Evaluation on the effect of "4+3" model on community residents' health literacy
收藏DataCite Commons2025-04-27 更新2025-04-16 收录
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Methods Using a random stratified cluster sampling method, a one-year "4+3" model intervention was conducted on 1860 selected residents. The health literacy survey questionnaires from the past two years were compared, and statistical methods such as chi square test and multiple logistic regression were used for statistical analysis.Results The overall health literacy of residents in Hebei Province has improved compared to 2022. The level of health knowledge and concepts, healthy lifestyle and behavioral literacy has been improved; There is no statistical significance in the level of health skill literacy. In 2023, the scientific health concept, health information literacy, and chronic disease prevention and control literacy of residents have all been improved; The level of safety and first aid literacy has decreased; There is no statistical significance in the changes in infectious disease prevention and control literacy and basic medical literacy. The results of multivariate logistic regression analysis showed that residents who were female, had a high level of education, engaged in medical related professions, and had a high per capita income had higher health literacy, and the difference was statistically significant.Conclusions The overall level of health literacy of residents in Hebei Province has improved. Residents with low education level, low family income and little knowledge of health literacy at work should be taken as the key population for health intervention, and health education on basic medical literacy, safety and first aid literacy should be strengthened to explore health literacy intervention methods from multiple angles.Objecitive By analyzing the changes in the health literacy level of residents in Hebei Province before and after the comprehensive intervention of the "4+3" model in 2022 and 2023, this provides a basis for promoting health literacy in our province in the future.
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Science Data Bank
创建时间:
2024-09-09



