当前偏差与健康。
Present bias and health.
作者信息
Wang Yang, Sloan Frank A
机构信息
Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, 1225 Observatory Drive, Madison, WI 53706, USA.
Department of Economics, Duke University, 213 Social Sciences Building, Box 90097, Durham, NC 27708, USA.
出版信息
J Risk Uncertain. 2018 Oct;57(2):177-198. doi: 10.1007/s11166-018-9289-z. Epub 2018 Oct 25.
Abstract
This study uses a dynamic discrete choice model to examine the degree of present bias and naivete about present bias in individuals' health care decisions. Clinical guidelines exist for several common chronic diseases. Although the empirical evidence for some guidelines is strong, many individuals with these diseases do not follow the guidelines. Using persons with diabetes as a case study, we find evidence of substantial present bias and naivete. Counterfactual simulations indicate the importance of present bias and naivete in explaining low adherence rates to health care guidelines.
摘要
本研究使用动态离散选择模型来检验个体在医疗保健决策中当前偏差的程度以及对当前偏差的天真程度。针对几种常见慢性病都有临床指南。尽管一些指南的实证证据很充分，但许多患有这些疾病的个体并未遵循这些指南。以糖尿病患者为例进行研究，我们发现了大量当前偏差和天真程度的证据。反事实模拟表明，当前偏差和天真程度在解释医疗保健指南低遵循率方面具有重要意义。
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