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REVIEW ARTICLE

Artificial intelligence in mental healthcare: A review of health economics, sustainability, and global health perspectives

Fabiana Chyczij1,2 Mariana Paixão1 Diogo Gonçalves Sara3*
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1 Unidade de Saúde Familiar Fénix, Unidade Local de Saúde de Trás-os-Montes e Alto Douro (ULSTMAD), Vila Real
2 Clinical Academic Center of Trás-os-Montes and Alto Douro, University of Trás-os-Montes and Alto Douro (UTAD), Vila Real, Portugal
3 Gabinete de Projetos e Investigação Aplicada, Murça, Portugal
Received: 27 June 2026 | Revised: 12 August 2026 | Accepted: 12 August 2026 | Published online: 24 August 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

Mental disorders are among the leading causes of disability worldwide, imposing burdens on individuals, healthcare systems, and economies. Shortages of mental health professionals, unequal access to care, and increasing demand highlight the need for innovative solutions. Artificial intelligence (AI) has emerged as a technology with potential to transform mental healthcare through improved diagnosis, treatment, monitoring, and service delivery. This review examines AI applications in global mental health, focusing on opportunities, challenges, and implications for health equity. A narrative review was conducted using PubMed, Scopus, and Web of Science. Studies addressing AI technologies, digital mental health interventions, predictive analytics, telepsychiatry, health system integration, and mental health were identified and synthesized. Findings indicate that AI can enhance mental healthcare through early detection, personalized treatment planning, predictive risk assessment, digital therapeutics, and remote care delivery. These applications may expand access to mental health services, particularly in underserved and resource-limited settings, while supporting sustainability through resource allocation and data-driven decision-making. However, challenges include data privacy, algorithmic bias, limited transparency, regulatory uncertainty, and the risk of exacerbating health inequalities. Effective implementation requires governance, culturally appropriate applications, and preservation of human-centered care. Future developments in personalized psychiatry, explainable AI, and integration into public health systems may expand AI’s role in mental healthcare. Overall, AI represents a tool for addressing global mental health challenges, but its benefits depend on responsible, equitable, and ethical implementation. Collaboration among healthcare professionals, researchers, policymakers, and technology developers is essential to ensure AI improves outcomes and supports sustainable healthcare systems worldwide.

Keywords
Artificial intelligence
Mental health
Global mental health
Health equity
Digital health
Healthcare sustainability
Funding
None.
Conflict of interest
The authors declare they have no competing interests.
References

Acuña-Rodríguez, M. P., Fiorillo-Moreno, O., Montoya-Quintero, K. F., & Tejan Mansaray, F. (2025). Mental Health Workforce Inequities Across Income Levels: Aligning Global Health Indicators, Policy Readiness, and Disease Burden. Psychology Research and Behavior Management, 18, 1449-1454. https://doi.org/10.2147/PRBM.S532912

 

Ahmed, M. M., Okesanya, O. J., Olaleke, N. O., Adigun, O. A., Adebayo, U. O., Oso, T. A., Eshun, G., & Lucero-Prisno, D. E. (2025). Integrating Digital Health Innovations to Achieve Universal Health Coverage: Promoting Health Outcomes and Quality Through Global Public Health Equity. Healthcare, 13(9), 1060. https://doi.org/10.3390/healthcare13091060

 

Alhuwaydi, A. M. (2024). Exploring the Role of Artificial Intelligence in Mental Healthcare: Current Trends and Future Directions – A Narrative Review for a Comprehensive Insight. Risk Management and Healthcare Policy, 17, 1339-1348. https://doi.org/10.2147/RMHP.S461562

 

Ali, M., Ali, S., Abbas, Q., Abbas, Z., & Lee, S. W. (2025). Artificial intelligence for mental health: A narrative review of applications, challenges, and future directions in digital health. Digital Health, 11. https://doi.org/10.1177/20552076251395548

 

Anastasiadou, O., Tsipouras, M., Mpogiatzidis, P., & Angelidis, P. (2025). Digital Healthcare Innovative Services in Times of Crisis: A Literature Review. Healthcare, 13(8), 889. https://doi.org/10.3390/healthcare13080889

 

Balaban, B. M., Sacală, I., & Petrescu-Niţă, A. C. (2025). TriagE-NLU: A Natural Language Understanding System for Clinical Triage and Intervention in Multilingual Emergency Dialogues. Future Internet, 17(7), 314. https://doi.org/10.3390/fi17070314

 

Ballout, S. (2025). Trauma, Mental Health Workforce Shortages, and Health Equity: A Crisis in Public Health. International Journal of Environmental Research and Public Health, 22(4), 620. https://doi.org/10.3390/ijerph22040620

 

Bitomsky, L., Pfitzer, E. C., Nißen, M., & Kowatsch, T. (2024). Advancing health equity and the role of digital health technologies: A scoping review protocol. BMJ Open, 14(10), e082336. https://doi.org/10.1136/bmjopen-2023-082336

 

Bobkov, A., Cheng, F., Xu, J., Bobkova, T., Deng, F., He, J., Jiang, X., Khuzin, D., & Kang, Z. (2025). Telepsychiatry and Artificial Intelligence: A Structured Review of Emerging Approaches to Accessible Psychiatric Care. Healthcare, 13(11), 1348. https://doi.org/10.3390/healthcare13111348

 

Borghouts, J., Eikey, E., Mark, G., De Leon, C., Schueller, S. M., Schneider, M., Stadnick, N., Zheng, K., Mukamel, D., & Sorkin, D. H. (2021). Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review. Journal of Medical Internet Research, 23(3), e24387. https://doi.org/10.2196/24387

 

Buntrock, C. (2024). Cost-effectiveness of digital interventions for mental health: Current evidence, common misconceptions, and future directions. Frontiers in Digital Health, 6, 1486728. https://doi.org/10.3389/fdgth.2024.1486728

 

Cameron, G., Mulvenna, M., Ennis, E., O’Neill, S., Bond, R., Cameron, D., & Bunting, A. (2025). Effectiveness of Digital Mental Health Interventions in the Workplace: Umbrella Review of Systematic Reviews. JMIR Mental Health, 12(1), e67785. https://doi.org/10.2196/67785

 

Carrera, A., Manetti, S., & Lettieri, E. (2024). Rewiring care delivery through Digital Therapeutics (DTx): A machine learning-enhanced assessment and development (M-LEAD) framework. BMC Health Services Research, 24(1), 237. https://doi.org/10.1186/s12913-024-10702-z

 

Chen, Y., Lehmann, C. U., & Malin, B. (2024). Digital Information Ecosystems in Modern Care Coordination and Patient Care Pathways and the Challenges and Opportunities for AI Solutions. Journal of Medical Internet Research, 26, e60258. https://doi.org/10.2196/60258

 

Chustecki, M. (2024). Benefits and Risks of AI in Health Care: Narrative Review. Interactive Journal of Medical Research, 13, e53616. https://doi.org/10.2196/53616

 

Cunha Reis, T. (2025). Artificial intelligence and natural language processing for improved telemedicine: Before, during and after remote consultation. Atencion Primaria, 57(8), 103228. https://doi.org/10.1016/j.aprim.2025.103228

 

Douglas, A. O., Senkaiahliyan, S., Bulstra, C. A., Mita, C., Reddy, C. L., & Atun, R. (2025). Global Adoption of Value-Based Health Care Initiatives Within Health Systems. JAMA Health Forum, 6(5), e250746. https://doi.org/10.1001/jamahealthforum.2025.0746

 

Edemekong, P. F., Pavan Annamaraju, Afzal, M., & Haydel, M. J. (2024). Health Insurance Portability and Accountability Act (HIPAA) Compliance. NCBI Books; StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK500019/

 

El Jabiry, S.-E., Bouazzaoui, M. A., Barrimi, M., Elghazouani, F., & Oneib, B. (2025). Stress, coping strategies, and relapse among schizophrenia patients at the psychiatric hospital of Oujda, Morocco. The Pan African Medical Journal, 52, 97. https://doi.org/10.11604/pamj.2025.52.97.44612

 

Espino Carrasco, D. K., Palomino Alcántara, M. del R., Arbulú Pérez Vargas, C. G., Santa Cruz Espino, B. M., Dávila Valdera, L. J., Vargas Cabrera, C., Espino Carrasco, M., Dávila Valdera, A., & Agurto Córdova, L. M. (2025). Sustainability of AI-Assisted Mental Health Intervention: A Review of the Literature from 2020–2025. International Journal of Environmental Research and Public Health, 22(9), 1382. https://doi.org/10.3390/ijerph22091382

 

Fahim, Y. A., Hasani, I. W., Kabba, S., & Ragab, W. M. (2025). Artificial intelligence in healthcare and medicine: Clinical applications, therapeutic advances, and future perspectives. European Journal of Medical Research, 30(1), 848. https://doi.org/10.1186/s40001-025-03196-w

 

Faiyazuddin, Md., Rahman, S. J. Q., Anand, G., Siddiqui, R. K., Mehta, R., Khatib, M. N., Gaidhane, S., Zahiruddin, Q. S., Hussain, A., & Sah, R. (2025). The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency. Health Science Reports, 8(1), e70312. https://doi.org/10.1002/hsr2.70312

 

Farzan, M., Ebrahimi, H., Pourali, M., & Sabeti, F. (2024). Artificial Intelligence-Powered Cognitive Behavioral Therapy Chatbots, a Systematic Review. Iranian Journal of Psychiatry, 20(1), 102-110. https://doi.org/10.18502/ijps.v20i1.17395

 

Flores, S., Jónsson-Bachmann, E., Ingesson-Hammarberg, S., Hammarberg, A., Nystrand, C., & Sampaio, F. (2025). A cost-effectiveness analysis of two psychological treatments for controlled drinking in individuals with alcohol use disorder. Cost Effectiveness and Resource Allocation, 23(1). https://doi.org/10.1186/s12962-025-00633-9

 

Gebler, R., Reinecke, I., Sedlmayr, M., & Goldammer, M. (2025). Enhancing Clinical Data Infrastructure for AI Research: Comparative Evaluation of Data Management Architectures. Journal of Medical Internet Research, 27, e74976. https://doi.org/10.2196/74976

 

Gomes, M., Murray, E., & Raftery, J. (2022). Economic Evaluation of Digital Health Interventions: Methodological Issues and Recommendations for Practice. PharmacoEconomics, 40(4), 367-378. https://doi.org/10.1007/s40273-022-01130-0

 

Gonçalves-Ferreira, D., Sousa, M., Bacelar-Silva, G. M., Frade, S., Antunes, L. F., Beale, T., & Cruz-Correia, R. (2019). OpenEHR and General Data Protection Regulation: Evaluation of Principles and Requirements. JMIR Medical Informatics, 7(1), e9845. https://doi.org/10.2196/medinform.9845

 

Gu, D., Andreev, K., & Dupre, M. E. (2021). Major Trends in Population Growth Around the World. China CDC Weekly, 3(28), 604-613. https://doi.org/10.46234/ccdcw2021.160

 

Hadjiat, Y. (2023). Healthcare inequity and digital health–A bridge for the divide, or further erosion of the chasm? PLOS Digital Health, 2(6), e0000268. https://doi.org/10.1371/journal.pdig.0000268

 

Herrera, C. A., Bascolo, E., Villar-Uribe, M., Houghton, N., Bennett, S., Castro, M. C., et al. (2025). No time to wait: Resilience as a cornerstone for primary health care across Latin America and the Caribbean, a World Bank-PAHO Lancet Regional Health Americas Commission. The Lancet Regional Health - Americas, 50, 101240. https://doi.org/10.1016/j.lana.2025.101240

 

Hu, P., Hu, L., Wang, F., & Mei, J. (2024). Editorial: Computing and artificial intelligence in digital therapeutics. Frontiers in Medicine, 10, 1330686. https://doi.org/10.3389/fmed.2023.1330686

 

Insel, T. (2023). Digital mental health care: Five lessons from Act 1 and a preview of Acts 2–5. NPJ Digital Medicine, 6(1), 9. https://doi.org/10.1038/s41746-023-00760-8

 

Jain, R., Rai, R. S., Jain, S., Ahluwalia, R., & Gupta, J. (2023). Real time sentiment analysis of natural language using multimedia input. Multimedia Tools and Applications, 82(26), 41021-41036. https://doi.org/10.1007/s11042-023-15213-3

 

Jayawardana, D., Gannon, B., Doust, J., & Mishra, G. D. (2023). Excess healthcare costs of psychological distress in young women: Evidence from linked national Medicare claims data. Health Economics, 32(3), 715-734. https://doi.org/10.1002/hec.4641

 

Joseph, J. (2025). Algorithmic bias in public health AI: A silent threat to equity in low-resource settings. Frontiers in Public Health, 13, 1643180. https://doi.org/10.3389/fpubh.2025.1643180

 

Kambar, T., Tariq, S., Shahzad, S., Sultan, H. S., Siddiqui, A. N., Shah, F. A., Khanani, H., Khan, A., Shah, H. H., Rauf, S. A., Zuberi, M. A. W., Waseem, R., Hussain, M. S., & Haque, M. A. (2026). AI in Mental Health: Transforming Diagnosis and Management of Depression and Anxiety. Health Science Reports, 9(4), e72316. https://doi.org/10.1002/hsr2.72316

 

Khalil, H., Ameen, M., Davies, C., & Liu, C. (2025). Implementing value-based healthcare: A scoping review of key elements, outcomes, and challenges for sustainable healthcare systems. Frontiers in Public Health, 13, 1514098. https://doi.org/10.3389/fpubh.2025.1514098

 

Kopach-Konrad, R., Lawley, M., Criswell, M., Hasan, I., Chakraborty, S., Pekny, J., & Doebbeling, B. N. (2007). Applying Systems Engineering Principles in Improving Health Care Delivery. Journal of General Internal Medicine, 22(Suppl 3), 431-437. https://doi.org/10.1007/s11606-007-0292-3

 

Krishnan, S. V., Ayyan, S. M., Sardesai, I., Ambalakat, A., Haneef, M. M., Ghiya, M., Aggarwal, P., Singh, A., Galwankar, S., Bhoi, S., & Chauhan, V. (2025). Strategies to Combat Overcrowding at Emergency Departments across India: A White Paper by the Academic College of Emergency Experts, India and the World Health Organization Collaborating Centre for Emergency and Trauma, South-East Asia. Journal of Emergencies, Trauma, and Shock, 18(4), 166-174. https://doi.org/10.4103/jets.jets_182_25

 

Kruk, M. E., Gage, A. D., Arsenault, C., Jordan, K., Leslie, H. H., Roder-DeWan, S., et al. (2018). High-quality health systems in the Sustainable Development Goals era: Time for a revolution. The Lancet Global Health, 6(11), e1196-e1252. https://doi.org/10.1016/S2214-109X(18)30386-3

 

Lejeune, A., Le Glaz, A., Perron, P.A., Sebti, J., Baca-Garcia, E., Walter, M., Lemey, C., & Berrouiguet, S. (2022). Artificial intelligence and suicide prevention: A systematic review. European Psychiatry, 65(1), e19. https://doi.org/10.1192/j.eurpsy.2022.8

 

Liu, W., Zhang, Y., Chen, J., Li, X., Huang, Y., Zhao, F., Chen, F., Qu, P., & Li, Y. (2025). Global burden and trends of major mental disorders in individuals under 24 years of age from 1990 to 2021, with projections to 2050: Insights from the Global Burden of Disease Study 2021. Frontiers in Public Health, 13, 1635801. https://doi.org/10.3389/fpubh.2025.1635801

 

Löchner, J., Carlbring, P., Schuller, B., Torous, J., & Sander, L. B. (2025). Digital interventions in mental health: An overview and future perspectives. Internet Interventions, 40, 100824. https://doi.org/10.1016/j.invent.2025.100824

 

Mahomed, F. (2020). Addressing the Problem of Severe Underinvestment in Mental Health and Well-Being from a Human Rights Perspective. Health and Human Rights, 22(1), 35-49.

 

Mendlovic, S., Frankova, I., Vermetten, E., Wasserman, D., Schulze, T. G., Falkai, P., Fountoulakis, K. N., Adorjan, K., Uchida, H., Fruchter, E., Gobbi, G., & Zohar, J. (2026). Responsible artificial intelligence integration framework for psychiatric guidelines. International Journal of Neuropsychopharmacology, 29(4). https://doi.org/10.1093/ijnp/pyag010

 

Mennella, C., Maniscalco, U., De Pietro, G., & Esposito, M. (2024). Ethical and regulatory challenges of AI technologies in healthcare: A narrative review. Heliyon, 10(4), e26297. https://doi.org/10.1016/j.heliyon.2024.e26297

 

Mohapatra, B., & Anaraky, R. G. (2026). Assistive Intelligence: A Framework for AI-Powered Technologies Across the Dementia Continuum. Journal of Ageing and Longevity, 6(1), 8. https://doi.org/10.3390/jal6010008

 

Morelli, S., D’Avenio, G., Daniele, C., Grigioni, M., & Giansanti, D. (2024). Under the Tech Umbrella: Assessing the Landscape of Telemedicine Innovations (Telemechron Study). Healthcare, 12(6), 615. https://doi.org/10.3390/healthcare12060615

 

Moreno-Pineda, M., Ortiz-Mallasén, V., & Cervera-Gasch, Á. (2026). Artificial Intelligence for the Early Detection of Patients with Cognitive Impairment: A Scoping Review. Healthcare, 14(6), 768. https://doi.org/10.3390/healthcare14060768

 

Mortimer, F., Isherwood, J., Wilkinson, A., & Vaux, E. (2018). Sustainability in quality improvement: Redefining value. Future Healthcare Journal, 5(2), 88-93. https://doi.org/10.7861/futurehosp.5-2-88

 

Nap, E. W., Scheepers, F. E., Mulder, C. L., & Kamperman, A. M. (2025). Development of a machine learning model for predicting compulsory psychiatric care using clinical notes. BMC Psychiatry, 25(1), 1196. https://doi.org/10.1186/s12888-025-07464-1

 

Nguyen, K. H., Comans, T., Nguyen, T. T., Simpson, D., Woods, L., Wright, C., Green, D., McNeil, K., & Sullivan, C. (2024). Cashing in: Cost-benefit analysis framework for digital hospitals. BMC Health Services Research, 24(1), 694. https://doi.org/10.1186/s12913-024-11132-7

 

Ni, Y., & Jia, F. (2025). A Scoping Review of AI-Driven Digital Interventions in Mental Health Care: Mapping Applications Across Screening, Support, Monitoring, Prevention, and Clinical Education. Healthcare, 13(10), 1205. https://doi.org/10.3390/healthcare13101205

 

Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021). Addressing bias in big data and AI for health care: A call for open science. Patterns, 2(10), 100347. https://doi.org/10.1016/j.patter.2021.100347

 

Olawade, D. B., Popoola, T. T., Egbon, E., & David-Olawade, A. C. (2025). Sustainable healthcare practices: Pathways to a carbon-neutral future for the medical industry. Sustainable Futures, 9, 100783. https://doi.org/10.1016/j.sftr.2025.100783

 

Olawade, D. B., Wada, O. Z., Odetayo, A., David-Olawade, A. C., Asaolu, F., & Eberhardt, J. (2024). Enhancing mental health with Artificial Intelligence: Current trends and future prospects. Journal of Medicine, Surgery, and Public Health, 3, 100099. https://doi.org/10.1016/j.glmedi.2024.100099

 

Orrù, L., & Mannarini, S. (2026). The Role of Artificial Intelligence in Clinical Psychology: How AI and NLP Systems Are Reshaping Psychological Interventions. A Systematic Review. Clinical Psychology & Psychotherapy, 33(2), e70242. https://doi.org/10.1002/cpp.70242

 

Osareme, O., Muonde, M., Maduka, C., Olorunsogo, T., & Omotayo, O. (2024). Demographic shifts and healthcare: A review of aging populations and systemic challenges. International Journal of Science and Research Archive, 11(1), 383-395. https://doi.org/10.30574/ijsra.2024.11.1.0067

 

Patel, N. M., Savaliya, G. V., Mehta, P. J., & Kataria, L. R. (2025). Global Disparities in Mental Health Systems: A Comparative Cross-sectional Study of Ten Countries with Different Income Levels. Indian Journal of Psychological Medicine. https://doi.org/10.1177/02537176251379999

 

Pham, T. (2025). Ethical and legal considerations in healthcare AI: Innovation and policy for safe and fair use. Royal Society Open Science, 12(5), 241873. https://doi.org/10.1098/rsos.241873

 

Phan, P., Mitragotri, S., & Zhao, Z. (2023). Digital therapeutics in the clinic. Bioengineering & Translational Medicine, 8(4), e10536. https://doi.org/10.1002/btm2.10536

 

Qin, R., Zhao, H., Gao, H., & Liu, H. (2025). Global trends in Alzheimer’s disease and other dementias: A comprehensive analysis of incidence, socio-demographic variations, and future projections. PLoS ONE, 20(12), e0338018. https://doi.org/10.1371/journal.pone.0338018

 

Ray, M. K., Dark, F., & Kisely, S. (2025). The future of psychiatry: Reclaiming relevance in an era of technological and systemic transformation. The Australian and New Zealand Journal of Psychiatry, 60(5), 411-417. https://doi.org/10.1177/00048674251401028

 

Razaghi, M., Hafez, A., Farina, J. M., Scalia, I. G., Pereyra, M., Abdelfattah, F. E., Sheashaa, H., Awad, K., Lester, S. J., Ayoub, C., & Arsanjani, R. (2026). Transforming clinical documentation with ambient artificial intelligence (AI) scribes: A narrative review of technology, impact, and implementation. Cardiovascular Diagnosis and Therapy, 16(1), 11. https://doi.org/10.21037/cdt-2025-454

 

Reckers-Droog, V., Enzing, J., & Brouwer, W. (2024). The role of budget impact and its relationship with cost-effectiveness in reimbursement decisions on health technologies in the Netherlands. The European Journal of Health Economics, 25(8), 1449-1459. https://doi.org/10.1007/s10198-024-01673-3

 

Rudd, M. D. (2023). Recognizing flawed assumptions in suicide risk assessment research and clinical practice. Psychological Medicine, 53(5), 2186-2187. https://doi.org/10.1017/S0033291721002750

 

Santos, A. R., Sampaio, F., Londral, A. R., & Perelman, J. (2025). Mapping methodologies for economic assessment of digital health technologies: A scoping review protocol. BMJ Open, 15(7), e099933. https://doi.org/10.1136/bmjopen-2025-099933

 

Srivastava, K. (2009). Urbanization and mental health. Industrial Psychiatry Journal, 18(2), 75-76. https://doi.org/10.4103/0972-6748.64028

 

Stoumpos, A. I., Kitsios, F., & Talias, M. A. (2023). Digital Transformation in Healthcare: Technology Acceptance and Its Applications. International Journal of Environmental Research and Public Health, 20(4), 3407. https://doi.org/10.3390/ijerph20043407

 

Subramaniam, S., Raju, N., Ganesan, A., Rajavel, N., Chenniappan, M., Prakash, C., Pramanik, A., Basak, A. K., & Dixit, S. (2022). Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review. Sustainability, 14(16), 9951. https://doi.org/10.3390/su14169951

 

Sun, C. F., Correll, C. U., Trestman, R. L., Lin, Y., Xie, H., Hankey, M. S., Uymatiao, R. P., Patel, R. T., Metsutnan, V. L., McDaid, E. C., Saha, A., Kuo, C., Lewis, P., Bhatt, S. H., Lipphard, L. E., & Kablinger, A. S. (2023). Low availability, long wait times, and high geographic disparity of psychiatric outpatient care in the US. General Hospital Psychiatry, 84, 12-17. https://doi.org/10.1016/j.genhosppsych.2023.05.012

 

Tavory, T. (2024). Regulating AI in Mental Health: Ethics of Care Perspective. JMIR Mental Health, 11, e58493. https://doi.org/10.2196/58493

 

The Lancet Healthy Longevity. (2021). Care for ageing populations globally. The Lancet. Healthy Longevity, 2(4), e180. https://doi.org/10.1016/S2666-7568(21)00064-7

 

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

 

Velupillai, S., Suominen, H., Liakata, M., Roberts, A., Shah, A. D., Morley, K., Osborn, D., Hayes, J., Stewart, R., Downs, J., Chapman, W., & Dutta, R. (2018). Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances. Journal of Biomedical Informatics, 88, 11-19. https://doi.org/10.1016/j.jbi.2018.10.005

 

Western, M., Smit, E., Gültzow, T., Neter, E., Sniehotta, F., Malkowski, O., Wright, C., Busse, H., Peuters, C., Rehackova, L., Oteșanu, G., Ainsworth, B., Jones, C., Kilb, M., Rodrigues, A., Perski, O., Wright, A., & König, L. (2025). Bridging the digital health divide: A narrative review of the causes, implications, and solutions for digital health inequalities. Health Psychology and Behavioral Medicine, 13(1). https://doi.org/10.1080/21642850.2025.2493139

 

White, N. M., Carter, H. E., Kularatna, S., Borg, D. N., Brain, D. C., Tariq, A., Abell, B., Blythe, R., & McPhail, S. M. (2023). Evaluating the costs and consequences of computerized clinical decision support systems in hospitals: A scoping review and recommendations for future practice. Journal of the American Medical Informatics Association, 30(6), 1205-1218. https://doi.org/10.1093/jamia/ocad040

 

World Health Organization. (2026). Towards responsible AI for mental health and well-being: Experts chart a way forward. https://www.who.int/news/item/20-03-2026-towards-responsible-ai-for-mental-health-and-well-being--experts-chart-a-way-forward

 

Yeasmin, S., Semi, M. M. A., Rony, M. K. K., Das, S., Sabeena, A. A., Rahman, R., Biswas, B., Ahmed, F., & Hossain, A. (2025). Artificial Intelligence for Mental Health Monitoring: A Solution for Digital Behavioral Health Care and Education—An Umbrella Review. Health Science Reports, 9(1), e71703. https://doi.org/10.1002/hsr2.71703

 

Zheng, H., & Zhang, X. (2025). Psychiatry in the age of AI: Transforming theory, practice, and medical education. Frontiers in Public Health, 13, 1660448. https://doi.org/10.3389/fpubh.2025.1660448

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