Trial reportBMC public health2018
Evaluation of a population-level strategy to promote tobacco treatment use among insured smokers: a pragmatic, randomized trial.
Trial report in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Population-Level Dissemination of a Smoking Cessation Smartphone App: Quasi-Experimental Comparison of Values-Based Messages in Social Media Advertisements.JMIR mHealth and uHealth · 2025Article
- Patient-generated health data: Impact on promoting patient-centered point of care tobacco treatment in patients with cancer.Journal of clinical and translational science · 2025Article
- Cognitive Distortions as Barriers to Seeking Smoking Cessation Treatment: A Comparative Study.Journal of clinical medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundMost smokers do not use evidence-based smoking cessation treatment. Increasing utilization of these services is an important public health goal. Health care systems and insurers are well positioned to support this goal within their patient populations. We tested whether a brief, mail-based intervention increased utilization of tobacco cessation services among insured smokers.
methodsAdult smokers were identified via automated health plan data and randomized to one of five treatment arms (n = 4767). Randomization was stratified by gender, age, and type of health plan coverage. Three arms received a letter containing motivational content and treatment referral information. Motivational content emphasized either the financial, health, or values-based benefits of quitting. One arm received a referral letter with no motivational content, and one arm received no letter. Enrollment in the referred tobacco cessation program was monitored for 5 months. Treatment was available to all participants through their insurance.
resultsAcross all four letter conditions, 0.8% of participants enrolled in tobacco treatment compared to 0.9% in the no letter reference group (p = .69). No single letter condition was superior to the others (p = .71), but treatment uptake was greater among participants who received their care and coverage from the health plan versus those with insurance coverage only (1.2% vs. 0.3%, p < .01).
conclusionsA one-time, mailed letter is not a cost-effective strategy for promoting use of covered smoking cessation treatment within large health plan populations, particularly when the message source is an insurance provider only and does not also provide clinical care. Health plans and insurers should consider alternative outreach efforts to promote treatment uptake among smokers. TRIAL REGISTRATIONS: TRN registered retrospectively with ISRCTN registry ( www.isrctn.com ). Registered on 11/01/2018. Registration number: ISRCTN32311137 .
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What OpenQuestion holds
Registered trials
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.