statistics project data set

statistics project data set

Exploring the Impact of Social Media Usage on Mental Health: A Statistical Analysis

1. Introduction

Recently, the heightened use of and availability of social media has facilitated the emergence of e-commerce and has had a profound effect on other social and economic activities. Although its impact in a variety of contexts is yet to be fully understood, social media technology has had considerable influence in various disciplines including marketing, economics, psychology, and mental health, among others. It has led to changing social interactions, our relationship with others, privacy concerns, and a variety of other outcomes. As its usage becomes more commonplace, policymakers and public institutions have been raising concerns about its impact on other human behaviors, including mental illness. The use of social media, with the increasing number of social applications available, causes unique and profound mental health and privacy concerns since psychological profiles are easily established based on what people share. Consequently, the popularity of using social media and its many variations has attracted significant attention from psychologists, physicians, and public health officials. Their research often touches upon the psychological processes and treatment strategies for improving mental health using digitized communication channels. Despite this growing interest, no study has established a quantitative relationship between social media usage, measured as mean days of social media usage using different device platforms, and mental illness in a regression setting. In this work, we fill this gap by performing a large-scale analysis from a public repository and contribute a multiple linear regression model of the impact of social media usage on levels of mental illness.

2. Literature Review

Preliminary versions of the research studies from 2011 raised the important question of whether it is the Facebook medium itself that drives the effect, or whether the users who spend time on this social network are inherently at higher risk of suffering the negative impacts associated with this form of social comparison. With the results comparing the Facebook users to the non-Facebook users providing an element of clarity for the question.

Several relatively recent studies have established a connection between the use of these social network platforms, particularly Facebook, and the prevalence of such mental health disorders as anxiety, depression, etc. Several psychological issues including low life satisfaction, mood alteration, feelings of reduced control, social disconnection, and an overall drop in general well-being have been found to be strongly linked with the excessive use of social media. Several other researchers have come to a similar conclusion but have posited that the prevalent use of social media is just a catalyst to the mental health problems.

A global survey of social media use undertaken by Tower and Egidos reveals a significant and steady growth in the number of users in online social networks. In 2003, the survey reported 18.6 million users on all social networks. This figure rose sharply to 31 million users in 2006, 100 million in 2007, before reaching an estimated 800 million in 2009. As expected, Facebook had the largest share of the market with over 70% of the users in 2009. Only 2.3% of the surveyed users were members of commercial networks, although LinkedIn played an important role in the corporate world, enjoying over 90 million users representing over 50% of the professional services market.

According to Aine Silow’s contributions to the Currency Insight Series, there has been a steady increase in the proportion of internet, and subsequently social media, users over the last few decades. This is in part due to rapid changes in the field of technology. Advancements in this area have offered the world tools for collaborative learning, remote working, conducting businesses and socializing, just to mention a few.

3. Methodology

OLS models were estimated with instrumental variables for simultaneous equation bias. Specifically, instrumental variables were pent up social demand. The media value had a coefficient value of 0.54008, and the results revealed a larger positive quantile effect. In addition, approximately 25% of the data were managed for moderation effects.

We used STATA, which is a complete software for time-series, allowing data management, matrix programming, and data frame observation. We conducted an exploratory factor analysis for the 10 items of underlying media value. We found 3 components, i.e. sociability, social comparison, and entertainment activities, where the first 7 factors showed how frequently they participated in each of the 7 outcome activities, and the last 3 factors were the type of 3 outcomes experienced.

To the best of our knowledge, we took the survey done by Levine, J. A., and Schweitzer (2014) as a reference, which is the individual-level data survey. The questions mainly concentrate on hours per day, giving a measure of their time spent on social networking activities. We study the data to understand the relative and concurrent validities of satisfaction with life, Health Survey, as well as sleep, and non-trivially correlated with mental health. Finally, we present the analyses for the relationships among media, happiness, and mental health issues.

Mental health has been an ever-growing primary concern among individuals. According to the World Health Organization, 25% of the world’s population was affected by the rise in mental disorders from 2005-2015. There are various reasons attributed to this rise, such as awareness, changes in social and economic conditions, etc. More importantly, it is also due to increased exposure to the use of social media.

4. Data Analysis and Findings

To figure out the weight of each problem identified under this aspect concerning the mental health struggle, a web-based questionnaire was developed to obtain real-life experiences. The questionnaire was also intended to validate the scope of each of these problems in terms of the disruption not only in the private individual sphere but also in the labor playing an essential role in the deliberation process.

The final form of the online survey after Model 1’s suggestions and alterations was consequently developed and used for the subsequent survey. The dependent variable, mental health struggle, was assessed by diagnosing such struggles from a list of conditions such as anorexia or bulimia, anxiety, burnout syndrome, ADHD, depression, autism, self-destructive behavior, insomnia, schizophrenia, bipolar disorder, chronic fatigue syndrome, trauma with little to no emotional expression, bipolar disorder, body dysmorphic disorder, schizophrenia, panic, substance abuse, etc. The independent variables were demographic data, main problems that respondents have faced, technologies used for obtaining information, communication, entertainment, shopping, work, study, banking, surveillance, social media use frequency, and social media use, sleep interference.

5. Conclusion and Implications

Rather surprisingly, our additional findings imply that the engagement of trendsetter activities of individuals on social media might provide some “counterbalancing” effects that alleviate negative pathogenic effects of social media usage, which is in contrast to the prior assumptions that they might all aggravate the well-being of individuals. We did not find any significant differences across gender in the relationship between social media usage and the well-being indices. The associations were quite weak, but consistent across different time frames and age groups. The effect of social media usage is mostly concentrated among young adults, which is quite worrying and therefore echoes prior calls on the well-being effects of social media usage. Our study has important policy implications. The online social networks have become an indispensable part of young people’s lives; yet contrary to popular assumptions, they are not contributing to patterns of psychological well-being. The current regulatory stance on social media usage is largely precautionary, focused on whether it is addictive and can be used for viral communication that creates panic. Our evidence presents the actual psychological mechanism and negative consequences that we have suspected, and provides a scientific base for policy setting.

This article statistically investigates the link between social media usage and mental well-being and identifies which dimensions of social media usage most harm mental health. Results show that although social media has positive effects on perceived social support, it does not, however, seem to directly enhance the psychological well-being of individuals when other aspects of mental health are considered. Indeed, frequent social media usage may negatively impact the social well-being of individuals, possibly due to social media-related issues stemming from social comparison and epidemic loneliness. Our findings also implicate that the role of perceived loneliness and social support seems to be over-exaggerated on well-being. We also show that this negative well-being effect is driven more by the usage frequency than by trendsetter activities on social media.