gms | German Medical Science

MAINZ//2011: 56. GMDS-Jahrestagung und 6. DGEpi-Jahrestagung

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V.
Deutsche Gesellschaft für Epidemiologie e. V.

26. - 29.09.2011 in Mainz

Predictors of self-reported burnout in nurses: work-related vs. individual factors in the European longitudinal Nurses' Early Exit-Study (NEXT). Comparing national differences and multivariate models

Meeting Abstract

  • Juliane Hardt - Bergische Universität Wuppertal, Institut für Sicherheitstechnik, Bereich Empirische Arbeitsforschung, Wuppertal
  • Michael Galatsch - Bergische Universität Wuppertal, Institut für Sicherheitstechnik, Fachgruppe Pflegeforschung, Wuppertal
  • Sascha Gerd Schmidt - Bergische Universität Wuppertal, Institut für Sicherheitstechnik, Fachgruppe Pflegeforschung, Wuppertal
  • Bernd Hans Müller - Bergische Universität Wuppertal, Fachgebiet Arbeitssicherheit/Ergonomie, Institut für Sicherheitstechnik, Wuppertal

Mainz//2011. 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi). Mainz, 26.-29.09.2011. Düsseldorf: German Medical Science GMS Publishing House; 2011. Doc11gmds268

DOI: 10.3205/11gmds268, URN: urn:nbn:de:0183-11gmds2681

Published: September 20, 2011

© 2011 Hardt et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Background: The demographic changes in Europe cause an increasing need of qualified nursing staff. Therefore, it is important to develop concepts for maintaining a high work ability and motivation of the nursing workforce based on risk factor models. Previous results from the NEXT study have indicated that the individual risk of burnout is an important prognostic factor of the intention to leave nursing [1], [2]. The aim of this analysis was to investigate the associations of sociodemographic, individual and work-related factors with burnout measures one year later among nurses in Europe using questionnaire data of a longitudinal study.

Method: Longitudinal data of 8877 qualified nurses and nursing aids in Germany (n=1639), Finland (n=2335), Italy (n=2314), the Netherlands (n=952), Poland (n=1223) and Slovakia (n=414) from the NEXT study were available for analyses [3]. The questionnaire comprised sociodemographic and institutional factors, nine work-related factors as well as individual factors (overcommitment [4], positive and negative affectivity [5]) that may be associated with burnout. The subjective extent of burnout symptoms was assessed with the scale "personal burnout" (Copenhagen Burnout Inventory [6], [7] at baseline and at one-year follow-up. Uni- and multivariate linear regression analyses were applied to analyze four models of factor groups with increasing model complexity in comparison of the 6 countries.

Results: Differences in the reported extent of individual and work-related indicators and differences between the prediction models of the six countries were remarkable. Mean levels of burnout measures were lowest in Dutch nurses who also reported better social support, and lower levels of work-family conflict, individual overcommitment and negative affectivity. A model optimizing strategy (stepwise method) with four consecutive linear regression models was applied. Sociodemographic and institutional factors had no effects (R²corr:.004-.051). Individual factors showed substantial effects for five of the six countries (∆R²corr:.115-.251;MD=.172); in contrast to work-related factors (∆R²corr:-.008-.029;MD=.034). When the models were adjusted for burnout level in the first year, model-fit indices again slightly increased (∆R²corr:.075-.202;MD=.180). Models were best predictive for the German and least predictive for the Polish sample.

Discussion: Our results show individual factors to be important predictors for burnout scores of nurses one year later. These findings were supported by the literature of burnout research [8], [9], [10], [11]. However, problems of type III error also need to be considered [cf. [12], [13], [14], [15]. Further analyses should be extended to model specific interaction effects of individual and work-related factors. Such models will provide further evidence for predictor models as well as preventional and interventional concepts.


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