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Compassion fatigue is a professional psychological problem caused by long-term work pressure, resulting in emotional exhaustion and a decline in empathy ability. It not only leads to individual symptoms such as sleep disorders and anxiety, but also increases clinical errors, reduces work efficiency, and causes the loss of medical talents. It has become a common challenge faced by medical staff worldwide. In the international medical system, midwives, as the core force safeguarding the health of mothers and infants, are working in an increasingly complex and high-pressure environment. Midwives, due to their continuous engagement of a large amount of emotional labor and frequent exposure to multiple pressures such as traumatic events during childbirth, obstetric emergency complications, and occupational exposure, have become a high-risk group for compassion fatigue.
The causes of compassion fatigue among midwives are complex and diverse. Moreover, most of the existing assessment tools for compassion fatigue are universal assessment scales, and the unique risks of midwives' work have not yet been highlighted and reflected. Therefore, it is urgent to establish an compassion fatigue assessment tool specifically for the midwife population, so as to accurately and efficiently identify the compassion fatigue status of midwives, provide a reference for managers to grasp the current situation of compassion fatigue among midwives, and formulate efficient and targeted management and take corresponding intervention measures, thereby effectively reducing the incidence of empathy fatigue among midwives.
This study summarized the factors that may affect the occurrence of compassion fatigue among midwives through literature review and clinical practice, conducted a cross-sectional study to explore the influencing factors of compassion fatigue among midwives, and established a nomogram prediction model, with the aim of helping clinical managers simply and quickly screen out high-risk groups of compassion fatigue It provides a reference basis for taking targeted and preventive management measures at an early stage.
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Data sourced from clinicaltrials.gov
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