Exploring the factorial structure of the Sport Anxiety Scale-2: Invariance across language, gender, age and type of sport.
In the environment of sports and sports competition, recreational and social evaluative aspects are simultaneously present (e.g., Miller, 2012). This characteristic makes competitive situations potentially anxiogenic, particularly for children, who have yet to develop an established repertoire of coping strategies. Consequently, anxiety is one of the most frequently studied topics in sports psychology and continues to be a major focus of investigation for researchers and consultants worldwide (e.g., Woodman & Hardy, 2003).
Competitive anxiety is defined as sport-specific trait anxiety that regularly appears before or during competition (Martens, 1977). This context-specific approach complements the dual conceptualization of state-trait anxiety proposed by Spielberger (1966). Multidimensional anxiety theory (Martens, Burton, Vealey, Bump, & Smith, 1990) holds that competitive anxiety, such as state and trait anxiety, can occur at the somatic or cognitive level. Somatic anxiety refers to bodily reactions to over-activation, such as muscular tension, whereas cognitive anxiety refers to thought content, such as worries related to the potential consequences of poor performance. Two questionnaires have been developed based on the above theory. The Competitive State Anxiety Inventory-2 (CSAI-2; Martens et al., 1990) focuses on the situational occurrence of the phenomenon, and the Sport Anxiety Scale-2 (SAS-2; Smith, Smoll, Cumming, & Grossbard, 2006) focuses on sport-specific trait anxiety, originally defined by Martens. While the study of state anxiety provides relevant information about an athlete's assessment of the competition, competitive trait anxiety (also called sport performance anxiety) provides information about an athlete's predisposition to respond to competition with state anxiety, which is a performance-related fear-of-failure construct (Smith, Smoll, & Passer, 2002).
To design individualized interventions for athletes, research in the field of competitive anxiety has focused on identifying differences in anxiety symptoms across groups that differ by gender, age or type of sport. With respect to gender, female athletes typically report higher levels of global competitive trait anxiety (Abrahamsen, Roberts, & Pensgaard, 2008; Martens et al., 1990), factors related to worries (Grossbard, Smith, Smoll, & Cumming, 2009) and precompetitive state anxiety (Thatcher, Thatcher, & Dorling, 2004). Moreover, some researchers suggest that gender serves as a moderator between the antecedents and consequences of anxiety. Specifically, moderating effects have been observed between the motivational climate and anxiety (Grossbard, Cumming, Standage, Smith, & Smoll, 2007) and between anxiety and performance (Woodman & Hardy, 2003). With respect to age, research has focused on the increasing competitive demands associated with age and has observed slightly higher levels of cognitive anxiety in older athletes (Craft, Magyar, Becker, & Feltz, 2003). However, these studies have also found that older athletes exhibit better coping strategies and are more likely than their younger counterparts to perceive this type of anxiety as facilitating their performance (Craft et al., 2003; Cruz, Dias, & Fonseca, 2010). With respect to the effect of the type of sport (i.e., individual versus team sports), studies have primarily focused on state anxiety. In their classic study, Simon and Martens (1979) found that athletes who participate in individual sports such as gymnastics report higher state anxiety levels than do athletes in team sports such as basketball. Consistent with this research, Kirby and Liu's (1999) study of Chinese athletes found that track and field participants report higher somatic anxiety and lower self-confidence than do basketball players. When the type of sport has been examined as a moderator variable, a meta-analysis of the relationship between the CSAI-2 and performance (Craft et al., 2003) has revealed a moderating effect of sport type such that cognitive and somatic anxiety exert a greater influence on performance in individual sports. Therefore, a review of the previous research indicates that most previous studies have focused on the effect of single variables on state anxiety rather than trait anxiety and that few studies have compared the simultaneous effect of multiple variables on competitive trait anxiety.
As noted above, the SAS-2 originated as a competitive trait anxiety measure based on multidimensional anxiety theory that assesses both somatic and cognitive symptoms of sport performance anxiety. The factor structure of the SAS-2 consists of three subscales: (1) a somatic anxiety factor, which evaluates the physiological elements of hyper-activation, such as muscle tension or stomach uneasiness; (2) the cognitive subscales of worry, which assess concerns associated with poor performance; and (3) concentration disruption, which detects difficulties in focusing on relevant aspects of the competitive activity. The item length and content of the SAS-2 have been adapted to be appropriate for children (Smith et al., 2006), and studies have confirmed that it exhibits good psychometric properties for both child and adult samples (Grossbard et al., 2007). As a result, the SAS-2 is viewed as one of the best assessment instruments for child and adolescent athletes (Harris, Blom, & Visek, 2013). In addition, the Spanish version of the questionnaire exhibited good psychometric properties in a study assessing competitive anxiety in Spanish child and adolescent athletes (Ramis, Torregrosa, Viladrich, & Cruz, 2010), and the questionnaire has exhibited good psychometric properties in validation studies of the Flemish- (Jannes, De Pelsemaeker, De Deken, & Van Damme, 2011) and Portugueselanguage versions (Sousa, Gomes, Torregrosa, Viladrich, & Cruz, 2011) of the questionnaire.
The above-mentioned studies validating the SAS-2 have included widely accepted procedures, such as translation and back-translation, expert judgment on construct equivalence and psychometric data on internal structure, construct validity and reliability. However, to confirm the equivalence of the different language versions and the comparability of scores across countries, evidence of measurement equivalence based on cross-cultural methods is also required (e.g., Marsh, Nagengast, & Morin, 2013). Due to the multidimensional nature of the SAS-2, measurement invariance based on confirmatory factor analysis (CFA) is the procedure of choice (e.g., Millsap, 2011). In addition, although studies have separately investigated the effects of gender, age and type of sport on competitive anxiety, a more comprehensive understanding is achieved by assessing the relative effect of each factor when all are included in a single analysis using a multiple indicators multiple causes (MIMIC) model (Joreskog & Goldberger, 1975). In this study, a MIMIC model was used to perform a multiple regression of the three SAS-2 factors on gender, age, language and type of sport to compare group means and determine the relative effects of these variables on the factors of somatic anxiety, worry, and concentration disruption.
To further our knowledge of competitive trait anxiety in youth sports and the psychometric properties of the SAS-2 questionnaire, the current study focused on the following goals: first, to validate the psychometric strengths of the SAS-2 by examining its configural, metric and scalar invariance across gender, age group, type of sport, and three languages; second, to use a MIMIC model to assess differences in competitive trait anxiety among subsamples by comparing the latent mean scores of these groups; and third, to use this MIMIC model to examine the relative contribution of each study variable to self-reported competitive anxiety.
The participants were 842 athletes (46% female) from Spain, Belgium and Portugal. The athletes ranged in age from 7 to 18 years. As some authors have suggested that cognitive-somatic discrimination might emerge as chronological age increases (see Grossbard et al., 2009), we generated three subsamples of equal size (<11 years; 11-13 years; and >13 years). All participants met the inclusion criteria of regularly practicing and competing in organized sports: 461 in individual sports (e.g., athletics, sailing, judo) and 381 in team sports (e.g., handball, football, water polo). Twenty-three sports were included in the study, and the most represented were basketball (n = 129), gymnastics (n = 113) and swimming (n = 111). Table 1 provides descriptive information for the sample grouped by country.
The Sport Anxiety Scale-2 (SAS-2; Smith et al., 2006) is a 15-item questionnaire that assesses the competitive trait anxiety experienced by athletes before or during competition. The scale includes three factors: somatic anxiety, worry and concentration disruption. Participants rate each item related to the statement "Before or while I compete in sports" (e.g., "my body feels tense"; "I worry that I will not play my best"; "it is hard to focus on what I am supposed to do") on a four-point Likert scale ranging from one (not at all) to four (very much). The score for each subscale is calculated as the mean of the scores of subscale items and varies from one to four, with a low score indicating a less intense form of that type of competitive anxiety and a high score indicating a high probability of exhibiting that type of anxiety. The items of the original version of the SAS-2 and the Spanish, Flemish and Portuguese versions are presented in Table 2.
The current research was developed in accordance with the Ethical Principles of Psychologists and Code of Conduct of the American Psychological Association (APA, 2010) as well as the principles of the ethical boards of all participating universities.
Questionnaire administration. After initially contacting club coordinators to request that they participate in our research, we contacted coaches to arrange a date and location to administer the questionnaire. The administration protocol required that two researchers always be present during the procedures to answer participants' questions and ensure that all steps of the protocol were followed. All athletes were informed of the confidentiality of data and voluntarily participated in the investigation. No important incidents occurred during administration of the questionnaire, and athletes were able to continue with their usual practice routines after they finished responding.
In this section, we describe the results of the preliminary analyses with regard to the following: the internal consistency, data normality and CFA of the three SAS-2 factors for each language version; the procedures used to perform the invariance test for language, gender age and type of sport; and the MIMIC procedure used to test the relative contribution of the variables to trait competitive anxiety.
Preliminary analyses. Using SPSS 17.0 (SPSS, 2008), internal consistency was assessed using Cronbach's alpha coefficients and inter-item correlations, and a normality test assessed skewness and kurtosis. Separate CFAs of the SAS-2 were performed for the Spanish (SPA), Flemish (FLE) and Portuguese (POR) sub-samples using MPlus 7.0 (Muthen & Muthen, 1998-2012). Based on the original model of Smith et al. (2006), we tested a three-factor CFA model in which all 15 SAS-2 items were employed as indicators of the associated somatic anxiety, worry or concentration-disruption latent factors based on the known pattern of relationships. Following the recommendations of Muthen & Muthen (1998-2012), we treated the SAS-2 items as ordinal variables and employed the weighted least square means and variance adjusted robust estimator (WLSMV). Chi-square, comparative fit index (CFI), Tucker-Lewis index (TLI) and root-mean square standard error of approximation (RMSEA) were used to evaluate the goodness of fit of the proposed models to the data. When testing models with quantitative indicators, CFI / TLI values above .95 and RMSEA values below .06 are considered indicators of excellent fit (Hu & Bentler, 1999), and CFI / TLI values above .90 and RMSEA values below .08 are considered indicators of acceptable fit (Marsh, Hau, & Wen, 2004). Although the behavior of these cutoff values with categorical data remain under discussion (Myers, Chase, Pierce, & Martin, 2011; Yu, 2002), we employed these criteria in this study following previous studies in our field (e.g., Marsh et al., 2013).
Invariance of the three-factor model for the SAS-2. Invariance testing was conducted across groups for three increasingly restrictive models: The multiple-group baseline model, the metric invariance model and the scalar invariance model. The multiple-group baseline model refers to the test of configural invariance across groups of the original model (i.e., the three correlated factors of somatic anxiety, worry and concentration disruption) with all parameters freely estimated. The metric invariance model, which was nested within the multiple-group baseline model, added the restriction of invariant factor loadings across groups. Finally, the scalar invariance model, which was nested within the metric invariance model, added the constraint of equal item thresholds across groups. MPlus performs measurement invariance testing by treating one sample as the reference group in which parameters are freely estimated and fixing the parameters of the other samples to be equal to those of this reference group. In our study, the reference group for language was Spanish, the reference group for gender was boys, the reference group for age was <11, and the reference group for type of sport was individual sport.
For the model comparison, both chi-square and CFI indices between nested models were compared. However, because the change in chi-square is sensitive to large sample size, the major indicators for testing model invariance were the changes in CFI, TLI and RMSEA. Following the recommendations of Cheung and Rensvold (2002) and Chen (2007), the more parsimonious model was selected only when the change in CFI and TLI was greater than -0.01 with respect to the more complex model or when the change in RMSEA was lower than 0.01.
MIMIC model for the three factors of the SAS-2. The relative contributions of language, gender, age and type of sport to variations on latent means of somatic anxiety, worry and concentration disruption were determined by performing a MIMIC analysis in which the SAS-2 quantitative latent factors were regressed on language, gender, age and type of sport. The reference groups for the MIMIC model were the same as those above for language, gender and type of sport (SPA, boys and individual sport, respectively), and nonredundant contrasts were set as predictive indicators (i.e., SPA versus FLE, SPA versus POR, boys versus girls and individual versus team sports). However, age was treated as a quantitative predictor for MIMIC modeling because it is a continuous variable.
Internal consistency was assessed for each subscale for every subsample. Cronbach's alpha coefficient ranged from .73 to .89, and inter-item correlations ranged from .31 to .61. These results supported the reliability of each language version of the questionnaire (see Table 1). With respect to distributional assumptions, skewness (range from -0.09 to 1.37) and kurtosis (range from -1.37 to 1.55) significantly departed from values expected under the normality assumption for 10 out of 15 items. Descriptive statistics for all subsamples are presented in Table 3.
A CFA of the correlated somatic anxiety, worry and concentration disruption (see Figure 1) was performed using the WLSMV estimator to address both the ordinality and non-normality of the data. Chi-squares ranging from 133.97 to 209.83 were significant in all samples, but both CFI and TLI were above .95, and the RMSEA indices were .04 for the SPA, .06 for the FLE and .07 for the POR versions of the questionnaire. We concluded that the model fit all the analyzed language-adapted versions. The global CFA results are presented in Figure 1.
Invariance of the SAS-2 Model
As Table 4 indicates, after configural invariance was established across all subsamples (the multiple-group baseline model), parameter invariance was supported at both the metric and scalar levels across all subsamples. The change of less than .01 in the CFI, TLI and RMSEA indices at the metric invariance level indicated that factor loadings were invariant across language, gender, age and type of sport. The negligible changes in these indices with the additional restriction of equal item thresholds supported scalar invariance across all subsamples.
The MIMIC model for the three factors of the SAS-2
Table 5 presents the standardized coefficients obtained for the MIMIC model regression of the three SAS-2 factors on the language, gender and type of sport contrasts as well as on participant age. The fit indices for the MIMIC model were excellent with a significant chi-square of 442.67(147), CFI and TLI of .97 and .96, respectively, and RMSEA under .05. For the language contrasts, although the FLE sample means were below the SPA means for somatic anxiety ([beta] = -.14; p = .002) and concentration disruption ([beta] = -.18; p<.001), the greatest effect was found for worry ([beta] = -.56; p<.001). The POR means were above the SPA means for both somatic anxiety ([beta] = .13; p = .001) and concentration disruption ([beta] = .16; p<.001), but there was no significant effect for worry. With respect to gender, there was only a significant effect for worry, with females exhibiting slightly higher means than males ([beta] = .11; p = .002). Similarly, there was an age effect for the worry subscale, with higher levels of this form of anxiety reported by older athletes ([beta] = .20; p<.001). Finally, there was an effect of the type of sport (i.e., individual versus team sports) for the somatic anxiety subscale, with athletes who participated in individual sports exhibiting higher levels of this type of anxiety ([beta] = -.24; p<.001).
The present study is a theoretical and methodological proposal focused on the construct of trait competitive anxiety (Martens et al., 1990; Martens, 1977; Smith et al., 2006). Our results provide evidence of invariance at the configural, metric and scalar levels for three language-adapted versions of the SAS-2. The SAS-2 factorial model also exhibited invariance across gender, age and type of sport.
Although there was language invariance with respect to the factor structure, the MIMIC model revealed differences across versions. Spanish athletes reported higher anxiety levels than Flemish athletes, and Portuguese athletes reported higher levels than Spanish athletes on somatic anxiety and concentration disruption, but beta weights were modest in both cases. However, a remarkable effect was found for the FLE/SPA contrast on worry, with Spanish athletes exhibiting higher levels of that form of anxiety. This effect might be due to the different connotation of the term "worry" in Romance languages (i.e., me preocupa / eu me preocupo) compared to Flemish (i.e., ik maak me zorgen). Whereas the Flemish connotation directly implies the uneasiness of anticipating negative consequences, the Romance concept suggests a sense of responsibility regarding the task at hand. This conceptual duality was previously noted by Lane, Sewell, Terry, Bartman and Nesti (1999) when reviewing the original version of the CSAI-2 (Martens et al., 1990), which included the phrase "I am concerned" instead of "I am worried". As these authors suggest, concern might refer to the acknowledgement of the challenge that the competition represents instead of the anxiety that it creates, which would be better expressed by "I am worried". We believe that different nuances are also found in the zorgen clause, which appears to be closer to "worry", whereas preocupacion resembles the concept of "concern".
Measurement invariance was also found with respect to gender, and only a slight significant effect of this variable on the worry factor was revealed by the MIMIC model. These results, obtained by children at an early stage of sport participation, only concur partially with previous studies of higher competitive level samples that suggest gender differences on the three anxiety factors (Abrahamsen et al., 2008; Grossbard et al., 2009). Similarly, a significant age effect on worry revealed higher levels of this cognitive form among older athletes, coinciding with the perspective that higher competitive demands generate higher cognitive symptoms (Craft et al., 2003). Finally, the MIMIC model showed a significant effect of the type of sport on the somatic anxiety factor, with athletes participating in individual sports reporting higher levels of this anxiety form. This outcome is consistent with earlier studies that suggest that when athletes compete as individuals, the pressure to achieve the desired outcome is borne by the individual alone, which intensifies somatic symptoms (Kirby & Liu, 1999; Ramis, Torregrosa, & Cruz, 2013; Simon & Martens, 1979).
This study exhibits certain limitations. The level of competition for study participants was essentially recreational or educational. Further studies should investigate athletes' competitive anxiety in more highly competitive contexts to determine the extent to which reported anxiety levels in general--and gender-based anxiety patterns in particular--vary depending on the competitive level, as the work of Jones et al. (1991) and Thatcher et al. (2004) suggests. Moreover, this study only employed a measure of trait anxiety. To provide a more comprehensive understanding of competitive anxiety, future research should incorporate state anxiety measures, but also individual or environmental variables that might predict anxiety symptoms, such as a coach's interpersonal style and intrinsic and extrinsic motivation.
In conclusion, the present findings demonstrate that the SAS-2 has a good factor structure and good internal consistency and can be used in research independently of participants' language (with respect to Spanish, Flemish and Portuguese), gender, age and type of sport. The SAS-2 appears to be a trustworthy instrument for applied practice and research in the field of sport psychology
We would like to acknowledge the contributions of Miquel Torregrossa, Jaume Cruz, Margarida Gomes, Dominik de Pelsemaeker, Daphne De Deken and Dirk Van Damme. We would also like to express our appreciation for the constructive comments provided by two anonymous reviewers that enabled us to improve the manuscript.
Abrahamsen, F.E., Roberts, G.C., & Pensgaard, A.M. (2008). Achievement goals and gender effects on multidimensional anxiety in national elite sport. Psychology of Sport and Exercise, 9(4), 449-464. doi:10.1016/j. psychsport.2007.06.005.
APA (2010, December). Ethical principles of psychologists and code of conduct. Retrieved from http://www.apa.org/ethics/code/principles.pdf.
Chen, F.F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464-504.
Cheung, G.W., & Rensvold, R.B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9, 233-255.
Craft, L.L., Magyar, T.M., Becker, B.J., & Feltz, D.L. (2003). The relationship between the competitive State Anxiety Inventory-2 and sport performance: A meta-analysis. Journal of Sport & Exercise Psychology, 25, 44-65.
Cruz, J.F., Dias, C., & Fonseca, A.M. (2010). Coping strategies, multidimensional competitive anxiety and cognitive threat appraisal: Differences across sex, age and type of sport. Serbian Journal of Sport Sciences, 1, 4-9.
Grossbard, J.R., Cumming, S.P, Standage, M., Smith, R.E., & Smoll, F.L. (2007). Social desirability and relations between goal orientations and competitive trait anxiety in young athletes. Psychology of Sport and Exercise, 8(4), 491-505. doi:10.1016/j.psychsport.2006.07.009.
Grossbard, J.R., Smith, R.E., Smoll, F.L., & Cumming, S.P. (2009). Competitive anxiety in young athletes: Differentiating somatic anxiety, worry, and concentration disruption. Anxiety, Stress, and Coping, 22(2), 153-166. doi:10.1080/10615800802020643.
Harris, B.S., Blom, L.C., & Visek, A.J. (2013). Assessment in youth sport: Practical issues and best practice guidelines. The Sport Psychologist, 27(2), 201-211. Retrieved from http://www.pubmedcentral.nih.gov/ articlerender.fcgi?artid=3919511&tool=pmcentrez&rendertype=abstract.
Hu, L., & Bentler, PM. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Coventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1-55.
Jannes, C.R., De Pelsemaeker, D., De Deken, D., & Van Damme, D. (2011). Psychometric properties of the Flemish version of the Sport Anxiety Scale-2. In 13th FEPSAC European Congress of Sport Psychology. Madeira.
Joreskog, K.G., & Goldberger, A.S. (1975). Estimation of a model with multiple indicators and multiple causes of a single latent variable. Journal of the American Statistical Association, 70(351), 631-639. doi:10.2307/2285946.
Kirby, R.J., & Liu, J. (1999). Precompetition anxiety in Chinese athletes. Perceptual and Motor Skills, 88, 297-303.
Lane, A.M., Sewell, D.F., Terry, P.C., Bartman, D., & Nesti, M.S. (1999). Confirmatory factor analysis of the Competitive State Anxiety Inventory-2. Journal of Sports Sciences, 17, 505-512.
Marsh, H.W., Hau, K.T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis testing approaches to setting cutoff values for fit indexes and dangers in overgeneralising Hu & Bentler's (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11, 320-341.
Marsh, H.W., Nagengast, B., & Morin, A.J.S. (2013). Measurement invariance of big-five factors over the life span: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects. Developmental Psychology, 49(6), 1194-218. doi:10.1037/a0026913.
Martens, R. (1977). Sport competition anxiety test. Champaign: IL: Human Kinetics.
Martens, R., Burton, D., Vealey, R.S., Bump, L.A., & Smith, D.E. (1990). Development and validation of the competitive state anxiety inventory-2. In R. Martens, R.S. Vealey & D. Burton (Eds.), Competitive Anxiety in Sport (pp. 117-190). Champaign: IL: Human Kinetics.
Miller, S.R. (2012). I don't want to get involved: Shyness, psychological control, and youth activities. Journal of Social and Personal Relationships, 29(7), 908-929. doi:10.1177/0265407512448266.
Millsap, R.E. (2011). Statistical approaches to measurement invariance. New York: NY: Routledge.
Muthen, L.K., & Muthen, B.O. (n.d.). MPlus User's Guide. Seventh edition. Los Angeles: CA: Muthen & Muthen.
Myers, N.D., Chase, M.A., Pierce, S.W., & Martin, E. (2011). Coaching efficacy and exploratory structural equation modeling : A substantivemethodological synergy. Journal of Sport & Exercise Psychology, 33, 779-806.
Ramis, Y., Torregrosa, M., & Cruz, J. (2013). Revisitando a Simon & Martens: la ansiedad competitiva en deportes de iniciacion [Simon & Martens revisited: Competitive anxiety in youth sports]. Revista de Psicologia del Deporte, 22, 77-83.
Ramis, Y., Torregrosa, M., Viladrich, C., & Cruz, J. (2010). Adaptacion y validacion de la version espanola de la Escala de Ansiedad Competitiva SAS-2 para deportistas de iniciacion [Adaptation and validation of the Spanish version of the Sport Anxiety Scale SAS-2 for young athletes]. Psicothema, 22, 1004-1009.
Simon, J.A., & Martens, R. (1979). Children's anxiety in sport and nonsport evaluative activities. Journal of Sport Psychology, 1, 160-169.
Smith, R.E., Smoll, F.L., Cumming, S.P., & Grossbard, J.R. (2006). Measurement of multidimensional sport performance anxiety in children and adults: The Sport Anxiety Scale-2. Journal of Sport and Exercise Psychology, 28, 479-501.
Smith, R.E., Smoll, F.L., & Passer, M.W. (2002). Sport performance anxiety in young athletes. In F.L. Smoll & R.E. Smith (Eds.), Children and youth in sport. A biopsychosocial perspective (2nd ed., pp. 501-536). Dubuque, IA: Kendall-Hunt.
Sousa, C., Gomes, M., Torregrosa, M., Viladrich, C., & Cruz, J. (2011). Psychometric properties of the MCSY S, AGSYS and SAS-2: Preliminary validation into Portuguese. In 13th FEPSAC European Congress of Sport Psychology. Madeira.
Spielberger, C.D. (1966). Theory and research on anxiety. In C.D. Spielberger (Ed.), Anxiety and behaviour (pp. 3-20). New York: NY: Academic Press.
SPSS (2008). SPSS Statistics for Windows. Chicago: SPSS Inc.
Thatcher, J., Thatcher, R., & Dorling, D. (2004). Gender differences in the pre-competition temporal patterning of anxiety and hormonal responses. The Journal of Sports Medicine and Physical Fitness, 44(3), 300-308.
Woodman, T., & Hardy, L. (2003). The relative impact of cognitive anxiety and self-confidence upon sport performance: A meta-analysis. Journal of Sports Sciences, 21(6), 443-457. doi:10.1080/0264041031000101809.
Yu, C.-Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. University of California Los Angeles.
Yago Ramis (1), Carme Viladrich (1), Catarina Sousa (1) and Caroline Jannes (2)
(1) Universitat Autonoma de Barcelona and (2) Ghent University
Received: November 17, 2014 * Accepted: March 6, 2015
Corresponding author: Yago Ramis
Dep. Psicologia Basica, Evolutiva i de l'Educacio. Edifici B
Universitat Autonoma de Barcelona
08193 Barcelona (Spain)
Table 1 Demographic characteristics and internal consistency for the Sport Anxiety Scale-2 (SAS-2) scales for each language version Individual Country N Female% sport % [M.sub.age] (SD) Spain 319 34.17 36.05 11.15 (1.66) Belgium 362 60.22 74.31 12.28 (2.54) Portugal 161 36.65 47.82 11.61 (2.20) Internal consistency Somatic anxiety Worry Conc. disr. Country [alpha] [??] [alpha] [??] [alpha] [??] Spain .83 .45 .78 .43 .73 .31 Belgium .81 .46 .88 .61 .77 .40 Portugal .79 .43 .76 .40 .81 .46 Note: Mage = mean age; SD = standard deviation; Conc. Disr. = concentration disruption; [alpha] = Cronbach's alpha coefficient; [??] = inter-item correlation Table 2 The Sport Anxiety Scale-2 items Item English (Smith et al., 2006) Spanish (Ramis et al., 2010) Somatic anxiety 2 My body feels tense Siento que mi cuerpo esta tenso 6 I feel tense in my stomach Siento un nudo en el estomago 10 My muscles feel shaky Siento que mis musculos tiemblan 12 My stomach feels upset Tengo el estomago revuelto 14 My muscle feels tight Siento mis musculos tensos because I am nervous porque estoy nervioso Worry 3 I worry that I will not Me preocupa no jugar o play well competir bien 5 I worry that I will let Me preocupa desilusionar a others down los demas (companeros, entrenadores, padres...) 8 I worry that I will not Me preocupa no jugar o play my best competir todo lo bien que puedo 9 I worry that I will Me preocupa competir play badly o jugar mal 11 I worry that I will mess up Me preocupa "cagarla" durante during the game el partido o la competicion Concentration disruption 1 It is hard to concentrate on Me cuesta concentrarme en el the game partido o la competicion 4 It is hard to me to focus on Me cuesta centrarme en lo que what I am supposed to do se supone que tengo que hacer 7 I lose focus on the game Pierdo la concentracion en el partido o la competicion 13 I cannot think clearly No puedo pensar con claridad during the game durante el partido o la competicion 15 I have a hard time focusing Me cuesta concentrarme en lo on what my coach tells que el entrenador me ha me to do pedido que haga Portuguese Item Flemish (Jannes et al., 2011) (Sousa et al., 2011) Somatic anxiety 2 Mijn lichaam is gespannen Sinto o meu corpo tenso (rijo) 6 Ik voel de spanning in Sinto um no no estomago mijn maag 10 Mijn spieren trillen Sinto os meus musculos a tremer 12 Ik heb last van mijn maag Sinto o meu estomago as voltas 14 Mijn spieren voelen gespannen Sinto que os meus musculos aan omdat ik nerveus ben estao tensos (rijos) porque estou nervoso Worry 3 Ik maak me zorgen dat ik niet Preocupa-me se nao jogar bem goed zal spelen 5 Ik ben bezorgd dat ik anderen Preocupa-me desiludir os zal teleurstellen outros (colegas, treinadores, etc.) 8 Ik ben bezorgd dat ik niet Preocupo-me se nao conseguir op mijn best zal spelen dar o meu melhor 9 Ik ben bang om slecht Preocupa-me que va jogar mal te spelen 11 Ik ben bezorgd dat ik de Preocupa-me fazer asneiras wedstrijd zal verknoeien durante o jogo Concentration disruption 1 Het is moeilijk om mij te E dificil concentrar-me concentreren op de wedstrijd nos jogos 4 Ik vind het moeilijk om me E dificil concentrar-me no te concentreren op wat ik que tenho de fazer zou moeten doen 7 Ik verlies de aandacht op Perco a concentracao de wedstrijd nos jogos 13 Ik kan niet helder denken Nao consigo pensar de forma tijdens de wedstrijd clara durante o jogo 15 Ik vind het moeilijk om me E dificil concentrar-me no te concentreren op hetgeen que o meu treinador me pede wat de coach zegt wat ik para fazer moet doen Table 3 Means and standard deviations of the three SAS-2 factors across language, gender, age and type of sport Language SPA (n = 319) FLE (n = 362) POR (n = 161) Somatic anxiety 2.13 (.77) 1.86 (.65) 2.18 (.77) Worry 3.02 (.74) 2.05 (.78) 3.04 (.75) Conc. Disr. 1.86 (.57) 1.60 (.52) 1.99 (.65) Gender Girls (n = 386) Boys (n = 456) Somatic anxiety 2.07 (.75) 1.98 (.72) Worry 2.56 (.92) 2.64 (.88) Conc. Disr. 1.76 (.60) 1.78 (.57) Age <11 (n = 277) 11-13 (n = 358) >13 (n = 207) Somatic anxiety 2.00 (.71) 2.08 (.77) 1.94 (.70) Worry 2.51 (.94) 2.72 (.88) 2.55 (.86) Conc. Disr. 1.81 (.53) 1.76 (.59) 1.74 (.64) Type of sport Individual (n = 461) Team (n = 381) Somatic anxiety 2.07 (.74) 1.96 (.72) Worry 2.45 (.92) 2.80 (.84) Conc. Disr. 1.75 (.60) 1.79 (.58) Note: SPA = Spanish; FLE = Flemish; POR = Portuguese Table 4 Factorial invariance of the SAS-2 across language, gender, age and type of sport [DELTA][ji Model t df al cuadrado] Language MG baseline model 482.84 261 Metric invariance 552.56 285 77.97 * Scalar invariance 667.51 339 144.44 * Gender MG baseline model 373.02 174 Metric invariance 405.41 186 36.07 * Scalar invariance 476.90 213 79.22 * Age MG baseline model 502.64 261 Metric invariance 545.05 285 47.30 * Scalar invariance 572.73 339 50.85 Type of sport MG baseline model 402.31 174 Metric invariance 421.86 186 22.34 * Scalar invariance 436.50 213 31.61 Model [DELTA]df CFI TLI RMSEA Language MG baseline model .976 .971 .055 Metric invariance 24 .971 .968 .058 Scalar invariance 54 .963 .966 .060 Gender MG baseline model .982 .979 .052 Metric invariance 12 .980 .978 .053 Scalar invariance 27 .976 .977 .054 Age MG baseline model .978 .974 .057 Metric invariance 24 .977 .974 .057 Scalar invariance 60 .979 .980 .050 Type of sport MG baseline model .979 .975 .056 Metric invariance 12 .978 .976 .055 Scalar invariance 30 .980 .980 .050 Model [DELTA]CFI [DELTA]TLI [DELTA]RMSEA Language MG baseline model Metric invariance -.005 -.003 .003 Scalar invariance -.008 -.002 .002 Gender MG baseline model Metric invariance -.002 -.001 .001 Scalar invariance -.004 -.001 .001 Age MG baseline model Metric invariance -.001 .000 .000 Scalar invariance .002 .006 -.007 Type of sport MG baseline model Metric invariance -.001 .001 -.001 Scalar invariance .002 .004 -.005 Note: [ji al cuadrado] = conventional chi-square fit statistic (under WLSMV estimation); df = degrees of freedom; CFI = comparative fit index; RMSEA = root mean square error of approximation; MG = multiple-group; MG Baseline Model = no invariance; Metric Invariance = invariant factor loadings; Scalar Invariance = invariant factor loadings and invariant item thresholds; Residual Invariance = invariant factor loadings, item thresholds and factor disturbances. * p<0.05 Table 5 Estimates of language, gender, age and type of sport in SAS-2 factors under the MIMIC model Somatic anxiety [beta] p S.E. Language SPA against FLE -.135# .002# .044# SPA against POR .132# .001# .038# Gender Boys against Girls .042 .308 .041 Age .048 .239 .040 Type of Sport Individual against Team -.236# <.001# .039# Worry [beta] p S.E. Language SPA against FLE -.563# <.001# .035# SPA against POR .063 .050 .032 Gender Boys against Girls .110# .002# .035# Age .200# <.001# .033# Type of Sport Individual against Team -.051 .153 .036 Concentration disruption [beta] p S.E. Language SPA against FLE -.181# <.001# .045# SPA against POR .160# <.001# .042# Gender Boys against Girls .053 .211 .042 Age -.018 .662 .041 Type of Sport Individual against Team -.074 .083 .043 Note: SPA = Spanish; FLE = Flemish; POR = Portuguese; standardized regression coefficients; significant coefficients are highlighted in bold Note: SPA = Spanish; FLE = Flemish; POR = Portuguese; standardized regression coefficients; significant coefficients are highlighted in #
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||articulo en ingles; SAS-2; Smith, Smoll, Cumming, & Grossbard, 2006|
|Author:||Ramis, Yago; Viladrich, Carme; Sousa, Catarina; Jannes, Caroline|
|Date:||Apr 1, 2015|
|Previous Article:||Evaluation of satisfaction in an extracurricular enrichment program for high-intellectual ability participants.|
|Next Article:||Analyzing data from a fuzzy rating scale-based questionnaire. a case study.|