[基于数据分析复杂性的公共卫生研究分类学]
José Antonio Supo Condori1,2, Héctor Raúl Zacarías Ventura2,3, Carlos Felipe Palacios Rosado1,4
1Escuela de Posgrado. Facultad de Medicina. Universidad Nacional de San Agustín de Arequipa. Arequipa. Perú.
Revista espanola de salud publica
|January 30, 2026
概括
本研究引入了公共卫生研究的六级分类,优先考虑数据分析的复杂性. 该框架帮助研究人员和决策者协调目标,设计和技术,以获得更好的公共卫生结果.
科学领域:
- 公共卫生研究方法论研究方法论
- 定性研究设计 定性研究设计
背景情况:
- 公共卫生研究需要操作分类,重点关注数据分析的复杂性.
- 现有的分类通常优先考虑研究设计或目的而不是分析深度.
研究的目的:
- 构建公共卫生研究水平的新型分类.
- 该分类是基于数据的分析处理,使用基于理论的原则.
主要方法:
- 理论-构造性的定性研究方法.
- 在主要数据库 (PubMed,Scopus,Web of Science等) 进行代文献搜索. ) 的情况.
- 对35个来源的文档分析,采用开放式,轴向式和选择性编码,并进行持续比较.
主要成果:
- 公共卫生研究的六级分类出现了:探索性,描述性,关系性,解释性,预测性和应用性.
- 每个级别由所采用的数据分析类型来定义,从没有统计数据到改进方法.
- 为了可重复性,为每个级别 (目的,分析单元,技术,示例) 建立了操作定义.
结论:
- 拟议的分类为公共卫生研究提供了一个连贯,可验证和可复制的框架.
- 它将数据分析作为研究结构的关键标准,改善目标,设计和技术之间的协调.
- 该分类为研究人员,审查人员和决策者提供了一个操作工具,并建议进行实证验证.
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