| Literature DB >> 35409585 |
Juan Carlos Guevara-Pérez1,2, Jorge Rojo-Ramos3, Santiago Gómez-Paniagua4, Jorge Pérez-Gómez3, José Carmelo Adsuar5.
Abstract
Given the importance of sport at a global level, the competitiveness of sport systems is a determining factor in attracting resources from different sectors. Competitiveness is largely measured by the athletes' level. Therefore, the production of competitive talent is an aspect that occupies the managers of different sports systems. This study analyzed the factor structure and reliability of a questionnaire for the evaluation of the perceptions of actors of a sport (canoeing) on the ability of the national system to produce talent in one of its modalities recently incorporated in the Olympic Games (OG) of Tokyo 2021. The sample consisted of 167 individuals linked to Spanish canoeing, who responded to the questionnaire "Evaluation of the current position in canoeing-sport with regard to talent" of the International Canoe Federation (ICF). Exploratory, confirmatory and reliability factor analyses were performed. The results showed a one-dimensional factor structure composed of seven items, with good and excellent goodness-of-fit values and high reliability (McDonald's Omega = 0.82). Thus, the ICF questionnaire can be considered a quick and easy to apply tool to analyze the perceptions about the development of talent in canoeing in order to take actions for the recruitment, promotion and development of talent.Entities:
Keywords: Olympic Games; canoeing; sport system; talent production; women and sport
Mesh:
Year: 2022 PMID: 35409585 PMCID: PMC8997617 DOI: 10.3390/ijerph19073901
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Characteristics of the sample (n = 167).
| Variable | Categories |
| % |
|---|---|---|---|
| Sex | Male | 105 | 62.9 |
| Female | 62 | 37.1 | |
| Age | Under 30 | 101 | 60.5 |
| Between 30 and 40 | 25 | 15 | |
| Between 41 and 50 | 31 | 18.6 | |
| Over 50 | 10 | 5.9 | |
| Modality | Kayak | 107 | 64.1 |
| Canoe | 60 | 35.9 | |
| Active in sports | Yes | 154 | 98.2 |
| No | 13 | 7.8 |
Descriptive statistics of items.
| Item | Mean | SD | Variance |
|---|---|---|---|
| 1 | 3.606 | 1.054 | 1.113 |
| 2 | 2.846 | 1.085 | 1.178 |
| 3 | 2.973 | 0.947 | 0.899 |
| 4 | 3.353 | 0.990 | 0.982 |
| 5 | 3.280 | 0.983 | 0.968 |
| 6 | 3.206 | 0.957 | 0.917 |
| 7 | 2.840 | 0.948 | 0.900 |
| 8 | 2.873 | 1.119 | 1.252 |
SD: Standard Deviation.
Items explained variance based on eigenvalues.
| Variable | Eigenvalue | Proportion of Variance |
|---|---|---|
| 1 | 3.382 | 0.483 |
| 2 | 0.959 | 0.137 |
| 3 | 0.820 | 0.117 |
| 4 | 0.705 | 0.100 |
| 5 | 0.510 | 0.072 |
| 6 | 0.389 | 0.055 |
| 7 | 0.232 | 0.033 |
| 8 | 0.160 | 0.020 |
Loading matrix.
| Item | Factor |
|---|---|
|
Do you consider that coaches have sufficient training to identify and develop athletes for women’s canoeing in Spain? | 0.523 |
|
Do you consider the current systems for the initiation and development of women’s canoeing in your club to be effective? | 0.591 |
|
Do you consider that there is a policy that links the Clubs–Autonomous Federations and the Royal Spanish Canoe Federation (RFEP) for the development of women’s canoeing in Spain? | 0.520 |
|
Do you consider that the current competition programs are adequate to develop women’s canoeing? | 0.872 |
|
Do you consider that the structure of the competition program encourages a progression in the development of canoe-women? | 0.840 |
|
Do you consider the age at which female athletes are currently joining canoeing in Spain to be appropriate? | 0.594 |
|
Do you believe that current talent recruitment strategies encourage the right type of athletes for women’s canoeing in Spain? | 0.711 |
|
Do you consider that this sport has a low dropout rate of female canoeists in Spain? | 0.081 |
Note: These items are a literal translation into English for ease of reading, not a cross-cultural adaptation into English.
Polychoric correlation matrix for 7 items.
| Items | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1 | 1 | ||||||
| 2 | 0.393 | 1 | |||||
| 3 | 0.258 | 0.113 | 1 | ||||
| 4 | 0.371 | 0.500 | 0.417 | 1 | |||
| 5 | 0.288 | 0.392 | 0.440 | 0.738 | 1 | ||
| 6 | 0.207 | 0.386 | 0.221 | 0.446 | 0.401 | 1 | |
| 7 | 0.399 | 0.282 | 0.398 | 0.460 | 0.537 | 0.480 | 1 |
Figure 1Factor model.
Goodness of fit indices.
| Indices | Values |
|---|---|
| NNFI | 0.971 |
| CFI | 0.992 |
| CMIN/DF | 1.322 |
| Ρ ( | 0.227 |
| RMSEA | 0.046 |
| RMSR | 0.034 |
NNFI: non-normed fit index; CFI: comparative fit index; CMIN/DF: minimum discrepancy per degree of freedom; P (χ2): chi-squared probability; RMSEA: root mean square error of approximation; RMSR: root mean square of residuals.
Reliability indices for each factor.
| Indices | Values |
|---|---|
| McDonald’s Omega | 0.816 |