ArticleApplied clinical informatics2023
A Clinical Decision Support System for Motivational Messaging and Tobacco Cessation Treatment for Parents: Pilot Evaluation of Use and Acceptance.
Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Automated Tobacco Cessation Intervention for Parents in Pediatric Primary Care: A Cluster-Randomized Clinical Trial.JAMA network open · 2025Trial
- Using In-Home Air Quality Monitoring to Reduce Cannabis Secondhand Smoke Exposure in Children: Quantitative Pilot Feasibility Study.JMIR formative research · 2026Article
- An Electronic Health Record-Based Tobacco Treatment System for Parents in Pediatric Primary Care.Pediatrics · 2026Article
- Combining International Standards to Develop Clinical Decision Support for Parent Smoking Cessation in Pediatrics.Journal of medical Internet research · 2025Article
- Sharing a Hybrid Electronic Health Record + Fast Healthcare Interoperability Resources Clinical Decision Support across Health Systems: Automating Smoking Cessation for Pediatric Caregivers.Applied clinical informatics · 2025Article
- Refer2Quit: A pilot referral approach to promote treatment for parents who smoke tobacco through pediatric primary care.Drug and alcohol dependence reports · 2025Article
- A Scoping Review of Interventions for Tobacco Cessation Among African American Individuals.Current addiction reports · 2025Review
- Pediatrician-Delivered Smoking-Cessation Messages for Parents: An Update.Academic pediatrics · 2023Review
- Behavioral Health Decision Support Systems and User Interface Design in the Emergency Department.Applied clinical informatics · 2023Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundResearch is needed to identify how clinical decision support (CDS) systems can support communication about and engagement with tobacco use treatment in pediatric settings for parents who smoke. We developed a CDS system that identifies parents who smoke, delivers motivational messages to start treatment, connects parents to treatment, and supports pediatrician-parent discussion.
objectiveThe objective of this study is to assess the performance of this system in clinical practice, including receipt of motivational messages and tobacco use treatment acceptance rates.
methodsThe system was evaluated at one large pediatric practice through a single-arm pilot study from June to November 2021. We collected data on the performance of the CDS system for all parents. Additionally, we surveyed a sample of parents immediately after the clinical encounter who used the system and reported smoking. Measures were: (1) the parent remembered the motivational message, (2) the pediatrician reinforced the message, and (3) treatment acceptance rates. Treatments included nicotine replacement therapy, quitline referral (phone counseling), and/or SmokefreeTXT referral (text message counseling). We described survey response rates overall and with 95% confidence intervals (CIs).
resultsDuring the entire study period, 8,488 parents completed use of the CDS: 9.3% (
conclusionA CDS system to support parental tobacco use treatment in pediatric primary care enhanced motivational messaging about smoking cessation and evidence-based treatment initiation.
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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.