YOUNG ATHLETES' MOTIVATIONAL PROFILES
1Faculty of Sports Sciences, University of Murcia, 2Faculty of Social
and Juridical Sciences, Miguel Hernández University of Elche, 3Faculty
of Humanities and Educational Sciences, University of Almería, Spain
05 May 2006
Journal of Sports Science and Medicine (2007) 6, 172 - 179
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aim of this study was to examine the relationship between motivational
characteristics and dispositional flow. In order to accomplish this
goal, motivational profiles emerging from key constructs within Achievement
Goal Theory and Self-Determination Theory were related to the dispositional
flow measures. A sample of 413 young athletes (Age range 12 to 16
years) completed the PMCSQ-2, POSQ, SMS and DFS measures. Cluster
analysis results revealed three profiles: a "self-determined
profile" characterised by higher scores on the task-involving
climate perception and on the task orientation; a "non-self-determined
profile", characterised by higher scores on ego-involving climate
perception and ego orientation; and a "low self-determined and
low non-self-determined profile" which had the lowest dispositional
flow. No meaningful differences were found between the "self-determined
profile" and the "non-self-determined profile" in dispositional
flow. The "self-determined profile" was more commonly associated
with females, athletes practising individual sports and those training
more than three days a week. The "non-self-determined profile"
was more customary of males and athletes practising team sports as
well as those training just two or three days a week.
WORDS: Self-determination, motivational climate, goal orientation,
Motivation has been a very important object of study among sports
and exercise psychologists. Achievement Goal Theory (Nicholls, 1989)
and Self-Determination Theory (Deci and Ryan, 1985;
Ryan and Deci, 2000)
are the most prominent current theories of motivation in the sport
psychology literature and each has had considerable success in explaining
motivational patterns in sport settings.
According to Achievement Goal Theory, individuals can define success
according to different criteria that reflects two different perspectives.
The first achievement goal perspective is self- referenced and reflects
a task goal orientation in which individuals consider themselves
to be successful when they have demonstrated personal improvement
and have displayed effort. The second achievement goal perspective
reflects a social comparison perspective in which success is considered
to be realized when individuals demonstrate superior skills relative
to others. Such a perspective is known as an ego orientation. At
around the age of 12 years, these goal orientations tend to become
consolidated in the individual's personality (Nicholls, 1989).
Coaches can be important influences in shaping the achievement goal
orientations of athletes. Their influence can be reflected in the
manner in which coaches respond during training sessions and competition
in relation to the implicit and explicit responses that they provide
in relation to the coach's own definition of success. A coach can
either prioritise personal improvement and effort in task execution,
which would reflect a task-involving climate or give more importance
to winning and the demonstration of a greater ability than others,
which be would reflective of an ego-involving climate.
Self-Determination Theory establishes different motivational types
along a continuum. Consequently, individuals can be unmotivated
(amotivation) or can range in self- determination from less self-determined
to more self-determined. Amotivation refers to a lack of intention
or the absence of motivation and therefore the involvement is likely
to be disorganised and accompanied by frustration, fear or depressed
feelings (i.e. "I don't really think my place is in sport").
On the self-determination continuum there are various points on
the continuum that distinguish between individuals in their levels
of self-determination. External regulation refers to of the motive
to participate to attain external incentives (i.e. "I do sports
for the prestige of being an athlete"). Introjected regulation
reflects motivation dictated by the desire to avoid culpability
and to minimize anxiety feelings (i.e. "I must do sports to
feel good about myself"). In the case of identified regulation,
the activity is more important for the individual although s/he
doesn't carry out this activity because of its inherent pleasure,
but as a means of achieving a goal, such as improving their health.
Integrated regulation consists of assimilating and organising several
identified regulations, evaluating them and classifying them in
relation to other values and needs. A clear example of this would
be an individual committed to the practice of physical activity
because this involvement reflects his/her orientation toward a healthy
lifestyle. This type of regulation is more often encountered among
adults rather than children, as younger populations may be too young
to have experienced a sense of integration (Vallerand and Rousseau,
Intrinsic motivation involves participating in an activity for the
pleasure and the enjoyment they get from it. Intrinsic motivation
describes the inclination towards consolidation, mastery, spontaneous
interest and exploration. This inclination is fundamental for social
and cognitive development and represents the main origin of pleasure
and vitality all throughout life (Ryan, 1995).
Pelletier et al., 1995
proposed three types of intrinsic motivation, called "intrinsic
motivation to know" (practising a sport for the pleasure of
knowing more about such sport), "intrinsic motivation to accomplish"
(practising a sport for the pleasure of improving skills) and "intrinsic
motivation to experience stimulation" (practising a sport for
the pleasure of living stimulating experiences).
The majority of investigations carried out have examined different
motivational types including their antecedents and their consequences
in an isolated way (Ntoumanis, 2002).
Findings have tended to indicate that the most self-determined motivational
types (i.e. intrinsic motivation and identified regulation) are
connected with the most positive consequences (Vallerand and Rousseau,
in relation to various outcomes such as affect (pleasure, enjoyment,
satisfaction, interest, positive emotions, better coping abilities
and flow), cognitions (concentration) and behavioural outcomes (effort,
intentions to continue exercising, sportspersonship and actual performance).
In this sense, Vallerand (1997;
proposed an analysis of how the motivation types established by
the Self-Determination Theory are combined to form motivational
profiles. Vallerand (1997;
suggested studying how the different motivation types occur jointly
in individuals by identifying groups of individuals with similar
scores and further examining the different social factors which
determine those profiles, as well as the outcomes that accompany
each profile. This approach allows identification of profiles related
to the most negative consequences, with the aim of developing strategies
to increase the strength and quality of such individuals' motivation
towards sports (Vlachopoulos et al., 2000).
Fox et al., 1994
suggested using the motivational profile approach to study goal
orientations and their consequences. Research shows that individuals
with high task and ego orientations, which is customary among elite
athletes (Hardy et al., 1996),
as well as individuals with high task orientations and low ego orientations
tend to show higher levels of adaptive motivational patterns as
reflected by hard work, intrinsic interest, enjoyment and higher
persistence in practice despite getting not necessarily better results
than those with a low task orientation (Dorobantu and Biddle, 1997;
Goudas et al., 1994;
Roberts et al., 1996;
Standage and Treasure, 2002).
Therefore, identifying subgroups of young people showing different
profiles based on these contemporary motivational rates could be
quite useful in increasing the effectiveness of interventions and
in realizing greater participation (Wang and Biddle, 2001).
Some investigators have already undertaken the study of motivational
profiles for individuals in different contexts, such as the research
conducted by Vlachopoulos et al., 2000 carried out with adult athletes and Wang and Biddle's
(2001) research with adolescent students with reference both
to Physical Education lessons and sport. Ntoumanis, 2002 examined motivational profiles in Physical Education lessons
with students between the ages of 14 and 16 years old. More recently,
Matsumoto and Takenaka, 2004 studied adults practising and not practising physical
activity and McNeill and Wang, 2005 examined motivational profiles in young people between
the ages of 14 and 15 years who practised or did not practise sport.
Each of these studies were grounded in Self-Determination Theory
and some of them also used Achievement Goal Theory, in both cases
trying to establish a relation between the different profiles and
specific social factors (such as motivational climates) and concrete
consequences, such as interest, effort, satisfaction, enjoyment,
boredom, level of participation in the physical activity and self-worth.
The combined results from these studies indicates that individuals
who have profiles with high scores on self-determined motivation
tend to view their involvement as occurring within a task-involving
climate and generally realize the most positive consequences.
In the present study, the motivational profile approach was used
in which the primary constructs from Self-Determination Theory and
Achievement Goal Theory were related to dispositional flow in a
sample of adolescent athletes. Dispositional flow reflects the individual's
tendency to experience an optimal psychological, or flow state.
According to Csikszentmihalyi, 1988, there are individual differences in the capacity to experience
this state and, as a result, some individuals are more prone to
experience this state and thus have what is known as an autotelic
personality. Jackson and Csikszentmihalyi, 1999 consider flow to be a conscious state that is experienced
in a wide range of contexts and which has universal characteristics
where the individual is totally absorbed by what he or she is doing.
Therefore, the flow state would synonymous with heightened concentration
and it would also be a harmonious experience where mind and body
work together, leaving the individual with the feeling that something
special had happened. The flow state is also inherently enjoyable.
It could be argued that flow raises the quality of the experience
from ordinary to optimal and it is at this point when the individual
feels truly active and connected with what he or she is doing. Given
the very positive features of this experience, it is therefore highly
interesting to analyse the factors that lead to the athlete's greater
disposition to experience flow and, in this way, design training
environments fostering the accomplishment of optimal experiences
so as to achieve higher adherence to practice and better execution.
Recent investigations indicate that many young athletes tend to
give up sport practice during adolescence (Wang et al., 2007). It is therefore essential to assess the factors related
to sports motivation at this age so as to better understand the
variables underlying sports commitment in order to gain the benefits
obtained from sport at physical (i.e. physical development), psychological
(i.e. higher concentration and less anxiety) and social levels (i.e.
sport as a medium of social relationships). Moreover, the attitudes
developed towards sport practice at this stage will have a strong
influence at the adult stage (Malina, 2001). No published works have been found regarding motivational
profiles in adolescent athletes. The only known work that uses this
approach with athletes, albeit with adult, is that by Vlachopoulos
et al., 2000.
Vlachopoulos et al., 2000 built on work from Vallerand and Fortier, 1998 that examined possible relationships between self-determined
and non-self-determined motivation types. Vlachopoulos et al., 2000 established four theoretical motivational profiles: the
traditional self-determined profile, represented by individuals
with high levels of self-determined motivation and low non-self-determined
motivation; a second profile in which individuals have high scores
both in self-determined and in non-self-determined motivation; a
third profile in which individuals have high scores only in non-self-determined
types of motivation; and a fourth profile in which individuals have
low scores in both motivation types. In their investigation only
the first two profiles were present because the other two are more
associated with sport abandonment which was not representative of
In the present study, it was hypothesized that a self-determined
profile would be related to a high task orientation, a task-involving
climate perception and dispositional flow. This study is unique
in that it utilized a motivational profile approach with adolescents,
which is a particularly important developmental phase in relation
to motivation whereas most previous research has utilised adult
athletes as their sample.
The sample for this study was comprised of 413 athletes (322 boys
and 91 girls), from 28 sports schools participating in various levels
of competition in the Region of Murcia (Spain). The participants
ranged in age from 12 to 16 years old (M = 13.74, SD = 1.34) and
72.2% of the sport participants practised their sport between 2
and 3 days a week whereas 27.8% practised more than 3 days a week.
The participants engaged in both individual sports (n = 206) and
team sports (n = 207).
Perceived Motivational Climate in Sport Questionnaire-2 (PMCSQ-2):
We used the Spanish version (Balaguer et al., 1997) of the Perceived Motivational Climate in Sport Questionnaire-2
(Newton and Duda, 1993; Newton et al., 2000), which has two factors: ego-involving motivational
climate perception and task-involving motivational climate perception.
The respondents respond to the stem "During the training session
for my team or training group…". This measure uses a Likert
scale ranging from 0 (total disagreement) to 10 (total agreement)
and is made up of 29 items: 14 of which measure the ego-involving
motivational climate perception (i.e. "The coach thinks that
only the best ones make it possible for the group to succeed")
and the other 15 items measure the task-involving motivational climate
perception (i.e. "Effort is rewarded"). The questionnaire
demonstrates good internal consistency with alpha values of .85
for the task climate and of .91 for the ego climate subscales.
of Success Questionnaire (POSQ): We used the Spanish version
(Cervelló et al., 1999) of the Perception of Success Questionnaire (Roberts
and Balagué, 1991; Roberts et al., 1998) for measuring the goal orientations of young athletes.
The questionnaire has 12 items, 6 of which assess the athletes'
task orientation (i.e. "I feel most successful when I practise
at my maximal capacity"). The other 6 items assess the athletes'
ego orientation (i.e. "I feel most successful when I am the
best"). The questionnaire uses a Likert scale ranging from
0 (total disagreement) to 10 (total agreement). This questionnaire
demonstrated good internal reliability in the present study with
Cronbach alpha values of .84 for the task subscale and .91 for the
Motivation Scale (SMS): We used the Spanish language translation
(Núñez et al., 2006) of the original version of the Sport Motivation Scale
developed by Brière et al., 1995
and Pelletier et al., 1995.
This scale assesses the different motivational types identified
by Self-Determination Theory: amotivation, external regulation,
introjected regulation, identified regulation, intrinsic motivation
to know, intrinsic motivation to experience stimulation and intrinsic
motivation to accomplish. This scale is comprised of 4 items for
each factor and so it has 28 total items with the stem question
of "I participate and try hard when practising my sport…".
The measure uses a Likert scale format with possible responses ranging
from 0 (total disagreement) to 10 (total agreement). Alpha values
of .74 for the intrinsic motivation to know, .75 for the intrinsic
motivation to experience stimulation, .74 for the intrinsic motivation
to accomplish, .70 for identified regulation, .64 for introjected
regulation, .67 for external regulation and .74 for amotivation
were found in this study.
Two subscales (introjected regulation and external regulation) had
an internal reliability value inferior to the recommended .70 (Nunnally,
Due to the small number of items which comprise the subscales, the
internal validity observed can be considered marginally acceptable
(Hair et al., 1998;
Nunnally and Bernstein, 1994).
Moreover, the introjected regulation factor has shown low alpha
values in previous studies (McNeill and Wang, 2005;
Wang and Biddle, 2001).
Flow Scale (DFS): We used the Spanish version (García Calvo
et al., 2005) of the Dispositional Flow Scale (Jackson et al., 1998) for measuring the variable of dispositional flow. The
questionnaire has 36 items that were developed to measure the disposition
of athletes to experience the flow state. This measure also uses
a Likert scale format with possible answers ranging from 0 (total
disagreement) to 10 (total agreement). The questionnaire had a Cronbach
alpha level of .91 for the overall scale in the present study.
We contacted the primary administrators and coaches at the selected
sports schools and informed them of our objectives while seeking
their cooperation and involvement. Upon receiving their support
we proceeded with the data collection. The primary researcher was
present during data collection to explain the purposes of our study
and to solve any potential problems. Participants required approximately
20 minutes to complete the questionnaires. All participation was
voluntary and corresponded to all procedures for the protection
of human participants.
Our data analysis proceeded in a specific way. First, we calculated
the descriptive statistics, the means, the standard deviations and
the correlation coefficients among the different variables. Secondly,
we carried out a cluster
analysis to classify the athletes into different
motivational profiles according to the scores obtained on the measures.
Thirdly, we examined whether there was any important difference
among profiles and examined potential group differences through
a MANOVA. Finally, we completed the examination with a residual
analysis to examine potential differences among groups depending
on gender, weekly practice days and sport type practised among the
Descriptive statistics and correlational analysis
Descriptive statistics were generated for the sample. Table
1 reveals that the athletes had stronger task climate perceptions
(M = 7.78) than ego climate perceptions (M = 4.32), as well as higher
scores on task orientation (M = 8.67) than on ego orientation (M
= 6.72). Furthermore, they had higher scores on intrinsic motivation
to know (M = 7.95), in intrinsic motivation to experience stimulation
(M = 7.78), in intrinsic motivation to accomplish (M = 8.05), in
identified regulation (M = 7.32) and in introjected regulation (M
= 7.57), than they did on external regulation (M = 6.27) and in
amotivation (M = 3.43). The mean score for dispositional flow was
It can also be observed that dispositional flow was positively and
significantly related with numerous variables including perception
of an ego-involving climate (r = 0.15, p < 0.01), the perception
of a task-involving climate (r = 0.43, p < 0.01), ego orientation
(r = 0.26, p < 0.01), task orientation (r = 0.38, p < 0.01),
intrinsic motivation to know (r = 0.44, p < 0.01), intrinsic
motivation to experience stimulation (r = 0.48, p < 0.01), intrinsic
motivation to accomplish (r = 0.44, p < 0.01), identified regulation
(r = 0.40, p < 0.01), introjected regulation (r = 0.36, p <
0.01) and external regulation (r = 0.32, p < 0.01). There were
no significant relationships involving amotivation.
We used a hierarchical cluster analysis to classify the athletes
into different profiles depending on the scores obtained in motivational
climates perceptions, goal orientations, sports motivation and the
dispositional flow. At each step of the algorithm, there was only
one object changing groups and groups were nested using the Ward
method which tends to form compact, same-size and same-shape clusters.
The decision to choose this method was based on the intent to minimise
the differences within the clusters and to avoid problems with forming
long, snake-like chains found with other methods (Hair et al., 1998). The cluster analysis was carried out with 12 variables,
previously converted into Z scores following the standard procedure
for this type of analysis.
As a way of determining the number of groups that would constitute
the group classifications it is useful to identify the used method's iterations. The dendogram
was used to identify the profiles and a solution of three clusters
was obtained for this sample of young athletes. It can be observed
that the greatest leaps occurred when the algorithm changed from
3 to 2, 2 to 1 and 1 to 0 groups. The Mojena criterion applied with
k = 2.5 offers a cut-off distance of 2.83 and selects the number
of groups to be 3. For this reason we take 3 as the number of groups.
In Table 2, the means, standard
deviations and Z scores of the variables in each cluster can be
observed. Differences in Z scores of 0.50 or greater were considered
higher, while differences from 0.25 to 0.49 were considered moderated
and inferior to 0.25 as lower, as a result we established different
groups with higher, moderated or lower punctuations compared with
other groups (Wang and Biddle, 2001).
Figure 1 shows the motivational
profiles for the three-cluster solution. The first profile was labelled
the "self-determined profile" and was comprised of 221
athletes (53.5% of the sample) and these individuals showed high
scores on intrinsic motivation, task orientation and task-involving
climate perception; moderate scores on identified regulation, introjected
regulation, external regulation, ego orientation, ego-involving
climate perception and dispositional flow and low scores in amotivation.
The second profile (n = 57; 13.8% of the sample) was labelled as
the "low self-determined and low non-self-determined profile"
and showed low scores on intrinsic motivation, identified regulation,
introjected regulation, external regulation, amotivation, ego orientation,
task orientation, ego climate perception, task climate perception
and the dispositional flow. The final subgroup was labelled the
"non-self-determined profile" and was comprised of 135
athletes (32.7% of the sample). This group had moderate scores on
intrinsic motivation, identified regulation, introjected regulation,
task orientation, task-involving climate perception and dispositional
flow as well as high scores in external regulation, amotivation,
ego orientation and ego climate perception.
Following these results, a MANOVA was conducted to find any differences
on the outcome variables in relation to the clusters. The results
revealed significant differences, Wilk's Λ = .181, F (24,798)
= 44.89, p < 0.001 among the groups. The subsequent ANOVAs pointed
out the existence of significant differences among the three clusters
on all variables (p < 0.001). Tukey's HSD revealed significant
differences among the three groups, except in identified regulation,
introjected regulation and the dispositional flow between cluster
1 and 3, and amotivation between cluster 1 and 2.
Gender, practice days and sport type differences
in cluster composition
A MANOVA was carried out to analyse the differences according to
gender, weekly practice days and sport type (individual or team)
among the motivational profiles and revealed significant differences
(Wilk's Λ = .936, F (6, 816) = 4.58, p < 0.001). The subsequent
ANOVAs showed significant differences for gender (F (2, 410) = 7.17,
p < 0.01), practice days (F (2, 410) = 4.53, p < 0.02) and
sport type (F (2, 410) = 8.60, p < 0.001). In Table
3 the composition of individuals in every cluster can be observed.
Concerning gender, cluster 1 is associated negatively with 72.4%
of men and positively with 27.6% of women, while cluster 3 is associated
positively with 88.9% of men and negatively with 11.1% of women.
In relation to the weekly practice days, it can be observed that
cluster 1 is connected negatively with 66.1% of athletes who train
2 or 3 days a week and positively with 33.9 % who practise more
than 3 days a week, while cluster 3 is connected positively with
80.0% who train 2 or 3 days a week and negatively with 20.0% who
practise sport more than 3 days a week. Finally, concerning
the sport type, cluster 1 is connected positively with 57.5% of
athletes practising individual sports and negatively with 42.5%
of athletes practising team sports, while cluster 3 is connected
negatively with 35.6% of athletes practising individual sports and
positively with 64.4% practising team sports.
In this work we have tried to identify different
motivational profiles in adolescent athletes, starting with the
Achievement Goal Theory and the Self-Determined Theory and have
related these profiles to the disposition to experience the flow
state or optimal psychological state. Analysing the different motivational
variables as a whole, by conforming profiles, provides more information
and allows the planning of intervention strategies to promote sports
motivation in those groups where it is most needed.
The cluster analysis revealed the presence of three motivational
profiles: a "self- determined profile", a "non-self-determined
profile" and a "low self-determined and low non-self-determined
profile". These results are similar to the four theoretical
profiles established by Vlachopoulos et al., 2000,
although in this study the profile that they identified with high
scores both in self-determined motivation and in non-self-determined
motivation has not been found. Vlachopoulos et al., 2000
did not find the presence of profiles that would be anticipated
to be the precursor to sport dropout such as the "non-self-determined
profile" and "low self-determined and low non-self-determined
profile", but it could be expected that they would be present
in adolescence, since adolescence is a period where participation
in sports progressively decreases.
The "self-determined profile" was characterised by high
scores on intrinsic motivation, moderate scores on identified regulation,
introjected regulation and external regulation, and low scores on
amotivation. Furthermore, this profile reveals high task orientation
and task-involving climate perceptions, as well as moderate ego
orientation and ego-involving climate perceptions. The "non-self-determined
profile" showed moderate scores on intrinsic motivation, identified
regulation and introjected regulation and high scores on external
regulation and amotivation. This profile was also characterised
by high ego orientation and an ego- involving climate perception,
as well as moderate task orientation and task-involving climate
perception. Both profiles revealed a moderate dispositional flow
tendency, with no significant differences between the profiles.
Finally, the "low self-determined and low non-self- determined
profile" showed low scores on all variables of the study.
These results lend support to previous work in the field of physical
activity and sport that have examined task- involving climate perceptions
Ntoumanis and Biddle, 1999;
Parish and Treasure, 2003)
and task orientations (Standage and Treasure, 2002;
Wang and Biddle, 2001)
and found these variables to be positively related to self-determined
motivation. An ego-involving climate perception (Ntoumanis, 2002;
Ntoumanis and Biddle, 1999)
and an ego orientation (Georgiadis et al., 2001)
have been found in previous research to be associated with the less
self-determined forms of motivation. These findings suggest that
during their training periods, coaches should develop climates that
promote hard work, effort and progress more than social comparison
to enhance self- determination and positive affective, cognitive
and behavioural consequences for young athletes (Vallerand and Rousseau,
Although we did not find significant differences between the "self-determined
profile" and the "non-self-determined profile" in
the tendency toward dispositional flow, previous research indicates
that self-determination is positively associated with flow (Jackson
et al., 1998;
Kowal and Fortier, 1999;
As a conclusion, it can be stated that if coaches promoted self-determined
motivational profiles among young athletes by transmitting task-involving
climates and also by using different strategies to foster feelings
of competence, autonomy and relatedness that they would take an
important step forward in improving young athletes' desires to practise
sport (Vallerand and Rousseau, 2001).
As expected, the highest percentage of athletes was found within
the "self-determined profile" (53.5%) and thus this group
is characterised by a self-regulated participation that should result
in more positive consequences. Individuals within the "non-self-determined
profile" group (32.7%) are seriously threatened by amotivation
and they could be affected by negative consequences in the short
term. Moreover, the "low self-determined and low non-self-determined
profile" reveals the lowest percentage of the sample (13.8%),
which is a positive piece of information because this profile is
the least desirable. On the one hand, it is worth mentioning that
the "self-determined profile" reveals a positive association
with females, athletes practising individual sports and those training
more than three days a week. On the other hand, the "non-self-determined
profile" is associated with males and athletes practising team
sports and those training two or three days a week.
Although a large proportion of the athletes were found to have a
self-determined profile, almost the half of the sample has less
desirable profiles that should be addressed by coaches. As indicated
previously, the coach must give priority to the display of effort
and not solely to the results. In this way, s/he will promote a
cooperative learning environment because s/he will treat all the
members of the group in a similar and beneficial way. Identifying
motivational profiles allows us to know to which type of individuals
an intervention should be targeted. Our results show that males,
team sport participants and athletes who train fewer days a week
should receive special attention because they tend to experience
less self-determination. It would be interesting to examine whether
these findings are generalizable to different samples of athletes,
because it will allow us to give information to coaches about the
individuals who would be most inclined to drop out of sport.
Despite the fact that the results of the study show differences
in the variables of the groups analysed, the size of these differences
is moderate. This finding could be due to the size of the sample
more than to the size of the effect. Differences found shall be
verified in different populations in future studies.
Future investigations should be focused on the analysis of motivational
profiles, in relation to a greater variety of affective, cognitive
and behavioural consequences as this study only examined relationships
between profiles and dispositional flow. It would also be appropriate
to use longitudinal studies to analyse the motivational profiles
and in this way being able to find out which of them lead to greater
persistence in sports practice and which profiles are associated
with premature abandonment.
|In conclusion, this study has tried to examine
the effects of different motivational variables as a whole through
different profiles in an adolescent athlete sample. We have identified
a "self-determined profile", a "non-self-determined
profile" and a "low self-determined and low non-self-determined
profile". The results provide information necessary to work on
the least desirable profiles through the transmission of task-involving
"self-determined profile" was characterized by high
task orientation, high task-involving climate perception and was
more commonly associated with females, athletes practising individual
sports and those training more than three days a week.
"non-self-determined profile" was characterized by high
ego orientation, high ego-involving climate perception and was
more customary of males and athletes practising team sports as
well as those training two or three days a week.
profiles revealed a moderate tendency toward dispositional flow,
with no significant differences between the two profiles.
"low self-determined and low non-self-determined profile"
had low scores on all of the variables in the study.
Antonio Moreno MURCIA
Employment: Full professor. Faculty of Sports Sciences,
University of Murcia, Spain.
Research interests: Sports motivation, aquatic activities.
Employment: Full professor. Faculty of Social and Juridical
Sciences. Miguel Hernández University of Elche, Spain.
Research interests: Sports motivation.
Employment: Predoctoral grant holder. Faculty of Humanities
and Educational Sciences, University of Almería, Spain.
Research interests: Sports motivation.