Causal inference in dentistry: Time to move forward.
Causal inference in dentistry: Time to move forward.
复制标题
牙科中的因果推断：是时候向前迈进了。
DOI：
10.1111/cdoe.12802
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发表时间：
2023
影响因子：
2.3
通讯作者：
D. Haag
中科院分区：
文献类型：
--
作者：
H. Schuch;G. G. Nascimento;F. Demarco;D. Haag
口腔疾病是一个关键的公共卫生挑战，与描述性和预测性流行病学一起，因果推理在制定和测试预防性口腔健康干预措施中发挥着至关重要的作用。通过不仅确定相关性，而且确定疾病的实际原因，因果推断可以量化干预措施的平均效果并指导政策。虽然作者通常对此并不明确，但大多数口腔健康研究都是以因果问题为指导的。然而，方法上的缺陷限制了他们的可解释性和他们的发现的实施。这份手稿是在口头研究中使用因果推理的行动呼吁。它的应用始于提出理论上合理的问题，明确因果关系，定义要评估的估计，并正确地测量它们。除了促进因果分析方法，我们强调需要更多的因果思维，以促进深思熟虑的研究问题，并使用适当的方法来回答他们。因果推断依赖于数据分析和数据质量的假设的可验证性，我们认为高质量的观察性研究可以用来估计平均因果效应。虽然个人努力接受牙科因果推理是必不可少的，他们不会产生实质性的结果，如果没有在该领域的系统和结构性的变化。我们敦促科学协会、资助机构、牙科学校和期刊促进研究的透明度、因果思维和因果推理项目，使该领域朝着更有意义的研究方向发展。现在也是研究人员向前迈进并与社区联系的时候了，共同进行调查并翻译他们的发现，并参与影响公共卫生的干预措施。最后，我们强调了从不同的数据来源和方法进行三角测量的重要性，以支持因果推理，并为有效改善人口口腔健康的干预措施提供决策依据。
Oral conditions represent a critical public health challenge, and together with descriptive and predictive epidemiology, causal inference has a crucial role in developing and testing preventive oral health interventions. By identifying not just correlations but actual causes of disease, causal inference may quantify the average effect of interventions and guide policies. Although authors are not usually explicit about it, most oral health studies are guided by causal questions. However, methodological deficiencies limit their interpretability and the implementation of their findings. This manuscript is a call to action on the use of causal inference in oral research. Its application starts with asking theoretically sound questions and being explicit about causal relationships, defining the estimates to evaluate, and measuring them properly. Beyond promoting causal analytical approaches, we emphasize the need for more causal thinking to promote thoughtful research questions and the use of appropriate methods to answer them. Causal inference relies on the plausibility of assumptions underlying the data analysis and the quality of the data, and we argue that high-quality observational studies can be used to estimate average causal effects. Although individual efforts to embrace causal inference in dentistry are essential, they will not yield substantial results if not led by a systematic and structural change in the field. We urge scientific societies, funding bodies, dental schools, and journals to promote transparency in research, causal thinking, and causal inference projects to move the field toward more meaningful studies. It is also time for researchers to move forward and connect with the community, co-produce investigations and translate their findings, and engage in interventions that impact public health. We conclude by highlighting the importance of triangulating results from different data sources and methods to support causal inference and inform decision-making on interventions to effectively improve population oral health.