Psychometric properties of the "sport satisfaction instrument (SSI)" in female athletes: predictive model of sport commitment.

Psychological Reports: Measures & Statistics 2014, 115, 1, 148-164. © Psychological Reports 2014

PSYCHOMETRIC PROPERTIES OF THE “SPORT SATISFACTION INSTRUMENT (SSI)” IN FEMALE ATHLETES: PREDICTIVE MODEL OF SPORT COMMITMENT1 A. GRANERO-GALLEGOS Teachers' Center of Cuevas-Olula, Almería, Spain A. BAENA-EXTREMERA, M. GÓMEZ-LÓPEZ, AND J. A. ABRALDES Department of Physical Activity and Sport, Faculty of Sports Sciences, University of Murcia Summary.—The objective of this research was to assess the psychometric properties of the Sport Satisfaction Instrument (SSI) in a Spanish sample of female athletes in team sports federations, to decide whether it constitutes a valid and reliable instrument to be used in the context of female competitive sport in future research. The SSI was administered to a total of 615 athletes from 12 to 38 yr. of age. Confirmatory procedures and psychometric analysis supported the hypothesized theoretical model of two factors (Satisfaction/fun and Boredom). For female athletes, the 7-item model showed better goodness-of-fit indexes upon eliminating Item 2 from the Boredom subscale. Concurrent validity was explored through the correlations with the Perception of Success Questionnaire and Sport Commitment, obtaining positive correlations between Satisfaction/fun and Task Orientation and Sport Commitment, whereas Boredom correlated positively but less closely with Ego Orientation. The importance of Satisfaction/fun in the prediction of Sport Commitment, starting from task orientation, is emphasized.

An issue that has concerned coaches and psychologists in competitive sports has been to achieve an optimum psychological state in athletes to improve their performance (García, Cervelló, Jiménez, Iglesias, & SantosRosa, 2005). Research has also focused on acquisition and improvement of the commitment to sports practice (Cecchini, González, & Montero, 2007; Sousa, Torregrosa, Viladrich, Villamarín, & Cruz, 2007); i.e., a psychological disposition representing the desire and decision to continue to practice a sport activity (Scanlan, Simons, Carpenter, Schmidt, & Keeler, 1993). Currently, most motivational psychology research carried out in the sport sphere is based on the achievement goal theory (Ames, 1984; Dweck, 1986; Nicholls, 1989). According to Nicholls (1984), people conceive of their capacity and judge their competence with regard to two goal perspectives that subjectively define success and failure: task orientation or mastery, and ego- or outcome-orientation. Task-oriented athletes usually judge their 1 Address correspondence to Antonio Baena-Extremera, C/ Granada 6, Güevéjar 18212, Granada, Spain or e-mail ([email protected]).

DOI 10.2466/08.06.PR0.115c14z1

13-PR_Granero-Gallegos_140045.indd 148

ISSN 0033-2941

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PSYCHOMETRIC PROPERTIES OF SSI

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capacity by self-comparison, whereas ego-oriented athletes judge their competence (or lack thereof) by comparing themselves with other athletes (Nicholls, 1984). The two goal orientations are independent, so people may be simultaneously task- and ego-oriented, varying the intensity of their motivational pattern (Nicholls, 1984, 1989). One person can have both orientations independently, one low and the other high, both low, or both high (Balaguer, Castillo, & Tomás, 1996). One of the most widely used instruments to measure dispositional achievement goals in sports is the “Perception of Success Questionnaire (POSQ)” designed by Roberts and Balagué (1989, 1991) and Roberts, Treasure, and Balagué (1998), and adapted to Spanish by Cervelló, Escartí, and Balagué (1999; “Cuestionario de Percepción de Éxito en el Deporte”). This scale has 12 items measuring dispositional goal orientations in sports through two dimensions that assess Task Orientation (six items) and Ego Orientation (six items). Goal orientations are good predictors of certain motivational variables, such as fun or intrinsic satisfaction with sports practice, defined as the fun or boredom that people feel when they practice a sport (Duda, Fox, Biddle, & Armstrong, 1992; Hom, Duda, & Miller, 1993; Cervelló, et al., 1999; Cecchini, González, Carmona, & Contreras, 2004). According to Duda (2001), Smith, Balaguer, and Duda (2001), and Castillo, Balaguer, and Duda (2002), independently of perceived competence, task-oriented athletes generally tend to achieve greater satisfaction and fun from sports practice; in contrast, ego-orientated athletes tend to be bored and do not consider fun to be an important element of sport performance. Determinants of satisfaction and fun experienced by athletes in achievement settings such as training or competitions may vary depending on the goal achievement adopted (Lochbaum & Roberts, 1993; Roberts, Hall, Jackson, Kimiecik, & Tonymon, 1995). Hence, it is essential to measure and determine athletes' satisfaction/fun or boredom. In order to measure participants' satisfaction with sports practice, Duda and Nicholls (1992) developed an instrument called the “Sport Satisfaction Instrument (SSI)” (“Cuestionario de Satisfacción en el Deporte”). This questionnaire proceeded from the adaptation of the original questionnaire, “Intrinsic Satisfaction Classroom Scale (ISC)” of Nicholls, Patashnick, and Nolen (1985) and Nicholls, Cheung, Lauer, and Patashnick (1989), referring to the school setting. This instrument measures students' satisfaction and intrinsic interest in school by means of eight items divided into two scales addressing satisfaction/fun (five items) and boredom (three items) with academic activities. In the case of the sport version SSI, the psychometric properties of this questionnaire, at an exploratory level in the work of Duda and Nicholls (1992), and in the works of Castillo, et al. (2002) and Castillo, Balaguer, Duda, and García-Merita (2004), showed the existence


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of two negatively related dimensions: satisfaction/fun (α = .94) and boredom (α = .83) in Duda and Nicholls (1992), and α = .84 and α = .76 in Castillo, et al. (2002). However, according to the latter authors, the reliability analysis of their work showed that internal consistency increased upon eliminating Item 2 (“In sports, I often daydream instead of thinking about what I'm doing”) from the Boredom scale. This is also the case in the work of Castillo, Balaguer, and Duda (2001) with the SSI, and of Baena-Extremera, Granero-Gallegos, Bracho-Amador, and Pérez-Quero (2012) with the SSI-EF: when eliminating this item, the internal consistency reliability of the scale improved. But in the sports sphere, only seven items were found in the research of Álvarez, Balaguer, Castillo, and Duda (2009) with male athletes, Castillo, et al. (2002) with adolescent athletes, and Ruiz-Juan, Gómez-López, Pappaous, Alacid, and Flores (2010). The last study proposes the elimination of Item 6 (“I usually find time flies when I am doing sports”) in paddlers. It is not clear whether the seven-item scale can be used with top-level female athletes. According to Castillo, et al. (2002), pleasant and satisfying experiences in sports increase athletes' commitment to sports practice, whereas boredom increases their tendency to drop out of sports, especially when they doubt their skill because of small difficulties arising during practice. Sousa, et al. (2007) pointed out that sports fun is an important predictor of sport commitment in young athletes. Sport commitment is defined as a psychological state representing the desire or resolve to continue sport participation (Scanlan, et al., 1993). Commitment is determined by the pleasure and fun obtained through practice, personal investments, engagement, and the social environment (Scanlan, Russell, Beals, & Scanlan, 2003; Scanlan, Russell, Wilson, & Scanlan, 2003). The assumption is that the greater the sport commitment, the lower the dropout rate (Schmidt & Stein, 1991; Torregrosa, Sousa, Viladrich, Villamarín, & Cruz, 2008). Sport commitment is assessed by the Compromiso Deportivo (SCQe), the Spanish version by Sousa, et al. (2007) of the Sport Commitment Questionnaire (SCQ) by Scanlan, et al. (1993). Currently, there is not enough research testing this aspect, and even less including female athletes. Therefore, the aim of this study was to provide evidence of the dimensionality of the Spanish version of the SSI in a sample of female athletes using confirmatory procedures, and to assess the psychometric properties of the Spanish version of the SSI. This research will extend existing knowledge, increase the possibility for application, and also improve the precision of the questionnaire. For this purpose, this study will: (a) examine its factor structure with confirmatory factor analysis (CFA); (b) assess internal consistency by means of Cronbach's α (≥ .70; Peterson, 1994), composite reliability coefficient (≥ .70; Hair, Black, Babi, & Anderson, 2009), and average variance extracted (AVE; > .50; Hair, et al., 2009); (c) verify its temporal stability (test-retest Cronbach's α and Pear-


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son's correlation coefficient; and (d) assess its empirical validity, calculating the correlations between the two SSI dimensions with the goal orientations through the POSQ and the sport commitment, and analyzing the predictive relationships of goal orientations and satisfaction/fun and boredom upon sport commitment. Previous research (Duda & Nicholls, 1992; Castillo, et al., 2002; Baena-Extremera, et al., 2012) leads to the expectation that task orientation will be positively correlated with satisfaction/ fun and negatively with boredom. Also, ego orientation is expected to have low positive correlation with boredom but no relation with satisfaction/fun. Similarly, a stronger correlation is expected between satisfaction/fun and sport commitment than between boredom and commitment. METHOD Participants Participants in this study were 615 female athletes from 16 teams of diverse autonomous communities of Spain (Andalusia, Murcia, Valencia, Madrid, Catalonia, and Galicia) and from seven federal sports collectives (handball, indoor soccer, soccer, water polo, hockey, basketball, and volleyball), competing at the highest level of their relevant leagues. Age ranged between 12 and 38 yr. (M = 21.6, SD = 5.0). Temporal stability of the SSI was assessed in a second sample of 60 athletes, randomly selected previously (M age = 20.4 yr., SD = 4.6), who completed the instrument a second time six weeks later. Measures Sport satisfaction.—Sport Satisfaction Instrument (SSI) (Duda & Nicholls, 1992; Balaguer, Atienza, Castillo, Moreno, & Duda, 1997). This scale is made up of eight items that measure intrinsic satisfaction with a sport activity, through two subscales that assess satisfaction/fun (3 items) and boredom (3 items) with sport practice. Items 1, 5, 6, 7, and 8 on the scale correspond to satisfaction/fun and Items 2, 3, and 4 to the boredom scale. Participants are requested to rate their agreement with the items that reflect criteria of fun or boredom on a five-point scale of polytomic items, with anchors 1: Strongly disagree and 5: Strongly agree. Success perceptions.—The Perception of Success Questionnaire (POSQ; Roberts & Balagué, 1991; Roberts, et al., 1998) was used, in the version validated in the Spanish sports context (Cervelló, et al., 1999), to measure the dispositional orientation of achievement goals. Previous studies on satisfaction/fun and boredom in the fields of sport (Castillo, et al., 2002; RuizJuan, et al., 2010) and education (Castillo, et al., 2001; Baena-Extremera, et al., 2012), have analyzed the relationship between these dimensions and success. The stem statement of the questionnaire is: “When I prac-


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tice sports, I feel successful when….” It has 12 items, six addressing task orientation (Items 3, 4, 7, 8, 10, and 11) and six addressing ego orientation (Items 1, 2, 5, 6, 9, and 12). Responses are rated on a five-point scale with anchors 1: Strongly disagree and 5: Strongly agree. In the present sample, reliability of the task orientation subscale was α = .86, and of ego orientation, α = .87. Commitment.—The sport commitment subscale (6 items) of the Sport Commitment Questionaire (SCQ) was used, adapted to the Spanish context by Sousa, et al. (2007), from that of Scalan, et al. (1993). Sousa, et al. (2007) found that sport fun was an important predictor of sport commitment in young athletes. In the instructions, athletes were asked to indicate their agreement or disagreement with the sport commitment-related statements on a five-point scale with anchors 1: Strongly disagree and 5: Strongly agree. In the present sample, reliability of the sport commitment subscale was α = .74. Procedure Permission was requested from the several participating clubs by a letter that explained the objectives of the research and how it would be performed. Enclosed, they could find a model of the questionnaires. The day before the competition, the researchers administered the questionnaire during the training sessions of the participating teams. All players were informed of the purpose of the study, that it was voluntary, of the absolute confidentiality of answers provided and data management, and that there were no right or wrong answers. They were also asked to answer as sincerely and honestly as possible. Analysis As the factor structures underlying the questionnaires have been consistent in the literature, confirmatory factor analysis (CFA) was conducted with LISREL 8.80 to assess the factor structure of the scale. Item analysis, homogeneity, and internal structure, correlations (Pearson coefficient), and internal consistency (Cronbach's α) of the scale were calculated with SPSS 17.0. RESULTS Item Analysis and Reliability of the Scale Table 1 presents the descriptive statistics of the SSI. In the statistical analyses of items, the item-factor distribution observed in the original instrument was maintained (Duda & Nicholls, 1992; Balaguer, et al., 1997). Item characteristics were analyzed, verifying whether the alpha of the scale increased upon eliminating an item, as well as taking into account Nunnally and Bernstein's (1994) criteria to retain an item within a


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TABLE 1 STATISTICAL ANALYSIS OF EACH ITEM OF THE SPORT SATISFACTION INSTRUMENT (N = 615) SUBSCALES Scale

M

SD

CCITCC c

α Without Each Skewness Item

Kurtosis

Satisfaction/Fun (α = .80) 8. Normalmente me divierto practicando deporte. [I usually have fun doing sports.]

4.62

1.03

.69

–.39

.73

–1.29

0.21

1. Normalmente me lo paso bien haciendo deporte. [I usually enjoy playing sports.]

4.55

1.11

.60

–.39

.76

–1.29

0.21

7. Normalmente participo activamente cuando hago deporte. [I usually get involved when I am doing sports.]

4.46

1.16

.63

–.35

.75

–1.27

0.22

6. Cuando hago deporte parece que el tiempo vuela. [I usually find time flies when I am doing sports.]

4.25

1.07

.54

–.35

.78

−1.10

0.95

5. Normalmente encuentro el deporte interesante. [I usually find playing sports interesting.]

4.52

1.03

.51

–.30

.79

−1.74

0.66

2. En el deporte a menudo sueño despierto en vez de pensar en lo que estoy haciendo. [In sports, I often daydream instead of thinking about what I'm doing.] 2.44

1.22

.23

–

.68

0.45

−0.70

3. Cuando practico deporte normalmente me aburro. [When playing sports, I am usually bored.] 1.32

1.06

.46

–.37

.31

0.75

0.19

4. Cuando hago deporte deseo que la competición termine rápidamente. [When I practice sports, I wish the competition were over soon.].

1.12

.49

–.45

.32

0.93

0.17

Boredom (α = .52)

1.54

Note.—CCIT-c: corrected item-total correlation coefficient; CC: correlation between the score of each item and the total score in each one of the components.


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factor [when the corrected item-total correlation coefficient (CCIT-c) ≥ 0.30, SD > 1], and that all the response options had been used at some time. In accordance with Bollen and Long's (1994) recommendations, skewness and kurtosis indexes were close to 0 and < 2 in both factors. The items of the first factor (satisfaction/fun) presented mean values between 4.25 for Item 6 and 4.62 for Item 8 (“I usually have fun doing sports”), and SDs were higher than 1, ranging between 1.03 for Items 8 and 5 (“I usually find playing sports interesting”), and 1.16 for Item 7 (“I usually get involved when I am doing sports”). Internal consistency of this dimension was adequate (α = .80). All CCIT-c values were higher than .50. Mean values of the items of the second factor (Boredom) ranged between 1.32 for Item 3 (“When playing sports, I am usually bored”) and 2.44 for Item 2, and SDs were higher than 1, ranging between 1.06 (Item 3) and 1.22 (Item 2). Internal consistency of this dimension was adequate (α = .52). The CCIT-c values were lower than .45 for Items 3 and 4 to .23 (> .30) for Item 2. The inadequate internal consistency and the low CCITc values motivated the elimination of Item 2 from this dimension; after elimination, alpha was .68. Although the reliability was lower than the recommended value due to having only two items, the internal validity was acceptable (Nunnally & Bernstein, 1994; Hair, et al., 2009). In the present work, the item-total correlations were positive with the corresponding theoretical dimension, and negative with the total score of the other dimension. Item 2 is noteworthy, as it obtained a negative and non-significant correlation with its scale (r = −.07); nevertheless, there was no overlap with the theoretical dimension of satisfaction/fun. Confirmatory Factor Analysis Structural equation models were to study the psychometric properties of the original theoretically proposed dimensionality (Duda & Nicholls, 1992; Balaguer, et al., 1997) and of the model in which the dimension boredom has only two items (eliminating item 2). Factor structure of the SSI was assessed with CFA. Initially, an analysis of the multivariate normality of the 8-item scale was performed. The normality test was conducted based on the Relative Multivariate Kurtosis (RMK) of PRELIS, of the LISREL 8.80 program. The Normalized Multivariate Kurtosis value of the instrument was 70.14 and the Mardia-Based-Kappa coefficient was 0.89. It is important to mention the test critical value of 1.96 (5%), where the upper limit for interval RMK was 1.03 and the outer limit for interval RMK was 0.98. The test results showed that multivariate normality cannot be accepted, indicating the use of robust estimators. For this reason, this analysis was performed with the Weighted Least Squares (WLS) estimation method for ordinal variables


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155

with the LISREL 8.80 program (Jöreskog & Sörbom, 1993). The matrix of polychoric correlations and the asymptotic covariance matrix were used as input for data analysis. A measurement model consisting of a two-factor model with two latent variables was hypothesized. To assess the models, various fit indexes were calculated, as recommended by authors like Bentler (2007), Markland (2007), or Miles and Shevlin (2007), among others. Fit was assessed by a combination of absolute and relative fit indexes. Among the absolute indexes, this study used the p value associated with the chi-squared statistic, which tests the null model against the hypothesized model (Barrett, 2007). The ratio between chi-squared and degrees of freedom (χ2/df ) is a heuristic used to reduce the sensitivity of chi-squared to sample size. In a model considered perfect, its value would be 1.0, and ratios lower than 2.0 would be considered indicators of a very good model fit (Tabachnik & Fidell, 2007) while values lower than 5.0 would be considered acceptable (Hu & Bentler, 1999). The goodness-of-fit index (GFI) was also calculated. This indicates the relative amount of variance and covariance reproduced by the specific model, compared with the saturated model, and its value should be equal to or higher than 0.90 for the fit of the model to be considered minimally acceptable, although authors like Hooper, Coughlan, and Mullen (2008) consider values ≥ 0.95. Among the relative rates, the normed fit index (NFI), the nonnormed fit index (NNFI), and the comparative fit index (CFI) were used). Among the incremental indexes, values ≥ 0.95 are considered to indicate a good fit (Hu & Bentler, 1999). Bentler (2007) also notes that the root mean square residual (RSMR) should be reported, and its value should be lower than 0.08. Authors like Kline (2005) recommend the use of the root mean square error of approximation (RMSEA) and, according to Hu and Bentler (1999), a value of ≤ 0.06 indicates a good fit, although Steiger (2007) notes that < 0.07 is the borderline consensus. The estimated parameters are considered significant when the t value is higher than 1.96 (p < .05). Following the recommendations of authors such as MacIntosh (2007), Markland (2007), or Levy and Hancock (2007) of formulating and analyzing various models if so recommended by the data, and of reporting the most relevant results, below are presented the results of the CFA corresponding to the two proposed models: one with 8 items and the other with seven items. The seven-item model was constructed without Item 2, taking into account the above-mentioned comments about the internal consistency and homogeneity of the items (Table 1) and considering that this item was eliminated from the factor Boredom in works like that of Castillo, et al. (2001). Figure 1 shows the path diagram at left, representing the model with Item 2, low factor loading (standardized regression weight = .32), and high measurement error (0.90). All the items presented


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A. GRANERO-GALLEGOS, ET AL. Eight-item Model

Seven -item Model Item 8

.95 .82

Satisfaction / fun

.83

.10

Item 1

.34

Item 7

.31

.95 .82

Satisfaction / fun

.75 .71

-.71

.32

Boredom

.81

.10

Item 1

.33

Item 7

.34

Item 6

.45

Item 5

.53

Item 3

.34

Item 4

.45

.74

Item 6

.44

Item 5

.49

Item 2

.90

Item 3

.34

Item 4

.49

.68

-.72

.81

.71

Item 8

.71

Boredom

.80

FIG. 1. Path diagram of the CFA, with standardized weights and measurement errors of each one of the SSI items in female athletes.

values higher than .05 in individual reliability (R2) except for Item 2 (R2 = .01), so the model should be reviewed and tested without this item. The goodness-of-fit indexes obtained for the eight-item model showed satisfactory fit: χ2(19) = 54.48, p < .001, χ2/df = 2.85, GFI = 0.99, NFI = 0.97, NNFI = 0.96, CFI = 0.98, RMR = 0.07, RMSEA = 0.06. The results of the 7-item model showed a very good fit of the model, both in absolute and in relative indexes: χ2(13) = 26.09, p = .002, χ2/df = 2.01, GFI = 1.00, NFI = 0.99, NNFI = 0.99, CFI = 0.99, RSMR = 0.05, RMSEA = 0.04. The 8-item model does not present the minimum requirements to guarantee convergent validity of the model (Hair, et al., 2009): in high standardized factor loadings (in Item 2, no higher than .60), although they are all statistically significant (t value > 1.96), both conditions are necessary to guarantee validity. The seven-item model indicates convergent validity of the model (standardized factor loadings > .60 in all cases and t value > 1.96). It is also considered important in CFA of ordinal scales to provide the values of composite reliability for each one of the critical dimensions in the correlation matrix, as it characterizes the relations between item responses and the latent variable measured (Elosua & Zumbo, 2008), as well as the variance extracted to study the validity of the scale. The composite reliability coefficient is considered more adequate than Cronbach's α, as it does not depend on the attributes associated with each concept (Vandenbosch, 1996). It is commonly considered that it should have a minimal value of .70 (Hair, et al., 2009). Table 2 shows that both satisfaction/ fun and boredom had a reliability > .70, although, in the seven-item model, it reached .86 in the boredom subscale.


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157

PSYCHOMETRIC PROPERTIES OF SSI TABLE 2 RELIABILITY AND VALIDITY OF THE SCALE Eight-item Model

Seven-item Model

Coefficients

Satisfaction/Fun

Boredom

Satisfaction/Fun

Boredom

Composite reliability

.91

.74

.90

.86

Variance extracted

.66

.52

.65

.75

Cronbach's α

.80

.52

.80

.68

The average variance extracted (AVE) shows the total amount of variance of the indicators tapped by the latent construct. Higher values indicate that the indicators are more representative of the critical dimension they load on. In general, it is suggested that its value should exceed 0.50 (Bagozzi & Yi, 1988; Hair, et al., 2009). When it is higher than 0.50, this implies that a high percentage of variance is explained by the construct in comparison with the error measurement variance (Arias, 2008). In this case, the variance extracted in each dimension considered was higher than 0.50, and it reached 0.75 in the seven-item model in the Boredom subscale, whereas in the eight-item model it was at the limit of consensus (0.52). Temporal stability of the SSI was assessed with the sample of 60 athletes who completed it two times, with a 6-week interval, as they had provided this study with their birth dates. The data of the seven-item model are presented. Pretest results in satisfaction/fun were α = .82, and in boredom, α = .70. Posttest data in satisfaction/fun were α = .81, and in boredom, α = .69. Test-retest correlation values for satisfaction/fun dimension were r = .75, and for boredom, r = .77. Test-retest data of the eight-item model in this sample of 60 athletes were: satisfaction/fun, r = .75; boredom, r = .73. Concurrent Validity To assess empirical validity, correlations (Pearson's coefficient) between the two dimensions of the SSI-PE were calculated, as well as correlations with the subscales of the POSQ and sport commitment (Table 3). The correlations between satisfaction/fun and boredom were significant and negative. Moreover, satisfaction/fun had a high positive correlation with task orientation and sport commitment, but it did not correlate with ego orientation. A significant and negative relationship was found between boredom and task orientation and sport commitment, and a positive, albeit less intense, one with ego orientation. As well, sport commitment had a positive correlation with task orientation and it did not correlate with ego orientation. Table 3 shows correlations of the three-item boredom subscale with fewer negative values for satisfaction/fun, sport commitment, and task orientation. Structural Equations have been used to analyze the predictive relationships of goal orientations and satisfaction/fun and boredom on sport


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158

A. GRANERO-GALLEGOS, ET AL. TABLE 3 CORRELATIONS BETWEEN THE SUBSCALES OF THE SSI, POSQ, AND SPORT COMMITMENT Subscale

1

1. Satisfaction/fun 2. Boredom

2

3

4

5

–.47†

.47†

.02

.41†

–.37†

–.29†

3. Task orientation

–.26†

4. Ego orientation

.10†

5. Sport commitment

.08* –.28† .36†

.32† .05

–.18†

Note.—Correlations with the 3-item boredom subscale have been added to the lower diagonal (including Item 2). *p < .05. †p < .01.

commitment, estimating structural regression models. In this case, the normality test was conducted based on the RMK of PRELIS, of the LISREL 8.80 program. The Normalized Multivariate Kurtosis value was 67.42 and the Mardia-Based-Kappa coefficient was 0.285. The critical value of the test was 1.96 (5%), where the upper limit of interval RMK was 1.008 and the outer limit of interval RMK was .992. Thus, the test results showed that multivariate normality cannot be accepted. As above, the data were found to not meet the assumptions of ML so WLS was used. The matrix of polychoric correlations and the asymptotic covariance matrix were used as input for data analysis. Initially, a model that related task orientation with satisfaction/fun and boredom, and also ego orientation with satisfaction/fun and boredom, was established. This way, all predictive relationships established between the two subscales of these latent variables could be analyzed. From here, direct relationships were established of satisfaction/fun and boredom with sport commitment. The obtained rates of fit indices of the model were acceptable. Then, to analyze the direct prediction relationships between task and ego orientation upon sport commitment, these estimates were added to the previous model. The fit indices resulting from the new model were also acceptable. The modification indices proposed in the output by the LISREL program were considered to improve these latest model fits, allowing a covariance error between boredom and satisfaction/fun. Thus, taking into account the discussion above regarding the appropriate adjustment parameters of a structural equation model, Fig. 2 presents the model established whose fit results were acceptable: χ2 = 393.56, df = 265, p < .001, χ2/df = 1.48, GFI = 0.96, NFI = 0.98, NNFI = 0.99, CFI = 0.99, RMSEA = 0.03. Figure 2 shows a statistically significant, positive path coefficient from task orientation to satisfaction/fun predictor but a negative path coeffi-


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159


.48

V3

.49

V4

.35

V7

.33

.58

.55

.43

.14

V1

V5

V6

V7

V8

.72

.40

V8

.32

V10

.82

.15

.65 .67 .75 .93

.71 .81 .77

TASK

.67

SAT/F .36

.82

-.28

.87 .24

V11

SC

.64

V1

.31

V2

.60 .83

.43

V5

.75

.36

V6

.48

V9

.24

V12

.80

-.57

EGO

.35

-.19

.63 .62 .66 .70 .68 .84

V1

.61

V2

.61

V3

.56

V4

.51

V5

.54

V6

.30

BOR

.72 .87

.84

.79

V3

V4

.30

.53

-.01

FIG. 2. Structural model of five hypothesized factors. The circles represent the latent constructs (5) and the squares the variables measured (25). All parameters are standardized and significant at p < .05. TASK: task orientation; EGO: ego orientation; SAT/F: satisfaction/ fun; BOR: boredom; SC: sport commitment.

cient to boredom. The path coefficient from ego orientation to boredom was positive and to satisfaction/fun was negative. From the model provided, the magnitude of the path coefficient to sport commitment was twice as large from satisfaction/fun than from boredom. The direct paths from goal orientations to sport commitment had smaller coefficients than through satisfaction/fun and boredom. DISCUSSION After reviewing the theoretical framework, the goal of this work was to examine the factor structure with CFA of the seven-item and eight-item SSI to compare them, assess their internal consistency, and to verify the temporal stability and empirical validity of the seven-item scale. As mentioned, the origin of these goals lies in the scarce research corroborating which is the most appropriate for female athletes: the seven-item or the eight-item model. As in the work of Castillo, et al. (2002) and Álvarez, et al. (2009), CFAs based on structural equation models supported the factor validity and reliability of the instruments. In the analysis of the SSI, the two dimensions hypothesized in the theoretical model used in sports were found. Some research in the academic context (Castillo, et al., 2001; BaenaExtremera, et al., 2012) recommend reviewing the theoretical model with seven and with eight items, proposing the elimination of Item 2 from the boredom factor of SSI versions. In sport contexts, Castillo, et al. (2002) and Álvarez, et al. (2009) also proposed eliminating Item 2 from the boredom factor. The CFA, as well as reliability issues and CCIT-c, suggested Item 2 should be eliminated. In the present study, in addition to Cronbach's α


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as a measure of internal consistency, evidence of composite reliability and AVE were presented for the Spanish version of the SSI. In the eight-item model, Cronbach's α of the second factor was inadequate until Item 2 was eliminated. Goodness-of-fit values obtained for the seven-item model were better than those of the eight-item model. The improvement achieved in the values of χ2/df and GFI by eliminating Item 2 is notable; the values are similar, but better than those of Castillo, et al. (2002). Likewise, the incremental indexes and the RMSEA improve in the seven-item model, indicating that this model has a better fit than the eight-item model initially proposed by Duda and Nicholls (1992) and used till now in most research. In the assessment of empirical validity, the patterns of correlations with the POSQ corroborate those of other research, like that of Duda and Nicholls (1992), Duda, et al. (1992), Duda (2001), Smith, et al. (2001), and Castillo, et al. (2002), showing that athletes with task orientation tend to achieve greater satisfaction and fun from sports practice, whereas athletes with ego orientation tend to be more bored. In the case of females, Duda, Chi, Newton, Walling, and Catley (1995) found a positive relation between task orientation and fun. But Roberts, et al. (1995) found no relation in females between satisfaction and ego orientation. As shown, the results support the use of the seven-item SSI instead of the eight-item model for female athletes, as confirmed by the data obtained. Moreover, they are coherent with the few similar investigations carried out in the sports context. The psychometric analyses show that the scores obtained with this scale are valid and reliable. Thus, the questionnaire is useful both in the area of sport psychology and adherence to physical-sport practice, and also in the acquisition of healthy habits. On the other hand, it has been shown that female athletes' motivational orientations are important for sport commitment. The results show a positive correlation between sport commitment and task orientation, coinciding with Garcia, Leo, Martín, and Sánchez (2008). The positive correlation between ego orientation and sport commitment was unexpected. Despite the positive relationship between task orientation and sport commitment, satisfaction/fun showed stronger predictive qualities of sport commitment, coinciding with Sousa, et al.'s (2007) results in young athletes. Limitations and Conclusion A potential weakness was not assessing the relationship between sport commitment and motivational contextual factors like the perception of motivational climate among peers. This could have been accomplished using the Peer Motivational Climate in Youth Sport Questionnaire (PEERMCYSQ: Ntoumanis & Vazou, 2005). Also closely related is the per-


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ception of motivational climate created by the coach, which could be measured with the Perceived Motivational Climate in Sport Questionnaire (PMCSQ–2). The coach's role is determinant in athletes' sport commitment and fun (Torregrosa, et al., 2008). Expanding the theoretical perspective, including self-determination theory (SDT), would provide a more complete view of sport motivation. This investigation has allowed the authors to comment on the scarce extant research. An internationally acknowledged and tested scale was used, and its adaptation and improvement with the seven-item model for female sport is a contribution to the development of new research. Another important aspect of the results is the fact that the association of sport commitment was much stronger through satisfaction/fun compared to boredom and task orientation. REFERENCES

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