ArticleBMC public health2025
Understanding acceptance of digital smoking cessation interventions: user behavior, key influencing factors, and the role of reimbursement.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smoking remains a prominent preventable health risk in Germany, creating a need for effective cessation interventions. Digital smoking cessation interventions (DSCIs) present promising support for individuals aiming to quit, yet their utilization and acceptance are not thoroughly understood. This study analyzes usage patterns and acceptance levels of DSCIs among smokers, occasional smokers, and former smokers in Germany, focusing on user behavior, acceptance determinants, and the influence of prescription and reimbursement status. An online questionnaire based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was administered to participants. Data were collected through recruitment via social media, email lists, counseling groups, and public postings. The responses were analyzed using SPSS. The study included 173 participants (61.85% female, 37.57% male, 0.58% diverse) with an average age of 35.28 years. They reported smoking for an average of 18.21 years and attempting cessation 3.42 times. Among respondents, 41.62% had used DSCIs, predominantly former smokers (54.17%) and women (79.17%), with the "Smoke Free" app being the most utilized intervention. Although 73.05% expressed willingness to (re)use DSCIs, actual usage showed moderate acceptance levels. Significant predictors of acceptance included willingness to pay (p = 0.013), self-efficacy (p = 0.018), and physician prescription with clinical evidence (p = 0.019). The results highlight a rising demand for digital solutions focused on long-term smoking cessation, particularly among middle-aged women, emphasizing the need for a deeper understanding of acceptance drivers and model expansions to address healthcare dynamics.
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.