Evidence map›Paper›PMID 42568597›Full record

ArticleFrontiers in public health2026

Integration of community-engaged research technology and methods to guide tobacco regulatory science in rural communities.

Melissa H Abadi, Stephen R Shamblen, Mary Kay Rayens, Kirsten T Thompson, Amy Wildman, Kathy Rademacher, William Wieczorek, Raphael Nishimura, Shyanika W Rose, Mikhail N Koffarnus and 2 more

Abstract read
In one paragraph

Article in Frontiers in public health, 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

12 authors.

Melissa H AbadiPacific Institute for Research and Evaluation, Louisville Center, Louisville, KY, United States.
Stephen R ShamblenPacific Institute for Research and Evaluation, Louisville Center, Louisville, KY, United States.
Mary Kay RayensUniversity of Kentucky, College of Nursing, Lexington, KY, United States.
Kirsten T ThompsonPacific Institute for Research and Evaluation, Louisville Center, Louisville, KY, United States.
Amy WildmanPacific Institute for Research and Evaluation, Louisville Center, Louisville, KY, United States.
Kathy RademacherUniversity of Kentucky, College of Nursing, Lexington, KY, United States.
William WieczorekPacific Institute for Research and Evaluation, National Capital Region, Beltsville, MD, United States.
Raphael NishimuraUniversity of Michigan, Survey Research Center, Institute for Social Research, Ann Arbor, MI, United States.
Shyanika W RoseUniversity of Kentucky, College of Medicine, Lexington, KY, United States.
Mikhail N KoffarnusUniversity of Kentucky, College of Medicine, Lexington, KY, United States.
Seth HimelhochDivision of the Biological Sciences, University of Chicago, Chicago, IL, United States.
Ellen J HahnUniversity of Kentucky, College of Nursing, Lexington, KY, United States.

Funding

AppalTRuST Project 3: Impact of proposed tobacco product rules in Appalachia on consumption and product switching with the Experimental Tobacco MarketplaceU54DA058256 · NIDA · UNIVERSITY OF KENTUCKY · PI Mikhail Nikolaas Koffarnus · 2023 to 2026
$19.2M
NIDA NIH HHS U54 DA058256
6 · The paper itself

Abstract

Objective: This study aims to build a rural Appalachian cohort to examine how US Food and Drug Administration (FDA) Center for Tobacco Products (CTP) regulatory policies influence tobacco and nicotine product use across levels of rurality. Methods: The AppalTRUST (Appalachian Tobacco Regulatory Science Team) Cohort integrates four inter-connected Community-engaged Research + Technology (CEnRT) elements to support recruitment and retention: (1) building trust and cultural relevance; (2) addressing barriers to participation in research; (3) focusing on ethics and confidentiality; and (4) fostering ongoing and consistent collaboration between the scientific and field teams. The study uses a dual sampling design to recruit 1,000 quota-based non-probability sample participants and 1,000 address-based probability sample participants. Eligible adults (ages 18+) are recruited from two Appalachian Kentucky catchments spanning rural and peri-urban counties. A local field team combines culturally relevant engagement strategies with technology-enabled procedures, including virtual consent and participant tracking, to foster trust and relevance with an underserved population. Anticipated results: Recruitment is ongoing. Feasibility indicators include enrollment of 985 non-probability sample participants and 209 probability sample participants, a 16% direct-mail response rate, and a 62% participant preference for text-based consent and survey reminders. Expected outcomes include guidance for applying CEnRT approaches in underserved populations, characterization of tobacco and nicotine use trends across the rural-peri-urban continuum, and description of marketing exposure and consumer choice among subgroups of young adults and daily users in Appalachia. Findings will inform FDA CTP regulatory decision-making in rural Appalachian communities. Discussion: This integrated CEnRT approach shows promise for recruiting and retaining rural Appalachian adults by centering community voice, trust, confidentiality, and practical engagement strategies.

Indexed as

Community-Based Participatory ResearchRural PopulationAdolescentAdultAppalachian RegionFemaleHumansKentuckyMaleMiddle AgedTobacco ControlUnited StatesUnited States Food and Drug AdministrationYoung Adultcommunity-engaged researchmethodsruraltechnologytobaccotobacco regulatory science

Identifiers

PMID42568597
PMCPMC13447286

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.