Sick Leave and Intention to Quit the Job among Nursing Staff in German Hospitals during the COVID-19 Pandemic
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
In: International Journal of Environmental Research and Public Health 19.4 (2022): 1947.
- Event
-
Veröffentlichung
- (where)
-
Erlangen
- (who)
-
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
- (when)
-
2022
- Creator
-
Schug, Caterina
Geiser, Franziska
Hiebel, Nina
Beschoner, Petra
Jerg-Bretzke, Lucia
Albus, Christian
Weidner, Kerstin
Morawa, Eva
Erim, Yesim
- DOI
-
10.3390/ijerph19041947
- URN
-
urn:nbn:de:bvb:29-opus4-188772
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:29 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Schug, Caterina
- Geiser, Franziska
- Hiebel, Nina
- Beschoner, Petra
- Jerg-Bretzke, Lucia
- Albus, Christian
- Weidner, Kerstin
- Morawa, Eva
- Erim, Yesim
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Time of origin
- 2022
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Intergenerational transmission of long-term sick leave
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Effect of Partial Sick Leave on Sick Leave Duration in Employees with Musculoskeletal Disorders
Sick leave patterns in common musculoskeletal disorders – a study of doctor prescribed sick leave
Being on Sick Leave: Possible Explanations for Differences of Sick-leave Days Across Countries Privatization
The Market for Paid Sick Leave
Profiling the US Sick Leave Landscape
Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals
Intergenerational transmission of long-term sick leave
Sick leave before, during and after pregnancy
Predicting prolonged sick leave among trauma survivors
Validation of sick leave measures: self-reported sick leave and sickness benefit data from a Danish national register compared to multiple workplace-registered sick leave spells in a Danish municipality