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系統識別號 U0026-2601201515020500
論文名稱(中文) 台灣護理人員疲潰:中文量表的驗證與預測因子檢測
論文名稱(英文) Burnout among Staff Nurses in Taiwan: Instrument Validation and Predictors Identification
校院名稱 成功大學
系所名稱(中) 健康照護科學研究所
系所名稱(英) Institute of Allied Health Sciences
學年度 103
學期 1
出版年 104
研究生(中文) 李歡芳
研究生(英文) Huan-Fang Lee
學號 TA8971026
學位類別 博士
語文別 英文
論文頁數 82頁
口試委員 指導教授-顏妙芬
召集委員-王志中
口試委員-林麗嬋
口試委員-劉立凡
口試委員-張海青
中文關鍵字 台灣護理人員  疲潰  馬氏疲潰量表中文版 
英文關鍵字 Taiwanese nurses  burnout  MBI-HSS Chinese version 
學科別分類
中文摘要 背景
疲潰在護理專業是全球重要的問題,因為它影響了個人、組織疾病人成果。疲潰是一種現象,描述人們經驗到情緒耗竭的狀態,就如同是蠟燭燒盡。疲潰的概念包含了情緒耗竭、去人性化、低個人成就感三個面向。護理人員疲潰自1970年代於西方國家開始被探究。馬氏疲潰量表示最廣泛被用來測量疲潰的量表。然而其因素結構在不同文化、國家與健康照護系統有所差異。因此,研究者建議在不同文化、國家與健康照護下需要有大樣本並拓展資料收集區域及在不同工作環境以探究護理人員疲潰。在台灣目前只有兩篇研究探討護理人員疲潰,此兩篇研究均是小樣本且聚焦在特定專科,且其測量工具未經檢測。
目的
本研究目的:(1)檢測台灣測量護理人員疲潰工具的適當性;(2)檢測運用中文版疲潰量表之疲潰分層與切點;(3)探究台灣護理人員疲潰盛行率;(4)探討預測台灣護理人員疲潰之預測因子。
方法
研究設計採橫斷性研究設計。樣本是依據台灣醫策會提供之483家醫院中依照以區域分層隨機方式選出參加醫院,排除床位數小於100床的醫院以及沒有內外科的單位。本研究在工具上分成兩個範疇,人口學和自填相關感受,其感受包括對疲潰感受、工作環境、工作滿意度、工作投入與心理健康。資料分析方面,除了描述性統計外,運用探索性因素分析與驗證性因素分析來檢測工具。運用集群分析檢測疲潰子量表的分層與切點。最後運用階層性迴歸探究疲潰的預測因子。
結果
因素分析結果顯示疲潰量表中文版在三個因素20題下有最適配的結構。此結構包含8題情緒耗竭、4題去人性化與8題低個人成就感,其整體解是變易量為57%。此效度指標卡方值/自由度為;3.59;適配度指數0.92;調整適配度指數0.9以及均方根近似誤0.05。而每個子量表各有三個分層。低度疲潰在情緒耗竭是低於21分、去人性化低於6分、低個人成就感高於25分;中度疲潰在情緒耗竭是22-32分、去人性化7-13分、低個人成就感16-24分;高度疲潰在情緒耗竭是高於33分、去人性化高於14分、低個人成就感低於15分。有80%的護理人員回答有中度以上的疲潰、66%有中度以上去人性化、75%有中度以上低個人成就感。與台灣護理人員疲潰相關的因子包括年紀、心理健康、工作滿意度、工作投入與工作環境。而最顯著的因子為心理健康與工作投入。這些因子對情緒耗竭、去人性化、低個人成就感的解釋力分別為35%、18%與39%。
英文摘要 Abstract
Background
Burnout in the nursing profession is a globally important problem because it affects individual, organizational, and patient outcomes. Burnout is a metaphor to describe people experiencing a state of emotional exhaustion similar to the extinguishing of a candle. Three components, emotional exhaustion (EE), personal accomplishment (PA), and depersonalization (DP), are included in burnout concepts. Nurse burnout has been investigated since the 1970s in western countries. The Maslach Burnout Inventory-Human Service Survey (MBI-HSS) has been widely used to measure burnout. However, the factor structure of the MBI-HSS differs in different cultures, countries, and healthcare provider systems; thus, researchers have suggested that larger sample sizes, expanding the data collection area, and different working environments are needed to investigate burnout differences across cultures, countries, and healthcare. Only two studies have investigated nurse burnout in Taiwan; both reported small sample sizes and focused on nurses working in specific specialties. However, neither identified suitable measurement instruments or predictors of burnout among Taiwanese nurses.


Aim
The aims of this study were to (1) validate a tool suitable for measuring nurse burnout in Taiwan; (2) determine the current burnout levels and cut points of the MBI-HSS Chinese version; (3) investigate prevalence rates of nurse burnout in Taiwan; and (4) explore the predictors of nurse burnout in Taiwan.

Methods
Research design: Cross-sectional.
Sample: Nurses from 483 hospitals accredited by the Taiwan Joint Commission on Hospital Accreditation and chosen using proportional stratified random sampling within a geographic area. The exclusion criteria were: working in a hospital with (1) fewer than 100 beds or (2) no surgical or medical units.
Instrument: Two categories of data—demographic information and self-reported statements of the nurses’ perceptions of their work environment, job satisfaction, work engagement, and mental health—are included in the current study. Five different inventories were adapted to explore the nurses’ perceptions.
Data analysis: In addition to descriptive statistics, exploratory factor analysis and confirmatory factor analysis were used to develop the instrument. The cut points of the burnout-measurement instrument for each level, low, moderate, and high were determined using level estimations and the K-mean grouping method. Finally, the predictors of burnout were investigated using hierarchical regression.

Results
Factor analysis showed an adequate fit between the three-factor 20-item model in the MBI-HSS Chinese version (MBI-HSS-CV). The new structure model contained eight items for emotional exhaustion, four items for depersonalization, and eight items for personal accomplishment, and the final result of variance was 57%. The validity indexes of the factor structure were x2/df = 3.59, GFI = 0.92, AGFI = 0.90, and RMSEA = 0.05. There were three levels of burnout.
The level of burnout was low if scores of emotional exhaustion was less than 21, depersonalization was less than 6, and personal accomplishment was greater than 25; it is moderate if scores of emotional exhaustion ranged from 22 to 32, depersonalization 7 to 13, and personal accomplishment 16 to 24; and it was high if scores of emotional exhaustion was greater than 33, depersonalization was greater than 14, and personal accomplishment was less than 15.
Eighty percent of the surveyed nurses reported more than moderate emotional exhaustion, 66% reported more than moderate depersonalization, and 75% reported more than moderate low personal accomplishment. Related factors for Taiwanese nurse burnout were age, mental health, job satisfaction, work engagement, and work environment. The most significant predictors were mental health and work engagement. The explained variances for each component were 35%, 18%, and 39% for emotional exhaustion, personal depersonalization, and accomplishment respectively.
論文目次 TABLE OF CONTENTS
ABSTRACT......i
ACKNOWLEDGMENTS.....vii
LIST OF TABLES......x
LIST OF FIGURES......xi
CHAPTER 1 INTRODUCTION....1
CHAPTER 2 LITERATURE REVIEW.....4
2.1 Research on the history of burnout..4
2.2 Definition of burnout.....6
2.3 Nurse burnout in various countries..9
2.4 Burnout-related factors....11
2.5 Nurse outcomes related to burnout..24
2.6 Measuring burnout in nurses: Maslach Burnout Inventory-Human Services Survey....26
2.7 Research framework and hypothesis..29
CHAPTER 3 METHODS......32
3.1 Research design and data sources...32
3.2 Data collected in this study...35
3.3 Measurement instruments....35
3.4 Data analysis......39
CHAPTER 4 RESULTS......41
4.1 Factorial structure of the MBI-HSS Chinese version.41
4.2 Levels and cut points of the MBI-HSS Chinese version.48
4.3 The prevalence rate of burnout for nurses in Taiwan.50
4.4 The predictors of burnout for nurses in Taiwan.50
CHAPTER 5 DISCUSSION.....55
5.1 The factor structure of the Maslach Burnout Inventory Chinese version......55
5.2 Levels and cut points of the Maslach Burnout Inventory Chinese version......60
5.3 The prevalence rate of burnout for nurses in Taiwan.62
5.4 The predictors of burnout for nurses in Taiwan.64
CHAPTER 6 LIMITATIONS AND FUTURE RESEARCHES....…..66
CHAPTER 7 CONCLUSIONS....67
CHAPTER 8 REFERENCES.....68

Table 1. Demographic characteristics of the participants.34
Table 2. Critical ratio, correlations, item mean (SD), and skew of Maslach
Burnout Inventory-Human Services Survey (MBI-HSS)..44
Table 3. The communality and factor loadings on structure matrix after re-structure MI-HSS...45
Table 4. K-mean grouping method of MBI-HSS Chinese version for emotional exhaustion, personal accomplishment, and
depersonalization subscales....49
Table 5. Level and cut points of MBI-HSS Chinese version.49
Table 6. Prevalence rate of burnout among Taiwanese nurses.......50
Table 7. Burnout subscale scores by demographic variables.52
Table 8. Correlation among continuous variables..53
Table 9 Hierarchical regressions to predict burnout and subscale scores......54
Figure 1. Research framework...31
Figure 2. Modification structure of MBI-HSS..47
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