我们可以通过检查该领域使用的研究设计来了解该领域正在解决的研究问题。本手稿通过描述国家卫生研究院通过赠款和合作协议支持的初级和二级预防研究中包含的研究设计的分布和趋势,研究了预防研究中正在解决的研究问题。连同预防研究的类型,人口,理据,暴露,以及与每种设计类型相关的结果。疾病预防办公室开发了一种分类法,对NIH资助的新校外研究项目进行分类,并创建了一个数据库,其中包含2012-2019财政年度的14,523个研究项目的代表性样本。对数据进行加权以代表整个校外研究组合。利用这个数据集,疾病预防办公室对NIH资助的一级和二级预防研究申请中提出的研究设计进行了表征.在FY12-19期间,NIH支持的新预防研究应用中提出的最常见的研究设计是观察性设计(63.3%,95%CI61.5%-65.0%),对现有数据的分析(44.5%,95%CI:42.7-46.3),方法研究(23.9%,95%CI:22.3-25.6),和随机干预(17.2%,95%CI:16.1%-18.4%)。观察性研究设计主导了一级预防研究,而干预设计在二级预防研究中更为常见。观察性设计对于难以操纵的曝光更为常见(例如,遗传学,化学毒素,和传染病(不是肺炎/流感或艾滋病毒/艾滋病),而干预设计对于更容易操纵的曝光更常见(例如,教育/咨询,药物/设备,饮食/营养,和医疗保健服务)。干预设计对于罕见或潜伏期长的结果并不常见(例如,癌症,神经系统疾病,阿尔茨海默病)和更常见的结果是更常见的或影响更早预期的结果(例如,医疗保健交付,健康相关的生活质量,物质使用,和药物/设备)。对现有数据的观察设计和分析占主导地位,这表明,美国国立卫生研究院资助的大部分预防研究继续关注关联问题以及风险和保护因素的识别问题.随机和非随机干预设计的纳入频率要低得多,这表明,美国国立卫生研究院预防研究的一小部分集中在干预措施是否可用于改变风险或保护因素或改变其他与健康相关的生物医学或行为结果的问题上.考虑到我们对美国死亡和残疾的主要危险因素已经了解了多少,对观察性研究的更多关注令人惊讶。因为这些危险因素占美国县级死亡率的74%,因为它们在临床和公共卫生指南的制定中起着至关重要的作用,其开发人员通常比观察性研究的结果更重地权衡随机试验的结果。全国范围内死亡和残疾的改善更有可能来自基于干预研究的指南,以解决主要风险因素,而不是额外的观察性研究。
We can learn a great deal about the research questions being addressed in a field by examining the study designs used in that field. This manuscript examines the research questions being addressed in prevention research by characterizing the distribution and trends of study designs included in primary and secondary prevention research supported by the National Institutes of Health through grants and cooperative agreements, together with the types of prevention research, populations, rationales, exposures, and outcomes associated with each type of design. The Office of Disease Prevention developed a taxonomy to classify new extramural NIH-funded research projects and created a database with a representative sample of 14,523 research projects for fiscal years 2012-2019. The data were weighted to represent the entirety of the extramural research portfolio. Leveraging this dataset, the Office of Disease Prevention characterized the study designs proposed in NIH-funded primary and secondary prevention research applications. The most common study designs proposed in new NIH-supported prevention research applications during FY12-19 were observational designs (63.3%, 95% CI 61.5%-65.0%), analysis of existing data (44.5%, 95% CI: 42.7-46.3), methods research (23.9%, 95% CI: 22.3-25.6), and randomized interventions (17.2%, 95% CI: 16.1%-18.4%). Observational study designs dominated primary prevention research, while intervention designs were more common in secondary prevention research. Observational designs were more common for exposures that would be difficult to manipulate (e.g., genetics, chemical toxin, and infectious disease (not pneumonia/influenza or HIV/AIDS)), while intervention designs were more common for exposures that would be easier to manipulate (e.g., education/counseling, medication/device, diet/nutrition, and healthcare delivery). Intervention designs were not common for outcomes that are rare or have a long latency (e.g., cancer, neurological disease, Alzheimer\'s disease) and more common for outcomes that are more common or where effects would be expected earlier (e.g., healthcare delivery, health related quality of life, substance use, and medication/device). Observational designs and analyses of existing data dominated, suggesting that much of the prevention research funded by NIH continues to focus on questions of association and on questions of identification of risk and protective factors. Randomized and non-randomized intervention designs were included far less often, suggesting that a much smaller fraction of the NIH prevention research portfolio is focused on questions of whether interventions can be used to modify risk or protective factors or to change some other health-related biomedical or behavioral outcome. The much heavier focus on observational studies is surprising given how much we know already about the leading risk factors for death and disability in the USA, because those risk factors account for 74% of the county-level mortality in the USA, and because they play such a vital role in the development of clinical and public health guidelines, whose developers often weigh results from randomized trials much more heavily than results from observational studies. Improvements in death and disability nationwide are more likely to derive from guidelines based on intervention research to address the leading risk factors than from additional observational studies.