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Content may be subject to copyright.
Content uploaded by Jeffrey Martin
Author content
All content in this area was uploaded by Jeffrey Martin
Content may be subject to copyright.
Content uploaded by Jeffrey Martin
Author content
All content in this area was uploaded by Jeffrey Martin
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RQES: June 2011 1
Martin, McCaughtry, Flory, Murphy, and Wisdom
Key words: health, [AQ: Use up to 3 more terms that are
not in the title.]
R
esearch focused on underserved children’s physical
activity (PA) behavior and fitness is increasingly im-
portant. Underserved children, such as minority children
living in low-income households, do not engage in enough
PA, either in or out of school (Martin et al., 2005), and
often lack fitness (Lindquist, Reynolds, & Goran, 1999),
compared to Caucasian children. Children of lower so-
cioeconomic status (SES) and minority children are at
greater risk for overweight and obesity, relative to higher
SES and Caucasian children (Gordon-Larsen, Nelson,
Page, & Popkin, 2006), and they engage in more sedentary
behavior. In general, children living in low-income house-
holds also underachieve and have a higher frequency for
dropping out of school (Taylor, 2005). Increasing PA has
been suggested as one way to improve academic achieve-
ment, given its link to cognitive processes (Sibley & Etnier,
2003). In addition to cognitive benefits, regular PA also
provides numerous mental and physiological benefits
(Friedenreich & Orenstein, 2002; U.S. Department of
Health and Human Services and U.S. Department of
Education [USDHHS], 2000).
Underserved children (non-White, low-income house-
holds), because they are less likely to be active, do not
fully enjoy these substantial benefits. Thus, research
geared toward understanding factors associated with
underserved children’s efforts to be physically active is
of particular value. Much research to date has focused
on important social-cognitive constructs, but far fewer
efforts have targeted the influence of the environment
on PA (Sallis, Prochaska, & Taylor, 2000). For instance, in
their research with underserved minority groups, Martin
and colleagues (Martin et al., 2005; Martin, Oliver, &
McCaughtry, 2007; Martin, McCaughtry, & Shen, 2008;
Martin & McCaughtry, 2008b), using cognitive and social
variables, accounted for a small but important amount of
variance (i.e., 10%) in PA.
Using ecologic models, researchers have recently
started to measure and assess how social and physical
Using Social Cognitive Theory to Predict Physical Activity
and Fitness in Underserved Middle School Children
Jeffrey J. Martin, Nate McCaughtry, Sara Flory, Anne Murphy, and Kimberlydawn Wisdom
Submitted: November 11, 2008
Accepted: October 19, 2009
Jeffrey J. Martin, Nate McCaughtry, Sara Flory are with the
Division of Kinesiology, Health, and Sport Studies at Wayne
State University. Anne Murphy is with Healthy Kids Evalua-
tion Services,
[AQ: Which city?]. Kimberlydawn Wisdom
is with the Michigan Department of Community Health
[AQ:
Which city?]
Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in
underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to
predict PA and fitness in middle school children (N = 506, ages 10–14 years). Using multiple regression analyses we accounted for
12% of the variance in PA and 13–21% of the variance in fitness. The best predictors of PA were barrier self-efficacy, classmate
social support, and gender; whereas, only gender predicted fitness. The results affirmed the importance of barrier self-efficacy and
gender differences. Our findings regarding classmate social support are some of the first to illuminate the importance of school-specific
peers in promoting PA.
Research Quarterly for Exercise and Sport
©2011 by the American Alliance for Health,
Physical Education, Recreation and Dance
Vol. 82, No. 2, pp. 1–
2 RQES: June 2011
Martin, McCaughtry, Flory, Murphy, and Wisdom
environmental factors influence PA (Sallis, 2009). Bron-
fenbrenner’s (1989) ecological systems theory employed
a multidimensional perspective of environmental influ-
ences on behavior by examining microsystems, meso-
systems, exosystems, and macrosystems. It outlined how
social environments (e.g., peers, classes, schools, families,
neighborhoods) and physical environments (e.g., school,
playground, neighborhood) influence PA behaviors. Most
PA investigators have examined perceptions [AQ: Whose?]
of the neighborhood built-environment, although re-
searchers recently started to examine children’s percep-
tions of the school environment (e.g., Robertson-Wilson,
Lévesque, & Holden, 2007).
Examining the school environment is a particularly
important consideration in underserved communities,
because children often have limited equipment and play
areas are often unsafe or in poor condition (McCaughtry,
Martin, Kulinna, & Cothran, 2006a). Physical education
teachers in urban schools also face unique challenges
(McCaughtry, Barnard, Martin, Shen, & Kulinna, 2006).
For instance, in addition to a lack of equipment, teach-
ers struggle with students who resist participating in any
activity other than basketball during physical education.
At the same time, teachers recognize that their students
love basketball. Teachers often fear for their own and their
students’ safety, because of the high level of community
violence (McCaughtry, Barnard, et al., 2006). Physical
education teachers of urban youth are also particularly
concerned about helping them become healthy and com-
bat rising levels of obesity (McCaughtry, Martin, Kulinna
& Cothran, 2006b).
As well as predicting PA, another purpose of our
study was to predict fitness. In addition to the scarcity of
PA research on the school environment, few research-
ers have objectively assessed fitness with underserved
children. Hence, our ability to obtain indices of both
cardiovascular fitness and muscular strength and endur-
ance, while considering the school environment, is an
additional advantage of the current study. Prior research
with inner-city African American middle school children
has supported a link between PA and cardiovascular fitness
(Martin et al., 2005).
We examined the following social cognitive theory
(SCT) variables. We first investigated barrier self-efficacy
and proxy self-efficacy. Barrier self-efficacy reflects a sense
of personal agency, whereas proxy self-efficacy pertains to
one’s confidence to involve others to help them achieve
their goals (Bandura, 1997). Dzewaltowski et al. (2007)
recommended that PA researchers strive to assess multidi-
mensional self-efficacy to determine which type of self-ef-
ficacy is most strongly linked to PA. They also argued that
proxy efficacy is particularly important to assess in middle
school children because they lack control over school PA
practices. Furthermore, given that the primary function
of the teacher-student relationship is educational, it seems
especially prudent to determine whether students have
confidence in their teacher’s ability to teach PA.
Many researchers have found that barrier self-efficacy
is related to PA in minority children (e.g., Martin & Mc-
Caughtry, 2008a). For instance, Beets, Piteti [AQ: “Pitetti”
in refs], and Forlaw (2007) found strong support for the
relationship between barrier self-efficacy and PA with
adolescent girls. Furthermore, Martin et al. (2008) found
that barrier self-efficacy predicted PA in Arab American
middle school children.
Work by Dzewaltowski et al. (2007) has substantiated
that proxy efficacy is an important form of self-efficacy for
PA promotion. In a study of predominately African Ameri-
can fifth-grade students, Saunders et al. (1997) found that
children reporting strong self-efficacy for seeking support
for their PA involvement were likely to be vigorously physi-
cally active. Although their measure of support-seeking
self-efficacy was conceptually similar to proxy self-efficacy,
it also included items reflective of personal agency efficacy
(Dzewaltowski et al., 2007). Thus, there is clearly a need
for more research examining both forms of self-efficacy.
We also measured social support. Children in the cur-
rent study are at an age where parental support is diminish-
ing as peer support is increasing (Furman & Buhrmester,
1992). Additionally, children from low-income families
perceive less sibling social support for PA compared to
children from higher income families (Duncan, Duncan,
& Strycker, 2005). Increased self-reflection and a desire
for independence, the onset of puberty, and burgeoning
nonfamily-related interests are all thought to contribute
to this developmental shift (Furman & Buhrmester, 1992).
Other researchers have also suggested that there is value
in examining social support in children of this age. For
example, Beets et al. (2007) found peer social support was
a direct predictor of PA, and they have maintained that
social support is multidimensional in that it is offered by
distinct groups (e.g., parents). However, we could find no
research aimed at determining whether social support
derived specifically from school classmates is important
for PA involvement or fitness. Therefore, to address this
shortcoming we measured classmate social support.
We examined both the physical and social school
PA environment. The physical environment refers to
the physical and institutional features of the school. For
instance, whether the school has a gym or outdoor areas
conducive to physical activity. In contrast, the social en-
vironment targets the degree to which school personnel
(e.g., teachers) are perceived to support PA.
Although the neighborhood built-environment
has been linked to PA (e.g., Evenson, Scott, Cohen, &
Voorhees, 2007), we are aware of only one PA research
study addressing the role of the school environment
(Robertson-Wilson et al., 2007). Robertson-Wilson et al.
(2007) found that students who considered their school
environment to be PA friendly also reported using more
RQES: June 2011 3
Martin, McCaughtry, Flory, Murphy, and Wisdom
school PA equipment and belonging to school sports
teams. However, no research linking the school environ-
ment to PA and fitness could be found.
In brief, our major purpose was to examine important
social, cognitive, and school environmental constructs
to determine whether they predicted PA and fitness. We
hypothesized that children who possessed strong barrier
and proxy self-efficacy, who had perceptions of positive
PA social support from their classmates, and who viewed
the school environment as conducive to PA would report
more PA, and exhibit greater fitness, compared to chil-
dren scoring less favorably on all constructs. A secondary
goal was to examine our data for gender differences. Re-
searchers examining PA and related psychosocial variables
have found a consistent pattern of gender differences
favoring boys, but have not examined perceptions of the
school environment.
Method
Participants and Setting
A sample of 506 middle school children from five
schools in a midwestern state participated. Children were
in grades 6 or 7 and ranged in ages from 10 to 14 years (M
= 12.0, SD = .89). Breakdown by gender was 50.6% girls (n
= 256) and 49.4% boys (n = 250). The racial-ethnic distri-
bution was mostly minority as follows: African American
(60%), Caucasian (12%), Asian American (8%), Arab
American (6.5%), Hispanic American (5.5%), Multiple
Race (5%), Bengali (2%), and other (1%). Schools were
located in the most economically depressed cities in the
state. For instance, 19–53% of the families with children
(ages 5–17 years) living in school districts in which we
collected data lived in poverty as determined by the U.S.
Census Bureau (2008), which calculates poverty as a ratio
of income to need. In turn, need is determined by age
and number of family members. Schools were located in
cities with populations that ranged in size from 16,746 to
159,589 (U.S. Census Bureau).
Instruments
Students provided demographic information and
answered questionnaires assessing all predictor variables
and PA. All questions have been used with children of
similar age (e.g., Martin et al., 2005, 2007, 2008). Student-
provided demographic information included their school
name, grade level, age, gender, and race.
Social Cognitive Theory Measures
Barrier Self-Efficacy. Children responded to four items
on a 7-point Likert-type scale. Items were taken from valid
and reliable youth PA self-efficacy scales used previously
(Barnett, O’Loughlin, & Paradis, 2002; Saunders et al.,
1997). A sample item was “How confident are you of
participating in physical activities that make you breathe
hard or feel tired when you have a lot of homework to
do.” Anchors were 1 = not at all confident and 7 = very
confident. All items were summed and divided by four to
obtain an overall barrier self-efficacy score ranging from
1 to 7. Adequate internal consistency and convergent
validity have been established in research with minority
children of similar age from inner- city schools (Martin &
McCaughtry, 2008a, 2008b; Martin et al., 2008).
Proxy Self-Efficacy. Children responded to three items
on a 6-point scale. We used three items from the six-item
Proxy Efficacy for Physical Activity (PEPA) scale, devel-
oped by Dzewaltowski et al. (2007) for use with middle
school children. We did not use three items that pertained
to after-school programs, because participants in our study
did not attend after-school programs. A sample item was
“How sure are you that you can get the school staff or
your teachers to plan physical activities for you and your
classmates.” Anchors were 0 = not at all sure and 5 = com-
pletely sure. All items were summed and divided by three
to obtain an overall proxy self-efficacy score ranging from
0 to 5. Dzewaltowski et al. provided extensive evidence
(e.g., confirmatory factor analysis) for the reliability and
validity of the PEPA scale.
Classmate Social Support. Children were asked four
questions on a 5-point scale from the Friends subscale
developed by Duncan et al. (2005). Duncan et al. ob-
tained items from valid and reliable social support scales
used previously in research with children (Sallis, Taylor,
Dowda, Freedson, & Pate, 2002). Additionally, they estab-
lished validity and reliability for the current scale using
confirmatory factor analyses (Duncan et al.). We made
two minor changes. First, we changed “friends” to “class-
mates,” because we were interested only in participants’
perceptions of their classmates’ support of PA. Second,
we eliminated one question addressing transportation,
because the children were too young to drive. A sample
question was “How much do your classmates talk with
you about your physical activity.” Anchors were 1 = never
and 5 = very often. All items were summed and divided by
four to obtain an overall score for classmate social support
ranging from 1 to 5.
School Physical Activity Environment. Children re-
sponded to 20 questions constituting the Questionnaire
Assessing School Physical Activity Environment (Q-Space),
developed by Robertson-Wilson et al. (2007) to assess
middle school students’ perceptions of the school physical
activity environment. The Q-Space has two subscales. The
12-item physical school PA environment subscale deter-
mines students’ perceptions of how physically “friendly”
the school is. Items reflect equipment and facility qual-
ity and programming (e.g., physical education classes).
4 RQES: June 2011
Martin, McCaughtry, Flory, Murphy, and Wisdom
An example item is “The indoor areas (e.g., gym) at
my school are in good condition.” The eight-item social
school PA environment subscale reflects students’ views
of the social PA environment. For instance, questions ask
whether teachers believe PA is important. An example
item is “Teachers supervise students being physically ac-
tive at recess or lunch breaks at my school.” Anchors were
1 = strongly agree and 5 = strongly disagree. Items were
summed and divided by 12 or 8 for average physical and
social subscale scores, respectively. Lower scores reflect
a more favorable environment. Robertson-Wilson et al.
established adequate internal consistency (α = .81–.86),
test-retest reliability, and construct validity. Additionally,
convergent and predictive validity was established via
expected correlations between the Q-Space subscales and
PA in the present study.
Physical Activity and Fitness
Physical Activity. We used the Godin Leisure-Time
Exercise Questionnaire (GLTEQ; Godin & Shephard,
1985), which yields reliable and valid scores. Students
read the header, “How many times in an average week
do you do the following kinds of exercise for more than
15 minutes during your free time?” and responded to the
next three statements: Strenuous Exercise (Heart beats
rapidly), Moderate Exercise (Not exhausting) and Mild
Exercise (minimal effort). We used the phrase “breathe
hard or feel tired” to enhance children’s understanding.
In addition, sample activities that are consistent with
each exercise category were provided to further assist
students’ understanding. Students’ answers for strenu-
ous, moderate, and mild exercise were then multiplied
by nine, five, and three Metabolic Equivalents (METS)
units respectively (Godin & Shephard, 1985). The GLTEQ
has been successfully employed (e.g., adequate reliability,
concurrent and convergent validity) with minority chil-
dren of similar age in previous research (Martin et al.,
2005, 2007, 2008), has been validated with children using
objective measures of PA (Jacobs, Ainsworth, Hartman, &
Leon, 1993), and has been used in health-related research
(Kriska & Caspersen, 1997).
Cardiovascular Fitness. This was determined with the
Progressive Aerobic Cardiovascular Endurance Run
(PACER). The Cooper Institute for Aerobics Research
(1987, 1999) [AQ: Not in refs] developed the PACER to
measure children’s cardiovascular fitness (i.e., an estimate
of VO
2
max). The PACER is part of the FITNESSGRAM®
and has produced reliable and valid scores in children
(Morrow, Jackson, Disch, & Mood, 2000) and has been
used with children of similar age (Martin et al., 2005).
The PACER test has shown acceptable concurrent validity
with measured maximal oxygen consumption (VO
2
max).
Criterion referenced validity has also been established
between measured VO
2
max and estimated VO
2
max from
the PACER. Furthermore, equivalent reliability scores
correctly classify students for cardiorespiratory fitness
(Plowman & Yan-Shu, 1999).
Muscular Strength and Endurance Fitness. These were
determined with the 90° push-up (PSU) test. The Cooper
Institute for Aerobics Research (1987, 1999) [AQ: Not in
refs] developed the PSU and testing protocol as part of the
FITNESSGRAM. The PSU has produced reliable and valid
scores in young children (Sherman & Barfield, 2006).
Procedures
We received permission from the University Internal
Review Board, the school districts, school principals, and
the full-time physical education teachers and obtained
parental assent and children’s assent to conduct our study.
A team of five researchers collected data on five different
days at five different middle schools. All data collectors
each had over 5 years of experience in collecting similar
fitness and psychosocial data. A complete day was spent
at each school testing all grade six students who were
present that day and grade seven students if time was
available. The schools selected were part of a larger project
designed to increase opportunities for healthy eating and
PA through changes to policy and support. At the begin-
ning of each school period, classroom teachers brought
their students to the gym. After instruction and modeling
of the PACER and PSU test, students then completed
both tests. Questionnaires were completed last. Typically
data collectors monitored 2–5 children and conversed
with them to make sure they understood all questions.
Students who had difficulty understanding the surveys
were given individualized assistance, such as having the
questions read out loud and receiving examples illustrative
of the item in question. Students averaged about 25 min
to complete the written survey.
Data Analysis
The Statistical Package for the Social Sciences 16.00
was used for all analyses. We first examined internal reli-
ability via alpha coefficients and then conducted descrip-
tive analyses and bivariate correlations. Next, we examined
gender differences using a multivariate analysis of variance
(MANOVA). All variables were analyzed simultaneously.
We then conducted a standard multiple regression (MR)
analysis in which all the independent variables (IVs; i.e.,
proxy and barrier self-efficacy, classmates social support,
social and physical school PA environment) were en-
tered simultaneously to predict PA (Tabachnick & Fidell,
2001). Two additional MR analyses were conducted with
the predictor variables from the first MR, in addition to
PA, used to predict cardiovascular fitness and muscular
strength and endurance fitness. Each IV is evaluated like
it was entered last, and, thus, the value of each predictor
RQES: June 2011 5
Martin, McCaughtry, Flory, Murphy, and Wisdom
variable can be assessed based on beta weights and asso-
ciated significance tests. Both variance inflation factors
(1.05–1.68) and tolerance figures (.60–.95) were adequate
based on the criteria of above 10 and below .10, respec-
tively (Cohen, Cohen, West, & Aiken, 2003) indicating a
lack of multicollinearity. An examination of the histogram
for PA indicated slightly positive kurtosis and skewness
deviations from normal. However, with large samples like
ours, these deviations do not make significant differences
in analyses (Tabachnick & Fidell, 2001, p. 74).
Results
Descriptive Statistics and Correlations
Means, standard deviations, ranges, skewness, kur-
tosis, and internal consistency are presented in Table 1.
Scale internal consistencies were all acceptable (Cron-
bach, 1951). In general, the means fell in the neutral
or mid-point of the scale ranges. Bivariate correlations
are presented in Table 2. Virtually all of the correlations
were significant, but small to moderate in size making
the associated effect sizes (i.e., variance accounted for)
relatively small. The one discernable pattern indicated
stronger associations among the social-psychological and
behavioral self-report scales, relative to correlations with
the fitness variables.
Gender Differences
The MANOVA examining for gender differences was
significant, F(8, 497) = 20.07, p < .001, partial eta squared
(η²) = .24. Analysis of variance follow-up tests revealed the
following six of eight differences. For the two fitness vari-
ables, boys, F(1, 504) = 58.60, p < .001, η² = .10, completed
more PACER circuits (M = 18.78) than girls (M = 13.69)
and more pushups, F(1, 504) = 125.59, p < .001, η² = .20,
(M = 9.34) than girls (M = 3.95). Boys, F(1, 504) = 8.14, p
< .005, η² = .016, also expended more (M = 90.94) total
METS than girls (M = 71.10).
For the social cognitive and environment constructs,
boys, F(1, 504) = 7.83, p < .005, η² = .015, reported more
(M = 2.74) classmate support than girls (M = 2.49). Boys,
Table 1. Measures for all variables
Variable M SD Range Skewness Kurtosis Alpha
BSE 4.16 1.34 1.0–7.0 .12 -.38 .73
PSE 2.60 1.26 0.0–5.0 -.18 -.58 .73
CSS 2.62 1.01 1.0–5.0 .33 -.60 .74
SSPA 2.56 .69 1.0–5.0 .34 .73 .76
PSPA 2.50 .62 1.0–5.0 .45 1.21 .77
PA 80.90 78.76 00.00–708 4.40 25.71 NA
PACER 16.20 7.90 00.00–55 1.54 3.58 NA
PSU 6.61 6.04 00.00–34 1.04 0.85 NA
Note. M = mean; SD = standard deviation; BSE = barrier self-efficacy; PSE = proxy self-efficacy; CSS = classmate social sup-
port; SSPA = social school physical activity environment; PSPA = physical school physical activity environment; PA = physical
activity in metabolic equivalents; PACER = Progressive Aerobic Cardiovascular Endurance Run score; PSU = 90° push-up test.
Table 2. Correlations among all psychological variables
BSE PSE CSS SSPA PSPA PA PACER
PSE .28*
CSS .39* .36*
SSPA -.20* -.26* -.31*
PSPA -.10* -.26* -.18* .59*
PA .26* .19* .25* -.17* -.15*
PACER .15* .05 .13** -.03 .03 .12*
PSU .13* .04 .12* -.08 -.02 .13* .42*
Note. BSE = barrier self-efficacy; PSE = proxy self-efficacy; CSS = classmate social support; SSPA = social school physical ac-
tivity environment; PSPA = physical school physical activity environment; PA = physical activity in metabolic equivalents; PACER
= Progressive Aerobic Cardiovascular Endurance Run score; PSU = 90° push-up test.
*Significant [AQ: At what p value?].
6 RQES: June 2011
Martin, McCaughtry, Flory, Murphy, and Wisdom
F(1, 504) = 6.16, p < .005, η² = .013, also reported greater
barrier self-efficacy (M = 4.30) than girls (M = 4.00). In
contrast, girls, F(1, 504) = 6.41, p < .005, η² = .013, reported
stronger perceptions of the social PA school environment
(M = 2.63) than boys (M = 2.49). There were no gender
differences for physical school PA environment or for
proxy self-efficacy. In general, the six effect sizes (η² =
.012–.20) are small to moderate (Cohen, 1988).
Multiple Regression Results
See Tables 3, 4, and 5 for the multiple regression
results. In our first regression equation predicting PA,
all predictor variables were entered simultaneously and,
because of the gender differences noted earlier, we also
entered gender. We accounted for 12% of the variance
in PA, F(6, 499) = 11.06, p < .001, R = .34, R² = .12. Based
on the standardized beta weights and associated signifi-
cance levels, it is apparent that barrier self-efficacy and
classmates’ social support for PA were the most critical
variables, with gender also contributing.
In the second equation, we predicted PACER scores
using the same predictor variables as in the first equation,
but with the addition of PA. Again, all predictor variables
were entered simultaneously. We accounted for 13% of
the variance in fitness, F(7, 498) = 10.24, p < .001, R =
.36, R² = .13. In the next equation, we predicted pushup
scores and again, all predictor variables were entered
simultaneously. We accounted for 21% of the variance in
fitness, F(7, 498) = 19.03, p < .001, R = .46, R² = .21. Given
the standardized beta weights and associated significance
levels, it is clear that gender made the biggest contribution
in predicting both indexes of fitness.
Discussion
The major purpose of this investigation was to predict
underserved middle school children’s PA and fitness levels
with a specific goal of determining the relative importance
of our various predictors. Consistent with the findings
from prior research (e.g., Morrow et al., 2000), boys
scored higher on the fitness measures than girls. Based
on the FITNESSGRAM’s Healthy Fitness Zone® norms,
both boys and girls mean scores for the PACER and PSU
tests, for their age group, were below the lowest range of
the zones. For instance, girls’ mean pushup scores were
4, whereas the healthy fitness zone ranges from 7 to 15.
Participants’ self-report of PA ranged from 4.4 to 4.9 for
at least 15 min of mild, moderate, and strenuous PA in an
average week. These results are comparable to previous
research with underserved minority children (Martin et
al., 2005, 2007, 2008). Extrapolating the PA findings to
an average week, suggests that children participated in a
minimum of 3–4 hr of PA per week, which is below the
Table 3. Standard multiple regression results predicting
physical activity
Variable [Missing symbol] t Sig.
BSE .167 3.58 .001*
PSE .068 1.45 .147
CSS .134 2.75 .006*
SSPA -.011 -0.20 .840
PSPA -.091 -1.76 .087
GEN -.930 -2.16 .031*
Note. [AQ: What is Sig.?] BSE = barrier self-efficacy; PSE =
proxy self-efficacy; CSS = classmate social support; SSPA =
social school physical activity environment; PSPA = physical
school physical activity environment; GEN = gender.
*Significant [AQ: At what p value?].
Table 4. Standard multiple regression results predicting
Progressive Aerobic Cardiovascular Endurance Run scores
Variable [Missing symbol] t Sig.
PA .053 1.20 .232
BSE .088 1.97 .062
PSE .025 .54 .592
CSS .050 1.01 .311
SSPA .030 .56 .578
PSPA .043 .81 .417
GEN -.304 -7.06 .001*
Note. [AQ: What is Sig.?] PA = physical activity; BSE = bar-
rier self-efficacy; PSE = proxy self-efficacy; CSS = classmate
social support; SSPA = social school physical activity environ-
ment; PSPA = physical school physical activity environment;
GEN = gender.
*Significant [AQ: At what p value?].
Table 5. Standard multiple regression results predicting push-
up scores
Variable [Missing symbol] t Sig.
PA .052 1.24 .217
BSE .058 1.29 .197
PSE .012 .27 .784
CSS .032 .68 .496
SSPA .016 .30 .761
PSPA -.016 -.31 .755
GEN -.432 -10.58 .001*
Note. [AQ: What is Sig.?] PA = physical activity; BSE = bar-
rier self-efficacy; PSE = proxy self-efficacy; CSS = classmate
social support; SSPA = social school physical activity environ-
ment; PSPA = physical school physical activity environment;
GEN = gender.
*Significant [AQ: At what p value?].
RQES: June 2011 7
Martin, McCaughtry, Flory, Murphy, and Wisdom
recommendation of 1 hr a day (Strong et al., 2005 [AQ:
Not in refs]; USDHHS, 2000).
There was a consistent theme to the children’s per-
spectives, as the mean scores for the nonfitness variables
were approximately neutral. All four means on the 5–6
point scales were 2.5 or 2.6. Barrier self-efficacy was also
in the middle (M = 4.2) of the 7-point scale. Children
did not perceive that they received a lot of support from
their classmates for PA, and they did not view the school
environment as particularly activity friendly. Conversely,
they were not overly critical of the school PA environment.
Similarly, they expressed only moderate amounts of self-
efficacy in their ability to overcome common barriers to
PA or to enlist significant others (i.e., proxy self-efficacy) in
the school to help them be active. Mean proxy self-efficacy
levels were comparable to those expressed by urban, rural,
and suburban sixth-grade students from Kansas (Dze-
waltowski et al., 2007). As a group, these children lacked
fitness, were not particularly active, and were neither
overwhelming positive nor negative in their perceptions of
the school PA environment and of their classmates’ social
support for PA. Additionally, they did not have particularly
strong barrier self-efficacy or proxy self-efficacy. In sum-
mary, children in the current study failed to express strong
thoughts or feelings in any of the psychosocial constructs
believed to be instrumental in facilitating PA. Given the
importance of peer (i.e., classmate) social support, adult
support (i.e., proxy efficacy), personal agency (i.e., bar-
rier efficacy) and a supportive environment for PA, it is
certainly plausible that underserved children’s lack of
strong beliefs in these areas contributes to their limited
PA. In particular, as we discuss in the next section, barrier
self-efficacy and classmate social support seem to be the
most important variables.
With respect to our major research question, we were
able to account for 12% of the variance in PA. This figure
is somewhat similar to the amount of variance accounted
for in previous studies of minority children (e.g., Martin et
al., 2005, 2007, 2008) although only 88% of the children
in the current study were minorities. It is also comparable
to the amount of variance that Zakarian and colleagues
accounted for (using 28 predictors) in predicting vigorous
PA in a similarly low SES minority population (Zakarian,
Hovell, Hofstetter, Sallis, & Keating, 1994).
The strongest standardized beta weights were as-
sociated with barrier self-efficacy and classmate social
support. The finding that classmates’ social support is
important is, to our knowledge, one of the first research
efforts that has focused specifically on school peers [AQ:
This confuses the finding and the effort—the finding is
not the effort and it does not “focus.” Decide which you
want to talk about]. This finding adds to a growing body
of knowledge about social support and friendship and
their relationships to PA in adolescent children (e.g.,
10–14 years old). For example, Smith (1999) found that
both close friendship and peer acceptance were positively
related to PA. Other researchers have also found that peer
support was positively related to PA (e.g., Martin & Mc-
Caughtry, 2008b). The finding that barrier self-efficacy was
an important predictor of PA is consistent with its central
position in SCT. For instance, out of six social cognitive
variables, barrier self-efficacy was the strongest predictor
of PA in Arab American middle school children (Martin
et al., 2008).
Although perceptions of the school PA environment
were not significant variables in the regression equations,
they were significantly related to PA and fitness in the
simple correlations. For instance, children who viewed the
social and physical school environment as more conducive
to PA expended more METS and demonstrated greater
fitness compared to children who viewed the school en-
vironment as less facilitative of PA. Similarly, proxy school
self-efficacy was significantly correlated with PA. This find-
ing contrasts with Dzewaltowski et al. (2007), who found
no relationship between proxy school self-efficacy and
PA. It may be that underserved children’s efficacy in their
school teachers [AQ: “efficacy in their school teachers”?]
is more critical to their PA compared to non-underserved
children. Fifty-seven percent of the underserved children
in the state where our study was conducted live with one
parent (National Center for Children in Poverty, 1996),
making it plausible that the influence that teachers of un-
derserved children have is more important relative to the
influence they might have on children from two-parent
homes. Our measure of PA reflects free-time PA, whereas
the setting for the physical and social school PA environ-
ment scales is the school. Thus, it is plausible that the lack
of complete congruence between these two measures
contributed to the inability of the school environment to
predict PA and to the small correlations among the school
environment and PA.
A secondary purpose of the current study was to
determine whether gender differences existed. Boys ran
longer during the PACER test, completed more push-ups,
and reported engaging in more PA than girls. Boys also re-
ported more classmate social support and greater barrier
self-efficacy. In contrast, girls viewed the social school PA
environment as more supportive of PA. With the excep-
tion of the social school PA environment, these findings
are quite consistent with a large body of research, and
they demonstrate that gender inequities in PA socializa-
tion likely exist (Greendorfer, 1993), although the effect
sizes were small for the psychosocial differences. Girls’
viewed the school social environment for PA as slightly
more favorable than the boys. Viewing the school social
environment for PA as form of PA social support makes
the gender difference finding consistent with the findings
of researchers who have reported that sometimes girls
perceive more support than boys in PA settings (Duncan
et al., 2005; Martin & Smith, 2002). These findings suggest
8 RQES: June 2011
Martin, McCaughtry, Flory, Murphy, and Wisdom
that it is important to be cognizant of gender differences
in PA research. The ability of gender to predict fitness
likely reflects the combined influence of biological and
social factors favoring boys, although puberty-related
changes have not yet been fully manifested in this age
group. The impact of genetics on fitness, relative to PA
behavior, also likely contributes to the stronger gender
relationship with fitness compared to PA, where social-
cognitive factors (i.e., efficacy and social support) were
important predictors of PA.
Some limitations of our research should be recog-
nized. Given the correlational design of the study, causal-
ity cannot be argued. Self-report research with young
children introduces the possibility of measurement error.
Also, we failed to predict approximately 80–90% of the
variance PA and fitness, suggesting that other potential
predictors of PA should be considered in future research.
Conclusions
We were able to account for 12% and 13–21% of
the variation in PA and fitness, respectively, with barrier
self-efficacy playing the most prominent role among the
various psychosocial and environment constructs. Mean
values indicated the children did not think the school en-
vironment was particularly conducive to PA. Similarly, they
were not very efficacious in their ability to seek support for
PA or to overcome barriers to PA. Future researchers con-
ducting interventions with underserved minorities might
consider changes in children’s perceptions of the school
environment as well as social cognitive constructs associ-
ated with increased PA and fitness. Bronfenbrenner’s
(1989) ecological systems theory is an excellent framework
for researchers who want to consider the influence of the
multiple distal and proximal social and physical environ-
ments on PA behaviors.
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Authors’ Notes
The current study was part of a larger project funded by
the Kellogg’s Foundation to [AQ: “through”?] the state
Surgeon General [AQ: This sentence is unclear]. The pur-
pose of the project was to increase healthy eating, physi-
cal activity, and tobacco avoidance in 16 middle schools
located in cities with high rates of poverty. The authors
thank the research staff in the Department of Biostatistics
and Research Epidemiology at Henry Ford Hospital for
data entry. Please address correspondence concerning this
article to Jeffrey Martin, Division of Kinesiology, Health,
and Sport Studies, 265 Matthaei Building, Wayne State
University, Detroit, MI 48202.
E-mail: aa3975@wayne.edu
