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Measurement invariance of the kidney disease and quality of life instrument (KDQOL-SF) across veterans and non-veterans.

Saban KL, Bryant FB, Reda DJ, Stroupe KT, Hynes DM - Health Qual Life Outcomes (2010)

Bottom Line: Since HRQOL outcome data are often used to compare groups to determine health care effectiveness it is imperative that measures of HRQOL are valid.Multigroup CFA results concerning metric and scalar invariance suggested partial strict invariance for the SF-36, but only weak invariance for the KDCS.Further evaluation of measurement invariance of the KDQOL-SF between Veterans and non-Veterans is needed using large, randomly selected samples before comparisons between these two groups using the KDQOL-SF can be done reliably.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Management of Chronic Complex Care, Edward Hines Jr. VA Hospital, Hines, IL, USA. Ksaban@luc.edu

ABSTRACT

Background: Studies have demonstrated that perceived health-related quality of life (HRQOL) of patients receiving hemodialysis is significantly impaired. Since HRQOL outcome data are often used to compare groups to determine health care effectiveness it is imperative that measures of HRQOL are valid. However, valid HRQOL comparisons between groups can only be made if instrument invariance is demonstrated. The Kidney Disease Quality of Life-Short Form (KDQOL-SF) is a widely used HRQOL measure for patients with chronic kidney disease (CKD) however, it has not been validated in the Veteran population. Therefore, the purpose of this study was to examine the measurement invariance of the KDQOL-SF across Veterans and non-Veterans with CKD.

Methods: Data for this study were from two large prospective observational studies of patients receiving hemodialysis: 1) Veteran End-Stage Renal Disease Study (VETERAN) (N = 314) and 2) Dialysis Outcomes and Practice Patterns Study (DOPPS) (N = 3,300). Health-related quality of life was measured with the KDQOL-SF, which consists of the SF-36 and the Kidney Disease Component Summary (KDCS). Single-group confirmatory factor analysis was used to evaluate the goodness-of-fit of the hypothesized measurement model for responses to the subscales of the KDCS and SF-36 instruments when analyzed together; and given acceptable goodness-of-fit in each group, multigroup CFA was used to compare the structure of this factor model in the two samples. Pattern of factor loadings (configural invariance), the magnitude of factor loadings (metric invariance), and the magnitude of item intercepts (scalar invariance) were assessed as well as the degree to which factors have the same variances, covariances, and means across groups (structural invariance).

Results: CFA demonstrated that the hypothesized two-factor model (KDCS and SF-36) fit the data of both the Veteran and DOPPS samples well, supporting configural invariance. Multigroup CFA results concerning metric and scalar invariance suggested partial strict invariance for the SF-36, but only weak invariance for the KDCS. Structural invariance was not supported.

Conclusions: Results suggest that Veterans may interpret the KDQOL-SF differently than non-Veterans. Further evaluation of measurement invariance of the KDQOL-SF between Veterans and non-Veterans is needed using large, randomly selected samples before comparisons between these two groups using the KDQOL-SF can be done reliably.

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Subscales of KDQOL. The ellipses represent latent factors (i.e., the SF-36 and KDCS instruments), the rectangles represent measured indicators (i.e., the subscales for each instrument), the lines connecting instruments to subscales are factor loadings, and the curve connecting the two instruments represents a factor correlation. Four KDCS subscales (sexual function, work status, patient satisfaction, and staff encouragement) were not included in the confirmatory factor analysis models for this study). Because of large amounts of missing data from both the VETERANS and DOPPs samples for the sexual function subscale, sexual function was not included in the calculation of the KDCS for this study. In addition, a one-factor confirmatory factor analysis of the KDCS demonstrated weak factor loadings of the subscales of work status, patient satisfaction and dialysis staff encouragement suggesting that these three subscales measure something other than HRQOL. Therefore, these four subscales were not included in our measurement models (see data analysis section for further details).
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Figure 1: Subscales of KDQOL. The ellipses represent latent factors (i.e., the SF-36 and KDCS instruments), the rectangles represent measured indicators (i.e., the subscales for each instrument), the lines connecting instruments to subscales are factor loadings, and the curve connecting the two instruments represents a factor correlation. Four KDCS subscales (sexual function, work status, patient satisfaction, and staff encouragement) were not included in the confirmatory factor analysis models for this study). Because of large amounts of missing data from both the VETERANS and DOPPs samples for the sexual function subscale, sexual function was not included in the calculation of the KDCS for this study. In addition, a one-factor confirmatory factor analysis of the KDCS demonstrated weak factor loadings of the subscales of work status, patient satisfaction and dialysis staff encouragement suggesting that these three subscales measure something other than HRQOL. Therefore, these four subscales were not included in our measurement models (see data analysis section for further details).

Mentions: Health-related quality of life was measured with the Kidney Disease Quality of Life Instrument -Short Form (KDQOL-SF). The KDQOL was developed as a self-report, health-related quality of life measurement tool designed specifically for patients with CKD [22]. The 134-item KDQOL was later condensed into the 80-item Kidney Disease Quality of Life Instrument-Short Form (KDQOL-SF) [39]. The questionnaire consists of the generic SF-36 [40] as well as 11 multi-item scales focused on quality of life issues specific to patients with kidney disease (Figure 1). Subscales of the KDCS are (1) symptoms/problems (6 items), (2) effects of kidney disease (4 items), (3) burden of kidney disease (3 items), (4) work status (2 items), (5) cognitive function (3 items), (6) quality of social interaction (3 items), (7) sexual function (2 items), (8) sleep (4 items), (9) social support (2 items), (10) dialysis staff encouragement (2 items), and (11) patient satisfaction. For example, related to the effects of kidney disease, participants are asked how true or false (using a 5 point Likert scale ranging from "definitely true" to "definitely false" the following statements are for them: (1) "My kidney disease interferes too much with my life;" and (2) "Too much of my time is spent dealing with my kidney disease" [22,39]. All kidney disease subscales are scored on a 0 to 100 scale, with higher numbers representing better HRQOL. The 11 kidney disease-specific subscales can be averaged to form the Kidney Disease Component Summary (KDCS) [21,41-44]. The KDQOL-SF has been widely used in several studies of patients with kidney disease, including the ongoing, international DOPPS [21,45-50], and has demonstrated good test-retest reliability on most dimensions [2,22]. Published reliability statistics for all subscales range from 0.68 to 0.94 with the subscale of social interaction (0.68) being the only subscale with an internal consistency reliability of less than the recommended 0.70 [22].


Measurement invariance of the kidney disease and quality of life instrument (KDQOL-SF) across veterans and non-veterans.

Saban KL, Bryant FB, Reda DJ, Stroupe KT, Hynes DM - Health Qual Life Outcomes (2010)

Subscales of KDQOL. The ellipses represent latent factors (i.e., the SF-36 and KDCS instruments), the rectangles represent measured indicators (i.e., the subscales for each instrument), the lines connecting instruments to subscales are factor loadings, and the curve connecting the two instruments represents a factor correlation. Four KDCS subscales (sexual function, work status, patient satisfaction, and staff encouragement) were not included in the confirmatory factor analysis models for this study). Because of large amounts of missing data from both the VETERANS and DOPPs samples for the sexual function subscale, sexual function was not included in the calculation of the KDCS for this study. In addition, a one-factor confirmatory factor analysis of the KDCS demonstrated weak factor loadings of the subscales of work status, patient satisfaction and dialysis staff encouragement suggesting that these three subscales measure something other than HRQOL. Therefore, these four subscales were not included in our measurement models (see data analysis section for further details).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2984554&req=5

Figure 1: Subscales of KDQOL. The ellipses represent latent factors (i.e., the SF-36 and KDCS instruments), the rectangles represent measured indicators (i.e., the subscales for each instrument), the lines connecting instruments to subscales are factor loadings, and the curve connecting the two instruments represents a factor correlation. Four KDCS subscales (sexual function, work status, patient satisfaction, and staff encouragement) were not included in the confirmatory factor analysis models for this study). Because of large amounts of missing data from both the VETERANS and DOPPs samples for the sexual function subscale, sexual function was not included in the calculation of the KDCS for this study. In addition, a one-factor confirmatory factor analysis of the KDCS demonstrated weak factor loadings of the subscales of work status, patient satisfaction and dialysis staff encouragement suggesting that these three subscales measure something other than HRQOL. Therefore, these four subscales were not included in our measurement models (see data analysis section for further details).
Mentions: Health-related quality of life was measured with the Kidney Disease Quality of Life Instrument -Short Form (KDQOL-SF). The KDQOL was developed as a self-report, health-related quality of life measurement tool designed specifically for patients with CKD [22]. The 134-item KDQOL was later condensed into the 80-item Kidney Disease Quality of Life Instrument-Short Form (KDQOL-SF) [39]. The questionnaire consists of the generic SF-36 [40] as well as 11 multi-item scales focused on quality of life issues specific to patients with kidney disease (Figure 1). Subscales of the KDCS are (1) symptoms/problems (6 items), (2) effects of kidney disease (4 items), (3) burden of kidney disease (3 items), (4) work status (2 items), (5) cognitive function (3 items), (6) quality of social interaction (3 items), (7) sexual function (2 items), (8) sleep (4 items), (9) social support (2 items), (10) dialysis staff encouragement (2 items), and (11) patient satisfaction. For example, related to the effects of kidney disease, participants are asked how true or false (using a 5 point Likert scale ranging from "definitely true" to "definitely false" the following statements are for them: (1) "My kidney disease interferes too much with my life;" and (2) "Too much of my time is spent dealing with my kidney disease" [22,39]. All kidney disease subscales are scored on a 0 to 100 scale, with higher numbers representing better HRQOL. The 11 kidney disease-specific subscales can be averaged to form the Kidney Disease Component Summary (KDCS) [21,41-44]. The KDQOL-SF has been widely used in several studies of patients with kidney disease, including the ongoing, international DOPPS [21,45-50], and has demonstrated good test-retest reliability on most dimensions [2,22]. Published reliability statistics for all subscales range from 0.68 to 0.94 with the subscale of social interaction (0.68) being the only subscale with an internal consistency reliability of less than the recommended 0.70 [22].

Bottom Line: Since HRQOL outcome data are often used to compare groups to determine health care effectiveness it is imperative that measures of HRQOL are valid.Multigroup CFA results concerning metric and scalar invariance suggested partial strict invariance for the SF-36, but only weak invariance for the KDCS.Further evaluation of measurement invariance of the KDQOL-SF between Veterans and non-Veterans is needed using large, randomly selected samples before comparisons between these two groups using the KDQOL-SF can be done reliably.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Management of Chronic Complex Care, Edward Hines Jr. VA Hospital, Hines, IL, USA. Ksaban@luc.edu

ABSTRACT

Background: Studies have demonstrated that perceived health-related quality of life (HRQOL) of patients receiving hemodialysis is significantly impaired. Since HRQOL outcome data are often used to compare groups to determine health care effectiveness it is imperative that measures of HRQOL are valid. However, valid HRQOL comparisons between groups can only be made if instrument invariance is demonstrated. The Kidney Disease Quality of Life-Short Form (KDQOL-SF) is a widely used HRQOL measure for patients with chronic kidney disease (CKD) however, it has not been validated in the Veteran population. Therefore, the purpose of this study was to examine the measurement invariance of the KDQOL-SF across Veterans and non-Veterans with CKD.

Methods: Data for this study were from two large prospective observational studies of patients receiving hemodialysis: 1) Veteran End-Stage Renal Disease Study (VETERAN) (N = 314) and 2) Dialysis Outcomes and Practice Patterns Study (DOPPS) (N = 3,300). Health-related quality of life was measured with the KDQOL-SF, which consists of the SF-36 and the Kidney Disease Component Summary (KDCS). Single-group confirmatory factor analysis was used to evaluate the goodness-of-fit of the hypothesized measurement model for responses to the subscales of the KDCS and SF-36 instruments when analyzed together; and given acceptable goodness-of-fit in each group, multigroup CFA was used to compare the structure of this factor model in the two samples. Pattern of factor loadings (configural invariance), the magnitude of factor loadings (metric invariance), and the magnitude of item intercepts (scalar invariance) were assessed as well as the degree to which factors have the same variances, covariances, and means across groups (structural invariance).

Results: CFA demonstrated that the hypothesized two-factor model (KDCS and SF-36) fit the data of both the Veteran and DOPPS samples well, supporting configural invariance. Multigroup CFA results concerning metric and scalar invariance suggested partial strict invariance for the SF-36, but only weak invariance for the KDCS. Structural invariance was not supported.

Conclusions: Results suggest that Veterans may interpret the KDQOL-SF differently than non-Veterans. Further evaluation of measurement invariance of the KDQOL-SF between Veterans and non-Veterans is needed using large, randomly selected samples before comparisons between these two groups using the KDQOL-SF can be done reliably.

Show MeSH
Related in: MedlinePlus