Classifying Internet Addiction Using Machine Learning Approach: A Study Among Adolescents in Bangladesh
Raising awareness among adolescents and their parents is crucial because IA is frequent. The ML framework can identify significant prognostic indicators and classify this IA problem more accurately, helping policymakers, stakeholders, and families understand and prevent this crisis by improving policy-making strategies and counseling services.
Authors
- Mahedi Hasan (ORCID: https://orcid.org/0000-0002-3263-4636)
- A. Mahmud (ORCID: https://orcid.org/0000-0001-8194-6874)
- Nafiul Hasan (ORCID: https://orcid.org/0000-0001-5959-9669)
- M. S. Hosain (ORCID: https://orcid.org/0009-0008-0010-3102)
- Md Abu Bakkar Siddik (ORCID: https://orcid.org/0000-0001-7752-1953)
- Mohammad Mizanur Rahman (ORCID: https://orcid.org/0000-0002-7318-9727)
- Mohammad Alamgir Kabir
- Md. Ahashan Habib
- Akher Ali (ORCID: https://orcid.org/0000-0001-7171-0737)
- Peal Ahamed Shanto (ORCID: https://orcid.org/0000-0001-7505-9881)
Institutions
- Texas Tech University (US)
- United States Department of Justice (US)
- Shahjalal University of Science and Technology (BD)
- Universiti Sains Malaysia (MY)
- Centre for Policy Dialogue (BD)
- Daffodil International University (BD)
- Manarat International University (BD)
- Hospital Universiti Sains Malaysia (MY)
- Jahangirnagar University (BD)
- Nanjing University (CN)
- University of Chittagong (BD)
Publication Details
- Journal
- Public Health Challenges
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1002/puh2.70165
- Primary Topic
- Impact of Technology on Adolescents
- Type
- article
- Field-Weighted Citation Impact
- 0.00