Understanding the Impact of Social Media on Mental Health in Autistic Youth and Expanding Access to Culturally Responsive Behavioral Health Services in Underserved Communities

Authors

  • Ayowole Samuel Ajiboye Jack, Joseph and Morton Mandel School of Applied Social Sciences, Case Western Reserve University, Cleveland, Ohio, USA Author
  • Tahir Kolawole Balogun Department of Political Science, Villanova University, Villanova, Philadelphia, USA Author
  • Paul Okugo Imoh Department of Medicine, Swansea University Wales United Kingdom Author
  • Amina Catherine Ijiga Department of Political Science (International Relations), Federal University of Lafia, Nasarawa State. Nigeria Author
  • Toyosi Motilola Olola Department of Communications, University of North Dakota, Grand Forks, USA Author
  • Emmanuel Oluwasayomi Ahmadu Department of Applied Sciences in Human Services, Cuyahoga Community College, Cleveland, Ohio, USA Author

DOI:

https://doi.org/10.32628/IJSRHSS25234

Keywords:

Autism Spectrum Disorder (ASD), Neurodevelopmental Disorders, Social Communication Deficits, Comorbid Mental Health Conditions, Prevalence in Children

Abstract

Autistic youth face an elevated risk of mental health disorders, with emerging evidence linking excessive social media use to heightened psychological distress. This review investigates how digital engagement intersects with systemic inequities to impact the mental health of autistic adolescents in underserved communities. Drawing on a convergent mixed-methods design, the study integrates psychometric data, digital behavior metrics, and stakeholder narratives to examine the nuanced effects of platform-specific social media usage, cultural stigma, and behavioral health access disparities. Findings reveal that increased engagement with algorithm-driven platforms like TikTok and Instagram correlates with higher anxiety and depression scores, particularly in youth from low socioeconomic and racially/ethnically marginalized backgrounds. Concurrently, structural barriers—including cultural incongruence, geographic isolation, and limited provider diversity—significantly reduce access to autism-informed behavioral health services. Gender-diverse and non-binary autistic individuals report the highest psychological distress, further emphasizing the need for intersectional frameworks. The analysis also shows that culturally inclusive interventions, digital literacy programs, and community awareness campaigns markedly improve service utilization and reduce therapy dropout rates. These results underscore the critical need for adaptive, neurodiversity-affirming mental health strategies that integrate digital risk management and culturally responsive care. The study advocates for co-designed interventions leveraging telehealth, ethical AI tools, and community-based literacy initiatives to promote psychological resilience in autistic youth navigating digital ecosystems and systemic marginalization.

Downloads

Download data is not yet available.

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).

Andrilla, C. H. A., Patterson, D. G., Garberson, L. A., Coulthard, C., & Larson, E. H. (2018). Geographic variation in the supply of selected behavioral health providers. American Journal of Preventive Medicine, 54(6, Supplement 3), S199–S207. https://doi.org/10.1016/j.amepre.2018.01.004

Balogun, T. K., Enyejo, J. O., Ahmadu, E. O., Akpovino, C. U., Olola, T. M., & Oloba, B. L. (2024). The Psychological Toll of Nuclear Proliferation and Mass Shootings in the US and How Mental Health Advocacy Can Balance National Security with Civil Liberties. IRE Journals, 8(4), 011-036.

Bird, G., & Cook, R. (2013). Mixed emotions: The contribution of alexithymia to the emotional symptoms of autism. Translational Psychiatry, 3(7), e285. https://doi.org/10.1038/tp.2013.61

Boyd, D. (2014). It's complicated: The social lives of networked teens. Yale University Press.

Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications.

Broder-Fingert, S., Shui, A., Pulcini, C. D., Kurowski, D., & Perrin, J. M. (2017). Racial and ethnic differences in subspecialty service use by children with autism. Pediatrics, 140(3), e20170955. https://doi.org/10.1542/peds.2017-0955

Broder-Fingert, S., Turchi, R. M., & Dosreis, S. (2020). Leveraging implementation science to advance equitable care for underserved children with autism spectrum disorder. Pediatrics, 145(Supplement 1), S53–S59. https://doi.org/10.1542/peds.2019-1895E

Centers for Disease Control and Prevention. (2023). Autism spectrum disorder (ASD): Data & statistics. https://www.cdc.gov/ncbddd/autism/data.html

Charmaz, K. (2014). Constructing grounded theory (2nd ed.). Sage Publications.

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.

Darko, D., Kwekutsu, E., & Idoko, I. P. (2025). Synergistic Effects of Phytochemicals in Combating Chronic Diseases with Insights into Molecular Mechanisms and Nutraceutical Development.

Gaye, A., Victor Bamigwojo, O., Idoko, I. P., & Fatai Adeoye, A. (2025). Modeling Hepatitis B Virus Transmission Dynamics Using Atangana Fractional Order Network Approach: A Review of Mathematical and Epidemiological Perspectives. International Journal of Innovative Science and Research Technology, 10(4), 41-51.

Gillespie-Lynch, K., Kapp, S. K., Brooks, P. J., Pickens, J., & Schwartzman, B. (2017). Whose expertise is it? Evidence for autistic adults as critical autism experts. Frontiers in Psychology, 8, 438. https://doi.org/10.3389/fpsyg.2017.00438

Hollocks, M. J., Lerh, J. W., Magiati, I., Meiser-Stedman, R., & Brugha, T. S. (2019). Anxiety and depression in adults with autism spectrum disorder: A systematic review and meta-analysis. Psychological Medicine, 49(4), 559–572. https://doi.org/10.1017/S0033291718002283

Hong, J. S., Kim, H. Y., & Lee, M. H. (2020). Social media use and depression in adolescents with autism spectrum disorder: The mediating role of social comparison. Journal of Adolescence, 83, 14–22. https://doi.org/10.1016/j.adolescence.2020.07.009

Idoko, I. P., David-Olusa, A., Badu, S. G., Okereke, E. K., Agaba, J. A., & Bashiru, O. (2024). The dual impact of AI and renewable energy in enhancing medicine for better diagnostics, drug discovery, and public health. Magna Scientia Advanced Biology and Pharmacy, 12(2), 99-127.

IJIGA, A. C., BALOGUN, T. K., SARIKI, A. M., KLU, E., AHMADU, E. O., & OLOLA, T. M. (2024). Investigating the Influence of Domestic and International Factors on Youth Mental Health and Suicide Prevention in Societies at Risk of Autocratization.

Ijiga, A. C., Balogun, T. K., Ahmadu, E. O., Klu, E., Olola, T. M., & Addo, G. (2024). The role of the United States in shaping youth mental health advocacy and suicide prevention through foreign policy and media in conflict zones. Magna Scientia Advanced Research and Reviews, 12(01), 202-218.

Ijiga, A. C., Peace, A. E., Idoko, I. P., Agbo, D. O., Harry, K. D., Ezebuka, C. I., & Ukatu, I. E. (2024). Ethical considerations in implementing generative AI for healthcare supply chain optimization: A cross-country analysis across India, the United Kingdom, and the United States of America. International Journal of Biological and Pharmaceutical Sciences Archive, 7(01), 048-063.

Ijiga, A. C., Peace, A. E., Idoko, I. P., Ezebuka, C. I., Harry, K. D., Ukatu, I. E., & Agbo, D. O. (2024). Technological innovations in mitigating winter health challenges in New York City, USA. International Journal of Science and Research Archive, 11(01), 535-551.

Kapp, S. K. (2020). Autistic community and the neurodiversity movement: Stories from the frontline. Springer.

Kerns, C. M., Kendall, P. C., Zickgraf, H., Franklin, M. E., Miller, J., & Herrington, J. (2014). Not to be overshadowed or overlooked: Functional impairments associated with comorbid anxiety disorders in youth with ASD. Behavior Therapy, 46(1), 29–39. https://doi.org/10.1016/j.beth.2014.03.005

Kinnaird, E., Stewart, C., & Tchanturia, K. (2019). Investigating alexithymia in autism: A systematic review and meta-analysis. European Psychiatry, 55, 80–89. https://doi.org/10.1016/j.eurpsy.2018.09.004

Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.

Lai, M. C., Kassee, C., Besney, R., Bonato, S., Hull, L., Mandy, W., & Szatmari, P. (2019). Prevalence of co-occurring mental health diagnoses in the autism population: A systematic review and meta-analysis. The Lancet Psychiatry, 6(10), 819–829. https://doi.org/10.1016/S2215-0366(19)30289-5

Magaña, S., Parish, S. L., Rose, R. A., Timberlake, M., & Swaine, J. G. (2015). Racial and ethnic disparities in quality of health care among children with autism and other developmental disabilities. Intellectual and Developmental Disabilities, 53(3), 161–172. https://doi.org/10.1352/1934-9556-53.3.161

Mandell, D. S., Wiggins, L. D., Carpenter, L. A., Daniels, J., DiGuiseppi, C., Durkin, M. S., ... & Kirby, R. S. (2009). Racial/ethnic disparities in the identification of children with autism spectrum disorders. American Journal of Public Health, 99(3), 493–498. https://doi.org/10.2105/AJPH.2007.131243

Marino, C., Gini, G., Vieno, A., & Spada, M. M. (2018). A comprehensive meta-analysis on problematic Facebook use. Computers in Human Behavior, 83, 262–277. https://doi.org/10.1016/j.chb.2018.02.009

Mazurek, M. O. (2013). Social media use among adults with autism spectrum disorders. Computers in Human Behavior, 29(4), 1709–1714. https://doi.org/10.1016/j.chb.2013.02.004

Metzl, J. M., & Hansen, H. (2014). Structural competency: Theorizing a new medical engagement with stigma and inequality. Social Science & Medicine, 103, 126–133. https://doi.org/10.1016/j.socscimed.2013.06.032

Nicolaidis, C., Raymaker, D., McDonald, K., Lund, E., Leotti, S., Kapp, S. K., & Boisclair, W. C. (2015). Comparison of healthcare experiences in autistic and non-autistic adults: A cross-sectional online survey facilitated by an academic-community partnership. Journal of General Internal Medicine, 30(8), 1105–1113. https://doi.org/10.1007/s11606-015-3244-9

Pew Research Center. (2022). Teens, social media and technology 2022. https://www.pewresearch.org/internet/2022/08/10/teens-social-media-and-technology-2022/

Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008). Psychiatric disorders in children with autism spectrum disorders: Prevalence, comorbidity, and associated factors in a population-derived sample. Journal of the American Academy of Child and Adolescent Psychiatry, 47(8), 921–929. https://doi.org/10.1097/CHI.0b013e318179964f

Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092

Whitney, D. G., & Peterson, M. D. (2019). US national and state-level prevalence of mental health disorders and disparities of mental health care use in children. JAMA Pediatrics, 173(4), 389–391. https://doi.org/10.1001/jamapediatrics.2018.5399

World Health Organization. (2022). Autism. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders

Zuckerman, K. E., Lindly, O. J., Reyes, N. M., Chavez, A. E., Macias, K., & Smith, K. N. (2017). Disparities in diagnosis and treatment of autism in Latino and non-Latino White families. Pediatrics, 139(5), e20163010. https://doi.org/10.1542/peds.2016-3010

Hong, M., Lee, S., Park, S., & Oh, I.-H. (2020). Prevalence and economic burden of autism spectrum disorder in South Korea using national health insurance data from 2008 to 2015. Journal of Autism and Developmental Disorders, 50(4), 1401–1410. https://doi.org/10.1007/s10803-019-04255-y

Downloads

Published

15-05-2025

Issue

Section

Research Articles

How to Cite

Understanding the Impact of Social Media on Mental Health in Autistic Youth and Expanding Access to Culturally Responsive Behavioral Health Services in Underserved Communities. (2025). International Journal of Scientific Research in Humanities and Social Sciences, 2(3), 33-56. https://doi.org/10.32628/IJSRHSS25234

Similar Articles

1-10 of 19

You may also start an advanced similarity search for this article.