Dynamical Systems Modeling to Identify a Cohort of Problem Drinkers with Similar Mechanisms of Behavior Change.
Dynamical Systems Modeling to Identify a Cohort of Problem Drinkers with Similar Mechanisms of Behavior Change.
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DOI：
10.17505/jpor.2017.09
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发表时间：
2017-01-01
影响因子：
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通讯作者：
Morgenstern, Jon
中科院分区：
文献类型：
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作者：
Bekele-Maxwell, Kidist;Everett, R A;Morgenstern, Jon
在酒精使用障碍患者中完全理解行为改变机制（MOBC）的一个挑战是，理论上改变过程是复杂的，动态的（时变的），有时是非线性的，它们相互作用影响酒精消费。我们使用动态系统建模来更好地了解接受治疗的问题饮酒者队列中的MOBC。我们将数学模型与治疗结束时成功减少饮酒的个体患者的生态瞬时评估数据进行了拟合。模型解与数据趋势相当一致，表明队列患者具有相似的MOBC。这项工作展示了使用个性化的方法进行心理研究，补充了通常在人口水平上应用的标准统计方法。
One challenge to understanding mechanisms of behavior change (MOBC) completely among individuals with alcohol use disorder is that processes of change are theorized to be complex, dynamic (time varying), and at times non-linear, and they interact with each other to influence alcohol consumption. We used dynamical systems modeling to better understand MOBC within a cohort of problem drinkers undergoing treatment. We fit a mathematical model to ecological momentary assessment data from individual patients who successfully reduced their drinking by the end of the treatment. The model solutions agreed with the trend of the data reasonably well, suggesting the cohort patients have similar MOBC. This work demonstrates using a personalized approach to psychological research, which complements standard statistical approaches that are often applied at the population level.