南部高科技園區員工之工作壓力與其相關因子兩年追蹤分析

Working Stress and Associated Factors with two Years Tracking Analysis of the High-Tech Workers in Southern Taiwan

謝依儒(Yi-Ju Hsieh)；林志遠(Chih-Yuan Lin)；黃建元(Chien-Yuan Huang)

高科技園區員工 ； 工作壓力 ； 工作壓力危險因子 ； high-tech workers ； work stress ； risk of work stress

中華職業醫學雜誌

22卷4期（2015 / 10 / 25）

249 - 261

繁體中文

目的：隨著時代環境的變遷，職場上的工作壓力越來越受到重視，而研究指出長期處在高工作壓力的環境下，生理、心理方面都可能因壓力引發許多健康問題。而工作壓力在高科技產業下又更為顯著，故本研究希望針對高科技勞工之工作壓力與其相關危險因子做長期性追蹤探討，期望能及早發現高工作壓力之高危險族群。方法：以南台灣高科技園區某一工廠勞工為對象，採自填式問卷調查的方式，於2012年以及2013年年度體檢期間進行問卷調查。問卷內容包含基本人口學資料、工作狀況、台灣人憂鬱症量表等，以SPSS17.0統計軟體進行分析。以邏輯式回歸分析工作壓力相關危險因子，以配對t檢定比較2012及2013年工作壓力相關危險因子之變化情形。結果：2012~2013年間均有填寫問卷的員工總計有效問卷646份，以單變項邏輯式迴歸分析發現上班型態（輪班）、經濟壓力、低工作控制能力、高工作投入、高服務疲勞、高個人疲勞、高工作疲勞、台灣人憂鬱症指數等為工作壓力之危險因子（p＜0.05）。再以多變項邏輯式迴歸分析，經調整上班型態、經濟壓力、工作控制能力、對工作投入狀況、服務對象疲勞、個人疲勞、工作疲勞、台灣人憂鬱症指數等變項後，發現低工作控制能力（Adjust odds ratio (AOR)=2.18; 95% confidence interval (95% C.I.)=1.35-3.52）及高個人疲勞（AOR=2.71,95% C.I.=1.26-5.83）為獨立危險因子。再進一步分析同一員工2年間相關危險因子的變化，以配對t檢定分析，2013較2012增加的有工作投入狀況、對服務對象疲勞、個人疲勞、工作疲勞等因子，其中個人疲勞具統計明顯相關（p＜0.05）。結論：本研究發現：低工作控制能力及高個人疲勞為高工作壓力的獨立危險因子。此外以配對t檢定分析，發現個人疲勞為獨立危險因子，其他項目雖有微幅增加，但無達到顯著意義。期望透過本研究提供高科技產業之高工作壓力族群的危險因子，作為早期偵測、評估及介入措施的依據，以期有效預防因工作壓力而產生的身心疾病。

Objective: With the changing of times and the environment, working pressure of the workplace has more and more attention, and the researches indicated that people working in a high stress environment for a long time may lead to many health problems of physiological and psychological aspects due to the pressure. The working pressure in the high-tech industry is more significant, so this study is to investigate to make long-term tracking of working stress and associated factors with the high-tech workers and expect early detection of the high-risk groups of high working stress. Materials and Methods: We recruited the high-tech workers in southern Taiwan, and collected their self-administered questionnaires in the 2012 and 2013 annual physical examination. The questionnaire included basic demographic, work status, Taiwanese depression scale. We used SPSS version 17.0 software for analysis. Logistic regression was used to analyze the risk factors of work stress. Paired sample test was then used to compare the change of work stress related risk factors between 2012 and 2013. Results: There were total valid 646 questionnaires that employees fill in during both years between 2012 and 2013. With univariate logistic regression analysis showed that work patterns (work shift), economic pressure, low job control, high job involvement, high service fatigue, high personal fatigue, high job fatigue and Taiwanese depression scale are risk factors of work stress. (p＜0.05). Then we analyzed with multivariate logistic regression analysis formula by controlling other risk factors (work patterns, economic pressure, job control, job involvement, serviceFatigue, personal fatigue, job fatigue and Taiwanese depression scale).The result showed low job control (Adjusted odds ratio [AOR]=2.18, 95% CI=1.35-3.52) and high personal fatigue (AOR=2.71, 95% CI=1.26-5.83) are the independent risk factors of work stress. Then we analyzed the changes of the related risk factors between the two years of the same employee with paired sample t-test analysis. The result showed there are job involvement, service fatigue, personal fatigue and job fatigue increased in 2013 compared with 2012 and personal fatigue has statistical significant correlation (p＜0.05). Conclusion: This study found that: low job control and high personal fatigue are the independent risk factors for higher work stress. With paired samples t-test analysis, we found personal fatigue is the independent risk factor, although a slight increase noticed in other factors, but they had no statistical significance. We hope it could provide the risk factors of high work stress groups of high-tech industry through this study, and as early detection, assessment and interventions basis for the effective prevention of physical and mental diseases induced by work stress.

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