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Journal of Early Adolescence
2015, Vol. 35(3) 353 –377
© The Author(s) 2014
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DOI: 10.1177/0272431614530807
jea.sagepub.com
Article
The Relationship of
Physical Fitness,
Self-Beliefs, and Social
Support to the Academic
Performance of Middle
School Boys and Girls
Sudhish Srikanth1, Trent A. Petrie1,
Christy Greenleaf1, and Scott B. Martin1
Abstract
We examined the influence of physical and psychosocial variables on math
and reading achievement test scores. Between 1 and 5 months prior to
taking annual standardized reading and math tests, a sample of (N = 1,211)
sixth through eight graders (53.7% girls; 57.2% White) self-reported levels of
physical activity, academic self-beliefs, general self-esteem, and social support
and participated in objective testing to obtain measures of body composition
(body mass index [BMI]) and cardiorespiratory fitness. Socioeconomic
status (SES) and state-based reading and math achievement test scores
were provided by the school district. Regression analyses revealed that
SES, academic self-beliefs, and cardiorespiratory fitness were the consistent
predictors of the students’ performance in reading and math; perceived
social support from family and friends and higher levels of self-esteem were
related to higher reading scores for the boys only. Our findings support
schools re-examining policies that have limited students’ involvement in
physical education classes.
1University of North Texas, Denton, TX, USA
Corresponding Author:
Trent A. Petrie, Department of Psychology, University of North Texas, 1155 Union Circle
#311280, Denton, TX 76203-5017, USA.
Email: Trent.Petrie@unt.edu
530807JEAXXX10.1177/0272431614530807Journal of Early AdolescenceSrikanth et al.
research-article2014
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354 Journal of Early Adolescence 35(3)
Keywords
academic performance, physical fitness, social support, self-esteem, middle
school students
Introduction
Physical inactivity, obesity, and inadequate cardiorespiratory fitness levels
are major problems among children and adolescents and have been related to
a host of physical and psychological health concerns, including poor aca-
demic performance (e.g., Ortega, Ruiz, Castillo, & Sjostrom, 2008). Early
adolescents’ academic achievement, particularly on state-based examinations
that may determine promotion to the next grade level, can have long-term
effects on their development in school and their ability to progress and be
successful, even into the secondary and post-secondary levels. Understanding
the factors related to their success, particularly ones that are amenable to
change, such as physical fitness and activity levels, is necessary for improv-
ing children’s and adolescents’ academic performances and the quality of
their school experiences.
Keeley and Fox (2009), in their review of 17 studies that investigated
either physical fitness or physical activity and academic achievement in chil-
dren and adolescents, concluded that both variables were related to higher
levels of performance, though effects were strongest for cardiorespiratory
fitness. Furthermore, they noted an association between children’s fitness
levels and better cognitive functioning and executive control (e.g., planning,
working memory, inhibition), which offers a potential mechanism to explain
the connection between cardiorespiratory fitness and academic performance.
Other research consistently has supported their conclusions, demonstrating
that better fitness, particularly aerobic (e.g., Chomitz et al., 2009; Cottrell,
Northrup, & Wittberg, 2007; Edwards, Mauch, & Winkelman, 2011; Rauner,
Walters, Avery, & Wanser, 2013; Roberts, Freed, & McCarthy, 2010;
Wittberg, Cottrell, Davis, & Northrup, 2010; Wittberg, Northrup, & Cottrell,
2009) and higher levels of physical activity (e.g., Fox, Barr-Anderson,
Neumark-Sztainer, & Wall, 2010; Kwak et al., 2009; Singh, Uijtdewilligen,
Twisk, Mechelen, & Chinapaw, 2012; Tomporowski, Davis, Miller, &
Naglieri, 2008), are associated with improvements in cognitive functioning
as well as better academic performance as measured through achievement
test scores and course and year-end grades.
Academic achievement, though, particularly among middle school stu-
dents, is determined by multiple physical and psychosocial factors (e.g.,
Kristjansson, Sigfusdottir, & Allegrante, 2010); thus, studies that have
examined it only in relation to physical activity and/or fitness have been
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Srikanth et al. 355
limited. Acknowledging a lack of comprehensive theories to address the
contextual and psychosocial variables that might explain the relation
between physical activity and children’s academic performance,
Tomporowski and colleagues (Tomporowski et al., 2008; Tomporowski,
Lambourne, & Okumura, 2011) proposed a working model to guide research-
ers in this area. In the model, they identified psychosocial factors (e.g., self-
esteem), physical fitness (e.g., cardiorespiratory), and health factors (e.g.,
obesity) as direct precursors to children’s mental functioning (e.g., academic
achievement), and suggested that socioeconomic status (SES) level and gen-
der may play a role as well and thus needed to be considered in future stud-
ies. This multidimensional model is consistent with Cottrell et al. (2007)
who suggested that future research examine not only body composition and
fitness levels, but also social, emotional, and environmental factors, such as
self-esteem and social support, so as to understand their relative importance
in predicting children’s academic performance. In the sections that follow,
we discuss these key variables in relation to academic performance (Cottrell
et al., 2007; Tomporowski et al., 2011), providing support for their inclusion
in this study.
Physical Activity and Physical Fitness
Physical activity is defined as any bodily movement produced by skeletal
muscles that requires energy expenditure (Caspersen, Powell, & Christenson,
1985), such as running or lifting weights, whereas cardiorespiratory fitness is
represented through the maximum rate the respiratory, cardiovascular, and
muscular systems can take in, transport, and use oxygen during exercise and
reflects the body’s ability to provide energy to the muscles using oxygen (The
Cooper Institute, 2007). Being physically active and physically fit have been
associated with improved academic performances in classroom grades and
standardized achievement test scores (e.g., Chomitz et al., 2009; Dwyer,
Sallis, Blizzard, Lazarus, & Dean, 2001; Edwards et al., 2011; Fox et al.,
2010; Keeley & Fox, 2009; Kristjansson et al., 2010; Roberts et al., 2010).
For example, Hillman et al. (2009) found, in an experimental study of male
and female preadolescent children, that a single 20-minute bout of treadmill
walking led to improved response accuracy in an incongruent visual stimuli
task as well as higher scores on a standardized test of reading comprehension;
although measured, the relation of gender and SES to the cognitive/achieve-
ment outcomes was not considered. In a cross-sectional study of middle and
high school students, Fox et al. (2010) examined the relation of self-reported
physical activity and sport team participation to self-reported course grades.
After controlling for SES level, they found that for high school girls, but not
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356 Journal of Early Adolescence 35(3)
boys, more time spent being physically active (at moderate to vigorous lev-
els) was associated independently with higher grade point averages. Singh et
al. (2012), in their systematic review of the literature, concluded that there
was strong evidence to link physical activity to higher levels of academic
performance across multiple dimensions (e.g., test scores).
Given the connection between being physically active and becoming aero-
bically fit, it is not surprising that cardiorespiratory fitness also has been
related to different measures of academic performance (e.g., Aberg et al.,
2009; Cottrell et al., 2007; Edwards et al., 2011; Rauner et al., 2013; Roberts
et al., 2010;Wittberg et al., 2010; Wittberg et al., 2009). For example, in a
cross-sectional study of fifth-, seventh-, and ninth-grade boys and girls from
California, students who met or exceeded FITNESSGRAM® (The Cooper
Institute, 2007) standards for aerobic fitness performed significantly better on
state reading, math, and language tests than the students who did not meet the
standards, even after controlling for SES level (Roberts et al., 2010). Using a
similar methodology, Rauner et al. (2013) discovered that even when the
influence of SES was controlled, aerobically fit fourth- to eighth-grade stu-
dents from Nebraska had greater odds of passing the state reading and math
tests compared with their aerobically unfit counterparts.
In a cross-sectional sample of fifth-grade boys and girls from West
Virginia, Wittberg et al. (2009) found that children who were in the healthy
fitness zone on cardiorespiratory fitness (as determined through the
FITNESSGRAM; The Cooper Institute, 2007), compared with those in the
needs improvement zone, scored significantly higher on state tests in read-
ing, math, science, and social studies; these results remained even after
controlling for gender, body mass index (BMI), and SES. In a separate
cross-sectional study, Wittberg et al. (2010) reported sex differences in fifth
graders’ academic performances that were based on the use of different
measures of aerobic fitness. For boys, only their times in the mile run were
related (inversely) to their performance in the achievement tests (e.g., read-
ing, math); for girls, only their performance in the Progressive Aerobic
Cardiovascular Endurance Run (PACER; a shuttle run) was associated with
their test scores. Similarly, in a cross-sectional study of third, fourth, and
fifth graders, a significant inverse relationship was found between one-mile
run times and reading and math test scores for girls; boys’ fitness levels,
however, were unrelated to their achievement test scores (Eveland-Sayers,
Farley, Fuller, Morgan, & Caputo, 2009). Although physical activity and
physical fitness have been associated independently with better academic
performances, fitness has not been examined extensively in relation to
other potential predictors to determine their relative influence (Tomporowski
et al., 2011).
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Srikanth et al. 357
Recently, researchers have identified potential cognitive and neurological
mechanisms that may underlie the connection between physical activity and
fitness and improved academic performance, including increased blood flow
to the brain, neural activity (e.g., P3 amplitude and latency) and response
accuracy, and improvements in cognitive functioning (Aberg et al., 2009;
Chaddock, Pontifex, Hillman, & Kramer, 2011; Chomitz et al., 2009; Hillman
et al., 2009; Keeley & Fox, 2009; Pontifex et al., 2011; Tomporowski et al.,
2008; Tomporowski et al., 2011). Consistently, aerobically fit children have
been found to have greater control of their executive functions, including
inhibition and working memory, and to be able to allocate cognitive resources
where needed and optimize behavioral responses to environmental learning
demands (Chaddock et al., 2011). Such cognitive processes are likely to
translate to fewer distractions and more time on task (e.g., studying), more
complete understanding of learning content (e.g., math), and better perfor-
mances in examinations that measure level of learning.
Body Composition
Body composition may be represented by individuals’ BMI (kg/m2), a pro-
portional measure of weight in relation to height, and a component of overall
health that may be related to academic performance (Tomporowski et al.,
2011). Studies have demonstrated small, but significant, relations between
BMI and academic performance (Castelli, Hillman, Buck, & Erwin, 2007;
Chomitz et al., 2009; Cottrell et al., 2007; Kristjansson et al., 2010; Roberts
et al., 2010; Welk et al., 2010), though its effects may be attenuated when
considered in conjunction with fitness and SES levels (Rauner et al., 2013).
For example, considered in conjunction with self-esteem, eating unhealthy
foods, and intake of fruits and vegetables, and after controlling for gender
and parental education level, BMI was related inversely (β = −.06) to grades
in core subjects, such as math, in a cross-sectional study of 9th- and 10th-
grade girls and boys (Kristjansson et al., 2010). In another cross-sectional
study, Castelli et al. (2007) reported that BMI was a significant predictor of
state-based academic achievement tests in math and reading, even after con-
trolling for the influences of the boys’ and girls’ other indices of fitness (e.g.,
PACER, curl-ups). However, a recent large, cross-sectional study demon-
strated that the association between BMI and state-based reading and math
test scores became nonsignificant when the students’ SES level was entered
into the model (Rauner et al., 2013). Thus, the effects of BMI on academic
achievement may vary and be explained by other factors, such as SES. Given
this finding, future studies should consider the potential influences of BMI,
but only when SES level is part of the prediction model.
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358 Journal of Early Adolescence 35(3)
Self-Beliefs: Academic and General
Academic self-beliefs, which are defined through students’ perception of
their proficiency (and competence) or interest in specific academic areas,
have been related positively to academic performance (Green, Nelson,
Martin, & Marsh, 2006; Liew, McTigue, Barrois, & Hughes, 2008; Osborne
& Jones, 2011; Pintrich & De Groot, 1990; Stringer & Heath, 2008; Valentine,
DuBois, & Cooper, 2004). For example, Pintrich and De Groot (1990) found,
in a cross-sectional study of male and female seventh graders, that academic
self-beliefs (as defined by feelings of competence and confidence in class
work) were related to better performances in homework, quizzes/exams,
essays/reports, and overall course grades. In a longitudinal study, fourth- and
fifth-grade boys’ and girls’ academic self-perceptions of competence in both
reading and mathematics, respectively, were significant predictors of their
scores on standardized reading and math tests 1 year later (Stringer & Heath,
2008). Similarly, Marsh, Trautwein, Ludtke, Koller, and Baumert (2005)
examined longitudinally the relation of academic self-concept and interests
in math to subsequent math achievement test scores and grades. Although
self-concept, as opposed to interests, had stronger effects on achievement and
grades, they found support for a reciprocal effects model across boys and
girls in which Time 1 math self-concept and interests predicted Time 2 grades
and achievement scores, and Time 1 math grades predicted the development
of interests and self-concept. In a meta-analysis of longitudinal studies exam-
ining the relation of self-beliefs to academic achievement, Valentine et al.
(2004) found support for a small but significant effect between the two vari-
ables. They noted that this effect was stronger when specific self-beliefs were
measured (e.g., in relation to math) and when self-beliefs and measures of
academic outcome are matched by subject area (e.g., math self-concept pre-
dicting math achievement test score). Students who perceive themselves as
being competent academically and interested in specific subjects may be
more motivated to study (and put forth more effort doing so), set more chal-
lenging academic goals, and use more effective studying and test-taking
strategies because such behaviors are consistent with their self-image as
being competent in those academic areas (Valentine et al., 2004). These
behaviors, in turn, would be expected to lead to improved academic perfor-
mance and, as Marsh, Trautwein, et al. (2005) demonstrated, influence the
development of subsequent interests and self-concept beliefs. Thus, in stud-
ies examining this connection, specific measures of academic self-beliefs,
such as in math, should be matched to the achievement area.
General self-beliefs, or self-esteem, have been conceptualized as repre-
senting individuals’ view of themselves as effective and capable, as having
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self-confidence and self-respect, and as satisfied with and proud of them-
selves as they currently are (Marsh, Parada, & Ayotte, 2004). In a nationally
based, cross-sectional sample of male and female adolescents, general self-
esteem was related to higher self-reported grades in core subject areas, such
as math and English (Kristjansson et al., 2010), even after controlling for
gender and parental education level. Self-esteem is associated with lower
levels of anxiety and depression, as well as higher levels of optimism and
coping, all of which may help students pay better attention in classes, be
more motivated toward their studies, and be able to handle the stressors
associated with maintaining a high level of academic performance (Lundy,
Silva, Kaemingk, Goodwin, & Quan, 2010; Rapport, Denney, Chung, &
Hustace, 2001). Students who feel positively about themselves and their
lives and believe they generally are capable and effective may bring the
necessary cognitive processing skills and maintain the needed attentional
focus and effort to improve their academic performances. However, the
association of general self-concept with academic performance, relative to
more specific indices of academic self-beliefs and to physical factors, such
as cardiorespiratory fitness, needs further study (Cottrell et al., 2007;
Valentine et al., 2004).
Social Support
Social support has been conceptualized as the degree to which individuals
are satisfied with the different types of support they receive, such as prob-
lem-solving and emotional assistance, and how much they can rely on dif-
ferent people in their lives, such as from family and friends, for such support
(Zimet, Dahlem, Zimet, & Farley, 1988). Middle school and high school
students with stronger perceptions of social support from peers, parents, and
teachers not only earned better grades in their classes but also had better
attendance, higher levels of engagement in classes, and higher levels of sat-
isfaction with their school experience (Rosenfeld, Richman, & Bowen,
2000). Even after accounting for the potential mediating effects of other
variables, such as anxiety and enjoyment, Ahmed, Minnaert, van der Werf,
and Kuyper (2010) found that both peer and parental support were related to
seventh-grade boys’ and girls’ math grades across three trimesters in their
cross-sectional study. Social support is likely to help students be more con-
fident in themselves and their abilities and feel in more control in challeng-
ing academic situations, which in turn can make their attitude more positive,
their motivation stronger, and their academic performance better (Ahmed
et al., 2010; Rosenfeld et al., 2000).
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360 Journal of Early Adolescence 35(3)
Gender Differences
Although almost all studies examining the relation of physical fitness, and
other psychosocial factors, to academic achievement have included boys and
girls in their samples, few have examined the potential effects of gender. In
the studies that have (e.g., Eveland-Sayers et al., 2009; Fox et al., 2010), the
associations of boys’ and girls’ fitness levels and performances in fitness tests
to academic outcomes (e.g., achievement tests) have varied. Furthermore,
Tomporowski et al. (2011) suggested that gender was a potential moderator
of the relation between psychosocial factors, physical fitness, and health fac-
tors (e.g., BMI) and students’ performance in academic achievement tests.
Thus, future fitness-academic performance research should examine this
relationship separately for boys and girls to determine the type of role, if any,
that gender may play.
The Current Study
In a number of large-scale, cross-sectional studies (e.g., Rauner et al., 2013;
Roberts et al., 2010; Wittberg et al., 2010; Wittberg et al., 2009), the positive
association of cardiorespiratory fitness with academic achievement has been
established in mixed samples of boys and girls. Few studies (e.g., Kristjansson
et al., 2010), however, have examined the effects of fitness in conjunction
with other psychosocial and physical factors to determine their relative
importance in understanding boys’ and girls’ academic performance.
Recently, Tomporowski et al. (2011) offered a conceptual model to guide
future research, identifying physical fitness, psychosocial factors, and health
factors as variables to consider when examining children’s and adolescents’
academic performance. Thus, consistent with recent research and working
models (Cottrell et al., 2007; Tomporowski et al., 2011), we took a multifac-
torial approach and examined the relation of cardiorespiratory fitness, physi-
cal activity levels, body composition, academic and general self-concept, and
social support to middle school students’ achievement in state administered
reading and mathematics examinations. Given the association that exists
between academic performance and SES (Cottrell et al., 2007), and the fact
that this variable may influence the effects of BMI (Rauner et al., 2013), we
controlled for it in our model as well. We hypothesized that, after controlling
for SES, cardiorespiratory fitness, physical activity, social support, general
and academic self-concept would be related positively to the children’s per-
formances in each academic achievement test; we expected children’s BMI
to be associated inversely with their performances. Because there is evidence
that the relationships between these variables and academic achievement
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Srikanth et al. 361
may differ between boys and girls (see Eveland-Sayers et al., 2009; Grissom,
2005; Tomporowski et al., 2011), we conducted the analyses separately for
the male and female students. Given that few studies have included gender as
an independent variable in this manner, we viewed this part of the analysis as
exploratory and did not make specific hypotheses as to how the strength of
the relations among the variables might vary between the boys and girls.
Method
Participants. Participants were 1,211 middle school students (650 girls) who
were drawn from five middle schools in a suburban school district in Texas.
The boy’s mean age was 12.45 years (SD = 1.00); 38.1% were in sixth grade,
37.4% in seventh grade, and 24.4% in eighth grade. In terms of race/ethnic-
ity, 57.2% were Caucasian, 24.2% were Mexican American, 9.1% were Afri-
can American, 1.1% were Asian, and 1.2% were American Indian. Consistent
with past research (Cottrell et al., 2007), SES was based on federal guidelines
for determining students’ status for free or reduced lunch based on family
income: 24.1% received free lunch, 6.2% received reduced lunch, and 69.7%
did not receive any reduction in their meals.
Mean age for the girls was 12.29 years (SD = 0.92); 37.8% were in sixth
grade, 35.5% in seventh grade, and 26.6% in eighth grade. Regarding race/
ethnicity, 58.6% were Caucasian, 23.4% were Mexican American, 9.2% were
African American, 2.3% were Asian, and 0.6% were American Indian. In
terms of SES, 24.6% received free lunch, 4.6% received reduced lunch, and
70.8% did not receive any reduction in their meals.
Measures
Cardiorespiratory fitness and body composition. The FITNESSGRAM (The
Cooper Institute, 2007) provides an objective measure of cardiorespiratory
fitness through the PACER test and body composition through the students’
BMI, which is represented in kg/m2. Administered by trained professionals,
the PACER is represented by the number of 20-meter laps students complete
within a specified timeframe and pace. Weight was measured by the research-
ers (in conjunction with the physical education teachers at each school) using
a Seca digital scale (Model 882) and recorded to the nearest 0.1 lb; scales
were recalibrated at the beginning of each testing day. Height and weight was
transformed into BMI within the FITNESSGRAM program. The FITNESS-
GRAM/ACTIVITY manual (The Cooper Institute, 2007) provides extensive
information about the validity and reliability of the PACER and BMI as mea-
sures of cardiorespiratory fitness and body composition, respectively.
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362 Journal of Early Adolescence 35(3)
Physical activity. The FITNESSGRAM (The Cooper Institute, 2007) provides
two self-report questions to assess how often individuals participated in
physical activities that were either aerobic in nature or focused on improving
strength. Each item is rated in terms of the number of days, out of the last
seven, they engaged in the described physical activities (e.g., for aerobic fit-
ness, a timeframe of 30 to 60 minutes or more per day is specified). Thus,
scores range from 0 to 7; higher numbers indicate more days (during the last
week) the individual engaged in that type of physical activity at the required
level. The FITNESSGRAM/ACTIVITY manual (see The Cooper Institute,
2007) provides extensive information about these questions as reliable and
valid representations of physical activity.
Academic self-beliefs. Two items from the Self-Description Questionnaire-I
(SDQ-I; Marsh, 1992; Marsh, Relich, & Smith, 1983) were used in the cur-
rent study to measure specific aspects of academic self-beliefs. The SDQ-I
was developed for children and early adolescents, and we included the items
“I am good at mathematics” (from the mathematics self-concept factor) and
“I like reading” (from the reading self-concept factor). We used these two
items for two reasons: (a) we wanted to use only single items to represent
each academic self-concept construct for the practical reason of shortening
the number of items on the survey, thereby reducing the potential of partici-
pant fatigue, and (b) these two items had the consistently highest factor load-
ings on their respective factors across samples of public and private school
students (Marsh et al., 1983). Participants rated each item on a 6-point scale
ranging from 1 (false) to 6 (true). Marsh and colleagues (Marsh, Ellis, Parada,
Richards, & Heubeck, 2005; Marsh et al., 1983; Marsh et al., 2004) have
provided extensive information regarding the validity of each self-concept
factor and that the factors are represented by the individual items, including
the two used in the current study. Furthermore, the use of single items from
self-concept measures has been established in previous studies with early
adolescents (e.g., Mitchell, Petrie, Greenleaf, & Martin, 2012; Petrie, Green-
leaf, & Martin, 2010).
General self-beliefs. The 10-item general self-esteem scale from the Self-
Description Questionnaire II General Self-Esteem (SDQII-GSE; Marsh,
1992) measures how proud and satisfied adolescents are with themselves and
the extent to which they see themselves as effective and capable (Marsh, Ellis
et al., 2005). On items such as “Overall, I have a lot to be proud of,” partici-
pants respond using a 6-point scale that ranges from 1 (false) to 6 (true). Total
score is the mean; higher scores represent greater esteem. Marsh, Ellis et al.
(2005) reported Cronbach’s alphas that ranged from .80 to .89 in a sample of
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Srikanth et al. 363
male and female adolescents; Cronbach’s alpha for the current sample was
.88. Marsh and colleagues (Marsh, 1992; Marsh, Ellis et al., 2005) have pro-
vided extensive information regarding the scale’s validity.
Social support. Eight items from the Multidimensional Scale of Perceived
Social Support (MSPSS; Zimet et al., 1988) were used to measure how much
help and support participants believe they receive from friends and family.
On items such as “My family helps me make decisions,” participants respond
using a 7-point scale that ranges from 1 (very strongly disagree) to 7 (very
strongly agree). Total score is the mean; higher scores represent more per-
ceived social support from friends and family. Zimet et al. (1988) reported a
Cronbach’s alpha of .88 and a 2- to 3-month test-retest reliability of .85 in a
sample of male and female undergraduates; Cronbach’s alpha for the current
sample was .89. Zimet and colleagues (Zimet et al., 1988; Zimet, Powell,
Farley, & Werkman, 1990) have demonstrated the scale’s validity.
Academic achievement. The school district provided the students’ scores on
the state’s standardized reading and mathematics examinations (i.e., The
Texas Assessment of Knowledge and Skills [TAKS]). Each school district in
the state administers these examinations on the same dates (for grade and
exam) during the month of April each academic school year. Examinations
are scored at the state level and then reported to each district. Scores used in
the current study were from examinations taken in April 2010.
Demographic information. The school district provided information on the stu-
dents’ race/ethnicity, age, grade level, and SES. SES level was based on fed-
eral guidelines for determining which students qualified for free or reduced
lunches at the school based on family income (www.fns.usda.gov/cnd/
Lunch/). Based on these data, students’ SES levels were classified as either
no assistance (high), partial assistance (medium), or full assistance (low).
Procedure
Approval for the study was received from the university’s Institutional
Review Board (IRB) for Human Subjects Research as well as from the
school district’s associate superintendent and the principals at each of the
five middle schools. Prior to participating in the study, parental consent
and child assent were obtained. At each school, the authors assisted PE
instructors in the administration of the FITNESSGRAM protocol to obtain
the state-required, annual fitness testing results during the 2009-2010 aca-
demic year.
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364 Journal of Early Adolescence 35(3)
FITNESSGRAM testing occurred at each school during a 1-week period
that was scheduled between November 2009 and March 2010; the testing dates
were determined by the principal at each school. During each week-long ses-
sion, the children completed the PACER as well as had their height and weight
measured. The students from whom consent and assent had been obtained also
completed a larger survey that included the previously described question-
naires during their PE classes. The complete survey took approximately 35
minutes to finish. To link questionnaire data to the results from their
FITNESSGRAM tests and with data supplied by the district, participants put
their student ID numbers (but no other identifying information) on their sur-
veys. Following completion of the survey, students were entered into a random
drawing for a series of cash prizes that were given away at each school.
Data Analysis
First, we addressed the issue of missing data and found that only between 0%
and 1.9% were missing across the questionnaire items. Because items were
either missing completely at random or at random, we replaced the values
using the expectation maximization procedure (Schlomer, Bauman, & Card,
2010). Second, we examined the distributional properties (e.g., skewness) of
all the measures and found them to be within acceptable levels, so no trans-
formations were made to the data. Next, we computed the zero-order correla-
tions among all the variables separately by gender.
To determine the relation of the different variables to the boys’ and girls’
performance in their math and reading examinations, we used hierarchical
regression and conducted the analyses separately by gender. For each regres-
sion model, there were two steps. At Step 1, we entered the families’ SES level
(as defined through the students’ qualifying for free or reduced lunches in
school) to control for influences of social affluence, prosperity, and education
(Cottrell et al., 2007; Edwards et al., 2011; Roberts et al., 2010). At Step 2, we
entered the remaining physical and psychosocial variables, including physical
fitness, physical activity (aerobic and strength), body composition (i.e., BMI),
reading or math self-concept score (matched to the achievement test being used
as the criterion variable), general self-concept, and social support.
Results
Descriptive Statistics
Correlations, means, and standard deviations for both the predictor and cri-
terion variables are presented by gender in Table 1. The correlations among
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365
Table 1. Means, Standard Deviations, and Pearson’s Product-Moment Correlations for the Criterion and Predictor Variables.
Variable 1 2 3 4 5 6 7 8 9 10 11
1. Reading — .65** .38** .21** .29** .25** .00 .17** .14** .18** .18**
2. Math .63** — .32** .45** .25** .26** −.08* .16** .15** .24** .14**
3. SES .31** .27** — .19** .13** .22** −.15** .16** .21** .24** .18**
4. SDQ-math .20** .41** .10* — .22** .14** −.04 .19** .22** .39** .21**
5. SDQ-reading .16** .12* .06 .27** — −.07 .01 .08 .04 .14** .16**
6. PACER .23** .27** .15** .06 −.10* — −.34** .25** .34** .24** .14**
7. BMI −.05 −.11* −.18** −.05 −.01 −.43** — −.03 −.11* −.14** −.07
8. Aerobic .07 .08 .11* .16** .02 .26** −.05 — .53** .22** .16**
9. Strength .14** .12* .12* .17** −.01 .36** −.11* .50** — .23** .15**
10. SDQ .25** .20** .18** .33** .15** .22** −.19** .19** .25** — .47**
11. MSPSS .26** .17** .14** .24** .26** .01 −.03 .13* .09 .35** —
Mean girls (SD) 807.64
(94.43)
764.10
(89.99)
— 4.18
(1.58)
4.35
(1.73)
30.08
(14.25)
21.01
(4.71)
4.08
(2.20)
4.75
(1.90)
4.95
(0.90)
5.52
(1.33)
Mean boys (SD) 785.30
(96.26)
760.05
(84.63)
— 4.56
(1.53)
3.91
(1.82)
37.50
(18.50)
21.58
(7.92)
3.71
(2.33)
5.04
(1.92)
5.05
(0.83)
4.97
(1.53)
Note. Girls above the diagonal (n = 650); boys below the diagonal (n = 561). Reading = TAKS reading scores (range = 249 to 1,002); Math = TAKS
math scores (range = 477 to 1,025); SES = socioeconomic status based on students qualifying for federal assistance in school meal programs; SDQ-
math = math self-concept (range = 1 [low] to 6 [high]); SDQ-reading = reading self-concept (range = 1 [low] to 6 [high]); PACER = cardiorespiratory
fitness test (range = 0 to 100 laps); BMI = body mass index (kg/m2); Aerobic = days of aerobic activity (range = 0 [low] to 7 [high]); Strength = days
of muscular exercises (range = 0 to 7); SDQ = Self-Description Questionnaire (range = 1 [low] to 6 [high]); MSPSS = perceived social support from
family and friends (range = 1 [low] to 7 [high]). TAKS= Texas Assessment of Knowledge and Skills; PACER = progressive aerobic cardiovascular
endurance run; MSPSS = multidimensional scale of perceived social support.
*p < .05. **p < .005.
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366 Journal of Early Adolescence 35(3)
the predictor variables ranged from −.01 to −.43 and .01 to .53, which sug-
gests that multi-colinearity would not be an issue during the regression
analyses.
Regression Analyses
Reading achievement. For the boys, the inclusion of SES at Step 1 was signifi-
cant, accounting for 9.7% of the variance, adj. R2 = .095, F(1, 559) = 59.78,
p < .0001. Step 2 of the model, where we included the physical and psycho-
social variables, was significant and accounted for an additional 12.1% of the
variance, F(7, 552) = 12.23, p < .0001. The overall model was significant,
accounting for 22% of the variance (adj. R2 = .21) of the boys’ reading scores,
F(8, 552) = 19.23, p < .0001. Within the full model, after controlling for
household SES level, being more aerobically fit (i.e., PACER), liking read-
ing, feeling supported by friends and family, having a positive general self-
concept, and having a higher BMI were associated with better performances
in the TAKS reading exam. See Table 2 for the detailed statistics from Step 2
of the regression analysis.
For the girls, the inclusion of SES level was significant, accounting for
14.5% of the variance, adj. R2 = .143, F(1, 648) = 109.61, p < .0001. Step 2,
which included entry of the remaining variables, accounted for an additional
11.8% of the variance, F(7, 641) = 14.65, p < .0001. The overall model was
significant, accounting for 26.3% of the variance (adj. R2 = .253) of the girls’
reading scores, F(8, 641) = 28.54, p < .0001. Within the full model, after
controlling for the girls’ families’ SES, several variables were related to bet-
ter performances in the TAKS reading test: being more aerobically fit, liking
reading, and having a higher BMI (see Table 2 for detailed statistics from
Step 2 of the model).
Math achievement. For the boys, the entry of SES level was significant,
accounting for 7.2% of the variance, adj. R2 = .070, F(1, 559) = 43.29, p <
.0001. Step 2, in which we entered the remaining physical and psychosocial
variables, was also significant, F(7, 552) = 22.34, p < .0001, ΔR2 = .21. The
overall model accounted for 27.7% (adj. R2 = .266) of the math test variance,
F(8, 552) = 26.40, p < .0001. After controlling for the boys’ families’ SES
levels, aerobic fitness and being good at mathematics were associated with
better performances in the math TAKS test (see Table 3).
For the girls, the inclusion of SES at Step 1 of the model was significant,
accounting for 9.9% of the variance, adj. R2 = .098, F(1, 648) = 71.50, p <
.0001. At Step 2, inclusion of the remaining variables was also significant,
F(7, 641) = 23.69, p < .0001, ΔR2 = .19. The overall model accounted for
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Srikanth et al. 367
28.4% (adj. R2 = .276) of the variance in the math scores, F(8, 641) = 31.85,
p < .0001. After controlling for their families’ SES level, the girls’ level of
cardiorespiratory fitness and the extent to which they reported being good at
mathematics were associated with better performances in the math TAKS test
(see Table 3).
Discussion
The students’ cardiorespiratory fitness levels, regardless of whether they
were boys or girls, were related to better performances in the state math and
reading tests, which is consistent with past studies (e.g., Aberg et al., 2009;
Table 2. Hierarchical Regression Analyses Predicting Reading Achievement for
Boys (n = 561) and Girls (n = 650) at Step 2 of the Model.
Step/predictor B SE B βt
Boys
SES 28.53 4.39 .25 6.49***
PACER 1.26 0.24 .24 5.34***
BMI 2.52 0.83 .13 3.04**
Days of aerobic activity −3.28 1.82 −.08 −1.81
Days of strength activity 1.80 2.29 .04 .79
I like reading 6.43 2.10 .12 3.07**
SDQ-GSE 12.62 4.94 .11 2.55*
MSPSS 10.54 2.62 .17 4.02***
Full model R2 = .22, Overall F(8, 552) = 19.228***
Girls
SES 33.26 3.96 .30 8.40***
PACER 1.52 0.26 .23 5.85***
BMI 2.47 0.73 .12 3.39**
Days of aerobic activity 2.82 1.75 .07 1.62
Days of strength activity −2.13 2.07 −.04 −1.03
I like reading 13.94 1.91 .26 7.30***
SDQ-GSE 0.44 4.24 .01 0.10
MSPSS 3.87 2.76 .06 1.40
Full model R2 = .26, Overall F(8, 641) = 28.54***
Note. Step 2 represents the final step of the model when all predictors have been entered.
SES = socioeconomic status; PACER = progressive aerobic cardiovascular endurance run;
BMI = body mass index; SDQ-GSE = Self-Description Questionnaire–General Self-Esteem;
MSPSS = Multidimensional Scale of Perceived Social Support.
*p < .05. **p < .005. ***p < .0005.
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368 Journal of Early Adolescence 35(3)
Chomitz et al., 2009; Cottrell et al., 2007; Edwards et al., 2011; Grissom,
2005; Rauner et al., 2013; Roberts et al., 2010). Castelli et al. (2007) found
that the number of PACER laps children ran, but not other measures of fitness
(e.g., number of sit-ups), was related to higher scores on state reading and
math exams. Although past studies (e.g., Grissom, 2005; Kwak et al., 2009)
have reported gender differences in how children’s physical activity and fit-
ness levels relate to academic achievement, our results suggest that the aero-
bic fitness levels of middle school boys and girls, at least as measured by the
PACER test, have comparable positive relations to their performances in
state-mandated math and reading achievement tests. Even though the stu-
dents’ self-reported involvement in physical activity (i.e., aerobic, strength)
Table 3. Hierarchical Regression Analyses Predicting Mathematics Achievement
for Boys (N = 561) and Girls (N = 650) at Step 2 of the Model.
Step/predictor B SE B βt
Boys
SES 20.28 3.71 .21 5.64***
The PACER 1.21 0.20 .26 6.10***
BMI 0.85 0.70 .05 1.22
Days of aerobic activity −2.20 1.54 −.06 −1.43
Days of strength activity −1.27 1.94 −.03 −0.65
I am good at math 21.15 2.16 .38 9.81***
SDQ-GSE −1.69 4.29 −.02 −0.39
MSPSS 3.37 2.18 .06 1.54
Full model R2 = .28, Overall F(8, 552) = 26.40***
Girls
SES 21.97 3.71 .21 5.92***
The PACER 1.05 0.24 .17 4.35***
BMI 0.30 0.68 .02 0.44
Days of aerobic activity 1.58 1.64 .04 0.97
Days of strength activity −2.54 1.95 −.05 −1.31
I am good at math 22.37 2.11 .39 10.63***
SDQ-GSE 0.95 4.15 .01 0.23
MSPSS −0.30 2.58 −.01 −0.12
Full model R2 = .28, Overall F(8, 641) = 31.85***
Note. Step 2 represents the final step of the model when all predictors have been entered.
SES = socioeconomic status; PACER = progressive aerobic cardiovascular endurance run;
BMI = body mass index; SDQ-GSE = Self-Description Questionnaire–General Self-Esteem;
MSPSS = Multidimensional Scale of Perceived Social Support.
*p < .05. **p < .005. ***p < .0005.
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Srikanth et al. 369
was associated with higher levels of cardiorespiratory fitness, it was only the
students’ aerobic fitness that predicted their academic performances. Higher
levels of fitness have been associated with improvements in cognitive con-
trol, including inhibition (ability to selectively pay attention to relevant infor-
mation) and working memory, as well as increases in response accuracy and
more cognitive flexibility to handle task demands (e.g., Chaddock et al.,
2011; Pontifex et al., 2011), which may explain why there was a positive rela-
tion between level of aerobic fitness and the children’s performance in their
exams. Although past studies have provided support for both physical activ-
ity (e.g., Singh et al., 2012) and physical fitness (e.g., Keeley & Fox, 2009),
their relative effects on academic performance have not been sufficiently
investigated. Thus, it will be important to determine the extent to which each
variable has an independent effect on children’s academic achievement and
whether fitness serves as a mediator for the influences of physical activity
levels (Tomporowski et al., 2011). Furthermore, in such studies, obtaining
objective measures of aerobic fitness (as was done in our study) and physical
activity will be important.
As expected, the children’s math self-belief was related significantly to
their performances in the math exams; no gender differences were found.
Because our measure of math self-beliefs focused on competency (i.e., “I
am good at mathematics”) as opposed to interests, it makes sense that the
measure of general self-beliefs, which provided an assessment of how
capable and effective the children thought they were, was unrelated to the
academic outcome. Basically, the boys and girls who believed they were
good at math, as opposed who just felt good about themselves generally,
performed better in the math exam, which is consistent with the matching
hypothesis discussed by Valentine et al. (2004). Similarly, Marsh, Trautwein,
et al. (2005) found that, in different samples of seventh-grade boys, their
perceptions of math self-concept predicted their performances in standard-
ized math achievement tests taken within the same academic year and over
the span of 2 academic years (i.e., from Grade 7 to Grade 8). Students who
perform well on academic tasks, and then attribute their success to internal
factors, such as effort, are likely to see increases in their academic self-
concept specific to the areas in which they have experienced the success
(see Marsh, Trautwein, et al., 2005). Thus, providing students with the tools
to be academically successful and helping them develop a belief in their
specific abilities may have long-term positive effects on their academic
performances in those areas.
For reading, the academic self-belief variable, which assessed more inter-
est than competence (i.e., “I like reading”), again was related positively to
both the boys’ and girls’ achievement scores, which is consistent with
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370 Journal of Early Adolescence 35(3)
studies that have demonstrated a prospective connection between academic
interests and subsequent performance in similarly matched tests (e.g.,
Marsh, Trautwein, et al., 2005). However, for the reading test scores, BMI
and other remaining psychosocial variables also were related, and the results
differed for the boys and girls. For the reading exam, the more support the
boys felt from friends and family and the more effective, capable, and posi-
tively they saw themselves generally, the better they did on the reading
exam; no such significant relations emerged for the girls. Reading has long
been viewed as a feminine activity (e.g., Cummings, 1994; Katz & Sokal,
2003), so girls experience little social disapproval when they read or express
being interested in reading. And, in our study, girls reported liking reading
more than the boys, and the correlations between reading interest and read-
ing achievement were higher for the girls (.29) than for the boys (.16). Boys,
on the other hand, run the risk, particularly in early adolescence, of being
teased and ostracized for spending time reading, perhaps then focusing
instead on what are perceived as more masculine academic pursuits (i.e.,
math and science) and developing more competence (and confidence) in
those areas. In our study, and consistent with past research (e.g., Marsh,
Trautwein, et al., 2005), the boys reported higher scores on math self-con-
cept than did the girls. Yet, without reading, learning and performance in
reading examinations are likely to suffer. Thus, boys who feel supported by
peers and family members and who generally feel competent, capable, and
effective in their lives may be more willing to read, despite potential social
and relational costs, and experience the benefit in terms of better academic
performances.
Although the bivariate relations between BMI and reading test scores
were nonsignificant for both boys and girls, in the regression models, with
the inclusion of the other variables, BMI became a significant, and positive,
predictor of reading achievement. This finding is both counterintuitive as
well as inconsistent with the past research (e.g., Eveland-Sayers et al., 2009;
Grissom, 2005; Kristjansson et al., 2010). For example, Castelli et al. (2007)
found that BMI was related inversely to math and reading test scores, even
when fitness was in the model and positively related to the children’s aca-
demic performance. Similarly, higher BMIs predicted poorer performances
in core course grades even as being more physically active was related to
better grades (Kristjansson et al., 2010). Other researchers (e.g., Cottrell et
al., 2007; Rauner et al., 2013), however, have found that the effects of BMI
became nonsignificant in their prediction models when other variables, such
as fitness or SES, were included. It is likely that in our analysis a suppression
effect was operating, such that the inclusion of fitness and SES with BMI
changed its relation to reading scores (Tabachnick & Fidell, 2013). More
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Srikanth et al. 371
research is needed to better understand the effects of BMI on academic per-
formance, particularly in conjunction with physical fitness and activity levels
as well as their family SES.
Limitations and Directions for Future Research
There are a few limitations to the present study that warrant discussion.
First, most of the psychosocial and physical variables used were self-report,
and we used single-item indicators of academic self-beliefs. Self-report may
be influenced by response biases and inaccurate reporting, and single-item
measures of constructs may not be as valid or reliable as the original factors
from which they are drawn. We did, though, incorporate objective measures
of cardiorespiratory fitness and body composition, and the use of single-
item measures in large-scale studies of young adolescents is not uncommon
to represent latent constructs (see Neumark-Sztainer, Wall, Larson,
Eisenberg, & Loth, 2011; Neumark-Sztainer, Wall, Story, & Standish, 2012).
In future studies, researchers might consider a more objective measure of
physical activity, such as having students wear accelerometers for a 1- to
2-week period, to complement the manner in which physical fitness was
assessed. Such an approach would allow for a more objective and complete
examination of the relative effects of physical activity and fitness on aca-
demic performance. Second, the sample was obtained from only one school
district in the southern United States, thereby limiting its generalizability to
similar suburban areas. The sample, however, was diverse in terms of racial/
ethnic and SES, and accurately represented the overall demographics of the
students in the district. Future studies might examine the influence of such
physical and psychosocial variables in urban or rural districts and among
high school students. Third, not all relevant physical and psychosocial fac-
tors were included in the study. We did use variables that had been shown to
relate to academic achievement, but time constraints placed on us by the
district in terms of access to the students prevented us from including other
potential predictors, such as anxiety, depression, nutritional status, to name
a few. Researchers may want to examine the relative predictive utility of
these other factors, as well as variables such as student delinquency, to deter-
mine their long-term effect on academic achievement. Finally, our data were
cross-sectional and we could not determine the temporal relationships
among the variables. In future studies, using cross-lagged panel analysis,
researchers could use longitudinal data to determine the extent to which fit-
ness (and perhaps other variables) actually predicts students’ subsequent
academic performances while controlling for the effects of past academic
achievement and past levels of fitness.
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372 Journal of Early Adolescence 35(3)
Implications
Our results are consistent with past research findings that have shown a mod-
erate and consistent relationship between fitness, aerobic in particular, and
children’s and early adolescents’ academic performances (as measured across
course grades and state achievement test scores). As such, these findings have
implications for potentially boosting middle school students’ academic
achievement. First, students’ confidence in their academic abilities in each
subject area was related strongly to their performances in the respective
examinations. Helping children achieve early academic successes upon
which they can build may lead to improvements in self-concept and a will-
ingness to engage in more complex and challenging learning in the future.
The more children believe in their own academic abilities, and understand
that their efforts lead to success, the more likely they are put in the time and
focus needed to be successful academically. Helping children see the connec-
tion between their efforts and their achievement is a necessary first step
(Dweck, 2006). Second, given that cardiorespiratory fitness was associated
with higher scores on both tests, even after controlling for SES, it makes
sense to dedicate time in which children can be physically active, such as
during PE classes, to have opportunities to become more fit. Although dis-
tricts often view PE classes as secondary to their academic mission (e.g.,
Grissom, 2005), students’ are likely to receive tangible academic benefits
from their involvement in PE classes and by improving their cardiorespira-
tory fitness; there is no evidence that increased involvement in school-based
physical activity has a detrimental effect on academic achievement (see
Keeley & Fox, 2009). If PE classes are not a potential venue for increasing
involvement in physical activity, schools might consider supporting before
school walking programs for kids who arrive early or after school programs
that allow students’ access to the gyms and other areas to be physically active.
We examined the relative utility of physical and psychosocial variables
in relation to middle school students’ academic performance in state-man-
dated math and reading examinations. After controlling for the students’
families’ SES level, we found that level of cardiorespiratory fitness, but
not actual involvement in physical activity (aerobic and strength), was
associated consistently with how the students’ performed in their math and
reading exams. This finding has policy implications when it comes to
whether, and for how long, students will take PE classes, and what com-
munities are doing to provide children and adolescents with easy and safe
access to environments, such as parks, where they can be physically active
and become physically fit. It also highlights the importance of students
having opportunities to develop their cardiorespiratory fitness, whether in
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Srikanth et al. 373
school-sponsored PE classes or through community or private sport and
activity opportunities.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: This study was funded by a grant from
the National Association for Sport and Physical Education.
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Author Biographies
Sudhish Srikanth was a student in the Texas Academy of Mathematics and Science
(TAMS) at the University of North Texas; he currently is an undergraduate at the
University of North Texas.
Trent A. Petrie, PhD, is a professor in the Department of Psychology and Director of
the Center for Sport Psychology and Performance Excellence at the University of
North Texas.
Christy Greenleaf, PhD, is an associate professor in the Department of Kinesiology,
Health Promotion, and Recreation at the University of North Texas.
Scott B. Martin, PhD, is a professor in the Department of Kinesiology, Health
Promotion, and Recreation at the University of North Texas.
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