Invarianza factorial de una medida de burnout académico entre estudiantes universitarios de Perú, México y Colombia  <span class="so-article-trans-title" dir="auto"> Translated title: Factorial invariance of an academic burnout measure among college students from Peru, Mexico and Colombia </span>

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Resumen El objetivo de este estudio fue analizar la invarianza de medición de una escala de agotamiento emocional académico entre estudiantes universitarios de Perú (n = 472; 76.059% mujeres; Medad= 20.636), México (n = 362; 66.298% mujeres; Medad = 21.063) y Colombia (n = 288; 88.194% mujeres; Medad = 21.780). La estructura interna se estudió con un análisis factorial confirmatorio para comprobar la unidimensionalidad de la Escala de Cansancio Emocional (ECE) en cada muestra, y la invarianza del modelo fue analizada con un análisis factorial multigrupo. Los resultados mostraron que el modelo unidimensional obtiene evidencias favorables en cada muestra respecto a sus cargas factoriales y confiablidad, y es invariante entre las muestras en su estructura (invarianza configural),cargas factoriales (invarianza métrica), thresholds (invarianza fuerte) y residuales (invarianza estricta). Aunque se necesita investigación adicional, el ECE parece ser una medida prometedora para su uso con estudiantes universitarios colombianos, mexicanos y peruanos.

Translated abstract

Abstract The aim of this study was to analyze the measurement invariance of a scale of academic emotional exhaustion among university students in Peru (n = 472; 76.06% women; Mage = 20.64), Mexico (n = 362; 66.3% women; Mage = 21.06), and Colombia (n = 288; 88.19% women; Mage = 21.78). The internal structure was analyzed with a confirmatory factor analysis in order to verify the single dimensionality of the Emotional Exhaustion Scale (ESS) in each sample, whereas the model’s invariance was analyzed with a multi-group factor analysis. The results showed that the one-dimensional model shows favorable evidence in each sample regard their factor loadings and reliability, and it was invariant across countries regarding its structure (configural invariance), factor loadings (metric invariance), thresholds (strong invariance), and residuals (strict invariance). Although additional research is needed, the ECE appears to be a promising measure to use among Peruvian, Mexican, and Colombian college students.

Related collections

Most cited references 90

Record: found
Abstract: found
Article: not found

A power primer.

Jacob Cohen (1992)

One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.