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.

Purpose: The aims of this study were to identify depression rates depending on the sex among elderly people living alone and to compare depression-related ecological system factors between two sex groups.Methods: A cross-sectional study was conducted using secondary data from the 7th Korean Longitudinal Study of Aging survey in 2018. A total of 893 elders living alone were included (152 men and 741 women). Hierarchical logistic regression was used to identify depression-related ecological system factors depending on the sex.Results: Men had significantly higher rates of depression (28.6%) than women (24.0%, p<.001). Depression-related ecological system factors in elderly women were higher educational level, poor subjective health status, impairment of instrumental activities of daily living, low satisfaction with children’s relation, financial based on children’s support, and rare meetings with close people. However, relation satisfaction with children was the only relevant depression-related ecological system factor in the men’s group.Conclusion: Our study findings show that depression-related ecological system factors vary depending on the sex of elderly people living alone. Thus, mental health professionals should provide sex-specific interventions to develop or implement depression-prevention strategies for the elderly living alone depending on the sex.

The Internet of Medical Things is promising for monitoring depression symptoms. Therefore, it is necessary to develop multimodal monitoring systems tailored for elderly individuals with high feasibility and usability for further research and practice. This study comprised two phases: (1) methodological development of the system; and (2) system validation to evaluate its feasibility. We developed a system that includes a smartphone for facial and verbal expressions, a smartwatch for activity and heart rate monitoring, and an ecological momentary assessment application. A sample of 21 older Koreans aged 65 years and more was recruited from a community center. The 4-week data were collected for each participant (n = 19) using self-report questionnaires, wearable devices, and interviews and were analyzed using mixed methods. The depressive group (n = 6) indicated lower user acceptance relative to the nondepressive group (n = 13). Both groups experienced positive emotions, had regular life patterns, increased their self-interest, and stated that a system could disturb their daily activities. However, they were interested in learning new technologies and actively monitored their mental health status. Our multimodal monitoring system shows potential as a feasible and useful measure for acquiring mental health information about geriatric depression.