评估彩票忠诚计划成员的问题赌博风险：一种机器学习方法

IF 3.7 2区医学 Q1 PSYCHOLOGY, CLINICAL

Addictive behaviors Pub Date : 2025-04-23 DOI:10.1016/j.addbeh.2025.108372

Paul Sacco, Jihyeong Jeong

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引用次数: 0

摘要

背景与目的彩票是一种相对良性的赌博形式。尽管如此，有赌博问题的个人可能会参与彩票游戏和/或专门玩彩票。彩票忠诚度计划的数据可用于筛选问题赌博，因为它们收集了注册以获得奖励的玩家的人口统计信息和购票信息。目前的研究评估了机器学习的可行性，利用从州彩票忠诚度计划收集的数据来识别有赌博问题的个人。方法将机票上传的数据与发送给忠诚度计划参与者的在线调查合并（N = 5903）。问题赌博严重程度指数（PGSI）用于筛选问题赌博，5或更大表示问题赌博(n = 809；14%)。其他调查项目询问其他赌博（例如赌场老虎机）的频率和花费金额。随机森林分析是一种预测建模技术，用于预测有赌博问题的个体。讨论与结论问题赌博在忠诚计划玩家中比在总体样本中更为常见。随机森林算法总体上表现相当好，但灵敏度较差，表明该模型不能有效识别有问题赌博的个体。彩票忠诚度计划可能是一个很有希望的筛选和二级预防措施的设置，因为问题赌博的患病率相对较高，但随机森林可能不是检测风险的最佳方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Assessing the risk of problem gambling among lottery loyalty program members: A machine learning approach

Background and Aims

Lottery gambling is a relatively benign form of gambling. Nonetheless, individuals with gambling problems may engage in lottery play and/or play the lottery exclusively. Lottery loyalty programs have data that could be used to screen for problem gambling, as they collect information on demographics and ticket purchases from players who sign up to receive incentives. The current study evaluates the feasibility of machine learning to identify individuals who have gambling problems using data collected from a state lottery loyalty program.

Methods

Data from ticket uploads was merged with an online survey sent to loyalty program participants (N = 5903). The Problem Gambling Severity Index (PGSI) was used to screen for problem gambling, with a five or greater denoting problem gambling (n = 809; 14%). Other survey items queried frequency of other gambling (e.g., casino slot machine) as well as amounts spent. Random forests analysis, a predictive modeling technique, was used to predict individuals who have gambling problems.

Discussion and Conclusions

Problem gambling was more common among loyalty program players than typical in population samples. The random forest algorithm performed fairly well overall, but sensitivity was poor, indicating that the model did not identify individuals with problem gambling effectively. Lottery loyalty programs may be a promising setting for screening and secondary prevention efforts because of relatively high prevalence of problem gambling, but random forests may not be the best approach for detecting those at risk.

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来源期刊

Addictive behaviors 医学-药物滥用

CiteScore

8.40

自引率

4.50%

发文量

283

审稿时长

46 days

期刊介绍： Addictive Behaviors is an international peer-reviewed journal publishing high quality human research on addictive behaviors and disorders since 1975. The journal accepts submissions of full-length papers and short communications on substance-related addictions such as the abuse of alcohol, drugs and nicotine, and behavioral addictions involving gambling and technology. We primarily publish behavioral and psychosocial research but our articles span the fields of psychology, sociology, psychiatry, epidemiology, social policy, medicine, pharmacology and neuroscience. While theoretical orientations are diverse, the emphasis of the journal is primarily empirical. That is, sound experimental design combined with valid, reliable assessment and evaluation procedures are a requisite for acceptance. However, innovative and empirically oriented case studies that might encourage new lines of inquiry are accepted as well. Studies that clearly contribute to current knowledge of etiology, prevention, social policy or treatment are given priority. Scholarly commentaries on topical issues, systematic reviews, and mini reviews are encouraged. We especially welcome multimedia papers that incorporate video or audio components to better display methodology or findings. Studies can also be submitted to Addictive Behaviors? companion title, the open access journal Addictive Behaviors Reports, which has a particular interest in ''non-traditional'', innovative and empirically-oriented research such as negative/null data papers, replication studies, case reports on novel treatments, and cross-cultural research.