by age and sex respectively.
Current physical activity rates of children and adolescents. Adolescents who
achieved recommended level of physical activity was only 23.8%. Adolescents had to be
active for a total of at least 60 minutes per day on each of the 7 days prior to the survey.
A total of 12.9% did not participate in at least 60 minutes of physical activity on any day
during the 7 days prior to the survey. The U.S. Department of Health and Human
Services recommends that young people aged 6–17 years participate in at least 60
minutes of physical activity daily (CDC, 2012). Physical activity levels decline as grade
levels become higher, particularly as children progress into adolescence and toward the
end of school years (Wallhead & Buckworth, 2004).
In a national survey, 77% of children aged 9–13 years reported participating in
free-time physical activity during the previous 7 days (CDC, 2010). In 2011, only 29%
percent of high school students had participated in at least 60 minutes per day of physical
activity on each of the 7 days before the survey (CDC, 2011). Only 43.2% of adolescents
participated in daily physical education classes in an average week. 14% of high school

50. 43
students had not participated in 60 or more minutes of any kind of physical activity on
any day during the 7 days before the survey (CDC, 2011).
There are many ways to become or maintain being physically active, both in and
outside a school setting. Each individual has the flexibility to choose from a variety of
sports and activities to be physically active. Some include, walking, long distance
running, lifting weights, swimming, basketball, soccer, and cycling. In physical education
settings, Anshel, Freedson and Haywood (1991) defined student attitudes as the
perceptions of students concerning teachers and physical activity that affects the process
of learning and motivation.
In Summary figures between children and adolescents overweight and obesity
figures are very similar. Although there are many opportunities to be active both inside
and outside of the school setting, obviously increasing the amount of physical activity
provided to children and adolescents is not the solution to the pandemic.
Physical activity and peer influence
There have been a plethora of studies conducted linking a person’s attitude to
their level of physical activity. Multiple factors may account to a person’s attitude
towards participation; these include a person’s body shape or level of fitness (Winters,
Petrosa, & Charlton, 2003). A study conducted by Kahn et al (2008) found perceived
peer attitudes about body shape and fitness were associated with physical activity in both
boys and girls. For girls, being thin was associated positively with being physical activity.
However for boys, importance to one’s friends that they can be physically fit and
muscular was associated positively with the participation in physical activity.
A study conducted by Sallis, Prochaska and Taylor (2000), reviewed 54 studies

51. 44
correlating physical activity among adolescents. Peer influence was found to be
indeterminate. However measures of parental support from significant others was
consistently related to adolescent’s physical activity as well as sibling physical activity
was directly related.
Lehto, Reunamo and Ruismaki (2012) looked directly at children’s peer relations
and their impact on physical activity. Lehto et al., (2012) found children were most
physically active when they interacted with their peers. This study shows that children
with lower social involvement were more likely to be less physically active. Furthermore,
children that were more physically active sought each other’s company. In addition, Efrat
(2009) found that 7 out of the 13 studies reviewed provided evidence that peer
relationships may influence physical activity behaviors. A cross sectional study
conducted by Voorhees et al (2005), examined the relationship between peer influences
on 6th and 8th grade girls. The Findings show that there is a positive relationship between
peer influences and being physically active. Further research by Anderson, Laska,
Veblen-Mortenson, Farbakhsh, Dudovitz and Story (2012) looked at peer leadership.
In a similar study by Lever-Landis, Burant, Drotar, Morgan, Trapl and Kwoh
(2003) examined the relationship between a single friend and a group of friends on their
influence towards physical activity. The findings indicated friend’s social support and
encouragement was significant in predicting physical activity levels.
A cross-sectional survey study was conducted on urban adolescent females by
Saxena, Borzekowski and Rickert (2002) examining the proportion of girls engaging in
vigorous physical activity from a sample of 305 12-21 year old inner-city adolescent girls
took part in this study. The most significant predictors of regular physical activity were

52. 45
having most or all friends exercising and belonging to a sports team.
The social influences on adolescent physical activity primarily have been assessed
by adolescents’ perception of the social support they have received for being physically
active from their friends, family and other adults who are important in their lives.
Friends are typically similar on a wide range of characteristics such as gender, age,
socioeconomic background, attitudes and interests (Bot et al., 2005; Daddis, 2008;
Kiesner et al., 2003; Savin-Williams & Berndt, 1990). Social influences on physical
activity can occur throughout life, they are particularly important to study in children and
adolescents, for several reasons. First childhood and adolescence are a formative period
when friends are a primary point of reference (Erwin, 1998). Physical activity levels
during adolescence predict adult levels, and active children and adolescents are more
likely to become active adults. (Barnekow-Bergkvist, Heinberg, Janlert, & Jansson,
1996). Furthermore, friends may have a direct impact on young peoples’ attitudes and
beliefs about physical activity. For example, adolescents’ perceptions of peer norms have
been found to predict their attitudes toward physical activity and intentions to in gage in
physical activity (Baker, Little & Brownell, 2003).
Many different factors influence adolescent’s level of PA, such as social
influences and social support from peers and parents. In a study by Patnode, et al.,
(2010), examined the influence of demographic, individual, social and environmental
factors on physical activity among 10-17 year old boys and girls. Patnode, et al., found
that peer support was significant among boys for predicting moderate to vigorous
physical activity. However females were more affected by environmental factors such as
distance from places to be physically active also distance from school.

53. 46
Adolescents’ activity levels have been positively associated with perceived social
support from friends (Duncan, Duncan, & Strycker, 2005) and participation in physical
activity with friends (Voorhees et al., 2003). A study conducted by Patnode, Lytle,
Erickson, Sirard, Barr-Anderson, & Story (2010) found that their peers significantly
influenced boys, to perform moderate to vigorous physical activity. However girls were
significantly influenced by distance to their school. Other studies that also found there to
be no link between peer influence and physical activity are (Dowda et al. 2007; Gillander
& Hammarstrom, 2002).
Hsu, et al., (2011) found low levels of physical activity were associated with low
levels of family and friend support. However family social support was the only
significant indicator or moderate to vigorous physical activity.
The conclusions to be drawn for the current literature, is that there have been
many studies that have found a significant influence of peers regarding physical activity
levels. This influence has come from many different factors, whether it be organized,
club teams to recreational leagues or just simply for fun. Furthermore a number of
constructs are linked to peer influence, which can be broken down into a number of
constructs such as, peer modeling, peer support, popularity, and peer victimization.
To summarize social influences can occur throughout a lifetime, however it is at
the child’s developmental years that are most significant. It is critical to recognize the
effect social or peer influence is having on children and adolescents that promote them to
not be physically active.
Theory of triadic influence
The Theory of Triadic Influence (TTI) provides a single unifying framework that

54. 47
organizes the construct from many other theories (Flay, 2002). The TTI has primarily
been used in the health fields, with focus on alcohol and tobacco use (Bavarian, Flay,
Ketcham & Smith, 2013; Kaai, Leatherdale, Manske, & Brown, 2013). A study
conducted by Kaai, Leatherdale, Manske and Brown (2013) examined what student or
school factors differentiated current smokers from experimental smoker among Canadian
secondary school students. The TTI was used to try and comprehend all the different
factors, which makes adolescents begin and maintain smoking. The TTI theorizes that
youth smoking behaviors are a result of a combination and interaction, of individual or
intrapersonal, social context or broader social influences. (Leatherdale & Burkhalter,
2012). The social context influences mainly include exposure to friends (Lipperman-
Kreda, Paschall & Grude 2009; Sabistion et al., 2009). All social variables were guided
by existing literature and TTI, which were interpersonal factors such as gender, grade and
alcohol and marijuana use. In addition social context measures such as parents, siblings
and friends smoking status was measured. Another study which again looked at drug and
alcohol dependence (Barvarian, Flay, Ketcham & Smith, 2013). The TTI was chosen as
the theoretical framework, as it is a meta-theoretical framework; which allows constructs
from many theories. The Behaviors, Expectancies, Attitudes, and College Health
Questionnaire, was used in this study (2013) and the studies analyses were guided by the
TTI.
The TTI’s intrapersonal stream of influence focuses on characteristics of one’s
biology, personality, and demography that ultimately influence feelings of self-efficacy
(Bandura, 1977) and behavioral control (Ajzen, 1988) toward a health behavior (Flay et
al., 2009).

55. 48
The TTI has three categories for independent variables for levels of influence.
These include ultimate level influence, distal level influence and proximal level
influence. Ultimate level influence is where the individual has very little control over
influences for example the cultural environment. This means that it is the most difficult
for one person to change. Distal level influence is variables that exercise limited control
over an individual. Proximal level influences; still include influences from ultimate and
distal factors. However the TTI argues that decisions, intentions and experiences have a
direct influence on a specific behavior. (Fishbein & Ajzen, 1975; Flay, Snyder &
Petraitis, 2009).
The TTI’s social interpersonal stream of influence represents characteristics in an
individual’s immediate social setting that contribute to social normative beliefs (Ajzen &
Fishbein, 1980) regarding a health behavior (Flay et al., 2009).
In short although the theory has been applied to other areas other than physical
activity, I believe that the framework can be applied to this field focusing on children and
adolescents, which would provide a new avenue for future research and understanding.

56. 49
References
Adler, P. A., & Adler, P. (2008). Peer Power: Preadolescent Culture and Identity. New
Brunswick; NJ: Rutgers University Press.
Anshel, M. H., Freedson, P., & Haywood, K. (1991). Dictionary of the Sport and
Exercise Sciences. Champaign, IL: Human Kinetics.
Babyak, M., Blumenthal, J. A., Herman, S., Khatri, P., Doraiswamy, M., Moore, K.
Craighead, W. E., Baldewicz, T. T., & Krishnan, K. R. (2000). Exercise treatment
for major depression: Maintenance of therapeutic benefit at 10 months.
Psychosomatic Medicine, 62, 633 – 638.
Baker, C, W., Little, T, D., & Brownell, K, D. (2003). Predicating adolescent eating and
activity behaviors: role of social norms and personal agency. Health psychology,
22, (2), 189-198.
Barnekow-Bergkvist, M., Hedberg, G., Janlert, U., & Jansson, E. (2008). Physical
activity pattern in men and women at the ages of 16 and 34 and development of
physical activity from adolescence to adulthood. Scandinavian journal of
medicine & science in sports and exercise, 40, (1), 181-188.
Bavarian, N., Flay, B, R., Ketcham, P, L., & Smit, E. (2013). Illicit use of prescription
stimulants in a college student sample: A theory-guided analysis. Journal of Drug
and Alcohol Dependence, 1, (32), 665–673.
Bot, S. M., Engels, R. C. M. E., Knibbe, R. A., et al. (2005). Friend’s drinking behaviour
and adolescent alcohol consumption: The moderating role of friendship
characteristics. Journal of Addictive Behaviors, 30, 929-947.
CDC. (2010). The Association Between School-Based Physical Activity, Including
Physical Education, and Academic Performance. Atlanta, GA: U.S. Department of
Health and Human Services.
CDC, (2009). Division of Adolescent and School Health. The 2009 Youth Risk Behavior
Survey. Available online at http://www.cdc.gov/HealthyYouth/yrbs/index.htm.
CDC. (2011). Youth Risk Behavior Surveillance—United States, 2011. MMWR 2012,
61(SS-4).
Daddis, C. (2008). Similarity between early and middle adolescent close friends’ beliefs
about personal jurisdiction. Journal of Social Development, 17:1019e38.
De Onis, M., Blössner, M., & Borghi, E. (2010). Global prevalence and trends of
overweight and obesity among preschool children. American Journal of Clinical
Nutrition, 92, (12), 57--64.

57. 50
Dowda M, Pate RR, Sallis JF, et al. (2007). Agreement between student- reported and
proxy-reported physical activity questionnaires. Journal of Pediatric Exercise
Sciences, 19, (3), 310-318.
Erwin, P. (1998). Friendship in Childhood and Adolescence. New York, NY: Routledge.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction
to theory and research. Reading, MA: Addison Wesley.
Flay, B. R. (2002). Positive youth development requires comprehensive health promotion
programs. American Journal of Health Behavior, 26, (6), 407.
Flay, B. R., Snyder, F. J., & Petraitis, J. (2009). The Theory of triadic influence. In R. J.
DiClemente, R. A. Crosby & M. C Kegler (Eds.), Emerging Theories in Health
Promotion Practice and Research (Second ed., pp. 451-510). San Francisco, Ca:
Jossey: Jossey-Bass.
Gallahue, D, L., & Ozmun, J, C. (2002). Understanding motor development: Infants,
adolescents, adults. (5th ed.). Boston: McGraw-Hill Higher Education.
Gillander Gadin K, Hammarstrom A. (2002). Can school-related factors predict future
health behavior among young adolescents? Public Health, 116, (1), 22-29.
Heitzler, C. D., Levin, M,S., Duke, J., Huhman, M. (2006).Correlates of physical activity
in a national sample of children aged 9-13 years. Journal of Preventative
Medicine, 42, (4), 254-260.
Kaai, S, C., Leatherdale, S, T., Manske, S, R., & Brown, S, K. (2013). Using student and
school factors to differentiate adolescent current smokers from experimental
smokers in Canada: A multilevel analysis. Preventative medicine, 57, (2), 113–
119.
Kiesner, J., Poulin, F., & Nicotra, E. (2003). Peer relations across contexts: Individual-
network homophily and network inclusion in and after school. Journal of Child
Development, 74, 1, (3), 28-43.
Leatherdale, S.T., Burkhalter, R. (2012). The substance use profile of Canadian youth:
exploring the prevalence of alcohol, drug and tobacco use by gender and grade.
Journal of Addictive Behavior, 37, 318–322.
Lehto, S., Reunamo, J., & Ruismaki, H. (2012). Children’s peer relations and children’s
physical activity. Journal of Social and Behavioral Sciences, 45, 277-283.
Levers-Landis, C, E., Brunat, C., Drotar, D., Morgan, L., Trapl, E. S., & Kwoh, K.
(2003). Social support, knowledge, and self-efficacy as correlates or osteoporosis

58. 51
preventative behaviors among preadolescent females. Journal of Pediatric
Psychology, 17, 433-345.
Lipperman-Kreda, S., Paschall, M.J., & Grube, J.W. (2009). Perceived enforcement of
school tobacco policy and adolescents cigarette smoking. Journal of Preventive
medicine, 48, 562–566.
Mather, A. S., Rodriguez, C., Guthrie, M. F., McHarg, A. M., Reid, I. C., & McMurdo,
M. E. (2002). Effects of exercise on depressive symptoms in older adults with
poorly responsive depressive disorder: Randomised controlled trial. British
Journal of Psychiatry, 1, (80), 411–415.
McGuire, M. T., Neumark-Sztainer, D. R., Story, M. (2002). Correlates of time spent in
physical activity and television viewing in a multi-racial sample of adolescents.
Journal of Pediatric Exercise Sciences, 14, (1), 75.
National Center for Health Statistics. (2012). Health, United States, 2011: With Special
Features on Socioeconomic Status and Health. Hyattsville, MD; U.S. Department
of Health and Human Services.
Ogden, C,L., Carroll, M,D., Kit, B,K., Flegal, K,M.(2012). Prevalence of obesity and
trends in body mass index among US children and adolescents, 1999-2010.
Journal of the American Medical Association, 307 (5), 483-490.
Patnode, C, D., Lytle, L, A., Erickson, D, J., Sirard, J, R., Barr-Anderson, D., Story, M.
(2010). The relative influence of demographic, individual, social and
environmental factors on physical activity among boys and girls. International
Journal of Behavioral Nutrition and Physical activity, 7, 79.
Poulin, F., Cillessen, A. H. N., Hubbard, J. A., et al. (1997). Children’s friends and
behavioral similarity in two social contexts. Journal of Social Development, 2, 24-
36.
Sabiston, C.M., Lovato, C.Y., Ahmed, R., et al. (2009). School smoking policy
characteristics and individual perceptions of the school tobacco context: are they
linked to students' smoking status? Journal of Youth and Adolescents, 38, 1374–
1387.
Sallis, J, F., Prochaska, J,J., & Taylor, W, C. (2000). A review of correlates of physical
activity of children and adolescents. Journal of Medicine and Science in Sports
and Exercise, 32 (5), 963-975.
Savin-Williams, R., & Berndt, T.J. (1990). Friendship and peer relations. In: Feldman SS,
Elliott GR, editors. At the threshold: The developing adolescent. Cambridge, MA:
Harvard University Press, 277-307.

59. 52
Steinberg, L., & Monahan, K.C. (2007). Age differences in resistance to peer influence.
Developmental Psychology, 43, 1531 1543.
Stigman, S., Rintala, P., Kukkonen-Harjula, K., Kujala, U., Rinne, M., & Fogelholm, M.
(2009). Eight- year-old children with high cardiorespiratory fitness have lower
overall and abdominal fatness. International Journal of Pediatric Obesity, 4, 98-
105.
Telma, R, Yang, X, L., Laakso, L, et al. (1997). Physical activity in childhood and
adolescence as a predictor of physical activity in young adulthood. American
Journal of Preventative Medicine, 13, 317-323.
Trost SG, Sallis JF, Pate RR, Freedson PS, Taylor WC, Dowda M. (2003). Evaluating a
model of parental influence on youth physical activity. American Journal of
Preventative Medicine, 25, (4), 277–282.
U.S. Department of Health and Human Services. (2008). Physical Activity Guidelines for
Americans. Washington, DC: U.S. Department of Health and Human Services.
Valois, R. F., Umstattd, R., Zullig, K. J., & Paxton, R. J. (2008). Physical activity
behaviors and emotional self-efficacy: Is there a relationship for adolescents? The
Journal of School Health, 78 (6), 321-327.
Voorhees, C, C., Murray, D., Welk, G., Birnbaum, A., Ribisl, K, M., Johnson, C, C., et
al. (2005). The role of peer social network factors and physical activity in
adolescent girls. American Journal of Health Behavior, 29, 183-190.
Wallhead, T. L. & Buckworth, J. (2004). The role of physical education in the promotion
of youth physical activity, Quest, 56, 285–301.
World Health Organization, (2011) http://www.who.int/about/contacthq/en/index. html.
Winters, E, R., Petrosa R, L., Charlton T, E. (2003). Using social cognitive theory to
explain discretionary, “leisure time” physical exercise among high school
students. Journal of Adolescents Health, 32, (6), 436-42.
Ya-Wen, Hsu,. Chou, C,P., Nguyen- Rodriguez, S, T., McClain, A, D., Belcher, B, R., &
Spruijt-Metz, D. (2011). Influences of Social Support, Perceived Barriers, and
Negative Meanings of Physical Activity on Physical Activity in Middle School
Students. Journal of Physical Activity and Health. Human Kinetics, 8, 210-219.