[Structural equation model analysis of infectious disease-specific health literacy scale in China].

To explore the relationship between different dimensions of infectious disease-specific health literacy scale in China. Structural equation model (SEM) was employed to assess the psychometric properties of the infectious disease-specific health literacy scale. Based on the database from a randomly selected sample of 4 499 adult residents in three provinces in China, from March to May 2015. AMOS 21.0 software was used to build the SEM for data analyses. SEM analyses showed a good model fit of data, with the following satisfied parameters: goodness-of-fit index was 0.969, adjusted goodness-of-fit index was 0.962, root mean square residual was 0.038, root mean square error of approximation was 0.038, standardized root mean square residual was 0.032, Tacker-Lewis index/non-normed fit index was 0.926, comparative fit index was 0.934, normed fit index was 0.925, relative fit index was 0.915, incremental fit index was 0.934, parsimony goodness-of-fit index was 0.782, parsimony-adjusted normed fit index was 0.817, parsimony-adjusted comparative fit index was 0.825 and critical N was 702. The established SEM showed that the total influence path coefficient of "infectious disease-related knowledge and values" on the "infectious disease prevention" , "management or treatment of infectious diseases" and "identification of infection sources" were 0.771, 0.744 and 0.843, respectively. The total influence path coefficients of "identification of infection sources" , "infectious disease prevention" on "management or treatment of infectious diseases" were 0.164 and 0.535, respectively. The effect of "infectious disease-related knowledge and values" on "management or treatment of infectious diseases" appeared the greatest (55.4%), followed by "infectious disease prevention" (28.6%) and "identification of infection sources" (2.7%). This SEM could be optimistically used for planning and evaluation of health education and promotion programs on infectious diseases prevention.