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Multiple Regression Analysis: The Influences of social media on Young Adults Mental Health

Multiple Regression Analysis: The Influences of social media on Young Adults Mental Health


The study examined how social media usage impacts the mental health of young adults. Multiple regression analysis was utilized to determine whether social media use predicts mental health markers such as melancholy, anxiety, and self-esteem. This investigation sheds light on how excessive social media use can harm young people’s mental health and has implications for public health efforts to promote proper social media use.


University students self-reported their weekly social media hours. Standardized questionnaires assessed depression, anxiety, and self-esteem, as well as the Beck Depression Inventory (BDI), GAD-7, and Rosenberg Self-Esteem Scale. We adjusted for age, gender, and academic stress.


Multiple regression was used to analyze social media use and mental health. This table shows the results:

Multiple Regression Analysis Results
Dependent Variable: Mental Health Outcomes
  Coefficients Std. Error t-Statistic p-value
Intercept 15.23 1.50 10.16 <0.001
Social Media Usage -0.42 0.08 -5.36 <0.001
Age -0.05 0.12 -0.42 0.676
Gender (Female) 2.71 1.27 2.14 0.033
Academic Stress 1.15 0.09 12.72 <0.001
R-squared: 0.45        


The regression results reveal numerous key insights. A substantial negative correlation exists between social media use and mental health outcomes (coefficient = -0.42; p < 0.001). As social media use grows, sadness, anxiety, and self-esteem deteriorate.

Young individuals who use social media more are more depressed, anxious, and self-conscious, according to the coefficient. This supports prior studies (Primack et al., 2017; Vannucci et al., 2017) showing that excessive social media usage may lead to social isolation, anxiety, and poor self-esteem. Control factors showed significant outcomes. Female gender and age did not influence mental health outcomes, as seen by their non-significant p-values. Academic stress significantly improves mental health outcomes (coefficient = 1.15, p < 0.001), suggesting an association between higher levels and worse mental health.

Implications for Social Change

The multiple regression analysis has major social transformation implications. First, the unfavorable association between social media use and mental health highlights the need for young individuals to utilize social media responsibly (Schønning et al., 2020). The excessive hours spent reading through feeds, social comparison, and cyberbullying or harassment may lead to mental health difficulties (Lukose et al., 2023). The results underscore the necessity for public health efforts to increase awareness of the mental health risks of excessive social media usage. Such efforts may teach young people about establishing social media limits, pausing, and getting treatment for depression or anxiety.

Interventions and support

Universities and colleges can help students manage social media and stress. Digital literacy training, mental health resources, and therapy for social media-related emotional issues may be used. Social Media Platform Responsibility: Social media platforms may encourage healthy use. They may promote screen time reduction, mental health assistance, and cyberbullying prevention (Draženović et al., 2023). Building a supportive community and peer network may assist young people in managing social media. Open dialogues about mental health and peer support may help individuals in need.

In conclusion, our multiple regression analysis shows that young people’s mental health depends negatively on social media use. This suggests that excessive social media usage may have harmful effects, requiring public health campaigns, interventions, platform modifications, and peer support. By implementing these strategies, society can promote responsible social media usage and youth mental health.