scholarly journals Quality of life in systemic sclerosis: Psychometric properties of the World Health Organization Disability Assessment Schedule II

2008 ◽  
Vol 59 (2) ◽  
pp. 270-278 ◽  
Author(s):  
Marie Hudson ◽  
Russell Steele ◽  
Suzanne Taillefer ◽  
Murray Baron ◽  
2008 ◽  
Vol 59 (2) ◽  
pp. 279-284 ◽  
Author(s):  
Marie Hudson ◽  
Brett D. Thombs ◽  
Russell Steele ◽  
Rita Watterson ◽  
Suzanne Taillefer ◽  
...  

2007 ◽  
Vol 29 (3) ◽  
pp. 254-257 ◽  
Author(s):  
Maria da Graça Castro ◽  
Margareth da Silva Oliveira ◽  
Alessandra Cecília Miguel ◽  
Renata Brasil Araujo

OBJECTIVE: To study the World Health Organization Quality of Life Instrument Bref psychometric properties in a sample of smokers. It is a self-administered instrument to evaluate quality of life. It contains 26 questions allocated to 4 domains: Social, Psychological, Physical and Environmental, there are 2 questions related to the Global domain. METHOD: The sample was formed by 276 tobacco users selected at random. The instruments applied were: World Health Organization Quality of Life Instrument Bref, Fagerström Test for Nicotine Dependence, and Medical Outcomes Study Short-Form 36-item. The statistical analysis was accomplished up by ANOVA, Cronbach's alpha, Pearson's Coefficient and Multiple Regression. RESULTS: The World Health Organization Quality of Life Instrument Bref presented good reliability (Cronbach's alpha 0.9207), converging validation (0.382 < r < 0.753; p < 0.001), discriminant validation and criterion validation (0.554 < r < 0.778; p < 0.001). CONCLUSION: The World Health Organization Quality of Life Instrument Bref proved to be an adequate instrument, with a good level of reliability, being easily and quickly administered.


Medicina ◽  
2009 ◽  
Vol 45 (6) ◽  
pp. 493 ◽  
Author(s):  
Miglė Bacevičienė ◽  
Regina Rėklaitienė

This study aimed to identify psychometric properties of the World Health Organization Quality of Life 100 questionnaire. Material and methods. A random sample of 1403 Kaunas city men and women aged 35–64 years was examined in 2001–2002. Quality of life was assessed by the self-administered World Health Organization Quality of Life 100 questionnaire. Statistics. Scores of all domains and facets of the questionnaire were transformed to reflect a scale from 0 to 100. The validity and reliability of the questionnaire were evaluated by Pearson’s correlation coefficients and by Cronbach’s α. The relationship between the WHOQOL-100 domains and the two general items (G1 and G4) was assessed using linear regression analysis. Exploratory factor analysis was conducted to explore the factor structure of the data. Results. The mean scores of the World Health Organization Quality of Life 100 questionnaire domains ranged from 51.3±15.1 (overall quality of life) to 72.0±16.4 (level of independence domain). The instrument displayed acceptable Cronbach’s α (0.77–0.91) and test-retest reliability (0.64–0.89). The overall assessment of quality of life (G1) was most strongly associated with the environment (β=0.31), psychological (β=0.18), and social relationships (β=0.17) domains. Overall health (G4) showed the strongest association with the level of independence (β=0.34) and physical (β=0.18) domains. The principal component analysis revealed five-factor solution, which accounted for 57.7% of a total variance. Conclusion. In the Lithuanian population, the World Health Organization Quality of Life 100 questionnaire was found to be a suitable instrument for evaluating quality of life.


Autism ◽  
2021 ◽  
pp. 136236132110518
Author(s):  
Jacqui Rodgers

The purpose of this letter to the editors is to highlight to the readership of Autism the recommended use of the Autism Quality of Life measure (ASQoL) for research with autistic adults. The ASQoL was developed for use alongside the World Health Organization Quality of Life – Bref (WHOQOL-Bref) and the World Health Organization disabilities module. The letter raises some concerns about the use of the ASQoL as a standalone measure in a recent study by Caron et al. published in Autism. Lay abstract This letter to the editors discusses the use of the ASQoL for research with autistic adults. The autism quality of life measure was developed for use alongside two existing measures of quality of life developed by the World Health Organization. It was not developed as a questionnaire to be used in its own. The letter raises some concerns about the use of the autism quality of life measure as a standalone measure in a recent study by Caron et al., published in Autism.


Geriatrics ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 102
Author(s):  
Margarida Goes ◽  
Manuel José Lopes ◽  
João Marôco ◽  
Henrique Oliveira ◽  
César Fonseca ◽  
...  

The aim of this study was to evaluate the psychometric qualities of the WHOQOL-BREF(PT) (the questionnaire developed by the World Health Organization Quality of Life Grpup for quality of life assessment), when applied to Portuguese elderly people residing in a community setting. The psychometric qualities were assessed by confirmatory factor analysis. A hierarchical second-order model and a third model were performed, and all three models presented similar and reasonable adjustment indexes. The data analysis showed that the construct failed only regarding discriminant validity because the correlations between the first-order factors were higher, associated with lower values of average variance extracted. The psychometric qualities found in the original translation/validation of the WHOQOL-BREF(PT) were compared with those found in this study; this study found higher correlations between domains but a similar level of factor reliability. The findings of this study lead to three recommendations: (i) to compute each factor score for each participant using the factor score weights obtained from confirmatory analysis models instead of adopting a unitary weight for each item, as proposed by the authors of the original translation/validation of the WHOQOL-BREF(PT); (ii) to compute a QOL score, which is not included in the original translation/validation; and (iii) to analyze differences between individual scores for each participants, which should be done by a group of health experts.


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