Trial reportDrug and alcohol dependence2019
Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use.
Trial report in Drug and alcohol dependence, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Barriers and Facilitators of Adherence to Nicotine Replacement Therapy: A Systematic Review and Analysis Using the Capability, Opportunity, Motivation, and Behaviour (COM-B) Model.International journal of environmental research and public health · 2020Pooled it
- Daily adherence to nicotine replacement therapy in low-income smokers: The role of gender, negative mood, motivation, and self-efficacy.Addictive behaviors · 2023Trial
- Effectiveness of a Community-Based Structured Physical Activity Program for Adults With Type 2 Diabetes: A Randomized Clinical Trial.JAMA network open · 2022Trial
- Predictors of abstinence, no heavy drinking days, and a 2-level reduction in World Health Organization drinking levels during treatment for alcohol use disorder in the COMBINE study.Alcoholism, clinical and experimental research · 2022Trial
- Bridging evidence gaps: the role of real-world data in tobacco harm reduction.Harm reduction journal · 2026Article
- A computational framework for longitudinal medication adherence prediction in breast cancer survivors: A social cognitive theory based approach.PLOS digital health · 2025Article
- Association of shared decision-making cessation model and adult smoking cessation rate: A prospective cohort study.Tobacco induced diseases · 2025Article
- Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.PloS one · 2025Article
- Predictors of Nicotine Replacement Therapy Adherence: Mixed-Methods Research With a Convergent Parallel Design.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2024Article
- Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms.Pain research & management · 2024Article
- Development and Content Validation of a Questionnaire for Measuring Beliefs About Using Nicotine Replacement Therapy for Smoking Cessation in Pregnancy.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023Article
- Predictors of smoking cessation outcomes identified by machine learning: A systematic review.Addiction neuroscience · 2023Article
- A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training.Information processing & management · 2022Article
- A qualitative analysis of nicotine replacement therapy uptake, consistent use, and persistence among primary care patients who smoke.Drug and alcohol dependence reports · 2022Article
- The associations between the credibility of the tobacco control regulatory body and smoking behavior change among Saudi smokers.Tobacco induced diseases · 2022Article
- Machine Learning and Medication Adherence: Scoping Review.JMIRx med · 2021Article
- Predictors of Adherence to Smoking Cessation Medications among Current and Ex-Smokers in Australia: Findings from a National Cross-Sectional Survey.International journal of environmental research and public health · 2021Article
- Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases.Frontiers in digital health · 2021Review
- A 5-Factor Framework for Assessing Tobacco Use Disorder.Tobacco use insights · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundNonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonadherence and suggest tailored interventions to address it.
aimsIdentify and characterize subgroups of smokers based on adherence to nicotine replacement therapy (NRT).
methodSecondary classification tree analyses of data from a 2-arm randomized controlled trial of Recommended Usual Care (R-UC, n = 315) versus Abstinence-Optimized Treatment (A-OT, n = 308) were conducted. R-UC comprised 8 weeks of nicotine patch plus brief counseling whereas A-OT comprised 3 weeks of pre-quit mini-lozenges, 26 weeks of nicotine patch plus mini-lozenges, 11 counseling contacts, and 7-11 automated reminders to use medication. Analyses identified subgroups of smokers highly adherent to nicotine patch use in both treatment conditions, and identified subgroups of A-OT participants highly adherent to mini-lozenges.
resultsVaried facets of nicotine dependence predicted adherence across treatment conditions 4 weeks post-quit and between 4- and 16-weeks post-quit in A-OT, with greater baseline dependence and greater smoking trigger exposure and reactivity predicting greater medication use. Greater quitting motivation and confidence, and believing that stop smoking medication was safe and easy to use were associated with greater adherence.
conclusionAdherence was especially high in those who were more dependent and more exposed to smoking triggers. Quitting motivation and confidence predicted greater adherence, while negative beliefs about medication safety and acceptability predicted worse adherence. Results suggest that adherent use of medication may reflect a rational appraisal of the likelihood that one will need medication and will benefit from it.
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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.