Perkembangan riset generative AI dalam kesehatan mental berdasarkan publikasi terindeks

  • Alzet Rama 
    Universitas Negeri Padang
    Indonesia
  • Mutia Ramdhatul Jannah
    Universitas Negeri Padang
    Indonesia

Abstract

Kemunculan generative artificial intelligence (GenAI) dan large language models (LLM) telah mengubah lanskap penelitian kesehatan mental secara signifikan sejak popularisasi ChatGPT pada akhir tahun 2022. Penelitian ini bertujuan memetakan evolusi, struktur intelektual, dan tren tematik penelitian global mengenai penerapan GenAI dalam kesehatan mental melalui pendekatan analisis bibliometrik. Data diperoleh dari basis data Scopus menggunakan strategi pencarian Boolean yang menggabungkan istilah generative AI, large language model, dan kesehatan mental, kemudian disaring melalui prosedur PRISMA hingga menghasilkan 917 artikel jurnal berbahasa Inggris yang terbit pada rentang tahun 2021 sampai 2025. Analisis dilakukan menggunakan Biblioshiny dan Bibliometrix mencakup tren publikasi tahunan, analisis sitasi, produktivitas sumber melalui Hukum Bradford, produktivitas penulis melalui Hukum Lotka, kolaborasi negara, pemetaan tematik, dan evolusi topik. Hasil menunjukkan pertumbuhan publikasi yang eksponensial, dari delapan artikel pada tahun 2021 menjadi 606 artikel pada tahun 2025, dengan dominasi Amerika Serikat, Tiongkok, dan Britania Raya, serta Journal of Medical Internet Research sebagai sumber paling produktif. Pemetaan tematik mengidentifikasi ChatGPT, large language model, dan kesehatan mental sebagai tema inti yang masih berada pada tahap perkembangan awal. Temuan ini mengonfirmasi bahwa penelitian GenAI untuk kesehatan mental merupakan bidang yang baru muncul dengan struktur keilmuan yang belum matang sehingga membuka agenda riset lanjutan terkait validasi klinis dan keamanan etis.

Keywords
  • generative artificial intelligence; large language model; kesehatan mental; analisis bibliometrik; ChatGPT; Bibliometrix
Lisensing Information
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References
  1. Abbasian, M., Khatibi, E., Azimi, I., Oniani, D., Shakeri Hossein Abad, Z., Thieme, A., Sriram, R., Yang, Z., Wang, Y., Lin, B., Gevaert, O., Li, L.-J., Jain, R., & Rahmani, A.M. (2024). Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI. npj Digital Medicine, 7(1), Article 82. https://doi.org/10.1038/s41746-024-01074-z
  2. Alanezi, F. (2024). Assessing the Effectiveness of ChatGPT in Delivering Mental Health Support: A Qualitative Study. Journal of Multidisciplinary Healthcare, 17, 461-471. https://doi.org/10.2147/JMDH.S447368
  3. Arillotta, D., Floresta, G., Guirguis, A., Corkery, J.M., Catalani, V., Martinotti, G., Sensi, S.L., & Schifano, F. (2023). GLP-1 Receptor Agonists and Related Mental Health Issues; Insights from a Range of Social Media Platforms Using a Mixed-Methods Approach. Brain Sciences, 13(11), Article 1503. https://doi.org/10.3390/brainsci13111503
  4. Blease, C., & Torous, J. (2023). ChatGPT and mental healthcare: balancing benefits with risks of harms. BMJ Mental Health, 26(1), Article 26. https://doi.org/10.1136/bmjment-2023-300884
  5. Blease, C., Worthen, A., & Torous, J. (2024). Psychiatrists’ experiences and opinions of generative artificial intelligence in mental healthcare: An online mixed methods survey. Psychiatry Research, 333, Article 115724. https://doi.org/10.1016/j.psychres.2024.115724
  6. Bokolo, B.G., & Liu, Q. (2023). Deep Learning-Based Depression Detection from Social Media: Comparative Evaluation of ML and Transformer Techniques. Electronics (Switzerland), 12(21), Article 4396. https://doi.org/10.3390/electronics12214396
  7. Chervenak, J., Lieman, H., Blanco-Breindel, M., & Jindal, S. (2023). The promise and peril of using a large language model to obtain clinical information: ChatGPT performs strongly as a fertility counseling tool with limitations. Fertility and Sterility, 120(3), 575-583. https://doi.org/10.1016/j.fertnstert.2023.05.151
  8. Crawford, J., Allen, K.-A., Pani, B., & Cowling, M. (2024). When artificial intelligence substitutes humans in higher education: the cost of loneliness, student success, and retention. Studies in Higher Education, 49(5), 883-897. https://doi.org/10.1080/03075079.2024.2326956
  9. Davis, R., Eppler, M., Ayo-Ajibola, O., Loh-Doyle, J.C., Nabhani, J., Samplaski, M., Gill, I., & Cacciamani, G.E. (2023). Evaluating the Effectiveness of Artificial Intelligence-powered Large Language Models Application in Disseminating Appropriate and Readable Health Information in Urology. Journal of Urology, 210(4), 688-694. https://doi.org/10.1097/JU.0000000000003615
  10. De Freitas, J., & Cohen, I.G. (2024). The health risks of generative AI-based wellness apps. Nature Medicine, 30(5), 1269-1275. https://doi.org/10.1038/s41591-024-02943-6
  11. Delello, J.A., Sung, W., Mokhtari, K., Hebert, J., Bronson, A., & De Giuseppe, T. (2025). AI in the Classroom: Insights from Educators on Usage, Challenges, and Mental Health. Education Sciences, 15(2), Article 113. https://doi.org/10.3390/educsci15020113
  12. Dergaa, I., Ben Saad, H., Glenn, J.M., Amamou, B., Ben Aissa, M., Guelmami, N., Fekih-Romdhane, F., & Chamari, K. (2024). From tools to threats: a reflection on the impact of artificial-intelligence chatbots on cognitive health. Frontiers in Psychology, 15, Article 1259845. https://doi.org/10.3389/fpsyg.2024.1259845
  13. Dergaa, I., Fekih-Romdhane, F., Hallit, S., Loch, A.A., Glenn, J.M., Fessi, M.S., Ben Aissa, M., Souissi, N., Guelmami, N., Swed, S., El Omri, A., Bragazzi, N.L., & Ben Saad, H. (2023). ChatGPT is not ready yet for use in providing mental health assessment and interventions. Frontiers in Psychiatry, 14, Article 1277756. https://doi.org/10.3389/fpsyt.2023.1277756
  14. De Freitas, J., Uğuralp, A.K., Oğuz-Uğuralp, Z., & Puntoni, S. (2024). Chatbots and mental health: Insights into the safety of generative AI. Journal of Consumer Psychology, 34(3), 481-491. https://doi.org/10.1002/jcpy.1393
  15. Elyoseph, Z., Hadar-Shoval, D., Asraf, K., & Lvovsky, M. (2023). ChatGPT outperforms humans in emotional awareness evaluations. Frontiers in Psychology, 14, Article 1199058. https://doi.org/10.3389/fpsyg.2023.1199058
  16. Elyoseph, Z., & Levkovich, I. (2023). Beyond human expertise: the promise and limitations of ChatGPT in suicide risk assessment. Frontiers in Psychiatry, 14, Article 1213141. https://doi.org/10.3389/fpsyt.2023.1213141
  17. Elyoseph, Z., Levkovich, I., & Shinan-Altman, S. (2024). Assessing prognosis in depression: Comparing perspectives of AI models, mental health professionals and the general public. Family Medicine and Community Health, 12(Suppl 1), Article e002583. https://doi.org/10.1136/fmch-2023-002583
  18. Elyoseph, Z., Refoua, E., Asraf, K., Lvovsky, M., Shimoni, Y., & Hadar-Shoval, D. (2024). Capacity of Generative AI to Interpret Human Emotions From Visual and Textual Data: Pilot Evaluation Study. JMIR Mental Health, 11(1), Article e54369. https://doi.org/10.2196/54369
  19. Franco D'Souza, R., Amanullah, S., Mathew, M., & Surapaneni, K.M. (2023). Appraising the performance of ChatGPT in psychiatry using 100 clinical case vignettes. Asian Journal of Psychiatry, 89, Article 103770. https://doi.org/10.1016/j.ajp.2023.103770
  20. Grodniewicz, J.P., & Hohol, M. (2023). Waiting for a digital therapist: three challenges on the path to psychotherapy delivered by artificial intelligence. Frontiers in Psychiatry, 14, Article 1190084. https://doi.org/10.3389/fpsyt.2023.1190084
  21. Hua, Y., Na, H., Li, Z., Liu, F., Fang, X., Clifton, D., & Torous, J. (2025). A scoping review of large language models for generative tasks in mental health care. npj Digital Medicine, 8(1), Article 230. https://doi.org/10.1038/s41746-025-01611-4
  22. Huang, X., Estau, D., Liu, X., Yu, Y., Qin, J., & Li, Z. (2024). Evaluating the performance of ChatGPT in clinical pharmacy: A comparative study of ChatGPT and clinical pharmacists. British Journal of Clinical Pharmacology, 90(1), 232-238. https://doi.org/10.1111/bcp.15896
  23. Kohnke, L., Zou, D., & Moorhouse, B.L. (2024). Technostress and English language teaching in the age of generative AI. Educational Technology and Society, 27(2), 306-320. https://doi.org/10.30191/ETS.202404_27(2).TP02
  24. Kraljevic, Z., Bean, D., Shek, A., Bendayan, R., Hemingway, H., Yeung, J.A., Deng, A., Baston, A., Ross, J., Idowu, E., Teo, J.T., & Dobson, R.J.B. (2024). Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study. The Lancet Digital Health, 6(4), e281-e290. https://doi.org/10.1016/S2589-7500(24)00025-6
  25. Lawrence, H.R., Schneider, R.A., Rubin, S.B., Mataric, M.J., McDuff, D.J., & Bell, M.J. (2024). The Opportunities and Risks of Large Language Models in Mental Health. JMIR Mental Health, 11, Article e59479. https://doi.org/10.2196/59479
  26. Levkovich, I., & Elyoseph, Z. (2023). Suicide Risk Assessments Through the Eyes of ChatGPT-3.5 Versus ChatGPT-4: Vignette Study. JMIR Mental Health, 10(1), Article e51232. https://doi.org/10.2196/51232
  27. Levkovich, I., & Elyoseph, Z. (2023). Identifying depression and its determinants upon initiating treatment: ChatGPT versus primary care physicians. Family Medicine and Community Health, 11(4), Article e002391. https://doi.org/10.1136/fmch-2023-002391
  28. Li, L., Peng, W., & Rheu, M.M.J. (2024). Factors Predicting Intentions of Adoption and Continued Use of Artificial Intelligence Chatbots for Mental Health: Examining the Role of UTAUT Model, Stigma, Privacy Concerns, and Artificial Intelligence Hesitancy. Telemedicine and e-Health, 30(3), 722-730. https://doi.org/10.1089/tmj.2023.0313
  29. Llanes-Jurado, J., Gómez-Zaragozá, L., Minissi, M.E., Alcañiz, M., & Marín-Morales, J. (2024). Developing conversational Virtual Humans for social emotion elicitation based on large language models. Expert Systems with Applications, 246, Article 123261. https://doi.org/10.1016/j.eswa.2024.123261
  30. Momenaei, B., Wakabayashi, T., Shahlaee, A., Durrani, A.F., Pandit, S.A., Wang, K., Mansour, H.A., Abishek, R.M., Xu, D., Sridhar, J., Yonekawa, Y., & Kuriyan, A.E. (2023). Appropriateness and Readability of ChatGPT-4-Generated Responses for Surgical Treatment of Retinal Diseases. Ophthalmology Retina, 7(10), 862-868. https://doi.org/10.1016/j.oret.2023.05.022
  31. Omar, M., Soffer, S., Agbareia, R., Bragazzi, N.L., Apakama, D.U., Horowitz, C.R., Charney, A.W., Freeman, R., Kummer, B., Glicksberg, B.S., Nadkarni, G.N., & Klang, E. (2025). Sociodemographic biases in medical decision making by large language models. Nature Medicine, 31(6), 1873-1881. https://doi.org/10.1038/s41591-025-03626-6
  32. Onder, C.E., Koc, G., Gokbulut, P., Taskaldiran, I., & Kuskonmaz, S.M. (2024). Evaluation of the reliability and readability of ChatGPT-4 responses regarding hypothyroidism during pregnancy. Scientific Reports, 14(1), Article 243. https://doi.org/10.1038/s41598-023-50884-w
  33. Radwan, A., Amarneh, M., Alawneh, H., Ashqar, H.I., AlSobeh, A., & Magableh, A.A.A.R. (2024). Predictive Analytics in Mental Health Leveraging LLM Embeddings and Machine Learning Models for Social Media Analysis. International Journal of Web Services Research, 21(1). https://doi.org/10.4018/IJWSR.338222
  34. Sai, S., Gaur, A., Sai, R., Chamola, V., Guizani, M., & Rodrigues, J.J.P.C. (2024). Generative AI for Transformative Healthcare: A Comprehensive Study of Emerging Models, Applications, Case Studies, and Limitations. IEEE Access, 12, 31078-31106. https://doi.org/10.1109/ACCESS.2024.3367715
  35. Salah, M., Alhalbusi, H., Ismail, M.M., & Abdelfattah, F. (2024). Chatting with ChatGPT: decoding the mind of Chatbot users and unveiling the intricate connections between user perception, trust and stereotype perception on self-esteem and psychological well-being. Current Psychology, 43(9), 7843-7858. https://doi.org/10.1007/s12144-023-04989-0
  36. Sallam, M., Salim, N.A., Barakat, M., & Al-Tammemi, A.B. (2023). ChatGPT applications in medical, dental, pharmacy, and public health education: A descriptive study highlighting the advantages and limitations. Narra J, 3(1), Article e103. https://doi.org/10.52225/narra.v3i1.103
  37. Shen, J., DiPaola, D., Ali, S., Sap, M., Park, H.W., & Breazeal, C. (2024). Empathy Toward Artificial Intelligence Versus Human Experiences and the Role of Transparency in Mental Health and Social Support Chatbot Design: Comparative Study. JMIR Mental Health, 11, Article e62679. https://doi.org/10.2196/62679
  38. Siddals, S., Torous, J., & Coxon, A. (2024). “It happened to be the perfect thing”: experiences of generative AI chatbots for mental health. npj Mental Health Research, 3(1), Article 48. https://doi.org/10.1038/s44184-024-00097-4
  39. Stade, E.C., Stirman, S.W., Ungar, L.H., Boland, C.L., Schwartz, H.A., Yaden, D.B., Sedoc, J., DeRubeis, R.J., Willer, R., & Eichstaedt, J.C. (2024). Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation. npj Mental Health Research, 3(1), Article 12. https://doi.org/10.1038/s44184-024-00056-z
  40. Tam, W., Huynh, T., Tang, A., Luong, S., Khatri, Y., & Zhou, W. (2023). Nursing education in the age of artificial intelligence powered Chatbots (AI-Chatbots): Are we ready yet?. Nurse Education Today, 129, Article 105917. https://doi.org/10.1016/j.nedt.2023.105917
  41. Torous, J., Linardon, J., Goldberg, S.B., Sun, S., Bell, I., Nicholas, J., Hassan, L., Hua, Y., Milton, A., & Firth, J. (2025). The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality. World Psychiatry, 24(2), 156-174. https://doi.org/10.1002/wps.21299
  42. Whiles, B.B., Bird, V.G., Canales, B.K., DiBianco, J.M., & Terry, R.S. (2023). Caution! AI Bot Has Entered the Patient Chat: ChatGPT Has Limitations in Providing Accurate Urologic Healthcare Advice. Urology, 180, 278-284. https://doi.org/10.1016/j.urology.2023.07.010
  43. Woodnutt, S., Allen, C., Snowden, J., Flynn, M., Hall, S., Libberton, P., & Purvis, F. (2024). Could artificial intelligence write mental health nursing care plans?. Journal of Psychiatric and Mental Health Nursing, 31(1), 79-86. https://doi.org/10.1111/jpm.12965
  44. Xie, Y., Seth, I., Hunter-Smith, D.J., Rozen, W.M., Ross, R., & Lee, M. (2023). Aesthetic Surgery Advice and Counseling from Artificial Intelligence: A Rhinoplasty Consultation with ChatGPT. Aesthetic Plastic Surgery, 47(5), 1985-1993. https://doi.org/10.1007/s00266-023-03338-7
  45. Xu, X., Yao, B., Dong, Y., Gabriel, S., Yu, H., Hendler, J., Ghassemi, M., Dey, A.K., & Wang, D. (2024). Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8(1), Article 31. https://doi.org/10.1145/3643540

Downloads

PDF

Statistic

Abstract Views
: 12 times
PDF
: 4 times