Assessing knowledge, attitudes, and practices towards causal directed acyclic graphs: a qualitative research project.
Assessing knowledge, attitudes, and practices towards causal directed acyclic graphs: a qualitative research project.
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DOI：
10.1007/s10654-021-00771-3
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发表时间：
2021-07
影响因子：
13.6
通讯作者：
Murray EJ
中科院分区：
文献类型：
--
作者：
Barnard-Mayers R;Childs E;Corlin L;Caniglia EC;Fox MP;Donnelly JP;Murray EJ
因果图提供了一个关键的工具，优化因果效应估计的有效性。虽然大量的文献存在的数学理论基础的因果图的使用，较少的文献存在，以帮助应用研究人员了解如何最好地开发和使用因果图在他们的研究项目。我们试图了解为什么研究人员做或不经常使用DAG的调查实践流行病学家和医学研究人员对他们的知识，兴趣水平，态度和实践中使用的因果图在应用流行病学和健康研究。我们使用Twitter和流行病学研究协会来传播这项调查。总体而言，大多数参与者报告说，他们对使用因果图感到满意，并报告说在他们的研究中“有时”、“经常”或“总是”使用因果图。接受培训似乎可以提高对因果图中所示假设的理解。许多没有使用因果图的受访者报告说，缺乏知识是他们在研究中使用DAG的障碍。流行病学家和医学研究人员对因果关系图很感兴趣，但对其理解存在一些障碍。需要更多的培训和更明确的指导。此外，方法论的发展，可视化的影响措施的修改和相互作用的因果关系图是必要的。
Causal graphs provide a key tool for optimizing the validity of causal effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects. We sought to understand why researchers do or do not regularly use DAGs by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. We used Twitter and the Society for Epidemiologic Research to disseminate the survey. Overall, a majority of participants reported being comfortable with using causal graphs and reported using them ‘sometimes’, ‘often’, or ‘always’ in their research. Having received training appeared to improve comprehension of the assumptions displayed in causal graphs. Many of the respondents who did not use causal graphs reported lack of knowledge as a barrier to using DAGs in their research. Causal graphs are of interest to epidemiologists and medical researchers, but there are several barriers to their uptake. Additional training and clearer guidance are needed. In addition, methodological developments regarding visualization of effect measure modification and interaction on causal graphs is needed.
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影响因子：
7.7
作者：
Textor, Johannes;van der Zander, Benito;Ellison, George T. H.
通讯作者：
Ellison, George T. H.
影响因子：
2.7
作者：
Pearl, J
通讯作者：
Pearl, J
DOI：
10.1016/0270-0255(86)90088-6
发表时间：
1986-01-01
期刊：
MATHEMATICAL MODELLING
影响因子：
--
作者：
ROBINS, J
通讯作者：
ROBINS, J
影响因子：
1.4
作者：
Pearl, Judea
通讯作者：
Pearl, Judea
影响因子：
5.4
作者：
VanderWeele, Tyler J.;Robins, James M.
通讯作者：
Robins, James M.