IDEAS home Printed from https://ideas.repec.org/a/eee/epplan/v72y2019icp145-151.html

A novel approach for evaluating programs designed to serve military veterans: Using an adapted common components analysis

Author

Listed:
  • Richardson, Cameron B.
  • Morgan, Nicole R.
  • Bleser, Julia A.
  • Aronson, Keith R.
  • Perkins, Daniel F.

Abstract

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.

Suggested Citation

  • Richardson, Cameron B. & Morgan, Nicole R. & Bleser, Julia A. & Aronson, Keith R. & Perkins, Daniel F., 2019. "A novel approach for evaluating programs designed to serve military veterans: Using an adapted common components analysis," Evaluation and Program Planning, Elsevier, vol. 72(C), pages 145-151.
    • Handle: RePEc:eee:epplan:v:72:y:2019:i:c:p:145-151
    DOI: 10.1016/j.evalprogplan.2018.10.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0149718918300168
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.evalprogplan.2018.10.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Morgan, Nicole R. & Davis, Kelly D. & Richardson, Cameron & Perkins, Daniel F., 2018. "Common components analysis: An adapted approach for evaluating programs," Evaluation and Program Planning, Elsevier, vol. 67(C), pages 1-9.
    2. Jacoby, Jacob, 1984. "Perspectives on Information Overload," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(4), pages 432-435, March.
    3. Chewning, Eugene Jr & Harrell, Adrian M., 1990. "The effect of information load on decision makers' cue utilization levels and decision quality in a financial distress decision task," Accounting, Organizations and Society, Elsevier, vol. 15(6), pages 527-542.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter Gordon Roetzel, 2019. "Information overload in the information age: a review of the literature from business administration, business psychology, and related disciplines with a bibliometric approach and framework development," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 479-522, December.
    2. Cédric Aubin, 2014. "La surcharge d'informations, une difficulté de plus pour décider à l'hôpital : problématique et solution," Post-Print halshs-01519472, HAL.
    3. Joost Impink & Mari Paananen & Annelies Renders, 2022. "Regulation‐induced Disclosures: Evidence of Information Overload?," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 432-478, September.
    4. Adam Sanjurjo, 2015. "Search, Memory, and Choice Error: An Experiment," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-16, June.
    5. Maren Hartmann & Barbara E. Weißenberger, 2024. "Information overload research in accounting: a systematic review of the literature," Management Review Quarterly, Springer, vol. 74(3), pages 1619-1667, September.
    6. G. Rejikumar & Aswathy Asokan-Ajitha & Sofi Dinesh & Ajay Jose, 2022. "The role of cognitive complexity and risk aversion in online herd behavior," Electronic Commerce Research, Springer, vol. 22(2), pages 585-621, June.
    7. Massimiliano Celli & Simona Arduini & Tommaso Beck, 2024. "Corporate Sustainability Reporting Directive (CSRD) and His Future Application Scenario for Italian SMEs," International Journal of Business and Management, Canadian Center of Science and Education, vol. 19(4), pages 1-44, July.
    8. Ozgur Turetken & Ramesh Sharda, 2005. "Clustering-Based Visual Interfaces for Presentation of Web Search Results: An Empirical Investigation," Information Systems Frontiers, Springer, vol. 7(3), pages 273-297, July.
    9. Pluyter, J.R., 2012. "Designing immersive surgical training against information technology-related overload in the operating room," Other publications TiSEM d48c5727-92fd-41b1-be5d-5, Tilburg University, School of Economics and Management.
    10. Daniel Kohlert & Andreas Oehler, 2009. "Scheitern Finanzdienstleistungen am Verbraucher?: Eine theoretische Analyse rationalen Verbraucherverhaltens im Rahmen des Anlageberatungsprozesses," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 78(3), pages 81-95.
    11. Stocks, Morris H. & Harrell, Adrian, 1995. "The impact of an increase in accounting information level on the judgment quality of individuals and groups," Accounting, Organizations and Society, Elsevier, vol. 20(7-8), pages 685-700.
    12. Zablah, Alex R. & Brown, Brian P. & Donthu, Naveen, 2010. "The relative importance of brands in modified rebuy purchase situations," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 248-260.
    13. Cauberghe, Verolien & De Pelsmacker, Patrick, 2010. "The Effectiveness of Telescopic Ads Delivered Via Interactive Digital Television: The Impact of the Amount of Information and the Level of Interactivity on Brand Responses," Journal of Interactive Marketing, Elsevier, vol. 24(4), pages 297-308.
    14. William G. Heninger & Alan R. Dennis & Kelly McNamara Hilmer, 2006. "Research Note: Individual Cognition and Dual-Task Interference in Group Support Systems," Information Systems Research, INFORMS, vol. 17(4), pages 415-424, December.
    15. Alan L. Montgomery & Kartik Hosanagar & Ramayya Krishnan & Karen B. Clay, 2004. "Designing a Better Shopbot," Management Science, INFORMS, vol. 50(2), pages 189-206, February.
    16. Pennington, Robin R. & Kelton, Andrea Seaton, 2016. "How much is enough? An investigation of nonprofessional investors information search and stopping rule use," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 47-62.
    17. Tianchang Ni & Runping Zhu & Richard Krever, 2023. "Responses to News Overload in a Non-Partisan Environment: News Avoidance in China," SAGE Open, , vol. 13(3), pages 21582440231, July.
    18. Tomi Rajala, 2019. "Mind the Information Expectation Gap," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 104-125, March.
    19. Pushkin Kachroo & Anjala Krishen & Shaurya Agarwal, 2017. "Fuzzy logic programming based knowledge analysis for qualitative comparative analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2101-2113, September.
    20. Peter Gordon Roetzel & Burkhard Pedell & Daniel Groninger, 2020. "Information load in escalation situations: combustive agent or counteractive measure?," Journal of Business Economics, Springer, vol. 90(5), pages 757-786, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:epplan:v:72:y:2019:i:c:p:145-151. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/evalprogplan .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.