Division on Addictions, Cambridge Health Alliance, Cambridge, MA 02155, USA.
Eur J Public Health. 2012 Apr;22(2):273-8. doi: 10.1093/eurpub/ckp232. Epub 2010 Jan 27.
The goal of this study is to identify betting patterns displayed during the first month of actual Internet gambling on a betting site that can serve as behavioural markers to predict the development of gambling-related problems.
Using longitudinal data, k-means clustering analysis identified a small subgroup of high-risk gamblers.
Seventy-three percent of the members of this subgroup eventually closed their account due to gambling-related problems. The characteristics of this high-risk subgroup were as follows: (i) frequent and (ii) intensive betting combined with (iii) high variability across wager amount and (iv) an increasing wager size during the first month of betting.
This analysis provides important information that can help to identify potentially problematic gamblers during the early stages of gambling-related problems. Public health workers can use these results to develop early interventions that target high-risk Internet gamblers for prevention efforts. However, one study limitation is that the results distinguish only a small proportion of the total sample; therefore, additional research will be necessary to identify markers that can classify larger segments of high-risk gamblers.
本研究旨在识别在某博彩网站实际参与网络博彩的第一个月所表现出的投注模式，这些模式可以作为行为标记，用以预测与赌博相关问题的发展。
本研究采用纵向数据，通过 K-均值聚类分析确定了一小部分高风险赌客。
该亚组的 73%的成员最终因赌博相关问题而关闭了账户。该高风险亚组的特征如下：（i）频繁且（ii）大量投注，同时（iii）投注金额变化大，以及（iv）在投注的第一个月内投注金额不断增加。
该分析提供了重要信息，可以帮助在与赌博相关问题的早期阶段识别可能存在问题的赌客。公共卫生工作者可以利用这些结果针对高风险网络赌客开展早期干预，以进行预防工作。然而，本研究存在一个局限性，即结果仅区分了总样本的一小部分；因此，还需要开展更多的研究以确定能够对更大比例的高风险赌客进行分类的标记物。
