The Relationship Between Social Media Use And Mental Health Issues In Adolescents

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1. 

Woods, H. C., & Scott, H. (2016). # Sleepyteens: social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. Journal of Adolescence, 51, 41-49.

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https://eprints.gla.ac.uk/120206/7/120206.pdf

The study evaluates the health related issues caused due to social media use by adolescents. It proceeds through the measurement of social media on the basis of time and also the calculation of the amount of emotional attachment in the social media of the adolescents under study. According to the study, those adolescents who used social media more at night and all over the day, they are more prone to suffer from the inadequate sleep and extreme level of anxiety. Higher the emotional attachment in social sites, higher the depression level. It has successfully measured the anxiety, depression, poor sleep quality and other attributes influenced by social media with the outcome of above 5 score of Pittsburgh Sleep Quality Index for the poor sleepers (35%) having longer engagement in the social media. Besides, 47% and 21% of the participants have been classified as anxious and depressed. The journal has concluded the relationship of social media and mental disorders through analysis of statistical measurements correlation coefficients and p-values (Woods & Scott, 2016).

2. 

Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, S. (2016). The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychology of Addictive Behaviors, 30(2), 252.

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https://irep.ntu.ac.uk/id/eprint/27290/7/27290_Kuss.pdf

This study of University of Bergen demonstrates the risk factors which are the consequences of the addiction towards social media, online activities, and video gaming. The risk is higher for those who are single as they are more engaged in online activities. These addictions lead to Attention Deficit/Hyperactivity Disorder (ADHD) and Obsessive-Compulsive Disorder (OCD). The empirical investigation has revealed that OCD symptoms are relatable with the disorder symptoms that happen for excessive addiction in social media and it results depressive and anxious attitude of men and women. The regression analysis of a sample of 23,533 respondents shows that there is high positive correlation lies among the measures of ADHD, OCD, and anxiety. The study also analyses the effect of addiction based on age, gender, education level, and marital status. There is positive association between video gaming and single people, primary and high school children, depression, OCD, and ADHD. Again, the negative association can be seen for females, students pursuing master’s degree, and anxiety (Andreassen et al., 2016).

3. 

Elhai, J. D., Levine, J. C., Dvorak, R. D., & Hall, B. J. (2017). Non-social features of smartphone use are most related to depression, anxiety and problematic smartphone use. Computers in Human Behavior, 69, 75-82.

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https://static1.squarespace.com/static/56916e4805f8e207077fb3ed/t/5851b2bb2994ca7a6254ba75/1481749179695/ElhaiLevineDvorakHall2017.pdf

The purpose of this article is to enlighten the problematic use of smartphone that causes the depression and other mental disorders. The authors have proceeded the study with the investigation of the two types of smartphone usage namely, process use and social use. The social use involves involvement in social media and chatting. Besides, the process use defines the non-social uses like entertainment, new-reading, and relaxation. The result has shown that process use is more responsible for problematic smartphone use and it is accountable for increased level of anxiety and depression. Moreover, the symptoms of depression have negative association with the more social smartphone use. The measurements of Smartphone Addiction Scale (SAS) have been taken into account here having 33 items on 6-point Likert scale. The change of the psychopathology reveals that depression is inversely proportional to the problematic use of smartphone. This study has used the measurement of SAS and also discussed about the variation of the smartphone usage and their effects (Elhai et al., 2017).

4. 

Demirci, K., Akgönül, M., & Akpinar, A. (2015). Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. Journal of behavioral addictions, 4(2), 85-92.

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https://akademiai.com/doi/pdf/10.1556/2006.4.2015.010

This journal article aims to highlight the predominance of smartphone use with anxiety and depression among university students. The study has also concluded that the addiction score is higher for female students than male students. The outcome has been evaluated from the study of the smartphone behaviors of 319 participants and dividing them into three groups namely, smartphone non-user group, low smartphone use group, and high smartphone use group. Then the scores of daytime dysfunction, depression and anxiety have been analysed using the Beck Depression Inventory, Pittsburgh Sleep Quality Index, and Beck Anxiety Inventory. The scores were higher for the high smartphone use group. The study offers a useful contribution towards the topic of interest by providing the measurements based on the above mentioned indices. It also reveals that the sleep problems comes from the overuse of smartphone and instructs that special care should be given to the university student with high depression scores (Demirci, Akgönül & Akpinar, 2015).

5. 

Weinstein, A., Dorani, D., Elhadif, R., Bukovza, Y., Yarmulnik, A., & Dannon, P. (2015). Internet addiction is associated with social anxiety in young adults. Annals of Clinical Psychiatry, 27(1), 4-9.

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https://s3.amazonaws.com/academia.edu.documents/42846485/Internet_addiction_is_associated_with_so20160219-31054-yd8sni.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1532946670&Signature=iSRPP4esQv8DD5k%2FNy5IflbJboM%3D&response-content-disposition=inline%3B%20filename%3DInternet_addiction_is_associated_with_so.pdf

The study develops the theory regarding the association of the social anxiety in adolescents. The Problematic Internet Use (PIU) and the psychiatric disorder due to PIU has been extensively discussed in this article. Two samples of University students of Israel having 60 males and 60 females in each sample, have been analysed. A demographic questionnaire with a Cronbach alpha value of 0.966, has been prepared to collect the data on age, sex, marital status, education, employment, and internet use from the 120 respondents. Then the Young Internet Addiction Test has been used to measure the internet addiction score on a 6-point scale based on 20 measuring attributes. The cut-off of the addiction score is >80. This cross-sectional study has found that there is a good positive association between the social anxiety and internet addiction for both the samples having correlation coefficient values 0.411 & 0.342. Moreover, the study also states that social anxiety is not affected by gender difference and the anxiety level is irrespective of any particular social networks (Weinstein et al., 2015).

6. 

De Choudhury, M., Counts, S., & Horvitz, E. (2013, May). Social media as a measurement tool of depression in populations. In Proceedings of the 5th Annual ACM Web Science Conference (pp. 47-56). ACM.

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https://www.munmund.net/pubs/websci_13.pdf

The research article provides an important contribution in the research topic of concern as it has used the social media as a tool to measure the depression level among populations. The study proceeds by considering depression as a global health challenge and it examines the potential role of social media activities for the enhancement of depression using the crowdsourcing technology to gather ground truth data. This methodology is useful to construct a big corpus of Twitter postings that is diagnosed with clinical depression. Then a probabilistic model is built on the basis of the corpus to identify the whether any social post correlates with the depression. Moreover, the depression is also analysed on the basis of the geographical and demographical barriers to find if any correlation exists using the reports provided by the Centers for Disease Control and Prevention on depression statistics. Thus study helps to figure out clinically depressed users by leveraging the depression using social media depression index (De Choudhury, Counts & Horvitz, 2013).

7. 

Rosen, L. D., Whaling, K., Rab, S., Carrier, L. M., & Cheever, N. A. (2013). Is Facebook creating “iDisorders”? The link between clinical symptoms of psychiatric disorders and technology use, attitudes and anxiety. Computers in Human Behavior, 29(3), 1243-1254.

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https://www5.csudh.edu/psych/Is_Facebook_Creating__iDisorders__The_Link_Between_Clinical_Symptoms_of_Psychiatric_Disorders_and_Technology_Use,_Attitudes_and_Anxiety-2013-Computers_in_Human_Behavior_Rosen_Whaling_Rab_Carrier_Cheever.pdf

This article aims to explain if the use of social media is responsible for mood disorders and to some great extent, historic personality disorders, narcissism and even schizoid personality disorders. The habit of excessive chatting and watching video clips, and video gaming is influencing the symptoms of personality disorders. The anonymous responses in the questionnaires of 1143 respondents have been used to study the predictor variables. The outcome shows that there is both negative and positive aspects of the use of social media and harmful effect of multitasking. The study tests four hypotheses. The second and the third hypothesis predict that technology related behaviors and the technology-related anxiety. The first and the fourth hypotheses predict whether social media activity will increase the clinical symptoms of mental disorders. The study plays an important role in explaining the psychological influence of technology and its impact on psychological health. However, the study is restricted on the respondents of Southern California only and the research does not provide any demographic explanations (Rosen et al., 2013).

8. 

De Choudhury, M., Counts, S., & Horvitz, E. (2013, April). Predicting postpartum changes in emotion and behavior via social media. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3267-3276). ACM.

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https://course.duruofei.com/wp-content/uploads/2015/05/Choudhury_Predicting-Postpartum-Changes-in-Emotion-and-Behavior-via-Social-Media_CHI13.pdf

The article focuses on the construction of predictive models using the Twitter posts of new mothers regarding the childbirth to forecast the behaviors and mood swings of the new mothers. These changes have been observed for 376 mothers to conclude the modification observed at the postpartum period. The observable change of the mothers is accurately presented for 71% of the cases. The accuracy level is more than 80% for data of 2-3 weeks old. The attributes of new mothers are explored and these are helpful to discover the psychological changes experienced by the mothers. The Postpartum Depression (PPD) is studied through the meta- analysis of the risk factors of PPD like prenatal depression, a strong factor of PPD.  Besides, the article talks about the expansion of the use of social networks based measures that are responsible to calculate the correlation among the mood changing variables. These variables are engagement level, linguistic style, emotion, and ego.  It concludes that after 3 months of childbirth, the maximum changes can be observed with 80% accuracy (De Choudhury, Counts & Horvitz, 2013).

9. 

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.

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https://www.csus.edu/faculty/m/fred.molitor/docs/social%20networking%20and%20depression.pdf

The study evaluates the association between depression and social media engagement among young adults with the application of the Experience Sample Method (ESM). The university students are the appropriate respondents for this study who are undergone by an online survey and completion of a questionnaire. Total 190 participants have responded the study and the calculation shows that the hours consumed after social media activities are less than 30 minutes and between 30 minutes to 2 hours. There has not been sufficient evidence in support of the positive relationship between the depression and the use of social networking sites. The logistic regression analysis has been used to calculate the relationship between the social networking sites and the probability of experiencing any sort of depression and there has been no significant association. The study has significant contribution in the clinical field to figure out the number of adolescents suffering from Facebook depression (Jelenchick, Eickhoff & Moreno, 2013).

10. 

Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015). Facebook use, envy, and depression among college students: Is facebooking depressing?. Computers in Human Behavior, 43, 139-146.

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https://s3.amazonaws.com/academia.edu.documents/45513616/Facebook_use_envy_and_depression_among_c20160510-590-rofc43.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1532996049&Signature=f1NTgQL%2BvijzgizZYvtIEpLIw%2Fg%3D&response-content-disposition=inline%3B%20filename%3DFacebook_use_envy_and_depression_among_c.pdf

The purpose of this study is to highlight the transition from school life to college life and the effect of social media like Facebook at that transition period. The framework of this research lies in the social rank theory of depression. A survey has been conducted on 736 college students to evaluate whether the depression is negotiated by the Facebook envy. The study is important as it provides research on Facebook envy which is the perception that others are happier than one. The research hypothesis developed here is whether the high Facebook use implies the higher level of Facebook envy. This Envy is measured using a 5-point Likert scale. The statistical analysis concludes that the there is no direct link between Facebook use and the generation of depression. The null hypothesis has been accepted here, concluding that Facebook envy is directly proportional with the intensity of Facebook use. However, this study restricts its research to highlight that sometimes Facebook use also lead to reduce depression among many college students (Tandoc, Ferrucci & Duffy, 2015).