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  • 學位論文

臺灣COVID-19疫情爆發期間前線護理人員之壓力與因應、復原力及悲憫疲憊相關性研究

The Correlation of Stress and Coping, Resilience, and Compassion Fatigue of Nurses Staying on Front-line during COVID-19 Outbreak in Taiwan

指導教授 : 邱飄逸

摘要


背景與目的:嚴重特殊傳染性肺炎(COVID-19)疫情期間,第一線護理人員長時間投入高風險的照護工作,極高的照護負荷,使其暴露於悲憫疲憊(compassion fatigue)高風險之下。堅守照護前線的護理人員面臨何種壓力源?運用何種壓力因應與復原力來調解悲憫疲憊的程度?現階段國內仍缺乏相關研究。本研究之目的在了解2021年5月後COVID-19社區疫情爆發期間,北部前線護理人員在提供確診者照護時所面臨之壓力源、壓力調適、復原力與悲憫疲憊之現況與其相關性。 研究方法:透過橫斷式(cross-sectional)研究設計,以立意取樣(purposive sampling)與滾雪球方式,於北部某醫學中心針對疫情期間曾經或目前仍持續照護COVID-19確診者之臨床護理人員進行收案。以自擬醫療人員COVID-19壓力源量表、護理職場壓力源與因應量表、短版復原力量表及悲憫疲憊簡版量表作為工具,透過線上填答方式收集資料。有鑑於壓力源及悲憫疲憊間存在多重影響因子,本研究以多重串聯式中介模型(serial multiple mediation model)作為架構,進一步分析復原力和不同的壓力因應模式在其中所表現的中介效應。 結果:共215位研究對象,平均年齡34.59歲(SD = 8.62),學歷以專科及大學畢業(92.6%)為多,臨床工作年資平均11.60年(SD = 8.15)。整體而言,前線護理人員之壓力源平均為3.24(SD = 1.033)分,介於高度和極高壓力之間,主要採取投入式問題導向之因應,有中度的復原力及悲憫疲憊程度。以不同年齡、學歷、收入、疫情期間是否與家人親友同住、過去之照護經驗及離職意願進行分組比較,發現存在不同程度的壓力源、因應模式、復原力及悲憫疲憊。序列中介分析結果發現,COVID-19壓力源程度對悲憫疲憊程度之直接效果顯著(B = 0.1272, p < 0.001, 95% CI [0.0985, 0.1560]),情緒導向壓力因應模式和復原力兩者交互作用下可中介調節護理人員因面臨COVID-19相關壓力源而導致的悲憫疲憊,且序列中介效果達統計上之顯著。 結論:情緒導向壓力因應模式和復原力可調節因疫情壓力產生的悲憫疲憊,從而強化心理韌性;而本研究亦深入了解前線護理人員之特質與壓力相關影響因素,可做為未來臨床人員心理健康介入措施之基礎。

並列摘要


Background: During the coronavirus disease 2019 (COVID-19) pandemic, front-line nurses are under a high burden of care, which causes heavy stressor and affects their psychological well-being. Nurses are prone to compassion fatigue after constantly offering support to comfort patients. Nevertheless, many nurses are still willing to stay at the forefront. What stressor and stress level and compassion fatigue level do these nurses have, and what coping models and self-healing process did they go through? The relevant research in Taiwan is limited. This research aimed to determine the relationship between COVID-19-related stressors, stress level, compassion fatigue, resilience status, and preferences of coping models among front-line nurses. Method: A cross-sectional survey via an online questionnaire was conducted from February 2021 to April 2021. Purposive and snowball sampling were applied to recruit the participants who were or are still continuing to care for patients diagnosed with COVID-19. The questionnaires included the self-administered COVID-19-Related Stress Scale, Nursing Workplace Stressors and Coping Scale (NWSCS), 14-item Resilience Scale (RS-14), and Compassion Fatigue Short Scale (CFSS). In view of the existence of mediators between stress and compassion fatigue, this study uses a serial multiple mediation model as a framework to analyze the mediating effects of resilience and coping models. Result: A total of 215 participants were included in the study, the average age was 34.59 years (SD=8.62); most of whom graduated from college or university (92.6%), and had an average working experience of 11.60 years (SD=8.15). Overall, the average stress level of front-line nurses was 3.24 (SD = 1.033) points, ranging between high and very high stress; they mainly adopted the immersive problem-oriented coping model, and had moderate level of resilience and compassion fatigue. Subgroups comparison were made based on age, education, income, whether living with family and friends during the epidemic, past care experience and willingness to leave; and the results revealed that, there were different levels of stressors, coping models, resilience, and compassion fatigue between these subgroups. The results of sequentially mediating effects reveled that the level of COVID-19 stressors had a significant direct effect on the level of compassion fatigue (B = 0.1272, p < 0.001, 95% CI [0.0985, 0.1560]). The emotion-oriented stress coping model and resilience concurrently and significantly mediated the compassion fatigue level of front-line nurses due to COVID-19-related stress. Conclusion: Emotion-oriented stress coping model and resilience can regulate compassion fatigue caused by the stress of COVID-19 epidemic. The results could be used to design the supportive interventions to improve the mental health of COVID-19 front-line nurses.

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