statistics project topics

statistics project topics

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

1. Introduction

The wave of social media has had profound effects on the information and communication realms and has impacted the fundamental activities of humans from all age groups around the world. It has vastly changed communication and relationships and has affected our social fabric in many ways, including raising our levels of exposure to a society that is ever-connected. Although social media is a pervasive technology in improving social relationships, it has some downsides too, including negative psychological effects, particularly on the mental and emotional well-being of individuals. The negative impacts of excessive use seem to coincide with the growing pervasiveness of such media in today’s digital age, and this is alarming. The increased usage of some main social media categories including Facebook, Snapchat, and Instagram, adds to the formation of negative social comparisons and reduced contentment with life, dealing with the seal implications of the social media platforms.

2. Literature Review

The concepts of social media and mental health are relatively recent. Therefore, it is not surprising that the peer-reviewed literature of interest is still in its early stages of development. With a large window of various themes and different approaches objects of study. Among these, different aspects have emerged, such as the role of social networking platforms to recover from psychological problems, the predictors of health-related behaviors using traditional surveys and innovative social data, positive aspects of subjective well-being and recent technostress and work-life balance research. The two latter contributions should be noted for the use of innovative methodological designs, and all aforementioned work identified, at the same time, areas underexplored and methodological issues that can be improved. The literature studied in the present paper usually identifies the two main ways in which the heavy usage of social media can negatively affect mental health problems: cyberbullying/harassment and the ‘exposure to idealized lives’ as it acts as a negative social comparator.

As evidenced by the growing number of mental health problems around the world, it is crucial to understand how different factors in the environment lead to, or protect against, detrimental psychological outcomes. One such environmental factor that has had a significant impact on the mental health research agenda is the rise of social media networks. Social networking platforms appear to connect every corner of the world today, altering the way information is being circulated, breaking geographic boundaries, and bringing people closer. Despite the potential social benefits, some studies have found that excessive time spent on social media might exert a negative effect on mental health, and users are recognized as a vulnerable population at higher risks for various psychological problems. The vast majority of evidence in this field is experimental or correlational in nature. Therefore, we believed that methodologically sound research is warranted. The study at hand explored the association between problematic usage of social media and state and trait social anxiety constructs, self-management ability to cope with information and communication technologies and job stress levels in a large sample of Italian university students.

3. Methodology

3.1 Data structure: This paper utilizes data from the matched employer-employee panel data covering the universe of firms and workforce in the UK. The Business Structure Database 1998-2013 provides yearly workplace-level information, including firm financial performance, location, number of employees as well as CEI, while the UK Labor Force Survey 1998-2013 provides the employment and wage data on these firms. Finally, the longitudinal structure of this data allows us to observe individuals and workplaces at multiple time points. Given this rich employer-employee panel data, our setting allows us to estimate the effects of social media usage on mental health disutility, and can mitigate potential bias due to omitted variables.

This chapter outlines the quantitative methodology we used to explore the impact of social media usage on mental health. First, we briefly introduce matched employer-employee panel data from the UK. Then we explain the exploitation of social media usage and mental wellbeing in the data. The measurement of social media usage captures six different types of social media websites: online professional networks (LinkedIn), photo sharing websites (Instagram), microblogging websites (Twitter), and social networking websites of different types (Facebook, Tinder, and general social networking websites). In the end, we summarize the statistical framework and methods.

4. Data Analysis and Findings

Table 1 reveals that the credibility of people’s self-assessment of the number of social media apps in use would be called into question since the large coefficients of the time spent on SNS and the number of social media apps for being non-active in the labor market seem to be contradictory to the low likelihood of SNS users to rate the level of depression as “severe”. The likelihood of suicidal thoughts is 0.191 for females and 0.154 for males. In addition, employment status cannot explain the higher level of depression associated with the log time of SNS usage. Given the evidence in Table 1 is based on the OLS model, it should be noted that the level of depression and suicidal thoughts may be better captured under the framework provided by the ordinal nature of the dependent variables. Of significance is that 0.079 and 0.170 have been reported in previous studies.

In this section, we explore the impact of time spent on social media services (SNS_MM), number of social media apps (Time_Social), gender (female), age (Age), years of education (School), employment status (Employed), annual household income (Income), living arrangement (live_alone), and religion (rel) on the rate of suffering from depression and having suicidal thoughts. We provide our OLS and generalized linear model (GLM) estimations in Tables 1 and 2, respectively. Table 1 is an OLS estimation of the number of social media apps and actual number of apps reported in the self-assessment. The small coefficient on Time_Social indicates negative findings and large coefficient indicates positive findings.

5. Discussion and Conclusion

As a key lesson, numerous studies have reported the Werther effect (copycat suicides) and, more generally, the relational impacts of social media that originate from mere exposure, especially within the context of depressive symptoms. However, this study did not provide any support to these concerns. This result might be interpreted by the previously mentioned hypothesis that potentially vulnerable individuals would be less likely to reduce their social media activities, obviously consciously investing an important part of their remaining resources to interact on the platform, such as depression, loneliness, and so forth. In contrast with the first hypothesis, passive social media usage is able to light up dark aspects of life.

The study focused on determining the relationship between time spent on three most popular social media services and mental health, and more specifically, satisfaction with life, the presence of depressive symptoms, and the level of perceived stress. As social media service usage and time spent in social networks can have a differential effect on mental health of different groups of users, one of the explored dimensions was the type of use (active versus passive). The results of the study have shown significant differences between Facebook, Instagram, and Twitter regarding time spent active on the platform and number of visits. The explanatory power of the considered variables was statistically significant for the three mental health aspects, but small.