Abstract
Social work scholars are increasingly conducting research using virtual spaces such as survey platforms, video interfaces, email, and online communities. Internet-based approaches can increase access to historically and socially excluded groups. However, online methods are also prone to data quality issues. Findings based on fraudulent data can result in policies, programming, and services that are not reflective of the lived experiences and needs of disenfranchised groups. To ensure social workers do not perpetuate harm by reporting findings from nonrepresentative survey responses, it is imperative that our data are valid. Authors of this article used case studies to share their experiences with online survey fraud, discussing how they mitigated challenges with bots, fake respondents, and multiple responses in studies with foster care and LGBTQ+ communities. Authors share how they centered community perspectives to inform recruitment and data collection practices to increase their capacity to identify valid data. They describe a rigorous, multiphase process for assessing data validity in real time based on lessons learned. Finally, they provide reflection questions that highlight important concepts for researchers to consider when using online recruitment and survey techniques with disenfranchised groups.
| Original language | English |
|---|---|
| Pages (from-to) | 185-192 |
| Number of pages | 8 |
| Journal | Social Work Research |
| Volume | 49 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Sep 2025 |
Keywords
- bots
- data validity
- fraudulence
- online surveys
- social work
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