Abstract
ABSTRACTBackgroundGood sleep is essential to human health. Insufficient quality sleep may compromise the wellness of nurses and even jeopardize the safety of patients. Although the contributors of sleep quality in nurses have been previously studied, the direct and indirect effects of modifiable work-related predictors remain uncertain.PurposeThe study was designed to explore the direct and indirect effects of modifiable work-related factors on sleep quality in Chinese nurses.MethodsA multistage sampling method was employed in this cross-sectional study to recruit 923 participants. An evidence-based predicting model was postulated and then subsequently tested and optimized using path analysis.ResultsThe final model fit the data well, with the involved predictors accounting for 34.1% of the variance in sleep quality of the participants. Shift work, job demands, exposure to hazards in work environments, chronic fatigue, and inter-shift recovery were identified as direct predictors, while whereas job satisfaction, job control, support at work, and acute fatigue were identified as indirect predictors.Conclusions/Implications for PracticeSleep quality in Chinese nurses is influenced directly and indirectly by various modifiable work-related factors. Interventions such as adjusting work shifts and reducing job burdens should be prioritized by administrative staff to ensure the sleep quality and clinical performance of Chinese nurses and to subsequently improve nursing care quality.
Highlights
“sleep quality” is widely used, this term lacks definitional consensus
Job demands, exposure to hazards in work environments, chronic fatigue, and inter-shift recovery were identified as direct predictors, while whereas job satisfaction, job control, support at work, and acute fatigue were identified as indirect predictors
This study conducted a multiaspect-oriented investigation of modifiable work-related factors that are associated with sleep quality in Chinese nurses and proposed, tested, and optimized an innovative, evidence-based hypothesized model using path analysis
Summary
“sleep quality” is widely used, this term lacks definitional consensus. A panel of experts that was recently assembled to address this intellectual enquiry drew the conclusion that sleep continuity variables such as sleep latency, length of sleep, and frequency of awakenings as well as sleep efficiency are appropriate indicators of good sleep quality across the human life-span (Ohayon et al, 2017). Individual factors, behavioral factors, physical factors, and psychosocial factors have been identified as contributors to poor sleep in nurses (Chung, Liu, Lee, & Hsu, 2013; Han et al, 2016). Most of these factors, for example, age and marital status, are not subject to immediate utilization in related organizational interventions. Most related research has focused on the effects of shift work or on isolated cases only (Caruso, 2014; Lin et al, 2014) It remains unclear how these proposed factors interrelate with each other and impact sleep quality. The contributors of sleep quality in nurses have been previously studied, the direct and indirect effects of modifiable work-related predictors remain uncertain.
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