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