高科技輪班人員睡前行為和睡眠品質之關聯

The relationship between bedtime behavior and sleeping quality for high-tech workers with working shifts in Taiwan.

李建凱(Jian-Kai Li 李建凱)

指導教授 ： 呂志維

中原大學/電機資訊學院/工業與系統工程研究所/碩士(2016年)

https://doi.org/10.6840/cycu201600879

摘要

本本研究旨在探討高科技產業的員工日間嗜睡程度與睡眠品質之狀況及相互關係，並瞭解不一樣的個人屬性對日間嗜睡愛普沃斯嗜睡量表（Epworth Sleepiness Scale）及睡眠品質的影響，個人屬性包含人口統計變項與個人健康狀況，睡眠品質的調查是使用匹茲堡睡眠品質量表（PSQI）為研究調查工具，本研究以 221 名高科技產業員工為研究對象，依高科技產業公司依照場區抽樣的方法抽樣並以實體紙本發送問卷，本研究回收 221 問卷經審剔除部份無效問卷後，以SPSS For Windows 套裝統計軟體統計並分析所得資料。
本研究結果發現：1)高科技產業員工男生為大多數，受試者43%身體質量指數為正常，有64%的自覺入睡良好，而自覺打呼狀況差及很差者有59%，有40%罹患有慢性疾病(高血壓);2)日間嗜睡有 36.1%的有日間嗜睡程度，夜班輪班人員睡眠品質會比日間輪班人員的睡眠品質更差;3)近 69.2%的人睡眠品質不良; 4) 員工不同的個人屬性對嗜睡程度量受不同年齡、服務年資及自覺睡眠狀況還有輪班情況會有所影響; 5)員工不同的個人屬性對睡眠品質因不同年齡、服務年資、婚姻狀況、身體質量質數、自覺睡眠狀況及自覺打呼情況比較而有差異; 6)不同日間嗜睡程度對整體睡眠品質並無顯著的差異，但是睡眠品質的構成因素方面對個人主觀睡眠品質及白天功能障礙有著顯著差異。
本研究發現員工有嚴重日間嗜睡程度者可能有較多白天障礙之狀況，故公司單位若希望員工能帶高效率、高生產和高利潤，建議公司單位能投資員工的健康，如可以提供健康活動場所、健康講座、支持健康活動進而培養員工健康的生活型態等，輪班的規律也可以調整為兩或三個月為輪班的規律，做二休二的輪班方式可能造成勞工生理時鐘很難快速調整，可能導致勞工睡眠品質與日間嗜睡的程度會減低。日間嗜睡程度高與睡眠品質的員工，建議要好好檢視其個人睡眠環境與生活型態，要改變原有不健康的生活型態，找出適合個人且可規律從事之運動生活增加睡眠準備，增加正常的運動增加個人睡眠的品質，建議睡眠品質較差的員工需要增加個人睡眠的時間，另外需找出導致自已睡眠品質不良之原因，或許增加了身體活動量即可改善睡眠品質不良問題。 由於日間嗜睡與睡眠品質關係的交互作用因素較複雜，研究者很難完全掌握各種可能的影響參數。本研究是採用受試者主觀自評問卷調查方式來收集資料，並沒有客觀儀器測量介入，因此建議將來欲詳細研究兩者間的因果關係，應規劃更為完善的實驗設計，結合實驗室腦波儀與呼吸及睡眠腦波去判讀與長時間的數據做參考會更為客觀，以期能更詳盡的的探討日間嗜睡程度與睡眠品質之關係。

關鍵字

高科技產業員工 ； 睡眠品質 ； 疲勞度

並列摘要

This research explores the level of sleepiness during daytime and the sleeping quality of high tech workers with different personality factors. Yet, to investigate the impact of daily sleepiness based on Epworth Sleepiness Scale. The personality factors include the changed in population and health condition. PSQI has been used to analyze the sleeping quality with the sample size of 221 high-tech workers. The actual surveys were delivered to the workers during the data collection stage. Then, SPSS had used to analyze the data and seek for the result of this research.

The results of the research were:
1. High-tech workers are mainly male with 43% positive health condition, 64% seem to have good sleeping quality, 59% snore during sleep and 40% are suspected to have hypertension.
2. 36.1% of high-tech workers are suspected to have strong feeling of sleepiness during daytime.
3. 69.2% of high-tech workers have bad sleeping quality.
4. Several factors such as age, employment period, self-conscious sleeping quality can affect workers in their sleeping quality.
5. Factors such as age, the length of employment, martial status, and healthy condition can increase workers’ self-snoring and sleepiness during daytime.
6. Self-sleepiness doesn’t have big impact on the overall sleeping quality of the high-tech workers, but individual subjective factors such as tiredness and stress can lead to negative sleeping quality.

Within the research, it discovered that high tech workers who have extreme daily sleepiness behavior would have many daytime obstacle symptoms. Thus, in order to foster employees with healthy living style, companies can invest more in employees’ health condition, such as proving community center, educating employees on healthy sleeping behavior through workshops, supporting healthy activities and changing the work shift to two or three months as a cycle. Moreover, work two days and off two days work shift format might cause employees to face difficult psychological sleeping pattern, but can lower down the daily sleepiness level and employees’ sleeping quality.

The research suggested that high daily sleepiness and sleeping quality employees should think of others’ sleeping environment and lifestyle. The change can be make by changing unhealthy lifestyle, increase exercise time, provide suggestions to bad sleeping quality workers to sleep earlier, and also to find out the leading cause to bad sleeping quality. Since the daily sleepiness and sleeping quality have comprehensive relationship, researchers have difficulty in taking all factors into consideration within the research. This research only use subjective self-answering survey to collect data without the use of objective tools to measure. Therefore, it is suggested that the more detail research on the relationship of daily sleepiness and sleeping quality of the employees should experiment with complete design, to combine Brainwave and breath during collecting data stage as the subjective data in the future.

並列關鍵字

elderly workers ； sleep quality ； fatigue levels

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