ArticlePreventive medicine2018
Leveraging technology to promote smoking cessation in urban and rural primary care medical offices.
Article in Preventive medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Pooled it
- Effect of Electronic Portal Messaging With Embedded Asynchronous Care on Physician-Assisted Smoking Cessation Attempts: A Randomized Clinical Trial.JAMA network open · 2022Trial
- Implementation of electronic signposting to interventions that prevent cancer: A realist review.PLOS digital health · 2026Article
- Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review.JMIR medical informatics · 2022Article
- COVID-19 and tobacco cessation: lessons from India.Public health · 2022Article
- Evaluation of a Proactive Smoking Cessation Electronic Visit to Extend the Reach of Evidence-Based Cessation Treatment via Primary Care.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
We examined the use of automated voice recognition (AVR) messages targeting smokers from primary care practices located in underserved urban and rural communities to promote smoking cessation. We partnered with urban and rural primary care medical offices (n = 7) interested in offering this service to patients. Current smokers, 18 years and older, who had completed an office visit within the previous 12 months, from these sites were used to create a smoker's registry. Smokers were recruited within an eight county region of western New York State between June 2012 and August 2013. Participants were contacted over six month intervals using the AVR system. Among 5812 smokers accrued 1899 (32%) were reached through the AVR system and 55% (n = 1049) continued to receive calls. Smokers with race other than white or African American were less likely to be reached (OR = 0.71, 0.57-0.90), while smokers ages 40 and over were more likely to be reached. Females (OR = 0.78, 0.65-0.95) and persons over age 40 years were less likely to opt out, while rural smokers were more likely to opt out (OR = 3.84, 3.01-4.90). Among those receiving AVR calls, 30% reported smoke free (self-reported abstinence over a 24 h period) at last contact; smokers from rural areas were more likely to report being smoke free (OR = 1.41, 1.01-1.97). An AVR-based smoking cessation intervention provided added value beyond typical tobacco cessation efforts available in these primary care offices. This intervention required no additional clinical staff time and served to satisfy a component of patient center medical home requirements for practices.
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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.