Striking a Balance: Mitigating Fraud While Ensuring Equity in Online Qualitative Research Recruitment

寻求平衡:在减少欺诈的同时确保在线定性研究招募的公平性

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Abstract

After the COVID-19 pandemic, online recruitment became a critical component of qualitative research in health care fields. However, fraudulent participants targeting research incentives have become more prevalent in health studies, raising significant issues for research ethics, data integrity, and the inclusion of diverse patient voices. While qualitative health research aims to listen to and amplify patients' and communities' voices, such fraud can severely impact research quality and foster mistrust toward participants. This issue is particularly critical in qualitative studies, where careful communication, engagement, and mutual trust between researchers and participants are hallmarks of the research process, especially when working with populations considered marginalized. Behaviors that researchers may associate with fraudulent participants also appear in the communication patterns of groups considered marginalized, especially when discussing sensitive topics. This similarity could lead to misplaced suspicion, unintentionally disadvantaging populations considered marginalized when they attempt to share their experiences. In this paper, 3 qualitative nursing researchers reflect on their experiences with recruitment and data collection in recent studies and provide recommendations based on their experiences and a review of relevant literature. These include methods for addressing challenges related to potentially fraudulent participants and balancing ethical approaches with justice and inclusivity while preserving research integrity, drawing on existing strategies from previous studies facing similar issues. The paper also identifies unaddressed areas requiring future attention and highlights the importance of promoting inclusivity for diverse populations and populations considered marginalized who may be disproportionately affected by mistrust in participant integrity.

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