Successful Digital Recruitment of Adolescents for Population-Based Research: A Case Study of Methods and Strategies

Recruiting adolescents for research presents significant challenges across various health domains, including limited access to target populations, parental consent requirements, reluctance to disclose sensitive information, and emerging digital-specific obstacles such as fraudulent enrollments and advertising restrictions. This paper addresses how online recruitment can overcome these widely known challenges while navigating new methodological complexities. It describes online recruitment of adolescents into a vaping cessation randomized clinical trial as a case study demonstrating comprehensive strategies that successfully recruited 1681 participants aged 13-17 from across the United States. The systematic, multifaceted approach included: establishing youth advisory and data safety and monitoring boards to inform study design and optimize recruitment strategies; strategically selecting and optimizing digital recruitment channels (primarily Instagram) with careful attention to cost efficiency ($148 per enrolled participant); identifying and addressing fraudulent enrollments through both automated detection systems and manual verification protocols that captured 960 potentially suspicious entries; and implementing procedures for adolescent assent with IRB waiver of parental consent and ensuring decisional capacity through structured screening (73.7% pass rate). Privacy protections and advertising restrictions designed to protect minors, while necessary, required broader targeting approaches that increased recruitment costs and complexity. Despite these challenges, the trial achieved a sizable sample and enabled the first published randomized trial of a vaping cessation intervention for adolescents. This integrated framework provides actionable guidance for researchers conducting fully remote studies with adolescents, particularly those involving sensitive health behaviors where traditional recruitment methods may be insufficient or inappropriate.