Slade Eric P, Becker Kimberly D
U.S. Department of Veterans Affairs, VA Capitol Healthcare Network (VISN5) Mental Illness Research, Education, and Clinical Center, 737 W. Lombard Street, Room 526, Baltimore, MD, 21201, USA,
Prev Sci. 2014 Dec;15(6):807-17. doi: 10.1007/s11121-013-0445-z.
This paper discusses the steps and decisions involved in proximal-distal economic modeling, in which social, behavioral, and academic outcomes data for children may be used to inform projections of the economic consequences of interventions. Economic projections based on proximal-distal modeling techniques may be used in cost-benefit analyses when information is unavailable for certain long-term outcomes data in adulthood or to build entire cost-benefit analyses. Although examples of proximal-distal economic analyses of preventive interventions exist in policy reports prepared for governmental agencies, such analyses have rarely been completed in conjunction with research trials. The modeling decisions on which these prediction models are based are often opaque to policymakers and other end-users. This paper aims to illuminate some of the key steps and considerations involved in constructing proximal-distal prediction models and to provide examples and suggestions that may help guide future proximal-distal analyses.
本文讨论了近端到远端经济模型构建中涉及的步骤和决策，其中儿童的社会、行为和学业成果数据可用于为干预措施的经济后果预测提供信息。当无法获取某些成年期长期成果数据时，基于近端到远端建模技术的经济预测可用于成本效益分析，或用于构建完整的成本效益分析。尽管在为政府机构编写的政策报告中存在预防性干预措施的近端到远端经济分析示例，但此类分析很少与研究试验一起完成。这些预测模型所基于的建模决策对于政策制定者和其他最终用户来说往往是不透明的。本文旨在阐明构建近端到远端预测模型所涉及的一些关键步骤和注意事项，并提供可能有助于指导未来近端到远端分析的示例和建议。
