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      Evaluation of the Functional Assessment of Cancer Therapy-General (FACT-G) Spanish Version 4 in South America: Classic Psychometric and Item Response Theory Analyses


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          The FACT-G has gone through many validation studies. However, little research has been conducted in South American Spanish speaking patients. The present study aimed to evaluate the FACT-G Spanish Version 4 in Uruguayan cancer patients.


          The data analyzed were collected from 309 patients, with various tumor sites, at different stages of disease and receiving different treatments.


          Reliability was evaluated using Cronbach's coefficient alpha and showed high internal consistency for each of the subscales and its total scale (range = .78 – .91) of the FACT-G. The FACT-G total score also showed significant mean differences among known groups (performance status, in vs. outpatients) when tested by ANOVA and t-test. When the tumor stage (Local and Regional vs. Metastatic disease) was used as a clinical anchor, the FACT-G total score, the Physical Well-being (PWB), and Functional Well-being (FWB) subscale scores showed mean differences, ranging from 5 to 10 points in a scale from 0–108 (effect sizes = 0.30–0.60). Item response theory (IRT)-based evaluation using mean square fit statistics (.60–1.4) criteria showed that only two items misfit: "Estoy satisfecho(a) con mi vida sexual" (I am satisfied with my sex life) and "Estoy satisfecho(a) de cómo estoy enfrentando mi enfermedad" (I am satisfied with how I am coping with my illness).


          The results indicated that, using both traditional and IRT approaches, the Spanish FACT-G has good reliability and validity to be used as a QOL instrument among Uruguayan cancer patients.

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          Most cited references31

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          A new scale of social desirability independent of psychopathology.

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            Graded Response Model

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              Methods to explain the clinical significance of health status measures.

              One can classify ways to establish the interpretability of quality-of-life measures as anchor based or distribution based. Anchor-based measures require an independent standard or anchor that is itself interpretable and at least moderately correlated with the instrument being explored. One can further classify anchor-based approaches into population-focused and individual-focused measures. Population-focused approaches are analogous to construct validation and rely on multiple anchors that frame an individual's response in terms of the entire population (eg, a group of patients with a score of 40 has a mortality of 20%). Anchors for population-based approaches include status on a single item, diagnosis, symptoms, disease severity, and response to treatment. Individual-focused approaches are analogous to criterion validation. These methods, which rely on a single anchor and establish a minimum important difference in change in score, require 2 steps. The first step establishes the smallest change in score that patients consider, on average, to be important (the minimum important difference). The second step estimates the proportion of patients who have achieved that minimum important difference. Anchors for the individual-focused approach include global ratings of change within patients and global ratings of differences between patients. Distribution-based methods rely on expressing an effect in terms of the underlying distribution of results. Investigators may express effects in terms of between-person standard deviation units, within-person standard deviation units, and the standard error of measurement. No single approach to interpretability is perfect. Use of multiple strategies is likely to enhance the interpretability of any particular instrument.

                Author and article information

                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                20 August 2003
                : 1
                : 32
                [1 ]Departamento de Psicología Médica, Facultad de Medicina – Universidad de la República, Uruguay
                [2 ]Departamento de Biofísica, Facultad de Medicina – Universidad de la República, Uruguay
                [3 ]Buehler Center on Aging, Center for Healthcare Studies, Division of General Internal Medicine, and the Department of Medicine, Feinberg School of Medicine, Northwestern University, Illinois, USA
                [4 ]Departamento de Oncología Clínica, Facultad de Medicina – Universidad de la República, Uruguay
                Copyright © 2003 Dapueto et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.

                Health & Social care
                Health & Social care


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