利用大数据平台推进“医教家结合”模式校园视力监测

Advancing Campus Vision Monitoring through the “Medical-Educational-Family Collaboration” Model Using a Big Data Platform

摘要: 目的：对比“医教家结合”校园视力监测新模式与传统视力监测模式的筛查效率，旨在为推广一种更高效、便捷且准确的视力监测模式提供依据。方法：采用随机抽样法选取300名学生，将其随机分成两组，分别使用“医教家结合”校园视力监测新模式与传统视力监测模式进行视力、屈光度检测，记录其筛查信息，对比两组在这个过程中所花费的时间，观察其结果并对比分析两组结果的差异是否具有统计学意义。结果：“医教家结合”视力监测新模式相较于传统视力监测模式极大地节省了筛查时间，提升了筛查效率，同时能够便捷地为教育部门、学校及家长提供直观的数据分析报告。结论：有效地推进“医教家”视力监测新模式，在节省时间成本的条件下，显著提升了筛查流程效率和用户满意度，为近视的早期监测、发现和干预提供了有力支持，并保证了数据的准确性、有效性、一致性和可比性。其对近视控制效果的长期影响，仍有待未来纵向研究进一步验证。

Abstract: Objective: To compare the screening efficiency of a new “medical-educational-family collaboration” school vision monitoring model with the traditional vision monitoring model, aiming to provide evidence for promoting a more efficient, convenient, and accurate vision monitoring approach. Methods: A random sampling method was used to select 300 students, who were then randomly divided into two groups. One group underwent vision and diopter testing using the new “medical-educational-family collaboration” school vision monitoring model, while the other group was tested using the traditional vision monitoring model. Screening information was recorded, and the time required for the process was compared between the two groups. The results were observed, and differences between the two groups were analyzed for statistical significance. Results: Compared to the traditional vision monitoring model, the new “medical-educational-family collaboration” vision monitoring model significantly reduced screening time and improved screening efficiency. Additionally, it provided intuitive data analysis reports for education departments, schools, and parents in a convenient manner. Conclusion: The effective implementation of the new “medical-educational-family collaboration” vision monitoring model significantly enhances the efficiency of the screening process and user satisfaction while reducing time costs. It provides strong support for the early monitoring, detection, and intervention of myopia, while ensuring data accuracy, validity, consistency, and comparability. The long-term impact of this model on myopia control requires further validation through future longitudinal studies.