Rational numbers (i.e., fractions, percentages, decimals, and whole-number frequencies) are notoriously difficult mathematical constructs. Yet correctly interpreting rational numbers is imperative for understanding health statistics, such as gauging the likelihood of side effects from a medication. Several pernicious biases affect health decision-making involving rational numbers. In our novel developmental framework, the natural-number bias—a tendency to misapply knowledge about natural numbers to all numbers—is the mechanism underlying other biases that shape health decision-making. Natural-number bias occurs when people automatically process natural-number magnitudes and disregard ratio magnitudes. Math-cognition researchers have identified individual differences and environmental factors underlying natural-number bias and devised ways to teach people how to avoid these biases. Although effective interventions from other areas of research can help adults evaluate numerical health information, they circumvent the core issue: people’s penchant to automatically process natural-number magnitudes and disregard ratio magnitudes. We describe the origins of natural-number bias and how researchers may harness the bias to improve rational-number understanding and ameliorate innumeracy in real-world contexts, including health. We recommend modifications to formal math education to help children learn the connections among natural and rational numbers. We also call on researchers to consider individual differences people bring to health decision-making contexts and how measures from math cognition might identify those who would benefit most from support when interpreting health statistics. Investigating innumeracy with an interdisciplinary lens could advance understanding of innumeracy in theoretically meaningful and practical ways.

有理数（即分数、百分比、小数和整数频率）是出了名的困难数学构造。然而，正确解释有理数对于理解健康统计数据至关重要，例如衡量药物产生副作用的可能性。一些有害的偏见会影响涉及有理数的健康决策。在我们新颖的发展框架中，自然数偏差——一种将有关自然数的知识误用于所有数字的倾向——是影响健康决策的其他偏差的潜在机制。当人们自动处理自然数大小而忽略比率大小时，就会出现自然数偏差。数学认知研究人员已经确定了自然数偏差背后的个体差异和环境因素，并设计了方法来教人们如何避免这些偏差。尽管来自其他研究领域的有效干预可以帮助成年人评估数字健康信息，但它们绕过了核心问题：人们倾向于自动处理自然数的大小而忽视比率的大小。我们描述了自然数偏差的起源，以及研究人员如何利用这种偏差来提高对有理数的理解，并改善包括健康在内的现实环境中的无数问题。我们建议修改正规的数学教育，以帮助孩子们学习自然数和有理数之间的联系。我们还呼吁研究人员考虑人们在健康决策环境中带来的个体差异，以及在解释健康统计数据时，数学认知的措施如何识别最能从支持中受益的人。用跨学科的视角研究不懂数可以以理论上有意义和实用的方式推进对不懂数的理解。