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Roles of Physical Activity Type in Exercise Motivational Profiles and Behavioral Frequencies Among College Freshmen

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This study examined the relationships among gender, race/ethnicity, physical activity (PA) type, exercise motivation, and frequencies of various exercise intensities. College freshmen (N = 170; 68 male, 102 female) in the southwestern U.S. completed an online survey on exercise motivation and behavior. Chi-square tests indicated that males generally performed more fitness training and less aerobic exercise than females, whereas no differences were found among racial/ethnic groups. Descriptive discriminant analyses revealed that sport participation contributed to the most adaptive motivational profile and highest behavioral frequencies, suggesting that sport participation is the most effective PA type for college freshmen to maintain exercise.
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Corresponding Author: Tsz Lun (Alan) Chu, PhD, Assistant Professor of Sport, Exercise and Performance
Psychology, University of Wisconsin-Green Bay, MAC C317,2420 Nicolet Dr., Green Bay, Wisconsin
54311, Phone: 920-465-5041, Fax: 920-465-5044, Email: chua@uwgb.edu
INTRODUCTION
It is well established that regular exercise
produces many health benets. Beyond physical
health benets, individuals who exercise regularly
tend to have better mental health than those
who do not (Downs & Ashton, 2011). However,
college students, especially those in the U.S.,
engage in low levels of physical activity (PA).
Based on the American College Health Associa-
tion’s (ACHA)Fall 2016 National College Health
Assessment (ACHA, 2016), only 43.6% of
U.S. college students met the American College
of Sports Medicine’s (ACSM) recommended
exercise guidelines for adults: at least 30 minutes
of moderate-intensity aerobic exercise for ve
days a week, or 20 minutes of vigorous-intensity
aerobic exercise for three days a week(ACSM,
2011).e decline in exercise participation has
been shown to happen during the transition
period from high school to the college freshman
year(Bray & Born, 2004; Serlachius, Hamer,
& Wardle, 2007). In addition to moderate and
vigorous aerobic exercise, adults including college
students are recommended to engage in muscle-
strengthening exercise that involve all major mus-
cle groups on two or more days a week (ACSM,
2011; U.S. Department of Health and Human
Services [USDHHS], 2008), yet only 37.6% of
U.S. college students met this guideline(ACHA,
2016). In light of their insucient PA engage-
ment, ACHA’s Health Campus 2020 student
objectives target 53.5 % and 41.4% of college
students in 2020 who will meet the guidelines
for aerobic exercise and muscle-strengthening ex-
ercise, respectively (ACHA, 2012). To reach this
goal and enhance health benets among college
students, it is imperative to study the correlates
of their behavioral frequencies of various exercise
intensities.
Investigating exercise motivation and
behavior of college freshmen, who are at higher
risk for declines in PA levels during college years
(Deforche, Van Dyck, Deliens, & De Bourde-
audhuij, 2015), is particularly important for
implementing PA interventions. During their
transition from high school to college, many
college freshmen live apart from their family for
the rst time and adopt a new lifestyle, such as
having more unhealthy food consumption, less
PA, and more sedentary behavior (Deforche et
al., 2015). Meanwhile, college freshmen who
live on campus have more access to the campus
recreation facility to engage in various sport
and exercise programs. Research has shown that
college students who use the campus recreation
facility regularly tend to be physically active
(Beggs, Nicholson, Elkins, & Dunleavy, 2014).
Campus recreation facility, therefore, may serve
as a convenient setting for reversing the trend of
PA declines during the transition to college.
Concerning PA participation, motivation
is a critical factor for individuals to choose which
activity to engage(Ball, Rice, & Parry, 2014;
Molanorouzi, Khoo, & Morris, 2015). Previous
studies have found a majority of college students
participate in the following PA types on campus:
R  P A T  E M
P  B F A C
F
Tsz Lun (Alan) Chu, PhD
Tao Zhang, PhD
Hongxin Li, MEd
Abstract: is study examined the relationships among gender, race/ethnicity, physical activity (PA) type,
exercise motivation, and frequencies of various exercise intensities.College freshmen (N = 170; 68 male,
102 female) in the southwestern U.S. completed an online survey on exercise motivation and behavior.
Chi-square tests indicated that males generally performed more tness training and less aerobic exer-
cise than females, whereas no dierences were foundamong racial/ethnic groups. Descriptive discriminant
analyses revealed that sport participation contributed to the most adaptive motivational proleand highest
behavioral frequencies, suggesting that sport participation is the most eective PA type for college freshmen
to maintain exercise.
Keywords: Sport participation; tness training; aerobic exercise; self-determination theory
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Chu, Zhang, Li
sports, group tness, aerobic exercise, informal
workouts, aquatics, and weight training (Beggs et
al., 2014; Lower, Turner, & Petersen, 2013). Yet,
little is known about the relations between the
PA types and exercise motivation among college
students. Examining college freshmen’s exercise
motivational proles and behavioral frequen-
cies across PA types in this study, therefore, can
further our understanding of how to help this
population meet the guidelines for both aerobic
exercise and muscle-strengthening exercise during
their transition to college.
PA Type
College students who engage in leisure
PA mostly did so through the forms of sport
participation, tness training, and aerobic
exercise (Ball et al., 2014; Beggs et al., 2014;
Molanorouzi et al., 2015; Moreno-Murcia, Silva,
Pardo, Sierra Rodríguez, & Huéscar Hernández,
2012). ese three forms constitute PA types
that are dierent in nature: (a) sport participa-
tion includes activities that focus on physical
skills and hand-eye coordination, with elements
of competition (e.g., rules, strategies) (Australian
Bureau of Statistics, 2008); (b) tness training
refers to multifaceted, structured activities such as
exercise for strength training and proprioception
training with a primary goal to enhance physical
tness (e.g. muscular strength and endurance)
and motor skills (e.g., balance, gait) instead of
competition(ACSM, 2011); and (c) aerobic ex-
ercise, also referred to as cardio exercise, includes
activities that stimulate heart rate and breathing
rate to meet the demands of the body's move-
ment for a sustained period(USDHHS, 2008).
Worthy of attention is that while aerobic exercise
is a type ofPA, not all PA (e.g., regular walking)is
aerobic exercise.Dierent individuals may choose
their primary PA type for various reasons. For
instance, female college students are more likely
to primarily engage in aerobic exercise, such as
jogging and group exercise, in order to maintain
regular PA instead of training for competition
and specic skills (Lowry et al., 2000). Further-
more, the literature suggests that dierent PA
types produce dierential health benets among
college students (Australian Bureau of Statistics,
2008; Ball et al., 2014; Lower et al., 2013): (a)
sport participation facilitates physical tness and
well-being through vigorous physical training; (b)
tness training promotes specic tness compo-
nents such as muscular strength and endurance
with a focus on personal achievement; and (c)
aerobic exercise enhances weight control and
cardiovascular tness. erefore, it is important
to note the individual preference toward PA types
and the physical and psychosocial variables that
inuence their dierential benets.
Motivation and preference toward PA
types vary across sex and race/ethnicity (Kil-
patrick, Hebert, & Bartholomew, 2005; Mola-
norouzi et al., 2015). In general, male college
students prefer team sports and strength train-
ing activities, whereas their female counterparts
prefer aerobic activities including cardio exercises,
dance, and yoga (Keating, Guan, Piñero, &
Bridges, 2005).Previous studies have revealed the
role of race/ethnicity in the types of PA and sport
participation among high school and college
students (Keating et al., 2005; Turner, Perrin,
Coyne-Beasley, Peterson, & Skinner, 2015), but
insucient evidence exists on the relations be-
tween race/ethnicity and PA types among college
freshmen. Given the diverse student popula-
tion in college, investigating the prevalence of
PA types among various racial/ethnic groups of
college freshmen have direct implications on PA
promotion during this transitional period.
Exercise Motivational Proles
Exercise motivation is an important cor-
relate of PA type, because individuals have varied
personal goals and motivational processes in
sport and exercise engagement (Sebire, Standage,
& Vansteenkiste, 2008). Self-determination
theory (SDT) is a well-established theory with
six mini-theories that examine various motiva-
tional factors(Deci & Ryan, 1985).To examine
exercise motivational proles in this study, three
mini-theories—goal contents theory (GCT),
basic psychological needs theory (BPNT), and
organismic integration theory (OIT)—were
used to address goal contents, psychological need
satisfaction, and motivational regulations, respec-
tively. Adaptive motivational proles are usually
based on learning goals or interests, and they
allow individuals to foster long-term involvement
and achievement through intrinsic and autono-
mous motivations(Deci & Ryan, 2000; Heyman
& Dweck, 1992). GCT distinguishes two types
of goal contents—intrinsic goals stem from en-
joyment and personal interests, whereas extrinsic
goals are grounded in external factors (e.g., fame)
that do not contribute to self-development (Deci
& Ryan, 2000). Within an exercise context,
intrinsic goals include body image and social
recognition, while extrinsic goals include social
aliation, health management, and skill develop-
ment (Sebire et al., 2008). In addition, BPNT
proposes that autonomy (i.e., feeling of volition),
competence (i.e., feeling of eectiveness), and re-
latedness (i.e., feeling of connectedness) are three
universal psychological needs that are crucial for
optimal functioning and well-being of human
beings (Deci & Ryan, 2000). Satisfaction of these
three psychological needs was found to be posi-
tively associated with intrinsic goals in exercise
(Sebire, Standage, & Vansteenkiste, 2009).
Another mini-theory OIT addresses dier-
ent forms of motivational regulation that inu-
ence a targeted behavior, such as exercise adher-
ence (Deci & Ryan, 2000). Intrinsic motivation
is a completely internalized regulation that signify
engagement in an activity for fun and enjoyment.
On the other hand, extrinsic motivation consists
of four forms of behavioral regulations (i.e.,
integrated, identied, introjected, and external)
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American Journal of Health Studies 34 (2) 2019
with varied degrees of internalization that explain
engagement in an activity for separable outcomes.
Lastly, amotivation represents an absence of inter-
nalization and intention for a behavior. Intrinsic
motivation and internalized forms of extrinsic
motivation (i.e., integrated and identied regula-
tions) are referred to as autonomous motivation.
With autonomous motivation, individuals engage
in exercise because of enjoyment, personal values,
and/or a mastery of activities. On the contrary,
the two minimally internalized forms of extrinsic
motivation (i.e., introjected and external regula-
tions) are referred to as controlled motivation.
With controlled motivation, individuals may
engage in exercise due to perceived pressure from
others and/or avoidance of negative health out-
comes (Deci & Ryan, 2000). Ample research has
shown that autonomous motivation is positively
related to psychological need satisfaction and
intrinsic goals, while controlled motivation is
negatively related to psychological need satis-
faction and positively related to extrinsic goals
(Sebire et al., 2008, 2009).
Individuals who primarily participate
in sports tend to be more autonomously moti-
vated than those who primarily engage in tness
activities or habitual exercise (Ball et al., 2014;
Frederick-Recascino & Schuster-Smith, 2003;
Frederick & Ryan, 1993). Moreover, sport
participants generally report higher competence,
intrinsic motivation, and enjoyment than indi-
viduals engaging in other PA types (e.g., tness
training, aerobic exercise) who tend to report
higher extrinsic motivation (Ball et al., 2014;
Beggs et al., 2014; Frederick & Ryan, 1993;
Molanorouzi et al., 2015; Moreno-Murcia et
al., 2012). Most of these past studies compared
two PA types within a sample of college students
(Ball et al., 2014; Frederick & Ryan, 1993;
Molanorouzi et al., 2015), but they neither
examined these relationships in college freshmen
nor compared all three PA types mentioned in
this study. erefore, comparing all three PA
types in relation to exercise motivational proles
would provide better insights into implementing
motivational interventions during the transition
to college.
Exercise Behavioral Frequencies
College freshmen’s primary PA type may
be associated with their frequencies of various
exercise intensities, including vigorous aerobic
exercise, moderate aerobic exercise, and muscle-
strengthening exercise. Vigorous aerobic exercise
is dened as exercise that triggers substantial
increase in heart rates with hard and fast breath-
ing and is commonly achieved through recre-
ational sport participation such as running and
ball games(USDHHS, 2008). It is an important
protective factor for physical and mental health
among college students (Downs & Ashton,
2011). Moderate aerobic exercise is dened as
exercise that triggers noticeably faster heartbeats
and breathing rate, such as brisk walking and
gardening. Moreover, muscle-strengthening ex-
ercise, including weight training, can be dened
as moderate or vigorous exercise that overloads
the major muscle groups of the body (USD-
HHS, 2008).
Although there is support that sport par-
ticipation tends to involve more vigorous aerobic
exercise (Downs & Ashton, 2011), limited
research has examined how primary engagement
in tness training or aerobic exercise contributes
to the frequencies of vigorous aerobic exercise,
moderate aerobic exercise, and muscle-strength-
ening exercise. Previous research ndings have
suggested that individuals who primarily engage
in tness training may have less total exercise
time, but more balanced distribution of aerobic
exercise and muscle-strengthening exercise, than
those primarily engage in aerobic exercise (Hein-
rich, Patel, O’Neal, & Heinrich, 2014). Because
regular participation in both aerobic and muscle-
strengthening exercises is recommended in
order to achieve health benets(ACSM, 2011),
investigating how PA types relate to exercise
behavioral frequencies may inform strategies that
help college freshmen meet the PA guidelines for
various exercise intensities through a combina-
tion of activity choices.
Purposes and Hypotheses
To our knowledge, this study was the rst
investigation that compared all three popular PA
types (i.e., sport participation, tness training,
and aerobic exercise) among college freshmen.
A purpose of this study was to explore whether
the prevalence of PA types varied across sex and
race/ethnicity, while the primary purpose was
to examine how these three PA types might
contribute to exercise motivational proles (i.e.,
goal contents, psychological need satisfaction,
and motivational regulations) and behavioral
frequencies (i.e., vigorous aerobic exercise, mod-
erate aerobic exercise, and muscle-strengthening
exercise). Based on our previously mentioned
review that reveals greater competence, intrinsic
motivation, and enjoyment in sports than tness
activities and habitual exercise, we hypothesized
that (a) the sport participation group would have
the most adaptive motivational prole—greatest
intrinsic goals, psychological need satisfaction,
and autonomous motivation; and(b) the tness
training group would have a more adaptive mo-
tivational prole than the aerobic exercise group.
We did not hypothesize the potential dierences
in exercise behavioral frequencies across the PA
types due to a lack of research evidence.
METHODS
Participants and Procedures
We obtained the formal approval of the
study from the university’s institutional review-
board (IRB) prior to participant recruitment and
data collection at a large-sized public university
in the southwestern U.S. To recruit participants,
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Chu, Zhang, Li
we contacted the Assistant Vice President for
Student Aairs who sent a recruitment email to
all 5,487 freshmen (51.3% White, 14.8% Black,
21.4% Hispanic/Latino, 7.1% Asian, and 5.4%
other) on our behalf at the beginning of the aca-
demic year. ese freshmen were invited to par-
ticipate in the study from September to October
2014. ey were eligible to be included in this
study if they met all three criteria: (a) a rst-time
freshman, (b) 18–20 years of age, and (c) at least
one campus recreation center entry since August
2014. Of the total 4,890 eligible freshmen
who had visited the campus recreation center, a
sample of 210 freshmen participated in the study
during a two-month period. Upon participants’
consent, we collected data via an online survey
that took approximately 20 minutes to complete.
Measures
e study measures were composed of
demographic information including self-reported
sex, age, race/ethnicity, academic major, SDT
variables related to exercise motivational proles
(goal content, psychological need satisfaction,
and motivation in exercise), as well as exercise
behavioral indicators assessing frequency of
recreation center visit, PA types, and frequency
of various exercise intensities (vigorous aerobic
exercise, moderate aerobic exercise, and muscle-
strengthening exercise).
Participants responded to a single-item
measure based on the aforementioned common
PA types of college students: “What is your pri-
mary purpose of visiting the recreation center?”.
Five activity choices were given in order to cate-
gorize participants into one of the three PA types:
sport participation (i.e., individual sports, team
sports), tness training (i.e., muscle-strengthen-
ing exercise, group exercise classes), and aerobic
exercise (i.e., cardio machines, jogging).
Participants’ goal content for exercise
was assessed with the 20-item Goal Contents
in Exercise Questionnaire (GCEQ) (Sebire et
al., 2008). Participants responded to the items
with the prompt “please indicate to what extent
these goals are important for you when exercis-
ing” in a 7-point scale ranging from 1 (not at all
important) through 4 (moderately important)
to 7 (extremely important). Of the 20 items, 12
assessed intrinsic goals (e.g., “to acquire new exer-
cise skills”) and eight assessed extrinsic goals (e.g.,
“to improve my appearance”). Research shows
this measure to be valid and reliable in college
students (Sebire et al., 2008).
Satisfaction of psychological needs (i.e.,
autonomy, competence, and relatedness) was
assessed using the 18-item Psychological Need
Satisfaction in Exercise Questionnaire (PNSE)
(Wilson, Rogers, Rodgers, & Wild, 2006).
Participants responded to the items with the
prompt “please answer the following questions
by considering how you typically feel while you
are exercising” in a 6-point scale ranging from 1
(false) to 6 (true). e measure consisted of three
6-item subscales for measuring autonomy (e.g., “I
feel free to exercise in my own way”), competence
(e.g., “I feel condent I can do even the most
challenging exercises”), and relatedness (e.g., “I
feel attached to my exercise companions because
they accept me for who I am”), respectively. is
measure was shown to have good validity and
reliability in college student samples (Wilson et
al., 2006)
Exercise motivation was assessed with
the 15-item Behavioral Regulations in Exercise
Questionnaire (BREQ) (Mullan, Markland, &
Ingledew, 1997). Participants responded to the
items based on the question “Why do you engage
in exercise?” in a 5-point scale ranging from 1
(not true for me) through 3 (sometimes true
for met) to 5 (very true for me). Four separate
subscales assessed one of the four motivational
regulations, including intrinsic motivation (e.g.,
“I exercise because it’s fun”), identied regulation
(e.g., “I value the benets of exercise”), introject-
ed regulation (e.g., “I feel ashamed when I miss
anexercise session”), and external regulation (e.g.,
“I exercise because other people say Ishould”).
Previous studies have indicated appropriate factor
structures and good reliabilities of this measure
among college students (Mullan et al., 1997).
Item scores for intrinsic motivation and identied
regulation were averaged as a measure of autono-
mous motivation(i.e., an adaptive motivation),
and those scores for introjected regulation and
external regulation were averaged as a measure of
controlled motivation(i.e., a maladaptive motiva-
tion)(Sebire et al., 2008).A motivation was not
assessed in this study because all participants had
used the recreational center that showed their
intention to exercise.
Participants’ exercise frequencies of various
intensities were assessed using the 3-item Leisure
Time Exercise Questionnaire (LTEQ) (Godin
& Shephard, 1985). Participants responded to
the items according to the question “During a
typical week, how many times on average do you
do the following kinds of exercise for more than
15 minutes during your free time?”. e three
items (i.e., types of exercise) were modied to
assess corresponding exercise intensities: vigor-
ous aerobic exercise, moderate aerobic exercise,
and muscle-strengthening exercise. e construct
validity and reliability of the scale have been sup-
ported in comparison to objectively-measured PA
(Jacobs, Ainsworth, Hartman, & Leon, 1993).
e frequency scores for these three items were
used separately in data analyses.
Data Analysis
Prior to conducting analyses, all data
were checked for missing values, invalid pat-
terns, outliers (|z| > 3), and multivariate normal-
ity using a graphical methodplotting chi-square
values against Mahalanobis D2(ompson,
1990). ere were less than 5% of data missing
at random, so expectation maximization (EM)
algorithm was used for data imputation (Tabach-
American Journal of Health Studies 34 (2) 2019
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nick & Fidell, 2007). Scores for each correspond-
ing scale and subscale of motivational constructs
were averaged.Cronbach’s alphas, descriptive
statistics, and correlation coecients were then
computed for the study variables. To examine any
signicant dierences in the composition of PA
types by sex and race/ethnicity, chi-square tests
of independence were conducted with a post-hoc
procedure to examine which groups constituted
the signicant dierences based on their adjusted
standardized residuals (García-Pérez & Núñez-
Antón, 2003). Bonferroni-corrected p values of
.0083 (.05/6) and .0042 (.05/12) were used to
determine the statistical signicance of the chi-
square tests regarding six tests for sex and 12 tests
for race/ethnicity.
To investigate the association of PA types
with exercise motivational proles and behavioral
frequencies, two separate descriptive discrimi-
nant analyses (DDA) were performed with two
respective functions to identify any signicant
group dierences (p < .05) among the three
groups (sport participation, tness training, and
aerobic exercise). Canonical correlations (R
c
)
were used to examine the magnitude of the group
dierences accounted for by the signicant func-
tions, and structure coecients (r
s
) > .30 were
used to determine the variables that primarily
contributed to these dierences (Tabachnick &
Fidell, 2007). Follow-up ANOVAs with Bonfer-
roni post-hoc tests were used to examine the
signicant dierences (p < .05) among the group
centroids that represent the composite scores in a
set of variables (i.e., motivational proles and be-
havioral frequencies). Cohen’s ds were then com-
puted to represent the eect sizes of the centroid
dierences. DDA is superior to the commonly-
used MANOVA with post-hoc univariate tests,
because DDA reduces Type I error by specifying
what the group dierences are using only one sta-
tistical procedure (Sherry, 2006), and it accounts
for the complex and interrelated nature of vari-
ables (e.g., frequencies of various exercise intensi-
ties) studied within the exercise context (Barton,
Yeatts, Henson, & Martin, 2016). Cohen’s d was
used to indicate small (0.2), moderate (0.5), and
large (0.8) eect sizes for the group dierences.
RESULTS
During data screening, we excluded 40
participants of which (a) nine were under 18
years of age, (b) eight were not rst-time fresh-
men, (c) ve had missing data for more than
half of the survey items, and (e) 18 consisted of
univariate and/or multivariate outliers. erefore,
this study included a nal sample of 170partici-
pants (68 male, 102 female).e demographic
composition of the participants, including sex,
age, race/ethnicity, college of study, frequency
of recreation center visits, are displayed in Table
1. e composition of these demographics is
comparable to those of the student population in
the same university, except that our sample had a
relatively higher female-to-male ratio (60.0% vs.
53.0% female), higher ratios of students in Arts
& Sciences (41.8% vs. 34.9%) and Engineering
(15.3% vs. 9.7%), and lower ratios of Busi-
ness (10.0% vs. 16.4%), Public & Community
Service (4.7% vs. 9.0%), and Merchandising,
Hospitality, & Tourism (1.8% vs. 4.4%) than
the general student population.e descriptive
statistics of study variables for the overall sample
and each PA type are displayed in Table 2. Par-
ticipants generally perceived high levels of need
satisfaction and autonomous motivation and
low levels of controlled motivation, while they
reported relatively equal levels of intrinsic and
extrinsic goals. All study measures demonstrated
good internal consistency (
α
s > .85) in this study.
PA Type Across Sex and Race/Ethnicity
Chi-square tests of independence indi-
cated signicant dierences in the composition of
PA type by sex, X
2
(2) = 13.33, p = .001, but not
by race/ethnicity, X
2
(8) = 14.00, p = .08. Upon
examination of the PA type composition between
the sexes, the male participants consisted of a
signicantly larger proportion of tness training
(36.8% vs. 16.7%; p = .002) and smaller propor-
tion of aerobic exercise (19.1% vs. 42.2%; p =
.003) than the female participants, whereas no
signicant dierences were found in the propor-
tion of sport participation between male and
female participants (44.1% vs. 41.1%; p = .70).
Exercise Motivational Proles and Behavioral
Frequencies AcrossPA Types
e DDA of exercise motivational proles
indicated a signicant full model of Function 1
to 2, Wilks’ = .79, X
2
(14) = .38.56, p< .001,
but a nonsignicant model of Function 2, Wilks
= .95, X
2
(6) = 8.31, p = .21. Function 1
explained 16.8% of the variance in the discrimi-
nation of motivational proles across PA types.
Examination of r
s
revealed that intrinsic goals,
competence, relatedness, and autonomous mo-
tivation primarily contributed to the dierences
in motivational proles (see Table 3). Follow-up
ANOVA results further showed that sport partici-
pation had a signicantly higher group centroid
than tness training (p < .001, Cohen’s d = .75)
and aerobic exercise (p < .001, Cohen’s d = .99),
whereas the group centroids of tness training
and aerobic exercise were not signicantly dif-
ferent (p = .58; see Figure 1). erefore, sport
participation had a more adaptive motivational
prole, signied by higher intrinsic goals, compe-
tence, relatedness, and autonomous motivation,
than tness training and aerobic exercise with
medium eect sizes.
e DDA of exercise behavioral frequen-
cies indicated a signicant full model of Function
1 to 2, Wilks’ = .83, X2 (6) = .31.29, p< .001,
and a signicant model of Function 2, Wilks
= .95, X2 (2) = 8.29, p = .02. Function 1 and
Function 2 respectively explained 13.0% and
- 62 -
Chu, Zhang, Li
4.9% of the variance in the discrimination of
behavioral frequencies across PA types. Examina-
tion of r
s
revealed that vigorous aerobic exercise
and muscle-strengthening exercise primarily con-
tributed to the dierences in behavioral frequen-
cies for Function 1 and Function 2, respectively
(see Table 3). Whereas these contributions were
mostly positive, vigorous aerobic exercise nega-
tively contributed to the behavioral frequencies
in Function 2. Follow-up ANOVA for Function
1 further showed that sport participation had a
signicantly higher group centroid than tness
training (p = .005, Cohen’s d = .54) and aerobic
exercise (p< .001, Cohen’s d = .87), while the
group centroids of tness training and aerobic ex-
ercise were not signicantly dierent (p = .12; see
Figure 1). On the other hand, follow-up ANOVA
for Function 2 showed that tness training had
a signicantly higher group centroid than sport
participation (p = .05, Cohen’s d = .44) and
aerobic exercise (p = .02, Cohen’s d = .51), while
the group centroids of sport participation and
aerobic exercise were not signicantly dierent (p
= .99; see Figure 1). erefore, the dierences in
exercise behavioral frequencies are characterized
by more vigorous aerobic exercise and muscle-
strengthening exercise in sport participation
than in tness training and aerobic exercise with
Table 1. Demographic Information of Study Participants (N = 170)
Demographic variables n %
Sex
Male 68 40.0
Female 102 60.0
Age
18 141 82.9
19 28 16.5
20 1 0.6
Race/Ethnicity
White 94 55.3
Black 20 11.8
Hispanic / Latino 41 24.1
Asian 9 5.3
Other 6 3.5
College of study
Arts & Sciences 71 41.8
Business 17 10.0
Education 17 10.0
Engineering 26 15.3
Music 10 5.9
Public Aairs & Community Service 8 4.7
Journalism 7 4.1
Merchandising, Hospitality, & Tourism 3 1.8
Visual Arts & Design 8 4.7
Undecided 3 1.8
Recreation center visit per week
<1 28 16.5
1 27 15.9
2 40 23.5
3 36 21.2
4 21 12.4
>4 18 10.6
-63 -
American Journal of Health Studies 34 (2) 2019
medium-to-large eect sizes, as well as larger ra-
tios of muscle-strengthening exercise to vigorous
aerobic exercise in tness training than in sport
participation and aerobic exercise with small-to-
medium eect sizes.
DISCUSSION
e purpose of this study, guided by
SDT, was to explore whether the prevalence of
PA types(i.e., sport participation, tness train-
ing, and aerobic exercise) varied across college
freshmen’s sex and race/ethnicity and to examine
the exercise motivational proles and frequen-
cies of various exercise intensities across the PA
types. Overall, most participants belonged to the
sport participation group, followed by the aerobic
exercise group. While a larger proportion of male
than female participants constituted the tness
training group, an opposite pattern was shown in
the aerobic exercise group. is nding supports
previous evidence of college students’ exercise be-
havior thatmale college students generally prefer
tness training for better tness, whereas their fe-
male counterpartsgenerally prefer aerobic exercise
for weight loss and better appearance (Keating
et al., 2005).is activity selection by gender is
also in line withSDT and Molanorouzi and col-
leagues’ (2015) nding that male exercisers were
more motivated by competition and mastery,
while female exercisers were more motivated by
physical condition and appearance.
As expected, the sport participation group
had the most adaptive motivational prole,
dierentiated by higher intrinsic goals, compe-
tence, relatedness, and autonomous motivation
than the tness training and the aerobic exercise
groups. ese ndings are consistent with previ-
ous studies on motivation and PA types, which
indicated higher intrinsic motivation among
sport participants than exercisers focusing on
tness and/or aerobic activities (Ball et al., 2014;
Frederick-Recascino & Schuster-Smith, 2003).
SDT posits that autonomy, competence, and
relatedness are three basic psychological needs
that lead to intrinsic motivation and long-term
engagement in an activity (Deci & Ryan, 2000).
Supporting these tenets of SDT, the intrinsic
nature of sport participation tends to promote
skill development, social aliation, and internal
drive to improve, thus providing opportunities
Table 2. Means and Standard Deviations of Exercise Motivational Proles and Behavioral Fre-
quencies for the Overall Sample and Each Activity Type
Overall
(N = 170)
Sport par-
ticipation
(n = 72)
Fitness train-
ing
(n = 42)
Aerobic
exercise
(n = 56)
α M SD MSD MSD MSD
Intrinsic goals .87 4.84 1.04 5.12 1.10 4.74 0.94 4.55 0.96
Extrinsic goals .90 4.77 1.35 4.76 1.40 5.00 1.32 4.60 1.31
Autonomy .90 5.12 0.82 5.09 0.84 5.06 0.86 5.21 0.77
Competence .89 4.55 0.92 4.86 0.81 4.41 0.82 4.26 1.01
Relatedness .91 4.11 1.13 4.31 0.99 3.96 1.29 3.96 1.16
Autonomous moti-
vation
.87 3.94 0.77 4.12 0.64 3.71 0.80 3.87 0.84
Controlled motiva-
tion
.85 2.68 0.94 2.66 0.92 2.79 0.98 2.62 0.94
Vigorous aerobic
exercise
2.63 1.70 3.26 1.65 2.14 1.60 2.18 1.58
Moderate aerobic
exercise
3.44 2.01 3.33 2.00 3.59 2.25 3.47 1.86
Muscle-strengthen-
ing exercise
2.39 1.78 2.88 1.80 2.60 1.84 1.56 1.43
Total exercise 8.46 3.56 9.47 3.83 8.33 2.81 7.21 3.34
Note.Behavioral frequencies (i.e., vigorous aerobic exercise, moderate aerobic exercise, muscle-
strengthening exercise, and total exercise)were based on the number of times per week participants
reported engaging in those exercises.
-64 -
Chu, Zhang, Li
to enhance intrinsic goals and motivation as well
as to satisfy competence and relatedness (Lower
et al., 2013). However, external goals, autonomy,
and controlled motivation did not dierentiate
the PA types in this study. It is plausible that
sport participation still contains an extrinsic
nature related to competition and outperforming
others, thus promoting certain external goals and
controlled motivation. However, the attribution
of external goals and controlled motivation in
the sport participation group is likely dierent
than in the tness training (i.e., to look t) and
aerobic exercise (i.e., to lose weight) groups. On
the other hand, a plausible reason for similar
levels of autonomy across PA types is that college
freshmen who engage in any of these PA types
mostly choose to exercise at a recreational facility
instead of being forced to do so. ese proles
with mixed goals, psychological need satisfaction,
and motivational regulations support the SDT
notion that motivational constructs are multidi-
mensional—individuals could score high or low
in all the constructs, or a combination of high
and low values(Chu, Zhang, & Hung, 2018;
Vansteenkiste, Sierens, Soenens, Luyckx, & Lens,
2009).
Regarding exercise behavior, the sport par-
ticipation group had higher behavioral frequen-
cies, characterized by more vigorous aerobic exer-
cise and muscle-strengthening exercise in general,
than the tness training and aerobic exercise
groups. e high frequency of muscle-strengthen-
ing exercise in the sport participation group may
be attributed to the sport participants’ needs to
keep improving strength and endurance for bet-
ter sport performance. e tness training group
had a larger proportion of muscle-strengthening
exercise to vigorous aerobic exercise than the
sport participation and aerobic exercise groups,
although the frequency of muscle-strengthening
exercise by itself was lower than in the sport par-
ticipation group. is nding implies that college
freshmen who focus on tness training perform
mostly muscle-strengthening exercise with little
vigorous aerobic exercise. Moderate aerobic exer-
cise did not contribute signicantly to the group
dierences in this study, which could be attrib-
uted to its activity nature—walking briskly, slow
Table 3. Results of the Descriptive Discriminant Analyses
Var i abl e Standardized
coecient
rsrs
2 (%)
Exercise motivational proles
Function 1 Rc= .41 Rc
2= 16.8%
Intrinsic goals .466 .548* 30.0%
Extrinsic goals –.180 .044 0.2%
Autonomy –.826 –.112 1.3%
Competence .898 .683* 46.6%
Relatedness –.102 .341* 11.6%
Autonomous motivation .195 .419* 17.6%
Controlled motivation –.200 .002 0.0%
Exercise behavioral frequencies
Function 1 Rc= .36 rc
2= 13.0%
Vigorous aerobic exercise .633 .831* 69.1%
Moderate aerobic exercise –.131 –.100 1.0%
Muscle-strengthening exercise .573 .804* 64.6%
Function 2 Rc= .22 Rc
2= 4.9%
Vigorous aerobic exercise –.847 –.505* 25.5%
Moderate aerobic exercise .229 .156 2.4%
Muscle-strengthening exercise .904 .593* 35.2%
Note.Rc= canonical correlation; Rc
2= squared canonical correlation; rs= structure
coecient; rs
2 = squared structure coecient. *|rs|>.30. Only signicant functions
are shown in the table.
- 65 -
American Journal of Health Studies 34 (2) 2019
bicy
cling, and jogging are unintentional
activities in
which most college students
do not engage very often(ACHA, 2012).
erefore, the frequency of moderate
aerobic exercise did not vary across PA
types. ese results further suggest that
sport participation is the most promising
PA type for college freshmen to meet the
recommended PA guidelines, although a
combination of tness training and aero-
bic exercise could potentially accumulate
enough vigorous and moderate aerobic
exercise. College freshmenin the aerobic
exercise group,femalesin particular, shall
spend more time on muscle-strengthen-
ing exercise through sport participation
or tness training in order to achieve two
days minimum of strength training per
week (ACSM, 2011).
ere are several limitations in this
study that need to be acknowledged. First
and foremost, all of the study measures
were self-reports, so they were subject to
biases and social desirability of report-
ing more adaptive exercise motivational
proles and higher behavioral frequen-
cies. Future research should incorporate
objective measures, such as accelerom-
eters, to assess participants’ exercise
behavioral frequencies. Second, given the
cross-sectional research design, we could
not interpret any causal eects of PA
type on exercise motivational proles and
behavioral frequencies. Experimental or
longitudinal research design is needed to
understand the potential inuence of PA
types by studying the changes in motiva-
tional proles and behavioral frequencies
over a period of time. Furthermore, more
qualitative studies are warranted to fur-
ther our understanding of “why” PA types
may be related to motivational outcomes
beyond “what” relationships exist among
the variables.
e last limitation is related to
the sample of this study. e data were
collected from a relatively small sample
of freshmen, with about 4% of response
rate, at only one large-sized public uni-
versity in the southwestern U.S. Although
this sample was representative of the
freshman population in the university, the
results might not be generalizable to other
smaller universities in a dierent region,
or to other types of institutions. More-
over, all of the participants had some
degree of motivation to exercise, andself-
selection bias might exist as the college
freshmen who chose to participate in this
study were likely to value exercise and
thus had adaptive motivational proles. A
higher ratio of female than male par-
ticipants could have also inuenced the
DDA results, as female exercisers tend to
engage in more aerobic exercise and less
muscle-strengthening exercise than their
male counterparts. us, further research
with larger sample sizes from a greater va-
riety of collegesare needed to test whether
our ndings will hold true. Despite this
Figure 1.Group centroids of the three activity types from the descriptive discriminant
analyses (DDA) in exercise motivation proles and behavioral frequencies.
- 66 -
Chu, Zhang, Li
sampling limitation, the sample char-
acteristics including the distribution of
race/ethnicity and college of study were
comparable to the student population in
the university, which enhanced the inter-
nal validity of the study ndings.
To our knowledge, this was the rst
study that investigated PA types based
on the dierential goals of the activities
in which college students tend to partici-
pate: sport participation based on social
aliations, tness training based on
physical and personal health awareness,
and aerobic exercise based on appearance
and health goals. Moreover, examination
of the three PA types using multivariate
analyses constitutes another major contri-
bution of this study. Instead of using only
univariate analyses such as ANOVAs with
post-hoc analyses, we conducted DDAs
as multivariate analyses, which provided
additional information regarding the
relative contribution of the variables that
dierentiated the three PA types. We
recommend that future research continue
to use multivariate analyses in order to
understand the complexity of physical
and psychological variables in sport and
exercise settings (Barton et al., 2016).
CONCLUSION
In light of the fact that most col-
lege fresh
men in the U.S. do not meet the
recommended
PA guidelines (ACHA, 2012),
this study highlights that the college freshmen
who visited the campus recreation center and
primarily participated in sports had the most
adaptive motivational proles and the highest
exercise behavioral frequencies. According to the
USDHHS(2008), sport activities consist of a
substantial amount of recommended moderate
and vigorous exercise that active adults should
achieve.us, sport participants may reap the
benets of having more adaptive motivation and
health outcomes. On the other hand, the college
freshmen who visited the campus recreation
center and primarily engaged in aerobic exercise
had the most maladaptive motivational proles
and the lowest behavioral frequencies. us, we
propose several practical implications for college
recreation and health professionalsin a large-sized
university setting with similar demographics to
consider. First, college campus activities should
include, but not limited to, exercise programs
that educate freshmen about the health benets
of sport participation and tness training beyond
aerobic exercise. For example, during freshman
orientations, campus recreation and student
health departments can organize workshops that
provide freshmen with information about dier-
ent opportunities for recreational sport participa-
tion. Second, recreational sport programs such as
intramural and club sports need to be organized
inclusively across skill levels to encourage par-
ticipation and satisfaction of psychological needs
among freshman participants. More specically,
recreational sport sta can create dierent levels
of sport teams within one sport to maximize par-
ticipants’ engagement and enjoyment. Last but
not least, health professionals should screen for
college students’ PA types beyond the quantity of
their exercise in order to understand their specic
activity engagement.
References
American College Health Association. (2012).
Healthy Campus 2020: Student objectives. Re-
trieved from http://www.acha.org/HealthyCam-
pus/HealthyCampus/Student_Objectives.aspx
American College Health Association. (2016).
Fall 2016 reference group executive summary.
National College Health Assessment. Retrieved
from http://www.acha-ncha.org/docs/NCHA-
II_FALL_2016_REFERENCE_GROUP_EX-
ECUTIVE_SUMMARY.pdf
American College of Sports Medicine. (2011).
ACSM issues new recommendations on quantity
and quality of exercise. Retrieved from http://
www.acsm.org/about-acsm/media-room/news-
releases/2011/08/01/acsm-issues-new-recommen-
dations-on-quantity-and-quality-of-exercise
Australian Bureau of Statistics. (2008). Dening
sport and physical activity, a conceptual model.
Retrieved from http://www.ausstats.abs.gov.au/
ausstats/subscriber.nsf/0/5527537D36688787CA
257508000F39D1/$File/4149055001_2008.pdf
Ball, J., Rice, M. R., & Parry, T. (2014). Adults’
motivation for physical activity: Dierentiating
motives for exercise, sport, and recreation. Recre-
ational Sports Journal, 38, 130–142. https://doi.
org/10.1123/rsj.2013-0018
Barton, M., Yeatts, P. E., Henson, R. K., & Martin,
S. B. (2016). Moving beyond univariate post-hoc
testing in exercise science: A primer on descrip-
tive discriminate analysis. Research Quarterly for
Exercise and Sport, 87(4), 365–375. https://doi.
org/10.1080/02701367.2016.1213352
Beggs, B., Nicholson, L., Elkins, D., & Dunleavy,
S. (2014). Motivation for participation in cam-
pus recreation based on activity type. Recre-
ational Sports Journal, 38, 163–174. https://doi.
org/10.1123/rsj.2014-0038
Bray, S. R., & Born, H. A. (2004). Transition
to University and Vigorous Physical Activ-
ity: Implications for Health and Psychological
Well-Being. Journal of American College Health,
52(June), 181–188. https://doi.org/10.3200/
JACH.52.4.181-188
Chu, T. L., Zhang, T., & Hung, T. M. (2018).
Motivational proles in table tennis players:
Relations with performance anxiety and sub-
jective vitality. Journal of Sports Sciences, 36,
2738–2750. https://doi.org/10.1080/02640414.
2018.1488517
Deci, E. L., & Ryan, R. M. (1985). Intrinsic moti-
vation and self-determination in human behavior.
New York, NY: Plenum Press.
Deci, E. L., & Ryan, R. M. (2000). e “what
- 67 -
American Journal of Health Studies 34 (2) 2019
and “why” of goal pursuits: Human needs and
the self-determination of behavior. Psychological
Inquiry, 11, 227–268. https://doi.org/10.1207/
S15327965PLI1104_01
Deforche, B., Van Dyck, D., Deliens, T., & De
Bourdeaudhuij, I. (2015). Changes in weight,
physical activity, sedentary behaviour and dietary
intake during the transition to higher education:
A prospective study. International Journal of Be-
havioral Nutrition and Physical Activity, 12, 16–
25. https://doi.org/10.1186/s12966-015-0173-9
Downs, A., & Ashton, J. (2011). Vigorous physical
activity, sports participation, and athletic iden-
tity: Implications for mental and physical health
in college students. Journal of Sport Behavior, 34,
228–249.
Frederick-Recascino, C. M., & Schuster-Smith, H.
(2003). Competition and intrinsic motivation in
physical activity: A comparison of two groups.
Journal of Sport Behavior, 26, 240–254.
Frederick, C. M., & Ryan, R. M. (1993). Dier-
ences in motivation for sport and exercise and
their relations with participation and mental
health. Journal of Sport Behavior, 16, 125–145.
García-Pérez, M. A., & Núñez-Antón, V.
(2003). e proper use of standardized re-
siduals. Educational and Psychological
Measurement, 63, 825–839. https://doi.
org/10.1177/0013164403251280
Godin, G., & Shephard, R. J. (1985). A simple
method to assess exercise behavior in the
community. Canadian Journal of Applied
Sport Sciences, 10, 141–146. https://doi.
org/10.1097/00005768-199706001-00009
Heinrich, K. M., Patel, P. M., O’Neal, J. L.,
& Heinrich, B. S. (2014). High-intensity
compared to moderate-intensity training for
exercise initiation, enjoyment, adherence,
and intentions: An intervention study. BMC
Public Health, 14, 789–794. https://doi.
org/10.1186/1471-2458-14-789
Heyman, G. D., & Dweck, C. S. (1992). Achieve-
ment goals and intrinsic motivation: eir
relation and their role in adaptive motivation.
Motivation and Emotion, 16(3), 231–247.
https://doi.org/10.1007/BF00991653
Jacobs, D. R., Ainsworth, B. E., Hartman,
T. J., & Leon, A. S. (1993). A simultane-
ous evaluation of 10 commonly used physical
activity questionnaires. Medicine & Science
in Sports & Exercise, 25, 81–91. https://doi.
org/10.1249/00005768-199301000-00012
Keating, X. D., Guan, J., Piñero, J. C., & Bridges,
D. M. (2005). A meta-analysis of college
students’ physical activity behaviors. Journal of
American College Health, 54, 116–126. https://
doi.org/10.3200/JACH.54.2.116-126
Kilpatrick, M., Hebert, E., & Bartholomew, J.
(2005). College students’ motivation for physical
activity: Dierentiating men’s and women’s mo-
tives for sport participation and exercise. Journal
of American College Health, 54, 87–94. https://
doi.org/10.3200/JACH.54.2.87-94
Lower, L. M., Turner, B. A., & Petersen, J. C.
(2013). A comparative analysis of perceived
benets of participation between recreational
sport programs. Recreational Sports Journal, 37,
66–83. https://doi.org/10.1123/rsj.37.1.66
Lowry, R., Galuska, D. A., Fulton, J. E., Wechsler,
H., Kann, L., & Collins, J. L. (2000). Physi-
cal activity, food choice, and weight manage-
ment goals and practices among U.S. college
students. American Journal of Preventive
Medicine, 18, 18–27. https://doi.org/10.1016/
S0749-3797(99)00107-5
Molanorouzi, K., Khoo, S., & Morris, T. (2015).
Motives for adult participation in physical activ-
ity: Type of activity, age, and gender. BMC Public
Health, 15, 66–77. https://doi.org/10.1186/
s12889-015-1429-7
Moreno-Murcia, J. A., Silva, F. B., Pardo, P. J. M.,
Sierra Rodríguez, A. C., & Huéscar Hernández,
E. (2012). Motivation, frequency and activity
type in physical exercise participants. Revista
Internacional de Medicina y Ciencias de La Ac-
tividad Física y El Deporte., 12, 649–662.
Mullan, E., Markland, D., & Ingledew, D. K.
(1997). A graded conceptualisation of self-deter-
mination in the regulation of exercise behaviour:
Development of a measure using conrma-
tory factor analytic procedures. Personality and
Individual Dierences, 23, 745–752. https://doi.
org/10.1016/S0191-8869(97)00107-4
Sebire, S. J., Standage, M., & Vansteenkiste, M.
(2008). Development and validation of the Goal
Content for Exercise Questionnaire. Journal
of Sport & Exercise Psychology, 30, 353–377.
https://doi.org/10.1123/jsep.30.4.353
Sebire, S. J., Standage, M., & Vansteenkiste, M.
(2009). Examining intrinsic versus extrinsic
exercise goals: Cognitive, aective, and behavioral
outcomes. Journal of Sport & Exercise Psychol-
ogy, 31, 189–210. https://doi.org/10.1123/
jsep.31.2.189
Serlachius, A., Hamer, M., & Wardle, J. (2007).
Stress and weight change in university students
in the United Kingdom. Physiology and Be-
havior, 92, 548–553. https://doi.org/10.1016/j.
physbeh.2007.04.032
Sherry, A. (2006). Discriminant analysis in
counseling psychology research. e Counsel-
ing Psychologist, 34, 661–683. https://doi.
org/10.1177/0011000006287103
Tabachnick, B. G., & Fidell, L. S. (2007). Using
multivariate statistics (5th ed.). Boston, MA:
Pearson.
ompson, B. (1990). MULTINOR: A FOR-
TRAN program that assists in evaluating multi-
variate normality. Educational and Psychological
Measurement, 50(4), 845–848. https://doi.
org/10.1177/0013164490504014
Turner, R. W., Perrin, E. M., Coyne-Beasley,
T., Peterson, C. J., & Skinner, A. C. (2015).
Reported sports participation, race, sex, eth-
nicity, and obesity in US adolescents from
NHANES Physical Activity (PAQ_D).
Global Pediatric Health, 2, 1–9. https://doi.
org/10.1177/2333794X15577944
Bozzolo, Beck, Wang
- 68 -
U.S. Department of Health and Human Services.
(2008). 2008 Physical Activity Guidelines for
Americans. Retrieved from https://health.gov/
paguidelines/pdf/paguide.pdf
Vansteenkiste, M., Sierens, E., Soenens, B., Luyckx,
K., & Lens, W. (2009). Motivational proles
from a self-determination perspective: e qual-
ity of motivation matters. Journal of Educa-
tional Psychology, 101, 671–688. https://doi.
org/10.1037/a0015083
Wilson, P. M., Rogers, W. T., Rodgers, W. M., &
Wild, T. C. (2006). e Psychological Need
Satisfaction in Exercise Scale. Journal of Sport &
Exercise Psychology, 28, 231–251. https://doi.
org/10.1024/1421-0185/a000107
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Book
I: Background.- 1. An Introduction.- 2. Conceptualizations of Intrinsic Motivation and Self-Determination.- II: Self-Determination Theory.- 3. Cognitive Evaluation Theory: Perceived Causality and Perceived Competence.- 4. Cognitive Evaluation Theory: Interpersonal Communication and Intrapersonal Regulation.- 5. Toward an Organismic Integration Theory: Motivation and Development.- 6. Causality Orientations Theory: Personality Influences on Motivation.- III: Alternative Approaches.- 7. Operant and Attributional Theories.- 8. Information-Processing Theories.- IV: Applications and Implications.- 9. Education.- 10. Psychotherapy.- 11. Work.- 12. Sports.- References.- Author Index.
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