| 胡佳,田向阳,陈继彬,任学锋,程玉兰.中国居民传染病健康素养测评量表的结构方程模型分析[J].Chinese journal of Epidemiology,2019,40(2):237-240 |
| 中国居民传染病健康素养测评量表的结构方程模型分析 |
| Structural equation model analysis of infectious disease-specific health literacy scale in China |
| Received:September 03, 2018 |
| DOI：10.3760/cma.j.issn.0254-6450.2019.02.021 |
| KeyWord: 传染病健康素养测评量表 结构方程模型 |
| English Key Word: Infectious disease-specific health literacy scale Structural equation model |
| FundProject:国家科技支撑计划（2013BAI06B06） |
| Author Name | Affiliation | E-mail | | Hu Jia | Chinese Center for Disease Control and Prevention, Beijing 100011, China
Chinese Center for Health Education, Beijing 100011, China | | | Tian Xiangyang | Chinese Center for Health Education, Beijing 100011, China | healthtian@163.com | | Chen Jibin | Chinese Preventive Medicine Association, Beijing 100011, China | | | Ren Xuefeng | Chinese Center for Health Education, Beijing 100011, China | | | Cheng Yulan | Chinese Center for Health Education, Beijing 100011, China | |
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| Abstract: |
| 目的 了解中国居民传染病健康素养测评量表不同维度之间的关系。方法 采用结构方程模型，使用2015年3-5月在我国3个省份随机抽取的4 499名城乡居民传染病健康素养数据库，运用AMOS 21.0软件构建结构方程模型进行分析。结果 结构方程模型适配度指标：适配度指数为0.969，调整后适配度指数为0.962，残差均方和平方根为0.038，渐进残差均方和平方根为0.038，标准化残差均方和平方根为0.032，非规准适配指数为0.926，比较适配指数为0.934，规准适配指数为0.925，相对适配指数为0.915，增量拟合指数为0.934，简约调整适配度指数为0.782，简约调整规准适配指数为0.817，简约调整比较适配指数为0.825，临界样本数为702，模型拟合效果良好。结构方程模型显示，传染病的基本知识与观念对传染病的预防、管理与治疗、辨认的总效应为0.771、0.744、0.843；传染病的辨认、预防对传染病管理与治疗的总效应分别为0.164、0.535。对传染病的管理与治疗影响强度最大的为传染病的基本知识与观念（55.4%）；其次为传染病的预防（28.6%）；而传染病的辨认影响较小（2.7%）。结论 提高我国居民传染病健康素养，重点是改善个体的传染病基本知识与观念、传染病预防技能。 |
| English Abstract: |
| Objective To explore the relationship between different dimensions of infectious disease-specific health literacy scale in China. Methods 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. Results 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%). Conclusion This SEM could be optimistically used for planning and evaluation of health education and promotion programs on infectious diseases prevention. |
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