The literature is replete with studies and information about registered nurse burnout, compassion fatigue, and turnover rates. Registered nurses enhance and bring benefits to the health care system, but stressful health care environments may contribute to their self-neglect and may adversely affect their decision to remain working at the bedside. Retention of registered nurses is necessary for the delivery of patient care. An investigation of self-compassion among registered nurses in the clinical workplace may help to understand how registered nurses deal with the pressures of the health care setting. In addition, there is a need for research to clarify what self-compassion looks like among nurses and how it may foster caring for themselves, nurse retention, and the delivery of quality patient care.
This qualitative study used a phenomenological method designed to illuminate registered nurses’ experiences of self-compassion in clinical practice. Also, findings from this study will contribute to the body of knowledge of self-compassion in the context of registered nurses. Van Manen’s phenomenological research method of the six activities were used to guide the study. Nine registered nurses were interviewed about their experiences of being kind and compassionate toward oneself in the clinical work setting. Transcripts of the study participants’ interviews were analyzed and four essential themes emerged that shed light on these nurses’ experiences of self-compassion: (1) Transforming Time Famine; (2) Authentic Communication and Presence, (3) Collegial Cohesion, and (4) Evolution Toward an Ideal Registered Nurse. Most of the participants in this study shared stressful situations in the clinical workplace along with encouraging learning points through their stories of being kind to themselves in the workplace while caring for others.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-06me-np18 |
Date | January 2019 |
Creators | McPhee, Caiocimara Braga |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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