A cross-cultural evaluation of the factorial invariance of the competitive aggressiveness and anger scale.
The Competitive Aggressiveness and Anger Scale (CAAS; Maxwell & Moores, 2007a) is an efficient method of assessment developed to identify athletes that may be more likely to display acts of aggression. As the field of sport and exercise psychology becomes increasingly cognizant of the impact of multiculturalism, researchers should begin making strides to validate widely used instruments of important psychological and behavioral constructs, such as anger and aggressiveness, cross-culturally. Therefore, the purpose of this study was to continue to test the psychometric properties of the CAAS in both American and English-speaking Hong Kong Chinese (hereafter referred to simply as Chinese) populations.
Defining Aggression, Aggressiveness, and Anger in Sport
Maxwell and Moores (2007a) noted that there has been a "heated" debate in the sport science literature regarding an appropriate definition of aggression in sport (see Kerr 1999, 2002; Sacks, Petscher, Stanley, & Tenenbaum, 2003; Tenenbaum, Sacks, Miller, Golden, & Doolin, 2000; Tenenbaum, Stewart, Singer, & Duda, 1997). The debate largely revolves around the inclusion or omission of sanctioned acts of aggression (e.g., punching in boxing or heavy tackles in American football). The International Society for Sport Psychology (ISSP) Position Statement favors omission (Tenenbaum, et al., 1997), regarding sanctioned acts as assertive rather than aggressive, whereas Kerr, amongst others (e.g., Maxwell & Moores, 2007b), favor inclusion (Kerr, 1999, 2002). The ISSP defined aggression as "... the infliction of an illegal aversive stimulus, either physical, verbal, or gestural, upon one person by another. Aggression is not an attitude but an unsanctioned behavior and, most critically, it is reflected in acts committed with the intent to injure (Lellnes & Nation, 1989)" (Tenenbaum et al., 1997; p. 1; italicized words added by authors). Kerr on the other hand, while not providing a clear-cut definition of aggression in sport, suggests "aggression can be seen as unprovoked hostility or attacks on another person which are not sanctioned by society" (Kerr, 1997, p. 115-116).
Ultimately, Maxwell and Moores (2007a) choose to integrate the ISSP's and Kerr's definitions and define aggression in sport as almost any intentional act, whether sanctioned or unsanctioned, inflicted on an opponent that causes significant physical or psychological harm. This working definition would seem to be a viable starting position for future debate and lends itself naturally to the sub-classifications of aggression resulting from instrumental or hostile motivations (e.g., Husman & Silva, 1984; Isberg, 2000; Smith, 1983). With a potentially viable working definition of aggression, Maxwell and Moores could then focus on well known antecedents of aggression, specifically aggressiveness and anger, when designing the CAAS.
Berkowitz (1993) identified high trait anger and aggressiveness as important antecedents of aggression. Aggressiveness is defined as the disposition to become aggressive or acceptance of and willingness to use aggression; whereas, anger has been described as a universal emotion, identifiable in numerous animal species, that has evolved because it possesses some survival value (Darwin, 1965; Spielberger, Reheiser, & Sydeman, 1995). One notion portrays anger as the subjective evaluation that increased physiological arousal is a result of threat to one's physical or psychological well being (Averill, 1983). An alternative definition states that anger is a negative feeling associated with specific cognitive and perceptual distortions and deficiencies (e.g., misappraisals and attributions of blame), physiological changes, and behavioral tendencies (Kassinove & Sukhodolsky, 1995; Novaco, 2000).
Development of the CAAS
Maxwell and Moores (2007a) generated a selection of items that described angry feelings, aggressive attitudes, acts of aggression, and acceptance of aggressive behavior. Their intention was to develop items that could be applied to most sports. Exploratory factor analysis of the potential items, using data from a diverse group of 309 athletes, revealed a 12-item two-factor structure, subsequently labeled anger and aggressiveness, with six items loading on each factor. Confirmatory factor analysis (CFA) supported the two factor structure in a second sample of athletes (n = 230), also from diverse sports. In addition, positive correlations were found between CAAS subscale scores and scores on all four subscales of the Buss-Perry Aggression Questionnaire (BPAQ; Buss & Perry, 1992). Maxwell and Moores demonstrated that the CAAS could be used to distinguish aggressive from non-aggressive athletes. Specifically, a group of 44 soccer players who regularly played together in one of three teams rated their teammates on a peer behavior questionnaire (PBQ) and completed the CAAS with respect to their own feelings and attitudes. The PBQ consisted often questions such as "Who on your team is often aggressive?" and "Who argues with the referee?" Participants were required to nominate at least one player from their team for each statement. Based on PBQ nominations, players were designated as aggressive (Fighters), non-aggressive (Calm), or Neutral. Fighters scored significantly higher than the other two groups on both CAAS subscales.
In a recent critique of the CAAS, Kerr (2008) claimed that the CAAS was of limited use for studying aggression in sport and went on to question the item content of the scale and its utility across diverse sports and populations. In doing so, Kerr disregarded the intent of the CAAS. The CAAS is not a measure of direct aggression; rather, it measures aggressiveness and anger and only predicts aggression indirectly in much the same way as motivational state (Apter, 1982), perceived physical ability (Archer & Benson, 2008), and physical size (Lemieux, McKelvie, & Stout, 2002) might predict aggression. In particular, Kerr questioned the inclusion of two items measuring verbally aggressive behavior and questioned whether the CAAS would be useful for specific sports and populations. In responding to the critique, Maxwell and Moores (2008c) rebuffed Kerr's suggestion that the CAAS was of limited utility in identifying aggressive athletes by restating the findings from their sample of soccer players and describing similar findings from as yet unpublished work with rugby players (Maxwell & Visek, 2009). However, they conceded that the two verbal items may be unnecessary and reiterated their previous statement (Maxwell & Moores, 2007a) that the CAAS' properties (e.g., factor structure) "... requires further testing in various sports and populations of athletes" (p. 190). Thus, confirmation of its properties in a new sample formed one of the aims of the current study.
When comparing the applicability of a scale across cultures, it is important to have clear theoretical reasons for predicting potential differences between the cultures in question. In fact, to provide a stringent test of multi-group invariance it is best to choose groups that are clearly different, rather than groups that are for all intense and purposes identical (e.g., Americans versus Canadians). Naturally, choice of group will depend on the availability of participants and eventual aims of the researcher. Perhaps the greatest cultural discrepancies are those that lie between East and West. Eastern cultures are nominally collectivist whereas western cultures are more individualistic (Hofstede, 1980). Individualism refers to the tendency to prioritize individual goals and contrasts with the tendency to be concerned for the group that typifies collectivistic orientations. Members of individualistic cultures are more likely to accept aggression as a means to achieving goals than are members of a collectivist culture. The Chinese are significantly more collectivistic than most western populations (Hofstede, 1980); thus, the latter are more likely to demonstrate aggression.
Recently, a growing interest in Chinese populations has emerged in the sport psychology literature. Of relevance to the current manuscript has been empirical research examining anger and aggression in Chinese individuals and their comparison with American and British peoples (Maxwell, 2007; Maxwell, Moores, & Chow, 2007; Maxwell & Siu, 2008; Maxwell, Sukhodolsky, & Sit, in press; Visek, Hurst, Maxwell, & Watson, 2008; Visek, Watson, Hurst, Maxwell, & Harris, in press). Maxwell and colleagues noted that the experience and expression of extreme emotions and behaviors are discouraged in Chinese society because they are seen as harmful to the body's normal harmony (Chen, Cheung, Bond, & Leung, 2005; Veith, 1972). The Confucian concept of "forbearance", identified by The Chinese Culture Connection (1987) is also another important Chinese social virtue, which advocates taking control of one's emotions (e.g., anger) or other psychological impulses. The goal of forbearance is to maintain harmony in stressful situations, such as avoiding interpersonal conflict. Consistent with Chinese values, Eid and Diener (2001) reported lower frequency and intensity of anger in Chinese cultures relative to Americans and Australians. It is likely that Chinese athletes would also tend to experience anger less intensely and express anger through aggression less frequently than do Western athletes. Consistent with this prediction, generally Maxwell and colleagues have demonstrated that the Chinese athletes are more likely to internalize anger, but are less likely to act aggressively, relative to western athletes (see Visek, Watson, et al., in press). It appears that there are good theoretical reasons for assuming that scales measuring constructs related to negative attitudes, emotions, and behaviors may not be invariant across western and eastern populations. Therefore, the second aim in the current study was to test this assertion as it applies to the CAAS using responses provided by American and Chinese athletes.
Structural Equation Modeling for Confirmatory Factor Analysis and Multi-Group Invariance
Structural equation modeling (SEM) has become a standard procedure for confirming the factor structure of commonly used psychometric instruments (e.g., Schutz & Gessaroli, 1993), but sport scientists have been slow to adopt the method (Marsh, 2007). SEM allows the testing of specific hypotheses (i.e., the predicted factor structure of a questionnaire) using techniques that incorporate measurement error into the equation (Byrne, 2001). Hypotheses are represented by model specification; in other words, the researcher designates relationships amongst measured (observed) variables and unmeasured (unobserved) latent constructs or factors. Marsh (2007) states that almost all constructs in sports science are latent constructs because they are normally implied indirectly from measurements made of related variables. For example, in the case of the CAAS, anger and aggressiveness are not measured directly and are latent constructs that are implied from responses to items (measurement variables). The test of the model resides in the fit between the observed data (responses to individual questions) and the theoretical model (the predicted relationships amongst the questions).
Although the adoption of SEM techniques is now gaining ground for use in confirmatory factor analyses of questionnaire factor structure (e.g., Maxwell & Moores, 2007a; Ntoumanis & Vazou, 2005; von Collani & Werner, 2005), its use for multiple group comparisons, although increasing (e.g., Kyle, Graefe, & Manning, 2005; McInerney & Ali, 2006; Standage, Duda, & Ntoumanis, 2005), is still relatively rare in the sport sciences. When comparing one culture with another it is often assumed that the factor structure of a particular scale is equivalent in both cultures; clearly, this assumption is not always valid. Maxwell (2007), for example, found that the factor structure of the 29-item BPAQ could not be replicated in a Chinese population, but that a 12-item short form suggested by Bryant and Smith (2001) could be replicated. Maxwell and colleagues (Maxwell et al., in press) found similar results for the State-Trait Anger Expression Inventory - Revised (STAXI-2; Spielberger, 1999). Both of these cases illustrate the problem with assuming structural equivalence across diverse populations and support the need to conduct analysis that explores this issue. Aside from deletion of items, other problems include cross-loading of items onto different factors, response bias, and measurement error (Marsh, 2007). Thus, it is important to validate scales prior to performing any cross-cultural comparisons based on theoretically derived latent constructs.
When considering the cross-cultural invariance of a particular scale, SEM techniques have been used successfully by several authors to compare the equivalence of scales across diverse groups and cultures (e.g., Byrne, 1988, 1993; Lonsdale, Hodge, & Rose, 2006; Marsh, Tomas-Marco, & Asci, 2002; Visek, Hurst, et al., 2008). For instance, Visek, Hurst, et al. found that the factor structure of the Athletic Identity Measurement Scale (Brewer & Cornelius, 2001) was invariant across samples of American and Chinese athletes. Therefore, the purpose of the current study was to use SEM techniques to further confirm the factor structure of the CAAS and explore its cross-cultural invariance in samples of American and Chinese athletes.
A convenience sample of male athletes (N= 677) participating in contact (i.e., basketball, soccer, and wrestling) and collision sports (i.e., American football and rugby union) participated in the study. Drawn from intact teams, the sample was comprised of American varsity and club athletes (n = 355) from both a Division I and Division II institution, and university and club Chinese athletes (n = 322). The American sample included athletes from all five sports in approximately equal numbers, whereas the Chinese sample included athletes participating in basketball, rugby, or soccer, again in approximately equal numbers (due to a coding error exact numbers are unknown). Only male athletes were used because of a severe paucity of female athletes participating in contact and collision sports in Hong Kong. The age distributions were as follows:American sample, 18-19 yrs = 181, 20-21 yrs = 122, 22-23 yrs= 50, 24+ yrs = 1, one unknown; Chinese sample, 18-19 yrs = 34, 20-21 yrs = 143, 22-23 yrs = 68, 24+ yrs = 76. The Chinese athletes were significantly older than the American sample ([chi square] (4) = 177.71, p < .001).
Competitive Aggressiveness and Anger Scale. The CAAS is a 12-item measure with six of the items assessing aggressiveness and six assessing anger (Maxwell & Moores, 2007a). Aggressiveness items are related to the acceptance and willingness to use both physical and verbal abuse to gain a competitive edge. Anger items describe incidences of irritation associated with losing and negative emotions directed at opponents and officials. Participants are asked to respond to each of the 12 items on a five-point Likert-type scale with anchors ranging from 1 (almost never) to 5 (almost always). In an effort to account for the severity of the CAAS items endorsed, participants' responses to each of the 12 items are multiplied by item severity scores and then summed to produce an aggressiveness subscale, anger subscale, and total CAAS score. Item severity scores were calculated from the mean scores from a sample (n = 81) of sport science researchers and masters students (with previous experience participating in competitive sport) that had rated each item's severity on a five-point Likert type scale with higher scores indicative of greater severity (see Maxwell and Moores (2007a) for a list of the item severity scores). Higher scores on the CAAS indicate greater degrees of aggressiveness and anger. Maxwell and Moores reported good fit between their data and the theoretical model ([chi square] (53)= 105.62, SRMR = .05, RMSEA = .07, CFI = .95; see Figure 1) and also reported sound internal reliability coefficients for the CAAS on the anger subscale ([alpha] = .78-.83), aggressiveness subscale ([alpha] = .83-.84), and the total score ([alpha] = .87-.88). One month test-retest reliability coefficients were also good for the anger subscale (r = .86), aggressiveness subscale (r = .84), and the total score (r = .88).
Institutional Review Board approval was granted to conduct the study. Coaches granted permission to access teams either during pre-season training or at the beginning of their respective competitive seasons. Athletes that volunteered to participate gathered in a distraction-free environment convenient to the team where questionnaire packets were distributed and participants were encouraged to provide honest responses.
Data collected for this study was one part of a larger study (Visek, Watson, et al., in press) that has already been accepted for publication. However, the larger study conducted by Visek and colleagues sought to introduce and empirically validate the Athletic Identity Maintenance Model, a theoretical model intended to account for sport aggression as a function of athletic identity. However, the data reported for the present study is focused solely on a psychometric evaluation of the CAAS and its utility across cultures.
Missing data values were minimal (2%); therefore, the researchers replaced missing values with the mean score of participants' distribution for the particular subscale of the CAAS (i.e., if item 3 was omitted, mean score on the Aggressiveness subscale was used to replace the Figure 1. Factor structure of the Competitive Aggressiveness and Anger Scale (CAAS) and model parameter as reported by Maxwell and Moores (2007a) for their sample of British ath-missing value). Cronbach's alpha (Cronbach, 1951) indicated sound internal reliability for the CAAS with coefficients ranging from acceptable to good (American sample: anger subscale [alpha] = .76, aggressiveness subscale [alpha] = .77, and the total score [alpha] = .84; Chinese sample: anger subscale [alpha] = .72, aggressiveness subscale [alpha] = .79, and the total score [alpha] = .86).
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Confirmatory factor analyses (CFA), conducted using Amos 5.0, were used to separately confirm the overall structure of the CAAS with the data collected from the American and Chinese athletes (i.e., to establish a baseline model; Byrne, 2004). The original factor structure of the CAAS and model parameters are shown in Figure 1. Hu and Bentler's (1999) recommendation of using at least two indices to establish model fit and imply factorial confh'mation was adopted for interpretation of the current data. They suggest combining the standardized root mean square residual (SRMR) with one other statistic. Numerous measures of model fit have been proposed; however, of the fit indices, the comparative fit index (CFI) and the root mean square error of approximation (RMSEA) are most reported (Ullman, 2001), with the latter deemed most useful (Byrne, 2001). Therefore, in the current study, a SRMR close to .08 coupled with a RMSEA close to .06 was deemed indicative of good model fit. Adequate model fit was accepted if both values were equal to or below .08 and poor model fit was concluded when either value exceeded .08. For information purposes, the Comparative Fit Index (CFI) and chi-square statistics are also reported, but were not consulted when establishing model fit.
To test for cross-cultural invariance, all measurement weights (factor loadings), measurement intercepts (item means), and structural covariances were constrained equally in a nested model comparison (based on the baseline model) following recommendations from Byrne (2001). Constraints on measurement residuals were not imposed as this is judged as too stringent (Byrne, 2001; 2004). The nested model comparison was evaluated using the chi-square statistic. Cross-cultural differences were deemed insignificant when p >. 10 for the chi-square change. Setting alpha at this level ensured tighter consistency across the two samples. Following discovery of non-invariance, constraints were removed systematically (i.e., from greatest difference between groups to lowest), beginning with measurement weights, then measurement intercepts, and finally structural covariances, until a satisfactory model was achieved.
Results from the current data indicated relatively poor fit for both the American and Chinese athletes with respect to Maxwell and Moores' (2007a) model (American sample: [chi square] (53) = 336.33, SRMR = .09, RMSEA = .12, CFI = .79; Chinese sample: [chi square] (53) = 197.13, SRMR = .05, RMSEA = .09, CFI = .89). Examination of the modification indices and inter-item correlations indicated items 3 and 4 (both refer to instances of verbal behavior) of the CAAS had similar error variances and were relatively highly correlated (r = .79 and .62, p < .01, for the American and Chinese samples, respectively), suggesting that by allowing the error terms for these two items to co-vary, a better fitting model could likely be obtained. With the error covariance added between items 3 and 4 (see Figure 1), results revealed a better fit to the American ([chi square] (52) = 138.04, SRMR = .05, RMSEA = .07, CFI = .94) and Chinese data ([chi square] (52) = 161.17, SRMR = .05, RMSEA = .08, CFI = .92). Deletion of either item made no significant difference to the overall model fit. The unconstrained subscale correlations, standardized estimates, and measurement error variances are presented in Figures 2 and 3 for the American and Chinese samples, respectively. Items' means, subscale means, and their standard errors are presented in Table 1. No differences were found between cultures for subscale means and total CAAS score (p > .45 in all three cases). The item correlation matrix for both samples is presented in Table 2.
Results indicated overall adequate fit for the combined data to the model ([chi square] (129) = 648.43, SRMR = .06, RMSEA = .08, CFI = .81) with error terms for CAAS items 3 and 4 allowed to correlate. However, the nested model comparison indicated significant differences between American and Chinese samples ([DELTA][chi square] (25) = 349.22, p < .001). It was also clear that significant differences existed at each level of analysis (i.e., measurement weights, intercepts, and structural covariances). Therefore, measurement weights, then measurement intercepts, and finally structural covariances were examined to identify potential differences. Constraints were removed systematically until a non-significant (p >. 10) chi square change was established at each level. By this method it was necessary to remove constraints on the measurement weight for CAAS item 8 (Officials' mistakes make me angry) and all but two of the measurement residuals (CAAS items 1 and 11 remained constrained). It was also necessary to remove the constraint that the covariance between the Anger and Aggressiveness factors be equal across cultures. The final model demonstrated good fit ([chi square] (117) = 315.96, SRMR = .05, RMSEA = .05, CFI = .93) and a non-significant chi square change ([DELTA][chi square] (13) = 16.74, p = .21).
The CAAS was developed out of a need for an effective scale that could discriminate non-aggressive from aggressive athletes (Maxwell & Moores, 2007a). Maxwell and Moores documented its sound psychometric properties in a British population, but stated that the CAAS would require additional testing in other sports and in different populations of athletes to further establish its utility. A similar call has been made in a critique of the CAAS' psychometric and theoretical foundation (e.g., Kerr, 2008) and thus formed the purposes for the current study. Results of confirmatory factor analyses of the CAAS indicated relatively poor fit for both the American and Chinese samples. Examination of the modification indices and inter-item correlations revealed that item 3 (I taunt my opponents to make them lose concentration) and item 4 (I verbally insult opponents to distract them) were highly correlated with similar error variances. Perhaps American athletes are similar to Chinese athletes and do not discriminate taunting from verbally insulting their opponents, which resulted in similar response patterns between items 3 and 4. When accounting for this in the factor structure (see Figure 1), satisfactory fit was obtained. Removal of either item did not improve model fit; therefore, Kerr's questioning of the inclusion of two verbal items in the aggressiveness subscale seems to be psychometrically insignificant, Values for Cronbach's alpha indicated good internal consistency across both the American and Chinese samples and are only marginally weaker than those reported by Maxwell and Moores (2007a).
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In order to claim measurement invariance across two (or more) groups, it is not sufficient to simply demonstrate similar factor structure in both independently. Current practice advises comparison of parameters, such as factor loadings and subscale correlations, across groups (e.g., Byrne, 2001, 2004). Execution of this recommendation indicated significant differences between the American and Chinese samples. In particular, the factor weight for item 8 of the CAAS (e.g., Officials' mistakes make me angry) was significantly different across groups and was consequently allowed to vary across groups. It is possible that Chinese athletes may be less inclined to become angry at officials or do not perceive their mistakes as commanding significant objection due to forbearance. To do so would disrupt the goal of forbearance which is to maintain harmony in stressful situations and control one's emotions. In this regard, it is also worth noting that the mean response for item 8 was lower in Chinese athletes. Numerous other differences between cultures were found for item means, such that only items 1 and 10 were constrained in the final nested model. Although this result may have suggested a potential bias in favor of one culture or the other, no clear pattern could be discerned.
Maxwell and Moores (2007a) reported a moderate correlation between the two subscales of the CAAS (see Figure 1). They suggested a relationship between the two constructs such that heightened aggressiveness may inflate the intensity of felt anger in response to provocation or perceived injustice (e.g., an official's mistake). In the current study, the correlation between subscales was higher in both the American and Chinese samples than was found originally by Maxwell and Moores (2007a). Further, the Chinese sample indicated the highest value, suggesting that the relationship between anger and aggressiveness is even stronger in these populations. These differences can likely be attributed to the composition of the samples. Maxwell and Moores' sample contained athletes from collision, contact, and non-contact sports, whereas the current samples contained only contact and collision sports. Therefore, it would not be surprising to find a weaker relationship between anger and aggressiveness for athletes participating in non-contact sports where the opportunity to become angry or behave aggressively may be less frequent or to which athletes who are naturally less aggressive may be attracted.
The differences for subscale and total scale means between the current samples and Maxwell and Moores' (2007a) British male contact athletes, is not easily explained. No differences were found between American and Chinese athletes for subscale and total scale scores, but both recorded higher means than Maxwell and Moores' sample of British male contact athletes (Aggressiveness M = 28.17, SD = 10.19; Anger M = 24.14, SD = 8.05). These results imply that American and Chinese athletes may be more aggressive than British athletes. With the exception of American football and wrestling, all three samples have athletes from similar sports (i.e., basketball, rugby, and soccer). Thus, while it might have been unsurprising if American athletes were more angry and aggressive than British athletes, it is very surprising that Chinese athletes should be also. Visek, Watson, et al. (in press) suggested that Chinese athletes may compensate for physical size with greater aggressiveness, but other research has shown lower aggression scores for Chinese athletes relative to British (Maxwell et al., 2005) and in Chinese non-athletes relative to American norms (Maxwell, 2007).
An alternative explanation resides in the assignment of item severity scores. Maxwell and Moores (2007a) noted that the severity ratings used to generate subscale (i.e., anger and aggressiveness) and total CAAS scores are general. A mixed sample of athletes from contact, collision, and non-contact sports was used to generate severity scores, and may vary across sports. When utilized in cultures and specific sports for which the item severity scores have not been normed, the CAAS may inadvertently be casting a bias on athletes' scores. For example, American and Chinese athletes may view certain acts as less severe than British athletes. The non-contact athletes used in Maxwell and Moores sample may have viewed certain acts as more severe than contact and collision athletes thus inflating severity scores. Using British norms might also inflate the American and Chinese means, if it is assumed that both of these populations rate the severity of items lower than their British counterparts. Future research should consider developing both cultural and sport-specific norms for the item severity ratings or at least demonstrating that they are invariant across cultures. Such norms would enable both sport scientists and sport psychology practitioners to better assess the anger and aggressiveness in athletes relative to their respective culture and sport. It should also be noted that item severity potentially undermines the validity of mean comparisons across cultures, but it does not alter the factor structure because it acts only as a simple scaling factor.
Overall, results support the use of the CAAS as a measure of anger and aggressiveness in American and English-speaking Hong Kong Chinese populations for sport psychology practitioners and researchers alike. The factor structure of the scale was generally replicated across cultures with only very minor modifications to the original structure. Continued efforts are required to fully validate the CAAS and explore its potential for the study of aggression in sport. Specifically, consideration should be given to the item severity scores of the CAAS and its relationships with observed athlete behavior. Through systematic study, the CAAS may be refined and improved so that it can be used to provide valuable and valid insights into the aggressive behaviors of athletes.
The collection of the Hong Kong data was supported by a Competitive Earmarked Research Grant (HKU7447/05H) by the Research Grants Council ofHong Kong awarded to the second author; and, collection of the American data was supported by grants from the West Virginia University Foundation and School of Physical Education awarded to the first author.
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Amanda J. Visek
The George Washington University
Jonathan P. Maxwell
The University of Hong Kong
Jack C. Watson II
West Virginia University
Jennifer R. Hurst
Truman State University
Address Correspondence to: Amanda J. Visek, The George Washington University Medical Center, School of Public Health and Health Services, Department of Exercise Science, 817 23rd Street NW, Washington DC, 20052. Phone: (202) 994-3997. Fax: (202) 994-1420. E-mail: firstname.lastname@example.org.
Table 1. CAAS Descriptives for the American and Chinese Samples American Chinese Item Item Description Mean (SD) Mean (SD) 1 I become irritable if I am 4.65 (1.61) 4.71 (l.31) disadvantaged during a match 2 I feel bitter towards my 4.92 (1.90) 4.30 (l.47) opponent if I lose 5 I show my irritation when 4.11 (1.77) 4.43 (l.58) frustrated during a game 8 Officials' mistakes make 5.75 (1.90) 5.42 (1.82) me angry 10 I get made when I lose points 5.71 (1.99) 4.62 (1.83) 12 I find it difficult to control 4.49 (2.36) 5.85 (2.40) my temper during a match Anger Subscale Total 29.62 (7.81) 29.33 (7.03) 3 I taunt my opponent to make 4.51 (2.28) 5.15 (2.02) them lose concentration 4 I verbally insult opponents 4.26 (2.38) 5.18 (2.14) to distract them 6 Opponents accept a certain 5.25 (1.85) 4.98 (1.74) degree of abuse 7 I use excessive force to gain 8.08 (3.19) 7.02 (2.83) an advantage 9 It is acceptable to use illegal 6.19 (3.47) 7.00 (2.88) force to gain an advantage 11 Violent behavior directed 6.84 (3.69) 6.68 (2.82) towards opponent is acceptable Aggressiveness Subscale Total 35.14 (11.79) 36.01 (10.62) Table 2. Inter-item Correlation Matrix for the American and Chinese Samples Item 1 2 3 4 5 6 1 -- .37 .20 .21 .33 .21 2 .36 -- .23 .25 .29 .18 3 .40 .35 -- .79 .40 .33 4 .36 .33 .62 -- .39 .32 5 .29 .28 .43 .43 -- .32 6 .32 .23 .36 .38 .35 -- 7 .35 .37 .46 .39 .33 .52 8 .29 .28 .25 .25 .27 .35 9 .30 .35 .45 .47 .35 .35 10 .41 .32 .36 .33 .47 .39 11 .33 .35 .38 .42 .43 .36 12 .37 .39 .41 .51 .40 .24 Item 7 8 9 10 11 12 1 .32 .35 .21 .30 .35 .34 2 .28 .27 .32 .37 .26 .32 3 .32 .26 .29 .18 .30 .36 4 .34 .26 .37 .18 .37 .42 5 .27 .34 .22 .31 .24 .52 6 .35 .24 .23 .25 .30 .30 7 -- .35 .32 .36 .52 .34 8 .37 -- .35 .42 .41 .41 9 .49 .37 -- .29 .47 .36 10 .42 .38 .39 -- .40 .29 11 .44 .25 .52 .46 -- .45 12 .34 .19 .50 .40 .58 -- Note. Inter-item correlation coefficients for the American sample appear above the diagonal and for the Hong Kong Chinese below the diagonal. All values are significant at p < .01
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|Author:||Visek, Amanda J.; Maxwell, Jonathan P.; Watson, Jack C., II; Hurst, Jennifer R.|
|Publication:||Journal of Sport Behavior|
|Date:||Jun 1, 2010|
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