โก Quick Summary
This study investigates the challenges and strategies of using social media recruitment for public health research among Indigenous and Native American populations in California, particularly in the context of COVID-19 vaccination. The findings reveal that while social media offers opportunities, it also presents significant hurdles, especially due to AI-related fraud that compromises data quality.
๐ Key Details
- ๐ Population Studied: Indigenous and Native American individuals in California
- ๐งฉ Focus: COVID-19 vaccination and social networks
- โ๏ธ Recruitment Methods: Social media platforms, including Facebook
- ๐ Challenges: Limited recruitment success and data quality issues due to bots
๐ Key Takeaways
- ๐ Social media recruitment is increasingly used in public health research.
- ๐ค AI sophistication poses a significant challenge to authentic participant recruitment.
- ๐ Recruitment efforts were limited despite targeted strategies and community collaboration.
- ๐ก Effective strategies included adaptations to survey design and quality assurance checks.
- ๐ซ Standard Facebook targeting approaches were largely unsuccessful.
- ๐ Data quality was compromised by fraudulent entries from bots.
- ๐ Recommendations are provided to improve recruitment of hard-to-reach populations.
๐ Background
The use of social media for recruitment in public health research has gained traction, offering a unique avenue to reach diverse populations. However, the complexities of engaging Indigenous and Native American communities require tailored approaches that respect cultural sensitivities and address potential barriers. This study sheds light on the practical challenges faced in this context, particularly in the age of artificial intelligence.
๐๏ธ Study
Conducted in California, this study aimed to recruit Indigenous and Native American individuals for research on COVID-19 vaccination and social networks. The researchers explored various recruitment strategies, including the use of social media platforms like Facebook, while also considering the implications of AI on data integrity and participant authenticity.
๐ Results
The study found that despite efforts to engage the community, recruitment was limited. The use of standard Facebook targeting methods did not yield the expected results, and the presence of fraudulent data from bots significantly compromised the quality of the data collected. These findings highlight the need for innovative approaches to recruitment that can effectively navigate the challenges posed by AI.
๐ Impact and Implications
The implications of this study are profound, particularly for public health researchers aiming to engage hard-to-reach populations. The challenges identified underscore the necessity for adaptable recruitment strategies that can mitigate the risks associated with AI-related fraud. By improving recruitment methods, researchers can enhance data quality and ensure that the voices of Indigenous and Native American communities are accurately represented in health research.
๐ฎ Conclusion
This study highlights the critical challenges of using social media for recruitment in public health research among Indigenous and Native American populations. As AI continues to evolve, researchers must adapt their strategies to ensure authentic engagement and data integrity. The recommendations provided can serve as a guide for future studies, emphasizing the importance of community collaboration and innovative approaches in overcoming recruitment barriers.
๐ฌ Your comments
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Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age.
Abstract
Using social media recruitment for public health research presents both opportunities and challenges. Despite its increased use, few studies have detailed the practical issues, challenges encountered, and alternative strategies available for social media recruitment. This paper explores strategies for recruiting Indigenous and Native American populations in California for a study on COVID-19 vaccination and social networks. We describe different recruitment approaches, challenges faced, and pros and cons of strategies used to enhance data quality and efficiency, including survey design considerations, Facebook targeting versus use of research panels, quality assurance checks, and decisions around participant incentives. Our local setting involved recruiting Native American and Mesoamerican Indigenous individuals living in California through social media platforms. We highlight key adaptations to survey design, recruitment strategies, and data cleaning processes, noting what approaches that were effective and those that were not. Despite targeted efforts and community collaboration, recruitment was limited, and fraudulent data from bots significantly compromised data quality. Standard Facebook targeting approaches were largely unsuccessful. Our findings suggest that the increasing sophistication of artificial intelligence is becoming a substantial obstacle to authentic participant recruitment through social media. We offer recommendations to improve recruitment of hard-to-reach populations and mitigate AI-related fraud risks in future research.
Author: [‘Diamond-Smith N’, ‘Comfort A’, ‘Epperson A’, ‘Riley AR’, ‘Beylin N’, ‘Garcia M’, ‘Francis S’, ‘Abascal Miguel L’]
Journal: JMIR Public Health Surveill
Citation: Diamond-Smith N, et al. Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age. Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age. 2025; 11:e76677. doi: 10.2196/76677