Document Type : Systematic Review and Meta-analysis
Authors
1
Doctoral Program in Medicine and Health Science, Universitas Gadjah Mada, Yogyakarta, Indonesia.
2
Public Health Study Program, Universitas Jambi, Jambi, Indonesia.
3
Public Health Study Program, Universitas Sumatera Utara, Medan, Indonesia.
4
Department of Physiology, Universitas Gadjah Mada, Yogyakarta, Indonesia.
5
Department of Health Behavior, Environment, and Social Medicine, Universitas Gadjah Mada, Indonesia.
Abstract
Background: Smoking behavior among adolescents is a significant global public health concern. Despite the implementation of numerous conventional interventions, their effectiveness remains variable, highlighting the need for more adaptive and individualized strategies. In this context, technological innovations via mobile health (mHealth) have emerged as a potentially effective approach for smoking prevention. However, evidence regarding their implementation, effectiveness, and impact specifically among adolescents remains scarce and fragmented. Objective: To identify the types, forms of implementation, and effects of mHealth interventions aimed at preventing smoking behavior among adolescents. Methods: A scoping review was conducted following the JBI and PRISMA-ScR guidelines. Articles were selected based on eligible criteria using the electronic databases PubMed, Scopus, Embase, Web of Science, and Cochrane Library. Eligible studies included experimental quantitative studies utilizing mHealth interventions targeting adolescents aged 13–18 years. Data processing was conducted using Rayyan.ai. The data were narratively analyzed and presented in tabular form. Result: The literature search identified 1,028 records, of which 16 studies met the eligibility criteria and were subsequently included in the analysis. The mHealth interventions identified included gamification-based apps, text messaging (SMS), and educational chatbots. Intervention platforms varied, ranging from smartphone applications to SMS-based programs. Most studies indicated that mHealth was effective in preventing smoking initiation, increasing risk perception, and reducing smoking intensity, although results varied by gender, age, and participants’ social backgrounds. Conclusion: mHealth interventions show promise as innovative strategies for smoking prevention among adolescents. Integrating mHealth into school and community programs, as well as tailoring interventions to local social and cultural contexts, is key to enhancing program effectiveness and reach. Further research is needed to evaluate long-term impacts and effectiveness across diverse populations.
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