Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Massachusetts General Hospital, Boston, Massachusetts, USA
Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Massachusetts General Hospital, Boston, Massachusetts, USA.
BMJ Open. 2021 Oct 25;11(10):e043830. doi: 10.1136/bmjopen-2020-043830.
Many studies have documented significant associations between religion and spirituality (R/S) and health, but relatively few prospective analyses exist that can support causal inferences. To date, there has been no systematic analysis of R/S survey items collected in US cohort studies. We conducted a systematic content analysis of all surveys ever fielded in 20 diverse US cohort studies funded by the National Institutes of Health (NIH) to identify all R/S-related items collected from each cohort's baseline survey through 2014.
An R|S Ontology was developed from our systematic content analysis to categorise all R/S survey items identified into key conceptual categories. A systematic literature review was completed for each R/S item to identify any cohort publications involving these items through 2018.
Our content analysis identified 319 R/S survey items, reflecting 213 unique R/S constructs and 50 R|S Ontology categories. 193 of the 319 extant R/S survey items had been analysed in at least one published paper. Using these data, we created the R|S Atlas (https://atlas.mgh.harvard.edu/), a publicly available, online relational database that allows investigators to identify R/S survey items that have been collected by US cohorts, and to further refine searches by other key data available in cohorts that may be necessary for a given study (eg, race/ethnicity, availability of DNA or geocoded data).
R|S Atlas not only allows researchers to identify available sources of R/S data in cohort studies but will also assist in identifying novel research questions that have yet to be explored within the context of US cohort studies.
许多研究都记录了宗教和精神信仰（R/S）与健康之间存在显著关联，但很少有前瞻性分析能够支持因果推断。迄今为止，还没有对美国队列研究中收集的 R/S 调查项目进行系统分析。我们对美国国立卫生研究院（NIH）资助的 20 项不同的美国队列研究中进行的所有调查进行了系统的内容分析，以确定从每个队列的基线调查中收集的所有与 R/S 相关的项目，截至 2014 年。
从我们的系统内容分析中开发了一个 R/S 本体论，以将所有识别出的 R/S 调查项目分类到关键概念类别中。对每个 R/S 项目进行了系统的文献综述，以确定通过 2018 年涉及这些项目的任何队列出版物。
我们的内容分析确定了 319 个 R/S 调查项目，反映了 213 个独特的 R/S 结构和 50 个 R/S 本体论类别。319 个现存的 R/S 调查项目中有 193 个已在至少一篇已发表的论文中进行了分析。利用这些数据，我们创建了 R/S 图谱（https://atlas.mgh.harvard.edu/），这是一个公开的在线关系数据库，允许研究人员识别已被美国队列收集的 R/S 调查项目，并通过其他可能对特定研究必要的队列中可用的数据（例如，种族/族裔、DNA 或地理编码数据的可用性）进一步细化搜索。
R/S 图谱不仅允许研究人员识别队列研究中可用的 R/S 数据来源，还将有助于确定尚未在 US 队列研究背景下探索的新研究问题。
