School of Psychology, University of Adelaide, Adelaide, SA 5005, Australia.
J Gambl Stud. 2010 Jun;26(2):205-27. doi: 10.1007/s10899-009-9160-x.
A quantitative observational study was undertaken to examine the relationship between individual factors and level of gambling involvement, in particular problem gambling (PG). The specific factors under study were personality, perceived luck, and attitudes towards gambling. A sample of university students (N = 185) completed a battery of questionnaires, consisting of the 16PF, Canadian Problem Gambling Index, Belief in Good Luck Scale (BIGL), Gambling Attitudes Scale (GAS), and the Impulsive Non-Conformity subscale (ImpNon) from the Oxford-Liverpool Inventory of Feelings and Experiences. Four groups were formed (Non-PG, Low-Risk, Moderate-Risk, and PG). Personality profiles varied between groups, and there were significant main effects and interaction effects on gender and personality factors. The PG group was higher on impulsivity, and belief in luck, and had more positive attitudes towards gambling. Multiple Regression Analysis and Discriminant Functions Analysis, using variables including some 16PF factors, BIGL and GAS variables, produced models that were highly predictive of gambling severity and gambling membership. In both models, impulsivity was the strongest predictor. These results were discussed in terms of their implications for future research and treatment of PG.
一项定量观察研究旨在探讨个体因素与赌博参与程度(特别是问题赌博)之间的关系。研究的具体因素包括人格、感知运气和对赌博的态度。一个大学生样本(N=185)完成了一系列问卷,包括 16PF、加拿大问题赌博指数、好运信仰量表(BIGL)、赌博态度量表(GAS)和牛津-利物浦情感和体验清单中的冲动非从众量表(ImpNon)。形成了四个组(非问题赌博者、低风险、中风险和问题赌博者)。人格特征在组间存在差异,性别和人格因素存在显著的主效应和交互效应。问题赌博组在冲动性、对运气的信念和对赌博的更积极态度方面得分更高。使用包括某些 16PF 因素、BIGL 和 GAS 变量在内的变量进行的多元回归分析和判别函数分析,产生了对赌博严重程度和赌博成员身份具有高度预测性的模型。在这两个模型中,冲动性是最强的预测因素。这些结果从未来研究和问题赌博治疗的角度进行了讨论。