M Ruggeri1, G Bisoffi, L Fontecedro, R Warner. 1. Department of Medicine and Public Health, Section of Psychiatry, University of Verona, Italy. mruggeri@borgoroma.univr.it
Abstract
BACKGROUND: Both subjective and objective information is necessary to assess quality of life (QOL). AIMS: To explore the role of subjective and objective QOL dimensions and their cross-sectional and longitudinal predictors. METHOD: The relationship between QOL, as measured by the Lancashire Quality of Life Profile (LQL), and demographic variables, diagnosis, psychopathology, disability, functioning, affect balance, self-esteem, service use and service satisfaction was investigated at two points in time, using factor analysis and multiple regression techniques. RESULTS: One subjective and two objective LQL factors with strong face validity were identified. Cross-sectional predictors of the subjective factor were primarily subjective measures; longitudinally, few predictors of this factor were identified. The cross-sectional and longitudinal predictors of the objective factors were primarily demographic and observer-rated measures. CONCLUSIONS: Subjective and objective data are distinct types of information. Objective measures may be more suitable in detecting treatment effects. Subjective information is necessary to complete the QOL picture and to enhance the interpretation of objective data.
BACKGROUND: Both subjective and objective information is necessary to assess quality of life (QOL). AIMS: To explore the role of subjective and objective QOL dimensions and their cross-sectional and longitudinal predictors. METHOD: The relationship between QOL, as measured by the Lancashire Quality of Life Profile (LQL), and demographic variables, diagnosis, psychopathology, disability, functioning, affect balance, self-esteem, service use and service satisfaction was investigated at two points in time, using factor analysis and multiple regression techniques. RESULTS: One subjective and two objective LQL factors with strong face validity were identified. Cross-sectional predictors of the subjective factor were primarily subjective measures; longitudinally, few predictors of this factor were identified. The cross-sectional and longitudinal predictors of the objective factors were primarily demographic and observer-rated measures. CONCLUSIONS: Subjective and objective data are distinct types of information. Objective measures may be more suitable in detecting treatment effects. Subjective information is necessary to complete the QOL picture and to enhance the interpretation of objective data.
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