Over the course of half a century, anxiety has been frequently considered in sports psychology as an acting emotion on performance (Grossbard et al., 2009: pp. 153-166) .
Consequently, concern about anxiety as a negative emotion (Lazarus, 2000: pp. 229-252) , has been addressed in many ways such as its nature and role in the field of sport (Woodman & Hardy, 2003: pp. 443-457) .
In this context, several unidimensional and multidimensional theoretical models have appreciated competitive anxiety. The transactional model of Lazarus and Folkman (1984) , is one of the most important models that has been agreed upon. This model indicates that the well-being of the athlete is endangered when the anticipation of the situation is threatening, and the achievement of the objective and the performance are put in a critical situation.
Anxiety that derives from the individual’s uncertain confrontation with environmental aggression is indicated as an unpleasant emotion (Lazarus, 2000: pp. 229-252; Skinner & Brewer, 2002: pp. 678-692) .
Some researchers in the field of sport psychology confirm that an unfavorable performance may be a result of a high level of competitive situational anxiety (Hardy, 1999: pp. 227-233; Horikawa & Yagi, 2012: pp. 1-5) .
The evaluation of precompetitive anxiety among our youth participants will provide us with a thorough understanding of the threatening situation, its interpretation and its frequency over time, with respect to coaching factors, level of experience and technical position, considered as environmental constraints in the training of young footballers.
The works of Khodayari et al. (2011: pp. 2280-2284), Sangari et al. (2012: pp. 1175-1178) , indicate that the level of competitive anxiety can be modified. However, the development of mental methods and techniques is essential, in order to reduce competitive anxiety and improve performance.
These are 76 Tunisian U15 footballers (average age 14.00, ET: 0.327), affiliated to the sectorial pre-training centers. These young athletes are subject to a training program supervised by the Tunisian National Technical Direction (Table 1).
To evaluate pre-competitive situational anxiety, we used the Tunisian version of the Competitive State Anxiety Inventory-2 Revised (CSAI-2R) including frequency and direction scales (Hajji & Elloumi, 2017: pp. 1-7) .
This version has allowed us to measure the level of intensity, direction and frequency of cognitive pre-competitive anxiety, somatic and the level of confidence a few minutes of the competition.
The intensity scale designed to measure precompetitive anxiety scores, each item is estimated on a four-point Likert scale (1 = not at all, 2 = somewhat, 3 = moderately, 4 = all at fact).
Table 1. The population of the study.
The direction scale designed to evaluate the directional interpretation of precompetitive anxiety. Responses range from minus three (−3) to plus three (+3) (−3 = very unfavorable, −2 = somewhat unfavorable, −1 = somewhat unfavorable, 0 = no effect on performance, +1 = somewhat favorable, +2 = quite favorable, +3 very favorable).
The frequency scale designed to evaluate the spread of pre-competitive anxiety over time, in this scale the responses range from 1 point (not at all) to 7 points (all the time).
After informing the managers of each training center through letters of recommendation certified by the National Technical Department, and after obtaining the consent of the coaches and parents, the athletes were invited during their sectorial groupings, to settle against the Tunisian version of CSAI-2R, 30 minutes before the competition.
In this context, studies by Stavrou et al. (2006: pp. 91-98) , indicate that the level of intensity and direction of precompetitive anxiety varies from one day to 30 minutes before the competition.
5.1. The Psychometric Properties of the Tunisian Version of CSAI-2R
5.1.1. The Internal Consistency of the Tunisian Version CSAI-2R
5.1.2. Exploratory Factor Analysis
The indices of the exploratory factor analysis are shown in Table 3.
Table 2. Cronbach alpha coefficients.
Table 3. The indices of the exploratory analysis.
The factor loads of the three scales are shown in Table 4.
5.1.3. Confirmatory Factors Analysis
The adjustment indices for the three subscales are shown in Table 5.
5.2. The Level of Competitive Anxiety
Mean scores and standard deviations for the different dimensions of precompetitive anxiety are shown in Table 6.
Generally, self-confidence is indicated as the most identified dimension in our participants, it is interpreted as a facilitator of performance and constantly demanded over time.
In relation to the training center factor, the dimension of self-confidence is most accepted by our elites across all three scales (see Table 7).
Table 4. Factor loads.
Table 5. Adjustment indices.
Table 6. Precompetitive anxiety scores.
5.3. The Effects of Interactions
Through MANOVA variance analysis, we distinguished only the effect of coaching on pre-competitive anxiety perceived by our participants
[Wilks Lambda = 0.292 < 1, F = 2.050, P = 0.005 < 0.05] (see Table 10)
Table 7. Pre-competitive anxiety scores versus training centers.
Table 8. Precompetitive anxiety scores in relation to the level of experience.
Table 9. Pre-competitive anxiety scores in relation to the player’s position.
Table 10. Impact of coaching, experience and technical position on precompetitive anxiety.
b. Exact statistics; c. The statistic is an upper bound of F that produces a lower bound on the level of significance.
The dimensions affected by this effect are the intensity of self-confidence and the frequency of somatic anxiety (see Table 11).
6.1. The Psychometric Properties of the Measuring Instrument
6.1.1. The Internal Consistency of the Scale
The coefficients of α Cronbach, are approved, and similar to those of the French version of Martinent et al. (2010) . In general, α Cronbach coefficients vary between 0.734 and 0.912, which are acceptable (De Vellis, 1991) .
6.1.2. Exploratory Factor Analysis for the Three Scales
1) The Kaiser-Meyer-Olkin Index
The value of Kaiser-Meyer-Olkin, which gives a global idea about the quality of inter-item correlations, is always greater than 0.5.
The KMO value for the scale of intensity equal to 0.801, for the scale of the direction equals 0.839, and for the scale of the frequency equal to 0.806, demonstrate that the correlations between the items are of good quality.
2) Bartlett Sphericity Test
The result of Bartlett’s sphericity test for intensity, direction and frequency scales is still significant at p < 0.05. We can therefore reject the null hypothesis that our data come from a population for which the matrix is an identity matrix, so the correlations are not all equal to zero.
3) Determinant of the matrix
The determinant values of the matrix for the three CSAI-2R scales are always small but different at zero (the intensity scale determinant = 4.149E−5, the
Table 11. Inter-subject effects tests.
direction scale determinant = 7.118E−5 and the determinant of the frequency scale = 5.701E−5), confirming the absence of multicollinearity (Hair et al., 2010) .
6.1.3. Confirmatory Factor Analysis
According to Tabachnick & Fidell (2007) , the results of the confirmatory factor analysis showed good fit indices for the three scales of our measuring instrument.
- The intensity scale: [X2 = 134.94 at p = 0.014; CFI = 0.947; TLI = 0.937 and RMSEA = 0.067],
- The scale of the direction: [X2 = 129.35 at p = 0.030; CFI = 0.952; TLI = 0.944 and RMSEA = 0.061],
- The frequency scale: [X2 = 147.08 at p = 0.002; CFI = 0.925; TLI = 0.911 and RMSEA = 0.078].
The AMOS software (see Figures 1-3), validates the factor structure of the three scales of the Tunisian version of CSAI-2R, which we used in our study.
6.2. The Level of Precompetitive Anxiety
According to the scores of the different dimensions of precompetitive anxiety, the dimension of self-confidence through its three measures, is the most identified among our young talents.
The same results were confirmed in relation to the factors of coaching, experience and technical position (defender, striker, goalkeeper...).
In this context, several studies confirm that elite athletes bring lower levels of cognitive and somatic anxiety intensity, and higher levels of precompetitive self-confidence.
These results are similar to those published in the work of Wolfram et al. (2008: pp. 153-159) , among elite riders evaluated by CSAI-2R.
Figure 1. Model of the hypothetical structure: the intensity scale. Circles represent latent constructions and squares represent measured variables. All parameters are standardized and significant at p < 0.05. Residual differences are indicated in small circles.
In the same vein, Mellalieu et al. (2006) , reported high levels of the direction of precompetitive anxiety and the intensity of precompetitive self-confidence in elite athletes.
Hanton & Jones (1999: pp. 1-21) , also reported that the majority of elite swimmers (85.3%) presented facilitative perceptions of pre-competitive anxiety. In addition, Hanton et al. (2004: pp. 169-181) , Craft et al. (2003: pp. 44-65) , Hanton et al. (2002: pp. 911-928) , indicate that measures of the intensity and frequency of pre-competitive anxiety manifest themselves as, predictors less important than the measure of direction, in elite athletes.
On the other hand, and in relation to the level of experience, Rokka et al. (2009: pp. 178-153) , confirmed that with 4 to 6 years of experience, the athlete
Figure 2. Model of the hypothetical structure: the direction scale. Circles represent latent constructions and squares represent measured variables. All parameters are standardized and significant at p < 0.05. Residual differences are indicated in small circles.
can adopt high levels of precompetitive self-confidence intensity and a facilitative directional interpretation of precompetitive anxiety. In contrast, less experienced athletes have revealed lower levels of self-confidence, with effects that are neither facilitative nor debilitating on their performance.
In contrast, Singley et al. (2012: pp. 453-496) , recently reported that there are no significant differences in frequency and direction levels of precompetitive cognitive and somatic anxiety, and in the level of intensity of precompetitive self-confidence between expert and non-expert cavaliers.
Based on the results obtained in our study and the results presented above, we have noted that most studies indicate that expert athletes reveal low levels of cognitive and somatic anxiety intensity and high levels of anxiety. Self-confidence with facilitating directional interpretations and positive diffusion over time of precompetitive anxiety.
Compared to the “technical station” factor, our study shows that through the three measures of pre-competitive anxiety, self-confidence is the most sought-after dimension by goalkeepers, defenders, players in the middle and
Figure 3. Model of the hypothetical structure: the frequency scale. Circles represent latent constructions and squares represent measured variables. All parameters are standardized and significant at p < 0.05. Residual differences are indicated in small circles.
attackers. In this context and following a thorough analysis of literature reviews in sports psychology, we found that our study is innovative in this field of study.
6.3. The Effects of Interactions
MANOVA variance analysis, which we performed to estimate interaction effect, coaching, experience and technical position, only demonstrates the presence of coaching influence on precompetitive anxiety in our participants.
The research interest in coaching behaviors and its effects on psychological variables such as anxiety (Keegan et al., 2011: pp. 1-55) , is exploited in young athletes with competitive practice (Fry et al., 2010: pp. 294-304; Gould et al., 2012: pp. 80-87) .
According to Martin et al. (2014: pp. 111-123) , young Americans view coaches as positive ascendants positive about their behaviors. In the same context, Balaguer et al. (2007: pp. 123-139) , ask that the coach support a favorable psychological environment for young athletes to exploit their maximum potential during the competition.
The coach-trainer represents informational support (Wolfenden & Holt, 2005: pp. 108-126) , and emotional support (Reinboth et al., 2004: pp. 297-313) . Coaches are among the most influential social factors in young athletes (Brustad et al., 2001: pp. 604-635) .
It has been justified that the motivational climate established by the coach (Gould et al., 2012: pp. 80-87; Smith et al., 2006: pp. 479-501) and the acts that he has commits to circulate (Fry et al., 2010: pp. 294-304) , have a direct influence on the personal and social development of young athletes.
In addition, coaches can have a negative influence on athletes (Keegan et al., 2011: pp. 1-55) , through certain behaviors which disadvantage the development of athletes (Reinboth & Duda, 2006: pp. 269-286) .
The management of stress and more precisely pre-competitive anxiety is a fundamental objective for the athlete and for all the actors active in the institutional system of training.
In this context, our work has been designed to present a well detailed repertoire to understand how pre-competitive anxiety is identified in our young footballers, during the main competitive events.
In our elite U15 footballers, the directional interpretation of self-confidence is always favorable for performance, and positively continuous over time.
The MANOVA analysis only shows the impact of the coach trainer. But the regression analysis did not reveal any significant predictive linear relationships.
On the other hand, the study of pre-competitive anxiety in relation to the technical position, such as the goalkeeper, the defender, the middle player or the attacker, is considered the first in this field of study.
Among the limitations of our work, we had examined only pre-competitive state anxiety and neglected precompetitive anxiety trait. However, the effect of personality, for example, among young elites in a decisive pre-training phase seems important to us for a highly selective career.
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