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BEYOND DEPRESSION DETECTION: UNVEILING THE COMPLEXITIES OF SOCIAL MEDIA AND MENTAL HEALTH

Journal: International Journal of Advanced Research (Vol.12, No. 08)

Publication Date:

Authors : ;

Page : 1661-1669

Keywords : Social Media Multiple Regression Analysis K-Means Clustering Distraction Mental Health Age Groups;

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Abstract

The burgeoning influence of social media raises concerns about its potential impact on mental health. Understanding how individuals engage with these platforms and the factors influencing their usage is crucial. This study addresses this gap by examining social media usage patterns and their association with mental well-being. A two-pronged methodological approach is employed. First, a multiple regression analysis explored the influence of various factors, including age, well-being, and distraction, on social media use. Subsequently, K-means clustering was utilized to identify distinct user groups based on their social media usage patterns. The findings revealed distinct usage patterns across different age groups. Notably, distraction emerged as a strong predictor of social media use, while other factors exhibited minimal direct effects. This suggests social media use is a multifaceted behavior influenced by a complex interplay of variables, not solely demographics or mental health states. These insights highlight the need for further research exploring the interactions between these factors and incorporating additional influences such as socioeconomics and digital literacy. A deeper understanding of social media usage patterns can lead to the development of effective interventions to promote responsible use and enhance mental well-being.

Last modified: 2024-09-27 18:59:11