Effect of Social Media on Mental Health

Part 1: Introduction and Research Rationale 

The last two decades have witnessed a growth in the utilization of various social media platforms. Social media is described as the technological platforms which present individuals with the opportunity to communicate and share different content (Koehler & Parrell, 2020). Examples of popular social media platforms are Facebook, Twitter, Instagram, Snapchat, TikTok, and Messenger (Karim et al., 2020; Koehler & Parrell, 2020; Palyan, 2019). Various researches have estimated the number of individuals who use social media sites. According to Palyan (2019) and Karim et al. (2020), out of the 4 billion people who use the internet globally, about 3.3 billion persons are described as active social media users. Koehler and Parrell (2020) state that an estimated 8 in every 10 Americans are active social media users. 

The use of social media has some notable benefits. It allows individuals to form social connections, which are vital in one’s life as they help relieve stress, anxiety, and sadness (Karim et al., 2020). Scholars who argue in support of social media’s social connectedness benefit state that it helps protect individuals’ mental health (Karim et al., 2020). Contrariwise, some scholars have contended that social media negatively impacts mental health since it takes away the much-needed time to have physical interactions, a crucial pillar of mental wellbeing. Compulsive social media use has been linked to psychiatric disorders such as depression, low self-esteem, and anxiety (Koehler & Parrell, 2020). 

Various researchers have focused on social media’s impacts on the general population (Palyan, 2019). College students account for a significant proportion of active social media users, about 90% (Perrin, 2015). However, only a few researchers have delved into social media’s influence on college students’ mental wellbeing. Thus, there is a need to shed more light on this grey area. Consequently, this research will investigate social media’s impact on university students’ mental wellbeing at the University of Guelf in Canada. Quantitative research will be conducted to investigate the phenomenon. The research question for this research will be, “What is the correlation between the daily hours expended on social media and depressive symptoms?” The study hypothesizes a positive correlation exists between the daily hours spent using social media sites and depressive symptoms. 

Part 2: Literature Review 

The young, adolescents and the youth account for a significantly higher proportion of active social media users than adults and the aged. The social media sites commonly used by the aforestated groups include Facebook, Instagram, and Twitter. Social media sites are primarily used to share information, communicate, and entertain (Bashir & Bhat, 2017). Social media has positively influenced various fields, such as education, health, politics, and marketing (Kaur & Bashir, 2015). On the flip side, social media has its fair share of negative impacts. 

According to Bashir and Bhat (2017), the youth have largely adopted active social media use without a clear understanding of its negative impacts. Young adults spend several hours each day using various social media sites. The young adults immerse themselves in a virtual world, making their social life more virtual than practical. Social media sites have led to a reduction in the number of hours spent having face to face conversations (Bashir & Bhat, 2017). Face to face interactions are important since they offer a real human connection that helps combat stress, sadness, and anxiety. Social connectedness helps to improve mental health (Bashir & Bhat, 2017). Consequently, the absence of adequate real social connections has made the younger generations prone to the detrimental effects of active social media use, including anxiety, stress, and depression, 

According to a review conducted by Bashir and Bhat (2017), active social media use exhibited a positive correlation to mental health issues such as anxiety, stress, depression, and loneliness. Individuals who spend extensive hours using social media become anxious when they have not checked their social networking sites. The obsession with the likes and comments made on social networking sites makes active users, especially young adults, stressed when mean comments are made. The social connectedness amongst compulsive social media users is quite virtual. As such, they experience emotional loneliness due to a lack of real human connections. Anxiety, stress, and loneliness may be aggravated into depressive symptoms, negatively impacting one’s mental health (Bashir & Bhat, 2017). Park et al. (2014) made a similar finding in their research involving college students and stated that stress arising out of social media usage negatively impacts students’ mental wellbeing. 

The positive correlation between high social media use and depressive symptoms was also established by Palyan (2019) after conducting a web-based survey involving 200 participants in California. Although the finding by Palyan is acceptable, the study is limited in the sense that it used a small sample size, thus decreasing the generalization of the findings. Several other studies have also found a positive correlation between many hours spent on social media sites and depression (Lin et al., 2016; Vannuci et al., 2017). Social media usage time is a crucial determinant of mental health status. 

A different school of thought to the positive correlation between time expended on social media and depression states that the association between these variables is inconclusive. Jelenchick et al. (2013) and Searbrook et al. (2016) have stated that there exist zero relationships between the time expended on Facebook and depression. These researchers have argued that there must be other factors that contribute to depressive symptoms. According to Swainston (2020), the personal differences of how one perceives their social media use are factors that could contribute to depressive symptoms. Swainston (2020) further argues that there is no direct causal link between social media usage and depression. She asserts that the already established impact of social media on sleep quality could be one of the mediating factors that impact psychological disorder levels. Consequently, this research will investigate the relationship between social media usage and depression. 

Part 3: Research Design & Statistical Methods 

Research Design 

A quantitative research design will be used to answer the research question. The independent variable in our research will be the number of hours expended on social media sites. The dependent variable in the research design is the presence or absence of depressive symptoms. The control variable will be a group of students who are not on social networking sites. The research will be conducted using online surveys and questionnaires. 

According to Evasiuk (2016), the quantitative research design is useful as it helps in the generalization of the findings and identifying trends in the larger population. Surveys are appropriate for this study since they help identify trends, attitudes, or opinions. Surveys are also essential in responding to descriptive questions and queries on the relationship between variables. 

Probability sampling will be used to select the participants of the study. The random sampling method will be used to recruit participants. The random sampling technique is preferred for use in this study because it accords all the students within the University of Guelf an equal opportunity to participate in the study. The participants in the study will be the University of Guelf students. The study seeks to use a sample size of 500 students and a control sample of 50 students. The control sample will comprise of students who are not on any social media site. 

Consent to conduct the research will be sought from the relevant authorities within the university. Afterward, students will be sensitized on the study’s aim through the various students’ social media platforms. Students will be asked to volunteer in either the two groups, the active social media users and non-users. The study will utilize an online web platform to collect data. An online web platform offers various advantages such as convenience and increased confidence level in the research by decreasing the social desirability bias. 

The survey will collect various data such as demographic information, including one’s age and gender. The frequency of using social media sites will be collected through querying the number of times the participant uses social media sites in a week and the number of hours used on social media accounts each day. Depressive symptoms amongst the participants will be determined using the Personal Health Questionnaire Depression Scale (PHQ-8). The scale’s eight parameters will be used to diagnose and assess the severity of depression. 

Statistical Methods 

Descriptive statistics will be used to analyze the collected data. Descriptive statistics will help measure the association between the independent and the dependent variables. The independent variable being the amount of time expended on social media sites and the dependent variable being the depressive symptoms. The mean and the standard deviation for the independent variable (number of hours spent on social media) will be determined. The descriptive statistics that will be determined in the dependent variable analysis are kurtosis, mean, standard deviation, median, mode, skewness, and the quartiles. The minimum level of measurement for the dependent variable will be zero for those not bothered by any of the 8 diagnostic criteria in the PHQ -8 scale. The maximum level of measurement for the dependent variable will be 24 for participants bothered by all of the 8 criteria on almost a daily basis. Each parameter bears a maximum of 3 points when one is bothered daily and thus the maximum score of 24 points. 

The relationship between the number of hours used on social media and depressive symptoms will be examined using the Pearson Correlation analysis (Pearson’s R). The statistical significance of the obtained results will be examined using the chi-square test. By choosing an alpha value of 0.05, the p-value obtained will help indicate whether the hypothesis is valid and if the results are reflective of the population. 

References 

Bashir, H., & Bhat, S. A. (2017). Effects of social media on mental health: A review.  International Journal of Indian Psychology ,  4 (3), 125-131. 

Jelenchick, L. A., Eickhoff, J. C., & Moreno, M. A. (2013). “Facebook depression?” social networking site use and depression in older adolescents.  Journal of Adolescent Health ,  52 (1), 128-130.  https://doi.org/10.1016/j.jadohealth.2012.05.008 

Karim, F., Oyewande, A., Abdalla, L., Chaudhry Ehsanullah, R., & Khan, S. (2020). Social media use and its connection to mental health: A systematic review.  Cureus . https://doi.org/10.7759/cureus.8627 

Kaur, R., & Bashir, L. (2016). Impact of stress on mental health of students: Reasons and Interventions.  International Journal of Education ,  5 , 30-35. 

Koehler, S. N., & Parrell, B. R. (2020). The impact of social media on mental health : A mixed-methods research of service providers’ awareness. 

Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., ... & Primack, B. A. (2016). Association between social media use and depression among US young adults.  Depression and anxiety ,  33 (4), 323-331. 

Palyan, V. (2019).  The Impact of Social Media on Mental Health — Spotlight on Research . Spotlight on Research. Retrieved 2 December 2020, from https://www.spotlightonresearch.com/mental-health-research/the-impact-of-social-media-on-mental-health#:~:text=Lin%20et%20al.,times%20the%20risks%20of%20depression . 

Park, N., Song, H., & Lee, K. M. (2014). Social networking sites and other media use, acculturation stress, and psychological wellbeing among east Asian college students in the United States.  Computers in Human Behavior ,  36 , 138-146.  https://doi.org/10.1016/j.chb.2014.03.037 

Perrin, A. (2015).  Social Media Usage: 2005-2015 . Pew Research Center: Internet, Science & Tech. Retrieved 2 December 2020, from https://www.pewresearch.org/internet/2015/10/08/social-networking-usage-2005-2015/. 

Seabrook, E. M., Kern, M. L., & Rickard, N. S. (2016). Social networking sites, depression, and anxiety: A systematic review.  JMIR Mental Health ,  3 (4), e50.  https://doi.org/10.2196/mental.5842 

Swainston, J. (2020).  Social Media Effects On Mental Health: 6 Life-Enhancing Tips . PositivePsychology.com. Retrieved 2 December 2020, from https://positivepsychology.com/social-media-effects/ . 

Vannucci, A., Flannery, K. M., & Ohannessian, C. M. (2017). Social media use and anxiety in emerging adults.  Journal of Affective Disorders ,  207 , 163-166.  https://doi.org/10.1016/j.jad.2016.08.040