Targeted social media recruitment yielded a 27.2% consent rate among eligible men who smoke, significantly outperforming EHR-based recruitment using NLP (2.8%) or discrete fields (1.2%).
Does community recruitment yield higher consent rates compared to EHR-driven recruitment for a smoking cohort?
Community-based social media recruitment generated higher engagement and consent rates for a smoking study compared to EHR-based recruitment, which suffered from misclassification and low consent rates.
Absolute Event Rate: 0% vs 0%
Abstract Introduction: Electronic Health Records (EHRs) are broadly used for research recruitment; however, reported social histories such as smoking status are inconsistently reported, incomplete, or inaccurate. The goal of this review is to analyze lessons learned in recruiting men for a stress reactivity study and compare various recruitment yields across EHR versus community strategies. Methods: In a large Los Angeles tertiary health system, we conducted two EHR driven outreach waves from January 2024-June 2025 targeting African American/Black and non-Hispanic White men aged 21-75. The first wave utilized a natural language processing (NLP) query of a combination of notes, smoking-related terms, and smoking-related health history. The second wave manually queried discrete social history fields that recorded tobacco use. Recruitment from the first two waves was standardized, with potential participants contacted via multiple text, phone calls, and email attempts. Parallel community recruitment used targeted social media advertisements linked to a REDCap survey screener, plus recontact of a prior smoking cohort who consented to future studies. Primary measured outcomes were the consent rate, contact rate, and proportion misclassified as smokers (those who were identified via EHR as smokers but reported being “never-users”). Results: In EHR wave 1 (NLP wave), 579 participants were approached, with 171 (29%) reached and 16 consented (2.8%). Among those who declined, 77 (49.6%) reported having a never-smoking history. EHR wave 2 (discrete fields) had more participants (1,374 patients): 141 (10.2%) were reached, and 16 (1.2%) consented to join the study. Community ads screened 1,488 potential participants, 404 were eligible (27.2%) and 110 consented to participate in study activities (27.2%). Conclusions: EHR recruitment alone, particularly when NLP driven, was demonstrated to misclassify presumed smokers and yielded low consent rates. Wave 2 (discrete field of social history) yielded improvement in specificity but not engagement. Social media targeted outreach generated the most positive recruitment activity; however, this requires phone verification to ensure individual authenticity. Multimodal recruitment, coupled with standardized, longitudinal EHR capture of smoking intensity (in pack-years) and history is essential for representative and accurate enrollment and improving lung cancer screening referral uptake. Citation Format: Trista A. Beard, Diana L. Morales, Kelsie Campbell, Alexandra L. Lindgren, Chanita Hughes Halbert, . Recruiting men who smoke for lung cancer risk research: Lessons learned using the electronic health record and community recruitment strategies abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5041.
Beard et al. (Fri,) reported a other. Targeted social media recruitment yielded a 27.2% consent rate among eligible men who smoke, significantly outperforming EHR-based recruitment using NLP (2.8%) or discrete fields (1.2%).
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