IDEAS home Printed from https://ideas.repec.org/a/spr/patien/v4y2011i4p267-275.html
   My bibliography  Save this article

Can Patients Diagnosed with Schizophrenia Complete Choice-Based Conjoint Analysis Tasks?

Author

Listed:
  • John Bridges
  • Elizabeth Kinter
  • Annette Schmeding
  • Ina Rudolph
  • Axel Mühlbacher

Abstract

Background: Schizophrenia is a severe mental illness associated with hallucinations, delusions, apathy, poor social functioning, and impaired cognition. Researchers and funders have been hesitant to focus efforts on treatment preferences of patients with schizophrenia because of the perceived cognitive burden that research methods, such as conjoint analysis, place on them. Objective: The objective of this study was to test if patients diagnosed with schizophrenia were able to complete a choice-based conjoint analysis (often referred to as discrete-choice experiments) and to test if meaningful trade-offs were being made. Methods: German outpatients diagnosed with schizophrenia were eligible to participate in this study if they were aged 18–65 years, had received treatment for at least 1 year and were not experiencing acute symptoms. Conjoint analysis tasks were based on six attributes, each with two levels, which were identified via a literature review and focus groups. A psychologist in a professional interview facility presented each respondent with the eight tasks with little explanation. All interviews were recorded, transcribed, and analyzed to verify that respondents understood the tasks. Preferences were assessed using logistic regression, with a correction for clustering. Results: We found evidence that the 21 patients diagnosed with schizophrenia participating in the study could complete conjoint analysis tasks in a meaningful way. Patients not only related to the scenarios presented in conjoint tasks, but explicitly stated that they used their own preferences to judge which scenarios were better. Statistical analysis confirmed all hypotheses about the attributes (i.e. all attributes had the expected sign). Having a supportive physician, not feeling slowed, and improvements in stressful situations (p>0.01) were the most important attributes. Conclusions: We found that patients diagnosed with schizophrenia can complete conjoint analysis tasks, that they base their decisions on their own preferences, and that patients make trade-offs between attributes. Copyright Adis Data Information BV 2011

Suggested Citation

  • John Bridges & Elizabeth Kinter & Annette Schmeding & Ina Rudolph & Axel Mühlbacher, 2011. "Can Patients Diagnosed with Schizophrenia Complete Choice-Based Conjoint Analysis Tasks?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 4(4), pages 267-275, December.
    • Handle: RePEc:spr:patien:v:4:y:2011:i:4:p:267-275
    DOI: 10.2165/11589190-000000000-00000
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.2165/11589190-000000000-00000
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.2165/11589190-000000000-00000?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    2. John Bridges & Elizabeth Kinter & Lillian Kidane & Rebekah Heinzen & Colleen McCormick, 2008. "Things are Looking up Since We Started Listening to Patients," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 1(4), pages 273-282, October.
    3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    4. Mickael Bech & Trine Kjaer & Jørgen Lauridsen, 2011. "Does the number of choice sets matter? Results from a web survey applying a discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 20(3), pages 273-286, March.
    5. Michael Klag & Ellen MacKenzie & Christopher Carswell & John Bridges, 2008. "The Role of The Patient in Promoting Patient-Centered Outcomes Research," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 1(1), pages 1-3, January.
    6. Ryan, Mandy, 1999. "Using conjoint analysis to take account of patient preferences and go beyond health outcomes: an application to in vitro fertilisation," Social Science & Medicine, Elsevier, vol. 48(4), pages 535-546, February.
    7. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    8. Tara Maddala & Kathryn A. Phillips & F. Reed Johnson, 2003. "An experiment on simplifying conjoint analysis designs for measuring preferences," Health Economics, John Wiley & Sons, Ltd., vol. 12(12), pages 1035-1047, December.
    9. Jordan J. Louviere & Towhidul Islam & Nada Wasi & Deborah Street & Leonie Burgess, 2008. "Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(2), pages 360-375, March.
    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. John F. P. Bridges & Jui-Hua Tsai & Ellen Janssen & Norah L. Crossnohere & Ryan Fischer & Holly Peay, 2019. "How Do Members of the Duchenne and Becker Muscular Dystrophy Community Perceive a Discrete-Choice Experiment Incorporating Uncertain Treatment Benefit? An Application of Research as an Event," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(2), pages 247-257, April.
    2. Marta Trapero-Bertran & Beatriz Rodríguez-Martín & Julio López-Bastida, 2019. "What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-15, July.
    3. Emily Lancsar & Peter Burge, 2014. "Choice modelling research in health economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 28, pages 675-687, Edward Elgar Publishing.

    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. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    2. Elizabeth Kinter & Thomas Prior & Christopher Carswell & John Bridges, 2012. "A Comparison of Two Experimental Design Approaches in Applying Conjoint Analysis in Patient-Centered Outcomes Research," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 5(4), pages 279-294, December.
    3. Poulos, Christine & Yang, Jui-Chen & Patil, Sumeet R. & Pattanayak, Subhrendu & Wood, Siri & Goodyear, Lorelei & Gonzalez, Juan Marcos, 2012. "Consumer preferences for household water treatment products in Andhra Pradesh, India," Social Science & Medicine, Elsevier, vol. 75(4), pages 738-746.
    4. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    5. Sever, Ivan & Verbič, Miroslav & Klarić Sever, Eva, 2019. "Cost attribute in health care DCEs: Just adding another attribute or a trigger of change in the stated preferences?," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    6. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    7. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    8. Deborah Marshall & John Bridges & Brett Hauber & Ruthanne Cameron & Lauren Donnalley & Ken Fyie & F. Reed Johnson, 2010. "Conjoint Analysis Applications in Health — How are Studies being Designed and Reported?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 249-256, December.
    9. Yang, Jui-Chen & Johnson, F. Reed & Kilambi, Vikram & Mohamed, Ateesha F., 2015. "Sample size and utility-difference precision in discrete-choice experiments: A meta-simulation approach," Journal of choice modelling, Elsevier, vol. 16(C), pages 50-57.
    10. Charles Cunningham & Ken Deal & Yvonne Chen, 2010. "Adaptive Choice-Based Conjoint Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 257-273, December.
    11. Jürgen Meyerhoff & Malte Oehlmann & Priska Weller, 2015. "The Influence of Design Dimensions on Stated Choices in an Environmental Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(3), pages 385-407, July.
    12. Axel C. Mühlbacher & Andrew Sadler & Christin Juhnke, 2021. "Personalized diabetes management: what do patients with diabetes mellitus prefer? A discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(3), pages 425-443, April.
    13. Axel Mühlbacher & Uwe Junker & Christin Juhnke & Edgar Stemmler & Thomas Kohlmann & Friedhelm Leverkus & Matthias Nübling, 2015. "Chronic pain patients’ treatment preferences: a discrete-choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(6), pages 613-628, July.
    14. Marcel F. Jonker & Bas Donkers & Esther de Bekker‐Grob & Elly A. Stolk, 2019. "Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 350-363, March.
    15. Mandy Ryan & Karen Gerard & Gillian Currie, 2012. "Using Discrete Choice Experiments in Health Economics," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 41, Edward Elgar Publishing.
    16. Danne, M. & Musshoff, O. & Schulte, M., 2019. "Analysing the importance of glyphosate as part of agricultural strategies: A discrete choice experiment," Land Use Policy, Elsevier, vol. 86(C), pages 189-207.
    17. Jui-Chen Yang & Shelby D. Reed & Steve Hass & Mark B. Skeen & F. Reed Johnson, 2021. "Is Easier Better Than Harder? An Experiment on Choice Experiments for Benefit-Risk Tradeoff Preferences," Medical Decision Making, , vol. 41(2), pages 222-232, February.
    18. Jorien Veldwijk & Mattijs S Lambooij & Esther W de Bekker-Grob & Henriëtte A Smit & G Ardine de Wit, 2014. "The Effect of Including an Opt-Out Option in Discrete Choice Experiments," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    19. Tappenden, P & Brazier, J & Ratcliffe, J, 2006. "Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A," MPRA Paper 29772, University Library of Munich, Germany.
    20. Ateesha Mohamed & A. Hauber & Maureen Neary, 2011. "Patient Benefit-Risk Preferences for Targeted Agents in the Treatment of Renal Cell Carcinoma," PharmacoEconomics, Springer, vol. 29(11), pages 977-988, November.

    More about this item

    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:spr:patien:v:4:y:2011:i:4:p:267-275. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.