Abstract

The United States is facing an imminent nurse staffing crisis. An aging workforce, an increasing elder population, and new staffing legislation have added to existing difficulties in retaining nurses. Retaining nurses is a priority in emergency departments, one of the few specialty departments that exceed the national average turnover rate, with an average of 95% of the nursing staff leaving their positions every five years.

This dissertation used dual-factor theory, dimensions of nursing surveillance, and intersectionality as theoretical frameworks; employed secondary analysis of the National Sample Survey of Registered Nurses (2018) dataset; and utilized hierarchical regression Modeling to examine the relative impact of workplace factors, educational factors, and key demographic variables on nurses' intention to leave their position for three groups, including emergency nurses, from a national sample. Given the findings of this dissertation, recommendations are made that can facilitate the development of targeted solutions to improve nursing retention.

Description

This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 28869168; ProQuest document ID: 2621218587. The author still retains copyright.

Author Details

Scott P. Kaye, PhD, RN-BC, CEN, CPEN, TCRN CCRN-K, CJCP, NPD-BC, NHDP-BC, AMB-BC, NEA-BC, FACHE

Sigma Membership

Non-member

Type

Dissertation

Format Type

Text-based Document

Study Design/Type

Other

Research Approach

Other

Keywords:

Nurse Turnover Intentions, Intention to Leave, Nursing Retention, Nurse Attrition

Advisor

Juan Battle

Second Advisor

Barbara DiCicco-Bloom

Third Advisor

Jessie Daniels

Degree

PhD

Degree Grantor

The City University of New York

Degree Year

2022

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

All permission requests should be directed accordingly and not to the Sigma Repository.

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

2022-03-28

Full Text of Presentation

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