0695 EXPLORE INFLUENCING FACTORS OF SLEEP DISTURBANCES AMONG NURSES IN CHINA BY USING BACK-PROPAGATION NEURAL NETWORK MODEL

Abstract

Introduction: Sleep disturbances and fatigue are prevalent among shift work nurses. Sleep problems could be resulted from physic‐psychological and environmental factors, and has negative effects on health. To date, research in shift work nurses' sleep are rare in China, which could be due to few people attentive the potential negative health impacts resulted from shift work and nurses are required to work rotating day/night shift within one week. This study aimed to describe sleep quality and further to explore factors related to sleep quality among the registered nurses (RNs) in Beijing, China. Methods: A total of 672 shift work RNs from one teaching hospital at Beijing participated in this study. A battery of questionnaires and physiological data (blood pressure, body mass index, blood sugar, ECG etc.) were collected to assess sleep quality, fatigue severity, and physical health. Back‐Propagation (BP) neural network was used to allowing for nonlinear self‐tuning adaptive control; further, to identify influencing factors for poor sleep. The demographics and physiological data were used as the input neurons (independent variables), fatigue severity as the covariate, and sleep quality as the output neuron (dependent variable) to simulate the analog BP neural network model, and identify the sensitivity of the factors accounted for poor sleep quality as index by the General Sleep Disturbance Scale. Results: Majority of the RNs reported clinically significant poor sleep (69.6%) and fatigue (75.3%). A total of 11 independent variables were entered the model; BMI (mean=21.97, SD=3.21; sensitivity=29.3%), total sleep hours in past week (mean=6.6, SD=1.5; sensitivity=26.4%), systolic pressure (mean=111.3, SD=12.7; sensitivity=22.8%), age (mean=31.8, SD= 6.8; sensitivity=21.9%), and total years working in the unit (mean=10.5, SD=7.5; sensitivity=21.8%) are the top five predictors for poor sleep quality. Conclusion: Most of RNs in this study experienced sleeping disturbances and severe fatigue, which could negatively impact to work safety and their own health, and call for further study in shift work coping. Objective sleep measurements are required to identify circadian rhythms issues. Tailored interventions are needed to help nurses to improve their sleep through sleep hygiene practice and maintain ideal BMI.