ArticleCurrent addiction reports2019
Mobile Applications for the Treatment of Tobacco Use and Dependence.
Article in Current addiction reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses 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
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Effectiveness of digital tools for smoking cessation in Asian countries: a systematic review.Annals of medicine · 2024Pooled it
- Smoking Cessation Apps: A Systematic Review of Format, Outcomes, and Features.International journal of environmental research and public health · 2021Pooled it
- Telephone Counseling and Messaging Guided by Mobile Profiling of Tobacco Users for Smoking Cessation: A Randomized Clinical Trial.JAMA network open · 2025Trial
- Smartband-based smoking detection and real-time brief mindfulness intervention: findings from a feasibility clinical trial.Annals of medicine · 2024Trial
- Effectiveness of Applying Green Heart, a Smartphone-Based Self-management Intervention to Control Smoking: A Randomized Clinical Trial.Archives of Iranian medicine · 2024Trial
- Effective Communication Supported by an App for Pregnant Women: Quantitative Longitudinal Study.JMIR human factors · 2024Trial
- Effectiveness of a Dyadic Buddy App for Smoking Cessation: Randomized Controlled Trial.Journal of medical Internet research · 2021Trial
- A Mobile Just-in-Time Adaptive Intervention for Smoking Cessation: Pilot Randomized Controlled Trial.Journal of medical Internet research · 2020Trial
- Mobile App-Based Smoking Cessation in Hispanic or Latino Adults: Culturally Tailored Spanish-Language Formative App Development Study.JMIR formative research · 2026Article
- Perceptions of User-Generated Content as a Source of Health Messages in Smoking Cessation Mobile Interventions: Focus Group Study.JMIR human factors · 2025Article
- Testing the Acceptability and Feasibility of a Gender-Informed Smoking Cessation mHealth App for Women: Mixed Methods Approach.JMIR human factors · 2025Article
- Applying Human-Centered Design to Develop Smartphone-Based Intervention Messages to Help Young Adults Quit Using E-Cigarettes and Cigarettes: A Remote User Testing Study.JMIR human factors · 2025Article
- Article
- Perceptions Toward an Attentional Bias Modification Mobile Game Among Individuals With Low Socioeconomic Status Who Smoke: Qualitative Study.JMIR serious games · 2025Article
- Initial assessment of a novel smoking cessation program integrating app-based behavioral therapy and an electronic cigarette: results of a pilot study.Addiction science & clinical practice · 2025Article
- A Gender-Informed Smoking Cessation App for Women: Protocol for an Acceptability and Feasibility Study.JMIR research protocols · 2024Article
- Acceptability of heart rate-based remote monitoring of smoking status.Addictive behaviors reports · 2024Article
- A feature-based qualitative assessment of smoking cessation mobile applications.PLOS digital health · 2024Article
- Perceptions of the Use of Mobile Technologies for Smoking Cessation: Focus Group Study With Individuals of Low Socioeconomic Status Who Smoke.JMIR formative research · 2024Article
- Feasibility and Engagement of a Mobile App Preparation Program (Kwit) for Smoking Cessation in an Ecological Context: Quantitative Study.JMIR mHealth and uHealth · 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
4 authors at 3 institutions in 2 countries.
Funding
Abstract
purpose of reviewSmoking remains a leading preventable cause of premature death in the world; thus, developing effective and scalable smoking cessation interventions is crucial. This review uses the Obesity-Related Behavioral Intervention Trials (ORBIT) model for early phase development of behavioral interventions to conceptually organize the state of research of mobile applications (apps) for smoking cessation, briefly highlight their technical and theory-based components, and describe available data on efficacy and effectiveness. RECENT
findingsOur review suggests that there is a need for more programmatic efforts in the development of mobile applications for smoking cessation, though it is promising that more studies are reporting early phase research such as user-centered design. We identified and described the app features used to implement smoking cessation interventions, and found that the majority of the apps studied used a limited number of mechanisms of intervention delivery, though more effort is needed to link specific app features with clinical outcomes. Similar to earlier reviews, we found that few apps have yet been tested in large well-controlled clinical trials, although progress is being made in reporting transparency with protocol papers and clinical trial registration. SUMMARY: ORBIT is an effective model to summarize and guide research on smartphone apps for smoking cessation. Continued improvements in early phase research and app design should accelerate the progress of research in mobile apps for smoking cessation.
Indexed as
Identifiers
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.