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INTRODUCTION
Especially in childhood and adolescence, participation in organized sports brings a variety of benefits to its participants, such as improved health and well-being, development of social skills (such as cooperation, discipline and leadership) and greater support of a physically active lifestyle (Konttinen et al., 2019). However, although a systematic review reveals that the sports context also has the potential for the development of negative experiences, this compilation of studies sheds light on the fact that this difference may be related to the environment in which this young person is inserted (Rigoni et al., 2017). In this sense, group cohesion is important to this context since it can be defined as a dynamic process, reflected by the group’s tendency to unite and remain united in the pursuit of meeting the needs of its members and/or of common objectives (Carron & Brawley, 2012; Eys et al., 2019).
Group cohesion, known to be a key element for sports performance, can be seen from the perspective of task or social cohesion (Nascimento Junior et al., 2019a, 2020b). Task cohesion refers to the willingness of group members to work together to achieve a common goal, while social cohesion refers to the degree to which members are satisfied with their affective needs (Eys et al., 2019). However, it is emphasized that there is also a negative group process, related to conflict, defined by disagreements and interpersonal problems, theorized by a two-dimensional nature, composed of social (negative affects) and tasks (disagreements in relation to objectives) conflicts (Barki & Hartwick, 2004). Given the context, understanding motivational aspects is essential to identify the factors that motivate young people to engage in training and goals within the sports context (Caruzzo et al., 2013; Nascimento Junior et al., 2019b).
Motivation is considered one of the main determining factors for successful experiences within the sports context, both in sports initiation and in high performance (Deci & Ryan, 2012; Rigby & Ryan, 2018; Ring & Kavussanu, 2018; Roberts & Walker, 2020). In addition, it is one of the psychological variables that best elucidates the reasons that lead people to present themselves as more determined than others in some activities, and essential for long-term participation in a practice, further illustrating what motivates them to start, continue or even give up an activity, whether it is sporty or not (Deci & Ryan, 2012; Rigby & Ryan, 2018).
Among the various theories that propose to understand this phenomenon stands out in the area of psychology of an under this perspective, the Achievement Goals Theory (AGT) has been widely used to understand the motivation of young people within the context of organized sport (Kallinen et al., 2019; Lochbaum et al., 2016). AGT seeks to elucidate how motivation directs young people and guides their behaviours. This makes it possible to understand how subjects achieve their goals, deal with failure and how they choose to engage in some activity (Duchesne & Ratelle, 2020).
AGT is subdivided into orientations of the type: task and ego orientation, which results in different positions of the subject facing the challenges. The first concerns the development of skills, in which the subject seeks personal improvement in the analysis of their behaviours and understands success because of their efforts (domain). On the other hand, the ego-oriented individual prioritizes the demonstration of skills and has a on social comparison, taking others as a reference. Considers success impressing people from the highlight of their skills (demonstration) (Nicholls, 1989). Both orientations can coexist in the individual, being possible the variation between orientation by the ego and orientation by the task (Nicholls, 1989).
Thus, the AGT can bring benefits when applied in environments where subjects are in the process of learning. According to Duchesne and Ratelle (2020), when developed within the school context, it was noticed that task-oriented students faced adversity satisfactorily, such as stress, given that those who enjoy the school experience more tend to become resilient and do not exhibit exhibitionist behaviour. Thus, it is suggested that individuals who are properly oriented also have a higher level of emotional control.
The overall purpose of the present study was to utilize regression and cluster analyses to investigate whether athletes’ AGT development through sports impacts their perception of team cohesion and group conflict. Firstly, we investigated whether AGT predicts team cohesion and group conflict. According to past research (Eys et al., 2019; Nascimento Junior et al., 2019a; Paradis et al., 2014a), the hypothesis was that task orientation would be positively associated with team cohesion and negatively with group conflict, whilst ego orientation would be positively associated with group conflict and negatively with team cohesion. The second aim was to assess whether athletes’ scores for team cohesion and group conflict would differ between different profiles of goals orientation. Based on past studies (Kallinen et al., 2019; Lochbaum et al., 2016), we hypothesized that athletes with higher scores of task orientation and lower scores of ego orientation would have higher scores of team cohesion and lower scores of group conflict. Thus, this study is relevant to the extent that the results obtained can contribute to the practical activities of athletes and coaches, as well as to the scientific community that seeks to understand more broadly how these variables are related and how they can be used to enhance athletes’ performance.
METHODS
Study design and procedures
The present study involved a cross-sectional research design with all data collected at a one-time point. Ethical approval was granted by the lead researcher’s university ethics and human research committee (protocol 1.648.086). Before any data was collected, permission was obtained from the organizing committee of the sports tournament where the data collection took place and the coaches of the teams involved. The data collection commenced after participants completed an informed consent form. Before completing the study questionnaire, brief instructions were provided to participants about the purpose of the research and what was required when completing the questionnaire. The questionnaire took participants 30 minutes to complete, and the order of the questionnaires was randomized among participants to avoid bias.
Participants
Participants were 413 young athletes participating in the final phase of the School Games of the state of Pernambuco, Brazil, in 2017. In this way, the participants were boys (n = 227) and girls (n = 186) aged between 14 and 17 years of the following sports: basketball (n = 67), futsal (n = 80), handball (n = 135), and volleyball (n = 131). The athletes had a mean age of 16.04± 0.89 years, time of practice of 7.29± 1.4 years and time within the team of 3.84± 2.91 years. The participants were selected in a non-probabilistic way and for convenience, and the selection criteria were as follows: 1) to practice the sport for more than 1 year; and 2) to have participated in some regional/state level competition during the 2016/2017 seasons. Only the athletes who had the consent term signed by the coaches (responsible for the athletes in the sports event) participated in the study.
Instruments
Youth Sport Environment Questionnaire (P-YSEQ)
This instrument was developed by Eys et al. (2009) and validated for Portuguese-speaking athletes by Nascimento Junior et al. (2018). P-YSEQ assesses team cohesion in youth between the ages of 13 to 17 years and consists of 16 items that evaluate task and social cohesion and 2 spurious items that do not enter into the analysis, totalling 18 items. Task cohesion contains eight items, and a sample item is “We all share the same commitment to our team’s goals”. Social cohesion contains eight items, and a sample item is “I spend time with my teammates”. All items are scored on a 9-point Likert-type scale anchored at the extremes of 1 (strongly disagree) and 9 (strongly agree). The literature has demonstrated the factorial validity, test-retest reliability, and internal consistency reliability of this scale in youth sport participants (Nascimento Junior et al., 2019a; Tamminen et al., 2019).
Group Conflict Questionnaire (P-GCQ)
The GCQ was developed by Paradis (2014b), and validated for the Brazilian context by Nascimento Junior et al. (2020a). P-GCQ contains 12 items distributed in two dimensions: task conflict (e.g., “The team’s ability to be successful is jeopardized because of heated disagreements during competition”) and social conflict (e.g., “Emotions run high in social situations over personal disagreements brought to light”). All items reference a cognition (such as disagreement), a negative emotion (such as anger), and a behavioral action (such as sabotage). Reponses are provided on a 9-point Likert-type scale, anchored at the extremes of 1 (strongly disagree) and 9 (strongly agree). Past research has demonstrated the factorial validity, test-retest reliability, and internal consistency reliability of this scale with youth sport participants (Nascimento Junior et al., 2020b; Paradis et al., 2014a).
Task and Ego Orientation in Sport Questionnaire (TEOSQ)
TEOSQ was developed by (Duda, 1989) and validated for the Brazilian context by Goulart et al. (2007). The Brazilian version of the TEOSQ consists of 8 task-related and 6 ego-related items reflecting the definitions of success in sports contexts. The items are prefaced with the heading “I feel most successful in this class when…” Young athletes rated each item on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5). The literature has demonstrated the factorial validity, test-retest reliability, and internal consistency reliability of this scale in youth sport participants (Caruzzo et al., 2013; Duchesne & Ratelle, 2020).
Data analysis
The correlation between all variables was performed using Pearson’s coefficient, and the following values were adopted to interpret the intensity of the correlations: 0.01 to 0.39= weak; 0.4 to 0.69= moderate; and 0.7 to 1.0= strong. A multiple regression model was used to determine if the achievement goals combined predict youth athletes’ perception of team cohesion and group conflict. There were no sufficiently strong correlations between variables that indicated problems with multicollinearity (VIF range= 1.07 to 1.13). Specifically, these VIF values were below the 5 or 10 deemed acceptable by Hair Jr. et al. (2014). All analyses were performed using IBM SPSS v.23.0, adopting a significance level of p < .05. In addition, a post hoc statistical power analysis in G*Power 3.1.9 (Faul et al., 2007) revealed our statistical power to be 99.9% based on our sample of 177 participants, a medium effect size (.15) according to Cohen (1992) f2 criteria, and a .05 p-value.
Youth athletes were grouped/classified using hierarchical and non-hierarchical cluster analysis. Firstly, the nearest neighbour hierarchical cluster analysis was conducted using the squared Euclidian distance as a measure of dissimilarity. The R-square was used as a criterion for the retention of the number of clusters. From this analysis, three clusters were retained. For the validation and classification of the youth athletes in the three clusters retained, a k-Means non-hierarchical cluster analysis was conducted. According to the criterion of Cumming and Duda (2012), z scores below −0.5 are considered to be low levels; z scores between −0.5 and +0.5 are moderate, and z scores over +0.5 are considered high. Differences between clusters for the dimensions of team cohesion and group conflict were tested by the Multivariate Analysis of Variance (MANOVA). The magnitude of the differences between the groups analyzed was obtained through the size effect, which shows a typical measure of deviation between group means, allowing for real quantification of the difference between them. Cohen (1992) described effect size as small (η2= 0.01), medium (η2= 0.06) or large (η2= 0.13).
RESULTS
Preliminary analysis
The data was first screened for missing values. There were no missing values, as the leading researcher ensured all surveys were fully completed during data collection. The data were then screened for univariate and multivariate outliers, with no outliers found within the sample. Finally, the data were screened for normality. The skewness values ranged from –1.00 to 0.51, and the kurtosis values ranged from –0.90 to 3.35, indicating reasonable normality (Tabachnick & Fidell, 2013).
Descriptive statistics and intercorrelations
Internal consistency and mean values for all the dimensions of achievement goals orientation, team cohesion and group conflict are presented in Table 1. In general, the youth athletes reported high scores in task orientation, task cohesion and social cohesion and lower scores in ego orientation, task conflict and social conflict. Task orientation was significantly correlated with task cohesion (r = 0.20, p< 0.001), social cohesion (r = 0.11, p< 0.05). Ego orientation was significantly correlated with task conflict (r = 0.23, p < 0.001) and social conflict (r = 0.28, p < 0.001). Task cohesion was negative association with task conflict (r = –0.16, p < 0.001) and social conflict (r = –0.21, p < 0.001).
Table 1. Summary of intercorrelations, scale ranges, means, standard deviations and reliability estimates.
| Variables | Goals orientation | Team cohesion | Team conflict | |||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |
| 1. Ego orientation | – | 0.01 | 0.00 | 0.07 | 0.23** | 0.28** |
| 2. Task orientation | – | 0.20** | 0.11* | -0.03 | -0.08 | |
| 3.Taks cohesion | – | 0.48** | –0.16** | –0.21** | ||
| 4. Social cohesion | – | –0.02 | –0.05 | |||
| 5. Task conflict | – | 0.81** | ||||
| 6. Social conflict | ||||||
| Mean | 2.24 | 4.09 | 7.29 | 6.55 | 4.72 | 3.93 |
| SD | 0.93 | 0.57 | 1.41 | 1.59 | 1.98 | 2.22 |
| Scale Ranges | 1-5 | 1-5 | 1-9 | 1-9 | 1-9 | 1-9 |
| Alpha coefficient | 0.79 | 0.91 | 0.79 | 0.88 | 0.89 | 0.94 |
Pearson correlation; *p < 0.05; **p < 0.01.
Multiple regression analysis
Standard multiple regression analysis (see Table 2) revealed that our model, which included all dimensions of achievement goals orientation (ego and task orientation), explained a significant amount of the variance of task (R 2= 0.03, p < 0.001) and social (R 2= 0.01, p < 0.05) cohesion. Task orientation made the largest positive contribution to both task (β= 0.50, p < 0.001) and social (β= 0.31, p < 0.05) cohesion.
Table 2. Goals orientation as predictors of team cohesion and group conflict of youth sport participants.
| Predictors | Task Cohesion | Social Cohesion | Task conflict | Social conflict |
|---|---|---|---|---|
| β (CI) | β (CI) | β (CI) | β (CI) | |
| Ego orientation | –0.01 (–0.13, 0.13) | 0.12 (–0.03, 0.29) | 0.49 (0.29, 0.69)*** | 0.67 (0.45, 0.89)*** |
| Task orientation | 0.50 (0.27, 0.74)*** | 0.31 (0.04, 0.57)* | –0.14 (–0.47, 0.18) | –0.34 (–.070, 0.01)* |
| R 2 | 0.03 | 0.01 | 0.05 | 0.08 |
| F | 9.142*** | 3.865* | 12.264*** | 19.822*** |
Note. Only the standardized regression coefficients which were less than our significance level of 0.05 are highlighted in bold. β = Standardized regression coefficient; CI: 95% confidence interval;
*p < 0.05
**p < 0.01;
***p < 0.001.
Our results also revealed that our models, including the dimension of achievement goals (ego and task orientation), explained a significant amount of the variance of both task (R 2= 0.05, p < 0.001) and social (R 2= 0.08, p < 0.001) conflict dimensions. Ego orientation made the largest positive contribution to task conflict (β= 0.49, p < 0.001) and social conflict (β= 0.67, p < 0.001), whilst task orientation made negative contribution (β= –0.34, p < 0.05) for social conflict.
Cluster analysis
Nonhierarchical cluster analysis confirmed the three-cluster solution, which are described in Figure 1. Athletes from Cluster 1 (n = 99) had high scores for ego orientation and moderate scores for task orientation which was called “High ego and task”. Cluster 2 (n = 149) was characterized by presenting low scores for ego orientation and task orientation. Cluster 2 received the denomination of “Low ego and task”. Athletes from Cluster 3 (n = 165) had high scores for task orientation and low scores for ego orientation and were called “High task and low ego”.
Figure 1. Graphic representation of the profiles of achievement goal of the youth athletes through cluster analysis.
Figure 2 shows the mean values and standard deviations used to create the clusters, and MANOVA was performed to examine the characteristics of each profile. Significant differences were found between Cluster 1 and Clusters 2 and 3 (p < 0.05) and Cluster 2 and 3 (p < 0.05) for both ego and task orientations (Figure 2).
*Significant difference (p < 0.05) between: (A) Cluster 1 with Clusters 2 and 3; (B) Cluster 2 and 3.
Figure 2. Mean scores and standard deviation of ego and task orientation of the cluster’s profiles. MANOVA.
When high task and low ego cluster (Cluster 3) was compared with low ego and task (Cluster 2) and high task and low ego cluster (Cluster 1) (see Table 3), there was a significant difference between groups in task cohesion (p = 0.001), task conflict (p = 0.003) and social conflict (p = 0.001). As shown in Table 3, youth athletes with high task and low ego orientations (M = 7.59, SD = 1.23) showed a higher score of task cohesion when compared to athletes with low ego and task orientations (M = 6.94, SD = 1.50). Further, athletes with high ego and task orientations showed higher scores of social (M = 4.76, SD = 2.35) and task (M = 5.29, SD = 2.00) conflict when compared to the other two clusters.
Table 3. Comparison of team cohesion and group conflict between clusters.
| Variables | Clusters | P-value | η2 | ||
|---|---|---|---|---|---|
| High ego and task (n = 99) | Low ego and task (n = 149) |
High task and low ego (n = 165) | |||
| M (Sd) | M (Sd) | M (Sd) | |||
| Social Cohesion | 6.70 (1.64) | 6.40 (1.59) | 6.60 (1.56) | 0.308 | 0.006 |
| Task Cohesion | 7.34 (1.46) | 6.94 (1.50)a | 7.59 (1.23) | 0.001* | 0.039 |
| Social Conflict | 4.76 (2.35)b | 3.95 (2.10) | 3.42 (2.11) | 0.001* | 0.054 |
| Task Conflict | 5.29 (2.00)b | 4.66 (1.83) | 4.44 (2.04) | 0.003* | 0.029 |
MANOVA. *Significant difference (p< 0.05) between: a) “Low ego and task” with “High task and low ego”; b) “High ego and task” with “Low ego and task” and “High task and low ego”; M: Mean; Sd: Standard deviation; η2: partial eta squared.
DISCUSSION
The main goal of this study was to analyze the perception of team cohesion and group conflict in Brazilian youth athletes through AGT based investigation using cluster analysis. Further, it was examined the predicting role of achievement goals on team cohesion and group conflict. The main findings revealed the positive predicting role of task orientation on the dimensions of team cohesion and the negative predicting role on social conflict, whilst ego orientation demonstrated a positive predicting role on both dimensions of group conflict. Further, from the profiles created through cluster analysis, it was possible to observe that youth athletes with high task and low ego orientations showed a higher score of task cohesion when compared to athletes with low ego and task orientations, whilst athletes with high ego and task orientations showed higher scores of social and task conflicts when compared to the other two clusters.
One of the main findings of this study refers to the positive predictor of task orientation on group cohesion, confirming the first hypothesis of the study. This finding shows that motivational orientation related to the development of their own skills, in addition to team spirit and cooperation, favours collective work and the engagement of athletes with team goals, in addition to facilitating the development of positive social relationships with teammates. Task orientation also provides the internalization of secondary characteristics such as perseverance, contribution to the group, constant improvement, self-assessment and the culture of effort (Montecinos et al., 2014), which are also associated with group cohesion (Eys et al., 2019). According to AGT (Sarrazin et al., 2001), achievement goals are competence-based aims those individuals target in evaluative contexts (i.e. in sports). The primary goal of a task-involved athlete is learning and mastery of the task for its own sake. Thus, task involvement appears when the athlete is intrinsically interested in the activity and judges his own self in a self-referenced manner (Duchesne & Ratelle, 2020). Task orientation has been associated with several positive outcomes, such as challenging tasks, effective study strategies, positive attitudes toward learning, enjoyment, intrinsic motivation and positive emotions (Harwood et al., 2015; Jaakkola et al., 2016; Keegan et al., 2010; Sit & Lindner, 2005).
Harwood et al. (2015) observed in a systematic review that the motivational climate focused on the task was consistently associated with a series of positive results of competence, self-esteem, performance, intrinsic motivation and positive affective states with colleagues. Elliot et al. (1999) observed that task-oriented individuals are primarily motivated by mastery or improvement of personal skills. Thus, these individuals reflect high levels of group cohesion in order to improve affective bonds (social cohesion) and desired objectives (cohesion for task). Thus, our findings corroborate the literature, demonstrating that task orientation can be considered a predictor of positive outcomes within youth sports, such as group cohesion (Harwood et al., 2015; Pineda-Espejel et al., 2017).
Furthermore, our results showed that this type of motivational orientation seems to act as a protective factor against the possible social conflicts that arise within the team, partially confirming the first hypothesis of the study. These findings show that characteristics such as the high standards of performance, organization and discipline of their capacities seem to impede the development of social conflicts within the group (Eklund & Tenenbaum, 2013; Eys et al., 2019; Paradis et al., 2014a).
Social conflicts within the group are linked to disagreements, behaviour oppositions (discussions, bullying, aggression) and seem to be inhibited when athletes have a common goal (e.g., winning a competition) (Paradis et al., 2014a). Thus, the orientation to the task seems to have an important role in protecting against the emergence of social conflicts among the young athletes surveyed since it stimulates the effort to achieve collective goals.
On the other hand, the orientation for the ego presented a positive predictor role on the dimensions of social conflicts and task within the group, confirming the second hypothesis of the study. According to AGT (Sarrazin et al., 2001), ego-oriented athletes are concerned with comparing their skills in relation to other athletes, defining their success from their own prominence, generating a social comparison, leading to group conflicts both of a social character and collective goals.
These findings reinforce the evidence already found in the literature that argues that ego orientation has been associated with negative outcomes within the sports context, such as higher levels of anxiety, development of burnout syndrome, and a greater predisposition to cheat to achieve success (Isoard-Gautheur et al., 2016; Pineda-Espejel et al., 2017), Ring and Kavussanu (2018) observed that the orientation for the ego was positively associated with the acceptance of cheating in young British athletes, as well as with the increased possibility of cheating within the scenario in which the athlete was inserted, against teammates, to achieve better personal performance.
From the three cluster profiles obtained, it was possible to verify that athletes with a high orientation for the task and low orientation for the ego (Cluster 3) reported higher cohesion scores for the task when compared to athletes with low values for orientation for ego and task (Cluster 2). These findings show that the greater the effort and interest of the athlete in their own performance parameters (task orientation), the more these athletes will be attracted to collective tasks and goals (Caruzzo et al., 2013; Duchesne & Ratelle, 2020). Such results are supported by the AGT (Sarrazin et al., 2001), which demonstrates that athletes with high task orientation scores are associated with higher levels of persistence and commitment in sports, in addition to being more interested and striving to improve their individual and collective performance. It is emphasized that athletes committed to their respective modalities are more likely to develop positive outcomes, such as group cohesion, intrinsic motivation, well-being, and sports success (Harwood et al., 2015).
Regarding group conflicts (see Table 3), the findings show that athletes with high orientation to the ego and task (Cluster 1) presented a higher perception of group conflict (social and task) when compared to the other cluster profiles. These findings indicate that the high orientation to the ego can lead to the triggering of conflicts for both the task and the social, even if the athlete has a high orientation for the task.
Specifically, it can be inferred that efforts to develop personal skills and compare them with others seem to act as a driver of behaviours that generate situations of disagreement among group members about the tasks to be performed, including differences in views, ideas and opinions (Eklund & Tenenbaum, 2013; Eys et al., 2019; Paradis et al., 2014b), in addition to interpersonal conflicts and personality confrontations that are not directly related to the execution of the tasks (Paradis et al., 2014b). Similar results were found by Castro-Sánchez et al. (2018) in a study with young Spanish semi-professional athletes. The authors observed that high levels of orientation for the ego and task favoured the emergence of rivalry within the group, especially in individual sports, while in team sports, conflicts can be perceived as a moment of group learning.
Limitations and future research directions
Despite the results presented in this study, it is important to highlight some limitations. First, the sample consisted only of athletes from a single state, which makes it impossible to generalize the results with the national and international scenarios. However, the athletes participated in the main sports competition in the region. In addition, the study presented a cross-sectional design, evaluating athletes in just one moment of the season, which makes it impossible to analyze the cause-and-effect relationships between variables. Thus, it is suggested that future research should also be conducted with athletes from other team sports in order to compare groups, as well as the involvement of other variables and with a longitudinal design to verify the possible variance of the variables over a season.
CONCLUSIONS
The evidence suggests that, in the context of youth athletes, task orientation seems to positively predict the perception of team cohesion, whilst ego orientation seems to be a positive predictor of group conflict and a negative predictor of task cohesion. Athletes with lower scores of task and ego orientations showed higher scores in task cohesion and group conflict. From a practical point of view, this study comprehensively showed how AGT could influence the activity of youth athletes because depending on the motivation of these subjects and the way they seek to achieve their goals, they can positively or negatively influence the group and the individual. Thus, the importance of developing an interpersonal environment with athletes, coaches and physical education professionals is highlighted since such environments tend to contribute to the development of cohesion and conflict within the group among young athletes.
