Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive Interventions

Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Prevention Science Springer Journals

Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive Interventions

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Publisher
Springer US
Copyright
Copyright © 2013 by Society for Prevention Research
Subject
Medicine & Public Health; Public Health; Health Psychology; Child and School Psychology
ISSN
1389-4986
eISSN
1573-6695
D.O.I.
10.1007/s11121-013-0445-z
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Prevention ScienceSpringer Journals

Published: Dec 15, 2013

References

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