The Quality of Life Scale (QOLS): Reliability, Validity, and Utilization, 2003, Burkhardt and Anderson

Sly Saint

Senior Member (Voting Rights)
Abstract
The Quality of Life Scale (QOLS), created originally by American psychologist John Flanagan in the 1970's, has been adapted for use in chronic illness groups. This paper reviews the development and psychometric testing of the QOLS.

A descriptive review of the published literature was undertaken and findings summarized in the frequently asked questions format.

Reliability, content and construct validity testing has been performed on the QOLS and a number of translations have been made.

The QOLS has low to moderate correlations with physical health status and disease measures.

However, content validity analysis indicates that the instrument measures domains that diverse patient groups with chronic illness define as quality of life.

The QOLS is a valid instrument for measuring quality of life across patient groups and cultures and is conceptually distinct from health status or other causal indicators of quality of life.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC269997/

Why assess Quality of Life in chronic illness?
Quality of life (QOL) measures have become a vital and often required part of health outcomes appraisal. For populations with chronic disease, measurement of QOL provides a meaningful way to determine the impact of health care when cure is not possible. Over the past 20 years, hundreds of instruments have been developed that purport to measure QOL [1]. With few exceptions, these instruments measure what Fayers and colleagues [2,3] have called causal indicators of QOL rather than QOL itself. Health care professionals need to be clear about the conceptual definition of QOL and not to confound it with functional status, symptoms, disease processes, or treatment side-effects [4-7].



Posting because 'improvement in QOL' seems to be repeatedly used to claim success for psychotherapy studies where outcome measures have failed to show effectiveness.
eg TC, RMM research.
 
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