在COVID-19大流行期间招募难以接触的人口
Jacob Boelter1, Alexis M Dennis1, Lisa Klein Vogel1
1University of Wisconsin-Madison.
概括
由于COVID-19大流行,需要调整基于社区的研究招聘. 这项研究成功地利用了虚拟方法来识别和吸引难以接触的人群,为未来受限制的研究环境提供了一个模型.
科学领域:
- 公共卫生 公共卫生
- 定性研究方法 定性研究方法
- 社区参与 社区参与
背景情况:
- 随着COVID-19的流行,传统的研究,特别是基于社区的样本生成被严重扰乱.
- 招募难以接触的群体带来了独特的挑战,与大流行相关的限制加剧了这一挑战.
研究的目的:
- 描述面对面招聘策略与虚拟方法的适应.
- 确定有效的方法来传播研究信息,并与难以接触的参与者进行虚拟联系.
- 为了在有限的条件下为未来的研究人员招聘提供见解.
主要方法:
- 在2021年底进行了两项定性研究研究.
- 将传统的面对面招聘技术调整为虚拟平台.
- 专注于识别和吸引难以接触的社区人口.
主要成果:
- 成功地从面对面转向研究信息的虚拟传播.
- 与以前难以接触的人群建立虚拟联系.
- 展示了虚拟招聘策略的可行性.
结论:
- 招聘方法的虚拟适应对于吸引难以接触的群体是有效的.
- 这些适应的策略提供了有价值的替代品,当亲自研究是有限的.
- 这种方法对提高未来研究工作的弹性和适应性有影响.
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