International Peer-Reviewed Journal•Open Access•ISSN 2456-8880
irejournals@gmail.com•+91-7433024337

Home / Current Issue / Paper 1706900

1706900 Vol 8 · Issue 7 Download Paper

Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education

Akinboyejo Asimolowo

Subject area: Science,Engineering and Technology  ·  Area of research: AI Driven Mental Health Support System

Abstract

This article examines the financial implications and economic benefits of implementing AI-driven mental health support systems in public schools. As student mental health challenges continue to rise, traditional support mechanisms often fall short due to resource constraints and high costs. This study explores how AI technologies can bridge these gaps, offering early detection, counseling, and intervention capabilities that contribute to a more comprehensive mental health strategy. Key findings indicate that AI integration can substantially reduce costs related to crisis intervention. Also, AI-driven support enhances academic performance, contributing to higher graduation rates and improved long-term economic prospects. These systems also contribute to broader societal costs associated with untreated mental health issues, such as unemployment and healthcare burdens. By strategically investing in AI solutions, policymakers can ensure immediate educational benefits with an enduring societal and economic growth, effectively creating the need for regulatory frameworks that address data security and ethical concerns.

Keywords

AI mental health, public education, financial implications, crisis intervention, academic performance, societal benefits, early intervention, data security.

References

[1] Alhuwaydi AM. (2024). Exploring the Role of Artificial Intelligence in Mental Healthcare: Current Trends and Future Directions - A Narrative Review for a Comprehensive Insight. Risk Manag Healthc Policy. 2024 May 21;17:1339-1348. doi: 10.2147/RMHP.S461562. PMID: 38799612; PMCID: PMC11127648.

[2] Alsayed, Sana'A & Assayed, Suha & Alkhatib, Manar & Shaalan, Khaled. (2024). Impact of Artificial Intelligence Chatbots on Student Well-being and Mental Health: A Systematic Review. People and Behavior Analysis. Vol. 2. 10.31098/pba.v2i2.2411

[3] American Academy of Pediatrics. (2024). HIPAA and FERPA basics. Retrieved from https://www.aap.org/en/patient-care/school-health/hipaa-and-ferpa-basics/

[4] Ananyi, Solomon & SOMIEARI-PEPPLE, Eucharia. (2023). COST-BENEFIT ANALYSIS OF ARTIFICIAL INTELLIGENCE INTEGRATION IN EDUCATION MANAGEMENT: LEADERSHIP PERSPECTIVES. 4. 353-370.

[5] Barna Group. (2024). Parents' perspectives on AI. Retrieved from https://www.barna.com/research/parents-ai/

[6] Bernard Marr. (2023). Opportunities And Challenges In Developing Intelligent Digital Therapies. https://www.forbes.com/sites/bernardmarr/2023/07/06/ai-in-mental-health-opportunities-and-challenges-in-developing-intelligent-digital-therapies/

[7] Carolyn J. Heinrich, Ann Colomer, Matthew Hieronimus. (2023). Minding the gap: Evidence, implementation and funding gaps in mental health services delivery for school-aged children. Children and Youth Services Review, Volume 150, 107023, ISSN 0190-7409. https://doi.org/10.1016/j.childyouth.2023.107023.

[8] Colizzi, M., Lasalvia, A. & Ruggeri, M. (2020). Prevention and early intervention in youth mental health: is it time for a multidisciplinary and trans-diagnostic model for care?. Int J Ment Health Syst 14, 23 (2020). https://doi.org/10.1186/s13033-020-00356-9

[9] Daniele, K., Gambacorti Passerini, M. B., Palmieri, C., & Zannini, L. (2022). Educational interventions to promote adolescents’ mental health: A scoping review. Health Education Journal, 81(5), 597-613. https://doi.org/10.1177/00178969221105359

[10] Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee Branstetter, Emma Brunskill, Kenneth R. Koedinger (2023). Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. https://arxiv.org/abs/2312.11274?utm_source=chatgpt.com

[11] David Nagel. (2023). AI to Experience Massive Growth in Education. https://thejournal.com/articles/2023/01/12/ai-to-experience-massive-growth-in-education.aspx

[12] David B. Olawade, Ojima Z. Wada, Aderonke Odetayo, Aanuoluwapo Clement David-Olawade, Fiyinfoluwa Asaolu, Judith Eberhardt. (2024). Enhancing mental health with Artificial Intelligence: Current trends and future prospects. Journal of Medicine, Surgery, and Public Health, Volume 3, 100099, ISSN 2949-916X. https://doi.org/10.1016/j.glmedi.2024.100099.

[13] Emily Berger, Andrea Reupert, Kelly-Ann Allen, Timothy Colin Heath Campbell (2022). A systematic review of the long-term benefits of school mental health and wellbeing interventions for students in Australia. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2022.986391/full

[14] European Parliament. (2020). Artificial intelligence in healthcare: Applications, risks, and ethical and societal impacts. Retrieved from https://www.europarl.europa.eu/RegData/etudes/STUD/2020/641530/EPRS_STU(2020)641530_EN.pdf

[15] Frazier T, Doyle Fosco SL. Nurturing positive mental health and wellbeing in educational settings - the PRICES model. Front Public Health. 2024 Jan 19;11:1287532. doi: 10.3389/fpubh.2023.1287532. PMID: 38312141; PMCID: PMC10834646.

[16] Gaggle. (2022). Mooresville Graded School District: Digital Safety Sentry. Retrieved from https://www.gaggle.net/case-studies/mooresville-graded-school-district

[17] Gaggle. (2022). North Carolina school districts can now request state funding to cover Gaggle safety management costs. Retrieved from https://news.gaggle.net/north-carolina-funding

[18] Gartner. (2023). Forecast Analysis: Artificial Intelligence Software, 2023-2027, Worldwide. Retrieved from https://www.gartner.com/en/documents/4916331

[19] Haque MDR, Rubya S. (2023). An Overview of Chatbot-Based Mobile Mental Health Apps: Insights From App Description and User Reviews. JMIR Mhealth Uhealth. 2023 May 22;11:e44838. doi: 10.2196/44838. PMID: 37213181; PMCID: PMC10242473.

[20] Insight Into Diversity. (2024). Funding expands student access to mental health services. Retrieved from https://www.insightintodiversity.com/funding-expands-student-access-to-mental-health-services/

[21] Jansen, S.N.G., Kamphorst, B.A., Mulder, B.C. et al. (2024). Ethics of early detection of disease risk factors: A scoping review. BMC Med Ethics 25, 25 (2024). https://doi.org/10.1186/s12910-024-01012-4

[22] Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, 15(16), 12451. https://doi.org/10.3390/su151612451

[23] Karen A. Rodriguez. (2020). Examining the Efficacy of a School-Based Mental Health Program in Iowa. https://scholarworks.waldenu.edu/dissertations

[24] Kazandjian M, Neylon K. (2024). Innovative Uses of Technology to Enhance Access to Services Within the Crisis Continuum. Publication No. PEP24-01-022. Rockville, MD: Substance Abuse and Mental Health Services Administration. https://store.samhsa.gov/sites/default/files/tacc-uses-technology-pep24-01-022.pdf

[25] Knapp M, Wong G. (2020). Economics and mental health: the current scenario. World Psychiatry. 2020 Feb;19(1):3-14. doi: 10.1002/wps.20692. PMID: 31922693; PMCID: PMC6953559.

[26] Huang Lan. (2023). Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers. 16. 2577-2587. 10.15354/sief.23.re202.

[27] Le LK, Esturas AC, Mihalopoulos C, Chiotelis O, Bucholc J, Chatterton ML, Engel L. (2021). Cost-effectiveness evidence of mental health prevention and promotion interventions: A systematic review of economic evaluations. PLoS Med. 2021 May 11;18(5):e1003606. doi: 10.1371/journal.pmed.1003606. PMID: 33974641; PMCID: PMC8148329.

[28] Levin, H.M., McEwan, P.J. (2003). Cost-Effectiveness Analysis as an Evaluation Tool. In: Kellaghan, T., Stufflebeam, D.L. (eds) International Handbook of Educational Evaluation. Kluwer International Handbooks of Education, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0309-4_10

[29] Linda Uchenna Oghenekaro & Christopher Obinna Okoro. (2024). Artificial Intelligence-Based Chatbot for Student Mental Health Support. https://www.scirp.org/journal/paperinformation?paperid=133222

[30] Mental Health Services Oversight & Accountability Commission. (2023). Mental Health Services Oversight & Accountability Commission (MHSOAC). Retrieved from https://www.mhsoac.ca.gov/

[31] Mongelli F, Georgakopoulos P, Pato MT. (2020). Challenges and Opportunities to Meet the Mental Health Needs of Underserved and Disenfranchised Populations in the United States. Focus (Am Psychiatr Publ). 2020 Jan;18(1):16-24. doi: 10.1176/appi.focus.20190028. Epub 2020 Jan 24. PMID: 32047393; PMCID: PMC7011222.

[32] Nadia Tamez-Robledo. (2024). Why Schools Still Struggle to Provide Enough Mental Health Resources for Students.

[33] Nazari A, Garmaroudi G, Foroushani AR, Hosseinnia M. The effect of web-based educational interventions on mental health literacy, stigma and help-seeking intentions/attitudes in young people: systematic review and meta-analysis. BMC Psychiatry. 2023 Sep 4;23(1):647. doi: 10.1186/s12888-023-05143-7. PMID: 37667229; PMCID: PMC10478184.

[34] Norori N, Hu Q, Aellen FM, Faraci FD, Tzovara A. Addressing bias in big data and AI for health care: A call for open science. Patterns (N Y). 2021 Oct 8;2(10):100347. doi: 10.1016/j.patter.2021.100347. PMID: 34693373; PMCID: PMC8515002.

[35] North State Journal. (2022, June 13). 67 districts in North Carolina are using a program that monitors student email accounts. Retrieved from https://nsjonline.com/article/2022/06/67-districts-in-north-carolina-are-using-a-program-that-monitors-student-email-accounts/

[36] Oseremi Onesi-Ozigagun, Yinka James Ololade, Nsisong Louis Eyo-Udo & Damilola Oluwaseun Ogundipe. (2024). REVOLUTIONIZING EDUCATION THROUGH AI: A COMPREHENSIVE REVIEW OF ENHANCING LEARNING EXPERIENCES. International Journal of Applied Research in Social Sciences P-ISSN: 2706-9176, E-ISSN: 2706-9184 Volume 6, Issue 4, P.No. 589-607, DOI: 10.51594/ijarss.v6i4.1011

[37] Prisca Ugomma Uwaoma, Tobechukwu Francisa Eleogu, Franciscamary Okonkwo, Oluwatoyin Ajoke Farayola, Simon Kaggwa, Abiodun Akinoso. (2023). AI’s Role in Sustainable Business Practices and Environmental Management. International Journal of Research and Scientific Innovation. ISSN 2321-2705. DOI: https://doi.org/10.51244/IJRSI.2023.1012029

[38] Reva Schwartz, Apostol Vassilev, Kristen Greene, Lori Perine, Andrew Burt,0 Patrick Hall. (2022). Towards a Standard for Identifying and Managing Bias in Artificial Intelligence https://doi.org/10.6028/NIST.SP.1270

[39] Stacey L. Bevan, Caroline C. DeWitt. (2024). Policy and practice innovations in school-based mental health services. Children and Youth Services Review, Volume 166, 107970, ISSN 0190-7409. https://doi.org/10.1016/j.childyouth.2024.107970.

[40] Taylor HL, Menachemi N, Gilbert A, Chaudhary J, Blackburn J. (2023). Economic Burden Associated With Untreated Mental Illness in Indiana. JAMA Health Forum.2023;4(10):e233535. doi:10.1001/jamahealthforum.2023.3535

[41] United Nations Children's Fund (UNICEF). (2023). The benefits of investing in school-based mental health support. Retrieved from https://www.unicef.org/reports/benefits-investing-school-based-mental-health-support

[42] Vivek Yadav (2021). AI and Economics of Mental Health: Analyzing how AI can be used to improve the cost-effectiveness of mental health treatments and interventions. Journal of Scientific and Engineering Research, 2021, 8(7):274-284 ISSN: 2394-2630

[43] Wilberforce Murikah, Jeff Kimanga Nthenge, Faith Mueni Musyoka. (2024). Bias and ethics of AI systems applied in auditing - A systematic review. Scientific African, Volume 25, e02281, ISSN 2468-2276. https://doi.org/10.1016/j.sciaf.2024.e02281.

[44] Wolff J, Pauling J, Keck A, Baumbach J. (2020). The Economic Impact of Artificial Intelligence in Health Care: Systematic Review. J Med Internet Res 2020;22(2):e16866. doi: 10.2196/1686

[45] World Health Organization 2024. https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health

[46] World Health Organization 2022 https://www.who.int/news-room/fact-sheets/detail/mental-disorders

[47] Yong, S.E.F., Wong, M.L. & Voo, T.C. (2022). Screening is not always healthy: an ethical analysis of health screening packages in Singapore. BMC Med Ethics 23, 57 (2022). https://doi.org/10.1186/s12910-022-00798-5

[48] Zając, T., Perales, F., Tomaszewski, W. et al. (2024). Student mental health and dropout from higher education: an analysis of Australian administrative data. High Educ 87, 325–343 (2024). https://doi.org/10.1007/s10734-023-01009-9

[49] Zhou Tian, Deng Yi. (2024). Application of artificial intelligence based on sensor networks in student mental health support system and crisis prediction. Measurement: Sensors, Volume 32, 101056, ISSN 2665-9174. https://doi.org/10.1016/j.measen.2024.101056.

How to cite this paper

Akinboyejo Asimolowo "Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education" Iconic Research And Engineering Journals Volume 8 Issue 7 2025 Page 206-216
Akinboyejo Asimolowo "Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education" Iconic Research And Engineering Journals, vol. 8, no. 7, Jan. 2025
Akinboyejo Asimolowo (2025). Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education. Iconic Research And Engineering Journals, 8(7).
Akinboyejo Asimolowo "Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education" Iconic Research And Engineering Journals, vol. 8, no. 7, Jan. 2025.
@article{1706900,
      author = {Akinboyejo Asimolowo},
      title = {Economic Impact Analysis: Cost-Benefit Assessment of AI-Driven Mental Health Support Systems in Public Education},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {7},
      pages = {206-216},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706900.pdf},
      abstract = {This article examines the financial implications and economic benefits of implementing AI-driven mental health support systems in public schools. As student mental health challenges continue to rise, traditional support mechanisms often fall short due to resource constraints and high costs. This study explores how AI technologies can bridge these gaps, offering early detection, counseling, and intervention capabilities that contribute to a more comprehensive mental health strategy. Key findings indicate that AI integration can substantially reduce costs related to crisis intervention. Also, AI-driven support enhances academic performance, contributing to higher graduation rates and improved long-term economic prospects. These systems also contribute to broader societal costs associated with untreated mental health issues, such as unemployment and healthcare burdens. By strategically investing in AI solutions, policymakers can ensure immediate educational benefits with an enduring societal and economic growth, effectively creating the need for regulatory frameworks that address data security and ethical concerns.},
      keywords = {AI mental health, public education, financial implications, crisis intervention, academic performance, societal benefits, early intervention, data security.},
      month = {January},
  }