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一项关于加拿大安大略省公共卫生部门在 COVID-19 大流行期间收集社会人口数据的促成因素和障碍的研究。

A study of the enablers and barriers to the collection of sociodemographic data by public health units in Ontario, Canada during the COVID-19 pandemic.

机构信息

Upstream Lab, MAP Centre for Urban Health Solutions, St. Michael's Hospital, Toronto, ON, Canada.

Peel Public Health, Mississauga, ON, Canada.

出版信息

BMC Public Health. 2024 Nov 6;24(1):3061. doi: 10.1186/s12889-024-20519-4.

Abstract

BACKGROUND

Collection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario's public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination.

METHODS

As part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario's 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description.

RESULTS

SDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. Identified barriers to SDD collection included: provincial data systems being perceived as lacking user-friendliness, SDD collection "was not a priority," time and other constraints on building staff and client rapport, and perceived discomfort with asking and answering personal SDD questions.

CONCLUSION

A combination of provincial and local organizational strategies including supportive data systems, training, and frameworks for data collection and use, are needed to normalize and scale up SDD collection by local health units beyond the context of the COVID-19 pandemic.

摘要

背景

收集和使用社会人口统计学数据(SDD),包括种族、族裔和收入,是了解健康不平等现象的基础。安大略省的公共卫生部门在 COVID-19 病例管理和疫苗接种活动中收集 SDD。本研究旨在确定在 COVID-19 病例管理和疫苗接种期间收集 SDD 的促成因素和障碍。

方法

作为一项更大的混合方法研究的一部分[1],使用定性方法来确定在 COVID-19 大流行期间收集 SDD 的促成因素和障碍。采用目的抽样法从安大略省的 34 个公共卫生部门招募参与者。使用 Zoom 在线进行了 16 个焦点小组和 8 个访谈。访谈数据采用归纳和演绎定性描述进行转录和分析。

结果

SDD 收集的促成因素包括:法律规定收集 SDD 并拥有专门的数据系统、技术和法律支持、高级管理层支持 SDD 收集、在工作人员和客户之间建立融洽关系和信任,以及从当地社区和其他司法管辖区的经验中获得洞察力。确定的 SDD 收集障碍包括:省级数据系统被认为缺乏用户友好性、SDD 收集“不是优先事项”、建立工作人员和客户融洽关系的时间和其他限制,以及对询问和回答个人 SDD 问题感到不适。

结论

需要省级和地方组织策略的结合,包括支持性的数据系统、培训以及数据收集和使用的框架,以便在 COVID-19 大流行之外,由地方卫生部门将 SDD 收集规范化和扩大规模。

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