Influencing Factors of Anxiety and Depression in Adolescents

Authors

  • Xinyun Zhang

DOI:

https://doi.org/10.61173/q93jah92

Keywords:

Anxiety, depression, adolescents

Abstract

Adolescent clinical depression and anxiety are on the increase, and the worldwide society considers this a public health issue. These issues degrade academic performance, social abilities, and fundamental life skills as people grow. Not addressing these problems may affect their job, relationships, and satisfaction as an adult. Researchers rely on biological, psychological, and technological systems to solve these young people’s many difficulties. One aim is to investigate whether these people have genetic features that indicate susceptibility and their families’ mental health histories. Others investigate how the COVID-19 epidemic affected teenage mental health. Social media use analysis tools incorporate machine learning and longitudinal data collecting. Socio-ecological model of biological, predispositional anxiety and stress, and technology ‘neuroscience’ unconsciously cause teenage anxiety and depression. Although worrying is caused by genetic susceptibility and neurochemical imbalances, contextual variables including family dysfunction, academic overpressure, and pandemic problems are all causes. These difficulties include disruptive social media use and sleepsustained don’ts of developmental and socially necessary digital invasive devices. The silent triad of genetics, life stress, and social media time combine to increase mental health risk, as expected. The findings indicate that anxiety and sadness are caused by several, interconnected variables. The best way to prevent and cure mental health issues in modern culture is via collaboration between schools, healthcare professionals, and families.

References

[1] Bitsko, R. H., Claussen, A. H., Lichstein, J., Black, L. I., Jones, S. E., Danielson, M. L., Hoenig, J. M., Davis, J. S. P., Brody, D. J., Gyawali, S., Maenner, M. J., Warner, M., Holland, K. M., Perou, R., Crosby, A. E., Blumberg, S. J., Avenevoli, S., & Kaminski, J. W. (2024). Mental health surveillance among children—United States, 2013–2019. MMWR Supplements, 71(2), 1–42.

[2] Kong, X. W., Yang, W., Xu, S., Yang, C., Kang, L., Qiu, L., & Liu, J. (2023). Analysis of the prevalence and influencing factors of anxiety and depression in the Chinese population: A cross-sectional survey. Heliyon, 9(5).

[3] Sijtsema, J. J., Veenstra, R., Creemers, D. H., Popma, A., Beeck, H. V., Franken, I. H., & Oldehinkel, A. J. (2021). Psychosocial and biological risk factors of anxiety disorders in adolescents: A TRAILS report. European Child & Adolescent Psychiatry, 30(12), 1969–1982.

[4] Liu, Y., Chen, C., Wang, H., Li, W., & Zhang, K. (2024). Key risk factors of generalized anxiety disorder in adolescents: Machine learning study. Frontiers in Public Health, 12, 1504739.

[5] Barendse, M. E. A., Flournoy, J. C., Casey, B. J., Chen, C., Larsen, B., Luna, B., & Yung-Ting, D. (2023). Longitudinal change in adolescent depression and anxiety symptoms from before to during the COVID-19 pandemic: A collaboration of 12 samples. Developmental Psychology, 59(4), 623–641.

[6] Racine, N., McArthur, B. A., Cooke, J. E., Eirich, R., Zhu, J., & Madigan, S. (2021). Global prevalence of depressive and anxiety symptoms in children and adolescents during COVID-19: A meta-analysis. JAMA Pediatrics, 175(11), 1142– 1150.

[7] Wade, M., Prime, H., Johnson, D., May, S. S., Jenkins, J. M., & Browne, D. T. (2021). The disparate impact of COVID-19 on the mental health of female and male caregivers. Social Science & Medicine, 275, 113801.

[8] Thompson, R. S., Peterson, J. S., Martin, M. J., & Rogers, J. (2025). Risk factors for problematic social media use in youth: A systematic review of longitudinal studies. Adolescent Research Review, 10(2), 215–234.

[9] Vitagliano, E. M., Engel, N. R., & Thompson, R. (2025). Social media use and depressive symptoms during early adolescence. JAMA Network Open, 8(5), e2411544.

[10] Deng, X. Z., Ma, S., Song, S., Wang, R., Chen, L., & Liu, Z. (2025). Identifying adolescent depression and anxiety through real-world data and social determinants of health: Machine learning model development and validation. JMIR Mental Health, 12, e66665.

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Published

2025-12-19