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公共卫生研究中创建和使用因果循环图的多样方法:一项范围综述的建议

Diverse Approaches to Creating and Using Causal Loop Diagrams in Public Health Research: Recommendations From a Scoping Review.

作者信息

Baugh Littlejohns Lori, Hill Carly, Neudorf Cory

机构信息

Community Health and Epidemiology, University of Saskatchewan, Saskatoon, SK, Canada.

出版信息

Public Health Rev. 2021 Dec 14;42:1604352. doi: 10.3389/phrs.2021.1604352. eCollection 2021.

Abstract

Complex systems thinking methods are increasingly called for and used as analytical lenses in public health research. The use of qualitative system mapping and in particular, causal loop diagrams (CLDs) is described as one promising method or tool. To our knowledge there are no published literature reviews that synthesize public health research regarding how CLDs are created and used. We conducted a scoping review to address this gap in the public health literature. Inclusion criteria included: 1) focused on public health research, 2) peer reviewed journal article, 3) described and/or created a CLD, and 4) published in English from January 2018 to March 2021. Twenty-three articles were selected from the search strategy. CLDs were described as a new tool and were based upon primary and secondary data, researcher driven and group processes, and numerous data analysis methods and frameworks. Intended uses of CLDs ranged from illustrating complexity to informing policy and practice. From our learnings we propose nine recommendations for building knowledge and skill in creating and using CLDs for future public health research.

摘要

在公共卫生研究中,复杂系统思维方法越来越受到重视,并被用作分析视角。定性系统映射,尤其是因果循环图(CLD)的使用,被描述为一种很有前景的方法或工具。据我们所知,目前还没有已发表的文献综述来综合关于CLD如何创建和使用的公共卫生研究。我们进行了一项范围综述,以填补公共卫生文献中的这一空白。纳入标准包括:1)专注于公共卫生研究;2)同行评审期刊文章;3)描述和/或创建了CLD;4)2018年1月至2021年3月以英文发表。从搜索策略中选出了23篇文章。CLD被描述为一种新工具,基于一手和二手数据、研究者驱动和小组过程,以及众多数据分析方法和框架。CLD的预期用途从说明复杂性到为政策和实践提供信息不等。根据我们的经验,我们为未来公共卫生研究中创建和使用CLD的知识和技能培养提出了九条建议。

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