Abstract
Although a significant amount of research has provided insight into predicting future turnover, it has not aided in understanding the impact of alternative outcomes to turnover, such as alternative withdrawal or intentions to reduce job inputs, have on nurses' work attitude as they function within their day-to-day work role. The on-going pressures to improve healthcare quality and decrease costs supports the need to study the alternative withdrawal process—so as to move beyond merely retaining registered nurses to retaining fully engaged registered nurses. Therefore, the primary intent of this study was to consider an alternative outcome to turnover occurring within the turnover process.
This study was a descriptive, cross-sectional survey design. The main variables and instruments used were: work engagement (UWES-9), job satisfaction (IWS), turnover cognitions (TCS), job search behavior (JSBI), and nurse demographics.
Sigma Membership
Non-member
Type
Dissertation
Format Type
Text-based Document
Study Design/Type
Cross-Sectional
Research Approach
Qualitative Research
Keywords:
Occupational Psychology, Alternative Withdrawal Process, Engaged Nursing Workforce
Advisor
Susan Dean-Baar
Second Advisor
Mark A. Mone
Degree
PhD
Degree Grantor
University of Wisconsin-Milwaukee
Degree Year
2007
Recommended Citation
Simpson, Michelle R., "The relationship between registered nurses' turnover cognitions, job satisfaction, job search behaviors, selected nurse characteristics and work engagement" (2023). Dissertations. 1543.
https://www.sigmarepository.org/dissertations/1543
Rights Holder
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All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
None: Degree-based Submission
Acquisition
Proxy-submission
Date of Issue
2023-08-07
Full Text of Presentation
wf_yes
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 3279104; ProQuest document ID: 304783298. The author still retains copyright.