BackgroundAlthough community health education has drawn lots of attention from the public, evidence on resident satisfaction is still sparse. This study aims to explore the relationships among five dimensions (perceived quality, perceived value, public expectation, public trust, and public satisfaction) of satisfaction with community health education among Chinese residents.MethodsWe constructed a theoretical public satisfaction model for community health education based on the American Customer Satisfaction Index (ACSI) model. There are five dimensions in the theoretical model, including public expectation, perceived quality, perceived value, public satisfaction, and public trust. We recruited 474 respondents from a quota sampling based on gender and age, and collected information on five dimensions of satisfaction with community health education. The relationships of the five dimensions were examined using structural equation model.ResultsThe mean scores of public expectation, perceived quality, perceived value, public satisfaction, and public trust for the participants were 11.44 (total 15), 123.89 (total 170), 14.18 (total 20), 10.19 (total 15), and 15.61 (total 20), respectively. We obtained a structural equation model with a good fitting degree. There was a direct effect of perceived quality on perceived value (γ = 0.85, P < 0.01), public trust (γ = 0.81, P < 0.01) and public satisfaction (γ = 0.58, P < 0.01), and a direct effect of public expectation on public satisfaction (γ = 0.36, P < 0.01) and perceived value (γ = 0.25, P < 0.01).ConclusionsWe provide a good tool to measure public satisfaction with community health education, which can be potentially used to measure public satisfaction and improve the effectiveness of health education.
BackgroundLiver hepatocellular carcinoma (LIHC) is an important pathological type of liver cancer. The immune infiltration of the tumor microenvironment is negatively correlated with the overall survival rate of LIHC. At present , the role and molecular mechanism of KPNA2 in LIHC have not been elucidated, and the prognostic correlation between the two and the immune infiltration of LIHC are still unclear. Our study evaluated the role of KPNA2 in LIHC through TCGA data.MethodGene expression profiling interactive analysis (GEPIA) is used to analyze the expression of KPNA2 in LIHC. We evaluated the impact of KPNA2 on the survival of LIHC patients through the survival module. Then, We downloaded the LIHC data set from TCGA. Logistic regression was used to analyze the correlation between clinical information and KPNA2 expression. Cox regression analysis was used to analyze the clinicopathological characteristics related to the overall survival rate of TCGA patients. In addition, we used the "correlation" modules of CIBERSORT and GEPIA to explore the correlation between KPNA2 and cancer immune infiltrate. Western blotting was used to detect the expression of KPNA2.ResultUsing logistic regression for univariate analysis, increased KPNA2 expression was significantly correlated with pathological stage, tumor status, and lymph node status. In addition, multivariate analysis showed that down-regulation of KPNA2 expression, negative pathological stage and distant metastasis are independent prognostic factors for good prognosis. Specifically, CIBERSORT analysis was used to establish a negative correlation between the up-regulated expression of KPNA2 and the level of immune infiltration of B cells, NK cells, mast cells, and T cells. In addition, we confirmed this in the "Association" module of GEPIA. The expression of KPNA2 in LIHC tissues was significantly lower than that in adjacent normal tissues by western blotting.ConclusionThe down-regulation of KPNA2 expression is associated with a good prognosis and an increase in the proportion of immune cells in LIHC. These conclusions indicate that KPNA2 is related to the level of immune infiltration of LIHC and can be used as a potential prognostic biomarker of LIHC and a potential target for clinical tumor treatment.
BackgroundLiver hepatocellular carcinoma (LIHC) is an important pathological type of liver cancer. The immune infiltration of the tumor microenvironment is negatively correlated with the overall survival rate of LIHC. At present, the role and molecular mechanism of KPNA2 in LIHC have not been elucidated, and the prognostic correlation between the two and the immune infiltration of LIHC are still unclear. Our study evaluated the role of KPNA2 in LIHC through TCGA data.MethodGene expression profiling interactive analysis (GEPIA) is used to analyze the expression of KPNA2 in LIHC. We evaluated the impact of KPNA2 on the survival of LIHC patients through the survival module. Then, We downloaded the LIHC data set from TCGA. Logistic regression was used to analyze the correlation between clinical information and KPNA2 expression. Cox regression analysis was used to analyze the clinicopathological characteristics related to the overall survival rate of TCGA patients. In addition, we used the "correlation" modules of CIBERSORT and GEPIA to explore the correlation between KPNA2 and cancer immune infiltrate. Western blotting was used to detect the expression of KPNA2.ResultUsing logistic regression for univariate analysis, increased KPNA2 expression was significantly correlated with pathological stage, tumor status, and lymph node status. In addition, multivariate analysis showed that down-regulation of KPNA2 expression, negative pathological stage and distant metastasis are independent prognostic factors for good prognosis. Specifically, CIBERSORT analysis was used to establish a negative correlation between the up-regulated expression of KPNA2 and the level of immune infiltration of B cells, NK cells, mast cells, and T cells. In addition, we confirmed this in the "Association" module of GEPIA. The expression of KPNA2 in LIHC tissues was significantly lower than that in adjacent normal tissues by western blotting.ConclusionThe down-regulation of KPNA2 expression is associated with a good prognosis and an increase in the proportion of immune cells in LIHC. These conclusions indicate that KPNA2 is related to the level of immune infiltration of LIHC and can be used as a potential prognostic biomarker of LIHC and a potential target for clinical tumor treatment.
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