دانلود رایگان مقاله ساختار داخلی معیار جایگزین فرسودگی شغلی

ABSTRACT

This study evaluates the factorial validity and reliability of the Slovenian adaptation of the Oldenburg Burnout Inventory (OLBI) in a sample of 1436 Slovenian employees of various occupations. Confirmatory factor analyses were used to evaluate alternative structural models of OLBI, and reliability of variant scales was estimated. The results reveal a different structure of the Slovenian adaptation compared with the original one and a very notable difference in reliability between positively and negatively framed items. The results could be explained with a response bias or the specific nature of burnout and work engagement that OLBI promises to assess simultaneously. Therefore, we believe that the internal structure of the original inventory needs to be reconsidered.

4. Discussion

In the presented study we adapted the Oldenburg Burnout Inventory (OLBI) to Slovenian language and analyzed its internal structure in a sample of Slovenian employees. Previous research (e.g. Demerouti et al., 2003; Halbesleben & Demerouti, 2005) suggests that a two-factor model with exhaustion and disengagement fits to the data better than an alternative two-factor model with positively and negatively framed items. However, the results of our study are not in line with these findings. The positive/negativemodel and the four factormodel showed better model fitthan the proposed two factor model and the singlefactor model (Table 1). The latter two models appear unattractive from the psychometric viewpoint also because of low reliability and problematic dimensionality, which seems to be a problem of the four factor model, as well. The most suitable solution would therefore be the positive/negative wording model, which was the best fitting a priori model and has acceptable reliability. This finding agrees with Qiao and Schaufeli (2011) who reported poor fit of the proposed two factor model and the single-factor model, while positive/negative and four factor models fitted to the data better. Another option which was not originally considered by Demerouti et al. (2003) is negative two-factor model. This model includes only negatively framed items, which generally show higher reliability than the positive items, and fits the data slightly better than the positive/negative wording model. Nonetheless, this comparison should be taken with some precaution, since it is generally easier to achieve a good approximation to a low-dimensional structure with a smaller rather than a larger number of variables.