TY - JOUR
T1 - A novel approach for evaluating programs designed to serve military veterans
T2 - Using an adapted common components analysis
AU - Richardson, Cameron B.
AU - Morgan, Nicole R.
AU - Bleser, Julia A.
AU - Aronson, Keith R.
AU - Perkins, Daniel F.
N1 - Funding Information:
This work was supported by a seed grant provided by the Social Science Research Institute (SSRI) at The Pennsylvania State University . The SSRI had no involvement in study conceptualization, execution, or write-up.
Funding Information:
The authors wish to thank our colleagues from The Veteran Metrics Initiative for their support of this work (Bradford Booth, Laurel Copeland, Erin Finley, Cynthia Gilman, Chris Jamieson, Suzanne Lederer, William Skimmyhorn, Jackie Vendermeersch, and Dawne Vogt - http://www.hjfcp3.org/tvmi/ ). We would also like to recognize the assistance of team members in the preparation of this manuscript. We thank April Gunsallus, MS, for her assistance with coding Veteran programs and Elise Dreibelbis for editing this manuscript. This work was supported by a seed grant provided by the Social Science Research Institute at The Pennsylvania State University.
Publisher Copyright:
© 2018 Elsevier Ltd
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/2
Y1 - 2019/2
N2 - Evaluators are challenged to keep pace with the vast array of Veteran support programs operating in the United States, resulting in a situation in which many programs lack any evidence of impact. Due to this lack of evidence, there is no efficient way to suggest which programs are most effective in helping Veterans in need of support. One potential solution to this dilemma is to reconceptualize program evaluation, by moving away from evaluating programs individually to evaluating what is common across programs. The Common Components Analysis (CCA) is one such technique that aggregates findings from programs that have undergone rigorous evaluation at the level of program components (e.g., content, process, barrier reduction). Given that many Veteran programs lack outcome evidence from rigorous studies, an adaptation to CCA is needed. This report examines cross-sectional data from a pilot study using an adapted CCA across five domains of well-being (i.e., employment, education, legal/financial/housing, mental/physical health, and social/personal relationships). The purpose of this preliminary study is to determine the feasibility of eliciting program nominations and program components from Veterans via an online survey. When coupled with a longitudinal research design, this adaptation to CCA will allow for stronger causal claims about the expected impact of different program components within and across a variety of domains.
AB - Evaluators are challenged to keep pace with the vast array of Veteran support programs operating in the United States, resulting in a situation in which many programs lack any evidence of impact. Due to this lack of evidence, there is no efficient way to suggest which programs are most effective in helping Veterans in need of support. One potential solution to this dilemma is to reconceptualize program evaluation, by moving away from evaluating programs individually to evaluating what is common across programs. The Common Components Analysis (CCA) is one such technique that aggregates findings from programs that have undergone rigorous evaluation at the level of program components (e.g., content, process, barrier reduction). Given that many Veteran programs lack outcome evidence from rigorous studies, an adaptation to CCA is needed. This report examines cross-sectional data from a pilot study using an adapted CCA across five domains of well-being (i.e., employment, education, legal/financial/housing, mental/physical health, and social/personal relationships). The purpose of this preliminary study is to determine the feasibility of eliciting program nominations and program components from Veterans via an online survey. When coupled with a longitudinal research design, this adaptation to CCA will allow for stronger causal claims about the expected impact of different program components within and across a variety of domains.
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U2 - 10.1016/j.evalprogplan.2018.10.012
DO - 10.1016/j.evalprogplan.2018.10.012
M3 - Article
C2 - 30343224
AN - SCOPUS:85055016880
SN - 0149-7189
VL - 72
SP - 145
EP - 151
JO - Evaluation and Program Planning
JF - Evaluation and Program Planning
ER -