Attractiveness of Nursing Homes for Nurses in Relation to Work Environment and Health and Attitudinal Outcomes: Results from the German 3Q-Study

Thursday, 15 July 2010: 4:05 PM

Sascha G. Schmidt, MScN, RN1
Rebecca Palm, RN1
Martin Dichter, BScN, RN1
Bernd H. Müller, Prof, Dr2
Hans Martin Hasselhorn2
1Institute for Safety Technology – Nursing Research Group, University of Wuppertal, Wuppertal, Germany
2Institute for Safety Technology, University of Wuppertal, Wuppertal, Germany

Learning Objective 1: identify the potential of work stressors with adverse consequences on attitudinal and behaviour intentional factors as well as psychological health for nurses.

Learning Objective 2: know what is important in the field of work environment for nurses for further research.


Worldwide, increasing need for long term care and nursing shortage constitute major challenges for nursing homes (NH). Consequently, it will be crucial for NH to present an attractive work environment for nurses. The objective of this study is to investigate work organisational core factors and their association with the attractiveness of NH for nurses in Germany.

Methods: Cross-sectional data (n=738) from a self-report questionnaire for nurses and auxiliary staff in 42 NH from the German 3Q-study ( was used. An Attractiveness –Index (AI) was calculated by means of the COPSOQ “Job Satisfaction” scale and the nurses’ own perception of “Satisfaction with Quality of Care in their NH” (own scale). A multivariate linear regression analysis and ANOVA with Bonferroni post hoc tests were performed for investigating AI in relation to aspects of work (content and organisation) and to outcomes such as health, work-ability, burnout and “intent to leave the institution”.


Analyses revealed large differences in the attractiveness of a NH. Main factors in the multivariate model were “quantitative demands” (β=-.236, p<.001) and “time for conversation with resident” (β=-213, p<.001) (multivariate model R²=.64). No association was found for “emotional demands” or “lifting/bending”. Nurses from NH with a good overall AI reported less burnout, better health and less intent to leave the institution.

Conclusion: The association of AI with work factors and health and attitudinal factors was expected. The strength of it, however, indicates the high relevance AI has for NH staffing. The results imply that some work factors strongly influence NH attractiveness for nurses and that attractiveness may have consequences on the psychological health and the staff turnover. Here, intervention seems possible and further research is needed.