无家可归的预测因素和后果:使用链接例行数据进行队列研究设计的协议
Eileen Mitchell1, Dermot O'Reilly1, Diarmuid O'Donovan1
1Centre for Public Health, Queen's University, Belfast, United Kingdom.
JMIR research protocols
|July 27, 2023
概括
这项研究将健康和住房数据联系起来,以了解北爱尔兰的无家可归. 结果将确定关键的风险因素和对这一脆弱人群的健康后果.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 社会流行病学 社会流行病学
背景情况:
- 在全球范围内,无家可归影响了超过1亿人,个人体验的身体和心理健康状况较差的比例更高.
- 行政数据对于了解无家可归的动态和影响越来越重要.
- 与普通人口相比,无家可归人口面临着严重的健康差异.
研究的目的:
- 整合行政医疗保健和社会住房数据,以确定无家可归的预测因素和后果.
- 获得对导致无家可归的因素和无家可归的结果的全面了解.
- 为无家可归者提供有针对性的干预和政策信息.
主要方法:
- 连接北爱尔兰各地的行政卫生和社会护理数据库.
- 进行描述性分析以确定无家可归者的趋势.
- 调查与无家可归人口关键健康和社会结果相关的风险因素.
主要成果:
- 结果将传播给利益相关者,在会议上提出,并在学术期刊上发表.
- 将制定政策简报笔记,以向决策者提供关键发现的信息.
- 该研究将提供数据驱动的洞察力,了解无家可归人口的健康和社会护理需求.
结论:
- 这项研究将通过利用相关的行政数据,确定北爱尔兰无家可归的预测因素和后果.
- 这项研究旨在利用例行收集的健康和社会护理信息,阐明这个脆弱群体内的趋势和结果.
- 结果将有助于基于证据的战略,以解决无家可归问题和改善健康结果.
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