International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

line decor
  
line decor

 Volume 12, Issue 9 (September 2025), Pages: 100-106

----------------------------------------------

 Original Research Paper

Social media addiction: A comprehensive state of mental health

 Author(s): 

 Ritu Chauhan 1, Abdallah M. A. Al-Tarawneh 2, Nidal A. Al-Dmour 3, *, Kashish Mudliyar 1, Khushi Dubey 1, Eiad Yafi 4, Taher M. Ghazal 5

 Affiliation(s):

  1Artificial Intelligence and IoT Lab, Center for Computational Biology and Bioinformatics, Amity University UP, Noida, India
  2Clinical Psychology, Faculty of Arts and Sciences, Al-Ahliyya Amman University, Amman, Jordan
  3Department of Computer Engineering, College of Engineering, Mutah University, Mu'tah, Jordan
  4Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia
  5Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan

 Full text

    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-2898-3905

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2025.09.009

 Abstract

Social media addiction, characterized by compulsive and excessive engagement with social platforms, negatively impacts mental health by fostering unfavorable comparisons between users’ lives and the idealized portrayals of others. These curated online personas can distort self-perception, diminish self-esteem, and contribute to long-term psychological distress. While social media offers networking and support, its detrimental effects necessitate a balanced approach to usage. This study investigates the relationship between social media addiction and mental health outcomes using a synthetic dataset, revealing a strong negative correlation (r = -1.0) between addiction severity and mental well-being. A Random Forest model was employed to predict mental health scores based on addiction levels, demonstrating the predictive utility of behavioral engagement metrics. The findings underscore the need for targeted interventions to mitigate the adverse mental health consequences of social media addiction, suggesting that structured approaches could help reduce its psychological burden.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Social media addiction, Mental health, Negative correlation, Random Forest model, Behavioral interventions

 Article history

 Received 11 November 2024, Received in revised form 5 April 2025, Accepted 11 August 2025

 Acknowledgment

No Acknowledgment. 

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Chauhan R, Al-Tarawneh AMA, Al-Dmour NA, Mudliyar K, Dubey K, Yafi E, and Ghazal TM (2025). Social media addiction: A comprehensive state of mental health. International Journal of Advanced and Applied Sciences, 12(9): 100-106

  Permanent Link to this page

 Figures

  Fig. 1

 Tables

  Table 1  Table 2  Table 3 

----------------------------------------------   

 References (20)

  1. Aksoy ME (2018). A qualitative study on the reasons for social media addiction. European Journal of Educational Research, 7(4): 861-865.  https://doi.org/10.12973/eu-jer.7.4.861    [Google Scholar]
  2. Amirthalingam J and Khera A (2024). Understanding social media addiction: A deep dive. Cureus, 16(10): e72499.  https://doi.org/10.7759/cureus.72499    [Google Scholar]
  3. Brevers D and Turel O (2019). Strategies for self-controlling social media use: Classification and role in preventing social media addiction symptoms. Journal of Behavioral Addictions, 8(3): 554-563.  https://doi.org/10.1556/2006.8.2019.49    [Google Scholar] PMid:31545100 PMCid:PMC7044631
  4. Chauhan R, Mehta K, Eiad Y, and Zuhairi MF (2024). Prediction of autism spectrum disorder using AI and machine learning. In the 18th International Conference on Ubiquitous Information Management and Communication, IEEE, Kuala Lumpur, Malaysia: 1-7.  https://doi.org/10.1109/IMCOM60618.2024.10418312    [Google Scholar]
  5. Chen A (2019). From attachment to addiction: The mediating role of need satisfaction on social networking sites. Computers in Human Behavior, 98: 80–92.  https://doi.org/10.1016/j.chb.2019.03.034    [Google Scholar]
  6. Gori A, Topino E, and Griffiths MD (2023). The associations between attachment, self-esteem, fear of missing out, daily time expenditure, and problematic social media use: A path analysis model. Addictive Behaviors, 141: 107633.  https://doi.org/10.1016/j.addbeh.2023.107633    [Google Scholar] PMid:36753932
  7. Hemalatha M, Maidin SS, and Sun J (2024). Empirical study of the correlation between social media content and health issues among college students using machine learning. Journal of Applied Data Sciences, 5(4): 2015-2024.  https://doi.org/10.47738/jads.v5i4.365    [Google Scholar]
  8. Hou Y, Xiong D, Jiang T, Song L, and Wang Q (2019). Social media addiction: Its impact, mediation, and intervention. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 13(1): 4.  https://doi.org/10.5817/CP2019-1-4    [Google Scholar]
  9. Ji Y, Liu S, Xu H, and Zhang B (2023). The causes, effects, and interventions of social media addiction. Journal of Education, Humanities and Social Sciences, 8(1): 897-910.  https://doi.org/10.54097/ehss.v8i.4378    [Google Scholar]
  10. Kumar N and Chauhan R (2024). Speculation of stock marketing using advanced recursive techniques. International Journal of Business Data Communications and Networking (IJBDCN), 19(1): 1-18.  https://doi.org/10.4018/IJBDCN.339890    [Google Scholar]
  11. Leong LY, Hew TS, Ooi KB, Lee VH, and Hew JJ (2019). A hybrid SEM-neural network analysis of social media addiction. Expert Systems with Applications, 133: 296-316.  https://doi.org/10.1016/j.eswa.2019.05.024    [Google Scholar]
  12. Mercan N and Uysal B (2023). The relationship of social media addiction with interpersonal problem-solving and personality traits in university students. Archives of Psychiatric Nursing, 43: 50-56.  https://doi.org/10.1016/j.apnu.2022.12.025    [Google Scholar] PMid:37032015
  13. Mim MN, Firoz M, Islam MM, Hasan M, and Habib MT (2024). A study on social media addiction analysis on the people of Bangladesh using machine learning algorithms. Bulletin of Electrical Engineering and Informatics, 13(5): 3493-3502.  https://doi.org/10.11591/eei.v13i5.5680    [Google Scholar]
  14. Reyaz S, Tiwari A, Agarwal T, Srivastava HK, Kumari J, and Sharma Y (2024). Impact of social media and anxiety among college students. International Journal for Multidisciplinary Research, 6(6): 1-14.  https://doi.org/10.36948/ijfmr.2024.v06i06.31894    [Google Scholar]
  15. Sun Y and Zhang Y (2021). A review of theories and models applied in studies of social media addiction and implications for future research. Addictive Behaviors, 114: 106699.  https://doi.org/10.1016/j.addbeh.2020.106699    [Google Scholar] PMid:33268185
  16. Talan T, Doğan Y, and Kalinkara Y (2024). Effects of smartphone addiction, social media addiction and fear of missing out on university students' phubbing: A structural equation model. Deviant Behavior, 45(1): 1-14.  https://doi.org/10.1080/01639625.2023.2235870    [Google Scholar]
  17. Turhan Gürbüz P, Çoban ÖG, Erdoğan A, Kopuz HY, Adanir AS, and Önder A (2021). Evaluation of internet gaming disorder, social media addiction, and levels of loneliness in adolescents and youth with substance use. Substance Use and Misuse, 56(12): 1874-1879.  https://doi.org/10.1080/10826084.2021.1958856    [Google Scholar] PMid:34328053
  18. Varma G, Chauhan R, and Singh D (2024). Towards cyber awareness among smart device users: An interactive, educational display of IoT device vendors compromise history. Multimedia Tools and Applications, 83(17): 52795-52818.  https://doi.org/10.1007/s11042-023-17520-1    [Google Scholar]
  19. Wang X and Shang Q (2024). How do social and parasocial relationships on TikTok impact the well-being of university students? The roles of algorithm awareness and compulsive use. Acta Psychologica, 248: 104369.  https://doi.org/10.1016/j.actpsy.2024.104369    [Google Scholar] PMid:38936231
  20. Yafi E, Chuahan R, Sharma A, and Zuhairi MF (2024). Integrated empowered AI and IoT approach for heart prediction. In the 18th International Conference on Ubiquitous Information Management and Communication, IEEE, Kuala Lumpur, Malaysia: 1-7.  https://doi.org/10.1109/IMCOM60618.2024.10418366    [Google Scholar]