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The Differential Effect of Team Cohesion and Leadership Behavior in High School Sports

The Differential Effect of Team Cohesion and Leadership Behavior in High School Sports Nicholas P. Murray* East Carolina University *Nicholas P. Murray; East Carolina University; Department of Exercise and Sport Sciences; 383 Ward; Greenviile, North Carolina27858; murrayni@mail.ecu.edu (email). ABSTRACT - The Murray - Team Cohesion & Leadership 217 1991). Despite this research, the relationship of team cohesion, coaching behavior and performance as measured by win/loss record is less clear. In this study, the focus is to clarify this relationship, and to examine these variables as they relate to situational differences in high school sports. Team sports also provide a unique opportunity to study team success and team cohesion in a realworld situation. Chelladurai and Carron (1978) developed a sport-specific model of leadership called the Multidimensional Model of Leadership (MML). The MML's basic tenet is that group performance and team satisfaction are the products of the congruence ofthe three states of leader behavior: required, preferred and actual. Required leader behavior is behavior expected ofthe leader by the demands of the parameters of the organization and its environment. Preferred leader behaviors are those behaviors that members would like to see in their leaders. These behaviors are a function of the members' characteristics and the situational characteristics. The actual leader behavior is influenced by the leader's characteristics including personality, ability and experience. Several studies have attempted to examine the theoretical relationship between either an antecedent (e.g. Chelladurai & Carron, 1983; Weiss & Friedrichs, 1986) to leadership or consequences (Boone, Beitel, & Kuhlman, 1997; Home & Carron, 1985; Serpa, Pataco, & Santos, 1991; Westre & Weiss, 1991) of leadership behavior. To quantify the MML, Chelladurai & Saleh (1980) developed the Leadership Scale for Sport (LSS). The LSS is a sport-specific measure, which consists of five dimensions of leader behavior - training and instruction, positive feedback, democratic behavior, autocratic behavior, and social support. Train and instruction is related instructional behaviors towards task accomplishment. Democratic and autocratic behaviors refer to social process of decision-making. Positive feedback and social support refer to the motivational tendencies ofthe coach and concem for the personal needs ofthe athletes (Chelladurai, 1985). The LSS has three different versions: the athletes' perception of their coaches' behavior; the athletes' preference for coaching behavior and the coaches' perception of their own behavior. In 1982, Carron developed an operational definition that describes group cohesion as a multidimensional entity. Carron proposed that cohesion has both task and social properties that comprise both individual and group aspects. In developing a multidimensional model of group cohesion, he further proposed both antecedents and consequences ofgroup cohesion. The antecedents ofgroup cohesion were placed into four categories: (1) leadership (2) situational (3) personal, and (4) team factors (Brawley, 1990). The consequences were identified in two categories: (1) individual and (2) group outcomes. Subsequently, in 1985, Carron, Widmeyer, and Brawley developed the Group Environment Questionnaire (GEQ) to quantify group cohesion as a multidimensional property. Since that point, there has been a considerable 218 Murray - Team Cohesion & Leadership amount of research dedicated to understanding the relationship of cohesion to many group related factors such as group size (Widmeyer, Brawley, & Carron, 1992), group performance (Williams & Widmeyer, 1991), sport interaction level (Matheson, Mathes, & Murray, 1997), and coaching behavior (Westre & Weiss, 1991) to name a few. Leadership, Cohesion and Performance Gardner et al. (1996) described the importance of studying the relationship of leader behavior, cohesion and performance relationship. There are two current issues, which need further consideration. First, group cohesion is hypothesized to positively influences performance (Widmeyer & Williams, 1991). But the majority of research has shown only a modest positive relationship between cohesion and performance (Mullen & Copper, 1994). However much of this research is done on non-sport teams or laboratory created groups. Research conducted on actual sport teams with the team performance being the unit of measurement the relationship strengthens. A recent effort by Carron, Bray and Eys (2002) compared elite basketball and soccer teams and demonstrated a strong positive relationship between cohesion and team success. Carron et al (2002) made two significant changes in methodology that lead to their conclusions. First, the team was used as the unit of analysis rather than the individual. To often in published work on cohesion the unit of measure has been the individual rather than the team. This is often cited as one of the flaws of group cohesion research (Carron & Spink, 1995). Second, they used team success as the dependent variable as it a cumulative measure of the team's efforts. With this notion in mind, there are relatively few studies that address this issue (Gardner et al., 1996; Pease & Kozub, 1994; Shields, et al., 1997; Westre & Weiss, 1991). Gardner et al. found a significant relationship of all five coaching behaviors to both social and task cohesion. However, Westre and Weiss (1991), and Pease and Kozub (1994) found that the leader behaviors of training and instruction, democratic style, social support and positive feedback were all positively related to cohesion. The autocratic scale was removed from analysis due to poor intemal consistency. Westre and Weiss also found that perceptions of team and individual success strongly related to coaching behavior and team cohesion. Shields et al. (1997) examined team cohesion as it relates to the three individual versions ofthe LSS. The perceived LSS version and the perceptual discrepancy scores (calculated from the difference between perceived and preferred versions) were most strongly related team cohesion. Multiple Time-point Measurement While these studies found significant relationships in the cohesion leadership relationship, all the studies examined cohesion fi-om a single time-point measurement. As Brawley (1990) points out, this is another pitfall in cohesion research. Using only a single time-point research, this ignores how cohesion Murray - Team Cohesion & Leadership 219 changes over time, and is dependent on the performance level ofthe team at the time of measurement (Boone et al., 1997; Matheson et al., 1997). Furthermore, since this study examines high school athletes, as did Westre and Weiss, it is possible that these athletes will have some level of cohesion developed at the beginning ofthe season. Many varsity level athletes may have years of playing time with fellow teammates and developed a cohesive group irrespective ofthe coaches' influence. Situational Differences Different sports require differing levels of interaction or interdependence among athletes to achieve success. The general distinction of sport interdependence is divided into two categories: coactive or interactive. Sports that require little interaction among team members for success exemplify low need for interdependence and are coactive in nature. Sports that require considerable interaction among team members for success exemplify high need for interdependence and are considered interactive in nature. There are, of course, varying degrees on the coactive to interactive continuum. Sports that require more coordination and cooperation should require greater task cohesion for team success. Soccer is a highly interdependent sport and should require high task cohesion for success. Baseball is a moderately interdependent sport, which requires less task cohesion for success. It has been shovra that cohesion is possible and beneficial in coactive sports (Widmeyer & Williams, 1991), but the amount of task cohesion needed should increase as the interdependence increases. In other words, the more athletes depend on each other for success the greater their task cohesion will need to be. Based on the theoretical and practical perspective described previously, the following three assumptions are made. First, leadership and cohesion are affected by the situation differences and are related to performance. Second, cohesion is dynamic process and it changes throughout the season. Thus it must be examined using multiple time-point method. Third, leadership is an antecedent to cohesion, and leadership behavior contributes to the development of cohesion. Based on these assumptions and previous leadership/cohesion research, the hypotheses in this study were: 1) higher scores on training and instruction, democratic behavior, positive feedback and social support will be positively related to higher task and social cohesion; and 2) both task and social cohesion will change over time. Soccer teams will require greater amounts of task and social cohesion for success than baseball teams. Method Participants Three hundred and twenfy male varsify high school soccer and baseball players participated in the study. All of the players had obtained a permanent 220 Murray - Team Cohesion & Leadership position on the varsity team. The teams played in the top two division levels in high school athletics, and the majority of teams played in highly competitive leagues. This study began with twenty teams, but two teams dropped out because of scheduling and end of season competition conflicts. Thus, eighteen teams were used from ten different high schools - nine soccer teams and nine baseball teams. The average size for the soccer teams were 20.75 players, and the average size for the baseball teams was 16.25 players. The players ranged in age from 14 to 18 years with an average of 16.8 years. The high schools' respective county school administrative offices were contacted by phone to gain permission to use their high school athletes in this study. Each gave approval contingent on the head coaches' approval. All athletes read and signed an informed consent form prior to participating in the study. Measures Two instruments were used in the study: the Leadership Scale for Sport (LSS, Chelladurai & Saleh, 1980) and the Group Environment Questionnaire (GEQ, Carron, Widmeyer, & Brawley, 1985). Performance was measured as wins and losses over the season. The LSS measures five dimensions of leadership behavior - training and instruction (TI), democratic behavior (DB), autocratic behavior (AB), social support (SS) and positive feedback (PF). The LSS comes in three versions: the athlete's preference for coaching behavior, the athlete's perception for coaching behavior and the coaches' perception of their own behavior. The athletes in this study only completed the athlete's perceived coaching version. The athlete's perception version of LSS contains forfy items prefaced by "My coach...", and is followed by statements such as "sees to it that athletes work to capacity". Each it is scored on a 5-point Likert-type scale ranging from "always" to "never". There are thirteen items for TI, nine items for DB, five items for AB, eight items for SS and five items for PF. The psychometric properties ofthe LSS have been demonstrated in several studies (for a review see Chelladurai, 1990). The GEQ assess the four dimensions of team cohesion - Individual Attraction to group-task (ATG-T), Individual Attraction to Group-Social (ATG-S), Group Integration-Task (GI-T), and Group Integration-Social (GI-S). The questionnaire contains 18 items that are scored on a 9-point Likert-type scale ranging from "strongly agree" to "strongly disagree". Each item is either positively stated or negatively stated. The questionnaire has five items for ATG-S, four items for ATG-T, five items for GI-T, and four items for GI-S. The score for each category is calculated by summing the values and dividing by the number items in that category. Procedure The GEQ was first administered prior to the first game, but after the final cuts were made and the coach had chosen his permanent roster. The GEQ was given Murray - Team Cohesion & Leadership 221 either prior to their practice or immediately following. There was no mention of the nature ofthe study, but each group was instructed to answer each question openly and honestly as they could, and they were also instructed not to consider questions together. The second administration ofthe GEQ and the administration ofthe LSS occurred immediately following the end of regular season and before post-season play began. The athletes were asked to indicate their coach's actual behavior when filling out the LSS. Individuals who were not present at the first administration of the GEQ were asked not to fill out the GEQ (second administration) or the LSS. Only three athletes were not included in the sample. Results Scale Reliabilities The LSS intemal consistency scores have generally been acceptable with the exception ofthe autocratic behavior scale. In the present study, Cronbach's alpha coeffient was utilized to examine the internal reliability of both scales. The intemal reliability for the LSS and the GEQ is represented in Table I. Table 1 Internal Reliability Scores for the LSS and the GEQ LSS Scale Training and Instruction Democratic Behavior Autocratic Behavior Social Support Positive Feedback GEO Cronbach's Alpha .87 .85 .68 .84 .86 ATG-T .71 ATG-S .78 GI-T .82 GI-S .80 Multivariate Regression Analysis To examine the relationship among leader behaviors and team cohesion, a multivariate multiple regression and a canonical correlation were conducted. The initial test used both soccer and baseball teams as the unit of analyses. The overall multivariate relationship revealed a significant relationship between leader behavior and team cohesion, Wilks lambda = .735, F(20, 512) = 2.4779, p < .0004. Using the canonical correlation to determine which specific variables contributed to the relationship, there were three leader behaviors that had a loading greater than .30, which according to Pedhazur (1982) determines significant contribution to the multivariate relationship. Positive feedback (.88), training and instruction (.87) and social support (.49) leader behaviors contributed to the overall relationship. All four cohesion measures were found 222 Murray - Team Cohesion & Leadership to be significant contributors with ATGS (.78), ATGT (.62), GIS (.69) and GIT (.88). This result supports previous research (e.g., Westre & Weiss, 1991) in that there is a significant relationship between coaching behavior and team cohesion in high school soccer and baseball teams. The analyses suggest that soccer and baseball coaches who rated highest in positive feedback and training and instruction had athletes who reported higher levels of task and social cohesion. Multivariate Analyses To test changes in cohesion across a season a 2 X 2 MANOVA (Sport X Session) with repeated measures on the second factor was used to evaluate if time and sport had an effect on cohesion. Results indicated a significant main effect for sport Wilks' lambda = .96, F(l, 150) = 6.0152p < .05). Time had no significant effect on cohesion. The univariate analyses for GI-T and ATG-T revealed a significant main effect (p < .01). The baseball teams indicated lower scores on GI-T and ATG-T cohesion scales (see Table 2). There were no other significant main effects or interactions. Table 2 Overall Cohesion Means and Univariate Fsfor Soccer and Baseball Teams GI-T ATG-T GI-S ATG-S Soccer 6.868 6.45 5.20 4.75 Baseball 4.75 3.86 4.11 4.26 Univariate Fs 12.35* 6.06* 2.61 1.26 Logistic Regression Cohesion, Leadership and Performance. Since performance was measured as win/loss, a logistic regression was utilized to determine the percent of variance in the dichotomous dependent variable explained by the independents. Because there were no significant difference between the first measure of cohesion and the second, averaged cohesion scores were used in the logistic regression. The model was run using sport, task cohesion (GI-T and ATG-T), social cohesion (GIS and ATG-S), leadership (L), sport/leadership interaction (Sport/L) with performance as the dependent variable. The variables that contributed significantly to the model were sport, task cohesion and the sport/cohesion interaction. Two equations represent the relationship of performance and cohesion. Baseball equation is as follows: Murray - Team Cohesion & Leadership 223 y p. . =12.128-O.iO81(GT-T) , and the soccer is as follows: = -l +00264 (GT-T) .Where ''^^X-/'C^) is the odds of performance. The equations demonstrate that soccer teams who do better tend to be more task cohesive, and baseball teams who do better tend to be less task cohesive. Leadership and social cohesion were excluded fi-om the model due to a lack of significance. Discussion The purpose of this study was to determine the directional relationship among leader behavior, cohesion and performance in high school sport teams. The first hypothesis was partially supported in that higher levels of task and social cohesion were related to higher levels positive feedback, training and instruction, and social support. Democratic behavior was found not to contribute significantly to the model as previous research has shown (e.g. Gardner et al., 1996; Westre & Weiss, 1991). The second hypothesis considered cohesion as dynamic process, and changing over time. This hypothesis was not supported. This result could be due to the nature of high school athletics. Many times these athletes have been playing together for years, and they will play several different sports together throughout the school year. Entering the season some level of cohesion will have already been developed and be more resilient to change. Furthermore, baseball teams and soccer teams differed on the level of task cohesion. Soccer teams indicated higher levels of GI-T and ATG-T. The task demands of soccer promote and require a greater amount of task cohesion. The final hypothesis was supported through the logistic regression in that the successful soccer teams tend to be more task cohesive, and conversely successful baseball teams tend to be less task cohesive. Leadership and social cohesion were excluded due to a lack of fit in the model. Soccer is a sport that takes more coordination and cooperation to be successful. It is more difficult to be on the field and not be in the play whereas in baseball it is possible to be in the game and not effect the results at all. In addition, in high school athletics, a baseball team can be successful through the skills of two or three great players. Overall, this study supports the notion that there is a significant relationship exists between leader behaviors and team cohesion. Specifically, coaches who rated highest in training and instruction, and positive feedback had teams with higher task and social cohesion. Although there was a significant relationship, the results fi-om this study do not suggest causality. The results do highlight the unique nature of cohesion as it relates to win/loss record. By examining high school soccer and high school baseball separately, it was also possible to parcel 224 Murray - Team Cohesion & Leadership apart the unique dynamics of these sports, and to demonstrate that even subtle changes in interdependence can have large effect on the need for team cohesion that contributes to team success. References Boone, K.S., Beitel, P., & Kuhlman, J.S. (1997) The effects ofthe win/loss record on cohesion. Journal of Sport Behavior 20(2) 125-135. Brawiey, L.R. (1990) Group Cohesion: Status, Problems, and Future Directions. InternationalJournal of Sport Psychology, 21, 355-379. Carron, A. V. (1982). Cohesiveness in sport groups: Interpretations and comxA^xaXiom. Journal of Sport Psychology, 4, 123-138. Carron, A. V., Bray, S. R., & Eys, M.A. (2002). Team cohesion and team success in sport. Journal of Sports Sciences 20(2), 119-126. Chelladura, P. & Saleh, S.D. (1980) Dimensions of leader behavior in sports. Canadian Journal of Applied Sport Sciences, 3, 85-92. Chelladurai, P. & Carron, A. V. (1978). Leadership. CAHPER Sociology of Sport Monograph Series. Calagary, Canada: University of Calgary Publishing. Chelladurai, P. & Carron, A.V. (1983). Athletic maturity and preferred kadership. Journal of Sport Psychology, 5,371-380. Chelladurai, P. (1985). Sport Management: Micro Perspective. London, Ontario: Sport Dynamics. Chelladurai, P. (1990) Leadership in sports: A review. InternationalJournal of Sport Psychology, 21, 328-354. Gardner, D.E., Shields, D.L., Bredemeier, B.J., & Bostrom (1996). The relationship between perceived coaching behaviors and team cohesion baseball and soflball players. The Sport Psychologist, 10 367-381. Home, T., & Carron, A.V. (1985) Compatibility in Coach-Athlete Relationships. 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The Journal of Psychology. 13(2). 196-210. Weiss, M.R. & Friedrichs, W.D. (1986) The infiuence of leader behaviors, coach attributes, and institutional variables on performance and satisfaction of collegiate basketball teams. Journal of Sport Psychology, 8, 332-246. Westre, K., & Weiss, M. (1991). The relationship between perceived coaching behaviors and group cohesion in high school football teams. The Sport Psychologist, 5. 41-54. Widmeyer, W.N., Brawiey, L.R., & Carron, A.V. (1985). The Measurement of Cohesion in Sport Teams: The Group Environment Questionnaire. London Ontario: Sports Dynamics. Widmeyer, W.N., Brawiey, L.R., & Carron, A.V. (1992). The effects of group size in sport. Journal of Sport and Exercise Psychology. 12(2), 177-190. Williams, J.M, & Widmeyer, W.N. (1991). The cohesion-performance outcome relationship in a coacting sport. Journal of Sport and Exercise Psychology, 13, 364-371.

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