The Susceptibles, Chancers, Pragmatists, and Fair Players: An Examination of the Sport Drug Control Model for Adolescent Athletes, Cluster Effects, and Norm Values Among Adolescent Athletes
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Notice bibliographique
Résumé
Although there are few high-profile cases of adolescent athletes being caught doping, up to a third of young athletes may dope. In order to generate a more accurate understanding of why adolescent athletes dope, it is important to validate models that help to explain this behavior. The aims of this study were 3-fold: firstly, to test the Sport Drug Control Model for Adolescent Athletes (SDCM-AA); secondly, to generate athlete profiles that would help quantify the proportion of athletes who are at risk of doping; and thirdly, to create norm values for the Adolescent Sport Doping Inventory (ASDI), which would allow national doping organizations, sporting organizations, and clubs to benchmark the scores of their athletes for key psycho-social variables linked to doping. A total of 2208 adolescent athletes from the United Kingdom, Australia, Hong Kong, and the United States completed the ASDI. The data presented an appropriate fit to the SDCM-AA model, in which 54% of the variance in susceptibility to doping was explained in the model, and 44.8% of attitudes toward doping was accounted for. Four distinct clusters of athletes emerged: the Susceptibles (i.e., identified with the benefits of doping, were willing to cheat, and viewed little threat), the Chancers (i.e., identified with the benefits of doping, scored high on willingness to cheat, and were highly influenced by their reference group, but had an average score for threat, self-esteem, and legitimacy), the Pragmatists (i.e., did not engage with any aspects of doping, but were more susceptible than the fair players), and Fair Players (i.e., high levels of sportspersonship, unwilling to cheat, and viewed doping as a threat). The revised SDCM-AA appears a valid model that helps explain the factors associated with doping attitudes and doping susceptibility. Adolescent athletes can be classified into one of four clusters, in relation to doping. Their cluster group could influence the content of the anti-doping education they receive.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle