EXERCISE AND QUALITY OF LIFE
Research article
Volume 2, No. 1, 2010, 1-14
UDC
316.61:796.035-057.875(73)(=134.2)
SOCIAL COGNITIVE DETERMINANTS OF PHYSICAL
ACTIVITY IN A PREDOMINANTLY HISPANIC
COLLEGE POPULATION
Dejan Magoc*
Department of Health Studies
Eastern Illinois University
Joe Tomaka
Department of Public Health
University of Texas at El Paso
Abstract
The purpose of this study was to assess the general level of physical activity (PA) among
predominantly Hispanic college population. In addition, the study examined the relationships
between the Social Cognitive Theory (SCT) constructs and PA. One hundred participants
completed the questionnaire in regard to PA and SCT. The results of this study showed that 59%
of the sample met recommendations for PA. Furthermore, self-efficacy was the only significant
predictor of PA METS, β = .35, p < .01. This study helps understand the relationship between the
SCT constructs and PA, suggesting that maintaining the SCT processes will lead to regular PA.
Thus, encouraging and targeting PA together with cognitive changes might be of great interest
for future research.
Key words: physical activity, SCT, college students, Hispanics
Introduction
The American Heart Association (AHA) and the American College of Sports Medicine
(ACSM) suggest at least 30 min of moderate physical activity (PA) at least 5 days a week or 20
min of vigorous PA at least 3 days a week (Haskell et al., 2007). Moderate PA is defined as any
activity that takes moderate physical effort and makes a person breathe somewhat harder than
normal (e.g. walking, cleaning), whereas vigorous PA is defined as any activity that takes hard
physical effort and makes a person breathe much harder than normal (e.g. jogging, skiing)
(Booth, 2000). Combinations of moderate and vigorous PA are also appropriate. For instance, a
person may be moderately physically active on 2 days a week for at least 30 min per day in
addition to 2 days of vigorous PA for at least 20 min per day (Booth, 2000).
* Corresponding author. Department of Health Studies, Eastern Illinois University, Lantz Charleston, IL 61920,
e-mail: dejanmagoc@yahoo.com
© 2010 Faculty of Sport and Physical Education, University of Novi Sad, Serbia
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D. Magoc and J. Tomaka
The relationship between PA and disease is unambiguous and lack of PA in the general
population has become a major public health concern (Petosa, Suminski, & Hortz, 2003).
Physical activity helps metabolism and immune function, minimizes risk factors for many heart
diseases, including diabetes and high blood pressure, and is also associated with decreased risk
of morbidity and mortality rates from cardiovascular disease
(Kujala, Kaprio, Sarna, &
Koskenvuo, 1998). Even though the health benefits of PA are numerous, most adults are not
sufficiently physically active (Insel & Roth, 2002; Pratt, Macera, & Blanton, 1999). In fact,
many Americans live sedentary lifestyles with approximately one-quarter reporting they engage
in no PA at all and about 25% meeting the recommended levels of PA (Centers for Disease
Control and Prevention [CDC], 2001).
Studies show that levels of PA drop abruptly from high school to college years and
beyond. For example, approximately 65% of high school students engage in vigorous PA,
compared to 32% of 18-24 year-olds and 23% of adults. A similar trend has been reported for
moderate PA showing that approximately 27% of high school students engage in moderate PA,
compared to 17% of 18-24 year-olds and 15% of adults (Rovniak, Eileen & Winett, 2002). This
is also true for college students where studies show surprisingly low participation in
recommended PA, ranging from 40-55% (Petosa et al., 2003; Suminski, Petosa, Utter, & Zhang,
2002). This means that only half of college students are sufficiently physically active and the
other half are not getting enough PA. This result is troubling because studies have shown that PA
decreases over the lifespan (Bradley, McMurray, Harrell & Deng, 2000; Caspersen, Pereira &
Curran, 2000; McMurray et al., 2000). Therefore, although increased PA would benefit all age
groups, it is especially important in young adults because studies show that they become less
active as they get older, and because habits learned early in life tend to persist into adulthood
(Department of Health and Human Services [DHHS], 1996).
Participation in PA among Hispanics
Rates of participation in PA are higher in white adolescents compared to Black and
Hispanics (Pratt et al., 1999). In addition, more white adults meet current recommendations for
PA than do Black and Hispanics (Pratt et al., 1999). In a study among a predominantly Hispanic
college population, Magoc and Tomaka (2006) reported that even though participation in some
level of PA among college students (the majority Hispanic) was high (61%), the majority of
students who reported some level of PA (69%) did not meet the recommendations for PA.
Although studies are few, researchers have identified differences between Hispanic and
Anglo populations across a number of dimensions relating to physical activity. Overall, these
studies have suggested that although they have favorable attitudes toward PA, Hispanic
populations tend to participate in leisure time PA less often and less frequently than do their
Anglo counterparts. For example, Hovell et al. (1991) reported that, on average, Hispanic adults
walk for only 48 minutes per week and engage in vigorous PA less than 2 times a week.
Similarly, Crespo, Keteyian, Heath, & Sempos (1996) reported that Hispanics were among the
most inactive people in the nation with 33% of Mexican American men and 46% of Mexican
American women not participating in any significant leisure time PA. The percentages for
women are particularly striking since women and Mexican-Americans are at increased risk of
diabetes. Mouton, Calmbach, Dhanda, Espino, & Hazuda (2000) have also shown that Mexican
Americans are less active and have lower levels of PA than European Americans. Dunn and
Wang (2003) also reported that Hispanic and African-American college students were less likely
to engage in PA than were White students.
The college setting represents an appropriate time for developing and promoting physical
activity, particularly since this time represents the transition to adulthood and independence, and
it is a time when parents and schools usually have little or no control over PA behaviors (Hoerr,
Bokram, Lugo, Bivins, & Keast, 2002). Habits developed during college will likely persist into
later adulthood. Moreover, as this generation moves into the workforce, many will enter
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Social Cognitive Determinants of Physical Activity
occupations requiring little physical exertion. Accordingly, the Hispanic college-age population
is an appropriate group for the development of effective ways to help this population engage in
PA on regular basis and learn skills that will keep them active throughout the lifespan.
Social Cognitive Theory
In order to develop more effective physical activity interventions, it is crucial to
incorporate theoretical approaches into interventions that adequately explain and predict PA
(Baranowski, Anderson, & Carmack 1998; Rovniak et al., 2002). Social Cognitive Theory (SCT)
has been one of the most widely used Behavioral Change Theories, and its constructs provide a
useful framework in the prediction of PA behavior and the design of behavioral interventions.
Glanz, Lewis, and Rimer (2002) explain why SCT is relevant to health education and
health behavior programs. First, SCT is based on a dynamic relationship between environment,
personal factors, and behavior (Allison, Dwyer, & Makin 1999; Glanz et al., 2002). According to
SCT, an individual’s behavior is determined by each of these three factors. And second, the
constructs from SCT suggest many possibilities for behavioral research and practice in health
education. The key SCT determinants of PA include: self-efficacy, self-regulation, social
support, outcome expectations and expectancies, environmental factors, and behavioral
capability (Bandura, 1997; Rovniak et al., 2002).
Self-efficacy is described as one’s confidence in performing a particular behavior (Glanz
et al., 2002). It represents a central component of SCT and an important personal determinant of
human behavior. It has also been defined as somebody’s beliefs about their ability to engage in a
certain behavior that will lead to expected outcomes (Ryan & Dzewaltowski, 2002). Depending
on self-efficacy beliefs, a decision will be made whether a behavior will be adopted and
maintained.
Self-regulation refers to motivational and self-regulatory skills (Bandura, 1997). Self-
regulation allows a person to set goals, track his or her progress, and evaluate his or her
capabilities to perform behaviors in given situations. According to Bandura (1997), people
cannot influence their motivation and actions without an adequate attention to their performance.
Thus, being able to set goals as well as monitor their progress can help people increase their
motivation toward certain behaviors.
Social Support represents a form of verbal or behavioral actions in support of a given
behavior
(Bandura,
1997). There are usually four types of social support: instrumental,
informational, emotional, and appraisal. All types of social support aid in behavioral processes
by physical actions
(instrumental), helpful information
(informational), affective support
(emotional), or reinforcement (appraisal).
People tend to adopt actions that will most likely produce positive outcomes and usually
tend to avoid actions that will bring unrewarding outcomes (Bandura, 2004). This has been
explained through outcome expectations. In addition to what people expect their action to
produce, people also place values on particular outcomes (Baranowski, Perry, & Parcel 2004).
This is further defined by outcome expectancies. Thus, people are more likely to change their
behavior if they believed the outcome would match their expectations and if they valued a
specific outcome.
Glanz et al. (2002) defined the environmental factors in SCT as factors physically
external to the person, but which can affect a person’s behavior and “situation” as a person’s
perception of the environment. One of the most important environmental determinants of PA is
physical safety. Ryan and Dzewaltowski
(2002) suggest that selecting and creating the
environment that supports desired behavior is an important strategy. An unsafe environment can
decrease an individual’s motivation to be physically active.
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D. Magoc and J. Tomaka
Behavioral Capability relates to knowledge and skills of a certain behavior. It has been
explained that if a person needs to perform a certain behavior, he or she must know what the
behavior is (knowledge) and how to do it (skill) (Glanz et al., 2002).
Overall, studies have found positive relations between SCT variables and PA (Rovniak et
al.,
2002; Petosa et al, 2003; Wallace, Buckworth, Kirby, & Sherman, 2000; Leslie, Owen,
Salmon, Bauman, Sallis, & Kai Lo, 1999), also suggesting that some constructs such as self-
efficacy, self-regulation, and social support show a stronger relationship with PA than some
others, such as outcome expectations. Even though theory-based programs and interventions
contribute to a variety of positive outcomes and can be effective for increasing people’s level of
PA, knowledge about PA, attitudes, and fitness level, more research is needed, so that definite
conclusion and decisions can be made regarding correlates and predictors of PA, especially
among diverse population.
Therefore, the overall aim of this study was to assess the general level of physical activity
in Hispanic college population. In addition, this study examined the relationships between PA
and SCT constructs, derived from Bandura’s SCT, using measures from previous research. We
expected SCT constructs to positively correlate with PA. It was also hypothesized that the
intercorrelations among the SCT constructs would be positive
Method
Participants and Setting.
The participants in this study were 100 part- or full-time currently enrolled male and
female students from a large southwestern university in the US with a large Hispanic enrollment.
All participants were recruited through classroom settings and completed the cross-sectional
survey.
Measures
Demographic variables. Demographic variables included self-reported gender, ethnicity,
class, height, and weight.
International Physical Activity Questionnaire. The short version of the International
Physical Activity Questionnaire (IPAQ) is structured to provide separate scores on three specific
types of physical activities (walking, moderate-intensity, and vigorous-intensity) within four
domains, including leisure time PA, domestic and gardening activities, work-related PA, and
transport-related PA (Booth, 2000). This study used only measures of moderate and vigorous
leisure time PA.
Self-Regulation Scales. The Exercise Goal-Setting Scale
(EGS) and The Exercise
Planning and Scheduling Scale
(EPS) measured students’ self-regulation in regard to PA
(Rovniak et al., 2002). Rovniak et al. (2002) showed good reliabilities for these scales in a
predominantly white student population (.89 and .87, respectively). In the present sample, we
also found good reliabilities for these scales (.92 and .76, respectively).
Social Support Scales. The Family and Friend Support for Exercise Habits Scales
assessed social support during the past three months that students have received from friends and
family members (Sallis, Grossman, Pinski, Patterson, & Nader, 1987). Petosa et al. (2003)
showed good reliabilities for these scales in a predominantly white college population (.61 and
.91, respectively). In the present sample, we also found good reliabilities for these scales (.89
and .90, respectively).
4
Social Cognitive Determinants of Physical Activity
Self-Efficacy Scale. The Self-Efficacy for Exercise Behavior Scale assessed students’
self-efficacy in regard to PA (Sallis, Pinski, Grossman, Patterson, & Nader, 1988). Petosa et al.
(2003) showed good reliability for this scale in a predominantly white college population (.97).
In the present sample, we also found good reliability for this scale (.91).
Outcome Expectations and Expectancies Scale. The self-report questionnaire assessed
students’ outcome expectations and expectancies in regard to PA (Steinhardt & Dishman, 1989).
Petosa et al. (2003) showed good reliability for this scale in a predominantly white college
population (.74). In the present sample, we also found good reliability for this scale (.76). We
further factor analyzed this scale to examine different sources of expectancies. Specifically,
principal axis factoring with oblimin rotation to simple solution revealed three expectancy
factors:
Psychological Effects, Image, and Competition. Eight items loaded on the
psychological effects factor and all reflected the expectancy that PA would reduce stress,
increase energy, or improve mood. Five items loaded on the image factor and all reflected the
expectancy that PA would enhance attractiveness or improve body image. Finally, six items
loaded on the competition factor and all reflected the expectancy that PA would enhance
competitive performance.
Procedures
Participants for this study were largely recruited through regular classroom meetings and
activities, with most receiving extra course credit for participation. All participants completed
informed consent forms prior to completing the questionnaires. In total, the survey took
approximately 20 minutes to complete.
Results
Descriptive Analysis
Demographics and Descriptive Statistics. Demographic data for the sample (n = 100) is
presented in Table 1. The sample primarily consisted of junior and senior level students of
predominantly Hispanic origin (82%). A slightly higher percentage of women participated in the
study (59%) than men. The sample had an average BMI of 26.5 (kg/m2). Men and women
significantly differed on two variables: Height and weight (both F(1,99) > 18.71, p < .001). Men
were significantly taller than women (Ms 70.32 and 63.98, respectively) and heavier (Ms 186.15
and 153.91, respectively). Majority of students self-rated their physical health as being “good” to
“fair”. About 54% of students self-rated their psychological health as being “good”, while about
47% of students self-rated their diet as being “fair”.
5
D. Magoc and J. Tomaka
Table 1
Descriptive Statistics for Study Variables
Men
Women
Mean (SD)/%
Mean (SD)/%
Mean (SD)/%
F
Hispanic
82.0%
41.0%
59.0%
.726
Class
3.28
(.75)
3.22
(.76)
3.32
(.75)
.446
Height (in)
66.63
(4.20)
70.32
(2.99)
63.98
(2.66)
122.18**
Weight (lbs)
167.07
(39.43)
186.15
(31.63)
153.91
(39.11)
18.71**
BMI
26.50
(5.43)
26.47
(3.81)
26.52
(6.36)
.00
Self-Rated Physical Health
2.34
(.81)
2.24
(.73)
2.41
(.85)
.99
(1-excellent; 5-very poor)
Self-Rated Psychological Health
2.04
(.76)
2.07
(.75)
2.02
(.78)
.13
(1-excellent; 5-very poor)
Diet
2.77
(.85)
2.90
(.83)
2.68
(.86)
1.69
(1-excellent; 5-very poor)
Note: * p < .05
** p < .001
Table 2 shows means and standard deviations for main outcome (PA and SCT) variables,
as well as reliability coefficients for the latter. As shown, all SCT scales showed good levels of
reliability with the exception of expectancies and self-regulation for plans which were somewhat
lower, but still acceptable. On average, students reported exercising about 3 times per week at
vigorous intensity and about the same number of times per week at moderate intensity. They also
reported achieving over 6000 total PA METS per week. Men and women differed on the
measures of vigorous PA F(1,99) = 5.44, p < .05, PA METS F(1,99) = 6.19, p < .05, Self-
Efficacy F(1,99) = 6.07, p < .05, Expectancies, F(1,99) = 11.14, p < .01, and Goals F(1,99) =
10.79, p < .01.
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Social Cognitive Determinants of Physical Activity
Table 2
Descriptive Statistics for Main Study Outcome Variables
Men
Women
Variables
Mean (SD)
Means (SD)
Means (SD)
F
Physical Activity
Vigorous Days
2.81
(1.67)
3.27
(1.34)
2.49
(1.81)
5.44*
Moderate Days
3.21
(1.99)
3.34
(1.96)
3.12
(2.03)
.30
PA METS
6454.79 (4980)
7903.79 (4956)
5447.85 (4784)
6.19*
SCT Constructs
Self Efficacy (α = .91)
44.32
(9.58)
47.07
(8.43)
42.41
(9.93)
6.07*
Social Support (α = .89)
52.25
(15.42)
51.05
(14.65)
53.08
(16.01)
.42
Expectancies (α = .74)
165.97
(51.71)
185.61
(44.26)
152.09
(52.42)
11.14**
Goals (α = .92)
31.66
(9.34)
35.17
(7.42)
29.22
(9.80)
10.79**
Plans (α = .76)
28.81
(7.29)
29.73
(6.67)
28.17
(7.67)
1.11
Note: * p < .05
** p < .01
The study also examined participation in the recommended levels of PA using definitions
given by the AHA and the ACSM suggesting at least 30 min of moderate PA at least 5 days a
week or 20 min of vigorous PA at least 3 days a week (Haskell et al., 2007). As shown in Table
3, 59% of the sample met recommendations for PA. However, 41% of the sample failed to meet
definition for recommended level of PA.
Table 3
PA of College Students Based on Recommended Levels
Levels of PA
Male
Female
Total
Insufficiently Active
11%
30%
41%
Sufficiently Active
30%
29%
59%
In addition, the study examined the number of persons who were overweight or obese,
using BMI guidelines established by the American College of Sports Medicine (ACSM, 2000).
Participants with BMI of 25 (kg/m2) or greater were classified overweight, those with BMI of 30
(kg/m2) or greater were classified obese, and participants with BMI between 18 (kg/m2) and 25
(kg/m2) were classified normal. Figure 1 shows the breakdown of participants into the various
categories. As shown, 56% of the sample was overweight, including 26% of those being
classified as obese. The rest of the sample (44%) was classified as normal weight.
7
D. Magoc and J. Tomaka
Figure 1. Percentage of Students in Indentified Weight Categories
Primary Analysis: Prediction of Physical Activity
The primary analysis for this study examined demographic and SCT variables in relation
to PA. Table 4 shows the Pearson correlations between the demographic and SCT variables and
total week PA METS. The correlations between demographic and SCT variables and PA ranged
from negative moderate (r = -0.22) to positive moderate (r = 0.46) and all were statistically
significant. The results showed that gender related negatively to most PA and SCT variables
indicating that women participated less in PA, had less self-efficacy, lower self-regulation, lower
outcome expectancies, and received less social support. As expected, the intercorrelations among
the SCT variables were moderate and all were positive. Also, the SCT variables correlated with
PA in expected ways.
Hierarchical multiple regression analysis examined the multivariate relationships among
PA METS and SCT variables. For this analysis, gender and BMI were entered into the regression
equation predicting PA METS on the first step and SCT variables having a significant univariate
association were entered on the second step. The results of this analysis were significant,
adjusted R2 = .21, F(7,89) = 4.58, p < .001. Results also indicated that the addition of the SCT
variables added significantly to the prediction of PA METS, ∆R2 = .16, F(5,89) = 3.81, p < 01.
Examination of the standardized beta coefficients reveled that self-efficacy was the only
significant predictor of PA METS, β = .35, p < .01. It was interesting to note that the coefficients
for Gender and BMI were no longer significant when self-efficacy was entered into the equation.
8
Social Cognitive Determinants of Physical Activity
Table 4
Demographic and SCT Variables in Relation to PA METS
PA
Gender
BMI
SE
SSFP
SRG SRP
OEV
OEP
METS
Gender
-0.24*
BMI
-0.22*
0.00
SE
0.46**
-0.24*
-0.19
SSF
0.22*
-0.21*
-0.17
0.32**
SRG
0.36**
-0.31*
-0.14
0.66**
0.38**
SRP
0.26**
-0.11
-0.08
0.55**
0.39**
0.59**
OEV
0.28**
-0.32**
-0.19
0.48**
0.42**
0.64**
0.59**
OEP
0.31**
-0.21*
-0.21*
0.49**
0.31**
0.60**
0.58**
0.91**
OEBI
0.26**
-0.20*
-0.18
0.47**
0.31**
0.44**
0.46**
0.71**
0.57**
Note: * p < .05
** p < .01
Abbreviations: Total Physical Activity METS (PA METS);Self Efficacy (SE); Social Support
Friend (SSF); Self Regulation Goals (SRG); Self Regulation Plans (SRP); Outcome Expectancy
Value (OEV); Outcome Expectancy Psychological (OEP); Outcome Expectancy Body Image
(OEBI)
Furthermore, we created three PA groups based on students’ PA participation level (low,
moderate, high). Table 5 shows the results of a series of one-way analysis of variance. One-way
ANOVA revealed that there were significant differences in gender, BMI, and SCT variables
among the three PA groups.
9
D. Magoc and J. Tomaka
Table 5
BMI and SCT Variables in Relation to 3 PA Groups
Physical
Activity
Groups
Low
Moderate
High
F
n = 4
n = 39
n = 57
BMI
32.53a (7.25)
27.11ab (6.26)
25.64b (4.35)
3.59*
Self-Efficacy
24.00a (7.26)
41.23b (7.92)
47.86c (8.25)
20.89**
Social Support
20.25ab (12.31)
21.87a (9.75)
27.74b (10.32)
4.34*
From Friends
Self Regulation
17.00a (3.56)
28.92b (7.44)
34.56c (9.31)
11.30**
(goals)
Self Regulation
21.00a (5.35)
25.33a (5.72)
31.74b (6.97)
14.41**
(plans)
Expectations
79.50a (28.35)
154.05b (44.66)
179.98c (49.87)
10.36**
Total
Expectations
27.75a (10.78)
69.21b (24.47)
84.17c (25.23)
12.27**
Psychology
Expectations
28.00a (13.14)
49.63b (14.81)
57.10c (13.71)
9.75**
Body Image
Note: * p < .05
** p < .001
Means not sharing a common subscript differ with p < .05 using the Tukey Procedure
Discussion
The American Heart Association (AHA) and the American College of Sports Medicine
(ACSM) suggest at least 30 min of moderate physical activity (PA) at least 5 days a week or 20
min of vigorous PA at least 3 days a week (Haskell et al., 2007). The purpose of this study was
to assess the general level of PA in Hispanic college population attending a large southwest
university in the US. In addition, this study examined the relationships between PA and SCT
constructs, derived from Bandura’s SCT, using measures from previous research. We expected
SCT constructs to positively correlate with PA. It was also hypothesized that the
intercorrelations among the SCT constructs would be positive.
The results of this study showed rates of PA to be slightly higher than previously
published results on college students ranging from
37-44% of students reporting being
sufficiently active (Petosa et al., 2003; Patrick, Covin, & Fulop, 1997; Douglas, Douglas, &
Collins, 1997; Haberman, & Luffey, 1998). These results might not be surprising knowing that
10
Social Cognitive Determinants of Physical Activity
majority of students in this study were kinesiology major. Thus, a slightly higher reported
participation in PA was expected. Furthermore, the results showed that students reached over
6000 METS of PA per week. However, the large standard deviation suggests that a proportion of
students scored considerably higher or lower than the mean.
The sample had an average BMI of 26.5 (kg/m2), which is slightly higher than BMIs
reported in other studies on college students (Rovniak et al., 2002; Wallace et al., 2000; Wyse,
Mercer, Ashford, Buxton, & Gleeson, 1995). In contrast to statements made above, it is
surprising that kinesiology major students (majority in this study) rated this high on BMI. On the
other hand, the ratio of weight and height is usually not considered the best estimate of BMI.
Regardless of these, in a way unexpected, results of BMI, the need for PA is important since the
previous results in this population also showed the rates of overweight and obesity to be high
(41% being overweight, including
13% classified as obese; Magoc & Tomaka,
2006).
Furthermore, 33% of El Paso adults are obese, and 16% of the Hispanics in the El Paso region
have been diagnosed with type 2 diabetes, which is more than 3 times the national average
(Heath & Coleman, 2003). In addition, the obesity rate among Hispanics is 22.6%, which is
higher than among non-Hispanic white (18.7%). However, the obesity among Hispanics is even
worse in Texas where one third of Hispanics are considered obese (Heath & Coleman, 2003).
The primary analysis in this study tested the relationships between the SCT constructs
and PA. As expected, the SCT constructs showed a positive correlation with the level of PA. In
addition, self-efficacy remained the most significant predictor of PA for both genders. These
results are consistent with previous studies reporting that self-efficacy was the strongest
predictor of regular PA (McAuley, 1992; Armstrong, Sallis, Hovell, & Hofstetter, 1993; Wallace
et al., 2000; Sallis, Hovell, & Hofstetter, 1992; Rovniak et al., 2002).
Limitations and Recommendations for Future Research
The present study has several limitations, and such limitations point toward the need for
future research. For example, one limitation of the present study was its cross-sectional design.
Even though useful, this type of design does not provide conclusions about causality. A real
problem in causal order exists in cross-sectional studies because the relationship between the
dependent and independent variables may just be reciprocal. In this study, specifically, the
higher level of self-efficacy may show increase the level of PA. On the other hand, the higher
level of PA may show increase in self-efficacy. Here comes the real problem because it is
uncertain whether self-efficacy precedes the PA or vice versa. This is especially typical in
correlational studies, and it refers to Ambiguous Temporal Precedence, one of the threats to
internal validity (Shadish, Cook, & Campbell, 2002). Longitudinal studies, however, would have
a greater ability to drawing conclusions regarding individual’s participation in PA and how such
activity relates to SCT variables.
A second limitation related to generalization, one of the threats to external validity
(Shadish et al., 2002). The results in this study were based on a sample of college students who
are primarily of Mexican origin. However, this sample is still small to draw conclusions about
the Hispanic college population in general and other Hispanic groups, in particular. In addition,
the majority of students in this study were kinesiology major, and it is uncertain that the same
results would hold for other majors.
A final limitation related to the self-report nature of the measures and accompanying
problems. Self-reports do not provide an objective measure of levels of PA. Without the use of
accurate and more objective ways to measure PA, there is always the risk of bias in the results.
In this regard, future studies might rely on a wider variety of data sources and more objective
measures (e.g., using pedometers, heart rate monitors), rather than relying exclusively on self-
reported questionnaires.
11
D. Magoc and J. Tomaka
The results of this study suggest that people with higher self-efficacy are more likely to
participate in PA. The results also help understand the relationship between the SCT variables
and PA, suggesting that maintaining the SCT processes will lead to regular PA. Thus,
encouraging and targeting PA together with cognitive changes might be of great interest for
future research.
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Submitted April 21, 2010
Accepted June 25, 2010
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