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El método Statis como alternativa para detectar "response shift" en estudios de calidad de vida relacionada con la salud

    1. [1] Universidad de Salamanca

      Universidad de Salamanca

      Salamanca, España

  • Localización: Revista de Matemática: Teoría y Aplicaciones, ISSN 2215-3373, ISSN-e 2215-3373, Vol. 16, Nº. 1, 2009, págs. 1-15
  • Idioma: español
  • DOI: 10.15517/rmta.v16i1.1415
  • Enlaces
  • Resumen
    • español

      Evaluar la Calidad de Vida de los pacientes es dif´?cil porque junto al cambio real(alpha) muchos pacientes que experimentan un cambio en su salud (diagnostico dec´ancer, por ejemplo), pueden cambiar sus est´andar internos de medida (recalibraci´on),sus valores (repriorizaci´on), o incluso reconceptualizar lo que antes entend´?an por Calidadde Vida (Cambios Beta y Gamma). Este fen´omeno es conocido como “ResponseShift” y justifica la paradoja descrita en la literatura por la cual pacientes con gravesproblemas de salud perciben una Calidad de Vida m´as alta de la estimada por m´edicosy familiares.En este trabajo, despu´es de evaluar los problemas existentes a la hora de definir elconstructo Calidad de Vida, centramos la atenci´on en las dimensiones del ResponseShift. Se discuten las limitaciones del m´etodo cl´asico de Ahmavaara y se proponensoluciones para detectar y evaluar las componentes Beta y Gamma del Response Shift.Palabras clave: Calidad de Vida, Response Shift, cambio Beta, cambio Gamma, m´etodoStatis Dual.

    • English

      After evaluating problems in conceptualisation of Quality of Life outcomes andestablishing an operational definition of HRQoL, we focus the attention on the different dimensions of Response Shift and the theoretical Models to explaining it. We payspecial attention to Schwartz and Sprangers Model.If Gamma change is present, the construct under assessment is not stable forthe patient; so it has no sense to compare scores because if an individual changesconceptualization of QoL over the course of time, then answers to the same items bythe same individual may not be as comparable over time as originally thought. So, itis crucial to capture Response Shift before Alpha change is evaluated.The analytical approaches to assess Response Shift are discussed, paying specialattention to the statistical aspects. We found several shortcomings of Ahmavaara’sMethod for comparing factorial structures and we have developed some alternativesto capture Beta and Gamma components of Response Shift.Keywords: Health Related Quality of Life (HRQoL), Response Shift, Beta change,Gamma change, Dual Statis method.

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