IDEAS home Printed from https://ideas.repec.org/p/wsu/wpaper/rosenman-5.html
   My bibliography  Save this paper

Patients' Perceptions and Treatment Effectiveness

Author

Listed:
  • Sean Murphy
  • Robert Rosenman
  • Jon Yoder
  • Dan Firesner

    (School of Economic Sciences, Washington State University)

Abstract

An extensive literature relating patients’ expectations to treatment outcomes has not addressed the determinants of these expectations. We argue that treatment history is part of a reference point that influences patients’ expectations of how effective further treatment might be, thus influencing whether to proceed with additional treatment or not. We hypothesize that those patients with unsuccessful prior treatments have diminished expected improvement from subsequent treatments. Prospect theory provides a theoretical foundation for reference frame effects, and the model is tested with data on patients diagnosed with idiopathic intracranial hypertension. Our results support the reference frame hypothesis.

Suggested Citation

  • Sean Murphy & Robert Rosenman & Jon Yoder & Dan Firesner, 2008. "Patients' Perceptions and Treatment Effectiveness," Working Papers 2008-19, School of Economic Sciences, Washington State University.
    • Handle: RePEc:wsu:wpaper:rosenman-5
    as

    Download full text from publisher

    File URL: http://faculty.ses.wsu.edu/WorkingPapers/Rosenman/WP_2008_19_IIH-PT.pdf
    File Function: First version, 2008
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jonathan R. Treadwell & Leslie A. Lenert, 1999. "Health Values and Prospect Theory," Medical Decision Making, , vol. 19(3), pages 344-352, August.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
    4. Diana Stratmann-Schoene & Thomas Klose, 2001. "Health Values and Prospect Theory," Medical Decision Making, , vol. 21(1), pages 57-59, February.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
    7. repec:adr:anecst:y:1999:i:55-56:p:09 is not listed on IDEAS
    8. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    9. Jason Abrevaya & Jerry A. Hausman, 1999. "Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells," Annals of Economics and Statistics, GENES, issue 55-56, pages 243-275.
    10. Wakker, Peter & Tversky, Amos, 1993. "An Axiomatization of Cumulative Prospect Theory," Journal of Risk and Uncertainty, Springer, vol. 7(2), pages 147-175, October.
    11. Emma B. Rasiel & Kevin P. Weinfurt & Kevin A. Schulman, 2005. "Can Prospect Theory Explain Risk-Seeking Behavior by Terminally Ill Patients?," Medical Decision Making, , vol. 25(6), pages 609-613, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sean M. Murphy & Dan L. Friesner & Robert Rosenman, 2012. "Patients' perceptions and treatment effectiveness: a reassessment using generalized maximum entropy," Applied Economics Letters, Taylor & Francis Journals, vol. 19(13), pages 1243-1248, September.

    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. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    2. LiCalzi, Marco & Sorato, Annamaria, 2006. "The Pearson system of utility functions," European Journal of Operational Research, Elsevier, vol. 172(2), pages 560-573, July.
    3. Ulrich Schmidt & Horst Zank, 2008. "Risk Aversion in Cumulative Prospect Theory," Management Science, INFORMS, vol. 54(1), pages 208-216, January.
    4. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    5. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier & Pinto, Jose Luis, 2016. "An elicitation of utility for quality of life under prospect theory," Journal of Health Economics, Elsevier, vol. 48(C), pages 121-134.
    6. Peter Brooks & Simon Peters & Horst Zank, 2014. "Risk behavior for gain, loss, and mixed prospects," Theory and Decision, Springer, vol. 77(2), pages 153-182, August.
    7. Pavlo Blavatskyy, 2021. "A simple non-parametric method for eliciting prospect theory's value function and measuring loss aversion under risk and ambiguity," Theory and Decision, Springer, vol. 91(3), pages 403-416, October.
    8. Marcello Basili & Alain Chateauneuf & Fulvio Fontini, 2005. "Choices Under Ambiguity With Familiar And Unfamiliar Outcomes," Theory and Decision, Springer, vol. 58(2), pages 195-207, March.
    9. Mohammed Abdellaoui & Han Bleichrodt & Corina Paraschiv, 2007. "Loss Aversion Under Prospect Theory: A Parameter-Free Measurement," Management Science, INFORMS, vol. 53(10), pages 1659-1674, October.
    10. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    11. Adam Booij & Bernard Praag & Gijs Kuilen, 2010. "A parametric analysis of prospect theory’s functionals for the general population," Theory and Decision, Springer, vol. 68(1), pages 115-148, February.
    12. Ulrich Schmidt & Chris Starmer & Robert Sugden, 2008. "Third-generation prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 203-223, June.
    13. Laurent Denant-Boemont & Olivier L’Haridon, 2013. "La rationalité à l'épreuve de l'économie comportementale," Revue française d'économie, Presses de Sciences-Po, vol. 0(2), pages 35-89.
    14. George Wu & Alex B. Markle, 2008. "An Empirical Test of Gain-Loss Separability in Prospect Theory," Management Science, INFORMS, vol. 54(7), pages 1322-1335, July.
    15. Peon, David & Calvo, Anxo & Antelo, Manel, 2014. "A short-but-efficient test for overconfidence and prospect theory. Experimental validation," MPRA Paper 54135, University Library of Munich, Germany.
    16. Veronika Köbberling & Peter P. Wakker, 2003. "Preference Foundations for Nonexpected Utility: A Generalized and Simplified Technique," Mathematics of Operations Research, INFORMS, vol. 28(3), pages 395-423, August.
    17. Elodie Adida, 2021. "Outcome-Based Pricing for New Pharmaceuticals via Rebates," Management Science, INFORMS, vol. 67(2), pages 892-913, February.
    18. Han Bleichrodt & Ulrich Schmidt & Horst Zank, 2009. "Additive Utility in Prospect Theory," Management Science, INFORMS, vol. 55(5), pages 863-873, May.
    19. George Wu & Jiao Zhang & Mohammed Abdellaoui, 2005. "Testing Prospect Theories Using Probability Tradeoff Consistency," Journal of Risk and Uncertainty, Springer, vol. 30(2), pages 107-131, January.
    20. Stefan A. Lipman & Werner B.F. Brouwer & Arthur E. Attema, 2019. "QALYs without bias? Nonparametric correction of time trade‐off and standard gamble weights based on prospect theory," Health Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 843-854, July.

    More about this item

    Keywords

    Prospect Theory; Treatment Outcomes; Treatment History; Misclassification; Monotone Rank Estimator;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:wsu:wpaper:rosenman-5. 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: Danielle Engelhardt (email available below). General contact details of provider: https://edirc.repec.org/data/ecwsuus.html .

    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.