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Journal ArticleDOI

Distinguishing between quality of life and health status in quality of life research: A meta-analysis

Kevin W. Smith, +2 more
- 01 Aug 1999 - 
- Vol. 8, Iss: 5, pp 447-459
TLDR
It is concluded that quality of life and health status are distinct constructs, and that the two terms should not be used interchangeably.
Abstract
Despite the increasing acceptance of quality of life (QOL) as a critical endpoint in medical research, there is little consensus regarding the definition of this construct or how it differs from perceived health status. The objective of this analysis was to understand how patients make determinations of QOL and whether QOL can be differentiated from health status. We conducted a meta-analysis of the relationships among two constructs (QOL and perceived health status) and three functioning domains (mental, physical, and social functioning) in 12 chronic disease studies. Instruments used in these studies included the RAND-36, MOS SF-20, EORTC QLQ-30, MILQ and MQOL-HIV. A single, synthesized correlation matrix combining the data from all 12 studies was estimated by generalized least squares. The synthesized matrix was then used to estimate structural equation models. The meta-analysis results indicate that, from the perspective of patients, QOL and health status are distinct constructs. When rating QOL, patients give greater emphasis to mental health than to physical functioning. This pattern is reversed for appraisals of health status, for which physical functioning is more important than mental health. Social functioning did not have a major impact on either construct. We conclude that quality of life and health status are distinct constructs, and that the two terms should not be used interchangeably. Many prominent health status instruments, including utility-based questionnaires and health perception indexes, may be inappropriate for measuring QOL. Evaluations of the effectiveness of medical treatment may differ depending on whether QOL or health status is the study outcome.

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Citations
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Journal ArticleDOI

PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations.

TL;DR: The PedsQL distinguished between healthy children and pediatric patients with acute or chronic health conditions, was related to indicators of morbidity and illness burden, and displayed a factor-derived solution largely consistent with the a priori conceptually-derived scales.
Journal ArticleDOI

The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity.

TL;DR: Measuring pediatric HRQOL may be a way to evaluate the health outcomes of SCHIP and demonstrate the feasibility, reliability, and validity of the PedsQL 4.0 as a pediatric population health outcome.
Journal ArticleDOI

A measure of quality of life in early old age: the theory, development and properties of a needs satisfaction model (CASP-19).

TL;DR: A needs satisfaction measure of QoL in early old age, which has four ontologically grounded domains: control, autonomy, pleasure, and self-realization, which appears to be a useful scale for measuring quality of life in older people.
References
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Book

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TL;DR: The General Model, Part I: Latent Variable and Measurement Models Combined, Part II: Extensions, Part III: Extensions and Part IV: Confirmatory Factor Analysis as discussed by the authors.
Journal ArticleDOI

Significance tests and goodness of fit in the analysis of covariance structures

TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
Book

Statistical Methods for Meta-Analysis

TL;DR: In this article, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Journal ArticleDOI

Statistical Methods for Meta-Analysis.

TL;DR: In this paper, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
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We conclude that quality of life and health status are distinct constructs, and that the two terms should not be used interchangeably.