PharmacoEconomics

, Volume 17, Issue 1, pp 13–35

A Comparative Review of Generic Quality-of-Life Instruments

  • Stephen Joel Coons
  • Sumati Rao
  • Dorothy L. Keininger
  • Ron D. Hays
Review Article

Abstract

The assessment of health-related quality of life (HR-QOL) is an essential element of healthcare evaluation. Hundreds of generic and specific HR-QOL instruments have been developed. Generic HR-QOL instruments are designed to be applicable across a wide range of populations and interventions. Specific HR-QOL measures are designed to be relevant to particular interventions or in certain subpopulations (e.g. individuals with rheumatoid arthritis).

This review examines 7 generic HR-QOL instruments: (i) the Medical Outcomes Study 36-Item Short Form (SF-36) health survey; (ii) the Nottingham Health Profile (NHP); (iii) the Sickness Impact Profile (SIP); (iv) the Dartmouth Primary care Cooperative Information Project (COOP) Charts; (v) the Quality of Well-Being (QWB) Scale; (vi) the Health Utilities Index (HUI); and (vii) the EuroQol Instrument (EQ-5D). These instruments were selected because they are commonly used and/or cited in the English language literature. The 6 characteristics of an instrument addressed by this review are: (i) conceptual and measurement model; (ii) reliability; (iii) validity; (iv) respondent and administrative burden; (v) alternative forms; and (vi) cultural and language adaptations.

Of the instruments reviewed, the SF-36 health survey is the most commonly used HR-QOL measure. It was developed as a short-form measure of functioning and well-being in the Medical Outcomes Study. The Dartmouth COOP Charts were designed to be used in everyday clinical practice to provide immediate feedback to clinicians about the health status of their patients. The NHP was developed to reflect lay rather than professional perceptions of health. The SIP was constructed as a measure of sickness in relation to impact on behaviour. The QWB, HUI and EQ-5D are preference-based measures designed to summarise HR-QOL in a single number ranging from 0 to 1.

We found that there are no uniformly ‘worst’or ‘best’ performing instruments. The decision to use one over another, to use a combination of 2 or more, to use a profile and/or a preference-based measure or to use a generic measure along with a targeted measure will be driven by the purpose of the measurment. In addition, the choice will depend on a variety of factors including the characteristics of the population (e.g. age, health status, language/culture) and the environment in which the measurement is undertaken (e.g. clinical trial, routine physician visit). We provide our summary of the level of evidence in the literature regarding each instrument’s characteristics based on the review criteria. The potential user of these instruments should base their instrument selection decision on the characteristics that are most relevant to their particular HR-QOL measurment needs.

References

  1. 1.
    Guyatt GH, Feeny DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med 1993; 118: 622–9PubMedGoogle Scholar
  2. 2.
    Patrick DL, Deyo RA. Generic and disease-specific measures in assessing health status and quality of life. Med Care 1989; 27: S217–32CrossRefGoogle Scholar
  3. 3.
    Bowling A. Measuring health: a review of quality of life measurement scales. 2nd ed. Buckingham: Open University Press, 1997Google Scholar
  4. 4.
    McDowell I, Newell C. Measuring health: a guide to rating scales and questionnaires. 2nd ed. New York: Oxford University Press, 1996Google Scholar
  5. 5.
    Lohr KN, Aaronson NK, Alonso J, et al. Evaluating quality of life and health status instruments: development of scientific review criteria. Clin Ther 1996; 18: 979–92PubMedCrossRefGoogle Scholar
  6. 6.
    Hays RD, Hadorn D. Responsiveness to change: an aspect of validity, not a separate dimension. Qual Life Res 1992; 1: 73–5PubMedCrossRefGoogle Scholar
  7. 7.
    Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York (NY): McGraw-Hill, 1994Google Scholar
  8. 8.
    Helmstadter GC. Principles of psychological measurement. New York (NY): Appleton Century Crofts, 1964Google Scholar
  9. 9.
    Weiner EA, Stewart BJ. Assessing individuals. Boston (MA): Little Brown, 1984Google Scholar
  10. 10.
    Fleiss JL. Statistical methods for rates and proportions. 2nd ed. New York (NY): Wiley, 1981Google Scholar
  11. 11.
    Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159–74PubMedCrossRefGoogle Scholar
  12. 12.
    Stewart AL, Sherbourne CD, Hays RD, et al. Summary and discussion of MOS measures. In: Stewart AL, Ware JE, editors. Measuring functioning and well-being: the Medical Outcomes Study approach. Durham (NC): Duke University Press, 1992: 345–71Google Scholar
  13. 13.
    Hays RD, Prince-Embury S, Chen H. RAND-36 Health Status Inventory: manual. San Antonio (TX): The Psychological Corporation, 1998Google Scholar
  14. 14.
    Ware JE, Sherbourne CD, Davies AR. Developing and testing the MOS 20-Item Short-Form Health Survey: a general population application. In: Stewart AL, Ware JE, editors. Measuring functioning and well-being: the Medical Outcomes Study approach. Durham (NC): Duke University Press, 1992: 277–90Google Scholar
  15. 15.
    Stewart AL, Hays RD, Ware JE. The MOS Short-Form General Health Survey: reliability and validity in a patient population. Med Care 1998; 26: 724–35CrossRefGoogle Scholar
  16. 16.
    Hays RD, Sherbourne CD, Mazel RM. User’s manual for the Medical Outcomes Study (MOS) core measures of health related quality of life. Santa Monica (CA): RAND, 1995: MR-162-RCGoogle Scholar
  17. 17.
    Stewart AL, Ware JE, editors. Measuring functioning and wellbeing: The Medical Outcomes Study approach. Durham (NC): Duke University Press, 1992Google Scholar
  18. 18.
    Ware JE, Sherbourne CD. The MOS 36-Item Short-Form Health Survey (SF-36): I. Conceptual framework and item selection. Med Care 1992; 30: 473–81PubMedCrossRefGoogle Scholar
  19. 19.
    Hays RD, Sherbourne CD, Mazel RM. The RAND 36-Item Health Survey 1.0. Health Econ 1993; 2: 217–27PubMedCrossRefGoogle Scholar
  20. 20.
    Essink-Bot ML, Krabbe PFM, Bonsel GJ, et al. An empirical comparison of four generic health status measures. Med Care 1997; 35: 522–37PubMedCrossRefGoogle Scholar
  21. 21.
    Hays RD, Marshall GN, Wang EYI, et al. Four-year crosslagged associations between physical and mental health in the Medical Outcomes Study. J Consult Clin Psychol 1994; 62: 441–9PubMedCrossRefGoogle Scholar
  22. 22.
    Ware JE, Kosinski M, Bayliss MS, et al. Comparisons of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: summary of results from the Medical Outcomes Study. Med Care 1995; 33: AS264–79CrossRefGoogle Scholar
  23. 23.
    Dexter PR, Stump TE, Tierney WM, et al. The psychometric properties of the SF-36 health survey among older adults in a clinical setting. J Clin Geropsychology 1996; 2: 225–37Google Scholar
  24. 24.
    Shadbolt B, McCallum J, Singh M. Health outcomes by self-report: validity of the SF-36 among Australian hospital patients. Qual Life Res 1997; 6: 343–52PubMedCrossRefGoogle Scholar
  25. 25.
    Rummel RJ. Applied factor analysis. Evanston (IL): Northwestern University Press, 1970Google Scholar
  26. 26.
    Ware JE, Kosinski M. SF-36 Health Survey (version 2.0) [technical note]. Boston (MA): The Health Institute, 1996Google Scholar
  27. 27.
    McHorney CA, Ware JE, Lu RJF, et al. The MOS 36-Item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care 1994; 32: 40–66PubMedCrossRefGoogle Scholar
  28. 28.
    Andresen EM, Bowley N, Rothenberg BM, et al. Test-retest performance of a mailed version of the Medical Outcomes Study 36-Item Short-Form Health Survey among older adults. Med Care 1996; 34: 1165–70PubMedCrossRefGoogle Scholar
  29. 29.
    Hays RD, Kallich JD, Mapes DL, et al. Development of the Kidney Disease Quality of Life (KDQOL) instrument. Qual Life Res 1994; 3: 329–38PubMedCrossRefGoogle Scholar
  30. 30.
    Kurtin PS, Davies AR, Meyer KB, et al. Patient-based health status measures in outpatient dialysis: early experience in developing an outcomes assessment program. Med Care 1992; 30: MS136–49CrossRefGoogle Scholar
  31. 31.
    Kantz ME, Harris WJ, Levitsky K, et al. Methods for assessing condition-specific and generic functional status outcomes after total knee replacement. Med Care 1992; 30: MS240–52CrossRefGoogle Scholar
  32. 32.
    Wagner AK, Keller SD, Kosinski M, et al. Advances in methods for assessing the impact of epilepsy and antiepilepsy drug therapy on patients’ health-related quality of life. Qual Life Res 1995; 4: 115–34PubMedCrossRefGoogle Scholar
  33. 33.
    Brazier JE, Harper R, Jones NMB, et al. Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ 1992; 305: 160–4PubMedCrossRefGoogle Scholar
  34. 34.
    Hays RD, Hayashi T. Beyond internal consistency: rationale and user’s guide for Multitrait Analysis Program on the microcomputer. Behav Res Methods, Instruments, and Computers 1990; 22: 167–75CrossRefGoogle Scholar
  35. 35.
    McHorney CA, Jr Ware JE, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 1993; 31: 247–63PubMedCrossRefGoogle Scholar
  36. 36.
    McHorney CA, Jr Ware JE, Rogers W, et al. The validity and relative precision of MOS short-and long-form health status scale and Dartmouth COOP charts. Med Care 1992; 30 (5 Suppl.): MS253–65Google Scholar
  37. 37.
    Vickrey BG, Hays RD, Rausch R, et al. Quality of life of epilepsy surgery patients as compared with outpatients with hypertension, diabetes, heart disease, and/or depressive symptoms. Epilepsia 1994; 35: 597–607PubMedCrossRefGoogle Scholar
  38. 38.
    Ganz PA, Day R, Ware JE, et al. Base-line quality of life assessment in the national surgical adjuvant breast and bowel project breast cancer prevention trial. J Natl Cancer Inst 1995; 87: 1372–82PubMedCrossRefGoogle Scholar
  39. 39.
    Sherbourne CD, Wells KB, Judd LL. Functioning and well-being of patients with panic disorder. Am J Psychiatry 1996; 153: 213–8PubMedGoogle Scholar
  40. 40.
    Lansky D, Butler JBV, Waller FT. Using health status measures in the hospital setting: from acute care to ’outcome management’. Med Care 1992; 30: MS57–73CrossRefGoogle Scholar
  41. 41.
    Solomon GD. Evolution of the measurement of quality of life in migraine. Neurol 1997; 48: S10–5Google Scholar
  42. 42.
    Garratt AM, Ruta DA, Abdalla MI, et al. Responsiveness of the SF-36 and a condition-specific measure of health for patients with varicose veins. Qual Life Res 1996; 5: 223–34PubMedCrossRefGoogle Scholar
  43. 43.
    Ware JE. The SF-36 health survey. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven, 1996: 337–45Google Scholar
  44. 44.
    McHorney CA, Kosinski M, Ware JE. Comparisons of the costs and quality of norms for the SF-36 health survey collected by mail versus telephone interview: results from a national survey. Med Care 1994; 32: 551–67PubMedCrossRefGoogle Scholar
  45. 45.
    Keller SD, Bayliss MS, Ware JE, et al. Comparison of responses to SF-36 health survey questions with one-week and four week recall periods. Health Serv Res 1997; 32: 3 7–84Google Scholar
  46. 46.
    Medical Outcomes Trust. Medical Outcomes Trust: approved instruments. Med Outcomes Trust Bull 1998; 6 (3): 15Google Scholar
  47. 47.
    Aaronson NK, Acquadro C, Alonso J, et al. International quality of life assessment (IQOLA) project. Qual Life Res 1992; 1: 349–51PubMedCrossRefGoogle Scholar
  48. 48.
    Anderson RT, Aaronson NK, Bullinger M, et al. A review of the progress towards developing health-related quality of life instruments for international clinical studies and outcomes research. Pharmacoeconomics 1996; 10: 336–55PubMedCrossRefGoogle Scholar
  49. 49.
    Ware JE, Gandek B. Overview of the SF-36 health survey and the international quality of life assessment (IQOLA) project. J Clin Epidemiol 1998; 51: 903–12PubMedCrossRefGoogle Scholar
  50. 50.
    McEwen J, McKenna SP. Nottingham Health Profile. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven, 1996: 281–6Google Scholar
  51. 51.
    Hunt SM, McEwen J, McKenna SP. Measuring health status. London: Croom Helm, 1986Google Scholar
  52. 52.
    McKenna SP, Hunt SM, McEwen J. Weighting the seriousness of perceived health problems using Thurstone’s method of paired comparisons. Int J Epidemiol 1981; 10: 93–7PubMedCrossRefGoogle Scholar
  53. 53.
    Hunt SM, McKenna SP, McEwen J, et al. The Nottingham Health Profile: subjective health status and medical consultations. Soc Sci Med 1981; 15: 221–9Google Scholar
  54. 54.
    Jenkinson C, Fitzpatrick R, Argyle M. The Nottingham Health Profile: an analysis of its sensitivity in differentiating illness groups. Soc Sci Med 1988; 27: 1411–14PubMedCrossRefGoogle Scholar
  55. 55.
    O’Brien B. Assessment of treatment in heart disease. In: Teeling Smith G, editor. Measuring health: a practical approach. Chichester: John Wiley and Sons, 1988: 191–210Google Scholar
  56. 56.
    Hunt SM, McEwen H, McKenna SP. Measuring health status: a new tool for clinicians and epidemiologists. JRColl General Pract 1985; 35: 185–8Google Scholar
  57. 57.
    Hunt SM, McEwen J, McKenna SP, et al. Subjective health assessments and the perceived outcome of minor surgery. J Psychosom Res 1984; 28: 105–14PubMedCrossRefGoogle Scholar
  58. 58.
    Hunt SM, Alonso J, Bucquet D, et al. Cross-cultural adaptation of health measures. Health Policy 1991; 19: 33–44PubMedCrossRefGoogle Scholar
  59. 59.
    Bergner M, Bobbitt RA, Carter WB, et al. The Sickness Impact Profile: development and final revision of a health status measure. Med Care 1981; 19: 787–805PubMedCrossRefGoogle Scholar
  60. 60.
    Bergner M. Development, testing and use of the Sickness Impact Profile. In: Walker SR, Rosser RM, editors. Quality of life assessment: key issues in the 1990s. Boston (MA): Kluwer Academic Publishers, 1993: 95–109CrossRefGoogle Scholar
  61. 61.
    Bergner M, Bobbitt RA, Kressel S, et al. The Sickness Impact Profile: conceptual formulation and methodology for the development of a health status measure. Int J Health Services 1976; 6: 393–415CrossRefGoogle Scholar
  62. 62.
    Damiano AM. The Sickness Impact Profile. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven, 1996: 347–54Google Scholar
  63. 63.
    Carter WB, Bobbitt RA, Bergner M, et al. Validation of an interval scaling: the Sickness Impact Profile. Health Serv Res 1976; 11: 516–28PubMedGoogle Scholar
  64. 64.
    Pollard WB, Bobbitt RA, Bergner M, et al. The Sickness Impact Profile: reliability of a health status measure. Med Care 1976; 14: 146–55PubMedCrossRefGoogle Scholar
  65. 65.
    Bergner M, Bobbitt RA, Pollard WE, et al. The Sickness Impact Profile: validation of a health status measure. Med Care 1976; 14: 57–67PubMedCrossRefGoogle Scholar
  66. 66.
    Deyo RA, Inui TS, Leininger JD, et al. Measuring functional outcomes in chronic disease: a comparison of traditional scales and a self-administered health status questionnaire in patientswith rheumatoid arthritis. Med Care 1983; 21: 180–92PubMedCrossRefGoogle Scholar
  67. 67.
    DeBruin AF, De Witte LP, Stevens F, et al. Sickness Impact Profile: the state of the art of a generic functional status measure. Soc Sci Med 1992; 35: 1003–14CrossRefGoogle Scholar
  68. 68.
    Read LJ, Quinn RJ, Hoefer MA. Measuring overall health: an evaluation of three important approaches. J Chron Dis 1987 40: 7S-21SCrossRefGoogle Scholar
  69. 69.
    Hall J, Hall N, Fisher E, et al. Measurement of outcomes of general practice: comparison of three health status measures. Fam Pract 1987; 4: 117–22PubMedCrossRefGoogle Scholar
  70. 70.
    Vetter N, Smith A, Sastry D, et al. Day Hospital: pilot study report. Research team for the care of elderly people. Cardiff: Department of Geriatrics, St David’s Hospital, 1989Google Scholar
  71. 71.
    Sullivan M, Ahlmen M, Bjella A, et al. Health status assessment in rheumatoid arthritis: II. Evaluation of a modified Shorter Sickness Impact Profile. J Rheumatol 1993; 20: 1500–7PubMedGoogle Scholar
  72. 72.
    Gerety MB, Cornell JE, Mulrow CD, et al. The Sickness Impact Profile for nursing homes (SIP-NH). J Gerontol 1994; 49: M2–8CrossRefGoogle Scholar
  73. 73.
    Roland M, Morris R. A study of the natural history of back pain. Part I: development of a reliable and sensitive measure of disability in low-back pain. Spine 1983; 8: 141–4PubMedCrossRefGoogle Scholar
  74. 74.
    Patrick DL, Sittampalam Y, Somerville SM, et al. A cross cultural comparison of health status values. Am J Public Health 1985; 75: 1402–7PubMedCrossRefGoogle Scholar
  75. 75.
    Chwalow AJ, Lurie A, Bean K, et al. A French version of the Sickness Impact Profile (SIP): stages in the cross cultural validation of a generic quality of life scale. Fundam Clin Pharmacol 1992; 6: 319–26PubMedCrossRefGoogle Scholar
  76. 76.
    Esteva M, Gonzalez N, Ruiz M. Reliability and validity of a Spanish version of the Sickness Impact Profile [abstract]. Arthritis Rheum 1992; 35 Suppl. 9: S219Google Scholar
  77. 77.
    Sullivan M, Ahlmen M, Archenholtz B, et al. Measuring health in rheumatic disorders by means of a Swedish version of the Sickness Impact Profile: results from a population study. Scand J Rheumatol 1986; 15: 193–200PubMedCrossRefGoogle Scholar
  78. 78.
    Jacobs HM, Luttik A, Touw-Otten FWMM, et al. Measuring impact of sickness in patients with nonspecific abdominal complaints in a Dutch family practice setting. Med Care 1992; 30: 244–51PubMedCrossRefGoogle Scholar
  79. 79.
    Nelson EC, Wasson JH, Johnson DJ, et al. Dartmouth COOP functional health assessment charts: brief measures for clinical practice. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven, 1996: 161–8Google Scholar
  80. 80.
    Nelson E, Wasson J, Kirk J, et al. Assessment of function in routine clinical practice: description of the COOP chart method and preliminary findings. J Chron Dis 1987; 40 Suppl. 1: 55S-63SCrossRefGoogle Scholar
  81. 81.
    Landgraf JM, Nelson EC, Hays RD, et al. Assessing function: does it really make a difference? A preliminary evaluation of acceptability and utility of the COOP function charts. In: Lipkin M, editor. Functional status measurement in primary care: frontiers of primary care. New York (NY): Springer-Verlag, 1990: 150–65CrossRefGoogle Scholar
  82. 82.
    Froom J. Functional status measurement in primary care. World Organization of National Colleges, Academics, and Academic Association of General Practitioners/Family Physicians (WONCA) Committee on International Classification Statement on Functional Status Assessment; 1988 Oct 24–28: Calgary. New York (NY): Springer-Verlag, 1990: xiii-xviiGoogle Scholar
  83. 83.
    Westbury RC. Use of the Dartmouth COOP Charts in a Calgary practice. In: Lipkin M, editor. Functional status measurement in primary care. New York (NY): Springer-Verlag, 1990: 166–80CrossRefGoogle Scholar
  84. 84.
    Larson CO, Hays RD, Nelson EC. Do the pictures influence scores on the Dartmouth COOP charts? Qual Life Res 1992; 1: 247–9PubMedCrossRefGoogle Scholar
  85. 85.
    Nelson EC, Landgraf JM, Hays RD, et al. The functional status of patients: how can it be measured in physicians office? Med Care 1990; 28: 1111–26PubMedCrossRefGoogle Scholar
  86. 86.
    Nelson EC, Landgraf JM, Hays RD, et al. The COOP function charts: a system to measure patient function in physician’s offices. In: Lipkin M, editor. Functional status measurement in primary care: frontiers of primary care. New York (NY): Springer-Verlag, 1990: 97–131CrossRefGoogle Scholar
  87. 87.
    Meyboom-de Jong B, Smith RJA. Studies with the Dartmouth COOP charts in general practice: comparison with the Nottingham Health Profile and the General Health uestionnaire. In: Lipkin M, editor. Functional status measurement in primary care: frontiers of primary care. New York (NY): Springer-Verlag, 1990: 132–49CrossRefGoogle Scholar
  88. 88.
    Wasson JH, Stukel TA, Weiss JE, et al. A randomized trial of use of patient self-assessment data to improve community practices. Eff Clin Pract 1999; 2: 1–10PubMedGoogle Scholar
  89. 89.
    Wasson JH, Kairys SW, Nelson EC, et al. A short survey for assessing health and social problems of adolescents. J Fam Pract 1994; 38: 489–94PubMedGoogle Scholar
  90. 90.
    Shigemoto H. A trial of the Dartmouth COOP Charts in Japan. In: Lipkin M, editor. Functional status measurement in primary care. New York (NY): Springer-Verlag, 1990: 181–7CrossRefGoogle Scholar
  91. 91.
    Drummond MF, O’Brien B, Stoddart GL, et al. Methods for the evaluation of health care programmes. 2nd ed. Oxford: Oxford University Press, 1997Google Scholar
  92. 92.
    Feeny DH, Torrance GW, Furlong WJ. Health Utilities Index. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven Publishers, 1996: 239–52Google Scholar
  93. 93.
    Coons SJ, Kaplan RM. Cost-utility analysis. In: Bootman JL, Townsend RJ, McGhan WF, editors. Principles of pharmacoeconomics. 2nd ed. Cincinnati (OH): Harvey Whitney Books Company, 1996: 102–26Google Scholar
  94. 94.
    Torrance GW, Feeny D. Utilities in quality-adjusted life years. Int J Technol Assess Health Care 1989; 5: 559–75PubMedCrossRefGoogle Scholar
  95. 95.
    Gold MR, Siegel JE, Russell LB, et al. Cost-effectiveness in health and medicine. New York (NY): Oxford University Press, 1996Google Scholar
  96. 96.
    Kaplan RM, Anderson JP. The General Health Policy Model: an integrated approach. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven Publishers, 1996: 309–22Google Scholar
  97. 97.
    Fanshel S, Bush JW. A Health Status Index and its application to health services outcomes. Oper Res 1970; 18: 1021–66CrossRefGoogle Scholar
  98. 98.
    Bush JW, Chen MM, Patrick DL. Health Status Index in cost effectiveness: analysis of PKU program. In: Berg RL, editor. Health Status Index. Chicago (IL): Hospital Research and Educational Trust, 1973: 172–208Google Scholar
  99. 99.
    Kaplan RM, Sieber WJ, Ganiats TG. The Quality of Well-Being Scale: comparison of the interview-administered version with a self-administered questionnaire. Psychol Health 1997; 12: 783–91CrossRefGoogle Scholar
  100. 100.
    Kaplan RM, Bush JW, Berry CC. Health status: types of validity and the Index of Well-Being. Health Serv Res 1976; 11: 478–507PubMedGoogle Scholar
  101. 101.
    Kaplan RM, Bush JW, Berry CC. Reliability, stability, and generalizability of a Health Status Index: proceedings of the social status section. Washington, DC: American Statistical Association, 1978: 704–9Google Scholar
  102. 102.
    Anderson JP, Kaplan RM, Berry CC, et al. Interday reliability of function assessment for a health status measure: the Quality of Well-Being Scale. Med Care 1989; 27: 1076–84PubMedCrossRefGoogle Scholar
  103. 103.
    Siu AL, Hays RD, Ouslander JG, et al. Measuring functioning and health in the very old. J Gerontol 1993; 48: M10–4CrossRefGoogle Scholar
  104. 104.
    Kaplan RM, Atkins CJ, Timms R. Validity of a Quality of Well-Being Scale as an outcome measure in chronic obstructive pulmonary disease. J Chron Dis 1984; 37: 85–9PubMedCrossRefGoogle Scholar
  105. 105.
    Orenstein DM, Nixon PA, Ross EA, et al. The Quality of wellbeing in cystic fibrosis. Chest 1989; 95: 344–7PubMedCrossRefGoogle Scholar
  106. 106.
    Kerner DN, Patterson TL, Grant I, et al. Validity of the Quality of Well-Being Scale for patients with Alzheimer’s disease. J Aging Health 1998; 10: 44–61PubMedCrossRefGoogle Scholar
  107. 107.
    Andresen EM, Patrick DL, Carter WB, et al. Comparing the performance of health status measures for healthy older adults. J Am Geriatr Soc 1995; 43: 1030–4PubMedGoogle Scholar
  108. 108.
    Patterson TL, Kaplan RM, Grant I, et al. Quality of well-being in late-life psychosis. Psychiatry Res 1996; 63: 169–81PubMedCrossRefGoogle Scholar
  109. 109.
    Pyne JM, Patterson TL, Kaplan RM, et al. Assessment of the quality of life of patients with major depression. Psychiatr Serv 1997; 48: 224–30PubMedGoogle Scholar
  110. 110.
    Kaplan RM, Anderson JP, Patterson TL, et al. Validity of the Quality of Well-Being Scale for persons with human immunodeficiency virus infection. Psychosom Med 1995; 57: 138–57PubMedGoogle Scholar
  111. 111.
    Bombardier C, Ware J, Russell IJ, et al. Auranofin therapy and quality of life in patients with rheumatoid arthritis: results of a multicenter trial. Am J Med 1986; 81: 565–78PubMedCrossRefGoogle Scholar
  112. 112.
    Wu AW, Mathews WC, Brysk LT, et al. Quality of life in a placebo-controlled trial of zidovudine in patients with AIDS and AIDS-related complex. J AIDS 1990; 3: 683–90Google Scholar
  113. 113.
    Balaban DJ, Sagi PC, Goldfarb NI, et al. Weights for scoring the Quality of Well-Being instrument among rheumatoid arthritics. Med Care 1986; 24: 973–80PubMedCrossRefGoogle Scholar
  114. 114.
    Hughes TE, Coons SJ, Kaplan RM, et al. Reweighting the Quality of Well-Being Scale in HIV-infected subjects [abstract]. Qual Life Res 1994; 3: 79–80Google Scholar
  115. 115.
    Hays RD, Siu AL, Keeler E, et al. Long-term care residents’ preferences for health states on the Quality of Well-Being Scale. Med Decis Making 1996; 16: 254–61PubMedCrossRefGoogle Scholar
  116. 116.
    Andresen EM, Rothenberg BM, Kaplan RM. Performance of a self-administered mailed version of the Quality of Well Being (QWB-SA) questionnaire among older adults. Med Care 1998; 36: 1349–60PubMedCrossRefGoogle Scholar
  117. 117.
    Torrance GW, Boyle MH, Horwood SP. Application of multiattribute utility theory to measure social preferences for health states. Oper Res 1982; 30: 1043–69PubMedCrossRefGoogle Scholar
  118. 118.
    Torrance GW, Zhang Y, Feeny D, et al. Multi-attribute preference functions for a comprehensive health status classification system. Hamilton (ON): McMaster University, Centre for Health Economics and Policy Analysis, 1992. Working paper no.: 92–18Google Scholar
  119. 119.
    Feeny D, Torrance GW, Goldsmith C, et al. A multiattribute approach to population health status. Hamilton (ON): McMaster University, Centre for Health Economics and Policy Analysis, 1994. Working paper no.: 94–5Google Scholar
  120. 120.
    Furlong W, Feeny D, Torrance GW, et al. Multiplicative multiattribute utility function for the Health Utilities Index Mark 3 (HUI3) system: a technical report. Hamilton (ON): McMaster University Centre for Health Economics and Policy Analysis, 1998. Working paper no.: 98–11Google Scholar
  121. 121.
    Boyle MH, FurlongW, Feeny D, et al. Reliability of the Health Utilities Index-Mark III used in the 1991 cycle 6 Canadian General Social Survey Health Questionnaire. Qual Life Res 1995; 4: 249–57PubMedCrossRefGoogle Scholar
  122. 122.
    Torrance GW, Furlong W, Feeny D, et al. Multi-attribute preference functions. Pharmacoeconomics 1995; 7: 503–20PubMedCrossRefGoogle Scholar
  123. 123.
    Saigal S, Rosenbaum P, Stoskopf B, et al. Comprehensive assessment of the health status of extremely low birth weight children at eight years of age: comparison with a reference group. J Pediatr 1994; 125: 411–7PubMedCrossRefGoogle Scholar
  124. 124.
    Saigal S, Feeny D, Furlong W, et al. Comparison of the health related quality of life of extremely low birth weight children and a reference group of children at age eight years. J Pediatr 1994; 125: 418–25PubMedCrossRefGoogle Scholar
  125. 125.
    Barr RD, Petrie C, Furlong W, et al. Health-related quality of life during post-inducing chemotherapy in children with acute lymphoblastic leukemia in remission: an influence of corticosteroid therapy. Int J Oncol 1997; 11: 333–9PubMedGoogle Scholar
  126. 126.
    Feeny DH, Furlong W, Barr RD, et al. A comprehensive multiattribute system for classifying the health status of survivors of childhood cancer. J Clin Oncol 1992; 10: 923–8PubMedGoogle Scholar
  127. 127.
    Barr RD, Furlong W, Dawson S, et al. An assessment of global health status in survivors of acute lymphoblastic leukemia in childhood. Am J Pediatr Hematol Oncol 1993; 15: 284–90PubMedGoogle Scholar
  128. 128.
    Feeny D, Leiper A, Barr RD, et al. The comprehensive assessment of health status in survivors of childhood cancer: application to high risk acute lymphoblastic leukaemia. Br J Cancer 1993; 67: 1047–52PubMedCrossRefGoogle Scholar
  129. 129.
    Barr RD, Pai MKR, Weitzman S, et al. A multi-attribute approach to health status measurement and clinical management-illustrated by an application to brain tumors in childhood. Int J Oncol 1994; 4: 639–48PubMedGoogle Scholar
  130. 130.
    Feeny D, Furlong W, Torrance GW. The Health Utilities Index: an update. Qual Life Newslett 1999; May-Aug: 8–9Google Scholar
  131. 131.
    The EuroQol Group. EuroQol: a new facility for the measurement of health-related quality of life. Health Policy 1990; 16: 199–208CrossRefGoogle Scholar
  132. 132.
    Kind P. Measuring valuations for health states: a survey of patients in general practice. York: Centre for Health Economics, University of York, 1990. Discussion paper no.: 76Google Scholar
  133. 133.
    Kind P. The EuroQol instrument: an index of health-related quality of life. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. 2nd ed. Philadelphia (PA): Lippincott-Raven Publishers, 1996: 191–201Google Scholar
  134. 134.
    Dolan P, Gudex C, Kind P, et al. A social tariff for EuroQol: results from a UK general population survey. York: Center for Health Economics, University of York, 1995. Discussion paper no.: 138Google Scholar
  135. 135.
    Essink-Bot ML, Bonsel GJ, van der Maas PJ. Valuations of health states by the general public: feasibility of a standardized measurement procedure. Soc Sci Med 1990; 31: 1201–6PubMedCrossRefGoogle Scholar
  136. 136.
    Brooks RG, Jendteg S, Lindgren B, et al. EuroQoL: health related quality of life measurement. Results of the Swedish questionnaire exercise. Health Policy 1991; 18: 37–48PubMedCrossRefGoogle Scholar
  137. 137.
    Nord E. EuroQol: health-related quality of life measurement. Valuations of health states by the general public in Norway. Health Policy 1991; 18: 25–36PubMedCrossRefGoogle Scholar
  138. 138.
    Johnson JA, Coons SJ. Comparison of the EQ-5D and the SF-12 in an adult US sample. Qual Life Res 1998; 7: 155–66PubMedCrossRefGoogle Scholar
  139. 139.
    van Agt HME, Essink-Bot M-L, Krabbe PFM, et al. Test-retest reliability of health state valuations collected with the Euro-Qol questionnaire. Soc Sci Med 1994; 39: 1537–44PubMedCrossRefGoogle Scholar
  140. 140.
    Dorman P, Slattery J, Farrell B, et al. Qualitative comparison of the reliability of health status assessments with the EuroQol and SF-36 questionnaires after stroke. Stroke 1998; 29: 63–8PubMedCrossRefGoogle Scholar
  141. 141.
    Hurst NP, Kind P, Ruta D, et al. Measuring health-related quality of life in rheumatoid arthritis: validity, responsiveness and reliability of EuroQol (EQ-5D). Br J Rheumatol 1997; 36: 551–9PubMedCrossRefGoogle Scholar
  142. 142.
    Brazier J, Jones N, Kind P. Testing the validity of the EuroQol and comparing it with the SF-36 health survey questionnaire. Qual Life Res 1993; 2: 169–80PubMedCrossRefGoogle Scholar
  143. 143.
    Hurst NP, Jobanputra P, Hunter M, et al. Validity of EuroQol: a generic health status instrument in patients with rheumatoid arthritis. Br J Rheumatol 1994; 33: 655–62PubMedCrossRefGoogle Scholar
  144. 144.
    Brazier JE, Walters SJ, Nicholl JP, et al. Using the SF-36 and EuroQol on an elderly population. Qual Life Res 1996; 5: 195–204PubMedCrossRefGoogle Scholar
  145. 145.
    Coast J, Peters TJ, Richards SH, et al. Use of the EuroQol among elderly acute care patients. Qual Life Res 1998; 7: 1–10PubMedCrossRefGoogle Scholar
  146. 146.
    de Charro F, Rabin R. EQ-5D from the EuroQol group: an update. Qual Life Newslett 1999; May-Aug: 3–4Google Scholar

Copyright information

© Adis International Limited 2000

Authors and Affiliations

  • Stephen Joel Coons
    • 1
    • 2
  • Sumati Rao
    • 1
  • Dorothy L. Keininger
    • 3
  • Ron D. Hays
    • 4
    • 5
  1. 1.Center for Health Outcomes and PharmacoEconomic Research, College of Pharmacy, College of PharmacyThe University of ArizonaTucsonUSA
  2. 2.Division of Social and Administrative Sciences, College of PharmacyThe University of ArizonaTucsonUSA
  3. 3.Research and Education DepartmentMAPI Research InstituteLyonFrance
  4. 4.School of Medicine, Division of General Internal Medicine and Health Services ResearchUniversity of California Los AngelesLos AngelesUSA
  5. 5.Health Program, RANDSanta MonicaUSA

Personalised recommendations