Transforming the SF-36 to account for death in longitudinal studies with three-year follow-up

Bowe, Steven, Young, Anne F., Sibbritt, David and Furuya, Hiroyuki 2006, Transforming the SF-36 to account for death in longitudinal studies with three-year follow-up, Medical care, vol. 44, no. 10, pp. 956-959, doi: 10.1097/01.mlr.0000228022.79359.95.

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Title Transforming the SF-36 to account for death in longitudinal studies with three-year follow-up
Author(s) Bowe, StevenORCID iD for Bowe, Steven
Young, Anne F.
Sibbritt, David
Furuya, Hiroyuki
Journal name Medical care
Volume number 44
Issue number 10
Start page 956
End page 959
Total pages 4
Publisher Lippincott Williams & Wilkins
Place of publication [New York, N.Y.]
Publication date 2006-10
ISSN 0025-7079
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
Health Policy & Services
Public, Environmental & Occupational Health
longitudinal models
Summary BACKGROUND: Analyses of longitudinal health-related quality of life data often exclude participants who die, which limits the generalizability of the results. Methods to incorporate death as a valid score in the Medical Outcomes Study Short-Form (SF-36) have been suggested but need to be evaluated in other populations. OBJECTIVES: We sought to apply a method of transforming the SF-36 Physical Component Score (PCS) to include death. A transformation to estimate the probability of being "healthy" in 3 years, based on the current PCS value, will be developed and validated. SUBJECTS: Women in the Australian Longitudinal Study on Women's Health (ALSWH), ages 70-75 years at Survey 1 in 1996 (n = 12,432), were followed-up at 3 yearly intervals for 6 years. RESULTS: The transformation derived from the ALSWH data provides evidence that the methodology for transforming the PCS to account for deaths is sound. The 3-year equation provided good estimates of the probability of being healthy in 3 years and the method allowed deaths to be included in an analysis of changes in health over time. CONCLUSIONS: For longitudinal studies involving the SF-36 in which subjects have died, we support the recommendation that both the PCS and its transformed value which includes deaths should be analyzed to examine the influence of deaths on the study conclusions. Using study data to derive empirical parameters for the transformations may be appropriate for studies with follow-up intervals of other lengths.
Language eng
DOI 10.1097/01.mlr.0000228022.79359.95
Field of Research 1117 Public Health And Health Services
1402 Applied Economics
Socio Economic Objective 929999 Health not elsewhere classified
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2006, Lippincott Williams & Wilkins
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Document type: Journal Article
Collection: PVC's Office - Health
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