Online recruitment of youth for mHealth studies

Abstract

Background: Social networking sites and apps have emerged as an opportunity to engage in research young men who have sex with men (YMSM) at risk of HIV infection who may not be otherwise reached by in-person recruitment efforts. This paper highlights lessons learned, best practices and on-going recruitment challenges in the iTech network of the NIH Adolescent Trials Network for HIV Interventions.

Methods: Recruitment was conducted for four randomized controlled trials (RCTs) of mHealth HIV prevention interventions for YMSM living in 10 US cities. Advertising was purchased on Facebook, Instagram, Snapchat, Twitter and Grindr. Users who clicked on banner ads were taken directly to a study-specific eligibility screener and if eligible, were asked to provide contact information for follow-up by respective study site staff. Ad and screening metrics (impressions, clicks, cost per click (CPC), click-through rate (CTR), number screened, number eligible, number who provided contact information and cost per eligible contact) were compared across platforms, studies and geographic areas (where available). Screening metrics were also calculated for in-person recruitment efforts.

Results: Grindr and Snapchat ads produced the highest CTRs as compared to Facebook ads. However, these ads had the lowest proportions of users who initiated eligibility screeners and ultimately Facebook ads yielded the lowest cost per eligible contact across studies. Instagram ads yielded the highest proportions of eligible contacts who were racial/ethnic minorities and under the age of 18. Geographic variability in cost per eligible contact was observed for studies with identical eligibility criteria running concurrently in different regions, driven by both advertising costs and the screening and eligibility rates. Despite lower eligibility rates, the total numbers of eligible contacts were higher for online advertising campaigns, as compared to other recruitment efforts, for all studies except P3. Ads recruiting for P3 had the highest cost per eligible contact, likely due to this study having the most stringent eligibility criteria of the studies described.

Conclusions: We implemented a successful online advertising strategy to recruit YMSM at high risk for HIV infection into four RCTs of mHealth interventions. This report provides a framework for evaluation of data from future online recruitment efforts across platforms and geographic areas, regardless of inevitable changes in the digital marketing space.

Keywords: Adolescent; HIV; advertising; social media.

Figure 1

Flow diagram of cascade between ad launch and study enrollment, with data source (ad platform or eligibility screener) for various metrics indicated.

Figure 2

Selected examples of online advertisements. (A) Facebook ad for MyChoices study; (B) Instagram ad for MyChoices study; (C) Stills from Snapchat video ad for Get Connected study; (D) Grindr ad for LYNX study; (E) Twitter ad for P3 study.