European Journal of Sport Science, 2015
Vol. 15, No. 2, 151–160, http://dx.doi.org/10.1080/17461391.2014.940557
ORIGINAL ARTICLE
Motivation towards dual career of European student-athletes
CORRADO LUPO1,2, FLAVIA GUIDOTTI1, CARLOS E. GONCALVES3,
LILIANA MOREIRA3, MOJCA DOUPONA TOPIC4, HELENA BELLARDINI5,
MICHAIL TONKONOGI5, ALLEN COLIN6, & LAURA CAPRANICA1
1
Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Rome, Italy, 2Motor Science
Research Center, S.U.I.S.M. Centro Servizi, Department of Medical Sciences, University of Turin, Turin, Italy, 3Faculty of
Sport Sciences, University of Coimbra, Coimbra, Portugal, 4Department of Sociology and History of Sport, Faculty of Sport,
University of Ljubljana, Ljubljana, Slovenia, 5Department of Health- and Social Sciences, Dalarna University, Falun,
Sweden, 6Department of Sport and Exercise Sciences, University of Northumbria, Newcastle, UK
Abstract
The present study aimed to investigate motivations for the dual career of European student-athletes living in countries
providing different educational services for elite athletes: State-centric regulation–State as sponsor/facilitator (State),
National Sporting Federations/Institutes as intermediary (Federation) and Laisser Faire, no formal structures (No
Structure). Therefore, the European Student-athletes’ Motivation towards Sports and Academics Questionnaire
(SAMSAQ-EU) was administered to 524 European student-athletes. Exploratory Factor Analysis, and Confirmatory
Factor Analysis were applied to test the factor structure, and the reliability and validity of the SAMSAQ-EU, respectively.
A multivariate approach was applied to verify subgroup effects (P ≤ 0.05) according to gender (i.e., female and male), age
(i.e., ≤24 years, >24 years), type of sport (i.e., individual sport and team sport) and competition level (i.e., national and
international). Insufficient confirmatory indexes were reported for the whole European student-athlete group, whereas
distinct three factor models [i.e., Student Athletic Motivation (SAM); Academic Motivation (AM); Career Athletic
Motivation (CAM)] emerged, with acceptable reliability estimates, for State (SAM = 0.82; AM = 0.75; and CAM = 0.75),
Federation (SAM = 0.82; AM = 0.66; and CAM = 0.87) and No Structure (SAM = 0.78; AM = 0.74; and CAM = 0.79)
subgroups. Differences between subgroups were found only for competition level (P < 0.001) in relation to SAM (P =
0.001) and CAM (P < 0.001). For SAM, the highest and lowest values emerged for Federation (national, 5.1 ± 0.5;
international, 5.4 ± 0.5) and State (national, 4.5 ± 0.9; international, 4.8 ± 0.7). The opposite picture emerged for CAM
(Federation: national, 3.3 ± 0.7; international, 3.5 ± 0.9; State: national, 5.0 ± 0.8; international, 5.0 ± 0.9). Therefore,
despite SAMSAQ-EU demonstrated to be a useful tool, results showed that European student-athletes’ motivation for dual
career has to be specifically investigated according to social contexts.
Keywords: SAMSAQ-EU, validity, athletic career
Introduction
Athletic career relates to different competitive sport
levels (i.e., local, regional, national or international),
with sport typology influencing different career
trajectories (Stambulova & Alfermann, 2009; Stambulova, Alfermann, Statler, & Côté, 2009). In general, youth athletes involved in sport academies start
competing around 8 years of age and a 10-year
experience is required to achieve elite performance,
with additional 5–10 years to compete at the highest
level (Wylleman & Reints, 2010). Thus, talent
selection, detection and development overlap primary to higher education (Wylleman & Reints, 2010).
Despite sport participation is strongly encouraged,
youth elite athletes encounter several difficulties in
combining their sport and educational commitments
(Capranica & Millard-Stafford, 2011; Conzelmann &
Nagel, 2003). In fact, to achieve athletic excellence
20–30 h.week–1 for training and competitions are
Correspondence: Corrado Lupo, Motor Science Research Center, S.U.I.S.M. Centro Servizi, Department of Medical Sciences, University
of Turin, Piazza Bernini, 12, 10143 Turin, Italy. E-mail: corrado.lupo@unito.it
© 2014 European College of Sport Science
152
C. Lupo et al.
required, whereas students spend around 30 h.week–1
to attain a satisfactory academic career (Aquilina,
2013). Furthermore, competition schedules spread
over several months (i.e., team sports) or packed
periods (i.e., individual sports) could affect the student-athlete’s capability to successfully organise his/
her athletic and educational commitments.
In Northern America, sport and educational systems are linked to support student-athletes in achieving both academic and sport requirements. However,
American student-athletes frequently struggle to meet
academic eligibility (Aries, McCarthy, Salovey, &
Banaji, 2004; Gatmen, 2012), being mostly motivated towards athletic success (Gaston-Gayles, 2005;
Simons, Van Rheenen, & Covington, 1999). Conversely, in Europe sport is usually organised at club
level, with no or limited relationship with the educational system. Therefore, European talented athletes
tend to drop out sport and prioritise education
to prepare for future job opportunities (Amara,
Aquilina, & Henry, 2004; Istituto Nazionale di
Statistica-ISTAT, 2007) or postpone (i.e., >24 years
of age) the achievement of a degree. Despite sport
should be an important cultural component independently of gender, women have fewer opportunities to
pursue professional athletic careers compared to men
(Guidotti & Capranica, 2013a; International Olympic Committee, 2004, 2012; International Working
Group on Women and Sport, 2012; Pfister, 2010). In
general, women seem to have a higher academic
motivation (AM) and a lower career athletic motivation (CAM) than men (Doupona Topic, 2005).
However, gender differences should be further
examined.
Recently, sport practice has been included in the
strategic agenda of the EU to promote integration
among nations and cultures (European Commission, 2007a, 2007b, 2011, 2012). In particular, the
European parliament has embraced several actions
to promote the dialogue between sport and educational bodies to establish ‘dual career’ (i.e., the
combination of elite sport and education) pathways
for student-athletes (European Commission, 2007a,
2007b, 2011, 2012), and consequently to promote
the transition from sport into the labour market.
Actually, member states present relevant differences
in dual career policies (Aquilina, 2013; Aquilina &
Henry, 2010; Henry, 2013), including State-centric regulations (i.e., France, Hungary, Luxemburg,
Poland, Portugal and Spain), State as a sponsor/
facilitator (i.e., Belgium-Flanders, Denmark,
Estonia, Finland, Germany, Latvia, Lithuania and
Sweden), National Sporting Federations/Institutes
as intermediary (i.e., Greece and United Kingdom)
and Laisser Faire/no formal structures (i.e., Malta,
Austria, Cyprus, Czech Republic, Ireland, Italy, the
Netherlands, Malta, Slovakia and Slovenia). Whilst
some European elite athletes could benefit from their
governments as guarantors for maintaining athletes’
rights in accessing education and work at the end of
their sport career (i.e., State-centric regulations and
State as sponsor), those living in countries with the
Laisser Faire approach have to succeed in personally
negotiating with the teaching staff a flexible attendance to courses and evaluation schedules. To safeguard the development of young athletes, European
Guidelines on Dual careers of Athletes have been
recently adopted (European Commission, 2012), in
which research for monitoring and evaluating the
European dimension of dual career is strongly
encouraged.
To understand academic and athletic motivations
of American student-athletes, the 30-item Studentathletes’ Motivation toward Sports and Academics
Questionnaire (SAMSAQ) has been validated
in American Division I NCAA student-athletes
(Gaston-Gayles, 2005). The instrument consists of a
three-factor structure, representing motivation towards elite sport [i.e., Student Athletic Motivation
(SAM)], motivation towards academic-related tasks
(i.e., AM) and motivation to pursue a professional
sport career (i.e., CAM). In particular, the SAM and
CAM factors refer to motivations towards the desire to
fulfil the current and perspective sport carriers, respectively. Conversely, AM refers to motivations to accomplish an academic degree (Gaston-Gayles, 2005). For
the three subscales, the author reported Cronbach’s
alpha coefficients ranging from 0.79 to 0.86.
In 2010, Fortes and colleagues harmonised the
original SAMSAQ to investigate the motivation
towards academics and sport of United Arab
Emirates students (i.e., athletes and non-athletes
belonging to several ethnic groups) enrolled in
business/management degrees. The questionnaire
included literally translated items from the SAMSAQ
and modified items introduced prominently for the
motivation towards an outstanding academic career
leading to a good job salary. Thus, relevant discrepancies with respect to the original American model
emerged. Nevertheless, the authors reported reliability estimates for the three subscales ranging from 0.70
to 0.84. When the validity of the original instrument
has been tested in a sample of Italian student-athletes
of several competition levels (i.e., county, regional
and national) enrolled in Sport Science degree
courses (Guidotti et al., 2013), the model maintained a three-factor structure (i.e., Cronbach’s alpha
coefficients ranging from 0.70 to 0.84) but the
factor loadings of each subscale diverged from the
American version. Furthermore, nine items were
removed due to low item-to-total correlations, low
reliability and low factor loading. These findings
Motivation towards dual career
indicate the potential impact of significant cultural
differences on the factor structure of this psychometric
tool. For this reason, a harmonised Italian version of
the SAMSAQ (i.e., SAMSAQ-IT/A) has been provided (Guidotti & Capranica, 2013b), including 21
items maintained from the SAMSAQ and 9 rephrased
items (i.e., Cronbach’s alpha coefficients ranging from
0.75 to 0.84), which were inserted to substitute those
considered not suitable for the Italian context.
At European level, pioneering research on crossnational comparisons of student-athletes’ motivation
towards the dual career in relation to gender, age
and type of sport, Lupo and colleagues (Lupo,
Tessitore, Capranica, Rauter, & Doupona Topic,
2012) administered to Italian and Slovenian studentathletes a questionnaire including the 30 items of the
SAMSAQ in addition to the 9 items of the Italian
harmonised version (SAMSAQ-EU). This tool
(Table I) maintained a three-factor structure of the
original model (Cronbach’s alpha coefficients ranging
from 0.78 to 0.85) and has proven to be useful for
ascertaining European student-athletes’ motivation
for a dual career in countries with No Structured
sport-education measures in place. Furthermore,
differences between countries in motivation for academic-related tasks and in motivation to pursue a
professional sport career called for further crossnational studies on the motivation of European
student-athletes living in countries with State-centric
regulations/State as sponsor and National Sporting
Federations/Institutes as intermediary policies (Lupo
et al., 2012).
Although the European Commission respects
the autonomy of sport-governing structures of member states, it calls for action to develop the European
dimension in sport by promoting trans-national
dialogue to improve employability and mobility
through education and training (European Commission, 2011). To understand the career development
of athletes and to monitor student-athletes’ adherence to both sport and academic programmes, there
is a need of a valid and reliable quantitative approach
to evaluate sport and academic orientations from a
psychological perspective (Stambulova, Stephan, &
Japhag, 2007). In fact, the knowledge of the studentathletes’ motivation in relation to different educational and sport systems in Europe could promote a
better understanding of their sport and academic
expectations, providing useful information for sport
and academic decision-makers. In this vein, crossnational comparisons related to the motivations
of the student-athlete toward a dual career could
contribute to develop appropriate strategies for
a sustainable combination of academic and sport
programmes.
153
Thus, the aim of the present study was two-fold:
(1) to validate a psychometric instrument (i.e., the
SAMSAQ-EU) in relation to State-centric regulation
and State as sponsor/facilitator (i.e., State), National
Sporting Federations/Institutes as intermediary (i.e.,
Federation) and Laisser Faire, no formal structures
(i.e., No Structure) European policies (Aquilina &
Henry, 2010); (2) according to the distinct European
policies on dual career (i.e., State, Federation and
No Structure), to verify differences between European student-athletes in relation to their gender, age,
type of sport and competition level. In particular, it
has been hypothesised that: (1) the SAMSAQ-EU
would show a single model with questionable validity
for the whole European student-athletes sample,
with more suitable distinct models for the educational services for elite athletes (i.e., State, Federation and No Structure); (2) motivation levels toward
dual career would vary in relation to the typology of
educational services provided for elite athletes, and
the athlete’s gender, age, type of sport and competition level.
Methods
Subjects
The local Institutional Review Board approved this
cross-national study including European studentathletes from six member states, classified according
to three dual career policy subgroups: (1) State, (2)
Federation and (3) No Structure. Out of the 25
countries included in the Aquilina and Henry (2010)
analysis, only six countries (24%) responded to
the invitation to participate in the study: France,
Portugal, Sweden (i.e., State, 21%), United Kingdom (i.e., Federation, 50%), Italy and Slovenia (i.e.,
No Structure, 22%).
To participate in the study, the following inclusion criteria for student-athletes were considered:
(1) being enrolled in a university course and (2)
competing in organised sport for at least 10 years at
national or international competition levels. Given
the profound differences within and between countries in their sport and educational organisation, the
recruitment of athletes was specific for each country
(Table II). Five-hundred-twenty-four European collegiate student-athletes met the inclusion criteria and
volunteered for the study (Table II).
Instrumentation and procedure
The SAMSAQ-EU (Lupo et al., 2012; Table I),
which is a harmonised psychometric instrument
including the 30-item SAMSAQ (Gaston-Gayles,
2005) and 9 rephrased items for Italian studentathletes (SAMSAQ-IT/A; Guidotti & Capranica,
154
C. Lupo et al.
Table I. The items of the SAMSAQ-EU instrument
Item/Tool
1/SAMSAQ
2/SAMSAQ
3/SAMSAQ
4/SAMSAQ
5/SAMSAQb
6/SAMSAQb
7/SAMSAQ
8/SAMSAQ
9/SAMSAQb
10/SAMSAQ
11/SAMSAQ
12/SAMSAQ
13/SAMSAQ
14/SAMSAQ
15/SAMSAQ
16/SAMSAQb
17/SAMSAQa,b
18/SAMSAQ
19/SAMSAQ
20/SAMSAQ
21/SAMSAQb
22/SAMSAQ
23/SAMSAQ
24/SAMSAQ
25/SAMSAQb
26/SAMSAQa,b
27/SAMSAQ
28/SAMSAQ
29/SAMSAQb
30/SAMSAQ
31/SAMSAQ-IT/A
32/SAMSAQ-IT/A
33/SAMSAQ-IT/A
34/SAMSAQ-IT/A
35/SAMSAQ-IT/A
36/SAMSAQ-IT/A
37/SAMSAQ-IT/A
38/SAMSAQ-IT/A
39/SAMSAQ-IT/A
Text
I am confident that I can achieve a high grade point average this year (3.0 or above).
Achieving an high level of performance in my sport is an important goal for me this year.
It is important to me to learn what is taught in my courses.
I am willing to put in the time to earn excellent grades in my courses.
The most important reason why I am in school is to play my sport.
The amount of work required in my courses interferes with my athletic goals.
I will be able to use what is taught in my courses in different aspects of my life outside of school.
I chose to play my sport because it’s something I’m interested in as a career.
I have some doubt about my ability to be a star athlete on my team.
I chose (or will choose) my major because it is something I am interested in as a career.
Earning a high grade point average (3.0 or above) is not an important goal for me this year.
It is important to me to learn the skills and strategies taught by my coaches.
It is important for me to do better than other athletes in my sport.
The time I spend engaged in my sport is enjoyable to me.
It is worth the effort to be an exceptional athlete in my sport.
Participation in my sport interferes with my progress towards earning a college degree.
I get more satisfaction from earning an “A” in a course toward my major than winning a game in my sport.
During the years I compete in my sport, completing a college degree is not a goal for me.
I am confident I can be a star performer on my team this year.
My goal is to make it to the professional level or the Olympics in my sport.
I have some doubt about my ability to earn high grades in my courses.
I am confident that I can make it to an elite level in my sport (Professional/Olympics).
I am confident that I can earn a college degree.
I will be able to use the skills I learn in my sport in other areas of my life outside of sports.
I get more satisfaction from winning a game in my sport than from getting an “A” in a course toward my major.
It is not important for me to perform better than other students in my courses.
I am willing to put in the time to be outstanding in my sport.
The content of most of my courses is interesting to me.
The most important reason why I am in school is to earn a degree.
It is not worth the effort to earn excellent grades in my courses.
Within an academia environment, I find it more challenging to face difficult tasks.
For me studies are important to achieve knowledge and skills.
For me, it is important to train seriously to improve my performance.
The achievement of a degree is important to enrich my knowledge.
In sport, I find stimulating those situations requiring high performances and being difficult to perform.
Situations that allow me to test my capacities stimulate me.
Difficult situations bother me.
For me it’s important not to make mistakes.
It’s important for me to obtain a degree because it will help me to find a job.
a
absent in SAMSAQ (Gaston-Gayles, 2005).
absent in SAMSAQ-IT/A (Guidotti and Capranica, 2013b).
b
2013b), was used in this study. To ascertain equivalence in meaning of the SAMSAQ-EU, the back
translation method was used for different national
languages in which the tool was applied (Su &
Parham, 2002).
According to the literature (Fortes, Rodrigues, &
Tchantchane, 2010; Gaston-Gayles, 2005; Guidotti
et al., 2013; Lupo et al., 2012), participants were
required to indicate their level of agreement (i.e.,
from a minimum of 1 – very strongly disagree to a
maximum of 6 – very strongly agree) to each
SAMSAQ-EU item. Assessments took place individually under the supervision of an investigator.
Participants were ensured that there were no right or
wrong answers, and were assured the confidentiality
of the responses. In addition to the 39-item SAMSAQ-EU, participants were also administered
demographic questions (i.e., age, gender, type of
sport and competition level).
Data analysis
To verify the applicability of the three-factor model,
an Exploratory Factor Analysis (EFA; Principal
Component Extraction; Varimax Rotation with
Kaiser’s normalisation) was applied. Coherently to
the literature (Costello & Osborne, 2005), the
following criteria were adopted: (1) the minimum
presence of five items for each factor; (2) if an item
loaded on a single factor, only values ≥0.40 were
taken into account; and (3) if an item loaded on two
factors, a 0.32 threshold of acceptability was set for
both values.
Institut National du
Sport, de l’Expertise
et de la Performance
(INSEP)
Bodies involved
in recruitment
procedures
88
56
31
95%
5%
38%
62%
8%
92%
31
13
18
90%
10%
78%
22%
16%
84%
113
28
85
71%
29%
63%
37%
87%
13%
Competition level
Type of sport
Age
Subjects (n)
Gender (n)
Female
Male
≤ 24 years
> 24 years
Team
Individual
National
International
44
17
27
82%
18%
10%
90%
16%
84%
Observatory of
Sport in
Universities (ODU)
University sport
offices of three
Slovenian Universities (i.e.,
Ljubljana,
Maribor, and Primorska
216
103
113
90%
10%
28%
72%
36%
64%
33
20
13
64%
36%
3%
97%
52%
48%
Talented Athlete
Scholarship
Scheme (TASS)
Database
Personally
in the academic
institution
Dalarna
University
Database
Personally
in the sport
environment
Sport clubs
(n = 85)
Database
Recruitment
modality
Portugal
Italy
France
Variable
Table II. Demographic characteristics and recruitment modalities of the European student-athletes sample
Country
Database
Slovenia
Sweden
United Kingdom
Motivation towards dual career
155
To evaluate the internal consistency of items on
each SAMSAQ-EU subscale, reliability estimates
(Cronbach’s alpha coefficients) were computed,
considering a Cronbach’s alpha coefficient of ≥0.7
acceptable for internal consistency (O’Donoghue,
2012). Items loading on two factors were used in
computing composite scores for both factors
(Gaston-Gayles, 2005).
To verify the accuracy of the factor structure, a
Confirmatory Factor Analysis (CFA; Maximum
Likelihood) was performed, taking into account
several fit indices (Jackson, Gillaspy, & PurcStephenson, 2009): chi-square (χ2), chi-square ratio
(χ2/df), comparative fit index (CFI), goodness of fit
index (GFI), normed fit index (NFI), Tucker–Lewis
index (TLI), Root Mean Square Error of Approximation (RMSEA) and p of close fit (PCLOSE).
Cut-off values for good fit were considered: ≤0.06
for RMSEA with no significant PCLOSE (P > 0.05),
≥0.90 for incremental indices (CFI, NFI and TLI),
≥0.91for GFI, ≥2 for chi-square ratio. According to
the literature (Hu & Bentler, 1999; Netemeyer,
Bearden, & Sharma, 2003), CFI and TLI values
≥0.95 and an RMSEA value ≤0.05 could be
preferred.
Gender (i.e., female vs. male), age (i.e., ≤24 years
vs. >24 years), type of sport (i.e., individual sport vs.
team sport) and competition levels (i.e., national vs.
international) were considered independent variables
to promote a specific scenario of the motivations of
the European student-athletes in countries providing
different educational services for elite athletes. A chisquare test verified unequal sample sizes (P ≤ 0.05)
between groups relatively to the frequency of occurrence of student-athletes’ gender, age, type of sport
and competition level.
To evaluate differences (P ≤ 0.05) between countries with different dual career policies, a multivariate
analysis of variance (MANOVA) was applied considering gender, age, type of sport and competition
level for each factor. Then, separate analyses of
variance (ANOVAs) were performed for each variable and factor to show univariate effects, if any.
When significant differences emerged, Bonferroni’s
post hoc test was applied. Because a large sample
size can lead to significant results for marginal
differences, effect sizes (ESs) were calculated
(Cohen, 1988), considering ≤0.2, 0.6 and 1.2, and
>1.2 trivial, small, moderate and large ES, respectively (Hopkins, 2008).
Statistical analyses were conducted in SPSS (19.0;
SPSS, Inc., Chicago, IL) and AMOSTM 19.0. First,
statistical procedures were applied for the whole
European sample, then separately for the dual career
policy subgroups. Due to difficulties in combining
elite sport and study commitments, the studentathlete population resulted very limited. Therefore,
156
C. Lupo et al.
when subgroups were analysed separately a subject
to item ratio ≥10:1 considered for EFA interpretation (Costello & Osborne, 2005) was not applicable.
Results
Overall, participants were mainly <24 years of age
(85%), and competing in individual sports (63%).
Males were more frequently represented in the State
(59%) and No Structure (60%) groups with respect
to their female counterparts, whereas the opposite
picture emerged for Federation (females = 64%,
males = 36%). Regarding the competition level, a
large proportion of student-athletes competing at
international level was found for State (54%) and
Federation (80%) groups, whereas a balanced distribution occurred for the No Structure counterparts
(national = 52%, international = 48%). Frequency of
occurrence (n) between groups showed no difference
for type of sport only. However, when relative
proportions (%) were considered no difference was
found between groups.
For the whole sample of European student-athletes, the SAMSAQ-EU (explained variance = 35%;
subject to item ratio = 13.4) showed a three-factor
model (SAM = 8 items; AM = 9 items; and CAM =
11 items), with acceptable Cronbach’s alpha coefficients for the three subscales (SAM = 0.76; AM =
0.76; and CAM = 0.77). However, 11 items (i.e., 3,
4, 6, 9, 13, 16, 17, 25, 28, 29 and 37) were removed
because of low threshold of acceptability, and the
model showed insufficient CFA values for the
requested fit indices. Therefore, subgroups analysis
was deemed necessary.
The models (with the related item scores and the
Cronbach’s alpha coefficients) of each subgroup are
reported in Table III. In general, EFA and reliability
estimates met the relative criteria, whereas CFA
indices approached the cut-off criteria for the preferred CFI, TLI and RMSEA only. For the State
subgroup, the SAMSAQ-EU (explained variance =
34%; subject to item ratio = 2.7) showed a threefactor model (SAM = 12 items; AM = 8 items; and
CAM = 5 items), with acceptable Cronbach’s alpha
coefficients for the three subscales (Table III). In
particular, 16 items (i.e., 1, 4, 5, 6, 7, 9, 12, 17, 23,
24, 28, 31, 35, 36, 37 and 38) were removed because
of low threshold of acceptability, and two items
loaded on two factors (i.e., SAM and AM: items
11 and 25). CFA showed a limited fit (GFI = 0.847,
NFI = 0.755, TLI = 0.926, CFI = 0.940, RMSEA =
0.046, PCLOSE = 0.615), with a significant chisquare value (229.302; P = 0.019) and a ratio value
of 1.2 between the hypothesised model and the
sample data. For the Federation subgroup, the
SAMSAQ-EU (explained variance = 38%; subject
to item ratio = 2.2) showed a three-factor
model (SAM = 12 items; AM = 13 items; and
CAM = 5 items), with sufficient Cronbach’s alpha
coefficients for two subscales (Table III). Eleven
items (i.e., 5, 8, 9, 17, 25, 26, 30, 31, 35, 37 and 38)
were removed because of low threshold of acceptability, and two items loaded on two factors (i.e., SAM
and CAM: items 24 and 36). CFA showed a limited
fit (GFI = 0.772, NFI = 0.673, TLI = 0.892, CFI =
0.908, RMSEA = 0.053 and PCLOSE = 0.375),
with a significant chi-square value (429.686; P =
0.001) and the ratio value of 1.24 between the
hypothesised model and the sample data. For the
No Structures subgroup, the SAMSAQ-EU
(explained variance = 35%; subject to item ratio =
8.4) showed a three-factor model (SAM = 11 items;
AM = 9 items; and CAM = 10 items), with
satisfactory Cronbach’s alpha coefficients for the
three subscales (Table III). Sixteen items (i.e., 5, 7,
9, 10, 11, 12, 14, 16, 17, 18, 21, 26, 29, 30, 37 and
39) were removed because of low threshold of
acceptability, and seven items loaded on two factors
(i.e., SAM and AM: items 35 and 36; SAM and
CAM: items 20, 27 and 33; AM and CAM: item
32). Also for this subgroup CFA showed a limited fit
(GFI = 0.908, NFI = 0.846, TLI = 0.902, CFI =
0.925, RMSEA=0.049 and PCLOSE = 0.538), with
a significant chi-square value (373.909; P ≤ 0.001)
and a ratio value of 1.8 between the hypothesised
model and the sample data.
For the dual career subgroups, Table IV shows
mean and standard deviation scores, and effects, for
each factor, and in relation to gender, age, type of
sport, and competition level. MANOVA showed a
main effect only for competition level (P < 0.001),
with univariate effects for SAM (P = 0.001, ES =
0.2–0.4) and CAM (P < 0.001, ES = 0.2–0.8).
Regarding SAM of national competition level, the
post hoc analysis maintained differences (P = 0.046,
ES = 0.4) only between student-athletes of Federation (5.1 ± 0.5) and State (4.5 ± 0.9) subgroups.
Moreover, for international competition level, State
student-athletes showed lower SAM scores (4.8 ±
0.7) with respect to Federation (5.4 ± 0.5, P <
0.001; ES = 0.4) and No Structure (5.1 ± 0.6, P =
0.031; ES = 0.2) counterparts. Concerning CAM of
national competition level, higher values were
observed for State (5.0±0.8) with respect to their
No Structure (3.7 ± 0.8, P < 0.001; ES = 0.2) and
Federation (3.3 ± 0.7, P < 0.001; ES = 0.8)
counterparts. Furthermore, differences between the
three subgroups were maintained for CAM of international competition level (P < 0.05; ES = 0.3–0.7),
with the highest values for State (5.0 ± 0.9),
intermediate for No Structure (4.6 ± 0.8) and the
lowest for Federation (3.5 ± 0.9) student-athletes.
Finally, only national and international studentathletes of No Structure subgroup showed
Motivation towards dual career
157
Table III. Factor loadings for Exploratory Factor Analysis and reliability estimates of the SAMSAQ-EU relatively to the State, Federation,
and No Structure groups
State
Item/tool
1/SAMSAQ
2/SAMSAQ
3/SAMSAQ
4/SAMSAQ
5/SAMSAQ
6/SAMSAQ
7/SAMSAQ
8/SAMSAQ
9/SAMSAQ
10/SAMSAQ
11/SAMSAQ
12/SAMSAQ
13/SAMSAQ
14/SAMSAQ
15/SAMSAQ
16/SAMSAQ
17/SAMSAQ
18/SAMSAQ
19/SAMSAQ
20/SAMSAQ
21/SAMSAQ
22/SAMSAQ
23/SAMSAQ
24/SAMSAQ
25/SAMSAQ
26/SAMSAQ
27/SAMSAQ
28/SAMSAQ
29/SAMSAQ
30/SAMSAQ
31/SAMSAQ-IT/A
32/SAMSAQ-IT/A
33/SAMSAQ-IT/A
34/SAMSAQ-IT/A
35/SAMSAQ-IT/A
36/SAMSAQ-IT/A
37/SAMSAQ-IT/A
38/SAMSAQ-IT/A
39/SAMSAQ-IT/A
Cronbach’s alpha
SAM-EU
AM-EU
Federation
CAM-EU
SAM-EU
AM-EU
No structure
CAM-EU
SAM-EU
0.548
0.544
CAM-EU
0.520
0.660
0.400
AM-EU
0.418
0.561
0.753
0.685
0.634
0.402
0.425
0.577
0.505
0.327
0.635
0.539
−0.571
0.560
0.544
0.559
0.640
0.624
0.575
0.459
0.411
0.658
0.579
0.578
0.599
0.505
−0.444
607
−0.485
0.479
0.694
0.625
0.588
0.550
−0.512
0.785
0.729
0.396
0.508
0.645
0.355
0.658
0.728
0.599
0.535
0.476
0.457
0.591
−0.451
−0.434
0.704
0.743
0.338
0.630
0.593
0.809
0.687
0.657
0.486
0.722
0.504
−0.526
0.533
0.633
0.400
0.438
0.727
0.421
0.401
0.82
0.529
0.66
0.442
0.556
0.517
0.383
0.389
0.610
0.385
0.397
0.506
0.82
0.75
0.650
0.75
0.87
0.78
0.74
0.79
SAM-EU, Student Athletic Motivation; AM-EU, Academic Motivation; CAM-EU, Career Athletic Motivation.
differences for both SAM (P < 0.001, ES = 0.3) and
CAM (P < 0.001, ES = 0.3) scores.
Discussion
This study represents the first approach to investigate the motivation towards dual career in European
student-athletes living in countries with different
sport and education policies. However, when structuring international studies several caveats have to be
considered: (1) local cooperation is crucial for the
recruitment process. In fact, diversification in
national sport organisation could result in different
opportunities to recruit athletes eligible for the study,
and (2) different national sport traditions could
determine several differences among countries in
terms of sport participation (i.e., individual and
team sports) and sport achievement at national and
international competition levels. The present study
presented several limitations due to a low response
(6 out of 25) of countries included in the Aquilina
and Henry (2010) analysis, an unbalanced recruitment of athletes competing at national (prevalence
in the Italian sample) and international (prevalence
in the French, Portuguese, Slovenian and English
samples) competition levels and a different distribution among countries in the proportion of athletes
competing in individual (prevalence in the French,
158
C. Lupo et al.
Table IV. Means, standard deviations, and effects (P ≤ 0.05) between different groups (State, Federation, No Structure) of the SAMSAQEU scores, in relation to Gender, Age (≤ 24 years, > 24 years), Type of Sport (Individual sport, Team sport), and Competition Level
(National, International) of each considered factor
SAM-EU
Gender
Female
4.5
Male
4.8
Age
≤ 24 years
4.6
> 24 years
4.8
Type of sport
Individual
4.8
sport
Team sport
4.4
Competition level
National
4.5
International 4.8
AM-EU
State
Federation
± 0.8
± 0.8
5.3 ± 0.5
5.4 ± 0.5
4.9 ± 0.8
4.9 ± 0.8
3.4 ± 0.7
3.3 ± 0.9
5.0 ± 0.6
5.0 ± 0.6
4.9 ± 0.6
4.7 ± 0.6
5.1 ± 0.8
5.0 ± 0.8
3.5 ± 0.8
3.4 ± 0.9
4.2 ± 0.9
4.0 ± 1.0
± 0.8
± 0.7
5.4 ± 0.5
5.5 ± 0.6
4.9 ± 0.8
5.0 ± 0.5
3.3 ± 0.8
3.6 ± 0.9
5.0 ± 0.6
5.3 ± 0.2
4.7 ± 0.7
4.8 ± 0.5
5.1 ± 0.8
4.7 ± 1.0
3.5 ± 0.8
3.5 ± 0.5
4.1 ± 0.9
3.9 ± 1.0
± 0.8
5.4 ± 0.5
5.0 ± 0.8
3.4 ± 0.8
5.0 ± 0.7
4.8 ± 0.7
5.0 ± 0.9
3.5 ± 0.8
4.3 ± 0.9
± 0.8
5.3 ± 0.5
4.8 ± 0.7
3.1 ± 0.8
5.0 ± 0.5
4.7 ± 0.6
5.2 ± 0.6
3.3 ± 0.8
3.7 ± 0.9
4.6 ± 0.8***
5.1 ± 0.6
3.2 ± 0.8
3.4 ± 0.9
5.0 ± 0.5
5.0 ± 0.6
4.7 ± 0.6
4.8 ± 0.6
5.0 ± 0.8*,** 3.3 ± 0.7
3.7 ± 0.8***
5.0 ± 0.9*,** 3.5 ± 0.9** 4.6 ± 0.8
± 0.9*
5.1 ± 0.5
± 0.7*,** 5.4 ± 0.5
No structure
State
CAM-EU
Federation No structure
State
Federation No structure
*Difference (P ≤ 0.05) with respect to their Federation counterparts; **Difference (P ≤ 0.05) with respect to their No Structure
counterparts; ***Difference (P ≤ 0.05) with respect to their International counterparts.
In particular Student Athletic Motivation (SAM-EU) included 12, 12, and 11 items for State, Federation, and No Structure groups,
respectively; Academic Motivation (AM-EU) included 8, 13, and 9 items for State, Federation, and No Structure groups, respectively; and
Career Athletic Motivation (CAM-EU) included 5, 5, and 10 items for State, Federation, and No Structure groups, respectively.
Slovenian, Swedish, and English samples) and team
sports (prevalence in the Italian and Portuguese
samples). In general, these limitations strongly influenced the validity and reliability of a common model
of the instrument. In particular, low subject to item
ratios emerged for the three SAMSAQ-EU models
(ratio: 4.4 ± 3.4, range: 2.2–8.4), thus affecting EFA
interpretation and increasing the risk of item misclassification and errors in both eigenvalues and
factor loadings (Costello & Osborne, 2005). Furthermore for CFA analyses, the optimal fit thresholds observed only for CFI, TLI and RMSEA could
have influenced the factor model interpretation and
comparability (Jackson et al., 2009). Therefore, it is
strongly recommended that future cross-national
studies include more European student-athletes to
substantiate the psychometric properties of the
instrument. Nonetheless, in analysing the motivations towards dual career of student-athletes from
European countries with heterogeneous dual career
policies (Aquilina & Henry, 2010), this study represents a starting point for initial tentative speculations
and future research in this area, in line with the
recommendations of the EU Guidelines on Dual
careers (European Commission, 2012).
Although each considered educational system
(i.e., State, Federation and No Structure) showed
distinct three-factor models (i.e., SAM, AM and
CAM), significant differences arose in terms of items
included in each factor. These findings substantiate
previous differences with respect to the original
model (Fortes et al., 2010; Guidotti et al., 2013;
Lupo et al., 2012) due to specific policies in
combining education and sport. Despite structural
differences between models, the SAMSAQ-EU
demonstrated to be a useful tool for a preliminary
evaluation of European student-athletes’ dual career
motivation, which could help educational and sports
bodies in providing effective supports and encouragements to student-athletes and in promoting
their personal development (European Commission,
2007a, 2007b, 2011, 2012). In considering the
heterogeneous and limited sample deriving from six
European countries, the present findings highlighted
the need of further research to develop a valid and
reliable instrument for the evaluation and monitoring of the student-athlete’s motivations towards a
dual career in international contexts.
European student-athletes showed high motivations for both sport and education, similarly to
American (Gaston-Gayles, 2005) and United Arab
Emirates student-athletes (Fortes et al., 2010).
Interestingly, only competition level succeeded in
discriminating between subgroups and within the
No Structure subgroup for SAM and CAM subscales. The lack of differences between national and
international athletes supported by State and Federation dual career policies indicates that a social
support allows elite athletes to commit to sport
independently from outstanding athletic achievements. In particular, the highest SAM and AM
scores emerged for student-athletes supported by
their National Federations. This might mirror an
effective capability of sport organisations to negotiate
with educational bodies their admission procedures,
examination schedules and tutoring, which could
Motivation towards dual career
promote academic success of elite athletes (Aquilina
& Henry, 2010; Henry, 2013). This subgroup also
showed the lowest CAM scores, indicating that
transition from sport to labour market might be
perceived as not occurring in a close future. Studentathletes living in countries with dual career policies
based on State-centric regulation–State as sponsor/
facilitator showed the highest motivation towards
their future career, indicating their expectations for
smooth career transitions at the end of the competitive phase of their life. Conversely, student-athletes
competing at national level in countries with a
Laisser Faire approach perceived their athletic commitment and career expectations less motivating.
These findings indicate that athletes involved at
national level might have a weaker athletic identity
(Sturm, Feltz, & Gilson, 2011; YukhymenkoLescroart, 2014), probably foreseeing difficulties in
career transitions when terminating their sport life.
Thus, policies combining education and training (e.
g. France) could represent a valuable model for the
development of dual career policies in other European countries not supporting student-athletes. In
fact, this is a challenge of the European initiatives in
the field of sport and higher education, especially
when considering that the new European Erasmus+
programme 2014–2020 is specifically dedicated to
Education, Training, Youth and Sport.
In considering the reduced opportunities to pursue professional athletic careers (Guidotti & Capranica, 2013a; International Olympic Committee,
2004, 2012; International Working Group on Women and Sport, 2012; Pfister, 2010), female studentathletes were expected to have higher AM and lower
CAM scores (Gaston-Gayles, 2005). Conversely, the
lack of gender differences suggests that the general
development of women’s sport in European countries could minimise this effect, therefore maintaining the relevant necessity to largely examine issues
about the relationship between motivation and student-athletes.
In the present study, no difference emerged for
age and type of sport, probably due to a general
trend towards increasing length in athletic career.
Although only involvement in professional sports
might provide sound financial support for future
years, these findings indicate that student-athletes
might perceive education as important to support
future engagement in professional positions. In fact,
outstanding athletic achievements could be a facilitator for some sport-related careers as sport managers, coaches, physical trainers and sport
commentators (Capranica et al., 2008; Guidotti &
Capranica, 2013a), especially when former athletes
can rely on a solid educational background.
159
Conclusions
Sport is a global phenomenon, also related to local
resonance and cultural practice. Thus, a universal
knowledge about ‘athletes in general’ has to be
considered inappropriate, especially in Europe where
differences in sport systems, societal norms and
cultural traditions exist. Although the SAMSAQEU has demonstrated to be an interesting preliminary tool to investigate European student-athletes’
motivation for a dual career, its high sensitivity to
specific social contexts underlines the need for
further research in this area (European Commission,
2012). This study highlighted the relevance of a
research line on understanding the motivation of
European student-athletes towards academic and
athletic careers. In considering the limited and very
heterogeneous sample included in this study, further
investigation is strongly needed to implement the
SAMSAQ-EU instrument. In fact, according to the
recommendations of the European Guidelines on
Dual careers of Athletes (European Commission,
2012), qualitative and quantitative cross-national
studies are deemed necessary for providing valuable
information to guide multi-sector (i.e., governments,
sport organisations and education bodies) efforts in
managing sport and education for future European
citizens, making it easier for athletes to combine
sports training with study or work.
Acknowledgements
The authors would like to express their gratitude to
the Dual Career Network (European athlete as
student, EAS) Board for the “Special Jury Prize of
the Benght Nybelius Scolarship 2013” recognised
in the 10th Annual EAS Conference (September
19–21, 2013, Trondheim, Norway). In addition, a
special acknowledgement has to be addressed to
Veronique Laseur and Patricia Vandewalle for their
precious support.
References
Amara, M., Aquilina, D., & Henry, I. (2004). Education of young
sportspersons (lot 1). Report Finale. Brussels: Directorate-General
Education and Culture. Retrieved from http://ec.europa.eu/sport/
library/documents/c3/pmp-study-dual-career_en.pdf
Aquilina, D. (2013). A study of the relationship between elite
athletes’ educational development and sporting performance. International Journal of the History of Sport, 30, 374–392.
doi:10.1080/09523367.2013.765723
Aquilina, D., & Henry, I. (2010). Elite athletes and university
education in Europe: A review of policy and practice in higher
education in the European Union Member States. International
Journal of Sport Policy, 1, 25–47. doi:10.1080/1940694100
3634024
Aries, E., McCarthy, D., Salovey, P., & Banaji, M. R. (2004). A
comparison of athletes and non-athletes at highly selective
colleges: Academic performance and personal development.
160
C. Lupo et al.
Research in Higher Education, 45, 577–602. doi:10.1023/B:
RIHE.0000040264.76846.e9
Capranica, L., & Millard-Stafford, M. L. (2011). Youth sport
specialization: How to manage competition and training?
International Journal of Sports Physiology and Performance, 6,
572–579.
Capranica, L., Tessitore, A., D’Artibale, E., Cortis, C., Casella,
R., Camilleri, E., & Pesce, C. (2008). Italian women’s
television coverage and audience during the 2004 Athens
Olympic Games. Research Quarterly for Exercise and Sport, 79
(1), 101–115. doi:10.1080/02701367.2008.10599465
Cohen, J. (1988). Statistical power analysis for the behavioral sciences
(2nd ed.). Mahwah, NJ: Lawrence, Erlbaum.
Conzelmann, A., & Nagel, S. (2003). Professional careers of the
German Olympic athletes. International Review for the Sociology
of Sport, 38, 259–280. doi:10.1177/10126902030383001
Costello, A. B., & Osborne, J. W. (2005). Exploratory factor
analysis: Four recommendations for getting the most from
your analysis. Practical Assessment, Research, and Evaluation, 10,
1–9.
Doupona Topič, M. (2005). Sport, gender and the issues of life.
In Keith D. Gilbert (Ed.), Sexuality, sport and the culture of risk
(pp. 103–118; Sport, Culture & Society, 6). Oxford: Meyer &
Meyer Sport.
European Commission. (2007a). Commission staff document: Action
plan ‘Pierre de Coubertin’, accompanying document to the white
paper on sport. Brussels: Directorate-General Education and
Culture.
European Commission. (2007b). White paper on sport. Brussels:
Directorate-General Education and Culture.
European Commission. (2011). Developing the European dimension
in sport. Brussels: Directorate-General Education and Culture.
European Commission. (2012). Guidelines on dual careers of athletes
recommended policy actions in support of dual careers in highperformance sport. Retrieved from http://ec.europa.eu/sport/
news/20130123-eu-guidelines-dualcareers_en.htm
Fortes, P. C., Rodrigues, G., & Tchantchane, A. (2010). Investigation of academic and athletic motivation on academic
performance among university students. International Journal
of Trade Economics and Finance, 1, 367–372. doi:10.7763/
IJTEF.2010.V1.65
Gaston-Gayles, J. L. (2005). The factor structure and reliability of
the student athletes’ motivation toward sports and academics
questionnaire (SAMSAQ). Journal of College Student Development, 46, 317–327. doi:10.1353/csd.2005.0025
Gatmen, E. J. P. (2012). Academic exploitation: The adverse
impact of college athletics on the educational success of
minority student-athletes. Seattle Journal for Social Justice, 10,
509–583.
Guidotti, F., & Capranica, L. (2013a). Management sportivo
femminile e carriera universitaria nelle scienze motorie: la
condizione attuale, le opinioni delle manager e delle docenti
universitarie e le nuove proposte [Female sport management
and academic career in sport sciences: Present condition,
women sport managers’ and university professors’ opinions
and perspectives]. Rivista Trimestrale di Scienza dell’Amministrazione, 1, 85–104.
Guidotti, F., & Capranica, L. (2013b). Le motivazioni verso sport,
istruzione e carriera sportiva degli studenti-atleti italiani. In A.
M. Pioletti & N. Porro (Eds.), Lo sport degli Europei (pp. 104–
120). Milan: Edizioni Franco Angeli.
Guidotti, F., Minganti, C., Cortis, C., Piacentini, M. F.,
Tessitore, A., & Capranica, L. (2013). Validation of the Italian
version of the student athletes’ motivation toward sport and
academics questionnaire. Sport Sciences for Health, 9(2), 51–58.
doi:10.1007/s11332-013-0145-x
Henry, I. (2013). Athlete development, athlete rights and athlete
welfare: A European union perspective. International Journal of
the History of Sport, 30, 356–373. doi:10.1080/09523367.2013.
765721
Hopkins, W. G. (2008). A scale of magnitudes for effect statistics.
Retrieved from www.sportsci.org/resource/stats/effectmag.htlm
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in
covariance structure analysis: Conventional criteria versus new
alternatives. Structural Equation Modeling, 6(1), 1–55.
doi:10.1080/10705519909540118
International Olympic Committee. (2004). Women and sport
progress report: A review of the IOC policy and activities to promote
women in and through sport. Marrakech: Third World Conference on Women and Sport.
International Olympic Committee. (2012). The Los Angeles
declaration. Retrieved from http://www.olympic.org/Docu
ments/Commissions_PDFfiles/women_and_sport/Los-AngelesDeclaration-2012.pdf
International Working Group on Women and Sport. (2012).
The Sydney scoreboard. Retrieved from http://www.sydneyscore
board.com/
Istituto Nazionale di Statistica-ISTAT. (2007). La pratica sportiva
in Italia. Retrieved from http://www3.istat.it/salastampa/comu
nicati/non_calendario/20070620_00
Jackson, D. L., Gillaspy, J. A., Jr, & Purc-Stephenson, R. (2009).
Reporting practices in confirmatory factor analysis: An overview and some recommendations. Psychological Methods, 14(1),
6–23. doi:10.1037/a0014694
Lupo, C., Tessitore, A., Capranica, L., Rauter, S., & Doupona
Topic, M. (2012). Motivation for a dual career: Italian and
Slovenian student-athletes. Kinesiologia Slovenica, 18, 47–56.
Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling
procedures: Issues and applications. Thousand Oaks, CA: Sage.
O’Donoghue, P. (2012). Statistics for sport and exercise studies: An
introduction. Abingdon: Routledge.
Pfister, G. (2010). Women in sport – Gender relations and future
perspectives. Sport in Society, 13, 234–248. doi:10.1080/17430
430903522954
Simons, H. D., Van Rheenen, D., & Covington, M. V. (1999).
Academic motivation and the student athlete. Journal of College
Student Development, 40, 151–162.
Stambulova, N., & Alfermann, D. (2009). Putting culture into
context: Cultural and cross-cultural perspectives in career
development and transition research and practice. International Journal of Sport and Exercise Psychology, 7, 292–308.
doi:10.1080/1612197X.2009.9671911
Stambulova, N., Stephan, Y., & Japhag, U. (2007). Athletic
retirement: A crossnational comparison of elite French and
Swedish athletes. Psychology of Sport and Exercise, 8, 101–118.
doi:10.1016/j.psychsport.2006.05.002
Stambulova, N., Alfermann, D., Statler, T., & Côté, J. (2009).
ISSP position stand: Career development and transitions of
athletes. International Journal of Sport and Exercise Psychology, 7,
395–412. doi:10.1080/1612197X.2009.9671916
Sturm, J. E., Feltz, D. L., & Gilson, T. A. (2011). A comparison
of athlete and student identity for Division I and Division III
athletes. Journal of Sport Behavior, 34, 295–306.
Su, C.-T., & Parham, L. D. (2002). Case report – Generating a
valid questionnaire translation for cross-cultural use. American
Journal of Occupational Therapy, 56, 581–585. doi:10.5014/
ajot.56.5.581
Wylleman, P., & Reints, A. (2010). A lifespan perspective on the
career of talented and elite athletes: perspectives on highintensity sports. Scandinavian Journal of Medicine and Science in
Sports, 20 (Suppl. 2), 88–94. doi:10.1111/j.1600-0838.2010.
01194.x
Yukhymenko-Lescroart, M. A. (2014). Students and athletes?
Development of the academic and athletic identity scale
(AAIS). Sport, Exercise, and Performance Psychology, 3(2), 89–
101. doi:10.1037/spy0000009.
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