In an Idaho-based hospital, the registered nurse (RN) turnover rate in the float pool was excessively high. The purpose of this project was to examine the effect of Appreciative Inquiry (AI) on a RN's sense of community (SOC) in a float pool and an RN's intent to stay employed after attending an AI event. Although much had been written about nursing retention, AI, and SOC separately, there was nothing on how AI could be used to increase a RN's SOC or intent to stay employed. AI is a change management framework that has been used to engage employees in a meaningful way. The goal of this project was to engage RN float staff in a 6-hour AI workshop to generate ideas on improving the work environment. The SOC theory by McMillan and Chavis provided the context for measuring RN perception. It was anticipated that participation would lead to an increased SOC and an increased likelihood of staying employed in the float pool. The Sense of Community Index 2 survey was administered pre and postworkshop to a convenience sample of RNs (n = 22) recruited from the float pool. Additionally, RNs were asked before and after the workshop how likely they were to leave their current position in the next 12 months. Data analysis was a paired t test based on a 1-group pretest and posttest design. Demographic data were collected to describe the sample population. The results, although not statistically significant, showed both an increased SOC and an increased intent to leave following the AI workshop. The findings show that AI may be useful for increasing SOC. However, as a tool for nursing retention, both AI and SOC require better understanding. It is hoped this study will provide leaders with a starting point for further investigation into how AI and SOC can be used to improve the nursing work experience.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2253 |
| Date | 01 January 2015 |
| Creators | Buck, Janet |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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