Evidence map›Paper›PMID 42275630›Full record

Trial reportJournal of medical Internet research2026

Sociodemographic Paradoxes and Enrollment Differences in In-Person Versus Online Recruitment to a Mobile Health Smoking Cessation Intervention for Food-Insecure Adults: Secondary Analysis of a Randomized Controlled Trial.

Charles E Hoogland, Steven K Sutton, Sarah R Jones, Bence Nagy, Samuel J Brockway, David Himmelgreen, Thomas Mantz, Michael S Businelle, Ya-Chen Tina Shih, Jennifer I Vidrine and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Charles E HooglandDepartment of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0000-0001-7735-1931
Steven K SuttonDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, United States.ORCID http://orcid.org/0000-0002-2504-7601
Sarah R JonesDepartment of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0000-0001-5513-2527
Bence NagyDepartment of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0009-0001-0820-0264
Samuel J BrockwayDepartment of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0009-0000-4761-768X
David HimmelgreenDepartment of Anthropology, Center for the Advancement of Food Security and Healthy Communities, University of South Florida, Tampa, FL, United States.ORCID http://orcid.org/0009-0006-8366-6095
Thomas MantzFeeding Tampa Bay, Tampa, FL, United States.ORCID http://orcid.org/0009-0002-6532-5124
Michael S BusinelleTSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.ORCID http://orcid.org/0000-0002-9038-2238
Ya-Chen Tina ShihJonsson Comprehensive Cancer Center, Program in Cancer Health Economics Research, Department of Radiation Oncology, School of Medicine, UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0001-7290-3864
Jennifer I Vidrine *Department of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0000-0002-9997-4459
Damon J Vidrine *Department of Health Outcomes & Behavior, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, FL, 33612, United States, 1 (813) 745-7937.ORCID http://orcid.org/0000-0002-8711-796X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Little is known about (1) sociodemographic, psychosocial, or smoking-related differences among individuals recruited to smoking cessation randomized controlled trials (RCTs) using in-person versus online recruitment methods or (2) the relative speed of recruitment using these 2 approaches. This secondary analysis is the first to examine these comparisons in a smoking cessation RCT for people experiencing food insecurity, a vulnerable special population for whom quitting is especially urgent. Objective: To compare (1) baseline sociodemographic, smoking-related, and psychosocial characteristics; and (2) screening, eligibility, and enrollment rates of in-person versus online recruits to a smoking cessation RCT for people experiencing food insecurity. Methods: Participants completed a brief eligibility questionnaire and a baseline assessment via tablet (in person) or personal electronic device (after clicking an online advertisement). Eligibility required past-30-day food aid use, smoking ≥5 cigarettes per day, and willingness to attempt quitting within 7 days post enrollment. Responses were compared using chi-squared and Fisher exact tests (categorical variables) and 2-tailed t tests (continuous variables). Results: Enrollees recruited online endorsed greater food insecurity (mean 4.5, SD 1.9 vs mean 3.0, SD 2.3; P<.001) and were more likely to be educated beyond high school or equivalent (69% vs 49%; P<.001), have household income of US $20,000 or more (46% vs 36%; P=.03), and be non-Hispanic White (77% vs 50%; P<.001). Online recruits indicated lower motivation to quit smoking (Contemplation Ladder; mean 7.2, SD 2.4 vs mean 8.0, SD 2.8; P<.001) and smoking cessation self-efficacy (mean 20.5, SD 8.0 vs mean 23.2, SD 8.6; P<.001). Online recruits also reported lower subjective social status (mean 4.6, SD 2.0 vs mean 5.9, SD 2.2; P<.001), greater financial strain (mean 17.9, SD 6.3 vs mean 16.2, SD 6.6; P=.004), more depressive symptoms (mean 8.6, SD 6.3 vs mean 7.4, SD 6.1; P=.04), greater loneliness (mean 6.0, SD 2.1 vs mean 5.2, SD 2.0; P<.001), less resilience (mean 19.5, SD 5.1 vs mean 20.5, SD 4.3; P=.02), less alcohol misuse (27% vs 37%; P=.02), and more past-30-day cannabis use (25% vs 15%; P=.01). Enrollment rates were higher online (64.8 per month; n=324) than in-person (7.7 per month; n=178). Although screened eligible at similar rates whether recruited online or in person (79% vs 75%; P=.10), eligible online individuals were more likely to enroll (71% vs 49%; P<.001). Conclusions: This study is the first to compare baseline participant characteristics by recruitment method (in person vs online) in a cessation RCT for people experiencing food insecurity and to evaluate the relative pace of recruitment via those methods. Online and in-person recruits were demographically and psychosocially distinct, and online recruitment was associated with faster accrual than in-person recruitment. These findings inform recruitment strategies for cessation interventions, especially those targeting food-insecure individuals.

Indexed as

Food InsecurityInternetPatient SelectionSmoking CessationTelemedicineAdultFemaleHumansMaleMiddle AgedSociodemographic Factorsfood assistancefood insecurityrandomized controlled trialrecruitment strategiessmoking cessationsocial status

Identifiers

PMID42275630
PMCPMC13258061

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.