Quality of Life Research

, Volume 25, Issue 10, pp 2481–2496 | Cite as

Health state descriptions, valuations and individuals’ capacity to walk: a comparative evaluation of preference-based instruments in the context of spinal cord injury

  • David G. T. WhitehurstEmail author
  • Nicole Mittmann
  • Vanessa K. Noonan
  • Marcel F. Dvorak
  • Stirling Bryan



This study explores variation in health state descriptions and valuations derived from preference-based health-related quality of life instruments in the context of spinal cord injury (SCI).


Individuals living with SCI were invited to complete a web-based, cross-sectional survey. The survey comprised questions regarding demographics, SCI classifications and characteristics, secondary health complications and conditions, quality of life and SCI-specific functioning in activities of daily living. Four preference-based health status classification systems were included; Assessment of Quality of Life 8-dimension questionnaire (AQoL-8D), EQ-5D-5L, Health Utilities Index (HUI) and SF-6D (derived from the SF-36v2). In addition to descriptive comparisons of index scores and item/dimension responses, analyses explored dimension-level correlation and absolute agreement (intraclass correlation coefficient (ICC)). Subgroup analyses examined the influence of individuals’ self-reported ability to walk.


Of 609 invitations, 364 (60 %) individuals completed the survey. Across instruments, convergent validity was seen between pain and mental health dimensions, while sizeable variation pertaining to issues of mobility was observed. Mean index scores were 0.248 (HUI-3), 0.492 (EQ-5D-5L), 0.573 (AQoL-8D) and 0.605 (SF-6D). Agreement ranged from ‘slight’ (HUI-3 and SF-6D; ICC = 0.124) to ‘moderate’ (AQoL-8D and SF-6D; ICC = 0.634). Walking status had a markedly different impact on health state valuations across instruments.


Variation in the way that individuals are able to describe their health state across instruments is not unique to SCI. Further research is necessary to understand the significant differences in index scores and, in particular, the implications of framing mobility-related questions in the context of respondents’ ability to walk.


Health-related quality of life Quality-adjusted life years Spinal cord injury Disability Utility measurement Health state valuation 



Financial support for this study was provided entirely by a grant from the Rick Hansen Institute (Rick Hansen Institute Translational Research Program, Grant #2012-29: Spinal Cord Injury and Secondary Complications: A Mixed-Methods Evaluation of Preference-Based Instruments). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing and publishing the report. We would also like to thank Health Utilities Inc. for the New Investigator Grant awarded to Dr. David Whitehurst, Dr. Davene Wright for her discussion of an early draft of this paper at the 2015 Vancouver Health Economics Methodology (VanHEM) meeting, Lidia Engel for her assistance with generating Fig. 1, and the two anonymous reviewers for their constructive and comprehensive comments.

Compliance with ethical standards

The study was approved by the University of British Columbia Behavioural Research Ethics Board (H12-01138) and Vancouver Coastal Health Authority (Research Study #V12-01138).

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Neumann, P., Goldie, S. J., & Weinstein, M. C. (2000). Preference-based measures in economic evaluation in health care. Annual Review of Public Health, 21, 587–611.PubMedCrossRefGoogle Scholar
  2. 2.
    Canadian Agency for Drugs and Technologies in Health. (2006). Guidelines for the economic evaluation of health technologies: Canada (3rd ed.). Ottawa, Ontario: Canadian Agency for Drugs and Technologies in Health.Google Scholar
  3. 3.
    National Institute for Health and Care Excellence. (2013). Guide to the methods of technology appraisal 2013. London: National Institute for Health and Care Excellence.Google Scholar
  4. 4.
    Statistics Canada. (2011). Canadian Community Health Survey (CCHS), 2010 Annual Component surveys. Ottawa, Ontario: Statistics Canada.Google Scholar
  5. 5.
    Richardson, J., McKie, J., & Bariola, E. (2014). Multiattribute Utility instruments and their use. In A. J. Culyer (Ed.), Encyclopedia of health economics (pp. 41–57). San Diego, CA: Elsevier.Google Scholar
  6. 6.
    Brooks, R. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72.PubMedCrossRefGoogle Scholar
  7. 7.
    Torrance, G. W., Feeny, D. H., Furlong, W. J., Barr, R. D., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Medical Care, 34(7), 702–722.PubMedCrossRefGoogle Scholar
  8. 8.
    Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multi attribute and single attribute utility functions for the Health Utilities Index Mark 3 System. Medical Care, 40(2), 113–128.PubMedCrossRefGoogle Scholar
  9. 9.
    Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21(2), 271–292.PubMedCrossRefGoogle Scholar
  10. 10.
    Brazier, J. E., & Roberts, J. (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care, 42(9), 851–859.PubMedCrossRefGoogle Scholar
  11. 11.
    Sintonen, H. (2001). The 15D instrument of health-related quality of life: Properties and applications. Annals of Medicine, 33(5), 328–336.PubMedCrossRefGoogle Scholar
  12. 12.
    Hawthorne, G., Richardson, J., & Osborne, R. (1999). The Assessment of Quality of Life (AQoL) instrument: A psychometric measure of health-related quality of life. Quality of Life Research, 8(3), 209–224.PubMedCrossRefGoogle Scholar
  13. 13.
    The Assessment of Quality of Life (AQoL) instruments. Melbourne (Australia): Centre for Health Economics. Accessed August 31, 2015.
  14. 14.
    Kaplan, R. M., Anderson, J. P., & Ganiats, T. G. (1993). The Quality of Well-being Scale: Rationale for a single quality of life index. In S. R. Walker & R. M. Rosser (Eds.), Quality of life assessment: Key issues in the 1990s (pp. 65–94). London: Kluwer Academic Publishers.CrossRefGoogle Scholar
  15. 15.
    Fryback, D. G., Palta, M., Cherepanov, D., Bolt, D., & Kim, J. (2010). Comparison of 5 health related quality of life indexes using item response theory analysis. Medical Decision Making, 30(1), 5–15.PubMedCrossRefGoogle Scholar
  16. 16.
    Whitehurst, D. G. T., Bryan, S., & Lewis, M. (2011). Systematic review and empirical comparison of contemporaneous EQ-5D and SF-6D group mean scores. Medical Decision Making, 31(6), E34–E44.PubMedCrossRefGoogle Scholar
  17. 17.
    Moock, J., & Kohlmann, T. (2008). Comparing preference-based quality-of-life measures: Results from rehabilitation patients with musculoskeletal, cardiovascular, or psychosomatic disorders. Quality of Life Research, 17(3), 485–495.PubMedCrossRefGoogle Scholar
  18. 18.
    Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2015). Comparing and explaining differences in the magnitude, content, and sensitivity of utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D multiattribute utility instruments. Medical Decision Making, 35(3), 276–291.PubMedCrossRefGoogle Scholar
  19. 19.
    Grieve, R., Grishchenko, M., & Cairns, J. (2009). SF-6D versus EQ-5D: Reasons for differences in utility scores and impact on reported cost-utility. The European Journal of Health Economics, 10, 15–23.PubMedCrossRefGoogle Scholar
  20. 20.
    Whitehurst, D. G., & Bryan, S. (2011). Another study showing that two preference-based measures of health-related quality of life (EQ-5D and SF-6D) are not interchangeable. But why should we expect them to be? Value Health, 14(4), 531–538.PubMedCrossRefGoogle Scholar
  21. 21.
    Konerding, U., Moock, J., & Kohlmann, T. (2009). The classification systems of the EQ-5D, the HUI II and the SF-6D: What do they have in common? Quality of Life Research, 18, 1249–1261.PubMedCrossRefGoogle Scholar
  22. 22.
    Espallargues, M., Czoski-Murray, C. J., Bansback, N. J., Carlton, J., Lewis, G. M., Hughes, L. A., et al. (2005). The impact of age-related macular degeneration on health status utility values. Investigative Ophthalmology and Visual Science, 46(11), 4016–4023.PubMedCrossRefGoogle Scholar
  23. 23.
    Whitehurst, D. G. T., Noonan, V. K., Dvorak, M. F. S., & Bryan, S. (2012). A review of preference-based health-related quality of life questionnaires in spinal cord injury research. Spinal Cord, 50(9), 646–654.PubMedCrossRefGoogle Scholar
  24. 24.
    Andresen, E. M., Fouts, B. S., Romeis, J. C., & Brownson, C. A. (1999). Performance of health-related quality-of-life instruments in a spinal cord injured population. Archives of Physical Medicine and Rehabilitation, 80(8), 877–884.PubMedCrossRefGoogle Scholar
  25. 25.
    Lee, B. B., Simpson, J. M., King, M. T., Haran, M. J., & Marial, O. (2009). The SF-36 walk-wheel: A simple modification of the SF-36 physical domain improves its responsiveness for measuring health status change in spinal cord injury. Spinal Cord, 47(1), 50–55.PubMedCrossRefGoogle Scholar
  26. 26.
    Engel, L., Bryan, S., Evers, S. M., Dirksen, C. D., Noonan, V. K., & Whitehurst, D. G. (2014). Exploring psychometric properties of the SF-6D, a preference-based health-related quality of life measure, in the context of spinal cord injury. Quality of Life Research, 23(8), 2383–2393.PubMedCrossRefGoogle Scholar
  27. 27.
    Craven, C., Hitzig, S. L., & Mittmann, N. (2012). Impact of impairment and secondary health conditions on health preference among Canadians with chronic spinal cord injury. Journal of Spinal Cord Medicine, 35(5), 361–370.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Richardson, J., Iezzi, A., Khan, M. A., & Maxwell, A. (2014). Validity and reliability of the Assessment of Quality of Life (AQoL)-8D multi-attribute utility instrument. Patient, 7(1), 85–96.PubMedCrossRefGoogle Scholar
  29. 29.
    Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., et al. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Seiber WJ, Groessl EJ, David KM, Ganiats TG, Kaplan RM (2008) Quality of well being self-administered (QWB-SA) scale user’s manual. San Diego, CA: Health Services Research Center. Accessed August 31, 2015.
  31. 31.
    Ware, J. E., Kosinski, M., Bjorner, J. B., Turner-Bowker, D. M., Gandek, B., & Maruish, M. E. (2007). User’s manual for the SF-36v2TM health survey (2nd ed.). Lincoln, RI: QualityMetric.Google Scholar
  32. 32.
    Whitehurst, D. G., Suryaprakash, N., Engel, L., Mittmann, N., Noonan, V. K., Dvorak, M. F., et al. (2014). Perceptions of individuals living with spinal cord injury toward preference-based quality of life instruments: A qualitative exploration. Health Qual Life Outcomes, 12, 50.PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Noreau, L., Noonan, V. K., Cobb, J., Leblond, J., & Dumont, F. S. (2014). Spinal cord injury community survey: A national, comprehensive study to portray the lives of Canadians with spinal cord injury. Topics in Spinal Cord Injury Rehabilitation, 20(4), 249–264.PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Brazier, J. E., Rowen, D., & Hanmer, J. (2008). Revised SF-6D scoring programmes: A summary of improvements. PRO Newsletter, 40, 14–15.Google Scholar
  35. 35.
    Perreault, W. D. (1975). Controlling order-effect bias. Public Opinion Quarterly, 39(4), 544–551.CrossRefGoogle Scholar
  36. 36.
    Xie, F., Pullenayegum, E., Gaebel, K., Bansback, N., Bryan, S., Ohinmaa, A., et al. (2016). Canadian EQ-5D-5L Valuation Study Group. A time trade-off-derived value set of the EQ-5D-5L for Canada. Medical Care, 54(1), 98–105.PubMedCrossRefGoogle Scholar
  37. 37.
    Brazier, J., Roberts, J., Tsuchiya, A., & Busschbach, J. (2004). A comparison of the EQ-5D and SF-6D across seven patient groups. Health Economics, 13(9), 873–884.PubMedCrossRefGoogle Scholar
  38. 38.
    Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–427.PubMedCrossRefGoogle Scholar
  39. 39.
    Shrout, P. E. (1998). Measurement reliability and agreement in psychiatry. Statistical Methods in Medical Research, 7(3), 301–317.PubMedCrossRefGoogle Scholar
  40. 40.
    Hanmer, J., Cherepanov, D., Palta, M., Kaplan, R. M., Feeny, D., & Fryback, D. G. (2016). Health condition impacts in a nationally representative cross-sectional survey vary substantially by preference-based health index. Medical Decision Making, 36(2), 264–274.PubMedCrossRefGoogle Scholar
  41. 41.
    Heintz, E., Wiréhn, A. B., Peebo, B. B., Rosenqvist, U., & Levin, L. Å. (2012). QALY weights for diabetic retinopathy: A comparison of health state valuations with HUI-3, EQ-5D, EQ-VAS, and TTO. Value Health, 15(3), 475–484.PubMedCrossRefGoogle Scholar
  42. 42.
    Joore, M., Brunenberg, D., Nelemans, P., Wouters, E., Kuijpers, P., Honig, A., et al. (2010). The impact of differences in EQ-5D and SF-6D utility scores on the acceptability of cost-utility ratios: Results across five trial-based cost-utility studies. Value Health, 13(2), 222–229.PubMedCrossRefGoogle Scholar
  43. 43.
    Mihalopoulos, C., Chen, G., Iezzi, A., Khan, M. A., & Richardson, J. (2014). Assessing outcomes for cost-utility analysis in depression: comparison of five multi-attribute utility instruments with two depression-specific outcome measures. British Journal of Psychiatry, 205(5), 390–397.PubMedCrossRefGoogle Scholar
  44. 44.
    Richardson, J., Chen, G., Khan, M. A., & Iezzi, A. (2015). Can multi-attribute utility instruments adequately account for subjective well-being? Medical Decision Making, 35(3), 292–304.PubMedCrossRefGoogle Scholar
  45. 45.
    Richardson, J., Iezzi, A., & Khan, M. A. (2015). Why do multi-attribute utility instruments produce different utilities: The relative importance of the descriptive systems, scale and ‘micro-utility’ effects. Quality of Life Research, 24(8), 2045–2053.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Whitehurst, D. G., Norman, R., Brazier, J. E., & Viney, R. (2014). Comparison of contemporaneous EQ-5D and SF-6D responses using scoring algorithms derived from similar valuation exercises. Value Health, 17(5), 570–577.PubMedCrossRefGoogle Scholar
  47. 47.
    Hays, R. D., Siu, A. L., Keeler, E., Marshall, G. N., Kaplan, R. M., Simmons, S., et al. (1996). Long-term care residents’ preferences for health states on the quality of well-being scale. Medical Decision Making, 16(3), 254–261.PubMedCrossRefGoogle Scholar
  48. 48.
    Yang, Y., Rowen, D., Brazier, J., Tsuchiya, A., Young, T., & Longworth, L. (2015). An exploratory study to test the impact on three “bolt-on” items to the EQ-5D. Value Health, 18(1), 52–60.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Tosh, J., Brazier, J., Evans, P., & Longworth, L. (2012). A review of generic preference-based measures of health-related quality of life in visual disorders. Value Health, 15(1), 118–127.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Kaplan, R. M., Tally, S., Hays, R. D., Feeny, D., Ganiats, T. G., Palta, M., et al. (2011). Five preference-based indexes in cataract and heart failure patients were not equally responsive to change. Journal of Clinical Epidemiology, 64(5), 497–506.PubMedCrossRefGoogle Scholar
  51. 51.
    Feeny, D., Spritzer, K., Hays, R. D., Liu, H., Ganiats, T. G., Kaplan, R. M., et al. (2012). Agreement about identifying patients who change over time: Cautionary results in cataract and heart failure patients. Medical Decision Making, 32(2), 273–286.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • David G. T. Whitehurst
    • 1
    • 2
    • 3
    Email author
  • Nicole Mittmann
    • 4
    • 5
  • Vanessa K. Noonan
    • 6
  • Marcel F. Dvorak
    • 2
    • 6
  • Stirling Bryan
    • 3
    • 7
    • 8
  1. 1.Faculty of Health SciencesSimon Fraser UniversityBurnabyCanada
  2. 2.International Collaboration on Repair Discoveries (ICORD), Faculty of MedicineUniversity of British ColumbiaVancouverCanada
  3. 3.Centre for Clinical Epidemiology and EvaluationVancouver Coastal Health Research InstituteVancouverCanada
  4. 4.Health Outcomes and PharmacoEconomics (HOPE) Research Centre, Sunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoCanada
  5. 5.Department of PharmacologyUniversity of TorontoTorontoCanada
  6. 6.Rick Hansen InstituteVancouverCanada
  7. 7.School of Population and Public HealthUniversity of British ColumbiaVancouverCanada
  8. 8.Health Economics Research UnitUniversity of AberdeenAberdeenUK

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