Parallel analysis and MBI-HSS: How many factors?
Abstract
It has been only recently possible to validate the Maslach Burnout Inventory-Human Services Survey (MBI-HSS)1 among health professionals of Cali2, an important step for using this instrument with local empirical support in regard to its reliability of scoring and internal structure. However, two aspects of this analysis can be considered as methodological weaknesses. First, the Cronbach alpha coefficient was calculated for the total group of items, and this is absolutely inappropriate because: a)the authors did not demonstrate empirical support for accomplishing this (e.g., a hierarchical factor analysis), b) the literature indicates that factors in the MBI-HSS are generally independent, a characteristic also reported by Córdoba et al. 2,Authors
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Keywords
- MBI-HSS
- analisis factorial
- burnout
References
Maslach C, Jackson, S. Maslach Burnout Inventory-Human Services Survey (MBI-HSS). En: Maslach C, Jackson, S. Leiter M (eds.). Maslach Burnout Inventory Manual. Mountain View: Consulting Pschologists Press; 1996.
Córdoba L, Tamayo J, González M, Martinez M, Rosales A, Barbato S. Adaptation and validation of the Maslach Burnout Inventory-Human Services Survey in Cali, Colombia. Colomb Med. 2011; 42(3): 286-293.
Hayton JC, Allen DG, Scarpello V. Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organ Res Meth. 2004; 7(2): 191-205.
Dinno A. Exploring the sensitivity of Horn’s parallel analysis to the distributional form of random data. Multivariate Behav Res. 2009; 44(3): 362–88.
Watkins, M. W. (2000). Monte Carlo PCA for Parallel Analysis [computer software]. State College, PA: Ed & Psych Associates.
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