Quality of Life Research

, Volume 25, Issue 3, pp 637–649 | Cite as

Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format

  • R. Norman
  • R. Viney
  • N. K. Aaronson
  • J. E. Brazier
  • D. Cella
  • D. S. J. Costa
  • P. M. Fayers
  • G. Kemmler
  • S. Peacock
  • A. S. Pickard
  • D. Rowen
  • D. J. Street
  • G. Velikova
  • T. A. Young
  • M. T. King



To assess the feasibility of using a discrete choice experiment (DCE) to value health states within the QLU-C10D, a utility instrument derived from the QLQ-C30, and to assess clarity, difficulty, and respondent preference between two presentation formats.


We ran a DCE valuation task in an online panel (N = 430). Respondents answered 16 choice pairs; in half of these, differences between dimensions were highlighted, and in the remainder, common dimensions were described in text and differing attributes were tabulated. To simplify the cognitive task, only four of the QLU-C10D’s ten dimensions differed per choice set. We assessed difficulty and clarity of the valuation task with Likert-type scales, and respondents were asked which format they preferred. We analysed the DCE data by format with a conditional logit model and used Chi-squared tests to compare other responses by format. Semi-structured telephone interviews (N = 8) explored respondents’ cognitive approaches to the valuation task.


Four hundred and forty-nine individuals were recruited, 430 completed at least one choice set, and 422/449 (94 %) completed all 16 choice sets. Interviews revealed that respondents found ten domains difficult but manageable, many adopting simplifying heuristics. Results for clarity and difficulty were identical between formats, but the “highlight” format was preferred by 68 % of respondents. Conditional logit parameter estimates were monotonic within domains, suggesting respondents were able to complete the DCE sensibly, yielding valid results.


A DCE valuation task in which only four of the QLU-C10D’s ten dimensions differed in any choice set is feasible for deriving utility weights for the QLU-C10D.


Quality of life Utility QLQ-C30 Discrete choice experiment Cancer 



The MAUCa Consortium, in addition to those named as authors, consists of the following members, all of whom made some contribution to the research reported in this paper: Helen McTaggart-Cowan, Peter Grimison, Monika Janda, and Julie Pallant. This research was supported by a National Health and Medical Research Council (Australia) Project Grant (632662). Associate Professor Janda was supported by a NHMRC Career Development Award 1045247. Dr. Norman was supported by a NHMRC early career research fellowship (1069732). Professor King was supported by the Australian Government through Cancer Australia.


This research was supported by a National Health and Medical Research Council (Australia) Project Grant (632662). Dr. Norman was supported by a NHMRC early career research fellowship (1069732). Professor King was supported by the Australian Government through Cancer Australia.

Compliance with ethical standards

Conflict of interest

The authors declare they do not have conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the University of Sydney Human Research Ethics Committee, Approval Number 2012/2444.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11136_2015_1115_MOESM1_ESM.docx (180 kb)
Supplementary material 1 (DOCX 179 kb)
11136_2015_1115_MOESM2_ESM.docx (14 kb)
Supplementary material 2 (DOCX 13 kb)


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • R. Norman
    • 1
    • 2
  • R. Viney
    • 2
  • N. K. Aaronson
    • 3
  • J. E. Brazier
    • 4
  • D. Cella
    • 5
  • D. S. J. Costa
    • 6
  • P. M. Fayers
    • 7
    • 8
  • G. Kemmler
    • 9
  • S. Peacock
    • 10
    • 11
    • 12
  • A. S. Pickard
    • 13
  • D. Rowen
    • 4
  • D. J. Street
    • 14
  • G. Velikova
    • 15
    • 16
  • T. A. Young
    • 4
  • M. T. King
    • 6
    • 17
  1. 1.School of Public HealthCurtin UniversityPerthAustralia
  2. 2.Centre for Health Economics Research and Evaluation (CHERE)University of Technology Sydney (UTS)SydneyAustralia
  3. 3.The Netherlands Cancer InstituteAmsterdamThe Netherlands
  4. 4.School of Health and Related ResearchUniversity of SheffieldSheffieldUK
  5. 5.Department of Medical Social Sciences, Feinberg School of MedicineNorthwestern UniversityChicagoUSA
  6. 6.Psycho-Oncology Cooperative Research Group (PoCoG)University of SydneySydneyAustralia
  7. 7.Institute of Applied Health SciencesUniversity of AberdeenAberdeenUK
  8. 8.Department of Cancer Research and Molecular MedicineNorwegian University of Science and Technology (NTNU)TrondheimNorway
  9. 9.Innsbruck Medical UniversityInnsbruckAustria
  10. 10.Faculty of Health SciencesSimon Fraser UniversityVancouverCanada
  11. 11.Canadian Centre for Applied Research in Cancer Control (ARCC)VancouverCanada
  12. 12.British Columbia Cancer AgencyVancouverCanada
  13. 13.Department of Pharmacy Systems, Outcomes and Policy, College of PharmacyUniversity of Illinois at ChicagoChicagoUSA
  14. 14.School of Mathematical and Physical SciencesUniversity of Technology SydneySydneyAustralia
  15. 15.Leeds Institute of Cancer and PathologyUniversity of LeedsLeedsUK
  16. 16.St James’s HospitalLeedsUK
  17. 17.Central Clinical School, Sydney Medical SchoolUniversity of SydneySydneyAustralia

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