High Social Media Use among Adolescents Associated with Increased High-Risk Behaviors and Poor Academic Outcomes

Research Article

J Fam Med. 2022; 9(6): 1310.

High Social Media Use among Adolescents Associated with Increased High-Risk Behaviors and Poor Academic Outcomes

Yoders AM1,2*, Ray SA1,2, Quinn MA2, Phalen K3, Cabral MD4, Shrestha M4 and Wood D1

1Department of Pediatrics, Quillen College of Medicine, East Tennessee State University, USA

2Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, USA

3College of Arts and Sciences, East Tennessee State University, USA

4Department of Pediatrics and Adolescent Medicine, Western Michigan University Homer Stryker M.D. School of Medicine, USA

*Corresponding author: author: Yoders AM, Quillen College of Medicine and College of Public Health, East Tennessee State University; 325 N. State of Franklin, Johnson City, TN 37604, USA

Received: June 27, 2022; Accepted: September 07, 2022; Published: September 14, 2022

Abstract

Purpose: With the marked increase in social media apps over the last two decades and teens’ dramatic increase in screen time, research examining the impacts of social media on teenage health outcomes is urgently needed. The purpose of this study is to examine the relationship between adolescent social media use and high-risk behaviors (alcohol use, tobacco, vaping, sexual activity) and academic outcomes (ability to get good grades and complete homework).

Methods: 234 adolescents were recruited via convenience sampling at two suburban/rural clinics. A survey assessed hours of social media use, participation in high-risk behaviors, and impact on academic outcomes. Variables were recoded into bivariate categories and multiple logistic regressions were conducted using SPSS, controlling for age, gender, race, and insurance status.

Results: High users of social media (4+ hours/day) were 3.4 and 3.0 times more likely to use alcohol (p<0.05) and tobacco (p<0.01), respectively. Highusers were also 3.2 and 3.0 times more likely to report that their social media use impacted their ability to get good/acceptable grades (p<0.01) and complete homework (p<0.01), respectively.

Conclusions: High levels of social media use were associated with increased likelihood of alcohol and tobacco use and had a negative effect on youth’s academic performance. Screening of adolescent social media use will better identify youth at risk for potentially harmful effects of excess social media use, allowing providers to intervene with the proper education for youth and their guardians.

Keywords: Social media use, Alcohol use, Tobacco use, Academic performance

Introduction

In 2018, 95% of teenagers were found to have access to a smart phone, with 45% of teens saying they are online “almost constantly” [1]. With the marked increase in social media apps over the last two decades and teens’ dramatic increase in screen time, research examining the impacts of social media on teenage health outcomes is urgently needed. When determining media’s impact on adolescent high-risk behaviors, previous literature has looked specifically at the relationship between social media habits and use of a particular substance. Multiple studies found that the type of media consumed, whether used for professional or personal use, impacted the levels of substance use among youth [2,3]. Increases in high-risk behaviors such as alcohol use, [2,4-8] tobacco and vaping, [5,9,10] and sexual activity [11] were found to be associated with exposure to media related to that specific activity. However, there is more limited research looking at general, everyday social media use (posts from friends and families, influencers, or accounts already followed) and its impact on these high-risk behaviors. Furthermore, very little research has examined the relationship between social media use and school performance. A 2018 study found that higher social media use predicted a decrease in school performance, [12] but additional research is needed to understand this association.

The current study examined the relationships between overall time spent on social media (no specifications on media content) and four high-risk behaviors (alcohol use, vaping, tobacco use, and sexual activity) in a suburban/rural adolescent population. Additionally, the impact of social media use on academic performance is uniquely studied by assessing youth’s perception of their social media use on their own grades and homework completion. By studying a wide range of adolescent outcomes, this study can provide further information on the impact of social media use and inform interventions to mitigate the impact of excessive social media use.

Methods

This study was approved by the East Tennessee State University IRB through an expedited review. A convenience sample of 234 adolescents was recruited from pediatric clinics at East Tennessee State University Quillen College of Medicine and Western Michigan University Homer Stryker M.D. School of Medicine. Data were collected via a paper survey during regular healthcare visits. Caregiver consent and youth assent were required for participation. The survey used in this study was adapted from previously administered questionnaires. The independent variable of social media use was assessed using questions adapted from the “Common Sense Census: Media Use by Tweens and Teens”, conducted by Common Sense Media, [13] stating “If you had to guess, how many total hours per day do you spend on any form of social media?” Social media use was coded into low use (0-3 hours/day) and high use (4+ hours/ day). These categories were chosen due to Common Sense Media’s description of “light media users” spending an average of about 3.5 hours/day on media.

Outcome variables included high-risk behaviors and academic outcomes, such as the ability to complete homework and achieve good grades. Questions assessing youth participation in high-risk behaviors were adapted from the validated Center for Disease Control and Prevention’s (CDC) Youth Risk Behavior Survey [14] and included alcohol use, tobacco use, vaping, and sexual activity, with all coded as “ever used/ever engaged” or “not used/never engaged.” Finally, to assess the impact of the youth’s social media use on academic outcomes, each youth was asked “how often do social media keep you from doing the following: (1) completing homework, (2) making good/acceptable grades in school.” They responded using a 4-point categorical scale with options of “never,” “rarely,” “sometimes,” or “often.” These responses were coded into categories of “no effect” and “any effect” (included responses of rarely, sometimes, or often).

Co-variates of age, gender, race, and insurance status were included for regression analyses. Age was kept as a continuous variable (12-17 years old) for a majority of analyses. However, categories of younger teens (12-14 years old) and older teens (15-17 years old) were used for comparison. Gender included male and female. Due to the small number of participants who identified as ‘non-binary’ or ‘prefer not to say,’ those participants were removed from the regression analyses. Race was coded into “White” and “Non-White” (Black or African American, Hispanic or Latinx, Native American or American Indian, Asian/Pacific Islander, or Other) due to the large majority of participants who identified as “White.” Insurance status, used as proxy for income level, was coded as “Medicaid” or “not Medicaid.”Survey data were entered into RED Cap and all analyses were completed using SPSS version 26.

Descriptive statistics were conducted and included frequencies, percentages, means, and standard deviations, where appropriate, for each variable. A series of regression analyses were completed to determine if social media use was independently associated with youth health outcomes. First, simple binomial logistic regressions were completed between social media use and each of the dependent variables. Then, multiple logistic regressions were completed to determine the most predictive model of the primary predictor, social media use, the covariates, and each dependent variable. The final multiple regression model, including odds ratios and confidence intervals, are reported.

Results

Demographic Information

Frequencies of demographic information of youth participants are presented in (Table 1). A majority of participating youth (78.6%) are high-school aged (14-17 years old). There was almost equal participation of male and female youth, with predominantly White participants (73.6%), followed by Hispanic or Latinx participants (12.1%) and Black or African American participants (8.2%). The remaining categories of race made up smaller percentages: Native American or American Indian (2.2%), Asian/Pacific Islander (1.3%), other (2.6%). 74% of participants reported Medicaid insurance, a metric for lower socioeconomic status.

Table 1: Demographic Information (n = 234).










  


    
Variable


    
n (%)


  


  


    
Gender


    

  


  


    
Male


    
114 (48.7%)


  


  


    
Female


    
120 (51.3%)


  


  


    
Race


    

  


  


    
White


    
172 (73.6%)


  


  


    
Black or    African American


    
19 (8.2%)


  


  


    
Hispanic    or Latinx


    
29 (12.1%)


  


  


    
Native    American or American Indian


    
5 (2.2%)


  


  


    
Asian/Pacific    Islander


    
3 (1.3%)


  


  


    
Other


    
6 (2.6%)


  


  


    
Age


    

  


  


    
12 years    old


    
17 (7.3%)


  


  


    
13 years    old


    
33 (14.2%)


  


  


    
14 years    old


    
48 (20.3%)


  


  


    
15 years    old


    
52 (22.0%)


  


  


    
16 years    old


    
43 (18.5%)


  


  


    
17 years    old


    
41 (17.7%)


  


  


    
Insurance Status


    

  


  


    
Medicaid


    
172 (73.7%)


  


  


    
Non-Medicaid


    
62 (26.3%)


  


















Table 1: Demographic Information (n = 234).

Variable Frequencies

Table 2 shows the frequency of the independent and dependent variables. Close to 40% of youth reported high social media use (4+ hours/day). Among the various social media platforms, Youtube was found to be the most highly used with 87% of participants reporting use at least every other day, if not more frequently. Youtube was followed by Instagram (67%), Snapchat (63%), and TikTok (55%) as the most frequently used platforms. For the high-risk behaviors, 17.8%, 17.0%, 23.5%, and 22.0% reported any alcohol use, smoking, vaping, and sexual activity, respectively. With academic outcomes, more than 45% of participants reported that social media affected their ability to complete homework and more than 33% reported it affected their ability to get good grades.

Table 2: Measures of Social Media Use and Dependent Variables (n = 234).










  


    
Variable


    
n (%)


  


  


    
Social Media (SM) Use by Time


    

  


  


    
Low (0-3    hr/day)


    
141 (60.2%)


  


  


    
High (4+    hr/day)


    
93 (39.8%)


  


  


    
Social Media (SM) Use by Platform


    

  


  


    
Youtube


    
204 (87.2%)


  


  


    
Instagram


    
156 (66.7%)


  


  


    
Snapchat


    
147 (62.8%)


  


  


    
TikTok


    
128 (54.7%)


  


  


    
Facebook


    
75 (32.0%)


  


  


    
Twitter


    
48 (20.5%)


  


  


    
Other, not    listed


    
73 (31.2%)


  


  


    
Alcohol Use


    

  


  


    
None


    
192 (82.2%)


  


  


    
Any


    
42 (17.8%)


  


  


    
Smoking


    

  


  


    
None


    
194 (83.0%)


  


  


    
Any


    
40 (17.0%)


  


  


    
Vaping


    

  


  


    
None


    
179 (76.5%)


  


  


    
Any


    
55 (23.5%)


  


  


    
Sexual Activity


    

  


  


    
None


    
183 (78.0%)


  


  


    
Any


    
51 (22.0%)


  


  


    
Youth’s perception that SM Use affected their ability    to Complete Homework


    

  


  


    
No Effect


    
126 (53.7%)


  


  


    
Any Effect


    
108 (45.3%)


  


  


    
Youth’s perception that SM Use affected their ability    to Get Good Grades


    

  


  


    
No Effect


    
156 (66.8%)


  


  


    
Any Effect


    
78 (33.2%)


  


















Table 2: Measures of Social Media Use and Dependent Variables (n = 234).

Figure 1 outlines the breakdown of each demographic category among the high users of social media. 57% of high social media users identified as female; 63% were older teens (15-17 years old), 75% identified as white, and 78% had Medicaid insurance. None of these relationships were significant.

Figure 1: 


    


    

    


    


    Figure 1:

Simple Logistic Regression Analyses

Bivariate logistic regressions between social media use and highrisk behaviors and academic outcomes (ability to complete homework and make good grades) are presented in (Table 3). Compared to low social media users (0-3 hours/day), high social media users (4+ hours/ day) were 3.8 times more likely to report any alcohol use (p=0.006), 3.3 times more likely to report any smoking (p=0.016), and 2.5 times more likely to report any vaping (p=0.024). There was not a significant association between social media use and youth report of sexual activity. With academic outcomes, high social media users were 3.3 times more likely to report that their social media use affected their ability to complete homework (p=0.000) and 2.8 times more likely to report that their social media use affected their ability to get good grades (p=0.003) compared to low social media users.

Table 3: Bivariate logistic regression analyses between social media use and health outcomes (reference group = low [0-3 hr/night] social media use).










  


    
Dependent Variable


    
Odds Ratio


    
Lower Confidence Interval


    
Upper Confidence Interval


  


  


    
Alcohol    Use


    
3.78**


    
1.45


    
9.83


  


  


    
Smoking


    
3.29*


    
1.25


    
8.70


  


  


    
Vaping


    
2.49*


    
1.13


    
8.49


  


  


    
Sexual    Activity


    
2.21


    
0.97


    
5.02


  


  


    
Youth’s    perception that SM Use negatively affected their ability to Complete Homework


    
3.27**


    
1.71


    
6.23


  


  


    
Youth’s    perception that SM Use negatively affected their ability to Get Good Grades


    
2.78**


    
1.41


    
5.49


  


  


    
* p    <0.05 ; ** p < 0.01


  


















Table 3: Bivariate logistic regression analyses between social media use and

health outcomes (reference group = low [0-3 hr/night] social media use).

Multiple Logistic Regression Analyses

Multiple logistic regression analyses between social media use and high-risk behaviors and academic outcomes (ability to complete homework and make good grades), controlling by age, gender, race and insurance status, are presented in (Table 4). Using the backwards selection method, the strongest model for each dependent variable was created. Race and insurance status were removed from each model and not included in the final models due to non-significant findings. Gender was removed from all models except the model between social media use and sexual activity.

Table 4: Multiple logistic regression analyses between social media use and health outcomes controlling by age, gender, race and insurance status (STRONGEST MODEL).










  


    
Dependent Variable


    
Independent Variables and    Co-Variates


    
Odds Ratio


    
Lower Confidence Interval


    
Upper Confidence Interval


  


  


    
Alcohol    Use


    
Age


    
1.65**


    
1.14


    
2.38


  


  


    

    
Social Media Use


    
3.36*


    
1.24


    
9.07


  


  


    
Smoking


    
Age


    
1.57*


    
1.08


    
2.28


  


  


    

    
Social Media Use


    
2.96*


    
1.08


    
8.09


  


  


    
Vaping


    
Age


    
1.38*


    
1.04


    
1.83


  


  


    

    
Social Media Use


    
2.23


    
0.99


    
5.04


  


  


    
Sexual    Activity


    
Gender (ref: male)


    
2.60


    
0.99


    
6.81


  


  


    

    
Age


    
2.54**


    
1.67


    
3.87


  


  


    
Youth’s    perception that SM Use negatively affected their ability to Complete Homework


    
Social Media Use


    
3.20**


    
1.67


    
6.14


  


  


    
Youth’s    perception that SM Use negatively affected their ability to Get Good Grades


    
Age


    
0.77*


    
0.61


    
0.98


  


  


    

    
Social Media Use


    
3.03**


    
1.49


    
6.17


  


  


    
* p    <0.05 ; ** p < 0.01


    

    

  


















Table 4: Multiple logistic regression analyses between social media use and health outcomes controlling by age, gender, race and insurance status (STRONGEST

MODEL).

With alcohol use, smoking, and vaping, age, and social media remained in the strongest models. High social media users were 3.4 times more likely to report any alcohol use compared to low social media users when controlling for co-variates (p=0.017). Alcohol use was directly associated with age; older individuals were more likely to report alcohol use (p=0.008). High social media users were 3.0 times more likely to report any smoking compared to low social media users when controlling for co-variates (p=0.034). Smoking was directly associated with age; older individuals were more likely to report smoking (p=0.017). The association between vaping and social media was no longer significant when controlling for co-variates. However, vaping continued to be directly associated with age; older individuals were more likely to report vaping (p=0.025). Sexual activity was directly associated with age; older individuals were more likely to report engaging in sexual activity (p=0.000). Sexual activity remained non-significantly associated with social media use after controlling for co-variates.

All co-variates were removed from the strongest model in the relationship between social media use and youth report of social media affecting the ability to complete homework. When controlling for co-variates, high social media users remained 3.2 times more likely to report their social media use affected their ability to complete homework when compared to low social media users (p=0.000). Regarding the relationship between social media use and youth report of social media’s effect on getting good grades, all co-variates were removed from the strongest model except age. When controlling for co-variates, high social media users remained 3.0 times more likely to report their social media use affected their ability get good grades when compared to low social media users (p=0.002). Youth’s report of social media’s effect on getting good grades was indirectly associated with age; older individuals were less likely to report their social media use affected their ability to get good grades compared to younger individuals (p=0.030).

Discussion

Recently, Instagram and Facebook have made headlines as researchers found time spent on those apps negatively impacted the mental health and self-image of teenagers [15,16]. As social media has become more engrained in our society, especially in the lives of adolescents, determining the possible negative impacts on health has become essential. In this study of adolescents in two suburban/ rural clinics, high social media users were found to have significantly higher rates of both alcohol and tobacco use. High use of social media was also found to be associated with increased likelihood of vaping; however, this finding was of borderline significance when adjusted for demographic characteristics. These results highlight the negative impact social media, of any content and not just substance-specific content can have on youth’s early engagement in substance use. Moreover, this study also found that high users of social media were more likely to report that their social media use negatively affected their ability to complete homework or their ability to get good/ acceptable grades.

Recognizing the impact of substance use on adolescent development and outcomes, Healthy People 2030 have listed multiple objectives regarding the reduction of adolescent alcohol and drug use [17]. The emphasis on early intervention has resulted in increased screening for these high-risk behaviors during routine adolescent care using standardized instruments such as the CRAFFT [Car, Relax, Alone, Forget, Friends, Trouble] [18]. However, Healthy People 2030 provide no specific recommendations on screening for social media use. As this study reinforces the association between social media use and high-risk behaviors among adolescents, it is necessary to increase screening for and education about the risks of excessive social media use. Screening for social media use among middle-school and early high-school aged youth can help predict which youth may be at a greater risk for participating in these potentially harmful behaviors. Furthermore, gaining knowledge of the adolescent’s social media habits will allow providers to provide targeted education to both youth and their guardians regarding safe social media habits and the benefits of monitoring youth social media activity.

The screening and intervention regarding social media among adolescents become even more important when we take into account the data regarding academic outcomes. Youth’s self-assessment of social media’s impact on their schoolwork is negative. Despite acknowledging that their social media use is problematic and interfering with their academic performance, youth continue to spend large amounts of their days on these apps. Incorporating screening into well-child checks would allow clinicians to identity youth whose social media use puts them at risk for academic problems and open the door for education on the potential risks of excess social media use.

The American Academy of Pediatrics released a policy guideline recommending no more than two hours of media time for children and teenagers [19]. 54% of the participants in this study reported using more than two hours of social media per day, not even accounting for other types of media like television or video games. This level of excess use re-emphasizes the need for adequate education to youth and their guardians. The AAP recommends developing a Family Media Plan which can personalize the situation and take into account the needs of each individual and the family as a whole [20]. By helping families create this plan, physicians can work together with guardians and adolescents in limiting the negative impacts of social media overuse.

This study had several strengths such as youth’s own assessment of their social media use on academic outcomes, the use of validated questions for high-risk behaviors, and a large pediatric sample size from two suburban/rural clinics which increases the generalizability to similar pediatric populations. There were also several limitations. First, the study utilized a convenience sampling technique; however, the refusal rate was extremely low (<5%), reducing the likelihood of selection bias. Second, due to the cross-sectional nature of the study, causal relationships could not be established. Finally, the use of youth self-report could be biased by youth’s underestimation of social media use, its impact on their academic performance, or in reporting high-risk behaviors.

In a discussion on social media, it would be remiss to not also acknowledge the addictive nature social media can have on its users. Recent literature has found that social media use among adolescents and young adults can reach an addictive level, comparable to the addiction of substances like alcohol, vaping, and marijuana [21-24]. While validated measures have been developed for the screening of various substance use and addictions (National Survey on Drug Use and Health [NSDUH] or CRAFFT), there is no validated screening tool for social media use or its potential addiction. It is possible that the screening tools previously used for substance use could be adapted and applied to social media use. Future studies can further examine the addictive potential of social media, develop validated screening tools to better equip providers in assessing youth social media use, and create interventions and educational material for youth and their guardians regarding safe and healthy social media practices.

In summary, we found that excessive social media use of any kind was strongly associated with an increased likelihood of initiating use of alcohol and tobacco use, as well as negatively impacting academic performance. We recommend that adolescents be screened for their use of social media at well-child visits, incorporating it as another “S” in the HEADDSS survey.

Conclusion

High use of social media can be associated with adolescent alcohol and tobacco use, as well as poor academic outcomes like getting good grades or completing homework. Screening for social media use during adolescent well-child checks can help identity at-risk youth and allow providers to educate and intervene regarding excessive and unhealthy social media use.

References

  1. Anderson, M., Jiang, J. Pew Res. 2018, May 20. http://assets.pewresearch. org/wpcontent/uploads/sites/14/2018/05/31102617/PI_2018.05.31_ TeensTech_FINAL.pdf
  2. Borzekowski DLG, Ross CS, Jernigan DH, DeJong W, Siegel M. Patterns of Media Use and Alcohol Brand Consumption Among Underage Drinking Youth in the United States. Journal of Health Communication. 2015; 20: 314- 320.
  3. Ilakkuvan V, Johnson A, Villanti AC, Evans WD, Turner M. Patterns of Social Media Use and Their Relationship to Health Risks Among Young Adults. The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 2019; 64: 158-164.
  4. Smout A, Chapman C, Mather M, Slade T, Teesson M, Newton N. It’s the Content That Counts: Longitudinal Associations between Social Media Use, Parental Monitoring, and Alcohol Use in an Australian Sample of Adolescents Aged 13 to 16 Years. International Journal of Environmental Research and Public Health. 2021; 18: 7599.
  5. Iannotti RJ, Kogan MD, Janssen I, Boyce WF. Patterns of adolescent physical activity, screen-based media use, and positive and negative health indicators in the U.S. and Canada. The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 2009; 44: 493-499.
  6. Fat LN, Cable N, Kelly Y. Associations between social media usage and alcohol use among youths and young adults: findings from Understanding Society. Addiction. 2021; 116: 2995-3005.
  7. Moreno MA, Whitehill JM. Influence of Social Media on Alcohol Use in Adolescents and Young Adults. Alcohol Research : Current Reviews. 2014; 36: 91-100.
  8. Riehm KE, Thrul J, Barrington-Trimis JL, Kelleghan A, Mojtabai R, Leventhal AM. Prospective Association of Digital Media Use with Alcohol Use Initiation and Progression Among Adolescents. Alcoholism, clinical and experimental research. 2021; 45: 877-885.
  9. Cavazos-Rehg P, Li X, Kasson E, Kaiser N, Borodovsky JT, Grucza R, et al. Exploring how social media exposure and interactions are associated with ENDS and tobacco use in adolescents from the PATH study. Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco. 2020; 23: 487-494.
  10. Vogel EA, Ramo DE, Rubinstein ML, Delucchi KL, Darrow SM, Costello C, et al. Effects of Social Media on Adolescents' Willingness and Intention to Use E-Cigarettes: An Experimental Investigation. Nicotine & tobacco research: official journal of the Society for Research on Nicotine and Tobacco. 2020; 23: 694-701.
  11. Gazendam N, Cleverley K, King N, Pickett W, Phillips SP. Individual and social determinants of early sexual activity: A study of gender-based differences using the 2018 Canadian Health Behaviour in School-aged Children Study (HBSC). PLoS ONE. 2020; 15: e0238515.
  12. Eijnden RVD, Koning I, Doornwaard S, Gurp FV, Bogt TT. The impact of heavy and disordered use of games and social media on adolescents’ psychological, social, and school functioning. Journal of Behavioral Addictions. 2018; 7: 697-706.
  13. Common Sense Media. The Common Sense Census: Media Use by Tweens and Teens. 2015.
  14. Brener ND, Kann L, Shanklin S, Kinchen S, Eaton DK, Hawkins J, et al. Methodology of the Youth Risk Behavior Surveillance System--2013. MMWR. Recommendations and reports : Morbidity and mortality weekly report. Recommendations and reports. 2013; 62: 1-20.
  15. Isaac, M., Frenkel, S., Mac, R. Facebook Struggles to Quell Uproar Over Instagram's Effect on Teens. The New York Times. Published online 2021.
  16. Wells G, Horwitz J, Seetharaman D. Facebook Knows Instagram Is Toxic for Teen Girls, Company Documents Show. The Wall Street Journal. Published online 2021.
  17. Drug and Alcohol Use - Healthy People 2030. health.gov. https://health.gov/ healthypeople/objectives-and-data/browse-objectives/drug-and-alcohol-use
  18. Knight, J. Car, Relax, Alone, Forget, Friends, Trouble - CRAFFT. Center for Adolescent Behavioral Health Research. https://njaap.org/wp-content/ uploads/2018/03/COMBINED-CRAFFT-2.1-Self-Admin_Clinician-Interview_ Risk-Assess-Guide.pdf
  19. Strasburger VC, Hogan M, Mulligan DA, Ameenuddin N, Christakis DA, Cross C, et al. Children, Adolescents, and the Media. Pediatrics. 2013; 132: 958-961.
  20. American Academy of Pediatrics. Family Media Plan. healthychildren.org. Published online.
  21. Kuss DJ, Griffiths MD. Social Networking Sites and Addiction: Ten Lessons Learned. International Journal of Environmental Research and Public Health. 2017; 14: 311.
  22. Kuss DJ, Griffiths MD. Online Social Networking and Addiction—A Review of the Psychological Literature. International Journal of Environmental Research and Public Health. 2011; 8: 3528-3552.
  23. Pontes HM, Taylor M, Stavropoulos V. Beyond "Facebook Addiction": The Role of Cognitive-Related Factors and Psychiatric Distress in Social Networking Site Addiction. Cyberpsychology, behavior and social networking. 2018; 21: 240-247.
  24. Kim H, Schlicht R, Schardt M, Florack A. The contributions of social comparison to social network site addiction. PLoS One. 2021; 16.

Citation:Yoders AM, Ray SA, Quinn MA, Phalen K, Cabral MD, Shrestha M, et al. High Social Media Use among Adolescents Associated with Increased High-Risk Behaviors and Poor Academic Outcomes. J Fam Med. 2022; 9(6): 1310.