ArticleSubstance abuse treatment, prevention, and policy2025
Adherence to mHealth quit smoking application 'stopcoach' on top of evidence based smoking cessation counselling: association with participant characteristics and long-term abstinence.
Article in Substance abuse treatment, prevention, and policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Developing a Machine Learning Model for Personalized, Predictor-Centric, Adaptive Intervention for Vaping Cessation in Young People: Secondary Data Analysis of Smartphone App Data.International journal of environmental research and public health · 2026Article
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8 authors.
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Abstract
backgroundSmoking is more common in lower socioeconomic position (SEP) groups, but smoking cessation interventions are less effective for these groups. StopCoach, an mHealth intervention, supports people with lower SEP in quitting smoking. A non-randomized controlled trial found that adding StopCoach to accredited smoking cessation counselling (SCC) led to higher abstinence rates immediately after and one year after SCC, compared to SCC alone. Users also rated its usability, acceptability, and practicality positively. Recent studies show a dose-response relationship, where more mHealth use improves smoking cessation outcomes. Since adherence is a challenge and often underreported, understanding adherence factors is crucial in evaluating eHealth intervention effectiveness.
aimThis study aims to assess the association between participant characteristics and StopCoach app adherence, as well as the association between app adherence and (short- and long-term) abstinence.
methodsMain outcomes are app adherence and abstinence. All participants (N = 132) were enrolled in group-based SCC. The association between user characteristics and adherence was estimated with logistic regression models. Chi-square tests were performed to test the association between app adherence and self-reported smoking abstinence. Short-term and long-term abstinence were defined as 4 weeks and 1 year after the quit date, respectively. App adherence was defined as the number of steps completed by a participant in the app.
resultsOlder users and those who had attended all SCC meetings were significantly more likely to be adherent to the app. More app-adherent participants were significantly more likely to be abstinent 1 year after the quit date. This association was non-significant at 4 weeks.
conclusionThe results indicate that mHealth interventions such as StopCoach may increase the effectiveness of traditional SCC programs. Users could benefit from further integration of StopCoach in SCC programs, as this could motivate them to be more adherent to StopCoach, resulting in them quitting successfully.
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