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Quality of Life and Technology Assessment (1989)

Chapter: 6. Assessing Quality of Life: Measures and Utility

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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Suggested Citation:"6. Assessing Quality of Life: Measures and Utility." Institute of Medicine. 1989. Quality of Life and Technology Assessment. Washington, DC: The National Academies Press. doi: 10.17226/1424.
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Assessing Quality of Life: Measures and Utility J. Ivy Brims md Sharon Wood-Dauphinee Quality-of-life research has included me study of levels of economic, political, social, and psychological wellbeing resuldng from varying governments and economic systems, as wed as policies and public pro- grams related to heath. Schuessler and Fisher (1985) wrote Mat quality- of-life research began in the 1960s wad We Report of the President's Commission on National Goals in the United States. Most specialists agree mat Me term "quality" has Me same meaning as "grade" or "rank," which can range from high to low or best to worst. What elements of life are to be so graded? The Imits of analysis can be as large as a nation. Countries can be racked on Weir economic systems and on me types and amounts spent by governments on social programs reladve to expenditures on industry and the military. At Me level of the individual, the elements can be objective (for example, job, income, shelter, and food) or subjective (happiness, sense of well-being, self- re~ization and Me perceptions of the worth and value of life, and me like). Editors' Note: The authors have supplied information about sources of descriptions of measures and their validity and ~liability. Those especially concerned about such matters may wish to go directly to the section entitled "Strategies Used to Assess Instruments," and then to the section entitled "l~e Sources of Descnp~ve ~fonnation for Quality-of-Iife Measures," which lists Awe key reference WOTICs that provide names, descnpua~s, and properties of a number of standard instruments. Readers may then skip to "Ten Review Fonns for Quality-of-Iife Measures," where sources are listed and rewew forms supplied for some instruments not described in standard works. Ibis chapter contains a special segment that describes utility analysis, a specie econanetnc approach to measures of quality of life. 65

66 J. I. WILLIAMS AND S. WOOD-DAUPHINEE The best known studies of the quality of life of individuals are Rose of Andrews and Wiley (1976) and Campbell and colleagues (1976, 1980) at We Institute for Social Research at the University of Michigan. Bow teams of ~nves~gators asked questions about the domains of life sadsfac- tion, including wow, marriage, leisure activities, family, housing, and neighborhood. They developed a global measure of sadsfacdon by com- bin~ng the scores in a genes measure. Quality of life series In the health sector are more limited In scope. In the health sciences, We task at hand is to assess We impact of disease and its management, including interventions, on the well-being of the patient. The health states of the Individuals may influence their quality of life without detenn~ng it As Ware (1987) noted "jobs, housing, schools, and the neighborhood are not attributes of an ~ndividual's health, and they are wed outside the purview of We health care system." Heady care researchers have developed numerous measures of quality of life over We past two decades, and several review articles have com- mented on Rose so far available. Their use in assessing the outcome of health care interventions has become popular. As we have seen In Chapter 2, recent studies have reported on the quality of life of men win mild to moderate hypertension undergoing andhypertensive therapy, of women win advanced breast cancer undergoing chemotherapy, and of cancer patients in hospice programs. Although a variety of studies purport to assess quality of life, there is remarkably little agreement about He underlying concepts or theoretical framework Hat He measures represent. These measures may include clinical symptoms (for example, pain, nausea, vomiting), functional dis- ability (Katz Activities of Daily Livings, heals status measures (RAND health status measures, Sickness Impact Profile), and measures of life satisfaction and psychological weD-be~ng. The World Heath Organization (WHO) has defined heady as a "state of complete physical, mental, and social weld-being and not merely He absence of disease or infirmity." Ware (1987) argues that five health concepts are inherent in this definition: physical health, mental health, social fi~nction~ng, role functioning, and general weD-being. He takes a conservative approach to He study of quality of life in He health sciences. Because the goad of health care is to maximize He health component of He quality of life, he suggests Hat He measures be restncted to assessing heals status. Spider (1987) includes He burden of symptoms in his operational decoration of health He would restrict the assessment of the attributes of

ASSESSING QUALITY OF LIFE 67 heath to those who are definitely sicL He sees lime point In extending me studies of quality of life in health care to me ostensibly healthy, but few writers in the field agree win this point of view. Wenger et al. (1984y, McDowell and Newell ~1987), and Kane and Kane (1981) offer systematic reviews of a number of measures used in qu~ity-of-life studies, including functional disability indices, heady status scales, and measures of life satisfaction. In Weir reviews, these authors discuss He reliability and validity of a number of me measures and Heir uses in heath care studies. We list He ~ns~nents they treat in He section entitled 'bee Sources of Desc~ip~ve Formation for Quality-of- Life Measures." This chapter focuses on measures developed specifically to assess quality of life. ISSUES IN SELECTING QUALITY-OF-LIFE: MEASURES To choose measures for assessing quality of life, researchers need to address seven issues, briefly reviewed below. Disease-Specific Versus Global Assessments Measures may focus on He symptoms, complaints, disabilities, and disruptions in life Hat are specific to He Caracas condition under study. ~deed, He disease-specific approach has been advocated in He study of arthritis, heart disease, and the evaluation of chemotherapy. Altematively, one can assess me quality of life resulting *om He overeat consequences of disease and management on He functional ca- pacities and padents' perception of weB-being. The more global meas- ures cover a number of dimensions urchin a summary score. For ex- ample, the Quality of Life Index developed by Spitzer et al. (1981) includes one item for each of He following dimensions: activities of daily living, pnncipal activities, heath, outlook, and support. Similarly, meas- ures of life satisfaction and general weD-being are global in perspective. Other measures, such as He linear analogue self-assessment scales developed by Pnestman and Baum (1976) or the Breast Cancer Question- naire Levine et al. 1988), are designed so that patients may repeatedly assess Heir symptoms and report Heir physical and emotional responses to adjuvant chemotherapy. The resulting scores show He padents' imme- diate and specific responses to disease and treatment.

68 J. 1. WIlLIAAiS AND S. WOOD-DAUPHINFF: Clinical Endpoints Versus ~ng-Term Outcomes Fletcher et al. (1988) state that me clinical endpoints commonly used for assessing prognoses include evidence of improvement foBow~ng inter- vention, remission of disease, and recurrence. CI=cal endpoints tradi- tionaDy focus on sets of outcomes that are assessed near Me time of diagnosis and treannent. Long-mnge outcomes can be viewed as Rose mat are important to patients as Hey live win Heir resulting states of heath. Patient Ratings Versus Proxy Assessments Investigators generally prefer Hat patients rate their own quality of life. Proxy assessments are important when patients are unable to respond. In these circumstances, researchers may use quality~f-life measures com- pleted by other persons such as ~ responsible clinician, spouse, close friend, or relative of me padent. Objective Versus Subjective Measures Objective measures are based on variables mat can be observed and recorded by venous testing procedures and assessors. Measures of dis- ease activity, remission of symptoms, presence of side effects, changes in functional capacity, ability to calTy out usual activities, and family and social activities are phenomena that can be observed and recorded. These variables are important determinants of quality of life, and agreement can be reached about changes in status that have occulted. Subjective measures provide oppormnides for individuals to express Heir Noughts, knowledge, attitudes, moods, and feelings. Subjective phenomena may be related to particular diseases or Apes of therapy, or they may be more global. Although researchers and policymakers tend to malce much of He distinction between objective and subjective measures, bow are probably necessary when assessing quality of life, and bow require ~nves~gadons into Heir reliability and validity. It is pethaps supposing Hat He objective measures often are not as weU standardized as He subjective measures; objectivity does not automatically mean mat measures are reliable and valid.

ASSESSING QUAIdTY OF LIFE Cognitive Functioning 69 Researchers commonly exclude cognitive funchon~ng from considera- tion In studies of qualitr of life. Except for diseases and therapies that obviously diminish mental capacity, investigators usually assume Mat the cognitive abilities of individuals are unaffected by episodes of illness and care. One may test this assumption by including tests of connive funcdon~ng, as did Croog et al. (1986) in their study of antihypenensive medications. Ratings and Utilities As Schuessler arid Fisher (1985) indicate, quality~f-life measures provide ratings or rankings of heady and life. Some assessments attempt to move *om states of health to judgments of ~e worm or value of life win a given state of heals. Lnvestigators' working win concepts and methods developed in economics, are desiring measures of the utilities of heady states, win me typical scores ranging from 0 for "Dead" to ~ for "Normal Heath." By multiplying the utility values by the number of years individuals live win a given health state, survival time can be expressed in Quality Adjusted Life Years (QUAY). Heath economists have used this approach to compare technologies in terms of costs per QALY gained. Not everyone agrees win such an approach, because it tends to diminish He value of a good, but troubled, life. Utility measures move He measurement of quality of life from rank- ings to judgments of word1 and value. This extension of the field of study is controversial; most particularly, me role of utility analysis in quality-of- life research is hotly contested. Timing of the Assessments Measures such as He linear analogue self-assessment scales, the Func- tional Living Index Cancer, and the Breast Cancer Questionnaire are designed for repeated use before, during, and immediately after treatment. The purpose of He repeated measures is to assess padents' short-temn responses dunng the course of therapy. Global assessment measures, such as He Spitzer Quality of Life Index, are designed to reflect the quality of life foBow~ng He impact of disease

70 J. I. WII1lAMS AND S. WOOD-DAUPHINEE and management or to reflect global changes In assessments over a long period of time. Investigators have used the Spitzer Quality of Life Index for repeated assessments during me course of therapy (Coates et al. 1987, Levine et at. 1988), but the scores tend to be less responsive to short-tenn clinical changes than me disease-specific measures. The basic issue is Me use of quality-of-life measures to assess short- tenn against long-tenn responses to therapy. For example, Levine et al. (1988) stopped taking assessments when patients withdrew from ~eat- ment or relapsed. Conversely, Chubon (1987) used the Life Situation Survey to compare the quality of life of patients in chronic care and rehabilitation programs wad Lose of healthy subjects. There is a problem win repeated self-assessment dunng me course of therapy. Investigators have found it difficult to maintain high self-assess- ment completion rates over seven weeks (Finkelstein et al. 1988, Ragha- van et al. 1988) and were not able to use We assessments because of missing values. Levine et al. (1988) minimized me problem by having nurses interview the patients during clinic visits; this procedure, however, added considerably to We time and costs of the study. If these measures are to be used repeatedly, the time and costs of ma~nta~ng high response rates over multiple assessments must be considered. Summary - Some qualiW-of-life studies ma~ntain one perspective or point of view. Yet it is becoming increasingly common for researchers to employ a mix of perspectives and mesons in assessing qualibr of life. We have re- viewed what is known about the conceptual framework, reliability, valid- id, and uses of specific measures. In any study, several tools may be combined to provide information on various perspectives: subjective and objective, disease-specif~c and global, clinical endpoints and long-term outcomes, and so on. No attempt win be made to sort out the combina- dons of approaches researchers have employed. Examples of multiple approaches to assessing quality of life are given in Chapter 2. STRATEGIES USED TO ASSESS INSTRUMENTS A bewildenng array of terms labels the properties of measures, and researchers in the heath sciences frequency employ strategies for devel- oping and testing measures that differ from Lose used in Me social

ASSESSING QUALt7Y OFL1FE 71 sciences. To standardize our work, we developed He Review Form for Quality-of-Life Measures. We used the Review Form to gamer biblio- graphic information, Be stated purpose of me measure, its underlying concept framework, and a descriptor of its content and fonnat. As part of this review, we have Died to use terms Cat are consistent wad Pose compiled in the Dictionary of Epidemiology Beast 1988) by the International Epidemiology Association and that are used by writers in epidemiology (Fe~nste~n 1987, McDowell and NeweB 1987) and Be social sciences (Bohmstedt 1981, Kerlinger 1986, NunnaBy 1978~. This section briefly reviews some s~ishcal and over expressions. Reliability Two basic strategies can be used to establish Be reliability of a meas- ure. For those based on subjective ratings of attitudes, perceptions, and sense of weD-being, investigators may assess Be reliability by examining the consistency of patterns of response across me items. Me coefficient alpha (Cronbach 1951) measures the intemal consistency of Be response, based on the average correlation among Be items and the number of items In Be instrument The coefficient assumes that the correlations in Be matrix are all positive, because they represent the same dimension. Val- ues of Cronbach's alpha range from O to I. If Cronbach's alpha is high (for example, 0.80 or higher)' Be responses are consistent, and the sum of Be item responses yields a score for Be underlying dimensions Cat the item represents. S=ed another way, if Be items are adequately sampled *om me domain of quality of life, Be son of Be responses should give a better indication of the quality of life of Be individual than Be response to any one item. A low coefficient alpha would indicate Cat the items did not come from the same conceptual domain or that Be noise in the items was substantial. The items can be divided and placed on altemate forms of the measure; the equivalence of the altemate fonns can be tested by comparing Be alphas. Alternatively, me items on one form can be split into two groups, and coefficients can be computed for each half and compared. Compa- rable coefficients confirm the consistency of the responses. The scores for the split fonns can also be correlated to see how Hey correspond. The Speannan-Brown formula uses this correlation to esti- mate the reliability of a scale containing ad items after adjusting for the presence of twice as many items on the composite scale as in each of He two groups (ZeDer and Cannines 1980~.

72 J. 1. W7ll~AMS AND S. WOOD-DAUPHINEE Researchers may decide to create a m~dimensional measure of qual- ity of life and Men select items mat represent me dimensions of interest. For example, quality-of-life measures may have items related to condi- tions specific to disease and management (for example, nausea and vomit- ing in response to chemotherapy for cancer), and Were may be additional items related Deco physical functioning, and social and psychological well- being. Factor analysis s~tisticaDy defines a small number of factors or under- lying dimensions that account for a high proportion of the common variance of We items. Exploratoty factor analysis is used to identify and discard items that are not correlated with We factors of interest. Altema- tively, an investigator may use factor analysis to confirm mat items selected to represent a single dimension of quality of life (for example, physical functioning) principally load onto mat factor and correlate weakly with over factors. The factor represents a single dominant dimension or variable when the factor loadings for the items are relatively high 0.60 or higher—and me common variance and the factor loadings cannot be increased by subdividing the items onto additional factors. Factors are not considered stable unless the results can be replicated in a number of samples and study settings. Once a factor is defined as representing a single variable or dimension, We responses for ~e items on each factor are summed to create the factor score. For a measure with a fairly large number of items and a high coefficient alpha, one can use factor analysis to define two or more factors underlying the responses. A measure mat is intemaBy consistent may still not represent a single dimension. Factor analysis is used to define the under- ly~ng dimensions, and the coefficient alpha may men be used to assess the strength of the consistency of the items on We separate factors. The stability of a scale or factor score is assessed by correlating the scores of subjects with the scores obtained in testing at another time. As Bohmstedt (1981) has noted, the test-retest coefficient can be influenced by true changes in scores. The interpretation of We coefficient of stability is not always straightforward. If me variables being considered are sufficiently objective to be evalu- ated by persons over man me patients, it is possible to compare raters' scores. For example, the Quality of Life Index is designed to be com- pleted by the heady professions responsible for me care of We patient and significant others as well as by patients themselves. Interrater agreement indicates the reliability of the scores by different raters on a single occa- sion, and intrarater agreement is We reliability of the scores by the same rater over repeated testings.

ASSESSING QUAL17Y OF LIFE 73 If the measure is categorical, Cohen's kappa Weiss 1981) is most frequently used to assess the level of agreement beyond Mat expecter! by chance. For mnkings of ordinal measures, Spearman's rho and Kend~l's tau may be used as measures of agreement In addition to kappa. Pearson's product moment correlation is commordy used for comparing quantitative scores of raters. The preferred measure of agreement is We ~ntracIass correladon coeff~- cient. It is particularly useful when Were are Wee or more ratings. It compares the variance between subjects, We variance between raters, and We van ance between times wad We error v an ance. The intraciass corre- lation is reliable if most of We variance in me mode! is accounted for by me van ance between subjects and if me variances by raters and by lime are minimal Weiss 1986~. The measure rests on the analysis of variance and can be use with ordinal as wed as interval data An intraciass correlation coefficient of, for example, 0.80 or higher indicates mat the measure is highly reliable. Scaling refers to We rules for assigning numbers to responses. The scaling determines whether We measure is a nominal, ordinal, interval, or ratio variable. Validity A first step in assessing the validity of a measure is to determine if the content of the items represents the domain or dimension of interest. Face validity is sometimes used to refer to me intuitive appeal of the items; content validity is reserved for me judgments of experts or specialists. When Were exists a v en able extemal to We measure against which me scores can be checked, that v en able can be used as a cr~tenon to judge the measures. For example, the quality-of-life scores should differentiate patients dying of cancer, patients in intensive care, outpatients win chronic diseases, and hearty individuals, even Cough mere may be substantial overlaps in We distributions of scores. Concurrent criterion validity refers to me ability of a measure to differ- entiate between groups at We time the measure is applied. Predictive criterion validity refers to the ability to use these scores to predict future health-related events and states. Quality-of-life measures can be compared win other measures as well. Concepts derived from theory and operationalized into reliable and valid measures are referred to as constructs. The measures under study can be tested against the constructs to determine if We observed relationships are as hypothesized. For example, quality of life should be negatively related

74 J. I. WIlllAMS AND S. WOOD-DAUPHINEE to measures of pain, anxiety, and depression. Similarly, a measure of quality of life should be positively related to life satisfaction and genes well-being. To judge the sensitivity or responsiveness of a measure, me ~nvestiga- tor should have a sense of how much change in a patient's clinical or func- donal stems would produce a change In their quality-of-life score. Sign~fi- cant clinical changes in the individual may not parallel changes in quality- of-life scores. Alternatively, a relatively small change in clinical levels may result in marked changes in a patient's sense of psychological well- being. Finally, Me practicality of a measure refers to He ease and convenience of administration and interpretation. Practicality is particularly important if a measure is to be used repeatedly. A REVIEW OF SELECTED MEASURES FOR ASSESSING QUALITY OF LIFE We reviewed 10 measures for rating quality of life using the Review Form for Quality-of-Life Measures. The section entitled "Ten Review Forms for Quality-of-Life Measures" presents the completed fonns, and Table 6-1 (see page 76, this volume) provides a summary. The Quality of Life Index (Qua), developed by Spitzer et al. (1981), has been tested In a variety of settings. It is used to assess He physical, psychological, and social functioning of patients. The QL-! yields a score that ranges from a high of 10 to a low of 0. Alternative fonns for completion by He patient, He physician or over health professional, relative, or significant other were developed to determine whether compa- rable ratings could be obtained from several sources. The reliability and validity of the QLl have been demonstrated in a series of studies in Australia, Canada, and He United States win a variety of patients. Chubon (1987), PadiBa et al. (1983), and Ferrans and Powers (1985) developed global measures of quality of life to be completed by patients. Chubon's Life Situation Survey assesses quality of life beyond disease- specific conditions and functional limitations, comparing He responses of patients in chronic care and rehabilitation programs with Hose of healthy subjects. Chubon tested his instrument with prison inmates, hospital patients, mentally retarded aunts, spinal injury patients, and Adversity students. Although He samples have been relatively small, the instn~nent appeared to wow well with all groups, and the differences in mean scores were as predicted. Chubon also found positive changes in me mean scores of patients who completed a program for chronic back pain.

ASSESSrNG QUAl~TY OF luff 75 PadiBa's Quality of Life Index focused on physical conditions, ac- tivities, and attitudes of the patients. We found no reports of Me measures other than the articles published by the developers of the instruments. PadiDa ong~naBy developed her measure while working with cancer patients. She adapted the measure for use with colostomy patients, adding a number of disease-specific items. Armour the measure was designed to be global, we found no use of We adapted measure across conditions. Ferrans' QuaUity of Life Index focused on We satisfaction of needs; this measure is broader In scope. It taps life satisfaction In areas outside the immediate reach of health care (for example, marriage, education, occu- pation, future retirement), In addition to items related directly to heath. By 1988' results had been reported for healthy graduate students and dialysis padents. Karnofsky and Burchemal (1949) were among the first to develop a measure to assess the ability of cancer padents to perform dally activities. Their measure has been studied extensively and is widely used, although it has been criticized both conceptually and for its measurement proper- ties. The consensus seems to be that it continues to be a useful tool for physicians to use In rating We impact of cancer and cancer treatment on patients' ability to lead normal lives. The Functional Living Index—Cancer DICE is one of the newer instruments. The FLIC contains 22 items pertaining to symptoms and complaints related to cancer treatment, as wed as me impact of disease and management on physical, psychological, and social functioning. The items were tested on 837 patients in Winnipeg and Edmonton, Canada. When the data were factor analyzed, Schipper et at. (1984) found mat the mean factor scores for four padent groups decreased with the extent of disease. The investigators have completed some construct validation exercises. The FLIC is designed to be completed daily by patients. The responsiveness of the scores to changes over time has yet to be estate fished. Selby et al. (1984) have taken another approach to We development of an instrument for cancer patients. They took 18 items from the Sickness Impact Profile and added 12 items based on clinical experiences along with 2 statements for a global rating of quality of life and life satisfaction. The resulting questionnaire is designed to be completed by either physi- cians or padents. Factor analysis has been used to define We dimensions the items represent. The changes in scores reflect response to chemo~er- apy. We found no reports of uses of the instrument by investigators other man Selby and his colleagues.

76 I. I. ARMS AD S. WOOD-DAUPH~EE TABLE 6~1 A Summary of He~-Related Quality-of-Life Measures Quarry of Life Lee Situation Quality of Lye Measure Index Survey Index . First author Spitzer Chubon papilla Assessment Global Global Disease-specif~c Rater Padent, clinician, Subject Patient significant over Subjects Healthy,cancer Smarts, inmates, Patients (cancer, patients, seriously patients (ESRD,a chemodlerapy or ilL chronically back, spinal injury, radiotherapy, ilL temiinally ill mentally receded) diabetics, healthy) Dimensions Principal activity, Life quality Physical condition, activities of daily daily activities, living, heals, personal abrades social support, outlook on life Reliability Eternal consistency $* * Rater ** Stability ** * * Validity Content ** * * Critenon Concurrent ** ** * Predictive * * Construct ** * Responsiveness * Applications by odlers ** Table 6-1 continues

ASSESSING QUALITY OF IDLE TABLE 661 (Condnued) 77 Quality of Lye Index Quality of Life Index KarnofsJcy Index of Performance Status F - ctio~ Living Index—Cancer Pedilla Ferrans Kamofsly Schipper Disease-specific Global Ca~-~ecific Cancer-~ecific Patient Subject Physician Patient Colostomy patients Healthy persons, Patients Patients dialysis patients Psychological and mealy care, physical Physical stems, physical well- functioning, marriage, physical activities being, body image, folly, Fiends, diagnosis/treat- stress, occupation, meet, surgical and education, le~e, nutritional response, social concerns * * * Symptoms, sociability, daily living, satisfaction retirement, pe~e of mind, faidl, life goals, appearance, happiness, satisfaction * * * * ** * * * * * * * ** * ** * Table 6-1 continues

78 TABLE 6-1 (Condnued) J. 1. WIll~AAlS AND S. WOOD-DAUP~rNFF Low Analogue Study Self-Assessm~ Bream Cancer Measure (waned) Scale Q~tionnawe First author Selby Priestman Levine Assessment Cancer-sp~ific Disease-speciB~c Cancer-,peafic Rater Patient, physician Patient Interviewer Subjects Cancer patients Patients (cancers Breast cancer of breast, long, patients bladder) Dimensions 12 categories of Symptoms, side Consequences SIP, clinical effects, anxiety, of hair loss, problems depression, emotionaldys- personal function, physical relations, physical symptoms, trouble performance with treatment, fatigue, nausea, positive well-being Reliability Internal consistency * Rater * Stability * Validity Content Cntenon Concurrent Predictive Construct * Responsiveness * Applications by others * * * * * * * ** * * * NOI,E: Symbols are as follows:—, not assessed; *, assessed; **, strong feature. End-stage renal disease.

ASSESSING QUALITY OF LIFE 79 We found considerable discussion of linear anadogue self-assessment (LASA) or visual analogue scales (VAS) for rating quality of life. These scales are typically 10 centimeters long with me low or poor end of the scale anchored at O and the upper end anchors at 100. In response to a cue word or phrase, patients mark Weir self-asses~nents on me line. The point marked to Me nearest millimeter produces the score. Priestman and Baum (1976) were among the first to use this technique for quality-of-life assessments of cancer patients. In a number of studies these and over ~nvesUgators have used items related to symptoms and side effects, anxi- ety and depression, personal relations, and functioning, but We actual cues have vaned from study to sway. The scores from repeated testing over me course of treatment for advanced cancer have been reported for individual items, but we found no reports of We fonnal psychometric properties in the measure. A minority of eligible subjects participated in We repeated use of me form, but the loss to foDow-up is not explained. The use of the LASA needs to be standardized so Tat measurement properties of me resulting scales can be formally tested. Thnee trends can be observed in the development of quality-of-life measures. First, although investigators have focused on We clinical relevance of We measures, minimal attention has been paid to the concep- tual underpinnings of quality of life or the theoretical bases for me particular measures. Second, most researchers develop and modify me measures without formally mshng me reliability, validity, and responsive- ness of the resuming scores. Third, Me various measures have been developed in isolation from each other, and attempts to compare and contrast me various measures of quality of life am rare. A REVIEW OF UTILITY ASSESSMENTS IN QUALITY OF LIFE The utility assessment of health states and quality of life has arisen from a theoretical perspective and methodology mat are distinct from those employed by behavioral and clinical scientists. Utility assessment has two components, Me judgment of Me value or worm of life at a given point in lime and me quantity or years of life spent in venous heady states. The utility value assigned to a health state generally ranges from 0, the value ascribed to death, to I, the value ascribed to me reference state of a healthy life. By multiplying a utility value for a health state by the number of years of duration of the expected heath state, the resulting product is the Quality Adjusted Life Years (QALY). Health economists

80 J. I. WlilIAMS AND S. WOOD-DAUPHIN posit Mat health care programs should be evaluated by comparing Me relative costs of the programs with the QALYs produced. The general approach for assessing utility values is based on modem utility theory, advanced by van Neumann and Morgenstern (1953~. The theory describes a method for decisionmaking under conditions of uncer- tainty based on a set of axioms of rational behavior. Holloway (1979) has summarized He wide uses of this model for decisionmaking. Dr~nmond et al. (1986), Torrance (1986, 19871, and Weinstein (1983) have written reviews and summaries of the utility analysis of health care programs. Smith (1988) has presented a number of papers with applications of utility analysis. The reader may wish to refer to these sources for detailed dis- cussions of He meow and methods of utility analysis. The major groups of researchers responsible for applying uglier theory to He heath field include He late lames Bush, Robert Kaplan, and Heir colleagues at the University of California at San Diego; Rachel Rosser and her colleagues at Charting Cross Hospital in London; George Tor- rance and his colleagues at McMaster University in Hamilton, Ontario; and Milton Weinstein and his colleagues at Haward University. Torrance (1986, 1987) and Kaplan and his associates (Kaplan et al. 1984, Anderson et al. 1988) have published information on He reliability and validity of their methods, and we review Heir works briefly. The description of He heady state is me first step in delving utility values. Torrance et al. (1982) have identified six attributes Hat should be included in a description of heath state: physical function, emotional function, sensory function, cognitive function, self-care, and pain The description would indicate He level of functioning on each of me attri- butes associated with a particular heath state. The descriptions can be presented in narrative paragraphs, videotapes of patients, or in other fonns. The descnphons are presented to patients wad He given heady states, Heir close relatives or friends, or headth care professionals for judgments of He utility values to be assigned to He states. The utility values may be rated on a visual analogue scale ranging Tom 0 to 100, win 0 indicating the worse possible health state (death) and 100 the best possible heal state. This method is referred to as a rating scale. The standard gamble technique was me original method for denying utility values. It sits directly on the axioms of utility theory. The subject uses the standard gamble to choose between two altematives to treannent. The outcome of an intervention (new procedure) may be a good outcome win a given probability (for example, 80 percent chance of restoration to

ASSESSING QUALITY OF LIFE 81 normal healed or a worse outcome with a given probability (such as a 20 percent chance of permanent disability or death). The second intenendon (for example, another treatment or no treatment at alp is presented wad a certain (100 percent sure) outcome of intermediate desirability relative to the good and bad outcomes associated wad Me first ~ntenention. The probabilities associated with We new intervention ~ p for a good outcome, ~ - p for a bad outcome) are varied urai} the subject perceives no real difference between me interventions, and the utility value is then calcu- lated for me venous heath states of me second intervention Torrance (1986) reported mat me standard gamble method can be used to measure utilities for chronic health states preferred to death, chronic states consid- ered worse man death, and temporary health states. Torrance et al. (1972) developed me time trade-off method for use In health care evaluations, and hey claim it is simpler to use than the standard gamble approach. The subject considers a heath state associated with a problem that is to last for a fixed period of time as opposed to a shorter period of hearty life. The subject is asked to "trade off " the time in a compromised health state with a lesser time in a heartier state. The time in me healthy state is varied until We point of indifference is found, and the utility value is calculated accordingly. Win six key attributes and multiple levels on each attribute, a large number of unique heady states would have to be defined to describe aD possible comb~nabons of attributes. Torrance et al. (1982) have used multiple attribute theory to reduce me number of measurements required to obtain We utility values for aU combinations of attribute levels. ToIraIlce (1987) presented a summary of me reliability ratings and tests of validity of me utility values fimm the rating, standard gamble, and time trade-off methods. The interrater and test-retest reliabilities range from 0.63 to 0.~. The results of the rating scales and time tmde-off mesons have been validated through comparisons win the standard gamble ap- proach. (Torrance refers to this as criterion validity for We standard gamble memos because it is derived directly from me axioms of utility theo~. We refer to this as construct validity because the standard gamble memos is a scientific construct for infemng preferences in decisionmak- ing.) Churchill and his associates (1987) compared time trade-off utilities of end-stage renal disease patients with the ratings of physicians on Me Quality of Life Index and found them to be congruent That is, they demonstrated construct validity. The mesons are time consuming, demanding of Me subjects, and costly ~ apply. The McMaster group has refined the methods and

82 J. I. WllLIAMS AND S. WOOD-DAUPHINEE simplified Me tasks. They have achieved participation and task comple- tion rates of at least 85 percent. The San Diego group has taken a different approach to assessing utility values (Kaplan et al. 1984, Kaplan and Bush 1982~. Their first step was to categorize individuals ~ ven heath states win respect to levels of mobility, physical activity, and social activity. The second step was ~ classify We same individuals by me symptoms and heal problems that Key have on a given day. Four hundred case descnphons were written to encompass me combinations of functional levels and symptoms or prob- lems. Random samples of individuals in a community gave preference rat- ings to We descriptions on a continuum ranging from O for dead to 1 for completely well. A model for preference structure assigned weights to each level of functioning and symptoms/problem complex. Quality of Well-Being scores are denved by applying We weights for functional levels and symptoms/problems to health sates of interest, and me Quality of Well-Be~ng (QWB) scores are the unlit values for those states. Anderson et al. (1988) compared the reliability of the QWB scores In general household samples and a cI~n~cal outcome sway of bum patients. En Initial interviews, the subjects completed self-a~n~rustered fonns and personal interviews. In a follow-up survey Key repeated the process. They used intemal consistency analysis to detect discrepancies In re- sponses and reported mat 50 percent of We discrepancies were me result of correctable elTors. They concluded that personal interviews are re- quired for the reliable use of the QWB. We found no published reports Tat compare the utility values denved by me standard gamble, time trade-off, and rating scale mesons outlined by Torrance with me QWB utility values developed by me San Diego group. Several questions and criticisms have been directed toward the use of utility values and QALYs in quality-of-life assessments. Some experts debate whether the utility values should be obtained from the public at large, the providers, or the patients themselves. Others argue that me utility assessments are incomplete unless Key include me perspectives of me family members whose lives are directly affected by me health status and quality of life of me patients. If the patient is unable to fonn a judgment, should the next of kin or some close fnend be asked to make a decision about He perceived utility of me patient's health status and prognosis? Patients' assessments of We utility of health states change as Weir health does. For this reason, utility values may not be stable over long

ASSESSING QUAL17Y OF LIFE 83 periods of time. Fur~ennore, projections about morbidity, disability, and mortality frequently depend on expert opinion in the absence of sound epidemiolog~cal data on Me natural history of disease and We impact of interventions. Consequently, assumptions about life expectancy may be only crude estimates of actual experience. Experts do not agree on Me key attributes to be included. Torrance advocates me inclusion of physical, emotional, sensory, cognitive, and self-care functioning, in addidon to paw, but he excludes social funcdon- ing. In actual use me descriptions used ~ Me standard gamble and time tradeoff methods vary according to He disease or technology being evaluated. The QWB is narrow ~ focus because it encompasses only mobility, physical activity, social activity, and symptoms. L.as~dy, although individuals may understand and agree win me ratings for He levels of functioning for a set of attributes, Hey agree less when the issue is whether a derived utility value accurately reflects He worth of human life. The public has even more skepticism about multiplying He life expectancy times the utility values to obtain a "quality-adjusted life year." ~ summary, uglier assessments of quality of life can at best be descnbed as technology with promise and potential, but not as one ac- cepted by the public. THREE SOURCES OF DESCRIPTIVE INFORMATION FOR QUALITY-OF-LIFE MEASURES The editors and He authors of this chapter refer readers to Tree books for reviews of more extensively studied and filmy established quality-of- life measures. The first, Assessment of Quality of Life in Clinical Trials of Cardiovascular Therapies, reviews six quality-of-life instruments and provides infonna~cion on Heir content, administrations development, va- lidity, reliability, gener~izability, applications, and major strengths and limitations. The book lists references for these instruments, contains reproductions of many of them, and compares and contrasts them. The citation for me book and He names of instruments included are: Wenger, N.K., Mattson, M.E., Fu~berg, C.D., and Elinson, I., eds. Assessment of Quality of Life in Clerical Trials of Cardiovascular Therapies. New York, Le Jacq Publishing, Inc., 1984 · Sickness Impact Profile (SIP) Quality of Well-Being (QWB) Scale Psychological General WeB-Being (PGWB) linden McMaster Health Index Questionnaire (MH1Q)

84 J. 1. WIllIAMS AND S. WOOD-DAUPHINEE · Nottingham Health Profile (CHIP) · General Health Rating Index (GENII) The second book is entitled Measuring Health: A Guide to Rating Scales and Questionnaires. It reviews measures by name, developers, purpose, conceptual basis, and description. It offers information on reliability and validity, altemadve fonns of each instrument (if any), references, commentaries on strengths and limitations, He addresses of He ong~nal test developers, and complete or partial reproductions of He instruments. Each review has been checked for accuracy and complete- ness by He instrument developers. This book features a "consumers guide?' to He venous instruments, which provides infonnation on nurnencal characteristics of the scale, length, applications, memos of admin~smcion, a rating of how widely each insurgent is use, and a rating of reliability and validity. The citation for He book and He names of ~nstn~ments listed are: McDowell, I., and NeweD, C. Measunng Health: A Guide to Rating Scales and Questionnaires. New York, Oxford University Press, Inc., 1987. Activities of Daily Living (ADL) Scales · The PULSES Profile (Physical condition, Upper limb functions, Lower I~rnb functions, Sensory components, Excretory Unctions, mend and emotional Status) The Barthe} Index The Index of Independence In Activities of Daily Living, or Index of ADL · The Kenney Self-Care Evaluation · The Physical Self-Maintenance Scale · The Functional Status Rating System Instrumental Activities of Daily Living QADL) Scales · A Rapid Disability Rating Scale The Functional Status Index The Pad ent Evaluation Conference System · The Functional Activities Questionnaire · The Lambeth Disability Screening Questionnaire · The Disability and Brnpair~nent Interview Schedule Psychological Indices . The Health Opinion Survey · The 22 Item Screening Score of Psychiatric Symptoms

ASSESSING QUALITY OF lie The Affect Balance Scale The General WeB-Being Schedule The Mental Heath Inventory Me General Heath Questionnaire Social Heath Indices · The Social Relationship Scale . 85 The Social Support Questionnaire The Social M~adjusunerd Schedule The Katz Adjustment Scales The Social Heath Battery The Social Dysfunction Rating Scale The Social Funchon~ng Schedule The Interview Schedule for Social Interaction The Structured and Scaled hnterview to Assess Malad- justment The Social Adjustment Scale Quality-of-Life and Life Satisfaction Indices · The Quality of Life Index · Four Single-Item Indicators of Well-Being · The Life Sadsfachon Index · The Philadelphia Genatnc Center Morale Scale Pain Measurements Visual Analogue Pain Rating Scales · The Oswestry Low Back Pen Disability Questionnaire · The McGill Pain Questionnaire · The Self-Radng Pain and Distress Scale · The Illness Behavior Questionnaire · The Pain Perception Profile Genera Hemp Measurements . . . . · The Arthritis Impact Measurement Scare The Physical and Mental hopairment-of-Function Evalu- ation The Functions Assessment Inventory The Nottingham Health Profile The Sickness Impact Profile The Mul~dieve} Assessment Instrument The Older Americans Resources and Services (OARS) Multidimensional Functional Assessment Questionnaire The Comprehensive Assessment and Refenal Evaluation The Quality of Well-Being Scale

86 J. I. WlU1~S ED S. WOOD-DAUPHINEE The Bird book, Assessing the Elderly: A Practical Guide to Measure- ment, contains reviews of instruments in four major areas of measurement important to long-term care (L`TC] providers: physical functioning, men- functioning, social functioning, and multidimensional or composite measures. It outlines methods of administration, reliability and validity; types of scales used; the strengths and limitations of the measures; and their similarities and differences and lists their items and characteristics according to function and purpose. It also offers practical suggestions for their use. The authors also cite unpublished instruments `'perhaps cir- culated at professional meetings"—that may be of interest to researchers developing or modifying instruments. The book citation and a partial list of instruments are as follows: Kane, R.A., and Kane, R.~. Assessing He Elderly: A Practical Guide to Measurement. Lexington, Massachusetts, D.C. Head and Com- pany, 1981. Measures of Physical Functioning Measures of Physical Heady Corned Medical Index Cumulative Illness Rating Scale Heals Apex Patient Appraisal and Care Evaluation (PACE) lI: Medical Data Patient CIassificadon for Long-Term Care ETCH: Brnpa~nnents and Medical Status Older Americans Resources and Senrices (OARS): Physical Heath Measures of Ability to Perfonn Activities of Daily Living (ADL) or Physical Functioning · PULSES Profile Index of ADL Kenney Self-Care Evaluation · Barthel Alex Rapid Disability Rating Scale (RDRS) · Barthe} Self-Care Ratings · Granger Range of Motion Scale · Kenney Self-Care Evaluation · PACE IT: Physical Function · OARS: Physical AILS · Functional Heals Status of He Institutionalized Eld- erly ADL`-A

ASSESSING QUALITY OF LIFE 87 Measures of Ability to Perform Ins~nental Activities of Daily Living (IADL3 . Punchonal Heady Status PGC ~s~umental Activities of Daily Living ~ument~ Role Maintenance Scale PAC:EB: lADEs OARS: Instruments ADL Functioning for Independent Living · Performance Activities of Daily Living (PADL) Pilot Gena~ic Arthritis Project Functional Status Measure (PGAP) Measures of Mental Functioning Measures of Cognitive Functioning Vigor, Intactness, Relationships, and Orientation (VIRO) Or~enmbon Scale Mental Status Questionnaire (MSQ) Short Portable Mental Status Questionnaire (SPMSQ) from OARS Philadelphia Gena~ic Center (PGC) Mental Status Questionnaire PGC Extended Mental Status Questionnaire Memory and ~fonnation Test ~) Dementia Rating Scale (DRS) Extended Scale for Dementia Face-Hands Test Visual Counting Test Set Test Misplaced Objects Test Wechsler Adult Intelligence Scale (WAIS) Short Fonn Wechsler Memory Test · Quick Test (QT) · Mini-Mental State Examination · Geriatric Interpersonal Evaluation Scale (GIES) Measures of Affective Functioning · Zung Self-Rating Depression Scale (SDS) · Beck Depression Index · Hopkins Symptom Checklist · Affect-Balance Scale Measures of General Mental Heals OARS Mental Health Screening

88 ]. I. WIMPS ED S. WOOD-DAUPH~= Screening Score Emotional Problems Questionnaire Savage-Bntten Alex Sandoz Clinical Assessment Genatrics London (Ontario) Psychogeriauic Rating Scale (LPRS) Gerontological Apperception Test (GAI) Senior Apperception Test (SAT) Genatric Mental State Examination · Psychological WeH-Being Interview · Nunes Observation Scale for Inpatient Evaluation POSIES Measures of Social Functioning Measures of Social Interactions and Resources . · Network Analysis Profile Social Networks Assessment Questionnaire · Role Actvin,r Scales Mutual Support Index Family Structure and Contact Battery (1968) Exchanges Between He Generations Index · Family Structure and Contact Battery (1972) Exchanges of Support and Assistance Index Hebrew Rehabilitation Center for He Aged (HRCA) Social Interaction Inventory Bennett Social Isolation Scales Family Adaptation, Partnership, Grown, Affection, Resolve (APGAR) OARS Social Resources Scale Social Dysfunction Rating Scale Social Behavior Assessment HRCA Reduced Actvides Inventory Activity Scale Unusual Day Future Activity Scores Measures of Subjective WeD-Being and Coping Cavan Attitude Inventory Kllmer Morale Scale Life Satisfaction Index OberIeder Attitude Scale Contentment Scale Tri-Scales

ASSESSING QUAL17Y OF LIFE PGC Morse Scale Geriatric Coping Schedule · Mode of Adaptations Patterns Scale · Genatr~c Scale of Recent Life Events Measures of Pemon-Environment Fit . 89 Importance, Locus, and Range of Ac~vides Check- list Locus of Desire Con=} Perceived Envirorunen~ Constraint Index Sadsfacdon wad Nuus~ng Home Scale Home for He Aged Description Questionnaire · Ward Atmosphere Scale · Commun~ty-Onented Programs Environment Scale (COPES) Sheltered Care Environment · Pemon-Environment Fit · Person-Environment Fit Scale Multidimensional Measures Sickness Impact Pro file (Sky Older Americans Research and Service (OARS) Center Instrument Comprehensive Assessment and Refed Evaluation (CARE) Patient Apprausal and Care Evaluation (PACE) · Stockton Geriatric Rating Scale · Plutchik Genatnc Rating Scale · Parachek Geriatric Rating Scale · Physical and Mental Impairment-of-Function Evalu- ation Scale (PAMIE) We also refer readers to the Clearinghouse on Heard Apexes of the Nationad Center for Heard Statistics of me U.S. Department of Heard and Herman Services. The Clearinghouse publishes a quarterly Bibliography on Health Iruiexes (editor, P. Enckson) Hat provides infom~adon on me reliability, validity, and sensitivity of various measures of heal status. TEN REVIEW FORMS FOR QUALITY-OF-LIFE MEASURES The review forms give, where available, the name of He measure, He auroras), primary referenceks), purpose, conceptual framework:, descrip- tion, reliability (including internal consistency, equivalence, stability,

go J. I. WII11AMS AND S. WOOD-DAUPHINEE inte~Tamr reliability, scaling, and scalability), validity (content, concur- rent, predictive, and construct), sensitivity, practicality, references, and applications (sometimes win descriptions). I. Review Form for Quality of Life Index and Quality of Life Uniscale Name of Measure: Quality of Life Index Spitter Quality of Life Un~sc~e~pit;zer Authors: Spitzer, W.O., Dobson, A.~., Hall, I., Chestennan, E., Levi, I., Shepherd, R., Bafflsta, R.N., and Catchiove, B.R. Primary References: Measunng me quality of life of cancer padents: A concise QL-index for use by physicians. Joumal of Chronic Diseases 34~12~:585-597, 1981. Mor, V. Cancer patients quality of life over the disease course: Lessons from me real wood. Journal of Chronic Diseases 40~61:535-544, 1987. Morns, I.N., Suissa, S., Sherwood, S., Wnght, S.M., and Greer, D. Last days: A study of the quality of life of terminally ill cancer patients. Journal of C hron~c Diseases 39~:47-62, 1986. Purpose: The Quality of Life Index (QLI) provides a measure to help physicians assess the relative benefits and risks of treatments for serious illness and of supportive programs such as palliative care or hospice service. Conceptual Framework: The QLl covers five dimensions: occupa- tional, household, or over principal activities; activities of daily living; health; support of family members or over significant persons; and out- look on life. It was designed to provide a global measure of these dimen- sions; it was not designed to be a measure of functions heady status. The QLl Upscale is a visual analogue scale on which me subject is asked to provide a global summary rating. The instruments are designed for use by patients, significant others, and amending heady professionals.

ASSESSING QUALITY OF I]FE 91 Reliability: Sternal consistency: 91 subjects in Australia, alpha = 0.76, Brown Cancer and Aging sway, alpha = 0.80, Brown Concrete Needs study, alpha = 0.77, diagonal Hospice study, alpha = 0.66. [nterrater: Speannan correlations of physicians' ratings were 0.84 English) and 0.74 (Francophone). Physician-patient correlations were 0.61 (Australia) and 0.69 (Canada). Scalability: Possible scores for each dimension are O (attribute in activity essentially absent), ~ Attribute or activity partially present), or 2 (attribute or activity fully present, normal). QLl scores range from O to 10. Anchonng adjectives are lowest quality and highest quality. The position of the mark on He line may be measured to He nearest millimeter or centimeter. Validity: Content: Content validity was based on a review of the literature and on information supplied by content panels of patients with venous dis- eases, Heir relatives, healthy persons, physicians, other health profession- als, arid clergy. Items were selected in a E-stage process; the final choices were based on methodological and content criteria Concurrent: In Australia, measures showed mean differences be- tween 84 healthy individuals in Sydney, 101 healthy individuals in Hunter Valley, 108 chronically ill patients, 105 cancer patients' and 78 senously iD patients In hospital. It also differentiated newly diagnosed cancer patients, (n = 397), recipients of chemotherapy (n = 194), and terminally id patients in He Brown studies. Scores are related to He of ~¢eannent in end-stage renal disease. Predictive: In the National Hospice Study, QLl scores declined over He last six weeks of He lives of patients. Construct: The QLl and QLl Uniscale have been related to the Karnofsky Index and measures of pain, depression, and nausea in the Brown studies. They have been compared with L~inear Analogue Self- Assessment MASAI measures in Australian Breast Cancer shoddies. QLl scores were compared with time ~ade-off utilities for end-s~ge renal disease patients by Churchill et al. (1987~. Sensitivity: QLl scores show detenoration over He last few weeks of the lives of padents in a hospice program. It has been used to demonstrate variable response to chemotherapy.

92 J. I. WIGWAMS AND S. WOOD-DAUPHINEE Practicality: The instrument is short easy to understand, and beef. The scores *om O ~ 10 have an intuitive appeal References and Applications: Churchill, D.N., Torrance, G.W., Taylor, D.W., Bames, C.C., L.udwin, D., Schimizu, A., and Smith, E.K. Measurement of quality of life In end-stage renal disease: The time tradeoff approach. CI=cal and Investigative Medicine 10~:14-20, 1987. Coates, A., Gebski, V., Bishop, I.F., Jeal, P.N., Woods, Rib., Snyder, R., Tattersall, M.H., Byme, M., Harvey, V., and Gill, G., for He Ausm- lian-New Zealand Breast Cancer Tnals Group, Clinical Oncology Society of Australia Improving the quality of life dllnng chemother- apy for advanced breast cancer. A comparison of intermittent and continuous treannent strategies. New England Joumal of Medicine 317(24):1490-1495, 1987. Three hundred and eight patients win advanced breast cancer were randomized to continuous or intermittent chemotherapy. Quality of life was measured win five LASA scores for physical well-being, mood, pain, nausea, vomiting, and appetite; He ELI Uniscale was completed by patients, and He QL~I by physicians. AU scores showed mat patients reported higher quality of life with continuous rawer Can intermittent therapy. This was con- sistent win me parents' clinical responses. Cough, I.R., Fu~val, C.M., Schilder, L`., and Grove, W. Assessment of me quality of life of patients win advanced cancer. European Journal of Cancer and Clinical Oncology 19~:~161-1165, 1983. One hundred patients completed 335 sets of LASA forms that included 21 LASA items; In addition the same 100 padents were rated on the QLl administered by a social worker, me QL`T com- pleted by patients, and a single wet/-being MASAI item. Investi- gators found mat He highest co'Telabons were between social workers' and patients, responses to the QLI. S~ngle-item weD- being was judged to be as useful as He 21-item foml. 2. Review Form for Life Situation Survey Name of Measure: Fife Situation Survey Author: Chubon, R.A.

ASSESSING QUAL17Y OF LIFE 93 Primary Reference: A quality of life rating scale. Evaluation and the Health Professions 10:186-200, 1987. Purpose: The Life Situation Survey is a subjective Vestment that can be used in a variety of populations, including patients in chronic care and rehabilitation programs. Conceptual Framework: Chubon is critical of quality-of-life measures that are disease-specific or focus on functional limitations. Chubon focuses on Me subjective aspect of life quality that may be more critical to understanding the impact of treatment. The Life Situation Survey in- eludes 20 statements; respondents indicate me degree to which they agree or disagree win the statements by checking six-point rating categones. A midpoint, We seventh category, was omitted and reserved for assignment of a score where no response was recorded. Half of the items are positively worded; the over half are negatively worded. Scores range from 20 to 140. Reliability: Stability: The test-retest reliability for 23 graduate students over one week was 0.91. Internal consistency: Cronbach's alpha for a variety of groups ranges from 0.74 to 0.95. The groups include prison inmates, hospital patients, Adversity students, mentally retarded individuals employed in work- shops, and spinal cord injury patients in rehabilitation. Scalability: The scores from the seven response categories are summed over me 20 items. Validity: Content: Items were developed by asking 168 persons with a variety of chronic and disabling conditions to indicate difficulties experienced as a result of this condition and actions that could be taken to improve the quality of Heir lives. The items were sorted into 17 categories Cough pilot tests. Twenty items for 10 categories were developed for me for. Concurrent: Chubon (1987) investigated the concurrent validity of the Life Situation Survey using seven groups. Chubon found that the means of inmate and patient groups were significantly different from He student group mean. Sample sizes, means, and standard deviations are displayed in Table 6-2.

94 J. I. WII HAMS AND S. WOOD-DAUPHINFF TABLE 6-2 Sample Sizes, Means, and Seward Deviations for Me Life Situation Survey Medium End-Stage Back Spinal Mentally Security Renal Disease Problem Injury Retarded Feature Students Inmates Patients Patients Patients Individuals - Sample size 50 44 27 22 16 30 Mean 107.3 743 83~2 81.1 87.9 102~3 Standard deviation 11.2 14.9 14.1 20.9 26A 13.8 Predictive: Mean scores and standard deviations forpre- and postu~at- ment groups for 37 of 55 persons who completed a 55-day program for chronic back pain were as follows: pre~eannent mean = 83 9? standard deviation= 13.3; posttreatment mean = 91.2, standard dev~abon = 18.4. Scores were higher for compliant than noncompliant patients. Practicality: The Life Situation Survey is short and easy to adrn~n~ster. References: Chubon, R.A. Quality of life measurement of persons with back prob- lems: Some preliminary findings. Journal of Applied Rehabilitation Counselling 16:31-34, 1985. Chubon, R.A. Quality of life and persons with end-stage renal disease. Dialysis and Transplantation 15:450 452, 1986. 3. Review Form for Quality of Life Index Name of Measure: Quality of Life Index (QLb Authors: PadiBa, G.V., Presant, C., Grant, M.M., Metter, G., Lipsett, I., and Heide, F. Primary Reference: Quality of life index for patients win cancer. Research in Nursing and Heals 6~3~:117-126, 1983.

ASSESSING QUALl7Y OF lIFE 95 Purpose: This instrument is used to measure ~e quality of life of cancer padents. Conceptual Framework: This instrument was derived from a measure ong~naDy proposed by Presant et al. (1981~. It is based on a defirudon of quality of life Mat includes performance, personal attitudes or affective states, well-being, and support. Description: The QLl contains 14 items organized into Tree groups: general physical condition, daily human activities, and personal attitudes. A self-a~nin~stered format is used. Reliability: Stability: Two samples of chemotherapy patients, one sample of radiation therapy patients, and one sample of nonpatients were use to assess test-retest reliability. The time span between administrations of the first and second measure vaned from 2 to 48 hours for ~e patients and several days for the nonpatients. For the patient samples, aD items had statistically significant coefficients (r > 0.60, p ~ 0.01~. For the nonpa- tients, the coefficients ranged from 0.~1 to 0.90. Internal consistency: Item analysis of We 14-item index across four samples yielded an alpha of 0.88. Scalability: Ten-cendmeter visual analogue scales are used. An overall score is obtained by summing the scores of me 14 items and dividing by 14. Subscale scores may also be calculated. Validity: Concurrent: Correlations between patient self-ratings, physician esti- mates of quality of life, and Karnofsky Index scores were in the low to moderate range for bow the subscales and We total scores across the three groups of patients. Construct: A principal component factor analysis provided three strong factors: psychological weld ng, physical wet/-being, and symp- tom control, plus a fours that relates to financial protection. Psycholog~- cal weB-being was the most important factor. The main factors co~Te- spond to the generally accepted definition of die components that com- pnse quality of life. Discrim~nant: Discr~m~nant validity was examined by comparing scores of the four groups 1lsing an analysis of variance. In teens of quality of life, a gradient was seen. Nonpatients demonstrated the highest scores,

96 J. I. WIGWAMS ANl) S. WOOD-DAUPHINEE followed by chemotherapy ou~adents9 radiotherapy patients, and chemo- therapy inpatients. Reference: Presant, C.A., Klahr, C., and Hogan, L. Evaluating quality~f-life in oncology padents: Pilot obsenrabons. Oncology Nursing Forum 8(3):26-30, 1981. 4. Review Form for the Quality of Life Ibex for Colostomy Patients Name of Measure: Quality of Life (QLD for colostomy patients Authors: PadiDa, G.V., and Grant, M.M. Primary Reference: Quality of life as a cancer nursing outcome variable. Advances in Nurs- ing Science 8~:45-60, 198S. Purpose: This ~ns~ument is used to assess Me quality of life of colos- tomy patients. Conceptual Framework: The QLl for patients win cancer (PadiBa et al., 1983) was modified for use as a disease-specific ~ns~ument for patients who had undergone colostomy. A multidimensional operational defection of quality of life was employed. Description: Ten items reflecting eating, pain, and sexual satisfaction, as well as interpersonal and body image aspects of self-worth were added to the ordeal 14 items of the QL`I. Descriptions of extreme subjective stances were used to anchor the 23 visual analogue scales. The instrument is self- a~nin~stered. Reliability: Sternal consistency: Scores from 135 patients who had colostomies for a variety of conditions (mostly colorectal cancer) were used to assess internal consistency. The alpha coefficients were as follows: psycholog~- cal well-being, alpha= 0.84; physical well-being, alpha = 0.87; body image, alpha = O.80; response to surgery, alpha = 0.71; nutritional re- sponse, alpha = 0.48; and social concerns, alpha = 0.90. Scalability: Scores fimm Me 23 visual analogue scales were summed and divided by 23. Subscale scores can be calculated.

ASSESSING QUALl7Y OF LIFE 97 Validity: Construct: Based on a factor analysis of He scores of 135 patients, six factors Disted under the section on internal consistency) were identified. To assess discnminant validity, mean scores of items common to bow this instrument and He QLl were calculated. Again, nonpadents had the highest scores and the declining gradient was as expected, with cancer inpatients scoring poorest. The colostomy patients had the second poorest scores. Reference: PadiBa, G.V., Present, C., Grant, M.M., Meyer, G., Lipsea, I., Heide, F. Quality of life index for patients win cancer. Research in Nursing and Heals 6(3):117-126, 1983. 5. Review Form for Quality of Life Index Name of Measure: Quality of Life Apex Authors: Ferrans, C.E., and Powers, M.~. Primary Reference: Quality of Life Index: Development and psychometric properties. Ad- vances in Nursing Science 8~1~:15-24, 1985. Purpose: The Quality of Life Index (QLI) is used to assess He quality of life of both hearty subjects and dialysis padents. Conceptual Framework: For this study, quality of life was defined as He sadsfachon of needs. The domains of quality of life as presented In the literature and He individuals' evaluation of satisfaction with each domain, as wed as its importance, were taken into account. Description: The Quality of Life Apex is compnsed of two sections, one dealing with He satisfaction of needs and He over with He importance of He various domains. Each contains 32 items Hat assess heath care, physical heal and functioning, marnage, family, friends, stress, standard of living, occupation, education, leisure, future retirement, peace of mind, personal faith, life goals, personal appearance, self-acceptance, general happiness, and general satisfaction. For use win dialysis patients, Here are also three items relating to treatment in each section.

98 J. 1. WIll~AMS AND S. WOOD-DAUPHINEE Reliability: Stability: Test-retest reliability within a two-week span for 69 gradu- ate students was 0.87. For 20 dialysis patients, web a one-month time span between me two tests, reliability was 0.81. Internal consistency: Analysis of graduate student scores gave an alpha coefficient of O.93. An alpha coefficient of 0.90 was obtained In the padents' scores. Scalability: Each item is accompanied by a six-point Likert scale ranging Tom "very satisfied', to "vex dissatisfied" in the satisfaction section and from `'veIy important" to `'very unimportant" in the impor- tance section. Scores are determined by adjusting satisfaction scores to incorporate importance. Specifically, satisfaction responses are recorded to make O the midpoint and Men multiplied by importance responses. Thus, We highest scores are for the items Mat have high satisfaction and high importance; me lowest are for low satisfaction and high importance. Adjusted scores for each item are summed to create subscale and total scores. Validity: Content: Items were based on a literature review of Me dimensions of quality of life as wed as on padent reports of how dialysis affected Me quality of their lives. Concurrent: The scores on me Quality of Life Index were correlated against an overall satisfaction win life measure (Campbell, 1976~. The correlation for graduate students was 0.75 and for dialysis patients, 0.65. Reference: Campbell, A., Converse, P.E., and Rodgers, W.~. The Quality of Amer~- can Life: Percep~dons, Evaluations and Satisfactions. New York, Russell Sage, 1976. 6. Review Form for Karnofsky Index of Performance Status (KPS) Name of Measure: Karnofsky Index of Performance Status (KPS) Authors: Kamofsky, D.A., and Burchemal, I.H. Primary Reference: The clinical evaluation of chemotherapeutic agents in cancer. In MacLeod, C.M., ed. Evaluation of Chemotherapeutic Agents in Cancer. New York, Columbia University Press, 191-205, 1949.

ASSESSING QUALI.IT OF LIFE 99 Purpose: The KPS is used to assess padents' overall ability to perfonn physical activities. Conceptual Framework: Pe~onnance status is measure by patients' ability to carry out normal activities independency or wad assistance. The presence of disease symptoms is also taken into account Perfo~m- ance is equated with quality of life. Description: The KPS is comprised of Tree general categones: self- care, general activities, and work. Within these categories, reflecting the level of care required, are ~ ~ specific criteria. Reliability: Stability: Fifty padents were rated by a social worker in Me clinic and again at home one week later. The two scores correlated sign~ficandy (Yates et al. 1980~. Interrater: Ratings by two independent physicians made the same day on emergency room patients and hemodialysis padents demonstrated problems in underrater agreement (Kappa = 50 percent and 29 percent, respectively) (Hutchinson et al. 1979~. Two ratings by nurses or social wooers of cancer patients made within one week of each other correlated moderately (0.69) (Yates et al. 1980~. Independent ratings by two students of 30 patients wad mixed diagno- ses correlated highly (0.86~. Information was obtained by chart reviews and patient interviews. Using 100 patients in a second study, Me correla- tions were higher (0.96) (Gr~eco and Long 1984~. Sets of physicians or mental health professionals assessed 75 cancer patients. Pearson correlations were 0.89 and Kappa statistics were 59 percent (Schag et al. 1984~. Forty-seven interviewers rated 17 narratives of patients' performance. Interrater reliability using Cronbach's coefficient alpha and the intraciass correlation coefficient gave values greater than 0.97 (Mor et at. 1984~. Scaling: The rank orders criteria are assigned scores from 100 down to O (100, 90, 80, etc.~. After the most appropriate criteria are selected, the patient is assigned a score. The instrument is generally used by a health professional, but patients can also rate themselves. Validity: Content: The process of content development was not wed descnbed by me original author. Gneco and Long (1984) revised me KPS by

100 I. I. WIMPS ED S. WOOD-DAUPH~EE providing more explicit descuphons of work, social interactions, and self- help skins. This new version combated highly with the ong~nal. Concurrent: Physician and self-assessment scores of functional ca- pacity (as defined in He KPS) were compared. Kappa scores ranged *om percent to 17 percent (Hutchinson et al. 1979~. The KPS correlated highly (0.84) with He Quality of WeD-Being Scale (Kaplan and Bush 1982) and moderately (0.68) win He self-report Health Perception Queshonna~re (Ware 1976, Gneco and Long 1984~. Predictive: In general terms, KPS scores are predictive of survival. Low scores are better predictors of early dead man are high scores of predicting longevity (Mor et al. 1984~. KPS scores are useful for predict- ing survival (Yates et al. 1980~. Construct: When KPS scores were correlate against single variables relating to physical functioning, psychological stems, and symptoms, Pearson correlations ranged from 0.09 to 0.63. AU but two of ten van- ables produced significant correlations (Yates et al. 1980~. KPS scores discriminated among five groups of patients representing different levels of functioning (GAeco and Long 1984~. KPS scores by physicians were correlated with ~ ~ variables assessing the type and severity of problems experienced by cancer patients. The correlations were significant but tended to be low (~0.51) (Schag et al. 19841. KPS scores correlated sign~ficandy with other functions measures. No significant relations were found, however, between KPS scores and me presence of symptoms or the extent of disease (Mor et al. 1984~. Sensitivity: KPS scores reflect a progressive detenoration of He physical condition of cancer padents within five months (especially the last two months) of death (Yates et al. 1980~. Practicality: The KPS takes only a few minutes to complete. References: Gneco, A., and Long, C.~. Investigation of He Karnofsky PerfoITnance Status as a measure of quality of life. Health Psychology 3~2~:129- 142, 1984. Hutchinson, T.A., Boyd, N.F., Feinstein, A.R., in collaboration with Gonda, A., Hollomby, D., and Rowat, B. Scientific problems In

ASSESSING QUALI~lY OF UFE 101 clinics scales, as demonstrated in He Ka~nofsky Index of Perfor- mance Status. Joumal of Chronic Diseases 32~9-10~:661-666, 1979. Kaplan, R.M., and Bush, J. Health-related quality of life measurement for evaluation research and policy analysis. Heals Psychology 1:61-80, 1982. Mor, V., Laliberte, L., Monis, J.N., and Wiemann, M. The Kamofsky Perfonnance Status Scale. An examination of its reliability and validity in a research serdng. Cancer S3~9~:2002-2007, 1984. Schag, C.C., Heinnch, R.L., and Ganz, P.A. Ka~nofsky performance status mv~simd: Reliability, validity, and Beelines. Journal of Clinical Oncology 2~3~:187-193, 1984. Ware, I.E., Jr. Scales for measuring general heady perceptions. Heady Services Research 1 ~ ~ 14) :3964 15, 1976. Yates, J.W., Chalmer, B., and McKegney, F.P. Evaluation of padents win advanced cancer using He Kamofsky perfonnance status. Can- cer45~8~:2220-2224, 1980. 7. Review for Functional Living Index~ancer Name of Measure: Functional Living Index—Cancer Authors: Schipper, H., Chinch, I., McMunay, A., and Levitt, M. Primary Reference: Measuring He quality of life of cancer padents: The Functional Living Index—Cancer: Development and validation loumad of Clinical Oncology 2~5~:472483, 1984. Purpose: The Functional Living Index—Cancer COLIC) is used to assess He overall funcdonal outcomes of cancer padents. The FLIC serves as an adjunct to traditional measures of Caracas assessment. Conceptual Framework: The investigators designed the instrument to get a global measure of quality of life. It includes psychosocial considera- tions, such as nausea and vomiting, which are at the interface of medico outcomes and psychosocial factors, as weD as other factors, such as freedom from pain, sociability, impact of illness, and satisfaction. It is cancer-specific, onented to daily living, and designed for self-adm~nistra-

102 J. I. WIlLIAMS AND S. WOOD-DAUPHINEE lion. The FLIC has 22 statements. Padents indicate how these statements apply to themselves on seYen-point Likert scales. Reliability: Internal consistency: The investigators developed the ~nstnunent over four testings In Winnipeg and Edmonton, Canada, using 837 patients over a ~ree-year period. Pnncipal factor analysis win an orthogonal varunax rotation was used to reduce We items and define Physical WeU- Being, an Ability Factor, and We Emotional Stam Factor. Scalability: Win seven-point scales for 22 items, We su~runary scores range from 22 to 154. Mean and standard deviations for summary and factor scores were not fourth. Validity: Content: A pane] of I} patients, relatives, physicians, nurses, and clergy generated a list of 250 items. The list was reduced to 92 items that were tested on 175 padents. Subsequent analysis of the questions reduced the number of statements to 20; in me last generation, items on nausea and recreational activity were added to bring the total to 22. Concurrent: The scores were compared across four groups of patients in Winnipeg and Edmonton, Canada: follow-up, adjuvant treatment, ac- tive treatment, and hospitalized, and a group of patients In extended care in Winrupeg. The average scores decreased with extent of disease from a high of Il6.6 to a low of 84.6. The overall analysis of variance was significant. A post hoc comparison of groups was not provided. Construct: The total score, Factor ~ (physical welD-being), and Factor 2 (psychologic scores) were correlated with the Katz Activities of Daily Living instrument, Goldberger's General Heady Queshonna~re win four subscales, the Beck Depression Inventory, Ka~nofsky Index, Speilberger State Treatment Anxiety Inventory, and Meizack Pain Inventory. AU instruments were tested in Winnipeg and Edmonton, except for Me Melzack Pain Inventory, which was tested only in Edmonton. Correlations were generally 0.50 or greater and in the predicted direction. Sensitivity: The investigators did not report the instrument to be respon- sive to significant clinical change. Schipper et al. found the items to be free of socially desirable responses when anadyzed win the Jackson Social Desirability Scale. Practicality: The FLIC is presented on tear sheets Cat Me patients can complete at home.and return according to a predetermined schedule. Response rates are reportedly high

ASSESSING QUALITY OF LIFE 103 References and Applications: Finkelstein, D.M., Cassile~, B.R., Bonomi, P.D.' Horton, I., Ezdinli, E.Z., Carbone, P.P., and Wolter, Id. A pilot study of me Functional Living Index—Cancer (E:LIC) Scale for me assessment of quality of life for metastadc lung cancer padents. American loumal of Coccal Oncology 2(6):630-633, 1988. Fifty padents enter the study and four were later removed. Forty- ~ee of the 46 patients admin~ste~d We initial FLIC completed at least 90 percent of We questions. Thirty-four of me 41 (83 percent) patients alive after one month completed the FLIC, but me comple- lion ram had dropped to 33 percent by six months. The investiga- tors found Hat in addition to He reduction In response due to morbidity and moronity, compliance is itself conelated wad qual- ity of life. They suggest cross-sectional comparisons of mean scores at each cycle rather man studying changes in the FLIC over time. They also suggest analyzing changes in reverse time—Blat is, looking at me scores for die periods preceding death. Ganz, P.A., Hasked, C.M., Figlin, R.A., La Soto, N., and Siau, I. Estimat- ing the quality of life in a clinical trial of patients win metastatic lung cancer using He Kamofsky performance status and He Functional Living~dex~ancer. Cancer61~4~:849-856,1988. The investigator used the Kamofsky Performance Stams and FLIC in a randomized trial of two programs for padents win advanced metas~tic non-small cell lung cancer. Forty-eight of 63 eligible patients participated in the Dial. The median survival was 16.9 weeks. A majority of patients had difficulty completing He FLIC; He investigators were unable to examine He effect of treatment on qua of life because of problems In He adm~s~tion of me form. 8. Review Form for Selby et ales Quality of Life Measure Name of Measure: Not named Authors: Selby, P.~., Chapman, J.A., Etazadi-Amoli, I., Dalley, D., and Boyd, N.F. Primary Reference: The development of a method for assessing He quality of life of cancer patients. British Joumal of Cancer 50~:13-22, 1984.

104 J. 1. WII~IAMS AND S. WOOD-DAUPlIINEE Purpose: This instrument is to be used to assess Me quality of life of patients win breast cancer. Conceptual Framework: One section of We ~nst~nent is based on me Sickness Impact Profile (SIP), a global measure of heal stems devel- oped by Bergner et al. (198 I). The over section reflects clinical problems specific ~ me disease. Description: The 12 categories of me SIP are each represented by one or more items for a total of 18 items. General areas included are work, home management, recreation, mobility, alertness, emotional behavior, eating, rest and sleep, social life, family relationships, body cane and movement, and communication. Twelve items mat reflect symptoms of me disease or of treatment are also included: pain, respiratory difficulty, sore mouth, nausea, vomiting, hair loss, attractiveness, appearance, dysuna, constipa- tion, diauThea, and fatigue. One item related to overall quality of life and one to satisfaction win life were also added, for a total of 32 items. The instrument can be self-adm~stered or it can be scored by a physician. Reliability: Stability: Ninety-six padents completed me index on me morning of a clinic visit and agate ne to twelve hours later. Generally, correlations were greater man 0.60, except for Nose dealing win nausea and vomit- ing. The investigators note that some patients received chemotherapy dunng me clinic visit. Internal consistency: Using me scores from 96 breast cancer patients, investigators reported an alpha of 0.71. Interrater: Self-assessments by 31 patients and ratings by physicians were correlated. Seventy-eight percent of the general items and 75 percent of the clinical items had a level of agreement greater than 0.60. An the study by Bell et al. (1985), all item scores by patients and their physicians correlated at least 0.5. Scalability: Eachitem is accompan~edby a Centimeter visual analogue scale anchored at each end by descriptive phrases. In the analyses, each item is treated independently. Item scores are not summed. Validity: Content: Two groups of patients uric breast cancer were interviewed using either an open-ended questionnaire or a structured questionnaire. The items were viewed as being bow relevant and important.

ASSESSING QUAl]IY OF LIFE 105 Additionally, when the repeated scores of 96 breast cancer padents on chemotherapy were enter into a regression analysis using Me item assessing the overall quality of life as We dependent van able and the other 31 items as the ~ndependentvar~ables, between 68 percent arid 83 percent of the variation In me global scale was explained. This information was seen as an indication of content validity. Construct: Using quality-of-life data from 96 patients, factor analysis determined five factors Mat made clinical and biological sense for breast cancer. When the items derived from me SIP categories were compared wad me linear analogue scores of me Sip, they correlated sign~ficandy and in me expected direction. Group scores of patients with different levels of clinical seventy differed sign~ficandy, demonstrating mat me ~ns~nent could disdnguish between groups of patients. Sensitivity: The instrument registered the ejects of chemotherapy when me treatment was started. BeD et al. (1985) reported Rat the measure was able to discriminate between high and low doses of chemotherapy. Data from an independent observer were more precise man data from We pa- dents. Practicality: Padents report the instrument to be quick, easy, and accept- able. References and Applications: Bed, D.R., Tannock, I.F., and Boyd, N.F. Quadity of life measurement in breast cancer patients. Bndsh loun~al of Cancer 51~4~:577-580, 1985. Twenty-five breast cancer padents participating in a randomized controlled Dial of chemotherapy were assessed 3 weeks after che- mo~erapy started (just prior to me next dose) and 24 hours later. Scores were obtained from padents and physicians. Bergner, M., Bobbit, R.A., Carter, W.B., and Gilson, B.S. The Sickness em pact Profile: Development and final revision of a heal status measure. Medical Care 19~:787-805, 1981. 9. Review Form for Linear Analogue Self-Assessment Name of Measure: Linear Analogue Self-Assessment (LASA)

106 Authors: Banm, M., and Priesunan, T.~. J. 1. WIGWAMS AND S. WOOD-DAUPHINEE Primary References: Baum, M., Priesunan, T.~., West, R.R., and [ones, E.M. A comparison of subjective responses In a trial comparing endocnne with cytotoxic treatment in the advanced carcinoma of Me breast. European Joumal of Clinical Oncology (Supplement) 1:223-226, 1980. Priesunan, Ad., and Baum, M. Evaluation of quality of life in padents receiving treatment for advanced breast cancer. Lancet 1~7965~:899- 900, 1976. Purpose: The LASA is used to achieve a more complete picture of patients' subjective responses ~ treatment. Conceptual Framework: The developers vary In me number of items Mat are used in me subjective ratings. For each variable, patients mark a 10-cendmeter line that is anchored at each end win words describing the extremes of Mat symptom. These include: Symptoms and side effects: alopecia, anorexia, appetite, constipa- tion, diarrhea, dyspnea, fatigue, nausea, pain, vomiting, and "other." Anxiety and depression: apprehension, depression, insomnia, irnta- biIity, level of anxiety, mood, and weD-being. Personal relations: decisionmaking, getting along win partners arid others, sexual relationships, and social relationships. Physical performance: ability to perfonn daily activities, employ- ment, level of activist, and social activities. Reliability: Stability: Twenty-nine breast cancer patients completed forms with 10 items. These fonns were completed again 24 hours later at home. The correlation between sums of scores was 0.87. Scalability: Scores are summed across items; means and standard deviations are reported. The LASA was designed for repeated testing (weekly) over the course of treatment Validity: Concurrent: One hundred women with advanced breast cancer were randomly allocated to endocnne or combination cymtoxic therapy. N~nety- two were available for assessment; 51 completed the LANA. Fourteen of Me 25 women in Me endocrine group completed Me LASA for six weeks.

ASSESSING QUALITY OF LIFE 107 Women In Me cytotox~c group had higher symptom-related scores and higher quality-of-life scores man women in me endocnne group. WeD- being differences reached significance after ~ ~ weeks. Predictive: Nonresponsive patients showed worse depression scores man women responding to t;reannent. Sensitivity: Changes in weekly scores indicate mat me LASA scores reflect clinical changes. Practicality: Generally, patients were able to complete me LASA homes without difficulty. NamraBy, for patients with advanced cancers, Were were marked patient attrition rates caused by deem or Habit to respond. References and Applications: Coates, A., DiDenbeck, C.F., McNeil, D.R, Kaye, S.B., Sims, K., Fox, R.M., Woods, Ah., Milton, G.W., Solomon, I., and TattersaD, M.H. On me receiving end IT. Linear Analogue Self Assessment MASAI in He evaluation of aspects of me quality of life of cancer patients receiving therapy. European Joumal of Cancer and Clinical Oncol- ogy 19~:1633-1637, 1983. One hundred and ten patients (30 with melanoma, 41 with lung cancer, 39 win ovarian cancer) completed 506 LASA fonns. The results were compared with performance states as measure by He Eastem Cooperative Oncology Group (ECOG) and response to therapy. LISA fonns included items for global well-being (for example, wet/-being, mood, appetite) and disease-specific conditions (such as, pain, nausea, vomiting). Bow ECOG scores arid the I,ASA scores for general well-being showed parallel and marked deterioration during He penod of radiotherapy with sub- sequent improvement. Coates, A., Gebski, V., Bishop, I.F., leal, P.N., Woods, Ah., Snyder, R., TattersaB, M.H., Byme, M., Harvey, V., and GiU, G., for He Austra- lian-New Zealand Breast Cancer Tnals Group, Clinical Oncology Society of Australia. Improving He quality of life dunng chemo~er- apy for advanced breast cancer. A comparison of intermittent and continuous treatment strategies. New England Joumal of Medicine 317(24):149~1495, 1987. Gough, I.R., Fum~val, C.M., Schilder, L., and Grove, W. Assessment of me quality of life of patients win advanced cancer. European loumal of Cancer and CI~rucal Oncology 19~:1161-1165, 1983.

108 J. 1. WIlLlAMS AlID 5. WOOD-DAUPHINEE Lanham, R.J., and DiGiannanton~o, A.F. Quality~f-life of cancer pa- tients. Oncology 45(1):1-7, 1988. A linear analogue scale consisting of 10 items, including feeling of well-being, mood, level of physical activity, pain, nausea, appetite, ability to perform work, social activities, level of anxi- ety, and whether treatment is helping, was a~nin~stered to 98 cancer patients over 293 office visits and 137 family practice padents over 137 visits. The differences in mean scores, 6.09 for Me cancer patients and 6.67 for me healthy patients, were statisd- cally significant, but Me investigators expected Me differences to be larger. The group differences for men were statistically sig- rnficant, but Me differences for women were not. Male cancer patients had sign~ficandy lower scores than female cancer pa- tients. The investigators identified work, physical activity, and socialization as special needs for men that should be addressed. Raghavan, D., Gnm~y, R., and Lancaster, L`. Assessment of quality of life in long-tem~ survivors treated by first-line intravenous cisplatin for invasive bladder cancer. Progress in Clinical and Biological Research 260:625-63 1, 1988. Questionnaires were sent to 29 patients by mail. In addition to the LASA, Me investigators included mul~ple-choice questions on physical well-being, symptoms of Me disease, side effects of treatment, functional status, sexual function, social interaction, satisfaction win treatment, and overall quality of life. Although Me patients answered the multiple-choice questions readily, half of them were unable to use Me LASA scales correctly. The highest nonresponse rate was on Me LISA items related to sexual fimction. 10. Review Form for Breast Cancer Chemotherapy Questionnaire Name of Measure: Breast Cancer Chemotherapy Questionnaire (BCQ) Authors: Levme, M.N., Guyatt, G.H., Gent, M., De Pauw, S., Goodyear, M.D., H~niuk, W.M., Arnold, A., Flndlay, B., Skillings, J.R., Bramwell, V.H., et al. Primary Reference: Quality of life in stage I! breast cancer: An instrument for clinical teals. Joumal of Clinical Oncology 6~12~:1798-~10, 1988.

ASSESSING QUALITY OF l]FE 109 Purpose: In planning their study, Me investigators decided Deco develop a new quesdonna~re to-measure the impact of adjuvant chemotherapy on physical, emotional, and social function of women wad stage ~ breast cancer. Conceptual Framework: The investigators reviewed We available meas- ures of quality of life for cancer patients' but these did not focus on me specific problems of women wad advanced breast cancer faced wad receiving adjuvant therapy. Their god was ~ develop a measure specific to me type of patient and me type of therapy. The items had to tap areas of physical, emotional, and social well-being that were important to me patient, quantifiable, valid, reproducible, responsive, simple, and conven- lent to use. The items were generated Trough a literature review and discussions wad medical oncolog~s~ts, oncology nurses, and stage ~ breast cancer padents. The original 150 items were pamd to 99, and 47 patients receiving adjuv ant chemotherapy were asked to rate me importance of these items on five-point Liken scales. The investigators grouped me items into me areas of consequences of hair loss, emotional dysfunction, physical symptoms, trouble and inconvenience associated USA treatment, fatigue, nausea, and positive weB-being. They furler decided Tat each area Could have a minimum of four items. The final 30 items were selected, by area, in teems of me highest mean ratings of importance. The women responded to items about how Hey had felt during He past two weeks on a sevens nt scale. Reliability: Stability: At each visit, He women were asked if their condition had changed dunng He past two weeks. On the first occasion that no change was reported, me investigators compared the current and last scores on me quality-of-life measures. The mean change scores and standard devia- tions were deemed stable and reliable, but they were not statishcaBy assessed. Scalability: The responses for each item had a score from ~ to 7, and He scores were summed across He 30 items. This score was later sfonned so Hat it ranged from 0 to 10. Validity: Content: The methods used for generating and selecting items assured the face and content validity of He items.

110 J. I. WI1MAJ`S AND 5. WOOD-DAUPHINEE Construct: The first step was to average Me scores for aB visits for each patient The mean BCQ scores were correlated wad the average SCORES for prudent and physician global Wings and We Kamofsky, RAND emotional, RAND physical, and Spider quality-of-life measures. The correlations ranged from 0.41 to 0.62. An analysis of change scores for a single two-week period showed Nat We global physical and emotional assessments by me patients were more spongy correlated wad the qual- ity-of-life ratings than We global assessments by the physicians. Sensitivity: The women in We two Eminent groups had me same therapy during the first 12 weeks, and We mean scores for women in the two groups were equivalent. For one group the treatment continued for 36 weeks and We other group stopped treannent after 12 weeks. The BCQ and Ka~nofsky scores were significantly lower for We short-te~m group man the Midweek group between weeks 12 and 36. The RAND and Spitzer scores did not vary si~ficandy dunng this period. The scores converged again after 36 weeks, when aB women were off therapy. Practicality: The lime, 30 minutes an interview, and costs of having me forms a~nin~stered by a nursefinterviewer were considerable. The ~nves- tigators have recommended that a self-a~n~rustered version of the ques- tionna~re be tested. Application: In He trial, 418 women were assigned to either 12 weeks or 36 weeks of adjuvant therapy. A nursep~nterviewer administered me BCQ, He RAND Physical Health and Mental Heady Status queshon- natures, and the Spitzer Quality of Life Index. The physician completed the Kamofsky Index. Global ratings of physical and emotional function- ing were provided independency by the physician and He patients. The measures were completed at He beginning and me follow-up visits over a period of 80 weeks. The women stopped completing the measures when there was a recurrence of disease or they refused trea~nent. The patients averaged lO visits and completed approximately 85 percent of the poten- hal assessments. REFERENCES Anderson, J.P., Bush, J.W., and BeIry, C.C. Edemas consistency analy- sis: A method for studying He accuracy of function assessment for health outcome and quality of life evaluation. Joumal of Clinical Epidemiology 41(2):127-137, 1988.

ASSESSING QUALITY OF LIFE 111 Andrews, F.M., and Witney, S.B. Social Indicators of WeB-Being: American Perspectives of Life Quality. New York, Plenum, 1976. Baum, M., PIiestman, T.~., West, R.R., and [ones, E.M. A compan son of subjective responses in a Dial comparing endocrine win cytotoxic treatment in Me advanced carcinoma of Me bmasL European Journal of Clinics Oncology (Supplement) 1:223-226, 1980. Bell, D.R., Tarmock, I.F., and Boyd, N.F. Quality of life measurement in breast cancer padents. British Journal of Cancer 51(4):577-580, 1985. Bergner, M., Bobbit, R.A., Carter, W.B., and Gilson, B.S. The Sickness Impact Profile: Development and final revision of a heath stems measure. Medical Care 19~8~:787-80S, 1981. Bohrnstedt, G.W. Measurement In Rossi, P.H., Wright, I.D., and Ander- son, A.B., eds. Handbook of Survey Research. New York' Academic Press, 1981. Campbell, A. The Sense of WeD-Being In America: Recent Pattems and Trends. New York, McGraw-HiL, 1980. Campbell, A., Converse, P.E., and Rodgers, W.~. The Quality of Ameri- can Life: Perceptions, Evaluations and Sadsfaccions. New York, RusseB Sage, 1976. Chubon, R.A. Qualitr of life measurement of persons with back prob- lems: Some preliminary findings. loumal of Applied Rehabilitation Counsehing 16:31-34, 1985. Chubon, R.A. Quality of life and persons win end-stage renal disease. Dialysis and Transplantation 15:45~452, 1986. Chubon, R.A. A quality of life racing scale. Evaluation and the Heath Professions 10:~86-200, 1987. Churchill, D.N., Torrance, G.W., Taylor, D.W., Bames, C.C., Ludwin, D., Shimizu, A., and Smith, E.K. Measurement of quality of life In end-stage renal disease: The time ~crade-off approach. Clinical and Investigative Medicine 10~1~:14-20, 1987. Coates, A., Dillenbeck, C.F., McNeil, D.R., Kaye, S.B., Sims, K., Fox, R.M., Woods, R.~., Milton, G.W., Solomon, ]., arid Tattersall, M.H. On the receiving end—II. Linear Analogue Self Assessment ROSA) in the evaluation of aspects of He quality of life of cancer padents receiving therapy. European Journal of Cancer arid Clinical Oncol- ogy 19~11~:1633-1637, 1983. Coates, A., Gebski, V., Bishop, Id., Jeal, PA., Woods, R.L"., Snyder, R., Tattersall, M.H., Byme, M., HaIvey, V., and Gill, G., for He Austra- lian-New Zealand Breast Cancer Tnals Group, Clinical Oncology Society of Australia Improving the quality of life during chemo~er- apy for advanced breast cancer. A comparison of intermittent md

112 J. 1. WII1"IAMS AND S. WOOD-DAUPHINEE continuous treatment strategies. New England Joumal of Medicine 317(24):1490-1495, 1987. Cronbach, L.~. Coefficient alpha and me intemal structure of tests. Psychometrika 22:293-296, 1951. Croog, S.H., Levine, S., Testa, M.A., Brown, B., Bulpitt, Cal., Jenkins, C.D., Klerman, G.~., and Williams, G.H. The effects of andhy- per~nsive therapy on Me quality of life. New England Journal of Medicine 314(26):1657-1664, 1986. Drummond, M.F., Stoddart, G.~., md Torrance, G.W. Me~ods for Me Economic Evaluation of Health Care Programmes. London, Oxford University Press, 1986. Erickson, P., ed. Bibliography on Health Indexes, Clearinghouse on Health Indexes, National Center for Heath Statistics, HyattsvilBe, Maryland. Feinstein, A.R. ClinImetrics. New Haven, Yale University Press, 1987. Ferns, C.E., and Powers, My. Quality of Life Apex: Development and psychometric properties. Advances in Nursing Science 8~:~-24, 1985. Finkelstein, D.M., Cassileth, B.R., Bonomi, P.D., Horton, I., Ez~inli, E.Z., Carbone, P.P., and Wolter, I.N. A pilot study of the Functional Living Index—Cancer (E;LIC) Scale for the assessment of quality of life for metastatic lung cancer patients. American loum~ of Clinical Oncology 2~6~:630-633, 1988. FIeiss, J.~. Stadshcal Me~ods for Rates and Proportions. 2nd ed. New York, John Wiley & Sons, 1981. FIeiss, Ids. The Design and Analysis of Clinical Experiments. New York, John Wiley & Sons, 1986. Fletcher, R.H., Fletcher, S.W., and Wagner, E.H. Clinical Epidemiology: The Essentials. 2nd ed. Baltimore, Williams and Wilkins, 1988. Ganz, P.A., HaskeH, C.M., Figlin, R.A., La Soto, N., and Siau, I. Estimat- ing the quality of life in a clinical trial of patients with metastatic lung cancer using He Ka~nofsky performance status and He Functional Living Index—Cancer. Cancer 61~4~:849-856, 1988. Cough, I.R., Funeral, C.M., Schilder, L., and Grove, W. Assessment of the quality of life of patients win advanced cancer. European Joumal of Cancer and CI~n~cal Oncology 19~:~161-~165, 1983. Grieco, A., and Long, C.J. Investigation of He Kamofsky Performance Status as a measure of quality of life. Health Psychology 3(2):129- 142, 1984. Holloway, C.A. Decision Making Under Uncertainty: Models and Choices. Englewood Cliffs, New Jersey, Prentice-Hall, Inc., 1979.

ASSESSING QUAld7Y OF llFE 113 Hutchinson, T.A., Boyd, N.F., Weinstein, A.R, in collaboration win Gonda, A., Hollomby, D., and Rowat B. Scientific problems in clinical scales, as demons~ed In He Karnofsky Index of Perfor- mance Stams. loumal of Chronic Diseases 32~9-10~:661-666, 1979. Kane, R.A., and Kane, Rip. Assessing He Elderly: A Practical Guide to Measurement. Lexington, Massachusetts, D.C. Heap and Company, 1981. Kaplan, R.M., and Bush, I.W. Heal~-related quality of life measurement for evaluation research and policy analysis. Heals Psychology 1:61- 80, 1982. Kaplan, R.M., Adcins, C.J.' and T~mms, R. Validity of a quality of well- being scale as an outcome measure In chronic obst~uc~ve pulmonary disease. Joumal of Chronic Diseases 37~2~:85-95, 1984. Karnofsky, D.A., and Burchem~, I.H. The clinical evaluation of che- motherapeutic agents in cancer. In MacLeod, C.M., ed. Evaluation of Chemotherapeutic Agents in Cancer. New York, Columbia Un~- versityPress, 191-205, 1949. Kerlinger, F.N. Foundations of Behavioral Research. 3rd ed. New York, Holt, Rinehart, and Winston, 1986. Lanham, R.~., and DiGiannanton~o, A.F. Quality-of-life of cancer pa- tients. Oncology 45~11:~-7, 1988. Last, J.M. ed. Dictionary of Epidemiology. 2nd ed. New York, Oxford University Press, 1988. Levine, M.N., Guyatt, G.H., Gent, M., De Pauw, S., Goodyear, M.D., H~yniuk, W.M., Arnold, A., Findlay, B., Skillings, I.R., Bramwell, V.H., et al. Quality of life in stage II breast cancer. An instrument for clinical trials. loumal of Clinical Oncology 6~12~:1798-1810, 1988. McDowell, I., and NeweE, C. Measunng Heals: A Guide to Rating Scales and Questionnaires. New York, Oxford University Press, Inc., 1987. Mor, V. Cancer patients quality of life over He disease course: Lessons from He real world. Joumal of Ch~n~c Diseases 40~6~:S35-544, 1987. Mor, V., Laliberte, L., Moms, ].N., and Wiemann, M. The Kamofsky Performance Status Scale. An examination of its reliability and validity in a research setting. Cancer53~9~:2002-2007, 1984. Morris, J.N., Suissa, S., Sherwood, S., Wright S.M., and Greer, D. Least days: A study of me quality of life of terminally ill cancer patients. loumal of Chronic Diseases 39~:47-62, 1986. NunnaBy, J.C. Psychometric Theo~. 2nd ed. New York, McGraw-Hi0, 1978.

114 ]. I. ARMS AD S. WOOD-DAUPHINEE PadiDa, G.V., and Grant, M.M.. Quality of life as a cancer nursing out- come variable. Advances In Nursing Science 8~11:45-60, 1985. PadiDa, G.V., Presant, C., Grant, M.M., Metter, G., Lipsett, I., and Heide, F. Quality of life index for patients win cancer. Research in Nursing and Heady 6(3):117-126, 1983. Presant, C.A., Klahr, C., and Hogan, L. Evaluating quality-of-life in oncology patients: Pilot observations. Oncology Nursing Forum 8(3):26-30, 1981. Priesunan, At., and Ballm, M. Evaluation of quality of life in patients receiving treatment for advanced breast cancer. Lancer 1(7965):899- 900, 1976. Raghavan, D., Grundy, R., and Lancaster, L. Assessment of quality of life in long-term survivors treated by first-line intravenous cispladn for invasive bladder cancer. Progress in Clinical and Biological Research 260:625-63 1, 1988. Schag, C.C., Heinnch, R.L., and Ganz, P.A. Kan~ofsly performance status revisited: Reliability, validity, and guidelines. Journal of Clinical Oncology 2~3~:~87-193, 1984. Schipper, H., Clinch, I., McMurray, A., and Levitt, M. Measuling the quality of life of cancer patients: The Functional Living Index Cancer: Development and validation. Journal of Clinical Oncology 2~5~:472483, 1984. Schuessler, K.F., and Fisher, G.A. Quality of life research and sociology. Annual Review of Sociology 11: 129-149, 1985. Selby, P.J., Chapman, J.A., Et~adi-Amoli, J., Dalley, D., and Boyd, N.F. The development of a method for assessing the quality of life of cancer patients. BntishioumalofCancerS0~:13-22, 1984. Smith, G.T., ed. Measunng Heady: Practical Approach. New York, John Wiley & Sons, 1988. Spitzer, W.O. State of science 1986: Quality of life and functional status as target vanables for research. Journal of Chronic Diseases 40~6~:465- 471, 1987. Spitzer, W.O., Dobson, A.J., Hall, J. Chestemlan, E., Levi, J., Shepherd, R., Banista, R.N., and Catchlove, B.R. Measunng the quality of life of cancer padents. A concise QL-index for use by physicians. Jour- nal of Chronic Diseases 34~12~:585-597, 1981. Torrance, G.W. Measurement of heath state utilities for economic am praisal: A review. Joumal of Health Economics 3:1-30, 1986. Torrance, G.W. Utility approach to measuring heal~-related quality of life. Journal of Chronic Diseases 40(6):593-603, 1987.

ASSESSING QUAL177' OF L]FE 115 Torrance, G.W., Thomas, W.H., and Sackett, D.~. A utility max~mizabon mode] for the evaluation of heady care programs. Heady Services Research 7~2~:~-133, 1972. Torrance, G.W., Boyle, M.H., and Horwood, S.P. Application of multiat- tnbute utility theory to measure social preferences for heady states. Operations Research 30:1043-1069, 1982. van Neumann, I., and Morgenstem, O. Theory of Games and Economic Behavior. 3rd ed. New York, John Wiley ~ Sons, 1953. Ware, JE., Ir. Standards for validating health measures: Definition and content. Journal of Chronic Diseases 40~6~:473480, 1987. Ware, lE., Ir. Scales for measuring general heady perceptions. Heath Services Research I1~14~:396415, 1976. We~nste~n, M.C. Economic assessments of medical practices and tech- nolog~es. Medical Decision Making 1:309-330, 1983. Wenger, N.K., Mauson, M.E., Furberg, C.D., and Elinson, I., eds. Assess- ment of Quality of Life in CI~n~cal Trials of Cardiovascular Thera- pies. New York, Le lacq Publishing, Inc., 1984. Yates, J.W., Chalmer, B., and McKegney, F.P. Evaluation of patients win advanced cancer using the Kamof~y perfonnance status. Can- cer45~:222~2224, 1980. ZeBer, R.A., and Carmines, E.G. Measurement in He Social Sciences. London, Cambridge University Press, 1980.

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The field of health care technology assessment focuses on the use of medical technologies—their impacts on safety, efficacy, and effectiveness; cost-effectiveness and cost benefit; quality; and their social, legal, and ethical implications. This wide-ranging monograph addresses some of the gaps in understanding health status and quality of life, such as the use of quality-of-life measures in technology assessment, organ transplantation, and pharmaceutical trials. One chapter provides basic references for the technical attributes of many established measures and some lesser known ones. The final chapter offers recommendations concerning the appropriate applications of these measures and highlights areas for cooperative research.

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