Modeling behavior in a clinically diagnostic sequential risk-taking task
Modeling behavior in a clinically diagnostic sequential risk-taking task
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DOI：
10.1037/0033-295x.112.4.862
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发表时间：
2005-10-01
影响因子：
5.4
通讯作者：
Lejuez, CW
中科院分区：
文献类型：
--
作者：
Wallsten, TS;Pleskac, TJ;Lejuez, CW
本文模拟了冒险任务中潜在的学习和顺序选择的认知过程，目的是了解它们是如何在这个中等复杂的环境中发生的，以及其中的行为如何与自我报告的现实世界风险承担相关。最佳随机模型假设参与者错误地将结果概率视为平稳，以贝叶斯方式更新概率，在响应之前而不是在响应期间评估选择策略，并保持恒定的响应敏感性。与主观收益值相关的模型参数与外部风险承担具有良好的相关性。总体方法（可以随着基本范式的变化而扩展）和具体结果都为风险选择理论和将风险承担理解为公共卫生问题提供了方向。
This article models the cognitive processes underlying learning and sequential choice in a risk-taking task for the purposes of understanding how they occur in this moderately complex environment and how behavior in it relates to self-reported real-world risk taking. The best stochastic model assumes that participants incorrectly treat outcome probabilities as stationary, update probabilities in a Bayesian fashion, evaluate choice policies prior to rather than during responding, and maintain constant response sensitivity. The model parameter associated with subjective value of gains correlates well with external risk taking. Both the overall approach, which can be expanded as the, basic paradigm is varied, and the specific results provide direction for theories of risky choice and for understanding risk taking as a public health problem.