Skip to main content
SpringerLink
Log in

Summary and Future Directions

  • Chapter
  • First Online:
Book cover Quality

  • 1264 Accesses

Abstract

In this chapter I review my working hypothesis and the available data that provide support. Central to this hypothesis is process of valuation. I discuss a number of aspects of the ­valuation process, first comparing statistical vs. cognitive approaches by examining the weighting task, then I discuss the cognitive basis of valuation methods, and finally discuss the literature demonstrating that values are stable parts of a person’s qualitative assessments. I also address what I consider to be the central issue in qualitative research: Can a quality be a quantity? This gave me the opportunity to consider the nature of measurement in the behavioral and social sciences, in general, and qualitative research, in particular. I briefly reviewed the history of development of subjective measurement and concluded that a greater role has to be found for axiomatic fundamental measurement in qualitative research. For this to happen, however, requires that investigators acknowledge the limitations of their current research strategy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This quotation was included in an article by Michell (1997). I have left a portion of the quote out that is available in the article.

  2. 2.

    By “thinking about” I mean both conscious and unconscious cognitive processes.

  3. 3.

    Kahneman’s approach has limited generality since it rejects a role for retrospective assessments in a qualitative assessment, yet it is clear that reflection is a regular part of a qualitative assessment, while Rasch’s approach is limited to the verbally fluent and breaks down when applied to the compromised person.

  4. 4.

    The summary qualitative statements were calculated by combining weights using either or both additive or multiplicative methods.

  5. 5.

    There are, however, alternative methods that could have been used by the authors of the QLI that would have a greater chance of evoking the reflective process hypothesized as being a critical part of a qualitative assessment. For example, the respondent might be asked to reread their satisfaction rating so that when they made their importance rating it was in the context of an estimate of their satisfaction. This ploy might generate the more delayed thought process characteristic of reflection. It would be even possible to measure the reaction time to the importance question with or without review of the satisfaction question, and in this way, provide some evidence that a reflective process occurred.

  6. 6.

    QLI is not unique in this regard, since I believe many qualitative assessments generate a summary statement using metaphoric arithmetization. This implies that the only “valid” measure of quality is a global assessment produced by the respondent.

  7. 7.

    An example of a study that avoids some of the difficulties that Ferrans and Powers have with their study but which still engages in metaphoric arithmetization is the Laman and Lankhorst (1994) report. In this study, respondents were administered the evaluated descriptor and importance weighting task concurrently, and the summary score involved multiplying these indicators and adding them together. Thus, this study avoids the potential confounding of sequential assessments, but the summary of this assessment still is subject to concerns about the meaning generated.

  8. 8.

    It is of interest to note that the Breast Cancer Questionnaire (Levine et al. 1988) did not include weights when the assessments were summed to give a composite score.

  9. 9.

    The term happiness, more so than satisfaction, is likely to evoke an experienced emotion, although it is possible that comparisons are also made when happiness is reported (e.g., as when using attaching the word “happiness” to a feeling that was evaluated). In addition, satisfaction is traditionally thought of as a representative of a “cognitive” process in attitude research.

  10. 10.

    This statement is additional evidence for the presence of metaphoric arithmetization.

  11. 11.

    It would be interesting to know more about the characteristics of these persons. For example, were they healthier than the persons who indicated clearer domain preferences? If so, then this would be consistent with the data from subjects that were presumed to be “healthy” (see Table 12:2; Part A).

  12. 12.

    The standard deviations from Table 1 (Hagell and Westergren 2006) were actually uniformly lower than what was found for total QLI score and its four subdomains.

  13. 13.

    The kind of experiment that I think should be done would involve asking a person to rate their satisfaction of a particular domain, say along a 7 point Likert scale, and then having identified this rating, immediately ask the person to rate the importance of this particular satisfaction rating. I would also include a control group where the two assessments were done consecutively. There are several analyses that could be done. First, does presenting the satisfaction rating immediately followed by the importance rating increase the importance rating compared to rating the domain independently, and second whether multiplying the importance rating by the satisfaction ratings statistically significantly increases the domain score. Aggregating these domains into a global assessment might be more complex because some domain composite scores may go up or some may go down after weighting, so that demonstrating that the weighted satisfactions scores accounts for more variance may not be straightforward and would require detailed subgroup analyses.

  14. 14.

    As will become clear in this section, this is exactly what happens when such standard qualitative assessments as the HUI or the QWB are used. In both cases, what is summed is the value, or utilities, not the ratings of the evaluated descriptors.

  15. 15.

    Before I proceed I need to review and clarify the difference between a number of terms that I have been using. I have already clarified the difference between the phrase “evaluated descriptor” and “valuation” (Chap. 8, p. 270), discussed the contribution of evaluated descriptor to inductive theory building, how qualitative researchers are prone to deductive imposition (Spates 1983; p. 42) or metaphoric arithmetization, and how evaluation of descriptors involves a conscious act, while valuation is a continuous mostly unconscious process. Now I would like to differentiate the terms value and appraisal, since they appear to semantically and cognitively overlap. A value, as a noun, refers to an idealized outcome or state, as such it is a abstract cognitive entity whose meaning is clarified by its concrete examples. In contrast, the term appraisal, as a noun, refers to the fact that a process has occurred (e.g., an evaluation) involving an object or life lived, and therefore, would be cognitively represented as a more concrete entity. Both valuation and appraisal may involve an evaluation, but valuation as a metacognitive process (Chap. 3, p. 64) may occur either as a nonconscious or continuous process. Thus, the terms appraisal and valuation overlap, but are sufficiently distinct that they should not be used as synonyms.

  16. 16.

    The investigators who developed these methods may not acknowledge that their procedures reflected how a person thinks, but to the extent that a person can complete the tasks involved (e.g., using the VAS, TTO, or SG), then it is certainly reasonable to assume that a person is capable of thinking in these ways, and that some may actually think this way when making decisions or judgments.

  17. 17.

    Fryback’s concern have a long history starting with a study by Patrick et al. (1973).

  18. 18.

    What I call “evaluated descriptors” Torrance et al. (1995) describes as a classification system, while what I describe as “valuation” they describe as preferences. The classification system consists of a variety of domains, and selection of levels within a domain results in a profile that characterizes the individual respondent. A preference implies that a choice has occurred, but a valuation refers to both a current and past process. Either can occur under conditions of ­certainty or uncertainty. Thus, the term valuation is a more comprehensive and inclusive term.

  19. 19.

    Bell et al. (1988) use their models to refer to decisions and choices under conditions of uncertainty, but I feel it can also be applied to decisions and choices where the outcomes are certain, such as a rating.

  20. 20.

    The TTO assumes that the utility of life duration is linear, so that it would be imperative that any correction supports this assumption.

  21. 21.

    An example of this type of study would be Sen’s (2001) report that residents of more affluent areas of India have more expectations (and therefore loss aversion) than other poorer areas and as a result expect and receive better healthcare services.

Abbreviations

AQOL:

Australian quality-of-life assessment (Hawthorne et al. 1999)

ATM:

Axiomatic theory of measurement

CBI:

Cancer behavior inventory (Merluzzi et al. 2001)

Com-QOL Scale:

Comprehensive Quality-of-life Scale(Cummins 1997)

EORTC QOQ30C:

European Organization for Research and Treatment of Cancer (Aaronson et al. 1991)

EQ-5D:

EuroQoL -5D (Kind 1996)

FACT-G:

Functional assessment of cancer therapy – general version (Cella et al. 1993)

FACT-P:

Functional assessment of cancer therapy – prostate (Esper et al. 1997)

FIMTM’s:

Functional Independence Measure (Hamilton et al. 1987)

FLIC:

Functional Living Index: Cancer (Shipper et al. 1984)

HALex:

Health and Activities Limitation Index (Erickson 1998)

HAQ:

Health assessment questionnaire (Fries et al. 1980)

HUI:

Health Utilities Index (Torrance et al. 1995)

IDUQOL Scale:

Injection Drug User Quality-of-life Scale (Russell et al. 2006)

LSIA:

Life Satisfaction Index A (Neugarten et al. 1961)

MAUT:

Multiattribute utility approach (Torrance et al. 1995)

MC X2:

Marlow-Crowne Social Desirability Scale (Strahan and Gerbasi 1972)

NHIS:

National Health Interview Survey

PAIS:

Psychosocial Adjustment to Illness Scale (Derogatis and Derogatis 1990)

PI-HAQ:

Personal impact health assessment questionnaire (Hewlett et al. 2002)

QALY:

Quality-adjusted life year(s)

QLI:

Quality-of-life Index (Ferrans and Powers 1985)

QOLA:

Quality-of-life assessment

QWB:

Quality of Well-being Scale (Kaplan and Anderson 1990)

QWB-SA:

Quality of Well-being Scale-Self-Administered (Kaplan et al. 1997)

RSES:

Rosenberg Self-Esteem Scale (Rosenberg 1979)

SAHS:

Self-assessed health status

SEIQoL-DW:

Schedule for individual quality-of-life-direct weighting (O’Boyle et al. 1995)

SF-12:

SF-12 Health survey (Ware et al. 1995)

SF-36:

SF-36 Health survey (Ware et al. 1994)

SF-6D:

SF-6D Health survey (Brazier et al. 2002)

SG:

Standard Gamble

SWLS:

Satisfaction With Life Scale (Diener et al. 1985)

TTO:

Time Trade-off (Torrance et al. 1995)

UW-QOL:

University of Washington Quality-of-life Assessment (Deleyiannis et al. 1997)

VAS:

Visual Analog Scale

WHOQOL-100:

World Health Organization Quality-of-life-100 (The WHOQOL Group 1998)

References

  • Aaronson NK, Ahmedzai S, Bullinger M, Crabeels D, et al. (1991). The EORTC core quality of life questionnaire: Interim results of an international field study. In, (Ed.) D. Osoba, The Effect of Cancer on Quality of life. Boca Raton FL: CRC Press. (p. 185–203).

    Google Scholar 

  • Abellan-Periñ JM, Bleichrodt H, Pinto-Prades JL. (2009). The predictive validity of prospect theory versus expected utility in health utility measurement. J Health Econ. 28, 1039–1047.

    Google Scholar 

  • Allport GW. (1961). Patterns and Growth in Personality. New York NY: Holt Rinehart & Winston.

    Google Scholar 

  • Anderson J. (1962). Studies in Empirical Philosophy. Sydney Australia: Angus and Robertson.

    Google Scholar 

  • Balaban DJ, Sagi PC, Goldfarb NI, Nettler S. (1986). Weights for scoring Quality of Well-being instrument among rheumatoid arthritics. Med Care. 24, 973–980.

    PubMed  CAS  Google Scholar 

  • Bardi A, Schwartz SH. (2003). Values and behavior: Strength and structure of relations. Personal Soc Psychol Bull. 29, 1207–1220.

    Google Scholar 

  • Barofsky I. (1996). Cognitive aspects of quality of life assessment. In, (Ed.) B. Spilker. Quality of life and Pharmacoeconomics in Clinical Trials, 2nd edition. New York NY: Raven Press. (pp. 107–115).

    Google Scholar 

  • Barofsky I. (2000). The role of cognitive equivalence in studies of health-related quality of life assessments. Med Care. 38 (Supp II), 125–129.

    Google Scholar 

  • Barsalou LW. (2008) Grounded cognition. Annu Rev of Psychol. 59, 617–645.

    Google Scholar 

  • Bell DE, Raiffa H, Tversky A. (1988). Descriptive, normative and prescriptive interactions in decision making. In, (Eds.) DE Bell, H Raiffa, A Tversky. Decision Making: Normative and Prescriptive Interactions. New York NY: Cambridge University Press. (pp. 9–30).

    Google Scholar 

  • Benyamini Y, Leventhal EA, Leventhal H. (2000). Gender differences in processing information for making self-assessments of health. Psychosom Med. 62, 354–364.

    PubMed  CAS  Google Scholar 

  • Bleichrodt H. (2002). A new explanation for the difference between time trade-off and standard gamble utilities. Health Educ. 11, 447–456.

    Google Scholar 

  • Bleichrodt H, Abellan-Periñ JM, Pinto-Prades JL, et al. (2007). Revolving inconsistencies in utility measurement under risk: Tests of generalizations of expected utility. Manag Sci. 53, 469–482.

    Google Scholar 

  • Bleichrodt H, Pinto L. (2005). The validity of QALYs under non-expected utility. Econ J. 115, 533–550.

    Google Scholar 

  • Borg I, Lingoes JC. (1987). Multidimensional Similarity Structure Analysis. New York NY: Springer.

    Google Scholar 

  • Borsboom D. (2005). Measuring the Mind: Conceptual Issues in Contemporary Psychometrics. Cambridge UK: Cambridge University Press.

    Google Scholar 

  • Bowling A, Windsor J. (2001). Towards the good life: A population survey of dimensions of quality of life. J Happiness Stud. 2, 55–81.

    Google Scholar 

  • Brazier J, Roberts J, Deverill M. (2002). The estimation of a preference-based measure of health from the SF-36. J Health Econ. 21, 271–292.

    PubMed  Google Scholar 

  • Brazier J, Roberts J, Tsuchiya A, Busschbach J. (2004). A comparison of EQ-5D and SF-6D across seven patient groups. Health Econ. 13, 873–884.

    PubMed  Google Scholar 

  • Bridgman PW. (1927). The Logic of Modern Physics. New York NY: Macmillan.

    Google Scholar 

  • Bridgman PW. (1959). The Way Things Are. New York NY: Viking.

    Google Scholar 

  • Byran S, Longworth L. (2005). Measuring health-related utility: Why the disparity between EQ-5D and SF-6D? Eur J Health Econ. 50, 253–260.

    Google Scholar 

  • Calman KC. (1987). Definitions and dimensions of quality of life. In, (Eds.)NK Aaronson, JH Berkman. The Quality of life of Cancer Patients. New York NY: Raven Press. (pp. 1–9).

    Google Scholar 

  • Campbell A, Converse PE, Rodgers WL. (1976). The Quality of American Life: Perceptions, Evaluations and Satisfaction. New York NY: Russell Sage Foundation.

    Google Scholar 

  • Campbell NR. (1920). Physics the Elements. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Cella DF, Tulsky DS, Gray G, Sarafian B, et al. (1993).The Functional Assessment of Cancer Therapy (FACT) scale: Development and validation of the general measure. J Clin Oncol. 11, 570–579.

    PubMed  CAS  Google Scholar 

  • Cliff N. (1992). Abstract measurement of adult intelligence. Psychol Bull. 40, 153–193.

    Google Scholar 

  • Connor-Spady B, Suarez-Alazor ME. (2003). Variation in estimation of quality-adjusted life years by different performance-based instruments. Med Care. 41, 791–801.

    Google Scholar 

  • Cummins RA. (1997). Comprehensive Quality of life Scale : Adult. Manuel. Melbourne Australia: Deakin University.

    Google Scholar 

  • Deleyiannis F W-B, Weymuller EA, Coltrera MD. (1997). Quality of life of disease-free survivors of advanced (Stage III or IV) Oropharyngeal cancer. Head Neck. 21, 466–473.

    Google Scholar 

  • Derogatis LR, Derogatis MF. (1990). The Psychological Adjustment to Illness Scale: Administration Scoring and Procedure Manuel. Towson MD: Clinical Psychometric Research.

    Google Scholar 

  • Diener E, Emmons RA, Larson RJ, Griffin S. (1985). The Satisfaction with Life Scale. J Personal Assess. 49, 71–75.

    Google Scholar 

  • Dingle H. (1950). A theory of measurement. Brit J Philos Sci. 1, 5–26.

    Google Scholar 

  • Dolan P. (2000). The effect of age on health state valuations. J Health Serv Res Policy. 5, 17–21.

    PubMed  CAS  Google Scholar 

  • Draycott SG, Kline P. (1994a). Further investigations into the nature of the BIP: a factor analysis of the BIP with primary abilities. Personal Individ Individ. 17, 201–209.

    Google Scholar 

  • Draycott SG, Kline P. (1994b). Speed and ability: A research note. Personal Individ Individ. 17, 763–768.

    Google Scholar 

  • Earles JLK, Connor LT, Smith AD, Park D. (1997).Interrelations of age, self-reported health, speed and memory. Psychol Aging. 12, 675–683.

    PubMed  CAS  Google Scholar 

  • Erickson P. (1998). Evaluation of a population-based measure of quality of life: the Health and Activity Limitation Index (HALex). Qual Life Res. 7,101-114.

    PubMed  CAS  Google Scholar 

  • Erickson P, Wilson R, Shannon I. (1995). Years of Healthy Life. Statistical Note #7. National Center for Health Statistics. Washington DC: Public Health Service.

    Google Scholar 

  • Esper P, Mo F, Chodak G, Sinner M, et al. (1997). Measuring Quality of life in men with prostate cancer using the Functional Assessment of Cancer Therapy-Prostate (FACT-P) instrument. Urology. 50, 920–928.

    PubMed  CAS  Google Scholar 

  • Fanshel S, Bush, JW. (1970). A Health Status Index and its application to the health services outcomes. Oper. Res. 18, 1021–106.

    Google Scholar 

  • Fechner GT. (1860). Elemente der Psychophysik. Leipzig: Breitkopf & Hartel.

    Google Scholar 

  • Ferguson A, Myers CS, Bartlett RJ, Banister H, et al.(1940). Final report of the committee appointed to consider and report upon the possibility of quantitative estimates of sensory events. Rep Brit Assoc Adv Sci . 2, 331–349.

    Google Scholar 

  • Ferrans CE, Frisch MB. (2005). Measuring quality of life: Is weighting with importance justified? Annual Meeting, International Society for Quality of life Research. San Francisco, CA. Qual Life Res. 14, A2012.

    Google Scholar 

  • Ferrans CE, Powers MJ. (1985). Quality of life index: development and psychometric properties. Adv Nurs Sci. 8, 15–24.

    CAS  Google Scholar 

  • Franks P, Hanner J, Fryback DG. (2006). Relative disutilities of 47 risk factors and conditions assessed with seven preference-based health status measures in a National U.S. sample: Toward consistency in cost-effectiveness analyses. Med Care. 44, 478–485.

    PubMed  Google Scholar 

  • Fraser CO. (1980). Measurement in psychology. Br J Psychol. 71. 23–34.

    Google Scholar 

  • Freitas AL, Gollwitzer PM, Trope Y. (2004). The influence of abstract and concrete mindsets on anticipating and guiding other’s self-regulatory efforts. J Exp Soc Psychol. 40, 739–752.

    Google Scholar 

  • Fries JF, Spitz P, Kraines RG, Holman HR. (1980). Measurement of patient outcome in arthritis. Arthritis Rheum. 23,137–145.

    PubMed  CAS  Google Scholar 

  • Frisch MB. (1992). The quality of life inventory: A cognitive-behavioral tool for complete problem assessment, treatment planning, and outcome evaluation. Behav Ther. 16, 42–44.

    Google Scholar 

  • Fryback DG, Dunham NC, Paita M, Hanner J, et al (2007). U.S. norms for six generic health-related quality of life indexes from the National Health Measurement study. Med Care 45, 1162–1170.

    PubMed  Google Scholar 

  • Fryback DG, Kim J-S, Palta M, Revicki DA. (2007). New perspectives on how preference-based indexes (EQ-5D, HUI2,HUI3, QWB-SA, and SF-6D) scale summary health-related quality of life. International Society for Quality of life Research Annual Meeting Abstracts Qual of Life Res A-5.

    Google Scholar 

  • Fryback DG, Palta M, Cherepanov D, Bolt D, et al. (2009). Comparison of 5 health-related quality of life indexes using item response theory analysis. Med Decis Mak. First published online October 20, 2009 as doi:10.1177/0272989X09347016.

  • Fujita K, Trope Y, Liberman N, Levin-Sagi M. (2006). Construal levels and self-control. J Personal Soc Psychol. 90, 351–367.

    Google Scholar 

  • Fulford KWM. (2000).Teleology without tears: Naturalism, neo-naturalism, and evaluationism in the analysis of function statements in biology (and a bet on the Twenty-first Century). Philos Psychiatr Psychol, 7,77–94.

    Google Scholar 

  • Garster NC, Palta M, Sweitzer NK, Kaplan RM, et al (2009). Measuring health-related quality of life in population-based studies of coronary heart disease: Comparing six generic indexes and a disease-specific proxy score. Qual Life Res. 18,1239–1247.

    PubMed  Google Scholar 

  • Gollwitzer PM. (1996). The volitional benefits of planning. In, (Eds.) PM Gollwitzer, JA Bargh. The Psychology of Action: Linking Cognition and Motivation to Behavior. New York NY: Gilford Press. (p. 287–312).

    Google Scholar 

  • Gorbatenko-Roth K, Levin I, Altmaier E, Doebbeling B. (2001). Accuracy of health-related quality of life assessment: What is the benefit of incorporating patients’ preferences for domain functioning? Health Psychol. 20, 136–140.

    PubMed  CAS  Google Scholar 

  • Grice P. (1989). Studies in the Way of Words. Cambridge MA: Harvard University Press.

    Google Scholar 

  • Grieve R, Grishchenko MK, Cairns J. (2009). SF-6D versus EQ-5D: Reasons for differences in utility scores and impact on reported cost-utility. Eur J Health Econ. 10, 15–23.

    PubMed  Google Scholar 

  • Guyatt GH, Nogradi S, Halcrow S, Singer J, et al. (1989). Development and testing of a new measure of health status for clinical trials in heart failure. J Gen Intern Med. 4, 101–107.

    PubMed  CAS  Google Scholar 

  • Guttman L. (1968). A general nonmetric technique for finding the smallest coordinate space for a configuration of points. Psychom. 33, 469–506.

    Google Scholar 

  • Hagell P, Westergren A. (2006). The significance of importance: An evaluation of Ferrans and Powers’ quality of life index. Qual Life Res. 15, 867–876.

    PubMed  Google Scholar 

  • Hamilton BB, Granger CV, Sheerwin FS, et al. (1987). A Uniform National Data System for Medical Rehabilitation. Baltimore MD: PH Brookes.

    Google Scholar 

  • Hand DJ. (1996). Statistics and the theory of measurement. J R Stat Soc A. 159 (Part 3), 445–492.

    Google Scholar 

  • Hawthorne G, Richardson J, Osborne R. (1999). The assessment of quality of life (AQoL) instrument: A psychometric measure of health-related quality of life. Qual Life Res. 8, 209–224.

    PubMed  CAS  Google Scholar 

  • Hawthorne G, Richardson J, Day NA. (2001). A comparison of the Assessment of Quality of life (AqoL) with four other generic utility instruments. Ann Med. 33, 358–370.

    PubMed  CAS  Google Scholar 

  • Hershey JC, Shoemaker PJH. (1985). Probability versus certainty equivalence methods in utility measurement: Are they equivalent? Manag Sci. 31, 1213–1231.

    Google Scholar 

  • Hewlett S, Smith AP, Kirwan JR. (2001). Values for function in rheumatoid arthritis: patients, professionals, and public. Ann Rheum Dis. 60: 928–933.

    PubMed  CAS  Google Scholar 

  • Hewlett S, Smith AP, Kirwan JR. (2002). Measuring the meaning of disability in rheumatoid arthritis: Personal Impact Health Assessment Questionnaire (PI HAQ). Ann Rheum Dis. 61: 986–993.

    PubMed  CAS  Google Scholar 

  • Hickey A, O’Boyle CA, McGee HM, Joyce CRB. (1999). The Schedule for the Evaluation of Individual Quality of life. In, (Eds.) CRB Joyce, HM McGee, CA O’Boyle. Individual Quality of life: Approaches to Conceptualization and Assessment. Amsterdam The Netherlands: Harwood. (pp. 119–133).

    Google Scholar 

  • Hsieh C-H. (2003). Counting importance: The case of life satisfaction and relative domain importance. Soc Indic Res. 61, 227–240.

    Google Scholar 

  • Jostmann NB, D Lakens, TW Schubert. (2009). Weight as an embodiment of importance. Psychol Sci. 20, 1160–1174.

    Google Scholar 

  • Kahneman D, Tversky A. (1979). Prospect theory: An analysis of decisions under risk. Econometrica. 47, 263–291.

    Google Scholar 

  • Kant I. (1786). Metaphysical Foundation of Natural Science. (J. Ellington [Translator] 1970). Indianapolis IN: Bobbs-Merrill.

    Google Scholar 

  • Kaplan RM, Anderson JP. (1990). The General Health Policy Model: An integrated approach. In, (Ed.) B. Spilker. Quality of life Assessments in Clinical Trials. New York NY: Ravens.

    Google Scholar 

  • Kaplan R, Anderson JP. (1996). The General Health Policy Model: An integrated approach. In, (Ed.) B Spilker. Quality of Life and Pharmacoeconomics in Clinical Trials. New York NY: Ravens. (p. 309–322).

    Google Scholar 

  • Kaplan RM, Bush JW, Berry CC. (1976). Health status: Types of validity and the index of well-being. Health Serv Res. 4, 478–507.

    Google Scholar 

  • Kaplan RM, Groess EJ, Sengupta N, Sieder W, et al. (2005). Comparison of measured utilities scores and imputed scores from the SF-36, in patients with rheumatoid arthritis. Med Care. 43, 79–87.

    PubMed  Google Scholar 

  • Kaplan RM, Sieber WJ, Ganiats TG. (1997).The Quality of Well-being Scale: Comparison of the interviewer-administered version with a self-administered questionnaire. Psychol Health. 12, 783–791.

    Google Scholar 

  • Keeney RL. (1988). Building models of values. Eur J Oper Res. 37, 149–157.

    Google Scholar 

  • Kind P. (1996). The EuroQoL instrument: An index of health-related quality of life. In, (Ed.) B Spilker. Quality of life and Pharmacoeconomics in Clinical Trials. Philadelphia PA: Lippincott-Raven. (p. 191–201).

    Google Scholar 

  • Kind P, Macran S. (2005). Eliciting social preference weights for Functional Assessment of Cancer Therapy-Lung health states. Pharmecon. 23, 1143–1153.

    Google Scholar 

  • Kline P. (1998). The New Psychometrics: Science, Psychology and Measurement. London, UK: Routledge.

    Google Scholar 

  • Knäuper B,Turner PA. (2003). Measuring health: Improving the validity of health assessments. Qual Life Res. 12(Suppl 1) 81–69.

    PubMed  Google Scholar 

  • Konerding U, Moock J, Kohlmann T. (2009). The classification of systems of the EQ-5D, the HUI II and the SF-6D: What do they have in common? Qual Life Res. 18,1249-1261.

    PubMed  Google Scholar 

  • Krantz DH, Luce RD, Suppes P, Tversky A. (1971). Foundations of Measurement. Vol 1. New York NY: Academic Press.

    Google Scholar 

  • Kristiansen CH, Hotte AM. (1996). Mortality and the self: Implications for when and how of value-attitude-behavior relations. In, C Seligman, JM Olsen, MP Zanna (Eds.). The Ontario Symposium. Vol 8. The Psychology of Values. Hillsdale NJ: Lawrence Erlbaum. (p. 77–106).

    Google Scholar 

  • Lakoff G, Johnson M. (1980). Metaphors We Live By. Chicago Il: University of Chicago Press.

    Google Scholar 

  • Laman H, Lankhorst GJ. (1994). Subjective weighting of disability: An approach to quality of life assessment in rehabilitation. Disabil Rehabil. 16, 198–204.

    PubMed  CAS  Google Scholar 

  • Levine MN, Guyatt GH, Gent M, De Pauw S, et al. (1988). Quality of life in Stage II breast cancer: An instrument for clinical trials. J Clin Oncol. 6, 1798–1810.

    PubMed  CAS  Google Scholar 

  • Locke EA. (1969). What is job satisfaction? Organ Behav Hum Perform. 4. 309–336.

    Google Scholar 

  • Locke EA. (1970). Job satisfaction and job performance: A theoretical analysis. Organ Behav Hum Perform. 5, 484–500.

    Google Scholar 

  • Luce RD, Krantz DH, Suppes P, Tversky A. (1990). Foundations of Measurement. Vol. 3. San Diego CA: Academic Press.

    Google Scholar 

  • Luce RD, Tukey JW. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. J Math Psychol. 1, 1–27.

    Google Scholar 

  • Marra CA, Woolcott JC, Kopec JA, Shojania K, et al (2005). A comparison of generic, indirect utility measures (the HUI2, HUI3,SF-6D and the EQ-5D) and disease-specific instruments in rheumatoid arthritis. Soc Sci Med, 60. 1571–1582.

    PubMed  Google Scholar 

  • Mastekaasa A. (1984). Multiplicative and additive models of job and life satisfaction. Soc Indic Res. 14, 141–163.

    Google Scholar 

  • McCelland DC. (1985). Human Motivation. Glenview Il: Scott, Foreman.

    Google Scholar 

  • McFarlin DB, Coster EA, Rice RW, Cooper AT. (1995). Facet importance and job satisfaction: Another look at the range-of-affect hypothesis. Basic Appl Soc Psychol. 16, 489–502.

    Google Scholar 

  • McGee HM, O’Boyle CA, Hickey A, O’Malley K, et al. (1991). Assessing the quality of life of the individual: The SEIQoL with a healthy and a gastroenterology unit population. Psychol Med. 21, 749–759.

    Google Scholar 

  • Merluzzi TV, Nairm RC, Hedge K, Martinez Sanchez MA, et al. (2001). Self-efficacy for coping with cancer: Revision of the Cancer Behavior Inventory (Version 2.0). Psycho-Oncol. 10, 206–217.

    CAS  Google Scholar 

  • Michell J. (1997). Quantitative science and the definition of measurement in psychology. Brit J Psychol. 88, 355–383.

    Google Scholar 

  • Michell J. (1999). Measurement in Psychology: Critical history of a methodological concept. Cambridge UK: Cambridge Press.

    Google Scholar 

  • Michell J. (1986). Measurement scales and statistics: A class of paradigms. Psychol Bull. 100, 398–407.

    Google Scholar 

  • Mobley WH, Locke EA. (1970). The relationship of value importance to satisfaction. Organ Behav Hum Perform. 5, 463–483.

    Google Scholar 

  • Morita S, Ohashi Y, Kobayashi K, Matsumot T, et al. (2003). Individual different “weights” of quality of life assessment in patients with advanced nonsmall-cell lung cancer. J Clin Epidemiol. 56, 744–751.

    PubMed  Google Scholar 

  • Mozley CG, Huxley P, Sutcliffe C, Bagley H, et al (1999). “Not knowing where I am doesn’t mean I don’t know what I like”: Cognitive impairment and quality of life responses in elderly people. Int J Geriat Psychiatr. 14, 776–783.

    CAS  Google Scholar 

  • Neugarten BL, Havinghurst RJ, Tobin SS. (1961). Measurement of life satisfaction. J Gerontol. 16, 134–143.

    PubMed  CAS  Google Scholar 

  • O’Boyle, Brown J, Hickey A, McGee H, et al. (1995). Schedule for the Evaluation of Individual Quality of life(SEIQoL): A direct weighting procedure for quality of life domains (SEIQoL-DW). Dublin UK: Administration Manuel; Department of Psychology, Royal College of Surgeons.

    Google Scholar 

  • Osoba D. (1994). Lessons learned from measuring health-related quality of life in oncology. J Clin Oncol. 12, 508–516.

    Google Scholar 

  • Osoba D, Hsu M, Copley-Merriman, Cooms J, et al. (2006). Stated preferences with cancer for health-related quality of life (HRQL) domains during treatment. Qual Life Res. 15, 273–283.

    PubMed  Google Scholar 

  • Park DC. (2000). The basic mechanisms accounting for age-related decline in cognitive function. In, (Eds.) DC Park, N Schwarz. Cognitive Aging: A Primer. Philadelphia PA: Taylor and Francis. (p. 3–21).

    Google Scholar 

  • Patrick DL, Bush JW, Chen MM. (1973). Towards an operational definitional of health. J Health Soc Behav. 14, 6–23.

    PubMed  CAS  Google Scholar 

  • Phillip EJ, Merluzzi TV, Peterman A, Cronk LB. (2009). Measurement accuracy in assessing patient’s quality of life: To weight or not to weight domains of quality of life. Qual Life Res. 18, 775–782.

    Google Scholar 

  • Pickard AS, Shaw JW, Lin H-W, Trasj PC, et al. (2009). A Patient-based utility measure of health for clinical trials of cancer therapy based on the European Organization for the Research and Treatment of Cancer quality of life questionnaire. Values Health 12, 977–988.

    Google Scholar 

  • Rand A. (1964). The objectivist ethics. In, (Ed.) A. Rand. The Virtue of Selfishness. New York NY: Signet. (pp. 13–35).

    Google Scholar 

  • Reed Johnson F, Hauber AB, Osoba D, Hsu M-A, et al. (2006). Are chemotherapy patients’ HRQOL importance weights consistent with linear scoring rule? A stated-choice approach. Qual Life Res. 15: 285–298.

    PubMed  Google Scholar 

  • Rice RW, Markus K, Moyer RP, McFarlin DB. (1991). Facet importance and job satisfaction: Two experimental tests of Locke’s Range of Affect hypothesis. J Appl Soc Psychol. 24: 1977–1987.

    Google Scholar 

  • Rogers SN, Laher SH, Overend L, Lowe D. (2002). Importance-rating using the University of Washington Quality of life questionnaire in patients treated by primary surgery for oral and oro-pharyngeal cancer. J Cranio-Maxilofac Surg. 30, 125–132.

    CAS  Google Scholar 

  • Rokeach M. (1973). The Nature of Human Values. New York NY: Free Press.

    Google Scholar 

  • Rosenberg, M. (1979). Conceiving the self. New York NY: Basic Books.

    Google Scholar 

  • Ross M. (1989). Relation of implicit theories to the construction of personal histories. Psychol Rev. 96, 341–347.

    Google Scholar 

  • Rosser R, Kind P. (1978). A scale of valuations of states of illness: Is there a social consensus? Int J Epidemiol. 7, 347–358.

    PubMed  CAS  Google Scholar 

  • Russell LB, Hubley AM. (2005). Importance ratings and weighting: Old concerns and new perspectives. Int J Test. 5, 105–130.

    Google Scholar 

  • Russell LB, Hubley AM, Palepu A, Zumbo BD. (2006). Does weighting capture what’s important? Revisiting subjective importance weighting with a quality of life measure. Soc Indic Res. 75, 141–167.

    Google Scholar 

  • Ruta DA, Garratt AM, Leng M, Russell IT, et al. (1994). A new approach to the measurement of quality of life: The Patient Generated Inventory (PGI). Med Care. 32, 1109–1126.

    PubMed  CAS  Google Scholar 

  • Schwartz CE, Sprangers MAG. (2000). Adaptation to Changing Health: Response Shift in Quality of life Research. Washington DC, American Psychological Association.

    Google Scholar 

  • Schwartz SH. (1992). Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In, (Ed.)MP Zunna. Advances in Experimental Social Psychology. (Vol. 25). New York NY: Academic Press. (pp. 1–65).

    Google Scholar 

  • Schwarz N, Strack F. (1999). Reports of subjective well-being: Judgmental processes and their methodological implications. In, (Eds.) D Kahneman, E Diener, N Schwarz. Well-being : The Foundations of Hedonic Psychology. New York, Russell Sage Foundation. (p. 61–84).

    Google Scholar 

  • Sen A. (2001). Objectivity and position: Assessment of health and well-being. In, (Eds.) J Drèze, A Sen. India: Development and Participation. Oxford UK: Oxford University Press. (p. 115–128).

    Google Scholar 

  • Shipper H, Clinch J, McMurray A, Levitt M. (1984). Measuring the quality of life of cancer patients: The Functional Living Index-Cancer: Development and validation. J Clin Oncol. 2, 472–483.

    Google Scholar 

  • Søgaard R, Christensen FB, Videba/ek TS, Bünger C, et al. (2009). Interchangeability of the EQ-5D and the SF-6D in long-lasting low back pain. Value Health. 12, 606–612.

    Google Scholar 

  • Spates JL. (1983). The sociology of values. Annu Rev Sociol. 9, 27–49.

    Google Scholar 

  • Stavem K, Frøland SS, Hellum KB. (2005). Comparison of preference-based utilities of the 15D, EQ-5D, and SF-6D in patients with HIV/AIDS. Qual Life Res. 14, 971–980.

    PubMed  Google Scholar 

  • Stevens SS. (1946). On the theory of scales of measurement. Psychol Bull 36, 221–263.

    Google Scholar 

  • Strahan R, Gerbasi KC. (1972). Short homogenous versions of the Marlow-Crowne Social Desirability Scale. J Clin Psychol. 28: 191–193.

    Google Scholar 

  • Stineman MG, Maislin G, Nosek M, Fiedler R, et al. (1998). Functional status; Application of a new feature trade-off consensus building tool. Arch Phys Med Rehabil. 79,1522–1529.

    PubMed  CAS  Google Scholar 

  • Stineman MG, Wechsler B, Ross R, Maislin G. (2003). A method for measuring quality of life through subjective weighting of functional status. Arch Phys Med Rehabil. 84 Suppl 2, S15-S22.

    PubMed  Google Scholar 

  • Stone PC, Murphy RF, Matar HE, Almerie MQ. (2009). Quality of life in patients with prostate cancer: Development and application of a hybrid assessment method. Prostate Cancer Prostatic Dis. 12, 72–78.

    PubMed  CAS  Google Scholar 

  • Stroop JR. (1935). Studies of interference in serial verbal reactions, J Exp Psychol. 18, 643–662.

    Google Scholar 

  • Suppes P, Krantz DH, Luce RD, Tversky A. (1989). Foundations of Measurement. (Vol. 2). New York NY: Academic Press.

    Google Scholar 

  • Todman J, Teunisse S, Phillips L. (2003). An “Innocuous Theoretical Indulgence”?: The use of weighting by importance. Qual Life Res 12: 825.

    Google Scholar 

  • Torelli CJ, Kaikati AN. (2009). Values as predictors of judgments and behaviors: The role of abstract and concrete mindsets. J Personal Soc Psychol. 96, 231–247.

    Google Scholar 

  • Torrance GW. (1976). Health status index models: A unified mathematical view. Manag Sci. 22, 990–1001.

    Google Scholar 

  • Torrance GW. (1986). Measurement of health state utilities for economic appraisal: A review. J Health Econ. 5, 1–30.

    PubMed  CAS  Google Scholar 

  • Torrance GW, Furlong W, Feeny D, Boyle M. (1995).Multi-attribute preference functions: Health Utilities Index. PharmEcon. 7, 503–520.

    CAS  Google Scholar 

  • Trauer T, Mackinnon A. (2001). Why are we weighting? The role of importance ratings in quality of life measurement. Qual Life Res 10, 579–585.

    PubMed  CAS  Google Scholar 

  • Tversky A, Kahneman D. (1992). Advances in Prospect Theory: Cumulative representation under uncertainty. J Risk Uncertain. 5, 297–323.

    Google Scholar 

  • Tyas S, Snowdon DA, Desrosiers MF, Riley KP. (2007). Healthy aging in the Nun Study: Definition and neuropathologic correlates. Age Aging. 36, 650–655.

    Google Scholar 

  • von Kries J. (1882). Über die Messung intensiver Grössen und über das sogenannte psychophysische Gesetz. Vierteljahrsschr wiss Philos. 6, 257–294.

    Google Scholar 

  • von Neumann J, Morgenstern O. (1944). Theory of Games and Economic Behavior. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • von Osch SMC, Stiggelbout AE. (2008). The construction of the standard gamble utilities. Health Econ. 17, 31–40.

    PubMed  Google Scholar 

  • von Osch SMC, Wakker PP, van den Hout WB, Stiggelbout AE. (2004). Correcting biases in standard gamble and time tradeoff utilities. Med Decis Mak. 24, 511–517.

    Google Scholar 

  • Wakefield JC. (1999). Evolutionary versus prototype analyses of the concept of disorder. J Abnorm Psychol. 108, 374–399.

    PubMed  CAS  Google Scholar 

  • Ware JE, Kosinski MA, Keller SD. (1994). SF-36 Physical and Mental Health Summary Scales: A Users Manual. Boston MA: The Health Institute, New England Medical Center.

    Google Scholar 

  • Ware JE, Kosinski MA, Keller SD. (1995). SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales. Boston MA: The Health Institute, New England Medical Center.

    Google Scholar 

  • Ware JE, Snow KK, Kosinski MA, Gandek B. (1993). SF-36 Health Survey: Manual and Interpretation Guide. Boston MA: The Health Institute, New England Medical Center.

    Google Scholar 

  • Wee H-L, Machin D, Loke W-C, Li S-C, et al. (2007). Assessing differences in utility scores: A comparison of four widely used preference-based instruments. Value Health. 10, 256–265.

    PubMed  Google Scholar 

  • Welham J, Haire M, Mercer D, Stedman T. (2001). A gap approach to exploring quality of life in mental health. Qual Life Res. 10: 421–429.

    PubMed  CAS  Google Scholar 

  • Wettergren L, Björkholm M, Langius-Eklöf. (2005). Validation of an extended version of the SEIQoL-DW in a cohort of Hodgkin lymphoma’ survivors. Qual Life Res. 14: 2329–2333.

    Google Scholar 

  • The WHOQOL Group. (1998). The World Health Organization Quality of life Assessment (WHOQOL): Development and general psychometric properties. Soc Sci Med. 46, 1569–1585.

    Google Scholar 

  • Williams B, Coyle J, Healy D. (1998). The meaning of patient satisfaction: An explanation of high reported levels. Soc Sci Med. 47, 1351–1359.

    PubMed  CAS  Google Scholar 

  • Williams PG, Wasserman MS, Lotto AJ. (2003). Individual differences in self-assessed health: An information-processing investigation of health and illness cognition. Health Psychol 22, 3–11.

    PubMed  Google Scholar 

  • Willis GB. (2005) Cognitive Interviewing: A Tool for Improving Questionnaire Design. Thousand Oaks CA: Sage.

    Google Scholar 

  • Wu C-H. (2008). Can we weight satisfaction score with importance ranks across life domains? Soc Indic Res. 86: 469–480.

    Google Scholar 

  • Wu C-H, Chen LH, Tsai Y-M. (2009). Investigating importance weights of satisfaction scores from a formative model with Partial Least Squares analysis. Soc Indic Res. 90, 351–363.

    Google Scholar 

  • Wu C-H, Yeo G. (2006a). Do we need to weight satisfaction scores with importance ratings in measuring quality of life? Soc Indic Res 78: 305–326.

    Google Scholar 

  • Wu C-H, Yeo G. (2006b). Do we need to weight item satisfaction scores by item importance? A perspective from Locke’s range-of-affect hypothesis. Soc Indic Res 79, 485–502.

    Google Scholar 

  • Wu C-H, Yeo G. (2007). Examining the relationship between global and domain measures of quality of life by three factor structure models. Soc Indic Res 84, 189–202.

    Google Scholar 

  • Wundt W. (1874). Grundzüge der physiologischen Psychologie. Leipzig Germany: Wilhelm Engelmann.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Quality of Life Institute, East Sandwich, MA, 02537, USA

    Ivan Barofsky

Authors
  1. Ivan Barofsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ivan Barofsky .

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Barofsky, I. (2012). Summary and Future Directions. In: Quality. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9819-4_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-9819-4_12

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-9818-7

  • Online ISBN: 978-1-4419-9819-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation