In clinical science, what we choose to measure says a lot about our priorities and the underlying power-structures that shape research. Nowhere is this better reflected than in the choice of primary outcomes for randomised controlled trials (RCTs), which are still considered by many as the gold standard of evidence. Good confirmatory RCTs demand a strong hypothesis, and a strong hypothesis requires a specific endpoint to be chosen by the investigators. For some clinical fields and disease states, this choice is substantially harder to make than for others. Take depression for example, one of the most common mental illnesses and one of the largest contributors to morbidity and poor health in the world. With no reliable biomarkers for diagnosis, mental health clinicians are left to measure symptoms in the form of questions and answers covering topics like mood, appetite, and sleep, with different weights placed on different categories of cognitive and somatic symptoms depending on the assessment scale. Ultimately, the task with each scale is the same—to sum up the scores and reduce the mental health state of the person seeking care to a single number. For a clinical trial, the choice then becomes which scale to use.

中文翻译：

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衡量成功：主要结果的问题。

在临床科学中，我们选择衡量的内容充分说明了我们的优先事项以及影响研究的潜在力量结构。在选择随机对照试验（RCT）的主要结局方面，没有什么比这更好地反映了这一点，许多人仍将其视为证据的黄金标准。好的验证性随机对照试验需要强有力的假设，强有力的假设需要研究者选择特定的终点。对于某些临床领域和疾病状态，这种选择比其他方法要难得多。以抑郁症为例，抑郁症是世界上最常见的精神疾病之一，也是造成发病率和健康状况不佳的最大原因之一。没有可靠的生物标志物进行诊断，精神卫生临床医生应以问答形式来衡量症状，这些话题涵盖诸如情绪，食欲和睡眠之类的话题，并且根据评估量表将不同的权重置于不同类别的认知和躯体症状上。最终，每个量表的任务都是相同的—汇总分数并将寻求护理的人的心理健康状况降低到一个数字。对于临床试验，选择就变成了要使用的量表。