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Cognitive Dissonance Personalized Feedback and Online Gambling Behavior: An Exploratory Study Using Objective Tracking Data and Subjective Self-Report

机译:认知失调个性化反馈和在线赌博行为:使用客观跟踪数据和主观自我报告的探索性研究

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摘要

Providing personalized feedback about the amount of money that gamblers have actually spent may—in some cases—result in cognitive dissonance due to the mismatch between what gamblers actually spent and what they thought they had spent. In the present study, the participant sample (N = 11,829) was drawn from a Norwegian population that had played at least one game for money in the past six months on the Norsk Tipping online gambling website. Players were told that they could retrieve personalized information about the amount of money they had lost over the previous 6-month period. Out of the 11,829 players, 4045 players accessed information about their personal gambling expenditure and were asked whether they thought the amount they lost was (i) more than expected, (ii) about as much as expected, or (iii) less than expected. It was hypothesized that players who claimed that the amount of money lost gambling was more than they had expected were more likely to experience a state of cognitive dissonance and would attempt to reduce their gambling expenditure more than other players who claimed that the amount of money lost was as much as they expected. The overall results contradicted the hypothesis because players without any cognitive dissonance decreased their gambling expenditure more than players experiencing cognitive dissonance. However, a more detailed analysis of the data supported the hypothesis because specific playing patterns of six different types of gambler using a machine-learning tree algorithm explained the paradoxical overall result.
机译:在某些情况下,由于赌徒实际支出与他们认为的支出之间不匹配,因此提供有关赌徒实际支出金额的个性化反馈可能会导致认知失调。在本研究中,参与者样本(N = 11,829)来自过去六个月在Norsk Tipping在线赌博网站上至少玩过一场有钱游戏的挪威人口。玩家被告知,他们可以检索有关他们在过去6个月内损失的钱数的个性化信息。在11,829名玩家中,有4045名玩家访问了有关其个人赌博支出的信息,并被询问是否认为自己损失的金额(i)高于预期,(ii)接近预期,或(iii)低于预期。假设那些声称赌博损失的钱比他们预期的多的球员更有可能经历认知失调状态,并且比其他声称损失金钱的球员更愿意减少赌博的支出。达到了他们的预期。总体结果与假设相矛盾,因为没有认知失调的玩家比经历认知失调的玩家减少了更多的赌博支出。但是,对数据进行更详细的分析支持了这一假设,因为使用机器学习树算法的六种不同类型赌徒的特定游戏模式解释了矛盾的总体结果。

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