Evidence map›Paper›PMID 42375166›Full record

ArticlePreventive medicine reports2026

Predictors of treatment engagement in a group-based, telehealth smoking cessation program.

Sarah M Noone, Emily A Atkinson, Andrea C King, Daniel J Fridberg, Emma I Brett

Abstract read
In one paragraph

Article in Preventive medicine reports, 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

5 authors.

Sarah M NooneUniversity of Chicago, Department of Psychiatry and Behavioral Neuroscience, 5841 S. Maryland Avenue, Chicago, IL 60637, United States of America.
Emily A AtkinsonUniversity of Chicago, Department of Psychiatry and Behavioral Neuroscience, 5841 S. Maryland Avenue, Chicago, IL 60637, United States of America.
Andrea C KingUniversity of Chicago, Department of Psychiatry and Behavioral Neuroscience, 5841 S. Maryland Avenue, Chicago, IL 60637, United States of America.
Daniel J FridbergUniversity of Chicago, Department of Psychiatry and Behavioral Neuroscience, 5841 S. Maryland Avenue, Chicago, IL 60637, United States of America.
Emma I BrettUniversity of Chicago, Department of Psychiatry and Behavioral Neuroscience, 5841 S. Maryland Avenue, Chicago, IL 60637, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Tobacco-related health disparities persist across age and socioeconomic status. Individual-level factors appear to influence engagement in smoking cessation treatment; however, findings have been mixed, with limited focus on telehealth treatment. The present study examined sociodemographic predictors of engagement in a telehealth smoking cessation program. Methods: Patients were primarily Black (78%), female (72%), and middle-aged or older (mean age = 58.2, range 21-92 years) adults who participated in a telehealth group smoking cessation program from 2020 to 2024 ( Results: Patients were more likely to complete treatment if they were older ( Conclusions: This study shows differences in treatment engagement based on individual-level factors; older age, White race, and having higher education was predictive of increased engagement. Increased treatment accessibility may improve engagement among those most at risk for smoking-related harms. Findings highlight the program's strength in engaging older patients in telehealth.

Indexed as

Group treatmentHealth disparitiesSmoking cessationTelehealthTreatment engagement

Identifiers

PMID42375166
PMCPMC13311180

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.