Chat with us, powered by LiveChat Fit a multiple regression model, testing whether a mediating variable partly or completely mediates the effect of an initial causal variable on an outcome variable. Think abou - Writingforyou

Fit a multiple regression model, testing whether a mediating variable partly or completely mediates the effect of an initial causal variable on an outcome variable. Think abou

  1. Fit a multiple regression model, testing whether a mediating variable partly or completely mediates the effect of an initial causal variable on an outcome variable. Think about whether or not the model will meet assumptions.
  2. Fit the model, testing for mediation between two key variables.
  3. Analyze the output, determining whether mediation was significant and how to interpret that result.
  4. Reflect on possible implications of social change.

2

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

Jailya Wooden

Walden University

RSCH 8260

September 9, 2023

Introduction

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.

Methodology

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.

Results

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.

References

Draženović, M., Vukušić Rukavina, T., & Machala Poplašen, L. (2023). Impact of Social Media Use on Mental Health within Adolescent and Student Populations during COVID-19 Pandemic: Review. International Journal of Environmental Research and Public Health, 20(4), 3392. https://doi.org/10.3390/ijerph20043392

Lukose, J., Gardner Mwansa, Ngandu, R., & Oki, O. (2023). Investigating the Impact of Social Media Usage on the Mental Health of Young Adults in Buffalo City, South Africa. IJSSRR, 6(6), 303–314. https://doi.org/10.47814/ijssrr.v6i6.1365

Schønning, V., Hjetland, G. J., Aarø, L. E., & Skogen, J. C. (2020). Social Media Use and Mental Health and Well-Being Among Adolescents – A Scoping Review. Frontiers in Psychology, 11(1949). https://doi.org/10.3389/fpsyg.2020.01949