Listado de sÃntomas breve (short checklist of symptoms) in Argentinean adults: psychometric study of its main clinical scales
AbstractThe main objective of this research was studying the psychometric properties of the Listado de sÃntomas breve (short checklist of symptoms; LSB-50) in a sample of 994 Argentinean adults (49.9% females; 50.1% males). Mean age was 40.66 years (standard deviation= 17.01; Min=18; Max=89). This screening test has seven main clinical scales: hypersensitivity, obsessive-compulsive, anxiety, hostility, somatization, depression, and sleep disturbance. Pearson correlations indicated that all scales had positive and mostly moderate associations. The second order confirmatory factor analysis showed a good fit for a hierarchical model where all scales loaded in one major factor. Internal consistency by Cronbachâ€™s alpha was adequate. Females scored significantly higher than males in all scales except for the hostility scale, in which no differences were found. Although statistically significant associations with age were found in some scales, correlations were very weak. Obsessive-compulsive, sleep disturbance and depression scales had the highest scores, while anxiety presented the lowest score. Based on the psychometric evidence found, the scale seems to be suitable for the local population. Consequently, the availability of such measure may contribute to conduct epidemiological studies of psychopathology in Argentina. Moreover, the scale could be used for the assessment of psychotherapy progress and outcomes of clients, as well as for psychotherapy research. Notwithstanding, more evidence of validity and reliability should be sought.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2016 Guadalupe de la Iglesia, Juliana Beatriz Stover, Mercedes FernÃ¡ndez Liporace, Alejandro Castro Solano
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.