Authors
Bikash K Pradhan, Katerina Lukavska, Roman Gabrhelík, Daniel Novak
Published in
JMIR formative research. Volume 10. Pages e80428. Oct 27, 2026. Epub Oct 27, 2026.
Abstract
In recent years, digital interventions for smoking cessation have seen increasing use, but program completion rates vary widely. Therefore, understanding the factors associated with program completion in cessation programs is critical for evaluating the feasibility and acceptability of the digital intervention program.
This study aims to identify the predictors (sex, age group, and health) of program completion in a cognitive behavioral therapy-based mobile smoking cessation program.
Participants enrolled in Adiquit, a mobile app-based smoking cessation program, were classified as completers if they had entered the Withdrawal-Relapse phase and had reported no lapse for 15 consecutive days or had finished all program sessions. User data for this study covered the period from launch through July 2024. Users who did not meet the completion criteria by the end of the study were classified as noncompleters. Predictors were assessed during the Entry and Equilibrium phases, including demographic characteristics, psychosocial factors, and early engagement metrics. Logistic regression was used to identify factors associated with completion.
The three strongest predictors of program completion, as identified by the multivariate model, are higher early engagement (session attendance and screen time), stronger perceived social support, and positive prequitting feelings.
The results of this study will help clarify the variables that lead to successful completion of such a digital intervention program, as well as their importance by sex, age group, health status, and employment status.
PMID:
42945121
Bibliographic data and abstract were imported from PubMed on 28 Oct 2026.
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