Psychology draft assignment
THE INFLUENCE OF SOCIAL MEDIA ADDICTION ON MENTAL HEALTH OUTCOMES
OF YOUNG ADULTS: A NARRATIVE REVIEW
Student Name
Saint Leo University
Month, Year
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Abstract
The rise of problematic social media use in recent years has been associated with a decline in
mental health. Social media use becomes problematic when users engage impulsively and
excessively with various platforms despite the potentially destructive consequences. This
decline in mental health has prompted researchers to explore the connection between social
media use and an individual’s well-being. The purpose of this narrative review is to explore
evidence for the influence of problematic social media use on the increased prevalence of
mental health outcomes based on the synthesis of qualifying empirical studies conducted
between 2017 and 2023. At this stage of the review, problematic social media use will be
generally defined as the overuse of social media in association with mental health symptoms,
such as stress, depression, and anxiety. For each mental health outcome or indicator, the analysis
will assess the theoretical foundations of the studies and the strength, direction, and consistency
of the association of mental health symptoms to social media use.
Keywords: social media addiction, problematic social media use, fear of missing out,
passive social media use
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Introduction
This narrative review seeks to explore evidence for the influence of problematic social
media use on the increased prevalence of mental health outcomes, specifically in young adults. It
is the goal of this review to direct future studies that may inform policy and practice. This review
will examine the relationship between mental health and problematic social media use.
Technology has transformed how individuals conduct their daily lives. Education,
entertainment, shopping, banking, and communication have all been impacted by the integration
of technology. Of these, communication may offer one of the most significant impacts on
modern society. Communication has changed substantially with the introduction of social media.
Creating a healthy balance between online lives and reality has become a challenge for many
young people (Sheridan, 2015). While there may be advantages to social media use to promote
mental health, numerous researchers suggest that additional studies and potential interventions
are needed to provide support and educate individuals about the possible dangers and negative
consequences of problematic social media use.
Martin et al. (2018) found that social media is a significant infiltrator of modern society,
as it pervades most aspects of our world today. Other studies have shown that there is a
significant relationship between the overuse or misuse of social media and adverse mental health
outcomes for young people (Barry et al., 2017; Martin et al., 2018; O’Reilly, 2020). One
illustration of this negative outcome is the link between social media use and body image
concerns (Barry et al., 2017). Other studies have explored social comparison (Barry et al., 2017),
and the Fear of Missing Out (O’Reilly, 2020). FOMO is exasperated when individuals discover
that they may have been intentionally excluded from events and may experience increased
feelings of seclusion, inadequacy, and loneliness. All of which may result in heightened issues
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with self-esteem (Salomon & Brown, 2019). Finally, researchers are discovering a connection
between social media and a rise in various depressive symptoms (Barry et al., 2017; O’Reilly,
2020; O’Reilly et al., 2019; Tiggermann & Slater, 2017).
The biopsychosocial model is one theoretical framework that aligns with the concepts in
this review. According to Greenfield (2018), the biopsychosocial model for behavioral addiction
may present an outline for possible treatment for this increasing mental health challenge. As
problematic social media has evolved into an addictive perception that is closely related to
traditional substance and behavior addictions, the biopsychosocial model of addiction may offer
guidance on therapeutic interventions (Greenfield, 2018). This narrative review seeks to assist in
the exploration of the correlation between the impact of problematic social media use and the
impact of access to social media and the neurobiological conditioning created through
smartphone applications (Greenfield, 2018).
Method
EBSCO, ERIC, PsycArticles, and JSTOR will be used for searches for qualified studies
published from January 2017 to the present. Searches will use the following terms: “Problematic
Social Media Use and (mental health OR anxiety OR Stress OR depression OR FOMO OR
college students OR well-being OR self-esteem).” Other terms that will be included are “social
media addiction” and “nomophobia.”
Screening
The following sub-sections include the inclusion and exclusion criteria for this review.
Additionally, contained within this section are the search terms and databases utilized for the
review. The screening section will conclude with a description of the population of interest for
this narrative review.
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Inclusion Criteria
Studies included in this review will have the following eligibility criteria:
• Participants must be between the ages of 16 and 30 and taking college courses
• There must be a measurement of problematic social media use
• The outcomes must include validated assessments of negative mental health outcomes
• Studies must be peer-reviewed, published in the last five years, in full-text, and accessible in
English
Exclusion Criteria
Studies excluded from this review include research with participants under the age of 16 or
over the age of 30. Additionally, this review will exclude studies conducted before 2016. Finally,
studies not included in this review include those that are non-English or not offered in English
text.
Search Databases and Search Terms
At this initial stage of the review, there are approximately 30 articles under review.
Quality Evaluation
The quality evaluation for this narrative review will include measures that are reliable
and valid, with all experimental designs internally valid and correlational methods analyzed
appropriately.
Population of Interest
For this review, the population of interest will include individuals who are any gender
and from varying ethnicities who are between the ages of 16 and 30. Additionally, this
population will either self-report problematic social media use or have been evaluated through
validated assessments. Finally, the population will have also reported mental health issues.
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Review
Organize the review in logical sections with structured headings. Results can be arranged
by indicating the proportion of studies that support aspects of your research question in the
affirmative (or, if more studies suggest findings do not align with your expectations, report in
terms of how many did NOT find xyz). This section will describe a narrative version of your box
score
Problematic Social Media Use
This section (social media addiction and daily time of social media usage - Durak &
Seferoğlu, 2019)
Attachments to Social Media
This section (five archetypes - Altuwairiqi et al., 2019), (scale used to determine social
media addiction - Şahin, 2018), (impact on daily life - Zahrai et al., 2022)
Passive Social Media Use
This section (PSMU (passive social media use) depression symptoms - Aalbers et al.,
2019)
Characteristics of Addiction
This section…
Anxiety and Social Media Use
This section…
Depression and Social Media Use
This section (problematic social media use and depression - Shannon et al., 2022),
(Increase SM and Increase Depression – Lin et al, 2016), (Envy – Wang, 2020)
Social Media and Self-Esteem
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This section (Envy – Wang, 2020) (Barry et al., 2017)
Social Media and FOMO
This section (FOMO, social comparison, and stalking are directly associated with fatigue
– Tandon, 2021) (O’Reilly, 2020)
Generational Cohorts’ Social Media Use
This section…
Social Media and Gender
Effects on Gender
This section (Increase SM and Increase Depression (gender) – ( Lin et al., 2016),
Marriage quality (Wang, 2020)
Limitations
Limitations include the inability to obtain articles for free or articles that are not eaily
attained through the library database.
Conclusion
Problematic social media use is found in many studies to correlate with an increase in
negative mental health outcomes. Findings may include an increase in negative self-esteem,
anxiety, depression, and ssssssssss. There may also be in increase in the Fear of Missing Out
(FOMO) and negative impacts on important friend and familial relationships. This review seeks
to better understand the relationship between problematic or addictive social media use and the
increase inegativeve health outcomes for young adults.
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References
Aalbers, G., McNally, R. J., Heeren, A., de Wit, S., & Fried, E. I. (2019). Social media and
depression symptoms: A network perspective. Journal of Experimental Psychology.
General, 148(8), 1454-1462. https://doi.org/10.1037/xge0000528
Altuwairiqi, M., Jiang, N., & Ali, R. (2019). Problematic attachment to social media: Five
behavioural archetypes. International Journal of Environmental Research and Public
Health, 16(12), 2136. https://doi.org/10.3390/ijerph16122136
Barry, C. T., Sidoti, C. L., Briggs, S. M., Reiter, S. R., & Lindsey, R. A. (2017). Adolescent
social media use and mental health from adolescent and parent perspectives. Journal of
Adolescence, 61, 1-11. doi:10.1016/j.adolescence.2017.08.005
Durak, H., & Seferoğlu, S. (2019). Modeling of variables related to problematic social media
usage: Social desirability tendency example. Scandinavian Journal of Psychology, 60(3),
277–288. https://doi.org/10.1111/sjop.12530
Lin, L. y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., Hoffman, B. L., Giles,
L. M., & Primack, B. A. (2016). Research article: Social media and depression. Depression
and Anxiety, 33(4), 323-331. https://doi.org/10.1002/da.22466
Liu, Z., Wang, X., & Chen, J. (2021). Why can’t I stop using social media problematically? the
impact of Norm and neutralization from the Regulatory Focus Perspective. International
Journal of Electronic Commerce, 25(2), 204–229.
https://doi.org/10.1080/10864415.2021.1887698
Martin, F., Wang, C., Petty, T., Wang, W., & Wilkins, P. (2018). Middle school students’ social
media use. Educational Technology & Society, 21(1), 213-224
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O’Reilly, M. (2020). Social media and adolescent health: The good, the bad, and the ugly.
Journal of Mental Health, 29(2), 200-206. doi:10.1080/09638237.2020.1714007
O’Reilly, M., Dogra, N., Hughes, J., Reilly, P., George, R., & Whiteman, N. (2019). Potential of
social media in promoting mental health in adolescents. Health Promotion International,
34(5), 981-991. doi:10.1093/heapro/day056
Şahin, C. (2018). Social Media Addiction Scale--Student form. The Turkish Online Journal of
Educational Technology, 17(1). https://doi.org/10.1037/t72756-000
Shannon, H., Bush, K., Villeneuve, P. J., Hellemans, K. G. C., & Guimond, S. (2022).
Problematic social media use in adolescents and young adults: Systematic review and
meta-analysis. JMIR Mental Health, 9(4). https://doi.org/10.2196/33450
Sheridan, P. M. (2015). “Tracking off-campus speech: Can public schools monitor students’
social media?” Southern Law Review, 25(1), 57-76
Tandon, A., Dhir, A., Talwar, S., Kaur, P., & Mäntymäki, M. (2021). Dark consequences of
social media-induced fear of missing out (FoMO): Social media stalking, comparisons, and
fatigue. Technological Forecasting & Social Change, 171, 120931.
https://doi.org/10.1016/j.techfore.2021.120931
Tiggemann, M., & Slater, A. (2017). Facebook and body image concern in adolescent girls: A
prospective study. International Journal of Eating Disorders, 50(1), 80-83.
doi:10.1002/eat.22640
Zahrai, K., Veer, E., Ballantine, P. W., de Vries, H. P., & Prayag, G. (2022). Either you control
social media or social media controls you: Understanding the impact of self‐control on
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excessive social media use from the dual‐system perspective. Journal of Consumer Affairs,
56(2), 806–848. https://doi.org/10.1111/joca.12449
Researcher Subjects Methods/IVs DVs Outcomes Impact of social media on mental health outcomes
Altuwairiqi et al., 2019 51 adult social media users who self-declared problematic attachment to social media
Qualitative phase: diary notes collected via Evernote, focus groups Quantitative phase: Chi- squared behavior archetypes transferred to numerical form
The Internal characteristics variable (PIVPERC), Positive emotions variable (PPOSPERC), Negative emotions variable (PNEGPERC), and Psychological states variable (PPSYPERC)
Researchers developed a set of five behavioral archetypes to represent users with problematic attachments to social media. These archetypes are Secure, Intimate, Escapist, Narcissist, and Discrepancy.
Şahin, 2018 998 students from 12 to 22 years of age
Quantitative Kaiser- Meyer-Olkin (KMO) coefficient and the Bartlett Sphericity test (exploratory factor analysis)
Different states related to social media use
Scale can be used to determine social media addictions of students, aged 12-22 years - Validity and reliability studies of the scale can be repeated in different sample groups and other age ranges
Zahrai et al., 2022 389 adults aged 18–44 years who spend more than 2 h daily on social media
Cross-sectional study, both implicit and explicit measurements combined in a strictly scheduled order to avoid any possible carryover effects (self-control, implicit attitude, impulsive and excessive social media use)
Negative impact of social media on daily life
Excessive users are driven more by their implicit attitudes rather than explicit beliefs in consuming social media, self-control has no significant influence on excessive users with a positive implicit attitude and high impulsive social media use
Liu et al., 2022 346 Chinese full-time students
Survey: Harman’s single- factor analysis (age, gender, habit, perceived usefulness of social media, and
Intention to reduce problematic social media use
Researchers developed a theoretical model to understand how to reduce problematic use, results show that both injunctive norms and neutralization have significant
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preference for online social interaction)
effects on guilt, which in turn increases intention to reduce problematic use
Shannon et al., 2022 18 studies were identified, with a total of 9269 participants in our review and included in the meta- analysis – Problematic social media use
A systematic search to identify studies in adolescents and young adults
Mental Health Outcomes (depression, stress, and anxiety)
Moderate but statistically significant correlations between problematic social media use and depression
Durak & Seferoğlu, 2019 580 undergraduate or graduate students in different state universities in Turkey.
Quantitative: structural equation modeling through Online Surveys: Social Media Disorder Scale (SMDS), Social Network Sites Usage Scale, Liebowitz Social Anxiety Scale, UCLA Loneliness Scale, Social Desirability Scale – social media use purposes
Problematic Social Media Use
There was a positive relationship between social media addiction and daily time of social media usage, recognition and publicity of social media, frequency of use for communication and loneliness, whereas there was a negative relationship with the frequency of using it for education.
Aalbers et al., 2019 125 students reported PSMU (passive social media use), depression symptoms, and stress 7 times daily for 14 days.
Multilevel vector autoregressive time-series models were used to estimate (a) contemporaneous, (b) temporal, and (c) between-subjects associations among these variables.
Passive social media use and depression symptoms and stress
(a) More time spent on PSMU was associated with higher levels of interest loss, concentration problems, fatigue, and loneliness. (b) Fatigue and loneliness predicted PSMU across time, but PSMU predicted neither depression symptoms nor stress. (c) Mean PSMU levels were positively correlated with several depression symptoms (e.g., depressed mood and feeling inferior)
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Lin et al., 2016 1,787 adults ages 19 to 32 were surveyed about SM use and depression
Chi-squared tests and ordered logistic regressions were performed with sample weights
Increase SM and Increase Depression (gender)
SM use was significantly associated with increased depression. Given the proliferation of SM, identifying the mechanisms and direction of this association is critical for informing interventions that address SM use and depression
Want et al., 2020 514 Chinese married adults (62% female) were recruited from 26 regions in China.
Cronbach’s α of a six-item questionnaire was 0.76. (effect of envy)
Marital quality and depression
High marriage quality can protect married adults from the adverse effects of upward social comparison on mobile social media.
Tandon et al., 2021 321 social media users from the United Kingdom 18-25 years of age
multivariate analysis and hetero-trait–mono-trait (HTMT) analysis to explore FOMO and fatigue
FOMO and: SM stalking, SM fatigue, SM envy, frequent posting
FOMO, social comparison, and stalking are directly associated with fatigue