(Stroke. 2000;31:2004.)
© 2000 American Heart Association, Inc.
Comments, Opinions, and Reviews |
Evaluation of Measures Used to Assess Quality of Life After Stroke
From the Department of Primary Care, University of Liverpool, Liverpool, UK.
Correspondence to Ms Deborah Buck, Research Associate, Department of Primary Care, University of Liverpool, The Whelan Building (2nd Floor), Brownlow Hill, Liverpool L69 3GB, UK. E-mail dbuck{at}liverpool.ac.uk
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Abstract |
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Background and Purpose—Assessment of quality of life (QOL) after stroke is becoming common with the recognition that evaluation of treatment should include quality as well as quantity of survival. This article will outline the main conceptual and methodological issues in QOL assessment, highlight advantages and disadvantages of measures used in stroke QOL research, and discuss some unresolved issues.
Summary of Review—We undertook a MEDLINE search using the keywords "stroke" and "quality of life" and reviewed 3 key texts on QOL measurement in stroke. Fifteen generic and 10 condition-specific measures used to assess QOL in stroke were identified and evaluated with the following criteria: reliability, validity, responsiveness, precision, acceptability, suitability for proxy respondents, mode of administration, and use of patient-centered approaches in development. Domains covered and level of comprehensiveness varied widely between generic and stroke-specific measures. No stroke-specific instruments used patient-centered approaches in their development. Four stroke-specific measures (Frenchay Activities Index, Niemi QOL scale, Ferrans and Powers QOL Index–Stroke Version, and Stroke-Adapted Sickness Impact Profile [SA-SIP30]) provided evidence of reliability and validity.
Conclusions—The need remains for a patient-centered, psychometrically robust, stroke-specific QOL measure. Patients should be involved in each stage of instrument development. Caution is needed in the selection of an instrument to measure QOL after stroke. Although the Ferrans and Powers QOL Index–Stroke Version, Niemi QOL scale, SA-SIP30, and Sickness Impact Profile come closest to satisfying many of the criteria outlined in this article, the selection of any individual instrument depends on the specific goals and constraints of a particular study.
Key Words: England • psychometrics • quality of life • stroke outcome
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Introduction |
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Assessment of quality of life (QOL) in stroke is becoming increasingly common. In this article, we evaluate outcome measures that have been used in stroke QOL research, updating a review by de Haan and colleagues in 1993.1 This takes into account further developments in the area and the increasing need in pharmacological intervention studies for a robust QOL measure. We discuss factors to be considered when QOL measures for stroke are selected on the basis of these evaluations, highlighting some important unresolved issues. We begin with a summary of some of the main conceptual and methodological issues in QOL assessment.
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Conceptual Issues in QOL |
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Impairment, Disability, Handicap, and QOL
The International Classification of Impairments, Disabilities and Handicaps (ICIDH) was published in 1980.2 It illustrates how disease can engender impairment, defined as a loss or abnormality of psychological, physiological, or anatomic structure or function. Impairment in turn may lead to disability, defined as a restriction or inability to perform an activity in a way considered normal for a human being. Handicap may arise either directly owing to impairments or because of disability after interaction with the physical or social environment. Handicap is defined as a disadvantage that restricts or prevents the performance of a role deemed normal.
QOL is said to lie beyond the disease-handicap continuum.3 Although the ICIDH offers an important theoretical perspective, it neglects wider QOL issues. Although handicap is the most relevant clinical outcome for patients and impairment the least relevant, QOL may be even more pertinent from the patient’s point of view.4
Definitions of QOL
Consensus about the definition of QOL has yet to be reached, but
most researchers believe it is multidimensional,5 6 7
comprising 3 broad "domains": physical, mental, and social. QOL has
recently been defined by the World Health Organization Quality of Life
(WHOQOL) Group as "individuals’ perceptions of their position in
life in the context of the culture and value systems in which they live
and in relation to their goals, expectations, standards and
concerns."8
The Importance of Measuring QOL
There is general agreement that the effects of treatment should be
measured in terms of quality as well as quantity of
survival.9 Medical advances may prolong life, but it is
important to know the nature of that further life.10
Without an assessment of QOL, a treatment may be deemed successful
despite poor psychosocial functioning or adjustment to illness. For
instance, stroke patients who are fully independent according to
Barthel Index scores may nevertheless experience limitations in areas
such as employment and leisure activities or in emotional
adjustment.11 Alternatively, a treatment beneficial to
psychosocial status may be rejected because it fails to improve
physical functioning. Medical interventions may be beneficial to
patients on impairment or disability measures, but without equally
refined QOL measurements, a clear and comprehensive evaluation of their
efficacy is not possible.9 The recent development of
thrombolytic and neuroprotective therapies has
highlighted the urgent need for improved outcome measures for stroke,
including QOL measures.
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Methodological Challenges to Assessing QOL |
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A recent UK National Health Service (NHS) Research and Development Health Technology Assessment (HTA) recommends that a number of criteria should be considered when outcome measures are chosen.12 These criteria are reliability, validity, responsiveness to change over time, precision, appropriateness, and acceptability.
Reliability and Validity
Evidence of reliability and validity is vital for QOL measures, as
with any outcome measures, to ensure confidence in their scientific
robustness.13 Reliability is the extent to which
measurements for the same individual on separate occasions or by
different observers produce similar results.14 Validity is
the extent to which an instrument measures what it is meant to measure.
One of the most meaningful indications of validity is the extent to
which the relevant patient group was involved in generating the content
of a measure.12 Thus, the determination of crucial domains
for specific conditions should be through patient-centered
methods.12 For stroke, Duncan and
colleagues15 in the United States recently found that 8
key areas (strength, hand function, activities of daily living,
mobility, communication, memory, emotion, and social participation)
emerged as the key areas from the patient’s perspective. Similarly,
Williams et al16 reported that patients identified 12 key
domains (mobility, energy, upper-extremity function,
work/productivity, mood, self-care, social roles, family roles,
vision, language, thinking, and personality).
Responsiveness of a Measure
Depending on the requirement of the study, a responsive QOL
measure may be needed. Such a measure will be able to detect even small
differences within an individual over time.17 Use of
unresponsive measures in intervention studies (for example, those
concerned with within-patient differences over time) would fail to
detect whether such changes had occurred, thus resulting in misleading
findings.
Precision
Precision is concerned with the number and accuracy of
distinctions made by a measure, that is, precision of response
categories or of numerical values.12 Also important to
precision is the capacity of a measure to report the most favorable or
poorest health states (in other words, the extent of floor and ceiling
effects).
Appropriateness
In the evaluation of outcome measures for use in clinical trials,
the HTA report emphasizes that any measure used should match the
specific purpose and questions of the trial.12 Similarly,
the content of a measure used to assess QOL in stroke should reflect
the aims of the study and consider the nature of the patient group.
Acceptability
Acceptability and average completion times need to be considered
in any outcome measure9 but especially for use in stroke
given the potential cognitive problems and feelings of tiredness that
may be experienced after stroke.1 Previous response rates
(to the measure overall and to individual items) should also be
examined. However, acceptability of a measure is best determined by
pretesting with patients in terms of wording, response options, and
general layout.12
In addition to the above criteria recommended in the HTA report, a number of other issues of particular relevance to stroke populations should be addressed: suitability of a measure for use with proxy respondents, intended mode of administration of the measure, and whether the measure is generic or stroke specific.
Proxy Respondents
Use of proxies (asking a relative or close friend to answer
questions as he or she believes the patient would) is important given
the difficulties that some people with stroke may have in communicating
or understanding research questions.18 19 20 The use of
proxies where necessary may be preferable to excluding more severe
cases from trials,20 particularly because such individuals
are likely to have a markedly reduced QOL.
Mode of Administration: Self- Versus Interviewer-Administered
Self-administered measures tend to be less resource intensive than
interviewer-administered measures. However, physical difficulties that
limit ability to complete a questionnaire or cognitive or linguistic
problems that affect concentration or understanding may render
self-completion an arduous if not impossible task for some
people.18 19 20 Interviewer-administered questionnaires may
also be problematic to apply, because some stroke patients
will be unable to respond in an interview setting owing to speech
problems. Thus, given the range of impairments often experienced after
stroke, it is important to establish whether a QOL measure can be both
self- and interviewer-administered.
Generic Versus Condition-Specific Measures
In generic QOL measures, certain domains will be key for all
patient groups, but there may also be an absence of areas that are
specific to a particular condition. Although generic measures enable
comparisons between groups with a diverse range of
illnesses,21 they cannot focus on the problems of a
specific condition and may not be sensitive to important changes in
QOL.
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Review of Outcome Measures Used in Stroke |
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A MEDLINE search and a review of 3 key texts1 19 22 identified 15 generic measures used in stroke QOL research and 10 condition-specific measures (although not all were stroke specific). The MEDLINE search was undertaken in October 1999 using the keywords "stroke" and "quality of life." No limit was put on the year of publication, but published language was limited to English only. This generated 351 articles. However, many of these were not relevant for the purposes of the present article, mainly because the article was not primarily about stroke. Thus, a total of 49 articles were consulted for the evaluation exercise. (A full list of the relevant articles consulted is available from the authors on request.) This evaluation was not intended as a full systematic review but rather to demonstrate the variety of measures used to assess QOL after stroke, to identify any stroke-specific measures, and to examine the strengths and weaknesses of the measures identified.
The identified measures were evaluated in terms of criteria recommended by the UK HTA report.12 We have included additional evaluation criteria that are important for stroke populations (suitability for use with proxy respondents and mode of administration), as outlined above. Given the essential differences between generic and condition-specific measures, as highlighted earlier, we evaluated each type separately. Two of the present authors undertook independent evaluations of the measures identified. There were few discrepancies, but when they arose, the issue was discussed and agreement achieved between the evaluators.
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Results |
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Generic Measures
Nine of the 15 generic measures or approaches identified were used to measure poststroke QOL in only a single study and/or they tapped only 1 domain of QOL (Karnofsky Performance Status Scale,1 Life Satisfaction Index Nottingham version,23 Geriatric QOL Questionnaire,23 Functional Life Scale,24 Hospital Anxiety and Depression scale,25 and various utility approaches [visual analogue scale,26 standard gamble technique,27 time trade-off,11 and global scale11 ]). Moreover, little information is available about their psychometric and other properties. Unlike standardized, indirect measures of utility such as the EuroQol,28 London Handicap Scale (LHS),29 and Health Utilities Index (HUI),30 the other utility measures are direct measures of personal preference regarding health states. They were developed for health economic evaluations and derived from a specific body of economic/decision theory.12 In the interests of brevity and focus, these measures will be excluded from our main evaluation because we are concerned only with standardized descriptive measures, both generic and condition specific, used in the assessment of QOL after stroke.
Tables 1
, 2, and 3
list the remaining 6 generic measures identified as having been used in
stroke QOL research. Each measure was systematically evaluated in terms
of its performance in stroke populations, by the criteria
outlined above. The Sickness Impact Profile (SIP)31 and
Nottingham Health Profile (NHP)32 were the only 2 generic
measures to exhibit all 3 psychometric properties of reliability,
validity, and responsiveness. The NHP, SIP, and HUI were developed by
use of patient-centered methods. Suitability for use with proxy
respondents in stroke studies is evident for the SIP, EuroQol, and HUI.
The MOS 36-Item Short Form Health Survey (SF-36),33 and
most of the other generic measures, can be either self- or
interviewer-administered. The LHS is a self-completion–only
measure.
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In terms of acceptability, the levels of comprehensiveness and number of items varied widely between measures. Although coverage is broad in some of the generic QOL measures, certain issues relevant to stroke, such as concentration and memory,34 are not covered at all. Average completion times ranged from 2 to 30 minutes. Overall response rates to the measures in stroke populations were acceptable in most cases, although a wide range was found for the EuroQol and SF-36. Response rates to individual items were good for the HUI and LHS, moderate for the SF-36, but not known for the other generic measures. Evidence of acceptability in terms of pretesting with stroke patients exists only for the HUI.
The level of precision (in terms of the number of response categories and evidence of floor or ceiling effects) also varies widely between measures. The SIP and NHP have only 2 response categories, for example, whereas the SF-36 has a combination of between 2 and 6 response categories depending on the domain, and the LHS has 6 response categories. Floor and ceiling effects in stroke populations are not known for most of the generic measures identified, but the SF-36 has high ceiling effects on some domains.
Condition-Specific Measures
The MEDLINE search identified 10 condition-specific measures that
had been used in stroke QOL research. However, 3 of these (the Heart
Patients Psychological Questionnaire,22 25 the
Multi-Dimensional Health Locus of Control Scale,22 and the
Life Orientation Test22 ) were not developed to be stroke
specific, and an additional MEDLINE search found little information
about these measures. Therefore, we focused only on the 7 identified
measures that were designed to be stroke specific (Tables 4, 5, and 6). All but 1 of these measures (the
Frenchay Activities Index [FAI])35 had been used in only
1 reported study. Although we did not focus on generic measures, which
were used in only 1 reported study, the stroke-specific measures
warrant further attention.
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Information about the domains covered and the psychometric and
other properties of the stroke-specific measures are outlined in Tables 4
, 5, and 6, which use the same evaluation
criteria as Tables 1, 2, and 3. Four of the
measures (the FAI, the Niemi QOL scale,36 the Ferrans and
Powers QOL Index–Stroke Version,37 and the 30-item
Stroke-Adapted SIP [SA-SIP30]38 ) exhibit both
reliability and validity. Only the FAI has been shown to be responsive
to change. Only the FAI has evidence of suitability for use with proxy
respondents, and only the FAI and SA-SIP30 can be both self- and
interviewer-administered. None of the stroke-specific measures used
patient-centered methods in their development.
As with the generic measures identified, stroke-specific instruments varied immensely in terms of their coverage and number of items. Average completion time was known only for the FAI (3 to 5 minutes). Overall response rates to the measures in field tests were acceptable where this information was known. Response rates to individual items were good for the Ferrans and Powers QOL Index–Stroke Version but were not reported for the FAI, the Niemi QOL Scale, the Viitanen Life Satisfaction interview,39 the Stroke Rehabilitation Outcome Study,40 the Ahlsio QOL interview,41 or the SA-SIP30. Acceptability of these stroke-specific measures was not pretested with patients.
Precision is difficult to assess for the stroke-specific measures. Where information was available, the number of response categories varied from 2 to 6, and floor or ceiling effects were not reported for any of these measures.
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Discussion |
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This article updates earlier reviews of generic and condition-specific measures for use in assessing QOL after stroke. To describe their performance and properties as they relate to stroke specifically, we considered only those measures that have been (rather than measures that could be) applied in this particular clinical population.
The limitations of this evaluation should be acknowledged. It is based on a MEDLINE search and 3 key texts in the area of QOL measurement in stroke. Resources were not available to review the "gray" literature. Our search may also have been constrained because some relevant studies did not use the term "quality of life." Our search was therefore not necessarily exhaustive.
The Measures
Although we have identified a number of generic scales used
to assess QOL in stroke, many are of limited value in assessing stroke
interventions42 owing to their lack of responsiveness to
changes in QOL. Moreover, such measures would not be adequate because
they do not reflect the concerns of stroke patients themselves. In
stroke rehabilitation, for example, where the reduction of handicap
tends to be the main objective, the outcome measure used should be one
developed to focus on issues of handicap. Many patients and healthcare
providers, however, also require information on whether that reduction
is associated with corresponding improvements in QOL.
We have also identified several stroke-specific measures used to assess QOL, but the psychometric testing of many of these has either been incomplete or absent. The FAI is the only stroke-specific measure that can be used to successfully assess QOL with proxy respondents when necessary. However, this measure, despite its use to measure QOL, was developed to assess premorbid levels of lifestyle activities and is therefore not comprehensive as a QOL measure. The issue of proxy measures is critical for this condition, because people with cognitive and language problems are often unable to respond to research questions,20 and their experiences are as important as those of people without cognitive impairments. The incorporation of proxy information may also increase the size and representativeness of the sample.43 However, good patient-proxy agreement is to a large extent dependent on the reliability of the measures used.44
Finally, none of the stroke-specific instruments identified cover all issues thus far found to be appropriate to people who have had a stroke. This could be a reflection of the fact that none have used a patient-centered approach in their development. We believe that to ensure that all pertinent issues are detected, a patient-centered approach should be adopted in the development of any condition-specific measure, and rigorous psychometric testing is essential.
Conclusions
Improved methods to measure QOL in stroke are required. QOL
measures must be valid, reliable, responsive, and comprehensive. The
importance of involving patients at every stage of measure development
has been stressed in a recent UK NHS HTA report.12 This
involvement should incorporate the use of qualitative research methods,
such as in-depth interviews, to ascertain the breadth and depth of the
impact of stroke on QOL. Such knowledge can then inform the content of
any subsequent outcome measure. Patients should also be involved in
confirming the content and testing of the response categories and
overall format of any new measure. In the United States, Duncan et
al15 and Williams et al16 have recently
undertaken patient-centered exercises to develop measures of the impact
of stroke. In the United Kingdom, the present authors are
developing a stroke-specific, patient-centered QOL measure that is
currently being tested for validity and reliability.
Until further evidence about these new measures becomes available, researchers in stroke need to be cautious in their choice of existing ones. We have highlighted the advantages and disadvantages of those that have been used to date. We would reiterate that evidence of validity and reliability should be the first considerations, together with appropriateness and comprehensiveness. Much research in stroke is also likely to require an instrument that can detect both between- and within-person differences in relation to stroke itself. Accepting these criteria, no specific recommendation can be given, because the choice of the most appropriate instrument must ultimately depend on a judgment of the fit between its content and coverage and the specific study questions.12 The following measures come closest to satisfying many of the criteria outlined in this article: the Ferrans and Powers QOL Index–Stroke Version, Niemi QOL scale, SA-SIP30, and SIP. However, the selection of any individual instrument will always depend on the specific goals and constraints of a particular study.
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Acknowledgments |
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The authors wish to thank Janssen-Cilag for its support in the preparation of this article and the referees who commented on an earlier version.
Received January 18, 2000; revision received May 23, 2000; accepted May 23, 2000.
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M. Fisher and for the Stroke Therapy Academic Industry Roundtabl Enhancing the Development and Approval of Acute Stroke Therapies: Stroke Therapy Academic Industry Roundtable Stroke, August 1, 2005; 36(8): 1808 - 1813. [Abstract] [Full Text] [PDF]
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S. L. Fritz, K. E. Light, T. S. Patterson, A. L. Behrman, and S. B. Davis Active Finger Extension Predicts Outcomes After Constraint-Induced Movement Therapy for Individuals With Hemiparesis After Stroke Stroke, June 1, 2005; 36(6): 1172 - 1177. [Abstract] [Full Text] [PDF]
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 J. Nilsson, M. G. Parker, and Z. N. Kabir Assessing Health-Related Quality of Life among Older People in Rural Bangladesh J Transcult Nurs, October 1, 2004; 15(4): 298 - 307. [Abstract] [PDF]
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 C Foerch, K R Kessler, D A Steckel, H Steinmetz, and M Sitzer Survival and quality of life outcome after mechanical ventilation in elderly stroke patients J. Neurol. Neurosurg. Psychiatry, July 1, 2004; 75(7): 988 - 993. [Abstract] [Full Text] [PDF]
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 U. Sveen, B. Thommessen, E. Bautz-Holter, T. B. Wyller, and K. Laake Well-being and instrumental activities of daily living after stroke Clinical Rehabilitation, March 1, 2004; 18(3): 267 - 274. [Abstract] [PDF]
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 P.W. Duncan, S.M. Lai, R.K. Bode, S. Perera, and J. DeRosa Stroke Impact Scale-16: A brief assessment of physical function Neurology, January 28, 2003; 60(2): 291 - 296. [Abstract] [Full Text] [PDF]
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J. W. Sturm, R. H. Osborne, H. M. Dewey, G. A. Donnan, R. A.L. Macdonell, and A. G. Thrift Brief Comprehensive Quality of Life Assessment After Stroke: The Assessment of Quality of Life Instrument in the North East Melbourne Stroke Incidence Study (NEMESIS) Stroke, December 1, 2002; 33(12): 2888 - 2894. [Abstract] [Full Text] [PDF]
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P. Clarke, V. Marshall, S. E. Black, and A. Colantonio Well-Being After Stroke in Canadian Seniors: Findings From the Canadian Study of Health and Aging Stroke, April 1, 2002; 33(4): 1016 - 1021. [Abstract] [Full Text] [PDF]
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J. I. Cameron and M. D. Buck Facilitating Data Collection in Stroke Patients and the Elderly Response Stroke, December 1, 2000; 31 (12): 3079 - 3083. [Full Text]
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