Statistical analysis
Data were presented as the mean ± standard deviation (SD). The chi-squared (χ2) test, Pearson’s correlation analysis, and multivariate analysis using the structural equation model (SEM) with path analysis were used to determine the structural relationship between the measured variables. Data were analyzed using EpiData version 3.1 software (EpiData, Buenos Aires, Argentina) and SAS version 9.4, software (SAS Institute, Cary, NC, USA), which were used for data entry and analysis. The intermediary effects of the variables were analyzed using IBM SPSS AMOS version 21.0 (IBM Corp., Armonk, NY, USA). The bootstrap number was set as 5,000. The significance of the specific intermediary was determined using the nonparametric percentile bootstrap method with deviation correction. Path analysis by the structural equation model (SEM) was performed to measure the associations and their importance. Path analysis included the use of the goodness-of-fit index (GFI), the adjusted goodness-of fit-index (AGFI) the incremental fit index (IFI), the comparative fit index (CFI), the Tucker-Lewis index (TLI), the normed fit index (NFI), and the root mean square error of approximation (RMSEA). The structural equation showed and ideal fit (GFI=0.995, CFI=0.995, TLI=0.953, IFI=0.996, NFI=0.991, AGFI=0.931, RMSEA=0.077, χ2/df=2.073). A P-value <0.05 was considered to be statistically significant.