(Stroke. 1999;30:1213-1217.)
© 1999 American Heart Association, Inc.
Original Contributions |
From the Faculties of Pharmacy and Pharmaceutical Sciences (A.S.P., J.A.J.), Medicine and Oral Health Sciences (A.P., T.N.), and Business (F.L.), University of Alberta, Edmonton, Canada, and Institute of Pharmaco-Economics (A.S.P., J.A.J.), Edmonton, Alberta, Canada.
Correspondence and reprints requests to A. Simon Pickard, Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2N8. E-mail spickard{at}pharmacy.ualberta.ca
| Abstract |
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MethodsIntraclass correlation coefficients (ICCs) and linear regression were used to assess the ability of the SF-12 physical component summary (PCS-12) scores to predict PCS-36 scores and the SF-12 mental component summary (MCS-12) scores to predict MCS-36 scores. Multivariate regression was used to explore the relationship between SF-12 and SF-36 scores.
ResultsThe MCS-12 and PCS-12 scores were strongly correlated with the corresponding SF-36 summary scores for surveys completed by proxy or self-report (ICCs ranged from 0.954 to 0.973). Regression analysis of the proxy assessments indicated that patient age was an important effect modifier in the relationship between MCS-12 and MCS-36 scores.
ConclusionsThe SF-12 reproduced SF-36 summary scores without substantial loss of information in stroke patients. Accordingly, the SF-12 can be used at the summary score level as a substitute for the SF-36 in stroke survivors capable of self-report. However, the mental health summary scores of proxy assessments are influenced by patient age, thereby limiting the replicability of the SF-36 by the SF-12 under these conditions.
Key Words: health status quality of life stroke outcome
| Introduction |
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The importance of using the SF-12 in place of the SF-36 is of particular consequence for the research evaluation of stroke patients. Time and cost savings may be realized through the use of a shorter battery of questions to be included into a longitudinal questionnaire series, while providing essentially the same prognostic information as the longer form. The shorter SF-12 questionnaire can substantially reduce the time spent by respondent and interviewer in an administered survey. Decreased respondent burden through use of the SF-12 in stroke patients may result in findings comparable with those of Dorman et al 6 with the EuroQol questionnaire. Shorter instruments with less missing data increase the efficiency of the study and reduce the resources required. Furthermore, by enabling responses from patients with poorer outcomes, a shorter, simpler instrument may provide more power to detect differences between groups because larger sample sizes will counter small losses in precision. The total time to complete the SF-12 questionnaire is less than 2 minutes for the majority of individuals,4 while the corresponding time to respond to the SF-36 is 10 to 12 minutes. These completion times are likely to be greater for both instruments in stroke patients.
Compared with the SF-36, the disadvantages of using the SF-12 include less-precise estimate of individual health and an inability to calculate summary scores when 1 item is left unanswered. This contrasts with the ability to impute missing data on the SF-36 because of multiple item domains. The SF-12 also does not appear to accurately reproduce the 8 domain scores of the SF-36.2 As a consequence, disaggregated summary scores may be less informative to users of the SF-12. Furthermore, use of the SF-12 in place of the SF-36 as a screening instrument to detect health problems may compromise the sensitivity and specificity offered by the more extensive 36-item survey.
Proxy assessment of the health status of stroke survivors is sometimes necessary because of cognitive impairment of the patient. This assessment is often performed by the patients' caregivers. Thus, it is also important to assess the replicability of SF-36 summary scores obtained via proxy assessment.
The purpose of this analysis was twofold: (1) to determine the degree to which the summary scores of the SF-12 replicate the MCS and PCS scores of the SF-36 in stroke patients and (2) to characterize identifiable differences in the relationship between the SF-36 and SF-12 summary scores. We adopted the convention suggested by the developers of the instruments,4 referring to the summary scores calculated from the SF-36 as the PCS-36 and MCS-36, and scores from the SF-12 as the PCS-12 and MCS-12.
Hypothesized for objective 1 was that PCS-36 and MCS-36 are highly correlated (ICC >0.90) with the scores of the PCS-12 and MCS-12, respectively. The hypothesized relationship between the SF-36 and SF-12 summary scores was also tested using simple linear regression, with a 2-tailed test to determine whether the SF-12 summary score differed significantly from a slope of 1.0 or intercept of 0 in relation to the respective SF-36 summary score. Objective 2 was hypothesis generating and was accomplished through exploratory correlational and regression analysis.
| Subjects and Methods |
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95 and 15% of patients
scoring
60. Self-report was not feasible for 53 of the 161 patients
due to the extent of their disability, so proxy assessment via a family
member was used to estimate the health status of these individuals. The
case mix of diagnoses was similar for both proxy-assessed and
self-reporting patients, with cerebral artery occlusion (ICD 434.91)
the diagnosis in 69% of self-reporting patients and 75% of patients
assessed by proxy. Acute but ill-defined cerebrovascular disease (ICD
436.00) was diagnosed in 24% of self-reporting patients and 25% of
patients assessed by proxy. The remaining 7% of self-assessed patients
suffered other stroke-related diagnoses.
Data Analysis
Scores for the MCS-36 and PCS-36 of the SF-36 Health Survey were
calculated using the SAS scoring program.7 Based on
findings by Ware and colleagues4 that scores for the
MCS-12 and PCS-12 did not differ if the items are presently
separately as opposed to being reconstructed from the SF-36, scores
were calculated from the subset of SF-12 items embedded within the
SF-36.
Proxy or self-reported assessments were described and analyzed independently. Because proxy assessments and self-assessments were not obtained for the same individuals, the direct comparison of these forms of assessment was not possible and was therefore not an objective of this analysis. One-way ANOVA was performed to detect significant differences between proxy- and self-assessed groups. Agreements between SF-12 and SF-36 summary scores were determined using ICCs8 and simple linear regression for the full sample and within the assessment groups.
Multiple linear regression analysis was used to address the second objective. The SF-36 summary scores were the dependent variables, with the corresponding SF-12 summary scores used as independent variables. Because age is typically related to PCS and gender to MCS, the linear regression models initially included age and gender. A dichotomous variable identified assessments as being completed by proxy or self-report. Interaction terms were also included in the regression model. Differences were considered statistically significance for a value of P<0.05. All analyses were performed using SPSS for Windows, Release 7.5.1.9
| Results |
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Physical Health
The mean PCS-36 scores for proxy-assessed stroke patients were
significantly below those of self-reporting stroke patients (Table 1
). PCS-12 scores were not
statistically different between proxy and self-report
(P=0.06). PCS-12 scores were in high agreement with PCS-36
scores for both self-assessments (ICC=0.959) and proxy assessments
(ICC=0.973). The slopes of PCS-12 in the simple regression models were
significantly different from 1.0, as evidenced by the boundaries of the
confidence interval (Table 1
). However, this is not an important
difference in terms of the interpretation of scores. There was no
significant deviation from 0 for the intercepts on any of the
regression models for PCS scores.
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In univariate correlations with SF-36 summary scores,
age was negatively correlated with PCS-36 for both self-reporting
(r=-0.308) and proxy-assessed
(r=-0.346) stroke patients. A weak to
medium-strength relationship (point biserial correlation=0.305) was
observed between patient gender and proxy-assessed PCS-36 score, but
not for self-reporting patients. All of the linear regression models
predicting PCS-36 scores showed PCS-12 to be the only significant
independent variable, and this relationship was not modified by
age, gender, or proxy assessment of health status (Table 2
).
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Mental Health
The mean scores obtained by proxy on both the MCS-12 and MCS-36
were significantly lower than for assessments by self-report (Table 1
). The absolute difference in health status between
proxy-assessed and self-reported mental summary scores was greater than
for the physical summary scores. MCS-12 and MCS-36 scores were
significantly correlated for self-report (ICC=0.954) and proxy
assessments (ICC=0.973). The slopes of MCS-12 in the simple regression
models were not significantly different from 1.0, but the intercept for
proxy assessments was significantly different from 0 (Table 1
).
Neither age nor gender independently correlated with MCS-36 score. In
fact, MCS-12 score was the only significant predictor variable for
self-reported MCS-36 scores using linear regression, giving an adjusted
R2=0.918 (Table 3
). However, the regression model
predicting proxy-assessed MCS-36 scores differed from the model based
on patient self-report. Age and the interaction term between age and
MCS-12 score were significant, while the MCS-12 score itself was not a
significant predictor. In the combined sample model, which identified
an assessment as being completed by proxy or self-report, significant
independent variables included MCS-12 score, proxy assessment
status, and interaction terms between age and proxy; MCS-12 and proxy;
and MCS-12, proxy, and age (Table 3
).
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| Discussion |
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The importance of incorporating generic health status measures in stroke outcome measure was recently emphasized by Duncan et al,10 who discussed the inadequacy of using measures such as the Barthel Index11 to capture the full impact of stroke-related disability. These authors indicated that standardized assessment of individuals with stroke must evaluate across the entire continuum of health-related functions, and they recommended that measures such as the MOS-36 (SF-36) be used in addition to the Barthel Index, which has a ceiling effect and captures only physical functionality.10
However, the use of generic health status measures in stroke patients can be similarly compromised by ceiling effects, floor effects, and insensitivity to change. A review by Williams12 cites potential problems with the content validity of both the domains and the items comprising the domains of the SF-36. For instance, the SF-36 does not assess language or cognition. A floor effect is likely to be encountered on some items, such as those regarding mobility, and the limited number of response options on some of the SF-36 items may impair the ability of the SF-36 to detect improvements in health status. As the SF-12 presents only one third of the items on the SF-36, it may be even less responsive to change. For these reasons, the SF-12 may be better suited to discriminate between patients rather than to evaluate change within individuals over time.
Due to the inability of some stroke survivors to self-complete health status questionnaires, the use of proxy assessments has been studied in several generic health status instruments, including the Health Utilities Index (HUI),13 the EuroQol,14 the Sickness Impact Profile (SIP),15 and the Health Status Questionnaire (formerly the SF-36 of the Medical Outcomes Study).16 The conclusions of these investigations have been mixed.
Mathias et al13 reported moderate to high agreement in interrater reliability between stroke patients and proxies on the HUI, suggesting that family caregivers can complete the HUI reliably when patients are unable to do so. Dorman et al14 concluded that the HRQL information obtained by proxy on the more observable domains of the EuroQol may be sufficiently valid and unbiased to be useable in most types of trials and surveys, but found poor agreement for the domain that assessed psychological function. Rothman et al15 studied the validity of proxy assessments using the SIP and also found that proxy responses for psychosocial attributes were less predictive of patient responses than proxy responses to observable attributes.
Segal and Schall16 indicated that proxy agreement for the HSQ (SF-36) scales was poor, with a median ICC of 0.32 for the 8 dimensions. Agreement was highest on the physical functioning dimension (ICC=0.67) but was otherwise poor for the other dimensions that largely consisted of more subjective items. The authors postulated that poorly educated respondents had more difficulty with comprehension of the HSQ items, further detracting from interrater reliability.
Stroke patients assessed by a proxy respondent in this study had significantly lower MCS-36 and PCS-36 scores. This was predictable and is precisely the reason that proxy assessments may have been necessary. Large differences in MCS-12 and MCS-36 scores were detected between assessments by proxy and self-report. However, the PCS-12 did not demonstrate a significant difference between proxy and self-report, which might suggest that the SF-36 is a more sensitive than the SF-12 as a discriminative measure.
The finding that age was an effect modifier in the relationship between MCS-36 scores and the MCS-12 in proxy assessments was of interest. Several possible explanations have been considered, including limitations in the study design, which did not randomly assign patients to assessment by proxy or self-report. This finding may have resulted from poorer health status typical of patients requiring proxy assessments as opposed to an association with surrogate assessment. Another plausible explanation is that proxy assessments of health status are less informative for domains that are more difficult to observe, such the domains comprising the MCS summary score.
Age appears to be a clinically important effect modifier for proxy
assessments when examined in the context of the
multivariate regression models. Table 3
conveys
the dramatic changes in the intercept and slope coefficients when proxy
assessments are separated from self-reporting patients. Patient age
modified the relationship between the MCS-12 and MCS-36 scores
generated by proxy assessment, which may imply that proxy respondents
took the age of the patient into account when assessing the patient's
mental health. Elaborating on the proxy assessment model from Table 3
, younger stroke patients with lower MCS-12 scores had poorer
predictions of MCS-36 scores compared with older proxy-assessed stroke
patients. When MCS-12 scores were higher, however, there was better
prediction of MCS-36 scores in younger patients assessed by proxy
compared with older patients. The intercept of the simple regression
model for proxy respondents in Table 1
would also seem to
indicate that the scaling of MCS-12 scores is not equivalent to the
MCS-36 scores. Age did not modify the relationship between MCS-36 and
MCS-12 scores for self-reporting patients.
The discrepancy discussed here between self-report and proxy assessments of health status was similarly observed in the health assessments of elderly men from the Finnish cohorts of the Seven Countries Study.17 The authors noted that age was not related to self-perceived health, whereas a significant association was detected between patient age and proxy (physician) ratings. Depression and other symptoms that explained self-ratings were not related to proxy assessments. These observations are supportive of our explanation for the interaction between MCS-12 summary scores and age being attributed to the use of surrogate assessments.
While the exploratory analysis of proxy assessments of stroke patients requires further research, previous studies have discussed the limitations of using both SF-36 and SF-12 as a means of generating information about the more subjective mental health and functional aspects of health status. A previous validation study1 of the SF-36 in stroke survivors reported that the SF-36 did not appear to characterize social functioning well. In addition, the poor agreement between proxy and self-completion responses reported by Segal and Schall16 and Rothman et al15 cast doubt on the validity of proxy respondents, particularly for the more subjective items. Similar to recommendations regarding the SF-36,1 the SF-12 needs to be supplemented by other measures for a comprehensive assessment of health in stroke survivors.
The SF-36 has the advantage of producing scores for the 8 subscales of the instrument. Although subscale scores have been produced for the SF-12, agreement with the SF-36 subscale scores was poor.2 Currently, use of only the physical and mental health summary scales are recommended for the SF-12. If greater detail on patient status and outcome is required, we suggest that the SF-36 should be chosen over the SF-12.
Conclusions
The SF-12 replicated SF-36 summary scores in this sample of stroke
survivors without substantial loss of information. Assessment of the
physical functionality of a stroke patient using the PCS-12 appears to
adequately replicate PCS-36 scores for both proxy and self-report.
MCS-12 also appears to replicate the MCS-36 scores for stroke survivors
capable of self-report. However, the relationship between MCS-12 and
MCS-36 scores by proxy respondents was modified by age in this sample,
a finding that requires further investigation. We recommend that the
SF-12 is an appropriate substitute for the SF-36 in stroke survivors
capable of self-report and possibly in proxy respondents when subscale
scores are not sought, but it should be supplemented by other
measures.
| Acknowledgments |
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Received December 28, 1998; revision received February 25, 1999; accepted March 5, 1999.
| References |
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