What does this research mean for the field?

Targeted social media recruitment yields significantly higher consent rates (27.2%) for enrolling men who smoke compared to EHR-based recruitment using NLP (2.8%) or discrete fields (1.2%), which suffer from high misclassification and low engagement. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The review aims to analyze recruitment lessons learned for a stress reactivity study targeting men who smoke, comparing EHR and community strategies.

April 5, 2026

Abstract 5041: Recruiting men who smoke for lung cancer risk research: Lessons learned using the electronic health record and community recruitment strategies

Resultado clave

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%).

Puntos clave

The review aims to analyze recruitment lessons learned for a stress reactivity study targeting men who smoke, comparing EHR and community strategies.
Conducted outreach waves using electronic health records from Jan 2024 to Jun 2025.
Used natural language processing to identify smokers and a separate query of social history fields.
Employed community recruitment strategies via social media and follow-up with a prior smoking cohort.
First EHR wave reached 29% of participants with a 2.8% consent rate.
Second EHR wave improved specificity but yielded a lower 1.2% consent rate.
Community outreach led to a 27.2% screening yield with 27.2% consenting to participate.

PICO estructurado

Does community recruitment yield higher consent rates compared to EHR-driven recruitment for a smoking cohort?

Población

African American/Black and non-Hispanic White men aged 21-75 targeted for a stress reactivity study in a large Los Angeles tertiary health system

Intervención

Community recruitment using targeted social media advertisements linked to a REDCap survey screener

Comparador

Electronic Health Record (EHR) driven outreach using natural language processing (NLP) queries and discrete social history fields

Resultado

Consent rate, contact rate, and proportion misclassified as smokers

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.

Resultado numérico

Tasa de eventos absoluta: 0% vs 0%

Resumen

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.

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