| Summary: | Fatigue among workers, particularly in the manufacturing sector, is a critical issue that affects employee well-being, productivity, and safety. This study investigates the relationship between workload, sleep quality, and fatigue among shift workers in the manufacturing industry. A set of questionnaires was used to determine workload, sleep quality and fatigue. Workload among the respondents was determined using the NASA Task Load Index (NASA–TLX), the Pittsburgh Sleep Quality Index (PSQI) to evaluate sleep quality, and the Industrial Fatigue Research Committee (IFRC) to assess fatigue levels among employees. The sample consisted of 108 participants, predominantly younger individuals (76.9% aged 18–30 years) and females (68.5%), with most in the early stages of their careers. A majority (65.6%) reported high workload levels, while 30.6% experienced somewhat high workloads. Sleep difficulties were universal, with 57.4% experiencing mild disruptions and 38.8% moderate disturbances. Fatigue was similarly prevalent, with 52.8% reporting high fatigue and 29.6% experiencing very high fatigue. An analysis of socio-demographic factors revealed no significant relationship between age, marital status, or working experience with workload, sleep quality, or fatigue. However, gender showed a significant association with fatigue (x2=12.905, p=0.005), suggesting that male and female workers experience fatigue differently. This findings highlights the potential influence of physiological and occupational differences in fatigue perception and management between genders. Pearson correlation analyses revealed a significant negative relationship between workload and fatigue (r=-0.432, p<0.001), suggesting that higher workloads are associated with lower levels of fatigue among shift workers. Sleep quality was strongly associated with fatigue (r=-0.565, p<0.001), indicating that poorer sleep quality is linked to higher levels of fatigue. Additionally, workload and sleep quality showed a significant positive correlation (r=0.275, p=0.004), implying that higher workloads are associated with slightly better sleep quality in this sample. Multiple linear regression analysis further supported these findings, revealing a negative association between workload and fatigue (β=-0.300, p<0.001) and a significant negative relationship between sleep quality and fatigue (β=-0.269, p<0.001). These results underscore the critical role of sleep quality in fatigue management and highlight the nuanced relationship between workload and fatigue. These findings emphasizes the multifaceted dynamics between workload, sleep quality, and fatigue. Interventions targeting workload management, sleep improvement, and fatigue monitoring are essential to enhance worker well-being and productivity. Future research should examine larger sample sizes and additional factors such as coping mechanisms, environmental conditions, and work schedules to develop comprehensive fatigue management strategies
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