Artificial intelligence (AI) in efforts to prevent teenage suicide: literature review

Muhammad Imron Rosadi(1*), Tahratul Yovalwan(2), Akmal Zaki Asaduddin(3)


(1) Master of Nursing Universitas Muhammadiyah Yogyakarta
(2) Master of Nursing Universitas Muhammadiyah Yogyakarta
(3) Master of Nursing Universitas Muhammadiyah Yogyakarta
(*) Corresponding Author

Abstract


Suicide is a highly complex mental health issue that is a leading cause of death and requires efforts to reduce the number of victims. In the modern technology era, the utilization of artificial intelligence (AI) is seen as a suicide prevention initiative and presents a significant challenge in global prevention efforts. This literature review aims to determine the use of Artificial Intelligence (AI) in efforts to prevent teenage suicide. The research method utilizes the PRISMA guidelines. This literature review employs a systematic approach and selection process. Literature sources were searched from Proquest, PubMed, Google Scholar, and Scopus databases. Out of the 7 reviewed articles, 2 were from South Korea, 2 from the United States, and the remaining 3 were from Spain, Italy, and Canada. The Cohort research design was the most prevalent in this literature review (N = 5), and one study used an RCT design (N = 1), while a Cross-Sectional research design was employed in one study (N = 1). Overall, it indicates that AI is capable of predicting suicide risk and preventing suicide. The results of the literature review indicate that the use of AI technology has benefits in preventing teenage suicide.

Keywords


Artificial Intelligent; Suicide; Adolescent

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References


Lejeune A, Le Glaz A, Perron P-A, Sebti J, Baca-Garcia E, Walter M, et al. Artificial intelligence and suicide prevention: A systematic review. European Psychiatry 2022;65. https://doi.org/10.1192/j.eurpsy.2022.8.

WHO. Suicide worldwide in 2019: Global Health estimates. 2019.

Ardi S. Kementerian Kesehatan Ungkap Kasus Bunuh Diri Meningkat Hingga 826 Kasus. 2023. https://ugm.ac.id/id/berita/kementerian-kesehatan-ungkap-kasus-bunuh-diri-meningkat-hingga-826-kasus/. (accessed November 6, 2023).

PHO. World Suicide Prevention Day 2022 2022. https://www.paho.org/en/campaigns/world-suicide-prevention-day-2022#:~:text=World%20Suicide%20Prevention%20Day%20(WSPD,focus%20attention%20on%20suicide%20prevention. (accessed November 6, 2023).

Hughes JL, Horowitz LM, Ackerman JP, Adrian MC, Campo J V., Bridge JA. Suicide in young people: screening, risk assessment, and intervention. BMJ 2023. https://doi.org/10.1136/bmj-2022-070630.

Bernert RA, Hilberg AM, Melia R, Kim JP, Shah NH, Abnousi F. Artificial intelligence and suicide prevention: A systematic review of machine learning investigations. Int J Environ Res Public Health 2020;17:1–25. https://doi.org/10.3390/ijerph17165929.

Bersia M, Koumantakis E, Berchialla P, Charrier L, Ricotti A, Grimaldi P, et al. Suicide spectrum among young people during the COVID-19 pandemic: A systematic review and meta-analysis. EClinicalMedicine 2022;54. https://doi.org/10.1016/j.eclinm.2022.101705.

Putri FNR, Riyono J. Teknologi artificial intellegence dalam upaya pencegahan bunuh diri. metrik serial humaniora dan sains 2022;3:10–8.

Rawat B, Singh Bist A, Fakhrezzy M, Dinda Octavyra R. AI Based Assistance to Reduce Suicidal Tendency Among Youngsters. APTISI Transactions on Management (ATM) 2023;7:102–9. https://doi.org/10.34306.

Bhandarkar AR, Arya N, Lin KK, North F, Duvall MJ, Miller NE, et al. Building a Natural Language Processing Artificial Intelligence to Predict Suicide-Related Events Based on Patient Portal Message Data. Mayo Clinic Proceedings: Digital Health 2023;1:510–8. https://doi.org/https://doi.org/10.1016/j.mcpdig.2023.09.001.

Srinivansan S, Harnett NG, Zhang L, Dahlgren MK, Jang J, Lu S, et al. Unravelling psychiatric heterogeneity and predicting suicide attempts in women with trauma-related dissociation using artificial intelligence. Eur J Psychotraumatol 2022;13. https://doi.org/10.1080/20008066.2022.2143693.

Choi SB, Lee W, Yoon J-H, Won J-U, Kim DW. Ten-year prediction of suicide death using Cox regression and machine learning in a nationwide retrospective cohort study in South Korea. J Affect Disord 2018;231:8–14. https://doi.org/https://doi.org/10.1016/j.jad.2018.01.019.

Servi M, Chiaro S, Mussi E, Castellini G, Mereu A, Volpe Y, et al. Statistical and artificial intelligence techniques to identify risk factors for suicide in children and adolescents. Sci Prog 2023;106. https://doi.org/10.1177/00368504231199663.

Ryu S, Lee H, Lee DK, Kim SW, Kim CE. Detection of suicide attempters among suicide ideators using machine learning. Psychiatry Investig 2019;16:588–93. https://doi.org/10.30773/pi.2019.06.19.

Shahidi F, Rennert-May E, D’Souza AG, Crocker A, Faris P, Leal J. Machine learning risk estimation and prediction of death in continuing care facilities using administrative data. Sci Rep 2023;13. https://doi.org/10.1038/s41598-023-43943-9.

Morales-Rodríguez FM, Martínez-Ramón JP, Giménez-Lozano JM, Morales Rodríguez AM. Suicide Risk Analysis and Psycho-Emotional Risk Factors Using an Artificial Neural Network System. Healthcare (Switzerland) 2023;11. https://doi.org/10.3390/healthcare11162337.

D’Hotman D, Loh E. AI enabled suicide prediction tools: A qualitative narrative review. BMJ Health Care Inform 2020;27. https://doi.org/10.1136/bmjhci-2020-100175.

Rebelo AD, Verboom DE, dos Santos NR, de Graaf JW. The impact of artificial intelligence on the tasks of mental healthcare workers: A scoping review. Computers in Human Behavior: Artificial Humans 2023;1:100008. https://doi.org/https://doi.org/10.1016/j.chbah.2023.100008.


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DOI: https://doi.org/10.26714/mki.7.1.2024.53-61

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