Factors associated with internet gambling in university students / by Nicholas M. Harris.
Notice bibliographique
Résumé
Problem gambling can have devastating financial, psychological, and social effects on the individual and the individual?s family. Over the past 15 years, Internet gambling has grown at an incredible pace and is believed to be a contributing factor to the increase in problem and pathological gamblers. Of particular concern is the increase in problematic gambling behaviours \nin university students. Research shows that university and college students engage in gambling more than any other group. The etiology of problem and pathological gambling is unknown, but is likely the result of numerous biological, psychological, and environmental factors. The current study examined factors related to problem Internet gambling in a university student sample (N = 325). Measures administered included the South Oaks Gambling Screen (SOGS), the DSM-lV-TR-Based Questionnaire (DBQ), the Canadian Problem Gambling Index (CPGI), three scales from the Jackson Personality Research Form (PRF) (Impulsivity, Desirability, and Infrequency), and a questionnaire examining gambling and Internet gambling behaviours and attitudes. Results showed that Internet gamblers were significantly more likely than non-Internet gamblers and non-gamblers to report engaging in high risk behaviours such as alcohol use, tobacco use, and marijuana use. Many Internet gamblers reported that Internet gambling negatively affects their academic achievement and some reported that it affects their class attendance. Internet gamblers were more likely than non-Internet gamblers to have reported having a family member with a past or current gambling problem, but no differences were found between Internet problem gamblers and Internet non-problem gamblers on this variable. Furthermore, as hypothesised, (1) Males were significantly more likely to gamble on the Internet, significantly more likely to meet DSM-IV-TR criteria for pathological gambling, and significantly more likely to meet CPGI criteria for problem gambling. However, males were not found to be significantly more likely than females to meet SOGS criteria for problem gambling. (2) Internet gamblers were significantly more likely to meet DSM-IV-TR criteria for pathological gambling and meet SOGS and CPGI criteria for problem gambling and (3) Internet gamblers were significantly more likely than non-Internet gamblers to report trusting the Internet gambling \nindustry. Finally, although impulsivity was not significantly correlated with problem gambling among all Internet gamblers, a significant positive correlation was found between impulsivity and problem Internet gambling behaviours among males. \nStudy population : Lakehead University students (Thunder Bay, Northwestern Ontario)
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».