Harmful Affects of Social Media on Teens

  1. Provide the citation and attach a pdf of the article
    • PDF: Article Review
    • Banyai, F., Zsila, A., Kiraly, O., Maraz, A., Elekes, Z., Griffiths, M. D., Andreassen, C. S., & Demetrovics, Z. (2017). Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample. PLoS ONE12(1), e0169839. https://link.gale.com/apps/doc/A476889741/AONE?u=klnb_fhsuniv&sid=bookmark-AONE&xid=f730142c
  2. What is the abstract of the article?   
    • Background: Despite social media use being one of the most popular activities among adolescents, prevalence estimates among teenage samples of social media (problematic) use are lacking in the field. The present study surveyed a nationally representative Hungarian sample comprising 5,961 adolescents as part of the European School Survey Project on Alcohol and Other Drugs (ESPAD). Using the Bergen Social Media Addiction Scale (BSMAS) and based on latent profile analysis, 4.5% of the adolescents belonged to the at-risk group, and reported low self-esteem, high level of depression symptoms, and elevated social media use. Results also demonstrated that BSMAS has appropriate psychometric properties. It is concluded that adolescents at-risk of problematic social media use should be targeted by school-based prevention and intervention programs.
    • Methods: The data were collected in March 2015 as part of the European School Survey Project on Alcohol and Other Drugs (ESPAD; [45]) that included a nationally representative adolescent sample. The target population was adolescents aged 16 years. In 2015, Hungary included a short section to assess internet and social media use in addition to the original questionnaire developed by the ESPAD Committee. To obtain a representative sample, two different grades (9th -10th ) were included in the Hungarian data collection, each containing a proportion of the target population. To reduce sampling error, the grades were divided into non-overlapping, homogeneous subgroups. The variables to ensure the representativeness of the adolescent sample were as follows: region (central/western/eastern Hungary), grade (9th, 10th), and type of class (secondary general, secondary vocational, vocational classes). The data were collected anonymously from the students in the classrooms of the schools by research assistants. The refusal rate was 7% on the level of the primary sampling unit (i.e., classes) that led to skewed nonresponse. To match the composition of the respondents with the sampling frame, data were weighted by strata with the matrix weighting method recommended by the Education Information System 2014/2015 (KIR-STAT; Elekes, 2015). The total sample consisted of 6,664 participants (50.94% male). The youngest participants were 15 years old, while the oldest were 22 years (mean age 16.62 years; SD = 0.96). The wide age range was due to a very small number of older students still attending the 9th or 10th grades at the age of 19 years or older at the time of data collection. The questions concerning internet use and social media use were included for this nationally representative sample of 9th -10th graders in secondary general and secondary vocational schools. Participant data with severe incompleteness or inconsistencies were excluded (3.72% of the sample), in addition to those participants who did not use the internet and/or any social media (an additional 6.83% of the original sample). After removing these participants, the final sample size was 5,961 (89.45% of the total sample). This study was approved by the Scientific Ethical Committee of Corvinus University of Budapest. The study design was based on an international protocol approved by the European School Survey Project on Alcohol and Other Drugs (ESPAD) Assembly, which was conducted in full compliance with the principles expressed in the Declaration of Helsinki. Written informed consent was requested from both the students and their parents (passive on behalf of their children).
    • Results:
      • Descriptive statisticsThe final sample only comprised those participants who reported using the internet and social media (n = 5,961, 89.45% of the total sample). Approximately half (49.17%) of the sample was male (n = 2931). Age ranged between 15 and 22 years (mean age 16.60; SD = 0.94). The mean number of hours using social media was 23.16 hours per week (SD = 15.57). There was a significant difference in weekly social media use between male and female adolescents (mean timemale = 20.53 hours, SDmale = 15.71; mean timefemale = 25.71 hours, SDfemale = 15.00; U = 3672101, p< 0.001; r = -0.17).
      • Confirmatory factor analysis
        A one-factor model with the six components (salience, tolerance, mood modification, relapse, withdrawal, conflict) as indicator variables was tested with confirmatory factor analysis. The analysis provided an acceptable fit to the data (χ2 = 5836.190 df = 15 p< 0.001; CFI = 0.950; TLI = 0.917; RMSEA = 0.073 (0.066–0.080) Cfit>0.90; SRMR = 0.034). All factor loadings were above the recommended threshold (>.50) and ranged from .598 to .814.
      • Latent profile analysis
        The latent profile analysis was performed on the six items of the BSMAS, and according to the criteria, the three-class solution was selected as the best-fitting model (see Table 1). The AIC, BIC, and SSABIC values decreased continuously as more classes were added to the analysis. However, the scale of decrease somewhat diminished after the third latent class was added. Based on the L-M-R test, the three-class solution was accepted. The entropy of the two-class solution was the highest, but the entropy of the three-class solution was also adequate. The features of the three classes are presented in Fig 1 and Table 2. The first class named ‘no-risk’ class represents the majority of social media users (78.3% of social media users; 70.7% of the total sample) who had the lowest scores on the BSMAS. The second class of social media users represents ‘low risk’ of problematic use (17.2% and 15.5% respectively), while the third class represents the population of ‘at-risk’ problematic social media users (4.5% and 4.1%, respectively). In the ‘at-risk’ group, ‘withdrawal’ and ‘tolerance’ criteria showed elevated levels compared to the other dimensions. Members of this class (i.e., those at-risk of problematic use) were likely to (a) be female, (b) use the internet and social media for more than 30 hours per week, (c) have lower self-esteem and higher level of depressive symptoms than social media users of the other two classes (Table 2).
    • Conclusions: In conclusion, the results of the present study suggest that the Bergen Social Media Addiction Scale [11] is a psychometrically valid scale that is an appropriate tool to identify the signs of risky social media use among adolescents. This instrument may be especially useful in school environments to identify those adolescents who are at-risk of problematic social media use and therefore could be utilized in prevention and intervention programs (i.e., content-control software, counseling, cognitive-behavioral therapy; [69]).
  3. Was the study experimental or non-experimental? The study is non-experimental. It is an observational study in which the researchers did not introduce manipulations or treatments. Then to get the results the students were polled on their behavior.
  4. Was the research qualitative or quantitative? This is a qualitative study because it uses a relatively small sample of students and analyzes behavior through the BSMAS scale to gather results.
  5. What was the population studied? In the participants and procedure methods portion of the article, it mentions the population as, “adolescents aged 16 years.”
  6. What sample was used for this study?  The sample was 5,961 9th and 10th graders from Hungary. The students selected varied in regions of Hungary and the type of classes they took.
  7. What was the method of measurement?
    • To measure social media use students were asked two questions. (1) In the last week how many days have you used social media? (2) On average how many hours a day did you spend on social media this month?
    • Behavior was measured by polling using the Bergen Social Media Addiction Scale (BSMAS), Rosenberg’s Self-Esteem Scale, and the Center of Epidemiological Studies Depression-Scale.
  8. What was the method of analysis?
    doi:https://doi.org/10.1371/journal.pone.0169839.g001

    These two forms of measurement were then compared and graphed to better understand the correlation between the use of social media and negative behaviors.

  9. What was the conclusion of the study? The study showed that there is a correlation to increased social media use results in more negative behaviors. It also demonstrates that the BSMAS scale can be used as a legitimate means of measurement to calculate such behaviors.
  10.  Why is this study useful to you? I believe this study was useful to me personally because I am still close to the age being measured by this study, and I am in fact a user of social media. Also one day I will have children so it is important to know the effect it has on adolescents. On the professional side of thinking, I will be promoting the use of the internet and social media in a way. I think it is crucial to acknowledge that this access to constant information and communication can be harmful, especially to young developing minds.
  11. What would be the next logical step in extending this study? There are a few directions I would like to see this study extended. I would like to see the physical effects overuse of social media can have on teenagers. This study just showed behaviors and mental health but I think it would be interesting to see the use of social media does result in an increase in physical self-harm or an increase in aggressive behavior. I would also like to see how we can combat this issue. The article mentioned prevention and intervention programs, but it would be helpful to know how effective each of them is. Lastly, a follow-up study on these participants would be interesting. Seeing if there is any observable disparity between those that were in the no-risk group compared to the at-risk group when they are 40 years old could show if overusing social media has a lasting effect.

About Gavin Stanley

I am a sophomore at FHSU, I graduated from Hodgeman County High School in 2020. I am currently working to get my bachelor's in Informatics with a concentration in computer networking & telecommunications. In my free time, I enjoy watching sports, playing video games, and hanging out with friends.

4 thoughts on “Harmful Affects of Social Media on Teens

  1. Your review was well written, thorough and a good summary of the information from the article. I like that you had a visual in your review, but it was too small to see well. This was a good choice of an article and it was very interesting to read. I think it the effects of social media is greatly disregarded by most people. It would be awesome to see this study done on older adolescents as well as adults.

  2. I wonder what the results would be like for a group in their 20s. I liked your point on why this study was important to you. I think that anymore when it comes to discussions of social media and mental health, most people (in my experience this advice comes from generations who didn’t grow up with social media) give the advice to just put your phone down or whatever. The truth is that young people use social media heavily and it isn’t going anywhere. I agree with you about seeing more studies on physical effects and how well intervention programs and such work because I feel like that hasn’t really been studied.

  3. The effect of social media on mental health is such a tricky subject. Much like culture at-large, the only inherent draw to social media is that it’s never in the same state for very long. Being addicted to it can be worse sometimes rather than others. In the grand scheme of social media’s history, it’s correlation with mental health can therefore be abused. It’s very real, but it’s tricky to measure. Even academic research doesn’t paint the full picture because there is no way to render it experimental. Social media is so ubiquitous that “control groups” probably have more factors at-play (such as poor access to technology), and introducing social media as a “treatment” would have a vast spectrum of results given that everybody has a different set of interests.

    Perhaps that’s why I’m not terribly concerned about social media’s influence on health. Granted, I am a female with low self-esteem who probably uses social media for 30 hours per week, but it’s not for vein reasons. I used it as a teenager to connect with other people who shared my hobbies, and given how niche my interests are, that would’ve been impossible otherwise. I’ve made great friends over social media as well. They’re a positive influence in my life and probably more responsible for my mental well-being than anything else online. Plus, in a place like Hungary, there are other factors at-play. The average Hungarian is probably less concerned with privileged hobbies; they’re probably more likely using social media to contextualize their illiberal government and terminal poverty. Those facts are certainly more depressive than social media as a tool in and of itself.

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