Factors associated with different levels of daytime sleepiness among Korean construction drivers: a cross-sectional study.

BACKGROUND: Commercial vehicle accidents are the leading cause of occupational fatalities and an increased risk of traffic accidents is associated with excessive fatigue, other health problems as well as poor sleep during work. This study explores individual and occupational factors associated with different levels of daytime sleepiness and identifies their association with driving risk among occupational drivers working at construction sites. METHODS: This cross-sectional and correlational study adopted a self-reported questionnaire of Korean construction drivers (N = 492). The data were collected from October 2018 to February 2019 using a battery of six validated instruments about participants' sociodemographic, health-related, and occupational characteristics. One-way ANOVA and multinomial logistic regression were conducted using IBM SPSS WIN/VER 25.0, with a two-tailed alpha of .05. RESULTS: Based on the Epworth Sleepiness Scale, "moderate" (31.7%) and "severe" (10.2%) daytime sleepiness groups were identified. There were significant differences in break time, driving fatigue, depressive symptom, subjective sleep quality, physical and mental health, and driving risk among the three groups (all p-values < .001). Driving fatigue (Adjusted Odds Ratio [aOR] = 1.08, 1.17), depressive symptoms (aOR = 0.91, 0.98), subjective sleep quality (aOR = 1.18 in moderate only), and driving over the speed limit (aOR = 1.43, 2.25) were significant factors for determining "moderate" and "severe" daytime sleepiness groups, respectively. CONCLUSION: A significant number of construction drivers experience excessive daytime sleepiness; thus it is important to reduce the negative impact of driving fatigue and other factors on daytime sleepiness. Our study findings suggest that occupational health care providers should pay attention to development and implementation of health management interventions to reduce driving fatigue that incorporate the drivers' physical, mental, and occupational factors. Professional organizations need to establish internal regulations and public policies to promote health and safety among occupational drivers who specifically work at construction sites.

Korean Version of the Swedish Occupational Fatigue Inventory among Construction Workers: Cultural Adaptation and Psychometric Evaluation.

The Swedish Occupational Fatigue Inventory (SOFI) has been tested in different languages and populations; thus, there is a need for a culturally adapted Korean version. We evaluated the psychometric properties of a Korean version of the SOFI among construction workers. The SOFI was translated into Korean and reviewed through a back-translation process involving standardized scaling procedures. Its reliability and validity were evaluated with a sample of 193 construction workers using internal consistency, item-subscale correlations, test-retest reliability, and content, construct, and concurrent validity. The Cronbach's alpha coefficients of the total scale and each subscale were satisfactory. Item-subscale correlations and test-retest reliability were both at acceptable levels. Confirmatory factor analyses revealed that the five-factor model had acceptable model fits corresponding to the structure of the original instrument. However, some modifications were made to improve in the new context from model fit (such as χ2(95) = 113.905 (p = 0.091), CFI = 0.994, and RMSEA = 0.033, as well as the lowest AIC = 383.905). Correlation analysis showed a significant relationship of SOFI with other fatigue measures in terms of total and subscale scores. Occupational fatigue is one of the important risk factors associated with workers' health and safety at work. The new translated instrument is a reliable and valid tool for assessing fatigue among Korean construction workers. However, this instrument should be tested extensively in other working populations to devise specific interventions concerning fatigue reduction.

Factors Associated with Poor Quality of Sleep in Construction Workers: A Secondary Data Analysis.

This study aimed to explore factors associated with poor quality of sleep in construction workers. This study was cross-sectional, correlational in design and used secondary data from fatigue instrument development study. We analyzed the data from 206 participants aged over 19 years who worked at construction sites for more than 6 months. We used multivariate binary logistic regression to identify the factors associated with poor quality of sleep. We classified the two sleep quality groups based on the Pittsburgh Sleep Quality Index (PSQI) score, and almost 63% of them were classified as the poor quality of sleep group. Based on multivariate binary logistic regression (Cox and Snell R2 = 0.317, Nagelkerke R2 = 0.429), the poor quality of sleep group tended to sleep for a shorter duration before the working day, and not only showed lower sleep latency and higher levels of daytime dysfunction and discomfort in daily life, but also had more chronic disease, depressive symptoms, and higher physical fatigue. Our study findings support that there are many modifiable factors associated with poor sleep and a high rate of poor quality of sleep occurred in construction workers. Thus, clinicians should consider providing diverse options for applying interventions to ensure better sleep, fatigue management, and depression prevention in construction workers after considering their unique characteristics.