INTRODUCTION

The sports performance of an athlete is the result of a set of physical, technical, tactical, and psychological variables that affect their performance in many competitive situations (Eys & Brawley, 2018; Weinberg & Gould, 2017). Among the psychological factors that improve or debilitate a performance, mood states stand out for promoting changes in behavior patterns (Berger & Owen, 1988; Searight & Montone, 2017; Carvalho et al. 2022), focus of vision, energy expenditure (Weinberg & Gould, 2017), aerobic resistance (Murgia et al. 2016), and modulation of athletes' organic responses (Arruda et al. 2013).

In this sense, positive mood states can help to overcome adverse or unpleasant situations during sports practice, which can cause internal imbalances that culminate in inadequate physiological and behavioral responses (Searight & Montone, 2017). Therefore, the athletes need to show an adequate mood profile to achieve higher sports performance (Brandt et al. 2014; Andrade et al. 2016; Weinberg & Gould, 2017), and said ideal profile, as named by Morgan (1980), would be the iceberg profile. When showing the iceberg profile, the athlete experiences low negative mood indexes (tension, depression, hostility, fatigue and confusion) and high positive mood index vigor (Rohlfs et al. 2008; Searight & Montone, 2017).

However, the mood profile of an athlete can change very fast due to their ephemeral nature (Lane & Terry, 2000), being of paramount importance to identify associated variables that can be manipulated, in order to provide better sports performance and competitive condition to the athlete (Lowther & Lane, 2002).

In this sense, group cohesion, considered as one of the most relevant sports variable for improving team performance and success (Benson et al. 2016; Saénz-López et al. 2021) has been highlighted. Understood as the tendency of a group to unite and remain united in the pursuit of goals and the satisfaction of affective needs (Carron et al. 1985; Weinberg & Gould, 2017), group cohesion is manifested in the social and task dimensions.

Social cohesion refers to interpersonal relationships that seek to meet the needs of social belonging, reflecting how much team members like each other (Carron et al. 2002; Eys et al. 2009). On the other side, task cohesion reflects the degree in which team members stay united to reach collective goals related to performance, referring on how much team members work together (Filho et al. 2014; Nascimento-Junior et al. 2016).

Both social cohesion and task cohesion notions are determined from the athletes’ individual perceptions on team environment (Eys et al. 2009). This way, the athlete’s perceptions and feelings on the sports environment stand out as important factors that can affect in changes in their mood states (Vieira et al. 2008). According to Oh and Gill (2017), environment perception developed by group members can affect members’ cognition, individual feelings, and behaviors. Scientific literature also associates group cohesion to better interpretation of pre-competition anxiety (Wolf et al. 2014), depressive symptoms on youth athletes (Nixdorf et al. 2016), satisfaction of basic needs (Erikstad et al. 2018), stress (Benrabah et al. 2020), and athletes’ personalities (Kim et al. 2020).

Thus, greater group cohesion of the teams seems to affect positively many psychological variables of sportspeople. From this presupposition, this study raises a research problem on the possibility of an associative relation between group cohesion and the athletes’ mood sates, when hypothesizing that higher cohesion levels are associated with better mood profiles, such as the iceberg profile.

The relation between group cohesion and mood states of adult athletes was investigated in the studies of Terry et al. (2000) and Lowther and Lane (2002), which showed strong indication of an association between the variables, offering support to the hypothesis of this study. However, when considering that emotional instability manifests more intensely in young athletes (Frank et al. 2015; Nixdorf et al. 2016; Sabato et al. 2016), the investigation of the relation between cohesion and mood in the context of youth sports is justifiable.

By considering that group cohesion consequences need to be widely investigated (Eys & Brawley, 2018) and new investigations on the group cohesion of young athletes are necessary (Benson et al. 2016; Eys et al. 2018; Filho et al. 2014), this study tries to analyze possible associations between group cohesion and pre-competition mood states in youth athletes.

MATERIALS AND METHODS

Participants

81 athletes from both sexes (M=62/ 76.5%; F= 19/ 23.5%), with average age of 15.6±1.2 years, who practiced collective sports (basketball, soccer, indoor soccer and volleyball) participated in the study. The sample was intentionally selected by convenience, as the purpose of the study was to investigate the pre-competition period and the athletes would participate of two state competitions. The power of the sample was calculated through G*Power 3.1.9.4 program, indicating post hoc values of α=0.05 and β=0.57, which must be analyzed with caution (Thomas et al. 2012). The participation in the study was voluntary, and no participants were excluded. The Research Ethics Committee of Instituto Federal do Paraná approved the study with opinion n. 3.424.869.

Instruments

To assess pre-competition mood states, we used the Profile Mood States - POMS inventory (Viana et al. 2001) composed of 42 simple mood indicators, which are answered in the five-point Likert scale and gathered in six dimensions (tension, depression, hostility, fatigue, vigor and confusion). High scores for each dimension represent bigger manifestation of said mood state. In the validation process for Portuguese, the instrument showed satisfying psychometric attributes (Viana et al., 2001).

In order to identify group cohesion levels, we used the Group Environment Questionnaire - GEQ (Nascimento-Junior et al. 2012) composed of 16 items to be answered in the 9-point Likert scale. The items of this tool assess group cohesion level in sport teams, by analyzing Individual Attraction and Group Integration factors, manifested in two dimensions (Task and Social). Higher average scores mean higher cohesion level in each one of the factors and dimensions. In the validation process for Portuguese, the instrument showed satisfying psychometric attributes (Nascimento-Junior et al. 2012). Both instruments were systematized in an electronic form.

Study Design and Methodological Procedures

This study is characterized by a cross-sectional outline with a quantitative analysis of the data (Thomas et al. 2012). In the two visits to the training sites of the teams participating in the study, we presented the research procedures and delivered them the Free and Informed Term of Consent (FITC) in our first visit. Our second visit, for signed terms collection and application of the research instruments, occurred on the week prior to the athletes’ participation in the two main youth competitions of the State of Paraná, and the following procedures took place: (a) before the commencement of the training activities, the athletes were directed to reserved spaces in the gymnasiums; (b) after the delivery of the signed TIFC, the athletes received a tablet with the research instruments; and (c) after answering to the questionnaire, the athletes would return to the training activities. The average time to answer to the questionnaire was 11 minutes per athlete.

Data Processing and Analysis

The answers in the forms feed the Microsoft Excel® worksheets, which are later exported to the Statistical Package Social Sciences (SPSS®) program, version 25, for statistical treatment and analysis. The category measures of the likert scale of the data collection instruments were converted into numbers, in order to obtain the averages of each mood states dimension and group cohesion. From the average mood indexes in each dimension, the sample was dichotomized into athletes with iceberg profile (WIP), those who show tension, depression, hostility, fatigue, and mental confusion indexes below the instrument average and vigor above the average, and without iceberg profile (WOIP), representing those who did not show that profile.

The average and standard deviation were used to analyze the dimensions of mood states, group cohesion and sample description. Data normality was verified through the Kolmogorov-Smirnov test. The Spearman Correlation Coefficient (CC) was used to assess the correlation between the dimensions of mood states and group cohesion. A binary logistic regression was conducted with the sample dichotomized into WIP and WOIP, to determine the explanatory percentage (R2) of group cohesion on mood states, as well as the odds ratio (OR) and the confidence interval (CI) of this relation. A significance level of p<0.05 was used in all tests.

RESULTS

The athletes investigated in the present study are from youth academy, participate in state and national competitions and had 3.9±1.7 years of sports experience (in competitions). Data referring to mood states profile indicate that 49.4% of the sample (n=40) showed the iceberg profile. Table 1 shows descriptive data on age, sex and quantitative number of athletes with iceberg profile.

Table 2 shows that social cohesion has a significant negative correlation with the depression and fatigue dimensions at 0.05 level (r= -.214 and r= -.260, respectively) and with the anger and confusion dimensions at 0.01 level (r= -.313 and r= -.348, respectively). Social cohesion is positively correlated with the vigor dimension (r=.371; p<0. 01), and no correlation with the tension dimension was observed. Task cohesion has a significant negative correlation with the tension dimension at 0.05 level (r= -.243) and with the depression, anger, fatigue and confusion dimensions at 0.01 level (r= -.309, r= -.359, r= -.334, and r= -.462 respectively). The task cohesion also has a positive correlation with vigor state (r=.381; p<0.01). The strongest correlation identified was negative, between task cohesion and confusion state (r= -.462; p<0.01).

Table 3 shows the results of the binary logistic regression, including the dimensions of social cohesion and task cohesion as predictor variables, and outcome variable dichotomized into groups with iceberg profile (WIP) and without iceberg profile (WOIP). Both social dimension (r2=0.218; OR=2.056; IC=1.35-3.12) and task dimension (r2=0.259; OR=2.481; IC=1.47-4.16) are shown as significant predictors of the athletes’ pre-competition mood states profile. Higher indexes of task and social cohesion are associated to the iceberg profile. Among the cohesion dimensions, task dimension appears as a stronger predictor of mood states.

DISCUSSION

This study sought to investigate the relation between group cohesion of sport teams and the pre-competition mood profile of youth athletes. The main findings indicate that: (a) practically half of the investigated athletes presented the iceberg profile, however, a representative part of the sample (50.6%) did not have a positive model of mood in the pre-competitive period; (b) social cohesion has a positive correlation with vigor state and negative correlation with depression, anger, fatigue, and confusion states; (c) task cohesion has a positive correlation with vigor state and a negative correlation with tension, depression, anger, fatigue, and confusion states and; (d) although the two group cohesion dimensions are significantly correlated with mood states, the binary logistic regression determined task cohesion as a more relevant predictor of the iceberg mood profile.

The fact that less than a half of the athletes assessed (49.4%) presented the iceberg mood profile suggests possible emotional alterations to most parts of the athletes in the period preceding the competition. Results that diverge from previous studies (Arruda et al. 2013; Brandt et al. 2014; Escobar & Lacerda, 2010; Neves et al. 2016), which indicated the prevalence of iceberg profile athletes during pre-competition period. It is worth to emphasize that these studies were conducted in semi-elite or elite adult athletes, unlike this research, which was carried out on youth athletes.

According to Vieira et al. (2008), changes in the athletes’ mood in the sport context, among other factors, can depend on previous experiences. In this sense, a possible speculation that can justify the disagreement of the results of this study with other results already presented in the literature is the influence of sports experience on the regulation of pre-competitive mood, as adult athletes have a longer sport trajectory, greater emotional intelligence (Suárez & Jiménez, 2021) and a more effective control of feelings of anxiety and distress (Zarceño et al. 2017), which can contribute in mood adjustment.

Although there is consensus on the importance of appropriate mood for the moment of competition (Brandt et al. 2014; Parsons-Smith et al. 2017; Weinberg & Gould, 2017), the lower rate of iceberg profile among young athletes (even more expressive in young women athletes), if compared to adult athletes who have better mood states (Arruda et al. 2013; Brandt et al. 2014; Escobar & Lacerda, 2010; Neves et al. 2016), suggest the need for a more careful look into mood states of youth athletes.

Both group cohesion dimensions (social and task) have a positive correlation with vigor and a negative correlation with negative mood states (except for social cohesion and tension states), indicating association between higher group cohesion levels with better pre-competition mood states. Fitzgerald et al. (2012) suggest that social relation influence the athletes’ behavioral and psychosocial results. In addition, according to Vieira et al. (2008), mood states of an athlete can alter from their situation awareness. In this sense, when perceiving a more cohesive, pleasant and welcoming social environment, due to the greater cohesion of their group, the athlete tends to have a more positive mood profile.

The results of this study suggest that the greater the cohesion perception among team members, the greater the chance of the athlete showing the iceberg profile. Kavussanu & Al-Yaaribi (2019) also identified a strong relation between pro-social behavior within the team and better emotional results on athletes, reinforcing this theory. In this sense, we can consider the development of good group cohesion levels as fundamental, which can affect positively mood and, consequently, the team's sport performance.

Task cohesion correlates strongly with mood states dimensions. In addition, logistic regression indicated higher odds ratio for task cohesion as mood states predictor. In this sense, athletes with high task cohesion levels have a greater chance of presenting mood states appropriate for better sport performance. Although social and task cohesion standards are susceptible to changes throughout the useful life of the group (Jamieson, 2010), for Dunlop et al. (2013), social cohesion can take some time to develop. As group members get to know each other, task cohesion manifests quickly, and can justify higher task dimensions levels in the assessed teams.

In general, task related aspects are more relevant for people involved in sport teams than social aspects (Leo-Marcos et al. 2013; Nascimento-Junior et al. 2018). In a complementary way, López et al. (2012) emphasize that in performance-oriented sport teams, there is a tendency to model behaviors aimed at task aspects, which can justify greater relevance of task cohesion for pre-competition mood states in youth athletes.

Recent reviews have indicated greater relation of task dimension with better sport teams performance (Benson et al. 2016; Filho et al. 2014), emphasizing the prominent role of task cohesion for teamwork productivity (Callow et al. 2009). Considering that highly task oriented individuals tend to feel well succeeded when they strive and see improvements as a result of their hard work (Kavussanu & Al-Yaaribi, 2019), it seems plausible a greater correlation of task dimension with better pre-competition mood states.

This study has some limitations. In relation to data collection instruments, although both have been validated for Portuguese context, specific versions for the age group of the surveyed population could have been used. No data were collected on the athletes' recent injury history. In addition, a larger sample could enable other analysis perspectives.

Finally, it is important to highlight that the intention of this study was not to exhaust the discussions about associative relation between the variables, but the opposite. We tried to explore in a preliminary manner the relation between group cohesion and mood states of youth athletes. In this sense, even considering these limitations, the original character of the study can represent an initial step for new investigations on the relation of constructs group cohesion and mood states and on how these variables relate to the sports performance of athletes in these age groups.

FINAL CONSIDERATIONS

This study tried to investigate the possible relation of group cohesion and pre-competition mood states of youth athletes of collective sport modalities. The expectation a priori was that higher group cohesion levels would be associated to the occurrence of the iceberg mood profile. The main results indicated that both task cohesion and social cohesion have a significant positive correlation with vigor state and a negative correlation with negative mood dimensions. In addition, task cohesion was revealed to be the strongest predictor of mood states, confirming the hypothesis of this study.

Data still suggest that youth athletes have a less adjusted mood profile than older and professional athletes, justifying a more accentuated care with this age group of athletes. In this sense, new studies on different aspects of mood in this population are necessary.

REFERENCES

Andrade, E., España, S., Rodríguez, D. (2016). Factores de estado de ánimo precompetitivo en adolescentes de deportes colectivos y satisfacción con el rendimento. Revista de Psicología del Deporte (Journal of Sport Psychology),25(2 ),229-236.

Arruda, F. S. D. A., Moreira, A., Nunes, J. A., Viveiros, L., De Rose, D., Aoki, M. S. (2013). Monitoramento do nível de estresse de atletas da seleção brasileira de basquetebol feminino durante a preparação para a Copa América de 2009. Revista Brasileira de Medicina do Esporte,19(1 ),44-47.https://doi.org/10.1590/S1517-86922013000100009.

Benrabah, K., Bennadja, M., Fayçal, K. M. (2020). The level of community cohesiveness under psychological pressure and control center for emerging football players u17. Acta Facultatis Educationis Physicae Universitatis Comenianae,60(1 ),44-54.https://doi.org/10.2478/afepuc-2020-0004.

Benson, A. J., Šiška, P., Eys, M., Priklerová, S., Slepička, P. (2016). A prospective multilevel examination of the relationship between cohesion and team performance in elite youth sport. Psychology of Sport and Exercise,27(1 ),39-46.https://doi.org/10.1016/j.psychsport.2016.07.009.

Berger, B. G., Owen, D. R. (1988). Stress reduction and mood enhancement in four exercise modes: Swimming, body conditioning, hatha yoga, and fencing. Research Quarterly for Exercise and Sport,59(2 ),148-159.https://doi.org/10.1080/02701367.1988.10605493.

Brandt, R., Liz, C. M., Crocetta, T. B., Arab, C., Bevilacqua, G., Dominski, F. H., … Andrade, A. (2014). Saúde mental e fatores associados em atletas. Revista Brasileira de Medicina do Esporte,20(4 ),276-280.https://doi.org/10.1590/1517-86922014200401607.

Callow, N., Smith, M. J., Hardy, L., Arthur, C. A., Hardy, J. (2009). Measurement of transformational leadership and its relationship with team cohesion and performance level. Journal of Applied Sport Psychology,21(4 ),395-412.https://doi.org/10.1080/10413200903204754.

Carron, A. V., Widmeyer, W. N., Brawley, L. R. (1985). The Development of an Instrument to Assess Cohesion in Sport Teams: The Group Environment Questionnaire. Journal of Sport Psychology,7(1 ),214-266.https://doi.org/10.1016/S0889-5406(05)81187-4.

Carron, A. V., Colman, M. M., Wheeler, J., Stevens, D. (2002). Cohesion and performance in sport: a meta analysis. Journal of Sport & Exercise Psychology,24(2 ),168-188.https://doi.org/10.1017/CBO9781107415324.004.

Carvalho, R., Monteiro, D., Rodrigues, F (2022). Relação entre os estados de humor e a síndrome de Overtraining em jovens atletas. Cuadernos de Psicología del Deporte,22(1 ),279-291.https://doi.org/10.6018/cpd.486041.

Dunlop, W. L., Falk, C. F., Beauchamp, M. R. (2013). How dynamic are exercise group dynamics? Examining changes in cohesion within class-based exercise programs. Health Psychology,32(12 ),1240-1243.https://doi.org/10.1037/a0030412.

Erikstad, M. K., Martin, L. J., Haugen, T., Høigaard, R. (2018). Group cohesion, needs satisfaction, and self-regulated learning: A one-year prospective study of elite youth soccer players’ perceptions of their club team. Psychology of Sport and Exercise,39,171-178.https://doi.org/10.1016/j.psychsport.2018.08.013.

Escobar, L., Lacerda, A. (2010). Identificação e caracterização dos estados de humor de atletas da seleção carioca de beach soccer durante o campeonato brasileiro. Movimento & Percepção,11(16 ),107-119.

Eys, M. A., Brawley, L. R. (2018). Reflections on cohesion research with sport and exercise groups. Social and Personality Psychology Compass,12(4 ),1-15.https://doi.org/10.1111/spc3.12379.

Eys, M., Bruner, M. W., Martin, L. J. (2018). The dynamic group environment in sport and exercise. Psychology of Sport and Exercise,42,40-47.https://doi.org/10.1016/j.psychsport.2018.11.001.

Eys, M., Loughead, T., Bray, S. R., Carron, A. V. (2009). Development of a cohesion questionnaire for youth: The Youth Sport Environment Questionnaire. Journal of Sport and Exercise Psychology,31(3 ),390-408.https://doi.org/10.1123/jsep.31.3.390.

Filho, E., Dobersek, U., Gershgoren, L., Becker, B., Tenenbaum, G. (2014). The cohesion-performance relationship in sport: a 10-year retrospective meta-analysis. Sport Sciences for Health,10(3 ),165-177.https://doi.org/10.1007/s11332-014-0188-7.

Fitzgerald, A., Fitzgerald, N., Aherne, C. (2012). Do peers matter? A review of peer and/or friends’ influence on physical activity among American adolescents. Journal of Adolescence,35(4 ),941-958.https://doi.org/10.1016/j.adolescence.2012.01.002.

Frank, R., Nixdorf, I., Beckmann, J. (2015). Depression in elite athletes: prevalence and psychological factors. Deutsche Zeitschrift Fur Sportmedizin,64(11 ),1-6.https://doi.org/10.5960/dzsm.2013.088.

Jamieson, J. P. (2010). The home field advantage in athletics: a meta-analysis. Journal of Applied Social Psychology,40(7 ),1819-1848.https://doi.org/10.1111/j.1559-1816.2010.00641.x.

Kavussanu, M., Al-Yaaribi, A. (2019). Prosocial and antisocial behaviour in sport. International Journal of Sport and Exercise Psychology,0(0 ),1-24.https://doi.org/10.1080/1612197X.2019.1674681.

Kim, J., Godfrey, M., Eys, M., Kim, J., Godfrey, M., Eys, M. (2020). The antecedents and outcomes of informal roles in interdependent sport teams. Sport Exercise and Performance Psychology,9(3 ),277-291.https://doi.org/10.1037 / spy0000179.

Lane, A. M., Terry, P. C. (2000). The Nature of Mood: development of a conceptual model with a focus on depression. Journal of Applied Sport Psychology,12(1 ),16-33.https://doi.org/10.1080/10413200008404211.

Leo-Marcos, F. M., Sánchez-Miguel, P. A., Sánchez-Oliva, D., Alonso, D. A., Calvo, T. G. (2013). El liderazgo y el clima motivacional del entrenador como antecedentes de la cohesión y el rol percibido en futbolistas semiprofesionales. Revista de Psicología del Deporte (Journal of Sport Psychology),22(2 ),361-370.

López, E. L., Rocha, D. C., Castillo, L. (2012). Relación entre cohesión y liderazgo en equipos deportivos del departamento de Boyacá - Colombia. Cuardernos de Psicología del Deporte,12(1 ),33-44.https://doi.org/10.4321/S1578-84232012000100004.

Lowther, J., Lane, A. (2002). Relationships between mood, cohesion and satisfaction with performance among soccer players. Athletic Insight,4(3 ),57-69.

Morgan, W. P. (1980). Test of Champions the Iceberg Profile. Psychology Today,14,92-108.

Murgia, M., Forzini, F., Filho, E., Di Fronso, S., Sors, F., Bertollo, M., Agostini, T. (2016). How do mood states change in a multi-stage cycling competition? Comparing high and low performers. Journal of Sports Medicine and Physical Fitness,56(3 ),336-342.

Nascimento-Junior, J. R. A., Granja, C. T. L., Fortes, L. D. S., Freire, G. L. M., Oliveira, D. V., Peixoto, E. M. (2018). Cross-cultural adaptation and psychometric properties of the portuguese version of the youth sport environment questionnaire (P-yseq). Journal of Physical Education and Sport,18(3 ),1606-1614.https://doi.org/10.7752/jpes.2018.03236.

Nascimento-Junior, J. R. A., Ribeiro, A. C., Moreira, C. R., Pizzo, G. C., Ribeiro, V. T., Vieira, L. F. (2016). Propriedades psicométricas do Questionário de Ambiente de Grupo (QAG) para o contexto do futebol e futsal de alto rendimento. Journal of Physical Education,27(1 ),2742-2742.https://doi.org/10.4025/jphyseduc.v27i1.2742.

Nascimento-Junior, J. R. A., Vieira, L. F., Rosado, A. F. B., Serpa, S. (2012). Validação do Questionário de Ambiente de Grupo (GEQ) para a língua portuguesa. Motriz. Revista de Educacao Fisica,18(4 ),770-782.https://doi.org/10.1590/S1980-65742012000400015.

Neves, A. N., Carvalho, A. J., Zanetti, M. C., Brandão, R. M. F., Ferreira, L. (2016). Dissimilaridade das habilidades mentais, traços de personalidade, alexitimia e estado de humor em atletas de tiro esportivo das Forças Armadas. Revista Brasileira de Psicologia Do Esporte,6(3 ),28-45.https://doi.org/10.31501/rbpe.v6i3.6618.

Nixdorf, I., Frank, R., Beckmann, J. (2016). Comparison of athletes’ proneness to depressive symptoms in individual and team sports: Research on psychological mediators in junior elite athletes. Frontiers in Psychology,7(6 ),1-8.https://doi.org/10.3389/fpsyg.2016.00893.

Oh, E., Gill, D. (2017). An examination of the relationship between team cohesion and individual anxiety among recreational soccer players. Journal of Amateur Sport,3(2 ),1-26.https://doi.org/10.17161/jas.v3i2.5883.

Parsons-Smith, R. L., Terry, P. C., Machin, M. A. (2017). Identification and description of novel mood profile clusters. Frontiers in Psychology,8(1 ),1-13.https://doi.org/10.3389/fpsyg.2017.01958.

Rohlfs, P. I. C. M., Rotta, T. M., Luft, C. D. B., Andrade, A., Krebs, R. J., Carvalho, D. (2008). Brunel Mood Scale (BRUMS): an Instrument for Early Detection of Overtraining Syndrome. Revista Brasileira de Medicina do Esporte,14(3 ),176-181.https://doi.org/10.1590/S1517-86922008000300003.

Sabato, T., Walch, T., Caine, D. (2016). The elite young athlete: strategies to ensure physical and emotional health. Journal of Sports Medicine,7(1 ),99-113.https://doi.org/10.2147/oajsm.s96821.

Saénz-López, P. B., Domínguez, C. V., Ruano, M. Á. G., González, J. A. R. (2021). The effect of teammates support on player’s free-throws effectiveness. Revista de Psicología del Deporte (Journal of Sport Psychology),30(2 ),81-86.

Searight, H. R., Montone, K. (2017). Profile of Mood States. In Encyclopedia of Personality and Individual Differences (pp,https://doi.org/1-6). https://doi.org/10.1007/978-3-319-28099-8_63-1.

Suárez, C. I., Jiménez, M. D. L. V. M. (2021). Rendimiento deportivo en atletas federados y su relación con autoestima, motivación e inteligencia emocional. Revista de Psicología Aplicada al Deporte y el Ejercicio Físico,6(2 ),1-13.https://doi.org/10.5093/rpadef2021a15.

Terry, P. C., Carron, A. V., Pink, M. J., Lane, A. M., Jones, G. J. W., Hall, M. P. (2000). Perceptions of group cohesion and mood in sport teams. Group Dynamics,4(3 ),244-253.https://doi.org/10.1037/1089-2699.4.3.244.

Thomas, J. R., Nelson, J. K., Silverman, S. J. (2012). Métodos de Pesquisa em Atividade Física (6a). Porto Alegre: Artmed..

Viana, M. F., Almeida, P., Santos, R. C. (2001). Adaptação portuguesa da versão reduzida do Perfil de Estados de Humor - POMS. Análise Psicológica,19(1 ),77-92.https://doi.org/10.14417/ap.345.

Vieira, L. F., Fernandes, S. uders, Vieira, J. L. L., Vissoci, J. R. N. (2008). Estado de humor e desempenho motor: um estudo com atletas de voleibol de alto rendimento. Revista Brasileira de Cineantropometria e Desempenho Humano,10(1 ),62-68.https://doi.org/10.5007/1980-0037.2008v10n1p62.

Zarceño, E. L., Vilella, S. B., Rosa, M. Á. S., López, N. P. (2017). Motivación y toma de decisiones en voleibol: Influencia de los años de experiencia. Revista de Psicología Aplicada al Deporte y el Ejercicio Físico,2(1 ),1-10.https://doi.org/10.5093/rpadef2017a4.

Weinberg, R. S., Gould, D. (2017). Fundamentos da Psicologia do Esporte e do Exercício (6a). Porto Alegre: Artmed..

Wolf, S. A., Eys, M. A., Kleinert, J. (2014). Predictors of the precompetitive anxiety response: relative impact and prospects for anxiety regulation. International Journal of Sport and Exercise Psychology,1,37-41.https://doi.org/10.1080/1612197X.2014.982676.

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