To enhance representation in LCS research, we examined associations between participant characteristics and their preferred mode of survey completion among individuals eligible for LCS.

Between February 2023 and April 2024, prospective participants were identified using electronic healthcare records from Mass General Brigham and the University of Oklahoma Health Sciences (OUHSC). We offered three modes of survey completion: online, by mail, or by phone. Eligible participants were 50–80 years old, had smoked within the past 15 years, and spoke English or Spanish. We used multinomial logistic regression to estimate relative risk ratios (RRR).

Outreach to 2,822 individuals resulted in a sample of 315 participants. The mean age was 61.7 years (SD = 10.9). Most respondents were women (63.0%) and identified as White (63.3%), 29.8 % were Hispanic. The most common survey completion mode was mail (37.1%), followed by online (35.9%) and phone (27.0%). Characteristics associated with completion by mail were study site (RRR = 6.86, 95%CI:3.10–15.14), and race (RRR = 3.63, 95%CI:1.53–8.61); with respondents at OUHSC or who did not identify as White being more likely to choose mail over online modality. Characteristics associated with phone completion, included older age (RRR = 1.11, 95% CI: 1.03–1.20), Spanish language preference (RRR = 9.28, 95%CI:2.38–36.09), and with local government or community insurance (RRR = 9.91, 95% CI:1.92–51.3).

The current trend toward online surveys may not fully account for individual preferences for LCS research engagement, and could limit the representativeness in LCS studies if offline alternatives are not offered.

Digital tools offer promising solutions to improve eligibility screening, recruitment, and retention in research, particularly in human genetic studies where representative sampling is critical. SMS text messaging has been found effective in population-based survey research, but evidence of its impact on genetic study recruitment – and how it varies by demographics – is limited.

We examined the effect of tailored SMS messages on enrollment in a population-based genomic screening study. We assessed differences in message open and consent rates across four message types and explored how these outcomes varied by demographic factors.

Participants were randomized to receive one of four SMS messages emphasizing different social values: generic, individual impact, community impact, or research discoveries. We calculated descriptive statistics for open and consent rates and used generalized linear logistic regression and Pearson’s Chi-Square Test to assess demographic differences.

Among 15,977 messages sent, 2.4% were opened (n = 382), and 35.3% of those who opened consented (n = 135). Females were more likely than males to open (3.1% vs. 1.6%) and consent (1.1% vs. 0.5%). Individuals aged 30–39 had the highest open rate (3.4%), and those 40–49 had the highest consent rate (1.6%). Message type was not significantly associated with open or consent rates.

Sociodemographic factors were more predictive of engagement than message content. Tailoring messages by demographic group may improve recruitment in genomic studies. Future research should explore the drivers of participant engagement in digital recruitment strategies.