Chatbot dalam Deteksi Kesehatan Mental : Tinjauan Literatur

DOI: https://doi.org/10.33650/trilogi.v6i1.10888

Authors (s)


(1)  Bunga Nur Indah Dewi   (Universitas Pendidikan Indonesia)  
        Indonesia
(2)  Maulana Achmad   (Universitas Pendidikan Indonesia)  
        Indonesia
(3) * Nurul Assyfa   (Universitas Pendidikan Indonesia)  
        Indonesia
(4)  Renalda Dhava Sanggara   (Universitas Pendidikan Indonesia)  
        Indonesia
(5)  Ressa Julliyana   (Universitas Pendidikan Indonesia)  
        Indonesia
(6)  Satria Rifqi Farhan   (Universitas Pendidikan Indonesia)  
        Indonesia
(7)  Nunung Siti Sukaesih   (Universitas Pendidikan Indonesia)  
        Indonesia
(*) Corresponding Author

Abstract


Background: The development of Artificial Intelligence (AI) technology in the healthcare sector has advanced rapidly and made a significant contribution to the progress of human civilization. Mental health is a fundamental aspect that affects the well-being of individuals and society as a whole. However, in reality, access to mental health services remains a major challenge in many regions worldwide, including Indonesia. Methods:This study employs a scoping review method to identify and map existing literature on innovations and the impact of AI-powered chatbots in the context of mental health detection.The article search process was carried out using electronic databases such as google schoolar and PUBMED. Then the articles that have been obtained are selected again by looking at the title, abstract and also the inclusion and exclusion criteria and obtained articles that are suitable for further review. Results: Searches across several journal databases found seven journal articles that met the criteria: articles focusing on the benefits of AI in detecting mental health issues, published in 2020, full-text, and written in English.The seven studies analyzed showed a decrease in depression and anxiety symptoms in people who consulted online regarding their mental health problems. Conclusion: In addressing mental health issues, chatbots can be used as a tool for mass screening to reduce symptoms of depression and anxiety while providing easy access to mental health support without stigma. However, chatbots have limitations in deep clinical assessment, lack critical thinking and dynamic adaptation, and pose risks of misdiagnosis in complex cases. Therefore, chatbots can serve as

Keywords

Chatbot; AI; Mental Health; Screening.



Full Text: PDF



References


A. Y. Chandra, D. Kurniawan, and R. Musa, “Perancangan Chatbot Menggunakan Dialogflow Natural Language Pro-cessing (Studi Kasus: Sistem Pemesanan pada Coffee Shop),” J. Media Inform. Budidarma, vol. 4, no. 1, p. 208, 2020, doi: 10.30865/mib.v4i1.1505.Zulkifli. (1994). Sufism in Java: The Role of the Pesantren in the Maintenance of Sufism in Java. Master Thesis. Singapore: Australian National University.

Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2(November), 100006. https://doi.org/10.1016/j.mlwa.2020.100006

Alarilla, A., Terrell, K., Kelly, P., Chesters, H., Gibson, F., Oldham, G., ... & Wray, J. (2024). Routine use of patient-reported experience and outcome measures for children and young people: a scoping review. Systematic Reviews, 13(1), 293. https://doi.org/10.1186/s13643-024-02706-x

Andika, E. A., & Renaldy, R. (2024, July). Perkembangan Sistem Berbasis Artificial Intelligence di Bidang Kesehatan. In Prosiding Seminar Nasional Informatika (Vol. 2, pp. 593-598). ISSN. 2988-2451.

Anmella, G., Sanabra, M., Primé-Tous, M., et al. (2024). Vickybot, a chatbot for anxiety-depressive symptoms and work-related burnout in primary care and health care professionals: Development, feasibility, and potential effectiveness studies. JMIR Publications. https://doi.org/10.2196/43293

Ardiansyah, G. R., Musayyanah, M., Aqvirandy, W., Farady, M. D., Cahya, M. N., & Hadiono, T. (2023). Deteksi kanker payudara menggunakan artificial neurol network pada deep learning. INFOTECH: Jurnal Informatika & Teknologi, 4(2), 259-269. https://doi.org/10.37373/infotech.v4i2.902

Beatty, C., Malik, T., Meheli, S., & Sinha, C. (2022). Evaluating the therapeutic alliance with a free-text CBT conversational agent (Wysa): A mixed-methods study. Frontiers in Digital Health. https://doi.org/10.3389/fdgth.2022.847991

Chui, M., et al. (2023) The State of AI in 2023: Generative AI’s Breakout Year. McKinsey & Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year

Dergaa, I., Fekih-Romdhane, F., Hallit, S., et al. (2024). ChatGPT is not ready yet for use in providing mental health assessment and intervention. Frontiers in Psychiatry. https://doi.org/10.3389/fpsyt.2023.1277756

Eriana, E. S., & Zein, A. (2023). Artificial Intelligence (AI). ISBN. 978-623-151-972-6.

Fadhillah, R., & Lestari, B. D. (2024). Penggunaan Ai Pada Mahasiswa Psikologi Dalam Meningkatkan Kesehatan Mental. Jurnal EMPATI, 13(4), 280-290. https://doi.org/10.14710/empati.2024.46723

Inkster, B., Kadaba, M., & Subramanian, V. (2023). Understanding the impact of an AI-enabled conversational agent mobile app on users' mental health and wellbeing with a self-reported maternal event: A mixed method real-world data mHealth study. Frontiers in Global Women’s Health. https://doi.org/10.3389/fgwh.2023.1084302

Jimma, B. L. (2023). Artificial intelligence in healthcare: A bibliometric analysis. Telematics and Informatics Reports, 9, 100041.https://doi.org/10.1016/j.teler.2023.100041

Kaywan, P., Ahmed, K., Ibaida, A., Miao, Y., & Gu, B. (2023). Early detection of depression using a conversational AI bot: A non-clinical trial. PLOS ONE. https://doi.org/10.1371/journal.pone.0279743

Kementerian Kesehatan Republik Indonesia. (2023). Hasil Survei Kesehatan Indonesia (SKI) tahun 2023. Jakarta: Kementerian Kesehatan RI.

Khairan, C., & Habib, M. (2025). Chatbot AI dalam Identifikasi Awal Gangguan Kesehatan Mental di Indonesia: Tantangan dan Prospek. Jurnal EMPATI, 13(6), 498-508. https://doi.org/10.14710/empati.2024.47903

Peters, M. D., Godfrey, C., McInerney, P., Khalil, H., Larsen, P., Marnie, C., ... & Munn, Z. (2022). Best practice guidance and reporting items for the development of scoping review protocols. JBI evidence synthesis, 20(4), 953-968. doi: 10.11124/JBIES-21-00242

Prochaska, J. J., Vogel, E. A., Chieng, A., Kendra, M., Baiocchi, M., Pajarito, S., & Robinson, A. (2021). A therapeutic relational agent for reducing problematic substance use (Woebot): Development and usability study. JMIR Publications. https://doi.org/10.2196/24850

Rahmadiannisa, M. S., Firdaus, F. S., Manaf, I. M., et al. (2024). Dopamind+: Mobile-based application to prevent and treat mental health disorders in adolescents. International Journal of Software Engineering and Computer Science (IJSECS). https://doi.org/10.35870/ijsecs.v4i12391

Riyadi, et al. (2024). Komunikasi Interpersonal Mahasiswa di Makassar Saat Pertama Kali ke Psikiater. Syntax Literate. (9)12. http://dx.doi.org/10.36418/syntax-literate.v9i12

Wulandari, D., & Elviany, R. (2024). Dampak Kesehatan Mental Dan Lonjakan Kasus Bunuh Diri Di Era Modern. Liberosis: Jurnal Psikologi dan Bimbingan Konseling, 2(1), 51-60. https://doi.org/10.3287/liberosis.v2i1.2086


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