IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v18y2017i9d10.1007_s10198-016-0856-4.html
   My bibliography  Save this article

Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques

Author

Listed:
  • Seda Erdem

    (University of Stirling)

  • Danny Campbell

    (University of Stirling)

Abstract

Stated preference elicitation techniques, such as discrete choice experiments and best-worst scaling, are now widely used in health research to explore the public’s choices and preferences. In this paper, we propose an alternative stated preference elicitation technique, which we refer to as ‘trio-wise’. We explain this new technique, its relative advantages, modeling framework, and how it compares to the best-worst scaling method. To better illustrate the differences and similarities, we utilize best-worst scaling Case 2, where individuals make best and worst (most and least) choices for the attribute levels that describe a single profile. We demonstrate this new preference elicitation technique using an empirical case study that explores preferences among the general public for ways to involve them in decisions concerning the health care system. Our findings show that the best-worst scaling and trio-wise preference elicitation techniques both retrieve similar preferences. However, the capability of our trio-wise method to provide additional information on the strength of rank preferences and its ability to accommodate indifferent preferences lead us to prefer it over the standard best-worst scaling technique.

Suggested Citation

  • Seda Erdem & Danny Campbell, 2017. "Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1107-1123, December.
  • Handle: RePEc:spr:eujhec:v:18:y:2017:i:9:d:10.1007_s10198-016-0856-4
    DOI: 10.1007/s10198-016-0856-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-016-0856-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10198-016-0856-4?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. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    2. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    3. Wiseman, V. & Mooney, G. & Berry, G. & Tang, K. C., 2003. "Involving the general public in priority setting: experiences from Australia," Social Science & Medicine, Elsevier, vol. 56(5), pages 1001-1012, March.
    4. Jordan Louviere & Terry Flynn, 2010. "Using Best-Worst Scaling Choice Experiments to Measure Public Perceptions and Preferences for Healthcare Reform in Australia," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 275-283, December.
    5. Potoglou, Dimitris & Burge, Peter & Flynn, Terry & Netten, Ann & Malley, Juliette & Forder, Julien & Brazier, John E., 2011. "Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data," Social Science & Medicine, Elsevier, vol. 72(10), pages 1717-1727, May.
    6. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    7. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    8. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    9. Riccardo Scarpa & Sandra Notaro & Jordan Louviere & Roberta Raffaelli, 2010. "Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 809-824.
    10. Campbell, Danny & Boeri, Marco & Doherty, Edel & George Hutchinson, W., 2015. "Learning, fatigue and preference formation in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 345-363.
    11. George W. Torrance & David Feeny & William Furlong, 2001. "Visual Analog Scales," Medical Decision Making, , vol. 21(4), pages 329-334, August.
    12. John Rose & Iain Black, 2006. "Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments," Marketing Letters, Springer, vol. 17(4), pages 295-310, December.
    13. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    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. Rebecca Kandiyali & Annie Hawton & Christie Cabral & Julie Mytton & Valerie Shilling & Christopher Morris & Jenny Ingram, 2019. "Working with Patients and Members of the Public: Informing Health Economics in Child Health Research," PharmacoEconomics - Open, Springer, vol. 3(2), pages 133-141, June.
    2. Ivan Sever & Miroslav Verbič & Eva Klaric Sever, 2020. "Estimating Attribute-Specific Willingness-to-Pay Values from a Health Care Contingent Valuation Study: A Best–Worst Choice Approach," Applied Health Economics and Health Policy, Springer, vol. 18(1), pages 97-107, February.

    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. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    2. Hajji, Assma & Trukeschitz, Birgit & Malley, Juliette & Batchelder, Laurie & Saloniki, Eirini & Linnosmaa, Ismo & Lu, Hui, 2020. "Population-based preference weights for the Adult Social Care Outcomes Toolkit (ASCOT) for service users for Austria: Findings from a best-worst experiment," Social Science & Medicine, Elsevier, vol. 250(C).
    3. Daniel R. Petrolia & Matthew G. Interis & Joonghyun Hwang, 2018. "Single-Choice, Repeated-Choice, and Best-Worst Scaling Elicitation Formats: Do Results Differ and by How Much?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(2), pages 365-393, February.
    4. Tatenda T Yemeke & Elizabeth E Kiracho & Aloysius Mutebi & Rebecca R Apolot & Anthony Ssebagereka & Daniel R Evans & Sachiko Ozawa, 2020. "Health versus other sectors: Multisectoral resource allocation preferences in Mukono district, Uganda," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    5. Lien Nguyen & Hanna Jokimäki & Ismo Linnosmaa & Eirini-Christina Saloniki & Laurie Batchelder & Juliette Malley & Hui Lu & Peter Burge & Birgit Trukeschitz & Julien Forder, 2022. "Valuing informal carers’ quality of life using best-worst scaling—Finnish preference weights for the Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(3), pages 357-374, April.
    6. Shittu, A. & Kehinde, M., 2018. "Willingness to Accept Incentives for a Shift to Climate – Smart Agriculture among Smallholder Farmers in Southwest and Northcentral Nigeria," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275983, International Association of Agricultural Economists.
    7. Hall, Natasha Yvonne & Le, Long & Abimanyi-Ochom, Julie & Mihalopoulos, Cathy, 2023. "Measuring the importance of different barriers to opioid agonist treatment using best-worst scaling in an Australian setting," Health Policy, Elsevier, vol. 138(C).
    8. Jennifer A Whitty & Ruth Walker & Xanthe Golenko & Julie Ratcliffe, 2014. "A Think Aloud Study Comparing the Validity and Acceptability of Discrete Choice and Best Worst Scaling Methods," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    9. Nicolas Krucien & Verity Watson & Mandy Ryan, 2017. "Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1-16, December.
    10. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    11. 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.
    12. Mesfin G. Genie & Nicolas Krucien & Mandy Ryan, 2021. "Weighting or aggregating? Investigating information processing in multi‐attribute choices," Health Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 1291-1305, June.
    13. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 46(1), pages 133-162.
    14. Yangui, Ahmed & Akaichi, Faical & Costa-Font, Montserrat & Gil, Jose Maria, 2019. "Comparing results of ranking conjoint analyses, best–worst scaling and discrete choice experiments in a nonhypothetical context," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.
    15. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    16. Katrina J Davis & Marit E Kragt & Stefan Gelcich & Michael Burton & Steven Schilizzi & David J Pannell, 2017. "Why are Fishers not Enforcing Their Marine User Rights?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(4), pages 661-681, August.
    17. Greiner, Romy & Bliemer, Michiel & Ballweg, Julie, 2014. "Design considerations of a choice experiment to estimate likely participation by north Australian pastoralists in contractual biodiversity conservation," Journal of choice modelling, Elsevier, vol. 10(C), pages 34-45.
    18. Campbell, Danny & Boeri, Marco & Doherty, Edel & George Hutchinson, W., 2015. "Learning, fatigue and preference formation in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 345-363.
    19. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
    20. Grilli, Gianluca & Notaro, Sandra & Campbell, Danny, 2018. "Including Value Orientations in Choice Models to Estimate Benefits of Wildlife Management Policies," Ecological Economics, Elsevier, vol. 151(C), pages 70-81.

    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:eujhec:v:18:y:2017:i:9:d:10.1007_s10198-016-0856-4. 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.