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Cut-off point for WHOQOL-bref as a measure of quality of life of older adults

OBJECTIVE: To propose a cut-off for the World Health Organization Quality of Life-Bref (WHOQOL-bref) as a predictor of quality of life in older adults. METHODS: Cross-sectional study with 391 older adults registered in the Northwest Health District in Belo Horizonte, MG, Southeastern Brazil, between...

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Detalles Bibliográficos
Autores principales: Silva, Patrícia Aparecida Barbosa, Soares, Sônia Maria, Santos, Joseph Fabiano Guimarães, Silva, Líliam Barbosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Saúde Pública da Universidade de São Paulo 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4203073/
https://www.ncbi.nlm.nih.gov/pubmed/25119934
http://dx.doi.org/10.1590/S0034-8910.2014048004912
Descripción
Sumario:OBJECTIVE: To propose a cut-off for the World Health Organization Quality of Life-Bref (WHOQOL-bref) as a predictor of quality of life in older adults. METHODS: Cross-sectional study with 391 older adults registered in the Northwest Health District in Belo Horizonte, MG, Southeastern Brazil, between October 8, 2010 and May 23, 2011. The older adults’ quality of life was measured using the WHOQOL-bref. The analysis was rationalized by outlining two extreme and simultaneous groups according to perceived quality of life and satisfaction with health (quality of life good/satisfactory – good or very good self-reported quality of life and being satisfied or very satisfied with health – G5; and poor/very poor quality of life – poor or very poor self-reported quality of life and feeling dissatisfied or very dissatisfied with health – G6). A Receiver-Operating Characteristic curve (ROC) was created to assess the diagnostic ability of different cut-off points of the WHOQOL-bref. RESULTS: ROC curve analysis indicated a critical value 60 as the optimal cut-off point for assessing perceived quality of life and satisfaction with health. The area under the curve was 0.758, with a sensitivity of 76.8% and specificity of 63.8% for a cut-off of ≥ 60 for overall quality of life (G5) and sensitivity 95.0% and specificity of 54.4% for a cut-off of < 60 for overall quality of life (G6). CONCLUSIONS: Diagnostic interpretation of the ROC curve revealed that cut-off < 60 for overall quality of life obtained excellent sensitivity and negative predictive value for tracking older adults with probable worse quality of life and dissatisfied with health.