Statistical Analysis
depression, anxiety
REGRESSION, SECONDARY
Data management and statistical analysis were performed using SPSS (version 26.0; IBM Corp), and a 2-sided α of <.05 was used to determine statistical significance. Normality tests were conducted for all continuous variables, and the results showed that all continuous variables in this study were normally or approximately normally distributed. Therefore, mean and SD was used to describe continuous variables. Frequency (percentage) was used to describe the categorical variables. Chi-square tests were used to compare baseline general information between participants who completed the questionnaire and those who did not complete throughout the intervention and follow-up.The generalized estimating equation (GEE) was used to assess the group, time, and time×group effects of the intervention on primary (anxiety and depression symptoms) and secondary outcomes (sleep quality, burnout, and work performance) in nurses. GEE has been widely used in the analysis of repeated measured randomized controlled design data and allows for missing values in the data, differences in the number of observations for each observation object, and the time interval between observations [Model 4 in the PROCESS plug-in was used to test the mediating effect of the intervention on nurses’ anxiety and depression symptoms. First, the residualized change scores of the mechanism variables and primary outcome variables were calculated based on the linear regression model to represent the changes in individuals before (T1) and after (T5) the intervention. The residualized change score was used as the mediating variable and outcome variable for the mediating analysis. The residualized change score represents the difference between an individual’s actual score immediately after the intervention and the score predicted at baseline [