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重症监护病房试验的核心社会人口统计学数据变量(CoDe-IT):使用德尔菲共识过程生成核心数据变量的方案。

Core socioDemographic data variables in ICU Trials (CoDe-IT): a protocol for generating core data variables using a Delphi consensus process.

机构信息

Department of Critical Care Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada.

Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.

出版信息

BMJ Open. 2024 Jul 23;14(7):e082912. doi: 10.1136/bmjopen-2023-082912.

Abstract

INTRODUCTION

Sociodemographic variables influence health outcomes, either directly (ie, gender identity) or indirectly (eg, structural/systemic racism based on ethnoracial group). Identification of how sociodemographic variables can impact the health of critically ill adults is important to guide care and research design for this population. However, despite the growing recognition of the importance of collecting sociodemographic measures that influence health outcomes, insufficient and inconsistent data collection of sociodemographic variables persists in critical care studies. We aim to develop a set of core data variables (CoDaV) for social determinants of health specific to studies involving critically ill adults.

METHODS AND ANALYSIS

We will conduct a scoping review to generate a list of possible sociodemographic measures to be used for round 1 of the modified Delphi processes. We will engage relevant knowledge users (previous intensive care unit patients and family members, critical care researchers, critical care clinicians and research co-ordinators) to participate in the modified Delphi consensus survey to identify the CoDaV. A final consensus meeting will be held with knowledge user representatives to discuss the final CoDaV, how each sociodemographic variable will be collected (eg, level of granularity) and how to disseminate the CoDaV for use in critical care studies.

ETHICS AND DISSEMINATION

The University of Calgary conjoint health research ethics board has approved this study protocol (REB22-1648).

摘要

简介

社会人口统计学变量会直接(例如,性别认同)或间接(例如,基于族裔群体的结构性/系统性种族主义)影响健康结果。确定社会人口统计学变量如何影响重症成年人的健康状况对于指导该人群的护理和研究设计非常重要。然而,尽管越来越认识到收集影响健康结果的社会人口统计学措施的重要性,但在重症监护研究中,社会人口统计学变量的数据收集仍然不足且不一致。我们旨在为涉及重症成年人的研究制定一组特定于健康社会决定因素的核心数据变量 (CoDaV)。

方法和分析

我们将进行范围综述,以生成一份可能的社会人口统计学措施清单,用于修改后的德尔菲法流程的第一轮。我们将邀请相关知识使用者(以前的重症监护病房患者及其家属、重症监护研究人员、重症监护临床医生和研究协调员)参与修改后的德尔菲共识调查,以确定 CoDaV。将与知识使用者代表举行最终共识会议,讨论最终的 CoDaV、如何收集每个社会人口统计学变量(例如,粒度级别)以及如何传播 CoDaV 以供重症监护研究使用。

伦理和传播

卡尔加里大学联合健康研究伦理委员会已批准本研究方案(REB22-1648)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e029/11268068/4e207527be02/bmjopen-14-7-g001.jpg

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