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ALGORITHMS, ADDICTION, AND ADOLESCENT MENTAL HEALTH: An Interdisciplinary Study to Inform State-level Policy Action to Protect Youth from the Dangers of Social Media
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A recent Wall Street Journal investigation revealed that TikTok floods child and adolescent users with videos of rapid weight loss methods, including tips on how to consume less than 300 calories a day and promoting a "corpse bride diet," showing emaciated girls with protruding bones. The investigation involved the creation of a dozen automated accounts registered as 13-year-olds and revealed that TikTok algorithms fed adolescents tens of thousands of weight-loss videos within just a few weeks of joining the platform. Emerging research indicates that these practices extend well beyond TikTok to other social media platforms that engage millions of U.S. youth on a daily basis.Social media algorithms that push extreme content to vulnerable youth are linked to an increase in mental health problems for adolescents, including poor body image, eating disorders, and suicidality. Policy measures must be taken to curb this harmful practice. The Strategic Training Initiative for the Prevention of Eating Disorders (STRIPED), a research program based at the Harvard T.H. Chan School of Public Health and Boston Children's Hospital, has assembled a diverse team of scholars, including experts in public health, neuroscience, health economics, and law with specialization in First Amendment law, to study the harmful effects of social media algorithms, identify the economic incentives that drive social media companies to use them, and develop strategies that can be pursued to regulate social media platforms' use of algorithms. For our study, we have examined a critical mass of public health and neuroscience research demonstrating mental health harms to youth. We have conducted a groundbreaking economic study showing nearly $11 billion in advertising revenue is generated annually by social media platforms through advertisements targeted at users 0 to 17 years old, thus incentivizing platforms to continue their harmful practices. We have also examined legal strategies to address the regulation of social media platforms by conducting reviews of federal and state legal precedent and consulting with stakeholders in business regulation, technology, and federal and state government.While nationally the issue is being scrutinized by Congress and the Federal Trade Commission, quicker and more effective legal strategies that would survive constitutional scrutiny may be implemented by states, such as the Age Appropriate Design Code Act recently adopted in California, which sets standards that online services likely to be accessed by children must follow. Another avenue for regulation may be through states mandating that social media platforms submit to algorithm risk audits conducted by independent third parties and publicly disclose the results. Furthermore, Section 230 of the federal Communications Decency Act, which has long shielded social media platforms from liability for wrongful acts, may be circumvented if it is proven that social media companies share advertising revenues with content providers posting illegal or harmful content.Our research team's public health and economic findings combined with our legal analysis and resulting recommendations, provide innovative and viable policy actions that state lawmakers and attorneys general can take to protect youth from the harms of dangerous social media algorithms.
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AI-driven social media algorithms are designed solely to capture attention for profit without prioritizing ethical concerns, personalizing content, and enhancing user engagement by continuously tailoring feeds to individual preferences.
“AI-driven social media algorithms are designed solely to capture our attention for profit without prioritizing ethical concerns, personalizing content, and enhancing user engagement by continuously tailoring feeds to individual preferences.”
From Social Media Algorithms and Teen Addiction: Neurophysiological Impact and Ethical Considerations (2025) · cites this paper as [18]
The section on social media effects says algorithms populate individualized feeds with content that keeps users engaged, and that platforms monetize users’ time and attention. The Introduction says advertising profits give platforms little incentive to moderate harmful practices. These passages support the engagement-and-profit point, but not the absolute claim that algorithms are designed solely for that purpose or that ethical concerns are never prioritized; page numbers were not available in our copy. (LLM, conf=0.84)
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MethodMaheux, A. J., Roberts, S. R., Nesi, J., Widman, L., & Choukas‐Bradley, S. (2022) · Journal of Adolescence · doi:10.1002/jad.12009 · Cited by 52 · cited 1×
“89 Results of these experimental study designs and longitudinal cohort study designs provide rigorous evidence linking high amounts of social media use, and time spent on image-based social media in particular, to mental health harms in young users.”
BackgroundRaffoul, A., Ward, Z. J., Santoso, M., Kavanaugh, J. R., & Austin, S. B. (2023) · PLoS ONE · doi:10.1371/journal.pone.0295337 · Cited by 40
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“25 Algorithmic curation plays a central role in determining what information becomes visible, amplified, and repeatedly encountered by users.”
InfluentialCastro, J. C. (2025) · Springer eBooks · doi:10.1007/978-3-031-83541-4_1
Ruscio, J., & Abaci, J. (2025) · Springer eBooks · doi:10.1007/978-3-031-82640-5_7
Youth and Screens: Frequently Asked Questions in Pediatric Practice
Hutson, E. (2025) · Journal of Psychosocial Nursing and Mental Health Services · doi:10.3928/02793695-20250905-02
Edukacja medialna w rodzinie w erze sztucznej inteligencji: wyzwania i zagrożenia
Kloch, J., & Przybysz, M. (2025) · Family Forum · doi:10.25167/ff/6016
The Institutional Stack: Realigning U.S. AI GovernancePreprint
Khan, M. S., Khan, M. S., Poyer, A. T., et al. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6295671
Keum, B. T., Wang, F., Ofei, L. M., Wong, M. J., Oh, H. Y., & Volpe, V. V. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1745978 · Cited by 1
“Integrating DSMM with Carter’s (62) Race-Based Traumatic Stress Model, 51 Conservation of Resources Theory, and emerging perspectives in digital media psychology (52) allows us to articulate what we term a Digital Susceptibility Hypothesis.”
Heard, E. M., Williams, C., Crawford, M., & Way, A. (2026) · Health Promotion Journal of Australia · doi:10.1002/hpja.70182
Minimierung toxischer Substanzen:
Sugden, S. G., & Betzler, F. (2026) · Nervenheilkunde · doi:10.1055/a-2839-0497
“Einsamkeit, Entfremdung, ein schlechtes Körperbild, Ess-störungen und Suizidalität bei Teenagern.”
Social Media Algorithms as Information IntermediariesPreprint
Drake, M. S., Koenraadt, J., Thornock, J. R., & Twedt, B. J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6731603
Luo, Z. (2026) · Media Literacy and Academic Research · doi:10.34135/mlar-26-01-01
Social and digital media use in children and adolescents: a perspective focused on risks
Domoff, S. E. (2026) · Frontiers in Developmental Psychology · doi:10.3389/fdpys.2026.1814457
Incel Identity Development: A Scoping Review of Biopsychosocial Markers
McGilvery, K., & Wiley, K. K. (2026) · Deviant Behavior · doi:10.1080/01639625.2026.2682351
Winstone, L., Parsonage, J. T. I., Muir, C., Randhawa, A., Cross, L., MacArthur, G., Asiedu-Addo, E., & Garavini, E. (2026) · Journal of Adolescence · doi:10.1002/jad.70231
“…clearer advertising disclosure, greater friction around repeated distressing content, safer defaults for younger users, reduced incentives for conflict amplification, and more visible tools for managing recommendations, consistent with emerging child‐centred design codes (Costello et al. 2023).”
InfluentialGroover, M. G., & Searight, H. R. (2026) · Open Journal of Depression · doi:10.4236/ojd.2026.153004
Dergaa, I., Chalghaf, N., Razzak, M., Muntean, R. I., Ștefănică, V., & Ceylan, H. İ. (2026) · JMIR Mental Health · doi:10.2196/98200
Mistareehi, H., Dronavalli, M., & Yarali, A. (2026) · AI and Ethics · doi:10.1007/s43681-026-01305-x
“Costello et al. [ 5 ] provide an interdisciplinary legal and public-health analysis of platform incentives and youth mental-health risks, while Weirauch et al. [6 ] synthesize platform and policy recommendations and identify persistent transparency and governance gaps.”
Higgs, J., Kaimana, M., & Isero, M. (2026) · Journal of the Learning Sciences · doi:10.1080/10508406.2026.2686084
The institutional stack: Realigning U.S. AI governance
Khan, M. S., Poyer, A., & Khan, M. J. (2026) · Telecommunications Policy · doi:10.1016/j.telpol.2026.103294
Halsall, T., Holmgren, A., Arseneau, Z., Jan, M., Khanna, N., Obeid, N., Þórisdóttir, I. E., Zenone, M., Cheng, M., & Bellefeuille, A. (2026) · Discover Public Health · doi:10.1186/s12982-026-02589-4
Online Diagnosis of Mental Illness: The Impact of Network Information on Cognition
Yao, X. (2026) · SHS Web of Conferences · doi:10.1051/shsconf/202623604005
“They use algorithms to push content that can attract users' continuous attention in users' personal information flow, so that users can remain active for a long time [6].”
Uzbay, T. (2026) · Journal of Public Health Policy · doi:10.1057/s41271-026-00662-5
subaşı, S., & Çakır, R. (2026) · Participatory Educational Research · doi:10.17275/per.26.71.13.5
Kritika, E. (2026) · International Journal of Digital Law and Governance · doi:10.1515/ijdlg-2026-0011
“…in adolescents suggest some important frontiers to be explored urgently and actively because of the sudden and swift development of technology and its possible in fl uence on well-being (Chakraborty et al. 2024; Costello et al. 2023; Ognibene et al. 2023; Torous et al. 2021; Shen et al. 2025).”
Evidence for Social Media Legislation Strategies
Nagata, J. M., Nayak, S., Huang, O. H., Li, E. J., Wong, J. H., Memon, Z., Zhang, S., Brindis, C. D., & Moreno, M. A. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.26965
Fatt, S. J., Shen, Y., Griffiths, S., & Fardouly, J. (2026) · Body Image · doi:10.1016/j.bodyim.2026.102190
Moravec, V., Gavurová, B., Rigelský, M., & Miovský, M. (2026) · Depression and Anxiety · doi:10.1155/da/3938343
Metadata
- Authors
- Costello, N., Sutton, R., Jones, M., Almassian, M., Raffoul, A., Ojumu, O., Salvia, M., Santoso, M., Kavanaugh, J. R., & Austin, S. B.
- Affiliations
- Michigan State University (US)
- Harvard University (US)
- Stanford University (US)
- Corresponding author
- Costello, Nancy
- Venue
- American Journal of Law & Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023-07
- Volume
- 49
- Issue
- 2-3
- Pages
- 135-172
- ISSN
- 0098-8588 (ISSN-L)
- 2375-835X
- OpenAlex
- W4391762088
- Cited by
- 54
- References
- 13
- Citations by year
- 2026: 31 · 2025: 20 · 2024: 3
- FWCI
- 23.16
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Law & Medicine (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Knowledge Commons (Lakehead University)
- Funders
- Canadian Institutes of Health Research (MFE- 171217)
- Maternal and Child Health Bureau (T76‐MC‐00001, MC00001)
- Institute of Population and Public Health (MFE‐171217)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Social Sciences › Communication › Digital Media and Philosophy
- Keywords
- social media algorithms, adolescent mental health, TikTok, eating disorders, body image, suicidality, platform regulation, state policy, Section 230, First Amendment, platform liability, child online safety
- MeSH terms
- Adolescent, Advertising, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Mental Health, Policy, Interdisciplinary Studies, Social Media
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