标题： 观察性研究中的因果语言：社会文化背景和团队构成 显示英文标题

标题： Causal Language in Observational Studies: Sociocultural Backgrounds and Team Composition

摘要： 在观察性研究中使用因果语言引发了对科学交流中夸大表述的担忧。 尽管有人认为这种语言应仅限于随机对照试验，但也有人认为严格的因果推断方法可以为观察性研究中的因果主张提供依据。 理想情况下，因果语言应与底层证据的强度相一致。 然而，通过使用计算语言学和回归方法分析超过90,000个观察性研究的摘要，我们发现因果语言在经验较少的作者、较小的研究团队、男性最后作者以及不确定性回避指数较高的国家的研究人员中更为常见。 我们的研究结果表明，因果语言的使用不仅由证据的强度驱动，还受到作者及其团队组成的社会文化背景的影响。 这项工作为理解科学交流中的系统性差异提供了新的视角，并强调了在评估科学主张时认识到这些人为因素的重要性。 显示英文摘要

摘要： The use of causal language in observational studies has raised concerns about overstatement in scientific communication. While some argue that such language should be reserved for randomized controlled trials, others contend that rigorous causal inference methods can justify causal claims in observational research. Ideally, causal language should align with the strength of the underlying evidence. However, through the analysis of over 90,000 abstracts from observational studies using computational linguistic and regression methods, we found that causal language are more common in work by less experienced authors, smaller research teams, male last authors, and researchers from countries with higher uncertainty avoidance indices. Our findings suggest that the use of causal language is not solely driven by the strength of evidence, but also by the sociocultural backgrounds of authors and their team composition. This work provides a new perspective for understanding systematic variations in scientific communication and emphasizes the importance of recognizing these human factors when evaluating scientific claims.