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Automated Tobacco Cessation Intervention for Parents in Pediatric Primary Care

2025· article· en· W4413758314 on OpenAlexaff
Emara Nabi-Burza, Brian P. Jenssen, Abra Jeffers, Janani Ramachandran, Jeritt G. Thayer, Bethany Hipple, Douglas E. Levy, Robert W. Grundmeier, Olivier Drouin, Márk Vangel, Nancy A. Rigotti, Tyra Bryant-Stephens, Ekaterina Nekrasova, Jonathan P. Winickoff, Alexander G. Fiks

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNational Cancer Institute
KeywordsPrimary careIntervention (counseling)Smoking cessationMedicineTobacco useFamily medicineEnvironmental healthNursing

Abstract

fetched live from OpenAlex

Importance: Treatment for tobacco use for parents in pediatric primary care settings is rarely provided but may support cessation and reduce childhood tobacco smoke exposure. Objective: To study the integration of the automated Clinical Effort Against Secondhand Smoke Exposure (eCEASE) tobacco cessation intervention into pediatric primary care via the electronic health record (EHR). Design, Setting, and Participants: This cluster-randomized clinical trial was conducted from July 16, 2021, to August 15, 2023, at 12 pediatric primary care practices in the Philadelphia, Pennsylvania, region. Participants included parents who used combusted tobacco in the past 7 days and attended a child's preventive health care visit. Intervention: In all practices, household members completed EHR previsit questionnaires about tobacco use. Parents in intervention practices were proactively offered eCEASE (automated delivery of nicotine replacement therapy [NRT], quitline and/or SmokefreeTXT enrollment, and navigator support). Control practice parents received usual care. Main Outcomes and Measures: The primary outcome was biochemically confirmed 7-day abstinence from combusted tobacco use by parents at the 1-year follow-up. Secondary outcomes included NRT and quitline and/or SmokefreeTXT use and recent quit attempts. Changes in cigarettes per day and smoking frequency (daily or nondaily) from baseline to 1-year follow-up were also examined. Results: Of 817 enrolled smoking parents (672 [82.3%] female), 323 of 408 (79.2%) in the intervention arm (6 practices) and 326 of 409 (79.7%) in the control arm (6 practices) were mothers; mean (SD) age was 36.17 (8.67) years. The follow-up survey was completed by 367 of 408 parents (90.0%) in the intervention arm and 368 of 409 (90.0%) in the control arm. Biochemically confirmed 7-day abstinence rates were 34 of 408 (8.3%) in the intervention arm vs 26 of 409 (6.4%) in the control arm (adjusted odds ratio, 1.34; 95% CI, 0.79-2.29). Among those who completed follow-up, 177 of 367 (48.2%) in the intervention arm vs 59 of 368 (16.0%) in the control arm reported using NRT; 93 of 367 (22.8%) and 8 of 368 (2.2%), respectively, reported using quitline and/or SmokefreeTXT messaging; and 294 of 367 (80.1%) vs 258 of 368 (70.1%), respectively, reported a quit attempt in the last 3 months. Compared with control practices, intervention practices reported a greater reduction in the mean (SD) number of cigarettes smoked daily (-3.32 [5.39] vs -1.81 [5.84]) and a greater reduction in the mean (SD) percentage of daily smokers (-35.2% [2.6%] vs -25.8% [2.6%]). Conclusions and Relevance: In this cluster-randomized clinical trial of an automated intervention to treat parental tobacco use in pediatric practices, the intervention did not significantly improve the primary outcome of quit rate at 1 year. Findings in this trial demonstrated increased treatment engagement and reductions in cigarette consumption, but additional strategies are needed to improve quit rates. Trial Registration: ClinicalTrials.gov Identifier: NCT04974736.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.340
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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