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观察性研究中往往存在未知或未测量的混杂因素，是流行病学因果关联研究中的重大挑战。本文介绍一种可以应用在观察性研究中的一种对未知/未测量混杂因素进行识别和效应评估的工具——“探针变量”。其主要可以分为暴露探针变量、结局探针变量以及中介探针3种形式，前2种不仅可以对未知/未测量混杂因素进行识别，也可以对其效应量进行估计，从而揭示真实的暴露与结局之间的关联。而中介探针则是针对“中介因子”进行控制，从而识别暴露和结局之间是否存在未测量混杂因素。该理论实践过程中最大的困难在于“探针变量”的选择和确定，不恰当的“探针变量”可能引入新的混杂，导致未测量混杂因素识别不准确。“探针变量”可以推荐作为观察性研究报告中的一项敏感性分析内容，有助于读者真实理解暴露与结局之间的关联，增加观察性流行病学研究中的证据力度。“,”There are usually unknown or unmeasured confounders in the observational study, which is a significant challenge in epidemiological causal association research. This paper presents a tool for identification and effect assessment of unknown/unmeasured confounders in observational studies: probe variables. It can be divided into three forms: exposure probe variable, outcome probe variable, and mediation probe variable. The first two types can identify unknown/unmeasured confounding factors and estimate their size of effect to reveal the real correlation between exposure and outcome. The mediation probe variable controls for “mediating factors” to identify unmeasured confounders between exposure and results. The most significant difficulty in this theory's practice is selecting and determining “probe variables.” Improper probe variables may introduce unknown confounders, which may lead to false identification of unmeasured confounders. Probe variables can be recommended as a sensitivity analysis in observational studies to help readers truly understand the association between exposure and outcomes and to increase the strength of evidence in observational epidemiological studies.