DOI: https://doi.org/10.14710/empati.2024.47903

CHATBOT AI DALAM IDENTIFIKASI AWAL GANGGUAN KESEHATAN MENTAL DI INDONESIA: TANTANGAN DAN PROSPEK

Fakultas Psikologi, Universitas Islam Negeri Syarif Hidayatullah Jakarta, Indonesia

Received: 25 Oct 2024; Published: 20 Jan 2025.

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Abstract

Kesehatan mental adalah aspek penting dari kesejahteraan yang seringkali diabaikan. Di Indonesia, prevalensi gangguan kesehatan mental pada usia 15 tahun ke atas mencapai 2%, dengan tantangan akses layanan yang terbatas (Kementerian Kesehatan RI, 2023). Teknologi AI, khususnya chatbot AI, menawarkan solusi potensial untuk deteksi awal gangguan kesehatan mental dengan menyediakan dukungan 24/7 dan skrining gejala awal (Fitzpatrick et al., 2017). Penelitian ini menggunakan metode tinjauan naratif untuk mengevaluasi potensi dan tantangan penerapan chatbot AI dalam konteks Indonesia. Pencarian sistematis dilakukan pada database elektronik utama seperti PubMed, Scopus, ScienceDirect, dan Google Scholar dengan kata kunci “Chatbot AI trends in mental health.” Pencarian dibatasi pada artikel berbahasa Inggris yang diterbitkan antara 2014 hingga 2024 untuk memastikan relevansi. Sebanyak 55 jurnal yang membahas penggunaan chatbot AI dalam kesehatan mental direview. Analisis data dilakukan secara tematik mengikuti prosedur Braun dan Clarke (2006), yang mencakup familiarisasi dengan data, pengkodean awal, pencarian tema, peninjauan tema, dan penamaan tema. Temuan menunjukkan bahwa chatbot AI dapat meningkatkan akses layanan kesehatan mental, mengurangi stigma, dan memberikan dukungan yang dipersonalisasi. Namun, tantangan seperti privasi data, keterbatasan empati, dan sensitivitas budaya harus diatasi. Studi ini merekomendasikan integrasi chatbot AI dalam sistem kesehatan mental Indonesia dan menekankan perlunya penelitian lebih lanjut untuk menilai efektivitas dan keamanan dalam konteks lokal.

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Keywords: akses layanan; Chatbot AI; deteksi awal; kesehatan mental; stigma

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  1. Aggarwal, A., Tam, C. C., Wu, D., Li, X., & Qiao, S. (2023). Artificial intelligence–based chatbots for promoting health behavioral changes: Systematic review. Journal of Medical Internet Research, 25, 1–17. https://doi.org/10.2196/40789
  2. Ahmed, A., Hassan, A., Aziz, S., Abd-alrazaq, A. A., Ali, N., Alzubaidi, M., … Househ, M. (2023). Chatbot features for anxiety and depression: A scoping review. Health Informatics Journal, 29(1). https://doi.org/10.1177/14604582221146719
  3. Anmella, G., Sanabra, M., Primé-Tous, M., Segú, X., Cavero, M., Morilla, I., … Hidalgo-Mazzei, D. (2023). Vickybot, a chatbot for anxiety-depressive symptoms and work-related burnout in primary care and health care professionals: Development, feasibility, and potential effectiveness studies. Journal of Medical Internet Research, 25. https://doi.org/10.2196/43293
  4. Balcombe, L. (2023). AI chatbots in digital mental health. Informatics, 10(4). https://doi.org/10.3390/informatics10040082
  5. Bendig, E., Erb, B., Schulze-Thuesing, L., & Baumeister, H. (2022). The next generation: Chatbots in clinical psychology and psychotherapy to foster mental health - a scoping review. Verhaltenstherapie, 32(1), 64–76. https://doi.org/10.1159/000501812
  6. Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., … Zilca, R. (2021). Artificially intelligent chatbots in digital mental health interventions: A review. Expert Review of Medical Devices, 18(1), 37–49. https://doi.org/10.1080/17434440.2021.2013200
  7. Brown, J. A., Russell, S., Hattouni, E., & Kincaid, A. (2020). Psychoeducation. In Oxford Research Encyclopedia of Education
  8. Corrigan, P. W., Druss, B. G., & Perlick, D. A. (2014). The impact of mental illness stigma on seeking and participating in mental health care. Psychological Science in the Public Interest, 15(2), 37-70
  9. D’Alfonso, S., Santesteban-Echarri, O., Rice, S., Wadley, G., Lederman, R., Miles, C., … Alvarez-Jimenez, M. (2017). Artificial intelligence-assisted online social therapy for youth mental health. Frontiers in Psychology, 8, 1–13. https://doi.org/10.3389/fpsyg.2017.00796
  10. D'Alfonso, S. (2020). AI in mental health. Current Opinion in Psychology, 36, 112-117
  11. Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017). Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial. JMIR Mental Health, 4(2), e19
  12. Fulmer, R., Joerin, A., Gentile, B., Lakerink, L., & Rauws, M. (2018). Using psychological artificial intelligence (Tess) to relieve symptoms of depression and anxiety: Randomized controlled trial. JMIR Mental Health, 5(4), e64
  13. Gaffney, H., Mansell, W., Edwards, R., & Wright, J. (2014). Manage Your Life Online (MYLO): A pilot trial of a conversational computer-based intervention for problem solving in a student sample. Behavioural and Cognitive Psychotherapy, 42(6), 731-746
  14. Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H. C., & Jeste, D. V. (2019). Artificial intelligence for mental health and mental illnesses: An overview. Current Psychiatry Reports, 21, 1-18
  15. Grové, C. (2021). Co-developing a mental health and wellbeing chatbot with and for young people. Frontiers in Psychiatry, 11, 1–12. https://doi.org/10.3389/fpsyt.2020.606041
  16. Haque, M. D. R., & Rubya, S. (2023). An overview of chatbot-based mobile mental health apps: Insights from app description and user reviews. JMIR MHealth and UHealth, 11. https://doi.org/10.2196/44838
  17. Iniesta, R., Stahl, D., Mcguf, P. (2016). Machine learning, statistical learning and the future of biological research in psychiatry. Psychol Med, 46, 2455–2465. https://doi.org/10.1017/S0033291716001367
  18. Inkster, B., Sarda, S., & Subramanian, V. (2018). An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: Real-world data evaluation mixed-methods study. JMIR mHealth and uHealth, 6(11), e12106
  19. Janssen, R.J., Mourão-Miranda, J., Schnack, H.G. (2018). Making individual prognosis in psychiatry using neuroimaging and machine learning. Biol Psychiatry Cogn Neurosci Neuroimaging, 3(9), 798–808. https://doi.org/10.1016/j.bpsc.2018.04.004
  20. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol, 2(4), 230–43. https://doi.org/10.1136/svn-2017-000101
  21. Jungmann, S. M., Klan, T., Kuhn, S., & Jungmann, F. (2019). Accuracy of a chatbot (Ada) in the diagnosis of mental disorders: Comparative case study with lay and expert users. JMIR formative research, 3(4), e13863
  22. Kapoor, P., Agrawal, P., & Ahmad, Z. (2021). Therapy chatbot: A relief from mental stress and problems. International Journal of Scientific & Engineering Research, 12(5), 1117–1122. https://doi.org/10.14299/ijser.2021.05.08
  23. Kementerian Kesehatan RI. (2018). Riset Kesehatan Dasar (Riskesdas) 2018. Badan Penelitian dan Pengembangan Kesehatan
  24. Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023). Natural language processing: State of the art, current trends and challenges. Multimedia Tools and Applications, 82(3), 3713-3744
  25. Klos, M. C., Escoredo, M., Joerin, A., Lemos, V. N., Rauws, M., & Bunge, E. L. (2021). Artificial intelligence based chatbot for anxiety and depression in university students: Pilot randomized controlled trial. JMIR Formative Research, 5(8). https://doi.org/10.2196/20678
  26. Koulouri, T., MacRedie, R. D., & Olakitan, D. (2022). Chatbots to support young adults’ mental health: An exploratory study of acceptability. ACM Transactions on Interactive Intelligent Systems, 12(2). https://doi.org/10.1145/3485874
  27. Kurniawan, M. H., Handiyani, H., Nuraini, T., Hariyati, R. T. S., & Sutrisno, S. (2024). A systematic review of artificial intelligence-powered (AI-powered) chatbot intervention for managing chronic illness. Annals of Medicine, 56(1). https://doi.org/10.1080/07853890.2024.2302980
  28. Limpanopparat, S., Gibson, E., & Harris, A. (2024). Artificial humans user engagement, attitudes, and the effectiveness of chatbots as a mental health intervention: A systematic review. Computers in Human Behavior: Artificial Humans, 2(2), 100081. https://doi.org/10.1016/j.chbah.2024.100081
  29. Miller, D. D., Facp, C. M., Brown, E. W. (2018). Artificial intelligence in medical practice: The question to the answer? Am J Med, 131(2), 129–33. https://doi.org/10.1016/j.amjmed.2017.10.035
  30. Omarov, B., Narynov, S., & Zhumanov, Z. (2023). Artificial intelligence-enabled chatbots in mental health: A systematic review. Computers, Materials and Continua, 74(3), 5105–5122. https://doi.org/10.32604/cmc.2023.034655
  31. Pham, K. T., Nabizadeh, A., & Selek, S. (2022). Artificial intelligence and chatbots in psychiatry. Psychiatric Quarterly, 93(1), 249–253. https://doi.org/10.1007/s11126-022-09973-8
  32. Potts, C., Ennis, E., Bond, R. B., Mulvenna, M. D., McTear, M. F., Boyd, K., … O’Neill, S. (2021). Chatbots to support mental wellbeing of people living in rural areas: Can user groups contribute to co-design? Journal of Technology in Behavioral Science, 6(4), 652–665. https://doi.org/10.1007/s41347-021-00222-6
  33. Rathnayaka, P., Mills, N., Burnett, D., De Silva, D., Alahakoon, D., & Gray, R. (2022). A mental health chatbot with cognitive skills for personalized behavioural activation and remote health monitoring. Sensors, 22(10). https://doi.org/10.3390/s22103653
  34. Schick, A., Feine, J., Morana, S., Maedche, A., & Reininghaus, U. (2022). Validity of chatbot use for mental health assessment: Experimental study. JMIR MHealth and UHealth, 10(10). https://doi.org/10.2196/28082
  35. Uban, A. S., Chulvi, B., & Rosso, P. (2021). An emotion and cognitive based analysis of mental health disorders from social media data. Future Generation Computer Systems, 124, 480-494
  36. Wang, J., Hwang, G. H., & Chang, C. Y. (2021). Directions of the 100 most cited chatbot-related human behavior research: A review of academic publications. Computers and Education: Artificial Intelligence, 2, 100023. https://doi.org/10.1016/j.caeai.2021.100023
  37. Zhang, T., Schoene, A. M., Ji, S., & Ananiadou, S. (2022). Natural language processing applied to mental illness detection

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