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Association of Individual and Neighborhood Characteristics to Problematic Internet Use among Youths and Adolescents: Evidence from Vietnam

Author

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  • Thao Thi Phuong Nguyen

    (Institute for Global Health Innovations, Duy Tan University, Da Nang 550000, Vietnam
    Faculty of Medicine, Duy Tan University, Da Nang 550000, Vietnam)

  • Ha Ngoc Do

    (Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam
    Vietnam Youth Academy, Hanoi 100000, Vietnam)

  • Thao Bich Thi Vu

    (Department of Research on Youth’s Organisations and Youth Campaign, Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam)

  • Khanh Long Vu

    (Department of Research on Youth’s Organisations and Youth Campaign, Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam)

  • Hiep Duy Nguyen

    (Department of Research on Children’s Issues, Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam)

  • Dung Tuan Nguyen

    (Department of Research on Youth and Legal Issues, Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam)

  • Hoang Minh Do

    (Department of Research on Youth Culture and Lifestyle, Youth Research Institute, Ho Chi Minh Communist Youth Union, Hanoi 100000, Vietnam)

  • Nga Thi Thu Nguyen

    (Faculty of Social Sciences and Humanities, Hanoi Metropolitan University, Hanoi 100000, Vietnam)

  • Ly Thi Bac La

    (Faculty of Preschool Education, Hanoi National University of Education, Hanoi 100000, Vietnam)

  • Linh Phuong Doan

    (Institute for Global Health Innovations, Duy Tan University, Da Nang 550000, Vietnam
    Faculty of Medicine, Duy Tan University, Da Nang 550000, Vietnam)

  • Tham Thi Nguyen

    (Institute for Global Health Innovations, Duy Tan University, Da Nang 550000, Vietnam
    Faculty of Medicine, Duy Tan University, Da Nang 550000, Vietnam)

  • Huong Lan Thi Nguyen

    (Institute for Global Health Innovations, Duy Tan University, Da Nang 550000, Vietnam
    Faculty of Medicine, Duy Tan University, Da Nang 550000, Vietnam)

  • Hoa Thi Do

    (Institute of Health Economics and Technology, Hanoi 100000, Vietnam)

  • Carl A. Latkin

    (Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA)

  • Cyrus S. H. Ho

    (Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore)

  • Roger C. M. Ho

    (Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
    Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore 119077, Singapore)

Abstract

Introduction: This study aimed to determine latent profiles from the Problematic Internet Use Questionnaire Short Form-6 (PIUQ-SF-6) score of Vietnamese youths and adolescents, which supports the diagnosis of problematic internet use among a large sample size. Moreover, it also explored factors that affect each latent profile of the PIUQ-SF-6 score among participants. Methods: A sample of 1477 Vietnamese people, aged 14 to 24, across five provinces participated in the study. Multinomial logistic regression determined factors related to the levels of the Problematic Internet Use Questionnaire Short Form-6 (PIUQ-SF-6) after using latent profile analysis. Results: Participants were divided into three profiles, including those at low, moderate, and high risk of internet addiction. The high-risk latent profile was obtained for 23.1% of adolescents, and the remaining percentages were, respectively, 40.2% and 36.7% of adolescents belonging to the moderate and low-risk groups. Moreover, factors including age, living alone, high Kessler psychological distress scale, excessive time on the internet, living in central cities, and high neighborhood disorder scores were found to be related to moderate- and high-risk internet addiction profiles. Conclusions: Factors analyzed according to individual and social characteristics further explore the reasons underlying increasing internet addiction among Vietnamese youths and inform early interventions.

Suggested Citation

  • Thao Thi Phuong Nguyen & Ha Ngoc Do & Thao Bich Thi Vu & Khanh Long Vu & Hiep Duy Nguyen & Dung Tuan Nguyen & Hoang Minh Do & Nga Thi Thu Nguyen & Ly Thi Bac La & Linh Phuong Doan & Tham Thi Nguyen & , 2023. "Association of Individual and Neighborhood Characteristics to Problematic Internet Use among Youths and Adolescents: Evidence from Vietnam," IJERPH, MDPI, vol. 20(3), pages 1-14, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2090-:d:1045105
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    References listed on IDEAS

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    1. Dang, Anh Kim & Nathan, Nila & Le, Quynh Ngoc Hoang & Nguyen, Long Hoang & Nguyen, Huong Lan Thi & Nguyen, Cuong Tat & Do, Huyen Phuc & Nguyen, Trang Huyen Thi & Tran, Tung Thanh & Nguyen, Tuan Anh & , 2018. "Associations between internet addiction and physical activity among Vietnamese youths and adolescents," Children and Youth Services Review, Elsevier, vol. 93(C), pages 36-40.
    2. Jun Liu & Jing Nie & Yafeng Wang, 2017. "Effects of Group Counseling Programs, Cognitive Behavioral Therapy, and Sports Intervention on Internet Addiction in East Asia: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 14(12), pages 1-17, November.
    3. Sergey Tereshchenko & Edward Kasparov & Nadezhda Semenova & Margarita Shubina & Nina Gorbacheva & Ivan Novitckii & Olga Moskalenko & Ludmila Lapteva, 2022. "Generalized and Specific Problematic Internet Use in Central Siberia Adolescents: A School-Based Study of Prevalence, Age–Sex Depending Content Structure, and Comorbidity with Psychosocial Problems," IJERPH, MDPI, vol. 19(13), pages 1-19, June.
    4. Jonathan Hassid, 2015. "China’s Responsiveness to Internet Opinion: A Double-Edged Sword," Journal of Current Chinese Affairs - China aktuell, Institute of Asian Studies, GIGA German Institute of Global and Area Studies, Hamburg, vol. 44(2), pages 39-68.
    5. Linh Phuong Doan & Linh Khanh Le & Tham Thi Nguyen & Thao Thi Phuong Nguyen & Minh Ngoc Vu Le & Giang Thu Vu & Carl A. Latkin & Cyrus S. H. Ho & Roger C. M. Ho & Melvyn W. B. Zhang, 2022. "Social Media Addiction among Vietnam Youths: Patterns and Correlated Factors," IJERPH, MDPI, vol. 19(21), pages 1-13, November.
    6. Stockdale, Susan E. & Wells, Kenneth B. & Tang, Lingqi & Belin, Thomas R. & Zhang, Lily & Sherbourne, Cathy D., 2007. "The importance of social context: Neighborhood stressors, stress-buffering mechanisms, and alcohol, drug, and mental health disorders," Social Science & Medicine, Elsevier, vol. 65(9), pages 1867-1881, November.
    7. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    8. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
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