Mats T Gullberg1, Gunilla Hollman-Frisman, Anna-Christina Ek. 1. Faculty of Health Sciences, Department of Medical and Health Sciences, Division of Nursing Science, Linköping University, 581 83, Linköping, Sweden. mats.gullberg@liu.se
Abstract
PURPOSE: The aim in the present study was to establish underlying dimensions of quality of life in Sweden, measured by QLI, and to obtain reference values among a representative sample between 18 and 80 years of age from the general Swedish population. METHOD: A total of 1,680 randomly selected persons completed the questionnaire (57% response rate). All data were coded and entered into the statistical software. Factor analysis, maximum-likelihood method with oblique rotation, was employed to explore and reveal underlying dimensions of the QLI. To describe QLI total and subscale reference values for different age groups and men and women, respectively, means and 95% CI as well as medians and quartiles were used. For comparisons related to demographic and background variables, parametric and non-parametric analyses were used (alpha=0.01). All data were analysed using SPSS 14.0 statistical software. RESULTS: Four underlying dimensions emerged: Family and friends, Health and functioning, Social and economic and Psychological/spiritual. Mean values for the total QLI and the four subscales ranged between 17.2 and 23.7 (possible range=0.0-30.0). CONCLUSIONS: The overall QLI and subscale scores correspond with those presented by other researchers. Population-based measures of generic quality of life and underlying dimensions are important considering the gain when results from specific patient groups are viewed.
PURPOSE: The aim in the present study was to establish underlying dimensions of quality of life in Sweden, measured by QLI, and to obtain reference values among a representative sample between 18 and 80 years of age from the general Swedish population. METHOD: A total of 1,680 randomly selected persons completed the questionnaire (57% response rate). All data were coded and entered into the statistical software. Factor analysis, maximum-likelihood method with oblique rotation, was employed to explore and reveal underlying dimensions of the QLI. To describe QLI total and subscale reference values for different age groups and men and women, respectively, means and 95% CI as well as medians and quartiles were used. For comparisons related to demographic and background variables, parametric and non-parametric analyses were used (alpha=0.01). All data were analysed using SPSS 14.0 statistical software. RESULTS: Four underlying dimensions emerged: Family and friends, Health and functioning, Social and economic and Psychological/spiritual. Mean values for the total QLI and the four subscales ranged between 17.2 and 23.7 (possible range=0.0-30.0). CONCLUSIONS: The overall QLI and subscale scores correspond with those presented by other researchers. Population-based measures of generic quality of life and underlying dimensions are important considering the gain when results from specific patient groups are viewed.