Competitive orientations and sport motivation of professional women football players: an internet survey.

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 predominantly seek to learn skills, be physically active, have fun and enjoy activity (Gill et al., 1996). These would be considered intrinsically-related motives. Extrinsically-related motives such as gaining rewards and recognition are cited less often (Gill et al., 1996). Sport-specific inventories exist for the measurement of competitive achievement orientation 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, 1998). Wartenburg and McCutcheon (1998) 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 and examine relationships among competitive orientations, sport motivation, and age of professional women football players. Participation on formal/structured contact football teams is a relatively new opportunity for women athletes. To date research has not examined competitive orientations and motives of women football players. A secondary aim is to examine differences in competitive orientation and sport motivation between 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, 1988). 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, 1988). 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 = 58) (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 (1988).

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(1,108) = 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, 1988), 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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Christina M. Beaudoin

University of Southern Maine 

Address Correspondence To: Christina Beaudoin, Ph.D., Department of Sports Medicine, University of Southern Maine, 37 College Ave., Gorham, ME 04038-1032, Phone: [phone], FAX: [phone], email: [e-mail]

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 = 58)        (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