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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 807-817 |
| Number of pages | 11 |
| Journal | Prevention Science |
| Volume | 15 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jan 1 2013 |
| Externally published | Yes |
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Keywords
- Economic projection
- Prevention
- Proximal–distal modeling
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
Cite this
Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive Interventions. / Slade, Eric; Becker, Kimberly D.
In: Prevention Science, Vol. 15, No. 6, 01.01.2013, p. 807-817.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Understanding Proximal–Distal Economic Projections of the Benefits of Childhood Preventive Interventions
AU - Slade, Eric
AU - Becker, Kimberly D.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - 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.
AB - 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.
KW - Economic projection
KW - Prevention
KW - Proximal–distal modeling
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UR - http://www.scopus.com/inward/citedby.url?scp=84889999962&partnerID=8YFLogxK
U2 - 10.1007/s11121-013-0445-z
DO - 10.1007/s11121-013-0445-z
M3 - Article
C2 - 24337979
AN - SCOPUS:84889999962
VL - 15
SP - 807
EP - 817
JO - Prevention Science
JF - Prevention Science
SN - 1389-4986
IS - 6
ER -