Next Article in Journal / Special Issue
Relative Income and Life Satisfaction among Chinese Adults
Previous Article in Journal
A CBR–AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions
Previous Article in Special Issue
Incorporating Physical Environment-Related Factors in an Assessment of Community Attachment: Understanding Urban Park Contributions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 11
Issue 20
10.3390/su11205650
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Decreasing Aggression through Team Communication in Collegiate Athletes

by
Hunhyuk Choi
1,
Jae-Ahm Park
2 and
Youngsook Kim
3,*
1
Department of Physical Education, Korea National University of Education, Cheongju 28173, Korea
2
Department of Sports and Leisure Studies, Daegu University, Daegu 38453, Korea
3
Department of Sport Science, Korea Institute of Sport Science, Seoul 01794, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(20), 5650; https://doi.org/10.3390/su11205650
Submission received: 2 April 2019 / Revised: 20 September 2019 / Accepted: 11 October 2019 / Published: 14 October 2019
(This article belongs to the Special Issue Psychology of Sustainability and Sustainable Development)
Browse Figure
Versions Notes

Abstract

:
Researchers have been interested in the topic of aggression in sports, and research shows it may not only hinder team success but also cause serious injuries (e.g., career-ending injuries) to athletes. Previous studies found that variables (e.g., communication, coaches, and efficacy) increased or decreased aggression in athletes; however, no studies have been conducted to investigate a model including these variables and aggression. Therefore, the purpose of this study is to simultaneously examine the relationships among communication, coach–athlete relationship, team efficacy, and aggression in team sports. After 294 collegiate athletes playing in team sports completed the battery of questionnaires, the data were analyzed for descriptive statistics and the structural equation modeling. The bootstrapping method was utilized to test the mediation effects. The results showed that communication was positively related to the coach–athlete relationship and team efficacy. The coach–athlete relationship was positively related to team efficacy which was negatively related to aggression. The bootstrapping results indicated a significant indirect effect from communication to aggression through coach–athlete relationship and team efficacy. The current study suggests that coaches should improve their communication skills to help athletes to have positive perceptions in the relationships with their coaches, to increase team efficacy, and to reduce aggressive behaviors.

1. Introduction and Literature Review

The psychology of sustainability and sustainable development which is relatively a new research of Sustainability Science is centered on the psychological approach in the constructional processes of sustainability and sustainable development, and it unveils psychological factors which are sustainable for individuals and also facilitate their well-being in different environments such as personal, social, and organizational environments [1]. Specifically, based on the psychology of sustainability and sustainable development perspective in organizations [2], fostering a healthy team environment can lead to healthy and successful outcomes as well as well-being in team members. As Di Fabio and Rosen stated “opening the black box of psychological processes“ leads to sustainable development [1], understanding the psychological processes of the team dynamic is essential to ultimately produce optimal outcomes and promote sustainability in teams.
Team communication is critical for sharing information, processing decision-making, providing solutions for problems, resolving team conflicts, and establishing interactional patterns [3,4]. In sports, effective instruction through clear communication facilitates athletes’ skill development, confidence improvement, motivation, and satisfaction [5]. Especially, effective communication between team members (i.e., coaches and athletes, as well as between athletes) enhances team coordination and, in turn, team success [6,7]. Communication is also considered a way to build foundations between individuals by sharing thoughts and emotions and to develop a rapport between coaches and athletes [8]. Effective (or positive) communication is, for example, that coaches use athlete-supportive, encouraging, and motivating verbal and non-verbal languages while communicating with athletes, whereas ineffective (or negative) communication is that coaches use intimidating, criticizing, yelling, and ignoring/disrespectful languages [5]. Therefore, coaches’ interaction and effective communication between coaches and athletes influences athletes’ development, performance, behaviors, psychological and emotional well-being, motivation, and sport persistence [9,10,11,12]. Given the open flow of communication in a close relationship, a co-oriented view can be created between coaches and athletes [13].
The formation of a close relationship based on trust and respect between the coach and athletes is essential for effective communication in order to lead to compatible coach–athlete partnerships [14]. The nature and quality of the relationship established between coaches and athletes affects athletes’ physical and psychological development, well-being, skill development, and athletic performance [15,16,17]. The relationship quality is also associated with athletes’ perceived training and performance satisfaction, physical self-concept, motivation, and passion [18,19,20,21]. Various conceptual models of the coach–athlete relationship were developed and examined [9,22]. As aforementioned, the open flow of communication results in co-orientation that represents coaches’ and athletes’ shared perspectives such as goals, values, and beliefs [23]. Shared knowledge and understanding made coaches and athletes appropriately work for each other’s needs, aspirations, and problems [15,22]. Communication enables coaches and athletes to develop co-orientation [24]. Although the original definition of co-orientation focused on relationship members’ perceptual consensus [25], co-orientation is closely related to effective communication, and previous research on the relationship between communication and successful performance showed similar results [26]. When coaches effectively communicated with athletes, athletes tried to achieve their goals [27]. Even though communication is the critical factor influencing athletes and team performance, as these studies illustrated, research examining the relationship between communication between team members and the coach–athlete relationship has been insufficient. Therefore, our first hypothesis was the following:
Hypothesis 1.
Communication has a positive effect on coach–athlete relationship.
In relation to communication and coach–athlete relationship, shared trust between team members and team efficacy have been known as factors that help to maximize team function, motivation, and persistence in teams [28,29,30]. Team efficacy is shared confidence within a team to successfully accomplish collective tasks [31], and it is also considered individual perceptions in a team toward the team’s capabilities [32]. Team efficacy is a crucial factor that influences team success [33,34]; research on team efficacy has been rare and limited in the sport psychology discipline. Team performance (achievement) especially can be enhanced by strengthening communication, cohesion, and skill usage. Successful experience also has a positive influence on team efficacy [35,36]. Additionally, communication is known to be a critical factor in predicting team efficacy between athletes and coaches [37]. Positive communication during competitions contributed to increased team performance [38]; whereas, negative communication was an obstruction for teams [39]. Moreover, the coach–athlete relationship as a psychological construct reflects social interpersonal nature and interaction within sport teams [40], and the quality of the coach–athlete relationship is directly and indirectly linked to collective efficacy [40,41,42]. The coach–athlete relationship is how athletes perceive their relationship with their coaches. As an antecedent of team efficacy within sport teams [35], Jowett et al. [40], for example, found that athletes’ perception on the relationship with their coaches positively influenced team efficacy. Therefore, we hypothesized as follows:
Hypothesis 2.
Communication has a positive effect on team efficacy.
Hypothesis 3.
Coach–athlete relationship has a positive effect on team efficacy.
In competitive sport situations, athletes often experience negative emotions (e.g., anxiety, frustration, and anger) which hinder optimal performance and team success. Recently, aggression has been the focus of attention because of its ability to influence the mental and physical health of athletes. Aggression that consists of anger and aggressiveness (i.e., aggressive behavior) can even cause critical issues such as serious injuries which may terminate athletes’ careers [43,44,45]. The aggressiveness appearing in adolescence tends to lead to school maladjustment such as low academic achievement or dropout and predicts the involvement of antisocial behavior or crime in adulthood [46]. Sport psychologists and sociologists have examined the concept of aggression and the relationship between aggression and other related factors (antecedents and consequences). In early research, aggression was defined as behaviors with intentions to harm another person physically and psychologically [47,48]. In addition, athletes’ aggression was defined as intentional behaviors aiming to harm opponents physically and psychologically whether it was socially acceptable or not [49]. To explain aggressive behaviors more clearly, various personal, emotional, and social variables also need to be studied together [50,51,52]. Studies showed male athletes experienced greater competitiveness and less empathy than female athletes, and thus male athletes generally scored higher on aggression than female athletes scored [53,54]; however, Keeler [55] reported there were no significant gender effects on aggression after controlling for basic demographic variables. Effective communication between coaches and athletes in competitive sports significantly influenced athlete aggressive behaviors during games [56]. For example, coaches’ verbal aggressiveness was negatively related to athletes’ intrinsic motivation, effort, and competence, and positively associated with anxiety [57]. In line with social learning theory [58], previous research indicated that athletes learned aggression from observation and indirect experiences from aggressive behaviors of coaches and peer athletes [59]. Young athletes also learned aggression through observing and modeling adult athletes who achieved their goals by aggressive behaviors [60]. Intriguingly, athletes in team sports (especially physical interactional sports such as rugby and soccer) showed a more aggressive disposition compared to athletes in individual sports [61]. In this perspective, immoral team environment and coaches’ behaviors may influence aggressive behavior in athletes [62]. Hodge and Ronsdale [63] reported that athletes who had good relationships with their coach showed less antisocial behavior and more social behavior. Aggression is a team problem as well as an individual problem [64]. Another study illustrated that aggression was an important factor for the belief of team efficacy [65]. Furthermore, the potential aggression of athletes in team sports influenced their emotions, team environment, and performance negatively, and consequently, it could intimidate positive values and functions of sports [66]. While team efficacy is one of the important antecedent factors influencing the aggression of athletes, in many studies, the relationship between team efficacy and aggressive behavior has not been examined empirically. Therefore, we hypothesized as follows:
Hypothesis 4.
Communication has a negative effect on aggression.
Hypothesis 5.
Coach–athlete relationship has a negative effect on aggression.
Hypothesis 6.
Team efficacy has a negative effect on aggression.
Importantly, researchers [67,68,69,70,71] have reported effective communication is one of the key factors to build strong social cohesion (i.e., interpersonal relationship) between coaches and athletes and between athletes and athletes, increase collective efficacy, help athletes regulate their negative emotions and behaviors such as anxiety and aggression, and finally contribute to team success and sustainability. Identifying factors related to aggression is essential to manage the various aggressive behaviors in sports situations and prevent athletes from serious injuries. However, only limited research has been conducted to examine the relationships among the variables, and no study has tested the variables simultaneously. Thus, the primary purpose of this study was simultaneously to investigate how team communication, team efficacy, and coach–athlete relationship influence aggression in order to reveal fundamental information for decreasing athletes’ aggression level. The hypothesis of the current study is as follows:
Hypothesis 7.
Communication has an indirect effect on aggression mediated by coach–athlete relationship and team efficacy.

2. Materials and Methods

2.1. Participants

We used purposeful sampling to recruit participants of this study. The participants were 294 Korean collegiate athletes (265 males and 29 females) in team sports with a mean of 21.51 (SD = 1.32) years old and also a mean of 9.78 (SD = 2.18) years of athletes’ experience. They responded to a battery of questions to measure team communication, coach–athlete relationship, team efficacy, and aggression. They were active members of team sports including basketball (n = 83, 28.2%), volleyball (n = 12, 4.1%), baseball (n = 86, 29.3%), soccer (n = 74, 25.1%), and handball (n = 39, 13.3%). Also, 76 (25.85%) of the participants had experience at the national representative level. After 29 questionnaires were discarded because of excessive missing values, 265 questionnaires were used for the analysis. General characteristics of the participants in this study are shown in Table 1 below.

2.2. Measures

The participants in this study were asked to complete a demographic questionnaire (e.g., sex, age, school year, and type of sports), the Korean version of the Scale of Effective Communication in Team Sports (SECTS-K), the Korean version of the Coach–Athlete Relationship Questionnaire (KrCART-Q), the Korean version of Collective Efficacy Questionnaire for Sports (CEQS), and the short version of competitive aggressiveness and anger scale (CAAS).
The SECTS-K was used to assess team communication. Choi et al. [72] modified the original SECTS-2 [73] by considering Korean culture and an understanding of Korean collegiate athletes. Team communication consists of 14 items in 3 factors measured on a 7-point Likert scale, which are acceptance and conflict (i.e., trust each other, communicate honestly and directly, share thoughts and feelings with one another; e.g., Try to make sure all players are included; 6 items, α = 0.84), particularity (i.e., use nicknames, languages, gestures that only team members can understand; e.g., Use slang that only team members would understand; 3 items, α = 0.79), and negative conflict (i.e., express negative feelings; e.g., Show that we lose our temper; 3 items, α = 0.69). A higher score indicates a higher level of team communication. Confirmatory factor analysis (CFA) of the SECTS-K was performed, and Table 2 shows the standardized loading values and composite reliabilities of subcomponents in the SECTS-K.
The KrCART-Q [74] was used to measure how athletes perceived their relationship with their coaches. The original CART-Q [21] was modified, and the KrCART-Q consists of 11 items in 3 factors measured on a 7-point Likert scale: closeness (i.e., perceptions of intimacy with each other; e.g., I like my coach; 4 items, α = 0.95), commitment (i.e., intentions to develop and maintain the relationship; e.g., I am committed to my coach; 3 items, α = 0.91), and complementarity (i.e., cooperative interactions between each other; e.g., when I am coached by my coach, I am responsive to his/her efforts; 4 items, α = 0.94). A higher score indicated a higher level of coach–athlete relationship. CFA of the KrCART-Q was performed, and Table 3 shows the standardized loading values and composite reliabilities of subcomponents in the KrCART-Q.
Team efficacy was measured by the Korean version of CEQS [75]. The original CEQS was developed by Short et al. [76]. This scale consists of 15 items in 4 factors: team strategy (e.g., we are strong on set plays; 4 items, α = 0.81), enough training (e.g., we have been enough training for the season/game; 3 items, α = 0.90), trust for leaders (e.g., we trust coaches and staff; 4 items, α = 0.94), and effective communication (e.g., we well communicate each other during a game; 4 items α = 0.92). This scale was also measured on a 7-point Likert scale. A higher score indicated a higher level of team efficacy. CFA of the CEQS was performed, and Table 4 shows the standardized loading values and composite reliabilities of subcomponents in the CEQS.
The CAAS was translated and modified into Korean [49] and used to measure trait anger and aggressiveness in competitive athletes. This scale consists of 2 factors with 12 items measured on a 5-point Likert scale: trait anger (e.g., I get mad towards my opponent if I lose; 6 items, α = 0.82) and competitive aggressiveness (e.g., it is ok to us physical force to win a game; 6 items, α = 0.85). A higher score indicated a higher level of aggression. CFA of the CASS was performed, and Table 5 shows the standardized loading values and composite reliabilities of subcomponents in the CAAS.

2.3. Procedures and Research Design

After obtaining the Institutional Review Board (IRB) approval, the first author contacted college sport team coaches in Korea to explain the purpose of this study and gain their permission to recruit participants (i.e., student-athletes). With coaches’ permission, the authors visited athletes before their practices. The coaches introduced the authors to their athletes and left the sites. The authors first explained the purpose of this study and informed the athletes that their participation was fully anonymous and voluntary. They were told to ask any questions before, during, and after completing the survey. After signing a written consent form and completing the survey, they put the survey in an envelope and left the sites. It took approximately 20 min for the participants to complete the survey. Because a cross-sectional research design was used for this study, the data were collected once.

2.4. Statistical Analysis

SPSS 22.0 was used to calculate the descriptive statistics, and AMOS 22.0 was used to conduct structural equation modeling (SEM) to identify the relationships among team communication, coach–athlete relationship, team efficacy, and aggressiveness. Following Anderson and Gerbing’s two-step approach in SEM [77], the measurement model was examined before verifying the structural model. For the mediation effect analysis, 2000 bootstrap samples were requested.

3. Results

3.1. Descriptive Statistics

Table 6 presents the means and standard deviations. All variables demonstrated satisfactory univariate skewness (<2) and kurtosis (<2). The sample reported high levels of communication, coach–athlete relationship, and team efficacy, as indicated on the seven-point Likert scale (communication M = 4.62, SD = 0.67, coach–athlete relationship M = 5.15, SD = 1.19, team efficacy M = 5.09, SD = 0.96). The sample reported moderate-to-low levels of aggression on the five-point Likert scale (aggression M = 2.84, SD = 0.78).

3.2. Measurement Model

A measurement model was examined with saturated pathways. The pathways of latent variables (measurement variables) are illustrated in Table 7. The fit of the measurement model was acceptable (χ2 = 240.97, df = 71, TLI = 0.90, CFI = 0.92, RMSEA = 0.08). The correlation analysis results showed that communication had a positive relationship with coach–athlete relationship (r = 0.56) and team efficacy (r = 0.79) but a negative relationship with aggression (r = −0.32). Additionally, a positive correlation between coach–athlete relationship and team efficacy (r = 0.74) was observed, but there was a negative relationship between coach–athlete relationship and aggression (r = −0.16). Team efficacy had a negative relationship with aggression (r = −0.34).

3.3. Structural Model

The structural model was verified, and the fit was found to be acceptable (χ2 = 240.97, df = 71, TLI = 0.90, CFI = 0.92, RMSEA = 0.08, SRMR = 0.076). In the model, communication was set as an exogenous variable, and coach–athlete relationship and team efficacy were set as endogenous and mediating variables. Furthermore, aggression was set as a dependent variable. As indicated in Figure 1, there were significant positive pathways from communication to coach–athlete relationship (H1: β = 0.56, p < 0.001) and to team efficacy (H2: β = 0.54, p < 0.001). Coach–athlete relationship was significantly related to team efficacy (H4: β = 0.43, p < 0.001). Team efficacy had a significant, negative association with aggression (H6: β = −0.36, p < 0.001), whereas coach–athlete relationship did not have a significant association with aggression (H5). The bootstrapping result indicated a significant indirect effect from communication to aggression through coach–athlete relationship and team efficacy in the model (H7: β = −0.088, p < 0.01). Standardized path coefficients for the structural model are shown in Table 8 below.

4. Discussion

The research results related to team sports indicated that effective communication has a positive influence on performance and competition results by improving the quality of the coach–athlete relationship and team efficacy and by decreasing aggression. In addition, recent coach–athlete relationship studies focused first on relational approaches in which coaches and athletes perceived themselves mutually in a friendly way, and second on the psychological influences of coach–athlete relationship. However, these studies suffer some limitations because they only considered an individual approach without group processes. Therefore, this study examined the effect of communication on aggression, with the coach–athlete relationship and team efficacy as mediating factors.
First, communication had a significant positive association with coach–athlete relationship (Hypothesis 1). This finding is consistent with previous studies that indicated the importance of communication on building and maintaining the quality relationship between coaches and athletes [8,9,13,14,22,23,24,25]. This finding is also well supported by the four stages of the linear group development theory, which states that a team goes through four stages to be an ideal team and that subjective and open communication is a key that can resolve conflicts, replace hostility with solidarity and cooperation, and stabilize interpersonal relationships [53]. Carron et al. [28] reported that team communication is necessary for the development of team structure and team maintenance. Furthermore, they suggested that decision-making, goal-setting, cooperation, team building, position, leadership, and conflicts in the team are also related to team communication [28]. Athletes especially perceived the evaluation of coaches and the effects of training differently depending on the communication style of the coaches. In other words, athletes prefer coaches who talk comfortably with consideration for the athletes while communicating. It also makes athletes believe that their training is more effective.
Second, communication had a significant positive relation to team efficacy (Hypothesis 2). This finding supports the previous research finding that effective communication among team members increased self-efficacy and collective efficacy and in turn performance [78]. The critical factors of team success are team communication, team cohesion, and skill enhancement [32]; thus, team outcomes can be improved or decreased by these factors. If team members do not communicate well within the team, the team members will not be cohesive and cooperative emotionally. As explained by the shared mental model [79,80], the result of effective verbal and non-verbal communication enables team members to build strong shared trust on performance ability and team work, anticipate one another’s behaviors, and coordinate their actions. Therefore, team members, including athletes, should communicate with each other consistently and effectively for team cohesion, team efficacy, and consequently team performance.
The coach–athlete relationship had a positive influence on team efficacy (Hypothesis 4). Recent studies on the coach–athlete relationship [40,81] emphasized on the two-way communication with a relational perspective. In team sports, trust between team members should be shared to achieve team goals. In addition, the coach–athlete relationship is important, as well as building trust between athletes during training and competition. With a qualitatively facilitated coach–athlete relationship, team members can have strong team cohesion and team efficacy. In the sport field, coaches and athletes are strongly emphasized to interact consistently. The coach–athlete relationship is an important factor that determines team cohesion, team efficacy, and team success (team performance). According to Jowett et al. [38], the interpersonal factor was divided into the coach–athlete relationship and team cohesion. Additionally, they reported that the coach–athlete relationship had more influence on team efficacy than team cohesion.
Team efficacy had a negative influence on aggression (Hypothesis 6), whereas coach–athlete relationship was not significantly associated with aggression (Hypothesis 5). Both findings were consistent with previous research showing there was insignificant association with the relationship between teacher–student relationship and aggression but significant association with the relationship between student–student relationship and aggression [82]. In previous studies [76,83], team efficacy was influenced by significant others such as coaches, team captain, and leading players. We can easily observe and experience the situation that athletes in sports team are trying to become cohesive by shouting “We are one team, and we can do it.” In this situation, the cohesion of the team increased. Therefore, aggressive behaviors during games decrease when players understand the importance of team cohesion and have fewer negative conflicts with other players.
Lastly, communication had a significant indirect effect on aggression mediated by coach–athlete relationship and team efficacy supporting Hypothesis 7. This study emphasized the importance of communication between coaches and athletes as the main factor and coach–athlete relationship and team efficacy as the mediating factors that control aggression in athletes. As Hypothesis 4 as well as Hypothesis 7, we expected to have partial mediation effects. That is, communication would have a direct association with aggression and an indirect association with aggression through coach–athlete relationship and team efficacy; however, communication was not significantly associated with aggression. The meaningful pathway that was found confirmed indications that effective communication enhanced the quality of the coach–athlete relationship, team efficacy, and consequently decreased athletes’ aggression. This supports previous research which found that fostering sustainable social environment decreased aggression [82].
There are several limitations to generalize the current findings. First, this study used a cross-sectional design to collect the data to examine the mediation effects of coach–athlete relationship and team efficacy on the relationship between communication and team efficacy. Because the data were collected only once, the results cannot provide clear causal relationships among variables in this study. Although aggression is generally considered more of a personality trait, it is possible that athletes may have higher levels of aggression during season than off season. Thus, a longitudinal approach to examine the relationship between communication and aggression with mediating variables should be conducted in future research. Second, this study did not analyze the data by sex (e.g., male vs. female), age (e.g., middle school, high school, and college), or sport types (e.g., collision type vs. contact type vs. non-contact type sports) because of the small sample size per group for the invariance test. For example, males from general psychology are usually more aggressive than females, but that is not always true. The results of the gender effects in a specific sport context are still equivocal. Therefore, future research should have enough sample size per group for the invariance test in order to find effects of moderating variables on the relationship between communication and aggression.

5. Conclusions

This study was an initial attempt to investigate the relationship between communication, coach–athlete relationship, team efficacy, and aggression in Korean collegiate athletes. The results of this study indicated that communication was positively related to the coach–athlete relationship and team efficacy. The coach–athlete relationship was positively related to team efficacy which was negatively related to aggression. There was a significant indirect effect from communication to aggression through coach–athlete relationship and team efficacy.
This study sheds light on that effective communication is an initial key factor to facilitate team environment and sequentially change variables in a team to regulate athletes’ aggression; therefore, coaches should pay attention on improving their communication skills to help athletes control their aggression. We believe that sport organizations and schools should provide educational workshops and programs for coaches to improve effective communication skills. The current study also provided a theoretical model of communication-aggression through coach–athlete relationship and team efficacy. Different perspectives were utilized to understand the possible relationship between the variables and aggression. As previous studies have mostly focused on what variables could enhance athletic performance so as to optimize team performance and win; however, not many studies have investigated the factors that might hinder team success. Given that notion, this study provides valuable practical information for coaches, athletes, educators in sports, and consultants. As Carron and Hausenblas [28] emphasized, active interaction with coaches and athletes in a team is essential to produce optimal performance. This study emphasizes on the importance of communication within team members (especially, coaches, and athletes) to improve the quality of coach–athlete relationship and increase team efficacy for fostering sustainable team environment in order to decrease aggression in athletes.

Author Contributions

Conceptualization, H.C., and Y.K.; methodology, H.C.; formal analysis, H.C.; data curation, H.C.; writing—original draft preparation, H.C., J.-A.P., and Y.K.; writing—review and editing, H.C., J.-A.P., and Y.K.; funding acquisition, H.C.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5B5A07921515).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Di Fabio, A.; Rosen, M.A. Opening the black box of psychological processes in the science of sustainable development: A new frontier. Eur. J. Sustain. Dev. Res. 2018, 2, 47. [Google Scholar] [CrossRef]
  2. Di Fabio, A. The psychology of sustainability and sustainable development for well-being in organizations. Front. Psychol. 2017, 8, 1534. [Google Scholar] [CrossRef] [PubMed]
  3. Boyd, D.E.; Webb, K.L. Interorganizational ethical conflict within alliances: A conceptual framework and research propositions. J. Bus.-Bus. Mark. 2008, 15, 1–24. [Google Scholar] [CrossRef]
  4. Kozlowski, S.W.; Bell, B.S. Work groups and teams in organizations. Handb. Psychol. 2003, 12, 333–375. [Google Scholar] [CrossRef]
  5. Sagar, S.S.; Jowett, S. Communicative acts in coach-athlete interactions: When losing competitions and when making mistakes in training. West. J. Comm. 2002, 76, 148–174. [Google Scholar] [CrossRef]
  6. Eccles, D.W.; Tran, K.B. Getting them on the same page: Strategies for enhancing coordination and communication in sports teams. J. Sport Psychol. Action 2012, 3, 30–40. [Google Scholar] [CrossRef]
  7. Salmela, J.H. Great Job, Coach!: Getting the Edge from Proven Winners; Potentium: Ottawa, ON, Canada, 1996. [Google Scholar]
  8. Philippe, R.A.; Seiler, R. Closeness, co-orientation and complementarity in coach–athlete relationships: What male swimmers say about their male coaches. Psychol. Sport Exerc. 2006, 7, 159–171. [Google Scholar] [CrossRef]
  9. Poczwardowski, A.; Barott, J.E.; Henschen, K.P. The athlete and coach: Their relationship and its meaning. Results of an interpretive study. Int. J. Sport Psychol. 2002, 33, 116–140. [Google Scholar]
  10. Martin, M.M.; Rocca, K.A.; Cayanus, J.L.; Weber, K. Relationship between Coaches’ use of Behavor Alteration Techniques and Verbal Aggression on Athletes’ Motivation and Affect. J. Sport Behav. 2009, 32, 227–241. [Google Scholar]
  11. Smith, R.E.; Smoll, F.L.; Barnett, N.P. Reduction of children’s sport performance anxiety through social support and stress-reduction training for coaches. J. Appl. Dev. Psychol. 1995, 16, 125–142. [Google Scholar] [CrossRef]
  12. Turman, P.D.; Schrodt, P. New avenues for instructional communication research: Relationships among coaches’ leadership behaviors and athletes’ affective learning. Commun. Res. Rep. 2004, 21, 130–143. [Google Scholar] [CrossRef]
  13. Roloff, M.E.; Miller, G.R. Interpersonal Processes: New Directions in Communication Research; Sage: Thousand Oaks, CA, USA, 1987. [Google Scholar]
  14. Carron, A.V.; Bennett, B.B. Compatibility in the coach-athlete dyad. Res. Quart 1977, 48, 671–679. [Google Scholar] [CrossRef]
  15. Jowett, S.; Cockerill, I.M. Olympic medallists’ perspective of the althlete–coach relationship. Psychol Sport Exerc 2003, 4, 313–331. [Google Scholar] [CrossRef]
  16. Côté, J.; Gilbert, W. An integrative definition of coaching effectiveness and expertise. Int. J. Sports Sci. Coach 2009, 4, 307–323. [Google Scholar] [CrossRef]
  17. Jowett, S. Interdependence analysis and the 3 + 1Cs in the coach-athlete relationship. In Social Psychology in Sport; Jowett, S., Lavallee, D., Eds.; Human Kinetics: Champaign, IL, USA, 2007; pp. 15–27. [Google Scholar]
  18. Jowett, S.; Nezlek, J. Relationship interdependence and satisfaction with important outcomes in coach–athlete dyads. J. Soc. Pers. Relat. 2012, 29, 287–301. [Google Scholar] [CrossRef]
  19. Jowett, S.; Cramer, D. The prediction of young athletes’ physical self from perceptions of relationships with parents and coaches. Psychol. Sport Exerc. 2010, 11, 140–147. [Google Scholar] [CrossRef]
  20. Adie, J.W.; Jowett, S. Meta-perceptions of the coach–athlete relationship, achievement goals, and intrinsic motivation among sport participants. J. Appl. Soc. Psychol. 2010, 40, 2750–2773. [Google Scholar] [CrossRef]
  21. Lafrenière, M.A.K.; Vallerand, R.J.; Donahue, R.; Lavigne, G.L. On the costs and benefits of gaming: The role of passion. Cyberpsychol. Behav. 2009, 12, 285–290. [Google Scholar] [CrossRef]
  22. Jowett, S.; Meek, G.A. The coach-athlete relationship in married couples: An exploratory content analysis. Sport Psychol. 2000, 14, 157–175. [Google Scholar] [CrossRef]
  23. Jowett, S.; Ntoumanis, N. The coach–athlete relationship questionnaire (CART-Q): Development and initial validation. Scand. J. Med. Sci. Sports 2004, 14, 245–257. [Google Scholar] [CrossRef]
  24. Duck, S. Meaningful Relationships: Talking, Sense, and Relating; Sage: Thousand Oaks, CA, USA, 1994. [Google Scholar]
  25. Newcomb, T.M. An approach to the study of communicative acts. Psychol. Rev. 1953, 60, 393. [Google Scholar] [CrossRef] [PubMed]
  26. Gould, D.; Guinan, D.; Greenleaf, C.; Medbery, R.; Peterson, K. Factors affecting Olympic performance: Perceptions of athletes and coaches from more and less successful teams. Sport Psychol. 1999, 13, 371–394. [Google Scholar] [CrossRef]
  27. Loughead, T.M.; Carron, A.V. The mediating role of cohesion in the leader behavior–satisfaction relationship. Psychol. Sport Exerc. 2004, 5, 355–371. [Google Scholar] [CrossRef]
  28. Carron, A.V.; Hausenblas, H.A.; Eys, M.A. Group Dynamics in Sport; Fitness Information Technology: Morgantown, WV, USA, 2005. [Google Scholar]
  29. Feltz, D.L.; Short, S.E.; Sullivan, P.J. Self-Efficacy in Sport; Human Kinetics: Champaign, IL, USA, 2008. [Google Scholar]
  30. Myers, N.D.; Feltz, D.L. From self-efficacy to collective efficacy in sport: Transitional methodological issues. In Handbook of Sport Psychology, 3rd ed.; Tenenbaum, G., Eklund, R.C., Eds.; Wiley: New York, NY, USA, 2007; pp. 799–819. [Google Scholar]
  31. Zaccaro, S.J.; Blair, V.; Peterson, C.; Zazanis, M. Collective efficacy. In Self-Efficacy, Adaptation, and Adjustment; Maddux, J., Ed.; Plenum: New York, NY, USA, 1995; pp. 305–328. [Google Scholar]
  32. Bandura, A. Self-Efficacy: The Exercise of Control; W.H. Freeman: New York, NY, USA, 1997. [Google Scholar]
  33. Myers, N.D.; Feltz, D.L.; Short, S.E. Collective Efficacy and Team Performance: A Longitudinal Study of Collegiate Football Teams. Group Dyn. 2004, 8, 126–138. [Google Scholar] [CrossRef]
  34. Myers, N.D.; Payment, C.A.; Feltz, D.L. Reciprocal Relationships Between Collective Efficacy and Team Performance in Women’s Ice Hockey. Group Dyn. 2004, 8, 182–195. [Google Scholar] [CrossRef]
  35. Feltz, D.L.; Lirgg, C.D. Perceived team and player efficacy in hockey. J. Appl. Psychol. 1998, 83, 557–564. [Google Scholar] [CrossRef]
  36. Kozub, S.A.; McDonnell, J.F. Exploring the relationship between cohesion and collective efficacy in rugby teams. J. Sport Behav. 2000, 23, 120–129. [Google Scholar]
  37. Fransen, K.; Vanbeselaere, N.; Exadaktylos, V.; Vande Broek, G.; De Cuyper, B.; Berckmans, D.; Ceux, T.; De Backer, M.; Boen, F. “Yes, we can!”: Perceptions of collective efficacy sources in volleyball. J. Sport Sci. 2012, 30, 641–649. [Google Scholar] [CrossRef]
  38. LeCouteur, A.; Feo, R. Real-time communication during play: Analysis of team-mates’ talk and interaction. Psychol. Sport Exerc. 2011, 12, 124–134. [Google Scholar] [CrossRef]
  39. Apitzsch, E. A case study of a collapsing handball team. In Dynamics within and Outside the Lab; Jern, S., Näslund, J., Eds.; LiU-Tryck: Linköping, Sweden, 2009; pp. 35–52. [Google Scholar]
  40. Jowett, S.; Shanmugam, V.; Caccoulis, S. Collective efficacy as a mediator of the association between interpersonal relationships and athlete satisfaction in team sports. Int. J. Sport Exerc. Psychol. 2012, 10, 66–78. [Google Scholar] [CrossRef]
  41. Olympiou, A.; Jowett, S.; Duda, J.L. The psychological interface of the coach-created motivational climate and the coach-athlete relationship. Sport Psychol. 2008, 22, 423–438. [Google Scholar] [CrossRef]
  42. Jowett, S.; Chaundy, V. An investigation into the impact of coach leadership and coach–athlete relationship on group cohesion. Group Dyn. 2004, 8, 302–311. [Google Scholar] [CrossRef]
  43. Sacks, D.N.; Petscher, Y.; Stanley, C.T.; Tenenbaum, G. Aggression and violence in sport: Moving beyond the debate. Int. J. Sport Exerc. Psychol. 2003, 1, 167–179. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Cusimano, M.D.; Sharma, B.; Lawrence, D.W.; Ilie, G.; Silverberg, S.; Jones, R. Trends in North American newspaper reporting of brain injury in ice hockey. PLoS ONE 2013, 8, e61865. [Google Scholar] [CrossRef] [PubMed]
  45. Cusimano, M.D.; Nastis, S.; Zuccaro, L. Effectiveness of interventions to reduce aggression and injuries among ice hockey players: A systematic review. Can. Med Assoc. J. 2013, 185, E57–E69. [Google Scholar] [CrossRef] [PubMed]
  46. Mathiesen, K.S.; Sanson, A. Dimensions of early chidhood behavior problems: Stability and predictors of change from 18 to 30 months. J. Abnorm. Child Psych. 2000, 28, 15–31. [Google Scholar] [CrossRef] [PubMed]
  47. Bandura, A. Social learning theory of aggression. J. Commun. 1978, 28, 12–29. [Google Scholar] [CrossRef] [PubMed]
  48. Silva, J.M. The perceived legitimacy of rule violating behavior in sport. J. Sport Psychol. 1983, 5, 438–448. [Google Scholar] [CrossRef]
  49. Maxwell, J.P.; Moores, E. The development of a short scale measuring aggressiveness and anger in competitive athletes. Psychol. Sport Exerc. 2007, 8, 179–193. [Google Scholar] [CrossRef]
  50. Hofmann, V.; Müller, C.M. Avoiding antisocial behavior among adolescents: The positive influence of classmates’ prosocial behavior. J. Adolesc. 2018, 68, 136–145. [Google Scholar] [CrossRef]
  51. Molero, M.M.; Pérez-Fuentes, M.C.; Carrión, J.J.; Luque, A.; Garzón, A.; Martos, A.; Simón, M.M.; Barragán, A.B.; Gázquez, J.J. Antisocial behavior and interpersonal values in high school students. Front Psychol. 2017, 8, 170. [Google Scholar] [CrossRef] [PubMed]
  52. Sánchez-García, M.; Lucas-Molina, B.; Fonseca-Pedrero, E.; Pérez-Albéniz, A.; Paino, M. Emotional and behavioral difficulties in adolescence: Relationship with emotional well-being, affect, and academic performance. An. De Psicol. Ann. Psychol. 2018, 34, 482–489. [Google Scholar] [CrossRef]
  53. Stanger, N.; Kavussanu, M.; Ring, C. Gender moderates the relationship between empathy and aggressiveness in sport: The mediating role of anger. J. Appl. Sport Psychol. 2017, 29, 44–58. [Google Scholar] [CrossRef]
  54. Christoforidis, C.; Kalivas, V.; Matsouka, O.; Bebetsos, E.; Kambas, A. Does gender affect anger and aggression in handball players? Cyprus J. Sci. 2010, 8, 3–11. [Google Scholar]
  55. Keeler, L.A. The differences in sport aggression, life aggression, and life assertion among adult male and female collision, contact, and non-contact sport athletes. J. Sport Behav. 2007, 30, 57–76. [Google Scholar]
  56. Blum, R.H.; Raemer, D.B.; Carroll, J.S.; Dufresne, R.L.; Cooper, J.B. A method for measuring the effectiveness of simulation-based team training for improving communication skills. Anesth. Analg. 2005, 100, 1375–1380. [Google Scholar] [CrossRef]
  57. Bekiari, A. Verbal aggressiveness and leadership style of sports instructors and their relationship with athletes’ intrisic motivation. Creat. Educ. 2014, 5, 114–121. [Google Scholar] [CrossRef]
  58. Bandura, A. Aggression: A Social Learning Analysis; Prentice-Hall: Upper Saddle River, NJ, USA, 1973. [Google Scholar]
  59. Hwang, O.C.; Park, J.G. The impacts of adolescent athletes’ passion and perceived coach-athlete relationship on aggressiveness. Korean J. Phys. Educ. 2012, 51, 279–292. [Google Scholar]
  60. Weinberg, R.S.; Gould, D. Foundations of Sport and Exercise Psychology, 7th ed.; Human Kinetics: Champaign, IL, USA, 2018. [Google Scholar]
  61. Maxwell, J.P. Anger rumination: An antecedent of athlete aggression? Psychol. Sport Exerc. 2004, 5, 279–289. [Google Scholar] [CrossRef]
  62. Chow, G.M.; Murray, K.E.; Feltz, D.L. Individual, team, and coach predictors of players’ likelihood to aggress in youth soccer. J. Sport Exerc. Psychol. 2009, 31, 425–443. [Google Scholar] [CrossRef]
  63. Hodge, K.; Lonsdale, C. Prosocial and antisocial behavior in sport: The role of coaching style, autonomous vs. controlled motivation, and moral disengagement. J. Sport Exerc. Psychol. 2011, 33, 527–547. [Google Scholar] [CrossRef] [PubMed]
  64. Brown, M.E.; Treviño, L.K. Ethical leadership: A review and future directions. Leadersh. Q. 2006, 17, 595–616. [Google Scholar] [CrossRef]
  65. Brown, M.E.; Trevino, L.K. Socialized charismatic leadership, values congruence, and deviance in work groups. J. Appl. Psychol. 2006, 91, 954–962. [Google Scholar] [CrossRef] [PubMed]
  66. Kim, S.O.; Kim, J.W.; Hwang, J. The relationship among stress, self-esteem, aggression and sociality of the school and club soccer athletes. Korean J. Sport Psychol. 2007, 18, 103–117. [Google Scholar]
  67. Carron, A.V.; Brawley, L.R. Cohesion: Conceptual and measurement issues. Small Group Res. 2012, 43, 726–743. [Google Scholar] [CrossRef]
  68. Paradis, K.F.; Carron, A.V.; Martin, L.J. Athlete perceptions of intra-group conflict in sport teams. Sport Exerc. Psychol. Rev. 2014, 10, 4–18. [Google Scholar]
  69. Martin, L.J.; Paradis, K.F.; Eys, M.A.; Evans, B. Cohesion in sport: New directions for practitioners. J. Sport Psychol. Action 2013, 4, 14–25. [Google Scholar] [CrossRef]
  70. Onağ, Z.; Tepeci, M. Team effectiveness in sport teams: The effects of team cohesion, intra team communication and team norms on team member satisfaction and intent to remain. Procedia-Soc. Behav. Sci. 2014, 150, 420–428. [Google Scholar] [CrossRef]
  71. Yang, J. Thriving Organizational Sustainability through Innovation: Incivility Climate and Teamwork. Sustainability 2016, 8, 860. [Google Scholar] [CrossRef]
  72. Choi, H.H.; Cho, S.K.; Kim, Y.S. Validation of the communication scale in team sports. Korea Soc. Wellness 2018, 13, 179–191. [Google Scholar] [CrossRef]
  73. Sullivan, P.J.; Short, S. Further operationalization of intra-team communication in sport: An updated version of the scale of effective communication in team sports (SECTS-2). J. Appl. Soc. Psychol. 2011, 41, 471–487. [Google Scholar] [CrossRef]
  74. Kim, K.H.; Park, J.G. Structural validation of the Korean version of coach-athlete relationship questionnaire (KrCART-Q). Korean J. Phys. Educ. 2008, 47, 219–233. [Google Scholar]
  75. Yoo, J.; Lim, S.W. A study on the development and validation test of the collective efficacy questionnaire for soccer. Korean J. Sport Psychol. 2009, 20, 17–31. [Google Scholar]
  76. Short, S.E.; Sullivan, P.; Feltz, D.L. Development and preliminary validation of the collective efficacy questionnaire for sports. Meas. Phys. Educ. Exerc. Sci. 2005, 9, 181–202. [Google Scholar] [CrossRef]
  77. Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
  78. Riggs, M.L.; Knight, P.A. The impact of perceived group success-failure on motivational beliefs and attitudes: A causal model. J. Appl. Psychol. 1994, 79, 755–766. [Google Scholar] [CrossRef]
  79. Braun, S.; Peus, C.; Weisweiler, S.; Frey, D. Transformational leadership, job satisfaction, and team performance: A multilevel mediation model of trust. Leadersh. Q. 2013, 24, 270–283. [Google Scholar] [CrossRef]
  80. Zoogah, D.B.; Noe, R.A.; Shenkar, O. Shared mental model, team communication and collective self-efficacy: An investigation of strategic alliance team effectiveness. Int. J. Strateg. Bus. Alliances 2015, 4, 244–270. [Google Scholar] [CrossRef]
  81. Choi, H.H.; Cho, S.K. The mediating role of the coach-athlete relationship in relationships between perceived passion and burnout in adolescent athletes. Korean J. Sport Psychol. 2014, 25, 111–125. [Google Scholar]
  82. Lee, Y.; Lim, S. Effects of Sports Activity on Sustainable Social Environment and Juvenile Aggression. Sustainability 2019, 11, 2279. [Google Scholar] [CrossRef]
  83. Vargas-Tonsing, T.M.; Warners, A.L.; Feltz, D.L. The predictability of coaching efficacy on team efficacy and player efficacy in volleyball. J. Sport Behav. 2003, 26, 396–407. [Google Scholar]
Sustainability 11 05650 g001 550
Figure 1. Structural equation model with standardized estimates among variables. Only significant paths are presented. The paths were significant at level p < 0.001.
Figure 1. Structural equation model with standardized estimates among variables. Only significant paths are presented. The paths were significant at level p < 0.001.
Sustainability 11 05650 g001
Table
Table 1. General characteristics of the participants (n = 294).
Table 1. General characteristics of the participants (n = 294).
CharacteristicsCategoryFrequency (n)Present (%)
SexMale26590.1
Female299.9
Age207926.9
217625.8
227224.5
235217.7
24 or older155.1
School yearFreshmen7926.9
Sophomores7625.8
Juniors7224.5
Seniors5217.7
Graduate school155.1
Type of SportsBasketball8328.2
Volleyball124.1
Baseball8629.3
Soccer7425.1
Handball3913.3
Table
Table 2. Standardized factor loading values and composite reliability.
Table 2. Standardized factor loading values and composite reliability.
Latent VariableItemStandardized Loading ValuesC.R
Acceptance & conflict10.7040.879
20.617
30.780
40.735
50.766
60.782
particularity10.6320.753
20.708
30.694
Negative conflict10.6210.722
20.610
30.676
Table
Table 3. Standardized factor loading values and composite reliability.
Table 3. Standardized factor loading values and composite reliability.
Latent VariableItemStandardized Loading ValuesC.R
Closeness10.9030.917
20.945
30.951
40.872
Commitment10.8650.842
20.879
30.891
Complementarity10.8390.903
20.926
30.919
40.919
Table
Table 4. Standardized factor loading values and composite reliability.
Table 4. Standardized factor loading values and composite reliability.
Latent VariableItemStandardized Loading ValuesC.R
Team strategy10.6960.724
20.762
30.885
40.602
Enough training10.8920.852
20.903
30.793
Trust for leaders10.8370.890
20.912
30.920
40.897
Effective communication10.8690.893
20.923
30.858
40.820
Table
Table 5. Standardized factor loading values and composite reliability.
Table 5. Standardized factor loading values and composite reliability.
Latent VariableItemStandardized Loading ValuesC.R
Anger10.5230.778
20.466
30.760
40.845
50.583
Aggressiveness10.4840.847
20.681
30.751
40.643
50.857
60.759
Table
Table 6. Means (M), standard deviation (SD), skewness, and kurtosis.
Table 6. Means (M), standard deviation (SD), skewness, and kurtosis.
ScaleMSDSkewnessKurtosis
Communication4.620.670.6710.656
Coach–athlete relationship5.151.19−0.4790.491
Team efficacy5.090.96−0.3120.279
Aggression2.840.78−0.2140.048
Table
Table 7. Factor correlations among the study variables.
Table 7. Factor correlations among the study variables.
Variable VariableEstimate
communication↔Coach–athlete relationship0.561
communication↔Team efficacy0.789
communication↔Aggression−0.322
Coach–athlete relationship↔Team efficacy0.743
Coach–athlete relationship↔Aggression−0.163
Team efficacy↔Aggression−0.335
Table
Table 8. Standardized path coefficients for the structural model.
Table 8. Standardized path coefficients for the structural model.
Hypothesized Pathb
DirectIndirect
H1: Communication → coach–athlete relationship0.561 ***
H2: Communication → team efficacy0.544 ***
H3: Communication → aggression −0.141
H4: Coach–athlete relationship → team efficacy0.438 ***
H5: Coach–athlete relationship → aggression0.183
H6: Team efficacy → aggression−0.360 ***
H7: Communication → coach–athlete relationship → team efficacy → aggression −0.088 **
** p < 0.01, *** p < 0.001, b = standardized regression weight.

Share and Cite

MDPI and ACS Style

Choi, H.; Park, J.-A.; Kim, Y. Decreasing Aggression through Team Communication in Collegiate Athletes. Sustainability 2019, 11, 5650. https://doi.org/10.3390/su11205650

AMA Style

Choi H, Park J-A, Kim Y. Decreasing Aggression through Team Communication in Collegiate Athletes. Sustainability. 2019; 11(20):5650. https://doi.org/10.3390/su11205650

Chicago/Turabian Style

Choi, Hunhyuk, Jae-Ahm Park, and Youngsook Kim. 2019. "Decreasing Aggression through Team Communication in Collegiate Athletes" Sustainability 11, no. 20: 5650. https://doi.org/10.3390/su11205650

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop