According to Iso-Ahola (1999) motivation represents the forces that
initiate, direct and sustain behavior. Because motivation influences
persistence, learning, and performance (Duda, 1989; Martens &
Webber, 2002; Vallerand, Deci, & Ryan, 1987); further understanding
and examining motivation within sport is warranted. A theoretical
approach that has greatly influenced the study of motivation is Deci and
Ryan's (1985, 1991) self-determination and cognitive evaluation
theory. Cognitive evaluation theory, a subtheory under
self-determination theory, posits that behavior can be intrinsically
motivated, extrinsically motivated or amotivated. Intrinsic motivation
(IM) refers to engaging in activity for its own sake (Deci & Ryan,
1985). Pleasure and satisfaction are derived from the activity and a
person will perform the activity in the absence of material or external
rewards or incentives. Conversely, extrinsic motivation (EM) refers to
behaviors that are engaged in as a means to an end and not for their own
sake (Deci, 1975). Lastly, amotivation, describes behaviors when there
is a lack of motivation and the behavior is done for neither intrinsic
nor extrinsic reasons (Deci & Ryan, 1985).
Closely associated with sport motivation is the area of achievement
or competitive orientations. In general, research reveals two basic
achievement or competitive orientations: a mastery or task-orientation
and an outcome-orientation (Ames, 1992; Duda, 1989; Duda, Chi, Newton,
Walling, & Catley, 1995). The mastery or task orientation is usually
associated with intrinsic motivation and encourages participation and
achievement (Gill, Williams, Dowd, Beaudoin, & Martin, 1996).
Conversely, the outcome-orientation is usually associated with being
extrinsically motivated; the focus is the end result of a competition.
Relative to sport motivation, sports participants predominantlyseek to learn skills, be physically active, have fun and enjoy activity(Gill et al., 1996). These would be considered intrinsically-relatedmotives. Extrinsically-related motives such as gaining rewards andrecognition are cited less often (Gill et al., 1996). Sport-specificinventories exist for the measurement of competitive achievementorientation and motivation.
Despite considerable empirical work related to sport motivation and
competitive orientations, research has been primarily limited to
children and young adults (e.g., college athletes). Knowledge regarding
competitive orientations and sport motivation among professional
athletes is limited. To our knowledge, only one other study has examined
competitive orientations of professional athletes (Wartenburg &
McCutcheon, 199 cool . Wartenburg and McCutcheon (199 cool found that male
minor league hockey players were higher in competitiveness, win, and
goal orientation compared to a cohort of fans. Furthermore, research
with professional women's sports is limited.
A professional women's sport that has experienced resurgence
is football. Women's football teams and a league (Women's
Professional Football League) formally appeared in the 1960's and
experienced limited success. In 1974, the National Women's Football
League consisting of seven teams evolved. Through the 1970's the
league experienced growth and expansion but ultimately folded in 1982
due to financial constraints associated with travel and operational
costs. The regeneration of women's professional football began in
1999 with the Women's Professional Football League (WPFL).
Currently there 16 teams in the WPFL, (7 southwest, 6 Atlantic coast,
and 3 midwest teams). Two additional leagues, the Independent
Women's Football League (IWFL) and National Women's Football
Association (NWFA) commenced play in 2000. During the 2005 season, the
IWFL competition consisted of 24 teams (10 Pacific coast, 3 midwest, 8
Atlantic coast, and 3 central southern teams) and the NWFA witnessed 35
teams competing during the 2005 season (20 Northern Division and 15
Southern Division teams). Women's professional football has
received limited media coverage (e.g., television, magazines, radio.
Currently, there are not any women receiving salaries for playing
professional football. Players represent a diverse group of participants
and include former high school athletes, women from flag football
leagues, and former Division I, II, and III athletes that participated
in a wide range of sports (Women's Professional Football League,
2005). Despite the resurgence and growth of women's professional
football, little is known about factors influencing participation in
women's football (e.g., psychological, sociological).
The primary aim of this exploratory study is to describe andexamine relationships among competitive orientations, sport motivation,and age of professional women football players. Participation onformal/structured contact football teams is a relatively new opportunityfor women athletes. To date research has not examined competitiveorientations and motives of women football players. A secondary aim isto examine differences in competitive orientation and sport motivationbetween younger and older players. Because the study is exploratory,specific hypotheses were not tested.
A final aim of the project is to examine to the feasibility and
utility of conducting sport and exercise psychology research through the
Internet. The Internet is providing new opportunities for conducting
psychological research, data collection, and disseminating results
(Kraut, Olson, Banaji, Bruckman, Cohen, & Couper, 2004).
Method
Participants
The overall sample consisted of 118 women professional football
players, representing women from 25 teams and 16 states. Players
represented teams from the National Women's Football Association
(NWFA), Women's Professional Football League (WPFL), and
Independent Women's Football League (IWFL). Participants ranged in
age from 18 to 45 (M = 31.11, SD = 6.09 years). Due to the method of
data collection, Internet survey, limited demographic information was
obtained from the participants (i.e., age, education, previous sport
experience). Relative to educational status, 21% of the participants
completed high school, 44.5% had a college degree, 18.5% had a graduate
degree and 6.0% report that they completed a doctorate degree. Ninety
percent of respondents (N = 107) reported that they had participated in
high school sports. Fifty-five percent (N = 65) reported that they
participated in a sport in college. All measures and procedures related
to the study were approved by the University's Institutional Review
Board for the Protection of Human Subjects.
Measures
Sport Orientation Questionnaire (SOQ). The SOQ is a 25-item scale
consisting of three subscales that assess competitiveness, win
orientation, and goal orientation (Gill & Deeter, 198 cool . The
competitiveness subscale measures the desire to enter and seek success
in sports competition. The win orientation subscale measures one's
desire to win and beat others. The goal orientation subscale measures
the desire to reach personal goals set relative to mastery of a given
sport or skill.
Participants responded to SOQ items based on a 5-point Likert scale ranging from "strongly agree" to "strongly
disagree". Test-retest reliability (0.73-0.89), intraclass
reliability (0.84-0.94), internal consistency (0.79-0.95) and construct
and concurrent validity have been adequately demonstrated (Gill &
Deeter, 198 cool . The first author of the SOQ provided permission for the
SOQ to be used as part of an Internet survey.
Sport Motivation Scale (SMS). The Sport Motivation Scale (SMS)
(Pelletier et al., 1995) assesses an athlete's intrinsic
motivation, extrinsic motivation and amotivation toward sports. Three
types of intrinsic motivation (IM) can be measured with the Sport
Motivation Scale: IM to Know, IM to Accomplish Things, and IM to
Experience Stimulation. According to Pelletier and colleagues (1995)
motivation to know refers to performing an activity for the pleasure and
satisfaction gained while learning, exploring, or understanding
something new. Motivation toward accomplishments is similar to mastery
motivation and a task-orientation. Intrinsic motivation to experience
stimulation refers to engaging in activity in order to experience
stimulating sensations (Pelletier et al., 1995).
The three types of extrinsic motivation (EM) that can be measured
with the Sport Motivation Scale are: EM-External Regulation,
EM-Introjection, and EM-Identification. External regulation refers to
behaviors that are controlled by external forces such as rewards.
Introjection refers to behaviors that are regulated by internal
pressures such as guilt or anxiety. Lastly, identification refers to
behaviors that are internally regulated and self-determined because one
views the behavior as important, yet it is still performed for extrinsic
reasons.
The SMS consists of 28 items and participants responded to items
based on a 7-point Likert scale ranging from "strongly agree"
to "strongly disagree". Adequate reliability and validity has
been reported for the SMS (Pelletier et al., 1995; Vallerand &
Lossier, 1994, 1999). The primary author of the SMS provided permission
for the SMS to be used as part of an Internet survey.
Procedures
Leagues and the respective teams were located through the Internet.
Participants were recruited during the off-season (December-February)
via an e-mail sent to a team coach or owner. If the team coach or owner
was interested in having players respond to the survey they were
instructed to send the e-mail message to the players. The e-mail inquiry
provided information about the study and contained a link to the
Principal Investigator's webpage. The link allowed participants to
access the Informed Consent document. If participants agreed to
participate in the study, they clicked an assent button and were linked
to the survey site. The survey site contained the 25-items from the
Sports Orientation Questionnaire (SOQ), 28-items from the Sport
Motivation Scale (SMS) and 7 demographic questions. Respondents were
informed that the survey would require approximately fifteen minutes to
complete. The Internet survey was created using SurveyWiz software,
which has been made available for academic use by Birnbaum (2000).
SurveyWiz is available from the following URL: http://
psych.fullerton.edu/mbirnbaum/programs/surveyWiz.HTM. Survey responses
were submitted to a secured data file site. There were no subject
identifiers (e.g. e-mail address) attached to survey responses. A Remote
Address (IP) was returned with submission of the survey responses and
examined by the Prinicipal Investigator to reduce the likelihood of
multiple submissions from a single respondent.
Data Analysis
All data was analyzed using SPSS for Windows (Version 12.0).
Pearson product moment correlations were conducted to examine
associations among competitive orientations, sport motivation, and age.
Descriptive statistics were computed to examine SOQ and SMS subscale
scores for the entire sample. In order to examine differences in
competitive orientations and sport motivation of younger and older
players a mean split of age was conducted, resulting in younger (N = 5 cool
(age range 18-30, M = 25.98, SD = 3.12 and older players (N = 59) (age
range 31-45, M = 36.15, SD = 3.54). One-way MANOVA was conducted to
examine differences in competitive orientations and sport motivation
between younger and older players.
Results
Table 1 presents pearson correlations among the SOQ, SMS, and age.
There were significant moderate correlations among the SOQ
competitiveness, win and goal scales (.25 to .64). Cronbach alpha
coefficients for the entire sample were 0.83 for competitiveness, 0.80
for win, and 0.73 for goal scales of the SOQ. Alphas are slightly lower
than those previously reported by Gill & Deeter (198 cool .
There were significant positive correlations between
competitiveness and the three IM scales of the Sport Motivation Scale.
Similar to correlations reported by Pelletier et al. (1995), there were
moderate to strong positive correlations among the three IM subscales
and three EM scales. There were also nonsignificant and negative
correlations between amotivation and three IM scales and nonsignificant
positive relationships between amotivation and the three EM scales.
Cronbach alpha coefficients for the entire sample were 0.86 for IM Know,
0.86 for IM Accomplish, 0.76 for IM Stimulation, 0.76 for EM
Identification, 0.70 for EM Introjection, 0.72 for EM External
Regulation, and 0.77 for Amotivation. These alphas are similar to alphas
ranging from 0.63-0.80 reported by Pelletier et al. (1995) and similar
to values reported by Martens and Webber (2002) and Sloan and Wiggins
(2001). Thus adequate internal consistency exists for both the SOQ and
SMS with this sample of female athletes.
Correlations between age and SOQ scales and SMS Intrinsic
Motivation scales were negative and nonsignificant, except for a
significant negative correlation between EM Identification and age.
Sample Comparisons. Table 2 presents SOQ and SMS scores for the
entire sample and younger and older participants. A one-way MANOVA on
the three SOQ scores revealed a nonsignificant age effect, F(3,106) =
1.61, p = 0.19. Aone-way MANOVAon the seven SMS scales revealed a
significant age effect, F(7, 102) = 2.18, p < 0.05. Univariate
results revealed that EM-Identification was greater for younger players
than older players, F(1,10 cool = 7.36, p < 0.05.
Discussion
The primary aim of this study was to examine relationships among
competitive orientations, sport motivation, and age of professional
women football players. Competitive orientation scores, as assessed by
the Sport Orientation Questionnaire (Gill & Deeter, 198 cool , for women
in the present study are similar to competitiveness, win and goal
orientation scores reported for intercollegiate male and female athletes
and professional male hockey players (Czech, Burke, Joyner, & Hardy,
2002; Gill, 1993).
SOQ scores are greater than those previously reported for college
nonathletes and adult sport and exercise participants (Gill et al.,
1996). The high competitive orientation scores in the present sample are
consistent with research revealing competitiveness as the score that
most differentiates athletes and nonathletes (Gill et al., 1996).
Successful athletes are highly motivated to compete.
Comparison of Sport Motivation Scale scores with other samples is
limited; however, IM and EM scores for participants in the present study
are greater than those reported by Pelletier et al. (1995). In general,
IM scores for participants in the present study were greater than EM
scores. Sloan and Wiggins (2001) examined motivational differences
between male collegiate and professional football players and found that
professional players reported greater IM-Know, IM-Introjection, and
EM-External Regulation than collegiate football players. Compared to IM
values reported by Sloan and Wiggins (2001), values for women in the
present study are slightly higher. EM values between the studies are
rather similar and amotivation values in the present study are lower
than those reported by Sloan and Wiggins (2001). Overall, it appears as
if women in the present sample were highly motivated to participate in
their chosen sport.
Correlational results generally support results of previous
studies. Although correlations among SOQ scales and age were
nonsignificant, the direction is consistent with the significant
negative association between age and competitiveness reported by Martin,
Eklund, and Smith (1994). Competitiveness was positively related to
intrinsic motivation. It is highly doubtful that the women in the
present study are participating solely for extrinsic purposes. Although
they are professional athletes, salaries of professional women football
players can not be compared to professional male football players. A
majority of players participated in high school sports and over half of
the sample participated in college athletics; it is likely that
continued participation in sport was primarily motivated by intrinsic
rather than extrinsic factors.
There was a significant negative association between age and
EM-Identification. EM-Identification relates to participation that is
influenced by interests, abilities and the desire to achieve
self-initiated goals. The person values or "identifies" with
the activity (Alexandris, Tsorbatzoudis, & Grouios, 2002). Thus,
over time, older athletes may have more difficulty identifying with a
given sport. Due to the intense physical demands of football and perhaps
competing demands (e.g., career, family) this inverse association
between EM-Identification and age is not surprising.
Due to the vigorous and demanding nature of professional football,
a secondary aim was to examine associations and potential differences in
competitive orientations and sport motivation between younger and older
players. Interestingly, there were no differences in competitiveness,
win or goal orientation between younger and older players. Relative to
sport motivation, younger players had greater levels of
EM-Identification than older players. Older athletes may have more
difficulty identifying with a given sport, particularly with a
physically demanding sport such as football. Despite this difference in
EM-Identification between younger and older players, this sample
represents a group of highly competitive and intrinsically motivated
women athletes.
A final aim of the study was to examine the feasibility and utility
of conducting sport and exercise research through the Internet. Although
the Internet is emerging as an acceptable environment for conducting
research (Kraut et al., 2004; Reips, 2002), there are advantages and
disadvantages of this research method that need to be considered.
Advantages of electronic survey research include lower costs, speed,
asynchronous communication, ease, wider sample, and emphererality (Kraut
et al., 2004; Reips, 2002; Thach, 1995). Limitations of Internet
research include sample bias, self-selection, limited control over
data-collection setting, potential multiple submissions, and drop-out
(Kraut et al., 2004; Reips, 2002). Multiple submissions were monitored
in the present study as a remote IP address was submitted when
respondents submitted their responses. An additional limitation of
Internet research is that response rates to online surveys are typically
lower that mail, telephone or written surveys (Kraut et al., 2004).
Potentially affecting results of the present study are sample bias,
self-selection, and response rates. Participants were recruited via an
e-mail sent to a coach or manager of a team belonging to one of three
professional women's football leagues. The percentage of messages
that were forwarded to team players is not known. In order to complete
the survey, players needed to be able to access the Internet, thus
players without access to the Internet may not have completed the
survey. Despite limitations, the present sample reflects a rather
diverse group of participants representing players from sixteen states
and twenty-five football teams. This range of responsiveness may not
have been possible with traditional paper-and-pencil surveys.
Overall, results of this study indicate that women football players
are highly competitive and intrinsically motivated. Although there have
been significant increases in athletic opportunities for women in the
past decades, professional and competitive opportunities for women
participating in stereotypical masculine sports (e.g., boxing, football)
(Koivula, 2001; Metheny, 1965; Postow, 1980) are limited. Results of
this study suggest that psychologically, women are capable of meeting
the "rigor" of stereotypical masculine sports. Future studies
might consider further examination of comparisons of competitive
orientations and sport motivation among women competing at professional
(e.g., WNBA, LPGA) and higher level sports competition (e.g., Olympic)
both at national and international levels. Also of interest might be a
comparison of competitive orientations and sport motivation among male
and female football players and other professional sports as well as
among participants in stereotypical gender-neutral, masculine or
feminine sports. Although not examined in the present study, it would
also be of interest to examine associations among competitive
orientations, sport motivation and sport performance and persistence.
Lastly, sport and exercise psychologists should consider the
opportunities of Internet research and the potential to expand the scale
and scope of their research projects.
Author Note
Readers interested in additional information about the leagues
referred to in the manuscript are encouraged to visit the following
websites: Independent Women's Football League,
http://www.iwflsports.com National Women's Football Association,
http://www.womensfootballcentral.com Women's Professional Football
League, http://www.womensprofootball.com
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Address Correspondence To: Christina Beaudoin, Ph.D., Department of
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Table 1
Correlations among SOQ, SMS, and Age
IM
Comp Win Goal Know
Comp -- .64 ** .32 ** .26 **
Win -- .25 ** .18 *
Goal -- .30 **
IM Know --
IM Stim
IM Acc
EM Ident
EM Intro
EM Ext Reg
Amot
IM IM EM EM
Stim Acc Ident Intro
Comp .43 ** .38 ** .22 * .16
Win .35 ** .26 ** .14 .11
Goal .14 .44 ** .31 ** .07
IM Know .47 ** .70 ** .50 ** .18
IM Stim -- .58 ** .30 ** .24 *
IM Acc -- .48 ** .29 **
EM Ident -- .26 **
EM Intro --
EM Ext Reg
Amot
EM
Ext Reg Amot Age
Comp .23 * -.27 ** -.17
Win .38 ** -.12 -.05
Goal .24 * -.14 -.16
IM Know .26 ** -.04 -.02
IM Stim .30 ** -.06 .02
IM Acc .41 * -.27 ** -.06
EM Ident .39 ** .05 -.20 *
EM Intro .41 ** .18 * .07
EM Ext Reg -- .08 -.10
Amot -- .12
* p < 0.05, ** p < 0.01
Table 2
SOQ and SMS Scores for All Players and Younger vs. Older Players
All Younger Older
Variable Players Players Players
(N = 5 cool (N = 55)
M SD M SD M SD
Age 31.11 6.09 25.98 3.12 36.15 3.54
Competitiveness (a) 58.45 5.73 59.43 4.84 57.50 6.37
Win (b) 22.53 4.18 22.87 4.22 22.20 4.14
Goal (c) 27.09 3.05 27.59 2.60 26.61 3.38
IM Know (c) 20.64 4.98 20.80 4.82 20.47 5.18
IM Acc (c) 22.35 4.52 22.78 4.27 21.93 4.75
IM Stim (c) 23.20 3.71 23.00 3.34 23.40 4.07
EM Iden (c) 16.83 5.32 18.16 5.26 15.49 5.07 *
EM Intro (c) 13.97 5.49 14.02 5.22 13.93 5.79
EM Ext Reg (c) 13.97 5.42 14.73 5.13 13.22 5.65
Amot (c) 7.27 4.14 6.64 3.98 7.91 4.24
* p < 0.05
(a) Range 13-65
(b) Range 6-30
(c) Range 4-28
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