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Measuring Gambling Harm: The Influence of Response Scaling on Estimates and the Distribution of Harm Across PGSI Categories
Journal of Gambling Studies ( IF 2.4 ) Pub Date : 2020-05-18 , DOI: 10.1007/s10899-020-09954-1
Paul Delfabbro , Neophytos Georgiou , Daniel L. King

Recent research has shown that harm is not just a feature of problem gambling, but can also be observed in other lower risk categories. Some debates exist, however, as to the distribution of harm across these categories and how harm should be best measured. This study was designed to examine how estimates of self-reported harm are affected by the methodology used. A particular focus was on how harm estimates for low and higher risk gambling (as classified by the PGSI) varied when respondents were able to make more graded attributions of their harm to gambling. An online panel sample of 554 gamblers responded to a brief survey that included the PGSI, measures of gambling harm drawn from Browne et al. (Assessing gambling-related harm in Victoria: a public health perspective, Victorian Responsible Gambling Foundation, Melbourne, 2016) as well as questions about demographics and gambling habits. The recruitment was designed to obtain good representation of each PGSI group, with 23% found to be problem gamblers; 36% moderate risk and 21% low risk gamblers. In support of Browne et al. (2016), the findings showed that higher proportions of harm in low risk gamblers is likely to be identified when one uses binary or ‘any harm’ scoring, but that this effect mostly disappears when more graded scoring or attribution of harm measures are used. Higher risk PGSI groups consistently reported more harms and more serious harms than lower risk groups. It was concluded that the measurement of gambling harm and its estimated distribution over PGSI categories is quite sensitive to how it is measured.



中文翻译:

衡量赌博危害:响应缩放对PGSI类别中危害的估计和分布的影响

最近的研究表明,伤害不仅是问题赌博的特征,而且在其他较低风险类别中也可以观察到。但是,关于这些类别中的危害分布以及如何最好地衡量危害,存在一些争论。本研究旨在检查自我报告危害的估计值如何受到所使用方法的影响。当受访者能够对赌博的危害做出更分级的归因时,重点尤其放在低风险和较高风险赌博(由PGSI分类)的危害估计上。554名赌徒的在线专家组样本对一项简短的调查做出了回应,其中包括PGSI,这是从Browne等人的文章中获得的赌博伤害度量。(评估维多利亚州与赌博相关的伤害:从公共卫生角度出发,维多利亚州负责任赌博基金会,墨尔本,2016年),以及有关人口统计学和赌博习惯的问题。该招募旨在使每个PGSI群体都能获得良好的代表性,其中23%被认为是有问题的赌徒;36%的中度风险者和21%的低风险赌徒。在布朗等人的支持下。(2016),研究结果表明,当人们使用二进制或``任何伤害''评分方式时,低风险赌徒中较高比例的伤害很可能会被识别出来,但是当使用更分级的评分或伤害措施归因时,这种影响大部分会消失。较高风险的PGSI组始终比较低风险的组报告更多的危害和更严重的危害。结论是,赌博伤害的衡量及其在PGSI类别上的估计分布对衡量方式非常敏感。该招募旨在使每个PGSI群体都能获得良好的代表性,其中23%被认为是有问题的赌徒;36%的中度风险者和21%的低风险赌徒。在布朗等人的支持下。(2016),研究结果表明,当人们使用二进制或``任何伤害''评分方式时,低风险赌徒中较高比例的伤害很可能会被识别出来,但是当使用更分级的评分或伤害措施归因时,这种影响大部分会消失。较高风险的PGSI组始终比较低风险的组报告更多的危害和更严重的危害。结论是,赌博伤害的衡量及其在PGSI类别上的估计分布对衡量方式非常敏感。招聘的目的是使每个PGSI组都能获得良好的代表,发现23%是问题赌徒;36%的中度风险者和21%的低风险赌徒。在布朗等人的支持下。(2016),研究结果表明,当人们使用二进制或``任何伤害''评分方式时,低风险赌徒中较高比例的伤害很可能会被识别出来,但是当使用更分级的评分或伤害措施归因时,这种影响大部分会消失。较高风险的PGSI组始终比较低风险的组报告更多的危害和更严重的危害。结论是,赌博伤害的衡量及其在PGSI类别上的估计分布对衡量方式非常敏感。研究结果表明,当人们使用二进制或“任何伤害”评分方式时,很可能会在低风险赌徒中发现较高比例的伤害,但是当使用更分级的评分方式或使用伤害措施的归因时,这种影响大部分会消失。较高风险的PGSI组始终比较低风险的组报告更多的危害和更严重的危害。结论是,赌博伤害的衡量及其在PGSI类别上的估计分布对衡量方式非常敏感。研究结果表明,当人们使用二进制或“任何伤害”评分方式时,很可能会在低风险赌徒中发现较高比例的伤害,但是当使用更分级的评分方式或使用伤害措施的归因时,这种影响大部分会消失。较高风险的PGSI组始终比较低风险的组报告更多的危害和更严重的危害。结论是,赌博伤害的衡量及其在PGSI类别上的估计分布对衡量方式非常敏感。

更新日期:2020-05-18
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