This mixed-methods study develops and evaluates a mobile health (mHealth) application for smoking cessation among Indonesian adolescents aged 13-15 years. The study uses a sequential exploratory approach with three phases: (1) qualitative research to inform app design; (2) app development using Rapid Application Development (RAD) model; and (3) a single-blind, two-arm randomized controlled trial comparing the mHealth intervention to paper-based materials. The intervention is grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT2) and Transtheoretical Model (TTM). Primary outcome is smoking abstinence at 1-, 3-, and 6-month follow-ups measured through self-report questionnaires.
Adolescent smoking is a growing public health concern worldwide, and it is particularly prevalent in low- and middle-income countries (LMICs) such as Indonesia. According to the World Health Organization (WHO), nearly 6.5% of adolescents aged 13-15 years globally use tobacco, with Southeast Asia, including Indonesia, contributing a significant proportion of this population. The prevalence of smoking among Indonesian adolescents has escalated over the past decade, with national surveys indicating a sharp increase from 7.2% in 2013 to 9.1% in 2018 and even higher figures reported by the 2019 Global Youth Tobacco Survey (GYTS) at 19.2%. Although more recent estimates suggest a slight reduction to 7.4% in 2023, smoking among adolescents remains a major public health challenge in Indonesia. Especially since Indonesia is the only country in Asia that has not ratified the WHO Framework Convention on Tobacco Control (FCTC). This condition is especially concerning given the strong empirical evidence of the detrimental effects of smoking on individual health, societal well-being, and the environment. Adolescent smoking is associated with numerous long-term health risks, including respiratory diseases, cardiovascular problems, and an increased likelihood of continuing smoking into adulthood. Furthermore, smoking during adolescence has been linked to mental health issues such as depression, anxiety, and suicidal ideation. Moreover, tobacco-related mortality is alarmingly high, with over 8 million deaths annually worldwide due to active smoking and exposure to secondhand smoke. In Indonesia, tobacco-related diseases contribute significantly to mortality, with an estimated 225,700 deaths annually attributed to smoking. Despite various tobacco control measures implemented in Indonesia, such as raising taxes on tobacco products, free smoking cessation consultation services, and establishing smoke-free zones, smoking rates among adolescents have remained persistently high. Technology-based interventions, particularly mobile health (mHealth) applications, have emerged as promising tools for promoting smoking cessation. The widespread use of smartphones among adolescents, with Indonesia being the fourth-largest smartphone market globally, presents a unique opportunity to leverage mHealth interventions to reduce smoking rates. However, the effectiveness of mHealth applications for smoking cessation has shown inconsistent results, particularly in LMICs where accessibility, engagement, and content relevance may differ from those in high-income countries. Previous studies have demonstrated that while mHealth applications can help individuals quit smoking in the short term, their long-term effectiveness remains unclear, especially among adolescent populations. There is a growing body of literature highlighting the importance of tailoring interventions to the unique needs of adolescents, taking into account developmental stages, peer influence, and social media dynamics. However, there is a significant gap in the availability of mHealth applications designed specifically for adolescents in Indonesia, and the existing tools often fail to integrate critical elements such as behavioral change techniques, social support, and interactive features. This study aims to address these gaps by developing an innovative mHealth intervention designed specifically for adolescent smokers in Indonesia. The intervention will be grounded in behavioral change theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Transtheoretical Model (TTM). UTAUT2 will ensure that the app is accepted, used, and engaging for adolescents, taking into account the influence of peers, ease of use, and intrinsic motivation factors. TTM will guide the app design by allowing it to adapt to the adolescent's specific stage in the smoking cessation process, providing tailored content and support. Together, these frameworks will make the mHealth app both effective, promoting long-term behavior change, relevant for adolescent smokers and better smoking cessation outcomes in Indonesia.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
110
Participants receive the mHealth smoking cessation application with: * Educational content about smoking risks and cessation benefits * Motivational messages and progress tracking * Social support features * Interactive elements and quizzes * Monthly monitoring and support
Participants receive paper-based smoking cessation module containing equivalent content: * Motivational content and cessation benefits * Ex-smoker success stories * Trigger identification and coping strategies * Weekly quizzes with prizes (online access) * Monthly check-ins
Multiple junior high schools and community health centers
Padang, West Sumatra, Indonesia
Self-reported smoking abstinence measured through questionnaire (Yes/No response where Yes = abstinent, No = not abstinent)
Time frame: 1, 3, and 6 months post-intervention
Smoking cessation self-efficacy using SEQ-12 (12-item Smoking Self-Efficacy Questionnaire)
Scale range: 12-60, where higher scores indicate greater self-efficacy for smoking cessation
Time frame: Baseline, 1, 2, 3, and 6 months
Motivation assessed via Richmond Test
Scale range: 0-10, where higher scores indicate greater motivation to quit smoking
Time frame: Baseline, 1, 2, 3, and 6 months
Social support measured through Multidimensional Scale of Perceived Social Support (MSPSS)
Scale range: 12-84, where higher scores indicate greater perceived social support
Time frame: Baseline, 1, 2, 3, and 6 months
Dependence level using Fagerström Test for Nicotine Dependence (FTND)
Scale range: 0-10, where higher scores indicate greater nicotine dependence
Time frame: Baseline, 1, 2, 3, and 6 months
App usage engagement measured through usage logs
Frequency and duration of app usage tracked through automated logging system. Measured as number of sessions per week and average session duration in minutes
Time frame: Baseline, 1, 2, 3, and 6 months
mHealth app usability measured through mHealth Usability Questionnaire (MAUQ)
mHealth Usability Questionnaire (MAUQ) scores. Scale range: 18-126, where higher scores indicate better perceived usability of the mobile health application
Time frame: Time Frame: 1, 2, 3, and 6 months
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