The study of relationship between occupational stress and sleep quality of video display terminals

Abstract

Objective: To investigate the sleep quality of video operators in Shenzhen, and explore the relationship between sleep quality and occupational stress and different work and life habits. Methods: In December 2020, a cluster sampling method was used to investigate 791 video operators in Shenzhen from June to December 2020 who were engaged in printing, design, IT and other industries. The Pittsburgh Sleep Quality Index Scale was used to investigate the sleep quality of video operators, and the Job Content Questionnaire was used to investigate the occupational stress of video operators, The Pay Return Imbalance Questionnaire was used to investigate the pay return imbalance of video operators. The measurement data conforming to the normal distribution shall be expressed by mean±standard deviation, and t-test, analysis of variance and linear correlation analysis shall be adopted according to the type of independent variable. Those that do not conform to the normal distribution are described by the median M (Q(1), Q(3)), and two sample Wilcoxon test is used according to the binary data of independent variable type. Kruskal Wallis test was used for multi classification data, and Spearman rank correlation was used for single factor analysis for ordinal classification data. The counting data were analyzed by chi square test or Fisher exact probability method. Logistic regression was used for multivariate analysis. Results: the pittsburgh sleep quality index was 4.76±2.86. 499 of them had high sleep quality. 292 people had low sleep quality, accounting for 36.91% (292/791). Compared with the low sleep quality group, the high sleep quality group had lower work requirement scores (13.48±1.77), higher autonomy scores (24.08±3.33), higher social support scores (23.95±3.08), lower pay scores (16.11±2.63), higher return scores (31.11±3.65), and lower internal input scores (14.98±2.55). There were statistically significant differences between the two scales in each dimension index group (P<0.05). Multi factor unconditional logistic regression analysis showed that high education level (OR=1.57, 95%CI=1.26~1.98, P<0.05), occupational stress (OR=1.69, 95%CI=1.21~2.36, P<0.05), and high pay and low return (OR=1.41, 95%CI=1.01~1.96, P<0.05) were the main influencing factors of sleep quality. Conclusion: The occurrence of occupational stress in video operators is a risk factor for low sleep quality, which should be paid enough attention.