AI 中文总结
针对数字健康测量支撑科学、临床或监管结论的程度问题，提出将推断有效性评估作为连接测量系统证据与可信结论的下游评估层。
AI 中文摘要
数字健康测量正日益为治疗评估、风险分级、临床监测及监管决策提供依据。现有有效性概念涉及测量的技术可靠性、临床意义、可用性与可扩展性，而推断有效性关注测量支撑科学、临床或监管结论的程度。我们提议将推断有效性评估作为下游评估层，用于连接测量系统证据与可信结论。
英文摘要
Digital health measures increasingly inform treatment evaluation, risk classification, clinical monitoring, and regulatory decisions. Existing validity concepts concern a measure's technical soundness, clinical meaningfulness, usability, and scalability. Inferential validity concerns how well a measure supports a scientific, clinical, or regulatory conclusion. We propose assessing inferential validity as a downstream evaluation layer that links measurement system evidence to trustworthy conclusions.
