Abdullah Malik, Azhar Ali, Muhammad Akram, Rizwan Rasheed
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引用次数: 0
摘要
研究目的本研究探讨了巴基斯坦制造业轮班工人的睡眠质量、累积性疲劳和职业伤害之间的关系。研究方法本研究使用自制问卷调查了 200 名轮班工人。睡眠质量采用匹兹堡睡眠质量指数(PSQI)进行评估,疲劳度采用标准轮班工作指数(SSI)进行评估。统计分析包括 t 检验、χ2 检验和逻辑回归。结果显示与白班工人相比,夜班工人发生工伤的几率更高(几率比 [OR] 3.591,95% 置信区间 [CI] [1.079, 11.944],P = 0.037)。累积疲劳度(OR 3.044,95% CI [1.145,8.089],p = 0.026)和 PSQI 综合评分(OR 1.249,95% CI [1.002,1.556],p = 0.048)也表明受伤风险增加。结论与白班工人相比,夜班工人的睡眠质量更差,疲劳程度更高,受伤风险也更高。雇主应采用人工智能来检测和管理疲劳,制定战略性的轮班时间表以获得最大的睡眠机会,并对工人进行培训以提高睡眠质量。
Assessment of sleep quality, fatigue and its association with occupational injuries among shift workers in an electronic industrial environment.
Objectives. This study explores the association between sleep quality, cumulative fatigue and occupational injuries among shift workers in Pakistan's manufacturing industries. Methods. The study surveyed 200 shift workers using a self-administered questionnaire. Sleep quality was assessed with the Pittsburgh sleep quality index (PSQI), and fatigue with the standard shiftwork index (SSI). Statistical analyses included t tests, χ2 tests and logistic regression. Results. Night shift employees had higher odds of occupational injuries (odds ratio [OR] 3.591, 95% confidence interval [CI] [1.079, 11.944], p = 0.037) compared to day shift workers. Cumulative fatigue (OR 3.044, 95% CI [1.145, 8.089], p = 0.026) and PSQI global score (OR 1.249, 95% CI [1.002, 1.556], p = 0.048) also indicated an increased injury risk. Conclusion. Night shift workers experienced poorer sleep quality, higher fatigue and increased injuries than day shift workers. Employers should implement artificial intelligence to detect and manage fatigue, set strategic shift schedules for maximum sleep opportunities and train workers to improve sleep quality.