Transformational leadership and task cohesion in sport: The mediating role of intrateam communication

Psychology of Sport and Exercise 14 (2013) 249e257

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Psychology of Sport and Exercise journal homepage: www.elsevier.com/locate/psychsport

Transformational leadership and task cohesion in sport: The mediating role of intrateam communication Matthew J. Smith a, *, Calum A. Arthur b, James Hardy b, Nichola Callow b, David Williams a a b

University of Chichester, Department of Sport and Exercise Sciences, Bishop Otter Campus, College Lane, Chichester, West Sussex PO19 6PE, UK Bangor University, Wales, Institute for the Psychology of Elite Performance, School of Sport Health and Exercise Sciences, George Building, Bangor, UK

a r t i c l e i n f o

a b s t r a c t

Article history: Received 26 March 2012 Received in revised form 1 October 2012 Accepted 2 October 2012 Available online 23 October 2012

Objectives: Little is known about the mechanisms that might mediate the relationship between transformational leadership behaviors and follower outcomes in the sporting domain. The purpose of this study was to examine whether intrateam communication mediated the effects of transformational leadership behaviors on task cohesion. Design/Methods: A cross-sectional study of university level ultimate frisbee players (N ¼ 199). Participants completed a measure assessing their perceptions of their captain’s transformational leadership behaviors. Post-competition, participants completed measures assessing perceptions of intrateam communication and task cohesion within their own team. Results: Multilevel analyses revealed intrateam communication to partially mediate the relationships between two of the transformational leadership behaviors and task cohesion. Conclusions: Intrateam communication is seen to be a mechanism that explains the relationship between transformational leadership and task cohesion. Overall, the results support and add to the range of positive effects associated with transformational leadership in sport, and are suggestive of interventions that may raise levels of team cohesion. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Communication Cohesion Sport Leadership Multilevel analyses

Transformational leadership is a relatively contemporary approach used to gain an understanding of leadership behaviors in sport. Transformational leadership involves the building of relationships with followers through personal, emotional, and inspirational exchanges, so that they are motivated to perform beyond the level of their normal expectations (Bass, 1985). A large body of evidence indicates that transformational leadership has a positive impact on a range of individual and group level outcomes, across a variety of domains, such as the military (e.g., Bass, Avolio, Jung, & Berson, 2003), education (e.g., Ross & Gray, 2006), and the public sector (e.g., Avolio, Zhu, Koh, & Bhatia, 2004). However, the transformational leadership literature is not without criticism. For example, Yukl (1999) described how transformational leadership is viewed as a key determinant of organizational effectiveness, but argued that the causal effects of leader behavior on the organizational processes that ultimately determine effectiveness are seldom examined in any detail. Team cohesion is an important variable in a variety of settings, including sport (Paskevich, Estabrooks, Brawley, & Carron, 2001). Theoretically and intuitively, it is apparent that highly cohesive, * Corresponding author. Tel.: þ44 (0)1243 816341; fax: þ44 (0)1243 816080. E-mail address: [email protected] (M.J. Smith). 1469-0292/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychsport.2012.10.002

unified teams are likely to work together more effectively and consequently perform better than less cohesive teams. Therefore, understanding how sports teams can become more cohesive is an important topic for researchers and sport psychology practitioners alike. Accordingly, the present study examined two variables proposed to predict cohesion; leadership behaviors and intrateam communication. The current research tests a proposition, articulated in Carron and Spink’s (1993) inputsethroughputseoutputs model of team building, that communication is a potential mechanism that might explain the processes through which leadership develops task cohesion. This research is underpinned by transformational leadership theory (Bass, 1985) and social exchange theory (Foa & Foa, 1974). Researchers have begun to address the understanding of how transformational leadership exerts an influence by examining potential mediating variables of the relationship between transformational leadership and follower outcomes. For instance, Kirkpatrick and Locke (1996) found self-efficacy beliefs mediated the relationship between transformational leadership and performance. In addition, Arnold, Turner, Barling, Kelloway, and McKee (2007) used a sample of health-care workers to investigate the relationship between transformational behaviors and psychological well-being, and found that the meaning ascribed to their work (over

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and above the extrinsic outcomes gained) mediated this relationship. Transformational leadership is also becoming a better understood phenomenon in the sporting context, where it has been shown to be associated with positive outcomes such as motivation and effort (Arthur, Woodman, Ong, Hardy, & Ntoumanis, 2011; Rowold, 2006) as well as group cohesion (Callow, Smith, Hardy, Arthur, & Hardy, 2009), and has also been discussed in some recent sport psychology book chapters (e.g., Chelladurai, 2007). However, only one study to date has explicitly examined transformational leadership using a mediational methodology. Charbonneau, Barling, and Kelloway (2001) found that intrinsic motivation mediated the relationship between transformational leadership and performance. If there are significant relationships between transformational leadership behaviors and individual or group outcomes in sport teams, it is important to understand the processes through which this occurs in order to develop a more complete understanding of the inner workings of transformational leadership (Bass, 1999). However, other than the work of Charbonneau et al. (2001), little is known about the mechanisms that could mediate the relationship between transformational leadership behaviors and follower outcomes in the sporting domain. For example, although previous literature has linked task cohesion with transformational leadership in a sport setting (Callow et al., 2009), no study has investigated potential mediators of this relationship. When relationships between independent and dependent variables are found, researchers should strive to identify the mediating variables that transmit these effects (MacKinnon, Fairchild, & Fritz, 2007), thereby providing a greater understanding of the relationship between variables. Therefore, the purpose of the current study was to expand on the work of Callow and her colleagues by examining whether perceptions of transformational leadership impact on task cohesion indirectly through intrateam communication. Transformational leadership behaviors and task cohesion Using the Differentiated Transformational Leadership Inventory (DTLI), Callow et al. (2009) examined the relationship between transformational leader behaviors and team cohesion. The DTLI, based on the conceptual models of Bass and Avolio (2005), and Podsakoff, MacKenzie, Moorman, and Fetter (1990), includes six distinct transformational behaviors: high performance expectations, appropriate role modeling, inspirational motivation, intellectual stimulation, individual consideration, and fostering acceptance of group goals and teamwork. Other researchers in sport (e.g., Arthur et al., 2011) and in the military (e.g., Hardy et al., 2010) have used the DTLI as a measure of transformational leadership as this conceptualization provides a more differentiated model than the Multifactor Leadership Questionnaire (MLQ-5X; Bass & Avolio, 2005). Of focus in the present study are three transformational leadership behaviors which Callow et al. found to positively predict task cohesion: individual consideration, where leaders show concern for their followers’ personal feelings and needs; fostering acceptance of group goals and teamwork, where leaders promote cooperation among their followers and encourage them to work together to develop and achieve team goals; and high performance expectations, where leaders express expectations for excellence and high quality on the part of followers. Callow et al. (2009) argued that individual consideration would predict task cohesion, as leaders who accommodate and respect players’ individual differences are likely able to blend their players’ talents into a cohesive working unit (Yukelson, 1997). Furthermore, it was suggested that through the process of involving players in the setting of team goals this would lead to higher levels of cohesion as players would work toward achieving these common goals.

Finally, the expected relationship between high performance expectations and task cohesion was justified via the Galetea effect (Eden & Ravid, 1982) through which expectations are transferred from leader to follower; thus, if leaders exhibit high performance expectations related to task aspects of cohesion, higher levels of cohesion are likely to be produced. As Callow and her colleagues found these three transformational leadership behaviors to predict task cohesion, the present study will focus on these specific behaviors and their relationship with intrateam communication and task cohesion. Intrateam communication and task cohesion Within the organizational psychology literature Dionne, Yammarino, Atwater, and Spangler (2004) presented a framework to better understand how transformational leaders might optimize team effectiveness. Crucial to the development of team performance were the mediating (teamwork) processes of communication and conflict management. For instance, Dionne et al. proposed that as individual consideration embodies attentive listening, addressing individuals’ needs, and establishing one-to-one relationships it ought to be a precursor to effective team communication. Within the physical activity and sport literature, communication has also been theorized to contribute to the cohesiveness of teams. For example, Carron and Spink’s (1993) conceptual model of team building, which is comprised of inputs, throughputs, and cohesion as an output, identifies communication to be a key process facilitating the bonding between group members. In their model, Carron and Spink theorize that group structures (e.g., leadership) influence group processes (e.g., communication) which in turn influence team cohesion. Empirical findings offer support for a positive relationship between communication and cohesion (e.g., Widmeyer & Williams, 1991). Although neither grounded in Carron and Spink’s framework nor transformational leadership theory, Hardy, Eys, and Loughead (2008) provide specific support for the mediating role of intrateam communication on the leadershipdtask cohesion relationship in a study of athlete leaders within interactive sports teams. Moreover, both Yukelson (2001) and Sullivan and Callow (2005) suggest communication to be central to the social dynamic of groups. However, much of the investigation of this complex social phenomenon suffers from a restricted operationalization of task oriented verbal instruction, disconnected to a firm theoretical backdrop (Sullivan & Feltz, 2003). Contrary to this summary statement, Sullivan and Feltz (2003), Sullivan and Callow (2005), and Sullivan and Short (2011) have developed communication assessment tools grounded within social exchange theory (e.g., Foa & Foa, 1974). Social exchange frameworks theorize human interactions to represent a series of exchanges between interacting parties for the long-term gain of resources. Such resources are described as commodities valued by those involved in the exchange process. Sports oriented research has identified that supportive consideration and appreciation between team members (termed acceptance) and conflict management are examples of commodities valued by team sport athletes and are thus captured via three subscales of the SECTS; acceptance, positive conflict, and negative conflict management. Furthermore, it is assumed that the most efficient manner through which to acquire resources is via mutual and reciprocal relationships. Using their social exchange oriented questionnaire, Sullivan and Feltz (2003) reported communication to be most consistently related to task not social cohesion; possibly reflecting the instrumental nature of sports teams and highlighting how communication reflecting the shared values of teams contributes to enhanced cohesiveness.

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Transformational leadership behaviors and intrateam communication

251

Method Participants

Given the social, developmental, and emotional emphasis of transformational leadership, leaders’ transformational behaviors are thought to influence followers’ values and attitudes (amongst other things) such as their internalization of the organizations’ moral values and collective orientation (Dvir & Shamir, 2003). Consequently it is likely that transformational leaders also impact on followers’ perceptions concerning social exchange oriented relationships with their team members; in turn, influencing intrateam interaction and communication. Furthermore, Dionne et al. (2004) state that the mediating (teamwork) processes of communication and conflict management are crucial to the development of effective performance within work teams and directly implicate transformational leadership behaviors as a precursor. For instance, Dionne et al. proposed that as individual consideration embodies attentive listening, addressing individuals’ needs, and establishing one-to-one relationships it ought to facilitate effective team communication. However it is noteworthy that there is general acceptance within the literature that certain transformational leadership behaviors place emphasis on different foci (e.g., individual vs. group, supportive vs. developmental, task vs. social). Consequently, given the socially related commodities valued by athletes, it is hypothesized that the socio-emotional oriented transformational leadership behaviors of individual consideration and fostering acceptance of group goals and teamwork ought to predict social exchange related values and communication resources. Conversely, the challenge oriented transformational leadership behavior of high performance expectations might not correlate with communication reflective of valued social resources. Summary and hypotheses The purpose of the present study was to examine the relationships between selected transformational leadership behaviors, intrateam communication, and task cohesion. More specifically, we placed a particular emphasis on the indirect effect of transformational leadership behaviors on task cohesion due to the mediating role of intrateam communication. In accordance with the theorizing of and empirical support provided by Callow et al. (2009), it was expected that the leader behaviors of high performance expectations, fostering acceptance of group goals and teamwork, and individual consideration would positively predict task cohesion. It was also hypothesized that socio-emotional transformational leadership behaviors (i.e., individual consideration and fostering acceptance of group goals and teamwork) would predict greater acceptance and positive conflict resolution as well as less negative conflict management. As such teams are better able to pool their resources within a socially supportive environment; thus, engendering stronger perceptions of task cohesion. Finally, consistent with previous research (e.g., Sullivan & Feltz, 2003; Sullivan & Short, 2011), intrateam communication was predicted to correlate with task cohesion. Specifically, the dimensions of communication acceptance and positive conflict were expected to have a positive relationship with task cohesion, and negative conflict was predicted to have a negative relationship with task cohesion. In summary, the following three specific hypotheses were developed; first, communication was expected to mediate the relationship between individual consideration and task cohesion; similarly communication was expected to mediate the association between fostering acceptance of group goals and teamwork and task cohesion. Finally, it was also hypothesized that communication would not mediate the relationship between high performance expectations and task cohesion.

The participants were players recruited from ultimate frisbee teams who had qualified for the British Universities and Colleges Sport (BUCS) Indoor National Finals, either in the open or women divisions. Ultimate frisbee was chosen as it is an interactive team sport, and one with which the present authors had data collection opportunities. Within the context of ultimate frisbee, there is not a separate coaching role: instead, the captain is recognized as the leader of the side and has overall responsibility for leading training sessions, devising tactics, and selecting the side. A total of 372 ultimate frisbee players from 51 teams were initially recruited. However, of these data 202 ultimate frisbee players were eligible for data analysis (see data analysis section for further details on eligibility). An additional three participants were removed from the study because they were the only athlete rating their captain and our chosen analyses required more than one participant per team. Thus, a final sample of 199 participants (male n ¼ 110, female n ¼ 89) from 48 teams (each captain had between 2 and 8 athletes rating them, mean ¼ 4.15 responders per captain) were used in the main data analysis. The mean age of the sample was 20.77 years (SD ¼ 2.03), and participants had played ultimate frisbee for an average of 1.66 years (SD ¼ 1.25) under their current leader. Measures Transformational leadership To assess perceptions of transformational leadership behaviors, the Differentiated Transformational Leadership Inventory (DTLI; Callow et al., 2009) was administered. The DTLI is an inventory that measures six transformational behaviors: (a) inspirational motivation1 (e.g., “My captain talks enthusiastically about what needs to be accomplished”); (b) appropriate role-modeling (e.g., “My captain leads from the front whenever he/she can”); (c) individual consideration1 (e.g., “My captain recognizes that different players have different needs”); (d) intellectual stimulation (e.g., “My captain challenges me to think about problems in new ways”); (e) high performance expectations (e.g., “My captain expects us to achieve high standards”); and (f) fostering acceptance of group goals and teamwork (e.g., “My captain develops a strong attitude and spirit among team members”). Each item from the inventory is scored on a five point Likert scale anchored by 1 (not at all) and 5 (all the time). Players were asked to complete the items from the individual consideration, high performance expectations, and fostering acceptance of group goals and teamwork subscales in relation to their team captain. Using a sporting population, Callow et al. (2009) reported support for the psychometric properties of the DTLI, and Arthur et al. (2011) found further support for the factorial and discriminant validity of this 6-factor model. For the current sample, Cronbach’s alpha coefficients for each of the three subscales exceeded .70. Intrateam communication The Scale for Effective Communication in Team Sports-British (SECTS-B; Sullivan & Callow, 2005) is an 18-item questionnaire

1 It is important to note that these behaviors are conceptual additions from the MLQ5X (Bass & Avolio, 2005), and as such contain a total of 3 items from MLQ-5X, and 3 items that have been modified from the original MLQ-5X items. All six items were reproduced by special permission of the Publisher, MIND GARDEN, Inc. www.mindgarden.com, from the “Multifactor Leadership Questionnaire for Research” by Bernard M. Bass and Bruce J. Avolio. Copyright 1995 by Bernard M. Bass and Bruce J. Avolio. All rights reserved. Further reproduction is prohibited without the Publisher’s written consent.

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assessing perceptions of intrateam communication. This multidimensional operationalization was originally developed by Sullivan and Feltz (2003) and included the four dimensions of acceptance, distinctiveness, positive conflict, and negative conflict. Sullivan and Callow (2005) carried out extensive validation procedures, including both exploratory and confirmatory factor analyses, in examining the factor structure of this scale with a sample of British athletes and found a 3-factor model to best fit the data. The three dimensions present in the British model were: communication acceptance, referring to the communication of consideration and support for individual team members (e.g., “.share thoughts with one another”); positive conflict, which refers to communication concerning interpersonal differences in a positive and productive way (e.g., “.work as a team to solve disagreements”); and negative conflict, referring to the communication of interpersonal differences in a confrontational and aggressive manner (e.g., “.personally criticize one another when we disagree”). All items begin with the statement “When our team communicates, we.”. Statements were scored on a 7-point Likert scale anchored by 1 (hardly ever) to 7 (very frequently). With respect to the current sample of athletes, the SECTS-B demonstrated acceptable internal consistency with Cronbach alpha coefficients of .77 for acceptance, .76 for negative conflict, and .80 for positive conflict. Team cohesion To assess team cohesion, the Group Environment Questionnaire (GEQ; Carron, Widmeyer, & Brawley, 1985) was used. The GEQ contains 18 items that measure the following four dimensions of task and social cohesion: attraction to group-task (e.g., “I do not like the style of play on this team”), group integration-task (e.g., “We all take responsibility for any loss or poor performance by our team”), attraction to group-social (e.g., “Some of my best friends are on this team”), and group integration-social (e.g., “Our team would like to spend time together in the off season”). Statements were scored on a 9-point Likert scale anchored by 1 (strongly disagree) to 9 (strongly agree). For the purpose of the present study, the two task dimensions were summed to provide a task-cohesion scale (Carron et al., 1985). Although some questions have been raised about the internal consistency of the GEQ subscales (e.g., Eys, Carron, Bray, & Brawley, 2007), numerous studies have supported the instrument’s content, concurrent, predictive, and factorial validity across a variety of groups and situations (see Carron, Brawley, & Widmeyer, 1998 for a review). The present study was concerned with task cohesion which demonstrated a Cronbach’s alpha coefficient of .81. Procedure Following institutional ethical approval, 54 team captains were approached at two national university ultimate frisbee competitions (BUCS Open National finals and BUCS Women’s National finals). We established verbally that the team captains were the true leaders of the side via certain criteria (i.e., they led trainings, devised strategies, and were the main communicator to the team). Three teams did not participate in the study as their current captain did not meet these criteria (for example, due to the usual captain being absent as a result of injury). After each captain had given permission for his/her team to participate in the study, the general purpose and nature of the study was explained to the players. Confidentiality of individual responses was assured in all cases, although players were informed that the captains would be provided with general (i.e., team level) feedback concerning their leadership behaviors (with feedback offered as an incentive for captains and teams to participate in the study). Players who volunteered to participate signed an informed consent form, completed demographic details (including email

address) and completed the DTLI. A week after completion of the DTLI the SECT-B and GEQ were sent to the players via email, with the request to return them to the researcher on completion as soon as possible. A total of 372 players completed the DTLI, and out of these 202 (54%) returned the remaining two measures via email within four weeks of them being sent. Thus, we were unable to control exactly when the second measures were completed. Significant and systematic differences on the demographic and leadership variables did not emerge between the final sample and those who failed to complete the second two measures. Analysis strategy Given that the current data consisted of two hierarchical levels, the athlete (Level 1) and the leader (Level 2), the nested nature of the data needed to be addressed in both the measurement and hypothesis testing. Multilevel confirmatory factor analyses (MCFA), where the within-group and between-group variance is modeled simultaneously, is regarded as an appropriate method to examine the factor structure of measurement models where the data are meaningfully nested (e.g., Muthén, 1989). In the current sample the item level intraclass correlation coefficients ranged from .06 to .36 suggesting that the data were meaningfully nested. Whilst MCFA is considered optimal it requires large level two samples, indeed Hox and Maas (2001) have suggested that the Level 2 sample size should be N  100 (i.e., 100 teams). However, in samples where the Level 2 N is considerably less than 100 then analyzing the pooled within-cluster covariance matrix effectively controls for the nested nature of the data (Hox & Maas, 2001; Muthén, 1989). Given the Level 2 N ¼ 48 in the current study, we adopted the recommendations of Muthén (1989), and Hox and Maas (2001) by imposing the TYPE ¼ COMPLEX command in Mplus 5.2 (Muthén & Muthén, 2007) with ordinal data. This controlled for the nested nature of the data and resulted in modeling the asymptotic within-teams covariance matrix, SW (Asparouhov & Muthén, 2006). This approach is consistent with that adopted by, for example, Myers, Beauchamp, and Chase (2011). The hypothesis testing phase of the research was analyzed using MLwiN (V. 2.1; Rasbash, Charlton, Browne, Healy, & Cameron, 2009). To assess whether it was appropriate to analyze the current data using a multilevel framework, the variance components of task cohesion, negative conflict, and positive conflict were examined. This involved calculating intraclass correlation coefficients, which define the proportion of between-group to total variance. The intraclass correlation for task cohesion, negative conflict, communication acceptance, and positive conflict were .19, .28, .14, and .10 respectively. This was deemed to be a meaningful amount of variance; therefore we adopted a multilevel framework (detailed in the results section) to examine the hypotheses. Centering decisions in multilevel analyses is a complex issue that has come under much scrutiny (e.g., Enders & Tofighi, 2007; Gavin & Hofmann, 2002). However, a full discussion of the technicalities of centering methods is beyond the scope of the current study; for a comprehensive discussion of centering in a sport context, please refer to Myers, Brincks, and Beauchamp (2010). Nonetheless, it is important to align centering decisions with the theoretical paradigm of the focal research question (Gavin & Hofmann, 2002). This is because the centering method adopted alters parameter estimation and interpretation of results. More specifically, in grand mean centering the Level 2 regression coefficients are adjusted for Level 1 predictors, or in other words, grand mean centering examines the effects of Level 2 predictors on an outcome after controlling for Level 1 predictors (Gavin & Hofmann, 2002). In contrast group mean centering removes group level variance from the Level 1 predictor. That is, group mean centering

M.J. Smith et al. / Psychology of Sport and Exercise 14 (2013) 249e257

provides a ‘pure’ estimate of Level 1 relationships because the between cluster variation has been removed from the estimate (Enders & Tofighi, 2007). In the current study we are primarily interested in Level 1 relationships (i.e., person level), as such we followed the recommendations of Enders and Tofighi that suggest when the substantive relationship of interest is at Level 1 then group mean centering is considered optimal. Consequently, group mean centering was adopted. Kreft and De Leeuw (1998) suggested that when conducting multilevel analyses, one needs to test whether the Level 1 predictors should be fixed or set random at Level 2. In the former case, it is assumed that the effect of the predictor on the outcome variable does not vary across the Level 2 units (i.e., leaders in our case), whereas a random effect implies the opposite. However, testing whether the variance at Level 2 is significantly different from zero is slightly problematic because the distribution of the estimated variance is only approximately normal. Consequently, Rasbash, Steele, Browne, and Goldstein (2009) recommend using the likelihood ratio test which compares a model where the Level 2 variances are constrained to 0 (fixed model) with a model where the Level 2 variances are free to vary (randomized model). The loglikelihood ratio is obtained from the two models, which is compared to a chi square distribution on 1 degree of freedom (when testing variance in intercept) and 2 degrees of freedom (when testing the variance in slopes). Following the testing of whether the Level 2 variances of both the intercept and slope should be randomized or fixed, multilevel mediation analyses were conducted; it is important to note that the calculation of the indirect effect in multilevel models is not always as simple as calculating the product of ab because in some specifications of multilevel models (e.g., random slopes model) the a and b coefficients may covary. Consequently, when calculating the indirect effect the covariance term (sa,b) needs to be added to the product of ab. However, in multilevel models where the a and b slopes are fixed the simple product term of ab is sufficient to quantify the indirect effect (Bauer, Preacher, & Gil, 2006). There are a number of different statistical procedures available to test the significance of the indirect effect. Bias corrected bootstrap techniques are considered the optimal method to test the significance of the indirect effect in non-nested data (Preacher & Hayes, 2004). However, there is currently no facility available to calculate bias corrected bootstraps in multilevel analyses. Consequently, we used the Monte Carlo Method for Assessing Mediation MCMAM (Bauer et al., 2006; MacKinnon, Lockwood, & Williams, 2004). To this end we used the Selig and Preacher (2008) calculator to estimate confidence intervals for the indirect effect using the MCMAM calculator. The confidence interval was set at 95% and 20,000 repetitions were specified.

253

scales used in the current study. The results revealed that the measurement model used in the current study demonstrated acceptable factor structure (c2 (614) ¼ 804.73, p < .01; RMSEA ¼ .04; CFI ¼ .96; TLI ¼ .95). The interfactor correlations ranged from .04e.96 (zero order r ranged from .33 to .77). The highest interfactor correlation was between communication acceptance and positive conflict. This raises some questions with regard to whether these two scales are empirically distinct at the measurement level. However, it is noted that the standard error was only .018 and thus the correlation does not encompass unity. Given that the central focus of the current research was not to develop a measure of communication we kept the measurement model consistent with the theoretical model. That is, the 3-factor communication model as proposed by Sullivan and Feltz (2003), Sullivan and Callow (2005), and Sullivan and Short (2011) was retained. None the less it is important to note that this large correlation is potentially problematic and future research should seek to further explore this measurement issue. Descriptive statistics, correlations, and alpha coefficients for all study variables are displayed in Table 1. Mean values for the variables are consistent with published data (e.g., Callow et al., 2009) and reveal that the ultimate frisbee captains made frequent use of the transformational leadership behaviors and were part of teams reporting to be reasonably cohesive indicating greater use of positive acceptance oriented as compared to negative conflict management communication. Prior to conducting the multilevel mediation analyses the loglikelihood ratio tests revealed that in all cases the random intercept fixed slope model best represented the data. In other words, the intercept significantly varied between leaders whereas slopes did not significantly vary across leaders. Consequently, in all analyses a random intercept fixed slope multilevel model was specified. The interested reader can obtain the results of the loglikelihood ratio tests by contacting the second author. The direct effects between the leader behaviors and task cohesion were all significant: individual consideration B1 ¼ .595 (SE ¼ .147), p < .01; fostering acceptance of group goals B1 ¼ .642 (SE ¼ .140), p < .01; high performance expectations B1 ¼ .468 (SE ¼ .161), p < .01. Hypothesis 1. The relationship between individual consideration and task cohesion will be mediated by communication. Multilevel analyses with communication acceptance conceptualized as the mediator revealed that the a path (individual consideration to communication acceptance; B1 ¼ .513, SE ¼ .113, p < .01) and b path (communication acceptance to task cohesion; B1 ¼ .803, SE ¼ .081, p < .01) were both significant and positive. The 95% confidence interval for the indirect effect excluded zero (CI ¼ .230, .611) indicating that the indirect effect was significant. Similarly, when positive conflict was entered as the mediator the a path (B1 ¼ .363, SE ¼ .123, p < .01), the b path (B1 ¼ .680, SE ¼ .083, p < .01) and the 95% confidence interval excluded zero (CI ¼ .079, .431) indicating that the indirect effect was significant. Conversely,

Results The measurement model was examined by conducting an omnibus confirmatory factor analysis including all measurement

Table 1 Means, standard deviations, zero order correlations, and alpha coefficients in parenthesis.

1. 2. 3. 4. 5. 6. 7. 8. 9.

Age Time with leader Individual consideration Fostering acceptance goals High performance expect. Communication acceptance Positive conflict Negative conflict Task cohesion

*p < .05; **p < .01.

Mean

SD

1.

20.77 1.66 3.96 4.22 4.06 5.51 5.15 2.89 6.96

2.03 1.25 0.65 0.70 0.66 0.88 0.90 1.06 1.16

e .41** .18* .20** .23** .11 .11 .13 .18*

2.

3.

4.

5.

6.

7.

8.

9.

(.82) .60** .32** .43** .25** .22** .35**

(.77) .45** .47** .32** .25** .47**

(.78) .21** .15* .01 .35**

(.82) .77** .38** .70**

(.80) .33** .63**

(.76) .31**

(.81)

e .02 .11 .04 .02 .06 .02 .03

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when negative conflict was included as the potential mediator a different pattern of results emerged as the a path (individual consideration to negative conflict; B1 ¼ .238, SE ¼ .132, p > .05) was non-significant, the b path was significant (B1 ¼ .328, SE ¼ .091, p < .01). Thus, whilst negative conflict was shown to negatively predict task cohesion, individual consideration did not predict negative conflict. Furthermore, the 95% confidence interval for the indirect effect included zero (CI ¼ .011, .0338). Consequently no evidence of mediation was provided when negative conflict was hypothesized as the mediator. Hypothesis 2. The relationship between fostering acceptance of group goals and teamwork and task cohesion will be mediated by communication. Multilevel analyses with communication acceptance as the mediator revealed that the a path (fostering acceptance of group goals and teamwork to communication acceptance; B1 ¼ .5.32, SE ¼ .108, p < .01) and b path (communication acceptance to task cohesion; B1 ¼ .803, SE ¼ .081, p < .01) were both significant and positive. The 95% confidence interval for the indirect effect excluded zero (CI ¼ .246, .621) indicating that the indirect effect was significant. Similarly, when positive conflict was entered as the mediator the a path (B1 ¼ .438, SE ¼ .117, p < .01), b path (B1 ¼ .680, SE ¼ .083, p < .01) and the 95% confidence interval excluded zero (CI ¼ .134,

.483) indicating that the indirect effect was significant. When negative conflict was included as the potential mediator a similar pattern of results emerged, the a path (B1 ¼ .326, SE ¼ .126, p > .01) and b path (B1 ¼ .328, SE ¼ .091 p < .01) were both significant and negative. Furthermore, the 95% confidence interval for the indirect effect excluded zero (CI ¼ .021, .222). The results demonstrated that the relationship between fostering acceptance of group goals and task cohesion is mediated by communication acceptance, and positive conflict and negative conflict. Hypothesis 3. The relationship between high performance expectations and task cohesion will not be mediated by communication. Collectively the results supported the above hypothesis. Although high performance expectations were significantly and positively related to task cohesion, B1 ¼ .468, SE ¼ .161, p < .01, this transformational leadership behavior was not significantly associated with communication acceptance (B1 ¼ .048, SE ¼ .129, p > .05), positive conflict (B1 ¼ .080, SE ¼ .135, p > .05) nor negative conflict (B1 ¼ .101, SE ¼ .142, p > .05). Furthermore, all of the confidence intervals for the indirect effects included zero (CI ¼ .164, .241; .127, .238; .059, .141) for communication acceptance, positive conflict and negative conflict respectively. Details of all the mediation analyses can be found in Table 2.

Table 2 Multilevel mediation analyses for all study hypothesis. Mediator Hypothesis 1 Individual Consideration Group Level variability Individual Level variability Hypothesis 2 Fostering acceptance group goals Group Level variability Individual Level variability Hypothesis 3 High performance expectations Group level variability Individual level variability

Communication acceptance a path B SE .513** .108 .133** .059 .578** .066

b path B .803** .378** .655**

SE .081 .113 .075

CI (lower) 0.230

CI (upper) 0.611

.532** .136** .566**

.108 .059 .065

.803** .378** .655**

.081 .113 .075

0.246

0.621

.048 .115** .655**

.129 .059 .075

.803** .378** .655**

.081 .113 .075

0.164

0.241

.363** .094 .688**

.123 .056 .079

.680** .351** .747**

.083 .113 .086

0.079

0.431

.438** .099 .666**

.117 .056 .076

.680** .351** .747**

.083 .113 .086

0.134

0.483

.080 .084 .726**

.135 .056 .083

.680** .351** .747**

.083 .113 .086

0.127

0.238

.238 .317** .785**

.132 .108 .090

.328** .279* .999**

.091 .111 .115

0.011

0.338

.326** .321** .767**

.126 .108 .088

.328** .279* .999**

.091 .111 .115

0.021

0.222

.101 .314** .799**

.142 .108 .092

.328** .279* .999**

.091 .111 .115

0.059

0.141

Mediator Hypothesis 1 Individual Consideration Group level variability Individual level variability Hypothesis 2 Fostering acceptance group goals Group level variability Individual level variability Hypothesis 3 High performance expectations Group level variability Individual level variability

Positive conflict

Mediator Hypothesis 1 Individual consideration Group level variability Individual level variability Hypothesis 2 Fostering acceptance group goals Group level variability Individual level variability Hypothesis 3 High performance expectations Group level variability Individual level variability

Negative conflict

*p < .05; **p < .01. a path denotes independent variable and mediator variable. b path denotes mediator variable and dependent variable.

MCMAM

M.J. Smith et al. / Psychology of Sport and Exercise 14 (2013) 249e257

Discussion The purpose of the present study was to further examine the relationship between transformational leadership and task cohesion, by focusing on intrateam communication as a potential mediator of this relationship. Taken together, the results indicate that intrateam communication mediates the relationship between selected transformational leader behaviors and task cohesion. However, the specific nature of this relationship is impacted on by which transformational leader behavior is included as the independent variable and by the nature of communication. Namely, whilst high performance expectations was shown to be significantly related to task cohesion it was not related to any of the sub-dimensions of communication. Furthermore, negative conflict was shown to only mediate the relationship between fostering acceptance of group goals and task cohesion. Taken together, the results support the current body of knowledge demonstrating that transformational leader behaviors directly relate to group outcomes such as cohesion, and extend this knowledge by highlighting a mechanism (i.e., intrateam communication) by which leadership behaviors are associated with task cohesion. Specifically, as expected the results revealed that the three transformational leader behaviors of individual consideration, fostering acceptance of group goals and teamwork, and high performance expectations, were all significantly related to task cohesion. This is in line with previous research that has found a positive relationship between transformational leadership and cohesion in military units (Bass et al., 2003) and in sports teams (Callow et al., 2009). Furthermore, the results of the present study reinforce the findings of Callow and her colleagues, as the same three transformational leadership behaviors had significant positive relationships with task cohesion. Similarly, as expected, intrateam communication was related to task cohesion, with communication acceptance and positive conflict displaying a significant positive relationship, and negative conflict a significant negative relationship with task cohesion. These results replicate the findings of Sullivan and Feltz (2003) and Sullivan and Short (2011), where the same significant directional relationships were gained for a sample involving a variety of sports teams from different levels of performance. These results also support the findings of ethnographic research where fluctuations in positive and negative communication influenced task aspects of cohesion through the course of a soccer season (Holt & Sparkes, 2001). In terms of the relationships between the three intrateam communication resources and the three transformational leadership behaviors, as expected only the socio-emotional supportive behaviors of individual consideration and fostering acceptance of group goals were significantly correlated with social exchange based communication. Indeed, there was no significant relationship between high performance expectations and communication. However, of the socio-emotional supportive relationships, individual consideration had a significant (positive) relationship with positive communication but no significant relationship with negative conflict, whereas fostering acceptance of group goals had significant positive relationship with communication acceptance and positive conflict, but had a negative relationship with negative conflict. Taken together, these results support the predicted relationship between transformational leadership behaviors and communication (Dionne et al., 2004). Yet, more importantly, when these results are interpreted in the context of the mediational hypotheses, the current findings extend the literature by highlighting a mechanism by which transformational leadership might be associated with task cohesion. In particular, the mediational analyses revealed that both communication acceptance and positive conflict mediated the

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relationship between individual consideration and task cohesion; communication acceptance, positive conflict, and negative conflict mediated the relationship between fostering acceptance of group goals and task cohesion, with the latter relationship being negative. In finding intrateam communication as a mediating variable, these results extend the work of Callow et al. (2009) by identifying a mechanism through which transformational behaviors exert an influence on task cohesion. However, we only included one potential mediator of the leadershipecohesion relationship. Indeed, Carron and Spink’s (1993) conceptual model of teambuilding also includes team sacrifices as a potential antecedent of cohesion. It is plausible to suggest that, as a result of the leader’s high performance expectations, commitment to the group would increase (Korek, Felfe, & Zaepernick-Rothe, 2010) with individual members making personal sacrifices (Powell & Van Vugt, 2003), and in turn cohesiveness would be enhanced (Prapavessis & Carron, 1997). Thus, further research should continue to meet the call of theorists (e.g., Bass, 1999) to examine how transformational leadership behaviors operate by investigating the role of commitment and sacrifice behavior as potential mediators of the transformational leadership to cohesion relationship. The results of the present study revealed the communication dimension of negative conflict to have a negative relationship with task cohesion. However, negative conflict only mediated the relationship between transformational leadership and task cohesion in the case of fostering acceptance of group goals and teamwork. This finding suggests that the absence of high performance expectations and individual consideration does not predict negative conflict, thus it might be that some form of negative leader behavior may predict this negative aspect of communication. This is an interesting issue, as in the main, the transformational leadership literature principally focuses on leadership behaviors that have a positive impact on individual and group functioning. In this study, we chose to use the Differentiated Transformational Leadership Inventory (DTLI; Callow et al., 2009) which is principally based on Podsakoff et al.’s (1990) conceptualization of transformational leadership behaviors, and includes seven positive behaviors. Other conceptualizations involving transformational leadership include negative aspects of leadership. For example, laissez-faire leadership is one of the three typologies of leadership behavior in the ‘fullrange leadership theory’ proposed by Avolio and Bass (1991). A leader who adopts a laissez-faire approach avoids making decisions, abdicates responsibility, and does not use their authority (Antonakis, Avolio, & Sivasubramaniam, 2003). Future research might therefore include follower perceptions of negative leader behaviors to examine the antecedents of the communication dimension of negative conflict. From an applied perspective, interpretation of the results leads to the suggestion that, if sporting leaders want develop task unity within their teams, they might focus on developing their leadership behaviors of individual consideration, fostering acceptance of group goals and teamwork, and high performance expectations, while enhancing positive communication and reducing negative conflict of their performers. However, it is acknowledged that the present study is correlational in nature and causality cannot be implied. Thus longitudinal intervention studies should be conducted, not only to explore causality, but also to establish if these leadership behaviors can actually be trained. Toward this end previous experimental studies (e.g., Barling, Weber, & Kelloway, 1996; Dvir, Eden, Avolio, Bass, & Shamir, 2002; Hardy et al., 2010) have demonstrated that transformational leadership behaviors can be trained. Therefore, a viable suggestion to improve intrateam communication and task cohesion would be to train the specific transformational leadership behaviors that have been found to predict these variables.

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While a number of different conceptualizations of transformational leadership exist in the literature, the majority of the research employed the Multifactor Leadership Questionnaire and its variant forms. Similarly, some of the early research in sport used the MLQ-5X (e.g., Charbonneau et al., 2001; Rowold, 2006). However, more recent research in the sporting domain has used a differentiated sport specific model of transformational leadership (Arthur et al., 2011; Callow et al., 2009). An advantage of a differentiated approach is that researchers are able to provide specific theoretical rationale for each of the separate transformational leader behaviors thus providing an opportunity for enhanced precision when theorizing. Furthermore, the literature that has adopted a differentiated approach to transformational leadership has generally demonstrated that the separate behaviors differentially predict outcomes (see for example, Arthur et al., 2011; Callow et al., 2009; Hardy et al., 2010; Podsakoff, MacKenzie, & Bommer, 1996; Rafferty & Griffin, 2004). Consistent with these studies the results of the current study demonstrated that different transformational leader behaviors have different relationships with outcomes, namely that high performance expectations does not appear to be related to intrateam communication. From an applied perspective being able to offer feedback to coaches based on the separate behaviors rather than transformational leadership as a whole will provide opportunities for greater precision when delivering interventions. The high interfactor correlation between positive conflict and communication acceptance and that these constructs could not be differentiated based on either their antecedents or predictive relationship brings into question the discriminate validity of the SECT-B. That is, the scales under scrutiny may not measure different or unique underlying constructs (resources). Interestingly, although interfactor correlations were not provided by Sullivan and Feltz (2003) and Sullivan and Short (2011), the zero-order correlations between the positive conflict and acceptance factors were r ¼ .52 and r ¼ .68 respectively, indicating that the high interfactor correlation may not be unique to the present study nor to the British version of the SECT. Given that validation is an on-going process not an end point (Carron et al., 1998), future research should further explore the SECT-B in terms of the theoretical distinctiveness of the two resources in question, the appropriateness of the items that measure them, and its discriminate validity. None the less, the questionable dimensionality of the SECT-B is a limitation of the current study. A strength of the current research is the use of multilevel modeling in both the measurement and hypothesis testing phases. This allowed for the control of non-independence and the exploration of individual and group level effects. The degree of confidence in the present findings is further strengthened by the study’s short-term prospective design. More specifically, the separation between data collection points created a temporal and locational separation which reduces the potential effects of common method variance (cf., Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). However, it should be noted that we were not able to control exactly when the second measures were completed, and the variation in time between participants completing the two sets of instruments is a limitation of the design. Another potential limitation of the study concerns the use of the “we” stem to measure intrateam communication, as this wording might have impacted on the predictive relationships between communication perceptions and the different constructs of the cohesion measure. With a global index of task cohesion used in the present study not accounting for this potential divergence in effects, future research might use other methods to measure communication and cohesion. A further limitation of the study concerns the nature of the sample employed. Although we deliberately utilized a closely matching sample to that

used by Callow and colleagues, its restriction to a single sport (ultimate frisbee) and competitive level (varsity) might raise issues regarding the generalizability of the results. Future research should explore the generalizability of the results with a more heterogeneous sample. In summary, the results of the present study extend our understanding of the correlates of transformational leadership behaviors. The findings suggest that the transformational behaviors of individual consideration and fostering acceptance of group goals and teamwork indirectly predict task cohesion, and in isolating intrateam communication, we identify a mediator of this relationship not addressed in previous research. In addition, using the differentiated model of transformational leadership allowed identification of specific leadership behaviors that predict both intrateam communication and task cohesion. 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