检测和防止假冒参与者:定性研究人员的方法和建议
Kristina Medero1, Hamdi Abdi1, CeRon Ford1
1Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, USA.
Qualitative health research
|April 18, 2025
概括
质量研究人员在远程数据收集中面对欺骗性参与者. 这项研究确定了红旗,并提供了确保研究有效性和可信度的策略,敦促机构关注这些结构性问题.
科学领域:
- 社会科学 社会科学 社会科学
- 定性研究方法 定性研究方法
- 数字研究 数字研究
背景情况:
- 由于COVID-19的流行,人们不得不从传统的面对面的定性数据收集转向远程和数字方法.
- 这种过渡带来了挑战,包括出现了"骗子参与者",他们伪装自己加入研究.
研究的目的:
- 在定性研究中识别和分类与骗子参与者相关的红旗.
- 提出方法和建议,以检测和防止骗子参与者.
- 在机构层面上解决假冒参与者所带来的结构性挑战.
主要方法:
- 关于两项涉及远程数据收集的定性研究案例研究的反思.
- 在招聘和数据收集阶段识别和分类红旗.
- 开发用于检测和防止假冒参与者的策略.
主要成果:
- 确定了几个红旗,按研究阶段 (招聘和数据收集) 分类.
- 开发了方法和建议,以减轻假冒参与者对研究有效性的影响.
- 该研究强调,需要机构关注与假冒参与者相关的结构性问题.
结论:
- 实施推策略对于保持定性研究的完整性至关重要,特别是随着对数字招聘的依赖日益增加.
- 解决骗子参与者的问题需要一个系统的方法,涉及学术界,机构审查委员会,出版商和审稿人.
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