ReviewJMIR mHealth and uHealth2022
Classification of Smoking Cessation Apps: Quality Review and Content Analysis.
Review in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Evaluating the Quality and Features of Visual Acuity Apps Using the Mobile App Rating Scale: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- Digital Smoking Cessation With a Comprehensive Guideline-Based App-Results of a Nationwide, Multicentric, Parallel, Randomized Controlled Trial in Germany.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024Trial
- Predicting the Users' Level of Engagement with a Smartphone Application for Smoking Cessation: Randomized Trial and Machine Learning Analysis.European addiction research · 2023Trial
- Investigating the Quality of Mobile Apps for Drug-Drug Interaction Management Using the Mobile App Rating Scale and K-Means Clustering: Systematic Search of App Stores.JMIR mHealth and uHealth · 2025Article
- Exploring relationships among smoking cessation app use, smoking behavioral outcomes, and pharmacotherapy utilization among individuals who smoke cigarettes.Addictive behaviors · 2025Article
- Mobile Apps Designed for Patients With Polycystic Ovary Syndrome: Content Analysis Using the Mobile App Rating Scale.Journal of medical Internet research · 2025Article
- Application of Behavior Change Techniques and Rated Quality of Smoking Cessation Apps in China: Content Analysis.JMIR mHealth and uHealth · 2025Article
- Understanding perspectives on smoking cessation based on Self-Determination Theory: A qualitative study.Tobacco prevention & cessation · 2025Article
- 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
- How Digital Solutions Might Provide a World of New Opportunities for Holistic and Empathic Support of Patients with Hidradenitis Suppurativa.Dermatology and therapy · 2024Article
- Article
- Efficacy of the QuitSure App for Smoking Cessation in Adult Smokers: Cross-Sectional Web Survey.JMIR human factors · 2024Article
- Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search.JMIR mHealth and uHealth · 2024Article
- Development and evaluation of visualizations of smoking data for integration into the Sense2Quit app for tobacco cessation.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Effectiveness of the QuitSure Smartphone App for Smoking Cessation: Findings of a Prospective Single Arm Trial.JMIR formative research · 2023Article
- Smartphone Apps Targeting Youth Tobacco Use Prevention and Cessation: An Assessment of Credibility and Quality.Current addiction reports · 2023Article
- Mobile applications (apps) for tobacco cessation: Behaviour change potential and heuristic analysis using the Mobile Application Rating Scale (MARS).F1000Research · 2023Review
- Developing and testing a smoking cessation app in Arabic language: A pilot randomized trial study protocol.Digital healthArticle
- 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
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany people use apps for smoking cessation, and the effectiveness of these apps has been proven in several studies. However, no study has classified these apps and only few studies have analyzed the characteristics of these apps that influence their quality.
objectiveThe purpose of this study was to analyze the content and the quality of smoking cessation apps by type and identify the characteristics that affect their overall quality.
methodsTwo app marketplaces (App Store and Google Play) were searched in January 2018, and the search was completed by May 2020. The search terms used were "stop smoking," "quit smoking," and "smoking cessation." The apps were categorized into 3 types (combined, multifunctional, and informational). The tailored guideline of Clinical Practice Guideline for Treating Tobacco Use and Dependence was utilized for evaluating app content (or functions), and the Mobile App Rating Scale (MARS) was used to evaluate the quality. Chi-square test was performed for the general characteristics, and one-way analysis of variance was performed for MARS analysis. To identify the general features of the apps that could be associated with the MARS and content scores, multiple regression analysis was done. All analyses were performed using SAS software (ver. 9.3).
resultsAmong 1543 apps, 104 apps met the selection criteria of this study. These 104 apps were categorized as combined type (n=44), functional type (n=31), or informational type (n=29). A large amount of content specified in the guideline was included in the apps, most notably in the combined type, followed by the multifunctional and informational type; the MARS scores followed the same order (3.64, 3.26, and 3.0, respectively). Regression analysis showed that the sector in which the developer was situated and the feedback channel with the developer had a significant impact on both the content and MARS scores. In addition, problematic apps such as those made by unknown developers or copied and single-function apps were shown to have a large market share.
conclusionsThis study is the first to evaluate the content and quality of smoking cessation apps by classification. The combined type had higher-quality content and functionality than other app types. The app developer type and feedback channel with the app developer had a significant impact on the overall quality of the apps. In addition, problematic apps and single-function apps were shown to have a large market share. Our results will contribute to the use and development of better smoking cessation apps after considering the problems identified in this study.
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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.