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The impact of considering adaptation in health state valuation

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  • Damschroder, Laura J.
  • Zikmund-Fisher, Brian J.
  • Ubel, Peter A.
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    Abstract

    Patients with chronic health conditions often rate their quality of life (QoL) significantly higher than non-patients. One explanation for this discrepancy is that non-patients focus on the negative aspects of the onset of a condition, especially the early difficulties people face when they first experience a debilitating condition, without considering that patients can adapt to it over time. To test this hypothesis, we had 359 people perform person tradeoff (PTO) elicitations in an online survey, varying whether the treatment programs under consideration saved the lives of patients (a) with pre-existing paraplegia; or (b) who would experience new onset of paraplegia. Half of each group completed an "adaptation exercise" which encouraged them to consider their own ability to emotionally adapt to negative events in general and specifically to having paraplegia. The adaptation manipulation increased the value participants placed on pre-existing paraplegia (p=0.03) and on new onset paraplegia (p=0.05), relative to saving healthy lives. Moreover, the adaptation exercise dramatically reduced the differences between evaluations of pre-existing and new onset paraplegia to values within 2% of each other. Our findings suggest that asking non-patients to do an adaptation exercise before giving QoL ratings may help close the gap in ratings between patients and citizen non-patients.

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    Bibliographic Info

    Article provided by Elsevier in its journal Social Science & Medicine.

    Volume (Year): 61 (2005)
    Issue (Month): 2 (July)
    Pages: 267-277

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    Handle: RePEc:eee:socmed:v:61:y:2005:i:2:p:267-277

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    Related research

    Keywords: Adaptation Person tradeoff Health state valuation Cost-effectiveness analysis Utility measure Internet survey;

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    Cited by:
    1. Dolan, Paul & Kavetsos, Georgios & Tsuchiya, Aki, 2013. "Sick but satisfied: The impact of life and health satisfaction on choice between health scenarios," Journal of Health Economics, Elsevier, vol. 32(4), pages 708-714.
    2. Schwarzinger, Michaël & Carrat, Fabrice & Luchini, Stéphane, 2009. ""If you have the flu symptoms, your asymptomatic spouse may better answer the willingness-to-pay question": Evidence from a double-bounded dichotomous choice model with heterogeneous anchori," Journal of Health Economics, Elsevier, vol. 28(4), pages 873-884, July.
    3. Cubi-Molla, P. & Jofre-Bonet, M. & Serra-Sastre, V., 2013. "Adaptation to Health States: A Micro-Econometric Approach," Working Papers 13/02, Department of Economics, City University London.
    4. Sylvie M. C. van Osch & Anne M. Stiggelbout, 2008. "The construction of standard gamble utilities," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 31-40.
    5. Octave Jokung & Serge Macé, 2013. "Long-term health investment when people underestimate their adaptation to old age-related health problems," The European Journal of Health Economics, Springer, vol. 14(6), pages 1003-1013, December.
    6. Victoria A. Shaffer & Lukas Hulsey, 2009. "Are patient decision aids effective? Insight from revisiting the debate between correspondence and coherence theories of judgment," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(2), pages 141-146, March.
    7. Michaël Schwarzinger & Fabrice Carrat & Stéphane Luchini, 2009. ""If you have the flu symptoms, your asymptomatic spouse may better answer the willingness-to-pay question". Evidence from a double-bounded dichotomous choice model with heterogeneous anchori," Post-Print inserm-00636179, HAL.
    8. McTaggart-Cowan, H & O'Cathain, A & Tsuchiya, A & Brazier, J, 2009. "A qualitative study exploring the general population’s perception of rheumatoid arthritis after being informed about disease adaptation," MPRA Paper 29836, University Library of Munich, Germany.
    9. N. Flynn, Terry & J. Peters, Tim & Coast, Joanna, 2013. "Quantifying response shift or adaptation effects in quality of life by synthesising best-worst scaling and discrete choice data," Journal of choice modelling, Elsevier, vol. 6(C), pages 34-43.

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