American Journal of Software Engineering and Applications

Submit a Manuscript

Publishing with us to make your research visible to the widest possible audience.

Propose a Special Issue

Building a community of authors and readers to discuss the latest research and develop new ideas.

Research Article |

Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being

This research rigorously explores the implementation of Chatbot-Enhanced Mental Health First Aid (MHFA) within corporate contexts, presenting an innovative paradigm for mitigating mental health risks and bolstering employee well-being. Amidst increasing recognition of the pervasive nature of mental health challenges in the workplace, this research elucidates the potential of AI-driven chatbots to augment conventional MHFA methodologies. These sophisticated chatbot systems offer an accessible, stigma-free avenue for support, facilitating early detection and preliminary counselling in instances of mental health crises. The study meticulously evaluates the efficacy of chatbots in crisis intervention and their seamless integration into holistic corporate wellness frameworks. These encompass a spectrum of initiatives, including proactive health promotion programs, adaptable work policies, and comprehensive employee assistance schemes. The research also navigates the intricacies of embedding MHFA programs in organisational structures, addressing challenges like resistance to technological and procedural shifts and concerns around data privacy. Strategic methodologies are proposed to navigate and surmount these barriers effectively. A pivotal aspect of this research is the ethical deployment and privacy preservation in the utilisation of chatbots. The paper provides a thorough critique of the ethical considerations and privacy safeguards essential in the management of sensitive mental health information, ensuring adherence to ethical standards and confidentiality. Concludingly, the study posits that the integration of chatbot-enhanced MHFA can substantially reduce workplace mental health stigma, align with legal compliance mandates, and facilitate cost-efficiency. This innovative approach supports the development of a more comprehensive and accessible mental health infrastructure within corporate settings. Looking ahead, the paper advocates for further empirical research to assess the longitudinal impacts of chatbot-enhanced MHFA, explore diverse employee interactions with these systems, and advance AI algorithms for tailored mental health support. The infusion of AI-driven chatbots in MHFA programs is heralded as a pivotal advancement, signifying a major stride towards fostering more resilient, supportive, and mentally healthy workplace environments.

Mental Health First Aid (MHFA), Corporate Well-Being, AI-Driven Chatbots, Mental Health in the Workplace, Early Intervention in Mental Health

APA Style

Banerjee, S., Agarwal, A., Bar, A. K. (2024). Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being. American Journal of Software Engineering and Applications, 12(1), 1-4. https://doi.org/10.11648/j.ajsea.20241201.11

ACS Style

Banerjee, S.; Agarwal, A.; Bar, A. K. Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being. Am. J. Softw. Eng. Appl. 2024, 12(1), 1-4. doi: 10.11648/j.ajsea.20241201.11

AMA Style

Banerjee S, Agarwal A, Bar AK. Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being. Am J Softw Eng Appl. 2024;12(1):1-4. doi: 10.11648/j.ajsea.20241201.11

Copyright © 2024 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Bovopoulos, N., Jorm, A. F., Bond, K. S., LaMontagne, A. D., Reavley, N. J., Kelly, C. M., Kitchener, B. A., & Martin, A. (2016). Providing mental health first aid in the workplace: a Delphi consensus study. BMC Psychology, 4(1), 41. https://doi.org/10.1186/s40359-016-0148-x
2. Chopra, P. (2009). Mental health and the workplace: issues for developing countries. International Journal of Mental Health Systems, 3(1), 4. https://doi.org/10.1186/1752-4458-3-4
3. Dulal-Arthur, T., Siddiqui, M., Vaughan, B., Thomson, L., Bartle, C., Hassard, J., & Blake, H. (2023). TRANSFORMING WORKPLACE LEARNING: IMPLEMENTING MENTAL HEALTH FIRST AID PROGRAMMES AT WORK. 5279–5286. https://doi.org/10.21125/iceri.2023.1317
4. Hadlaczky, G., Hökby, S., Mkrtchian, A., Carli, V., & Wasserman, D. (2014). Mental Health First Aid is an effective public health intervention for improving knowledge, attitudes, and behaviour: A meta-analysis. International Review of Psychiatry, 26(4), 467–475. https://doi.org/10.3109/09540261.2014.924910
5. 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, e44838. https://doi.org/10.2196/44838
6. Keil K. (2019). Mental health first aid. The Canadian veterinary journal = La revue veterinaire canadienne, 60(12), 1289–1290.
7. Mantzios, M., Cook, A., & Egan, H. (2019). Mental health first aid embedment within undergraduate psychology curriculums: an opportunity of applied experience for psychology students and for enhancing mental health care in higher education institutions. Higher Education Pedagogies, 4(1), 307–310. https://doi.org/10.1080/23752696.2019.1640631
8. Rathnayaka, P., Mills, N., Burnett, D., De Silva, D., Alahakoon, D., & Gray, R. (2022). A Mental Health Chatbot with Cognitive Skills for Personalised Behavioural Activation and Remote Health Monitoring. Sensors, 22(10), 3653. https://doi.org/10.3390/s22103653
9. Singh, V., Kumar, A., & Gupta, S. (2022). Mental Health Prevention and Promotion—A Narrative Review. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.898009
10. World Health Organization. (2022, June 8). Mental disorders. Retrieved December 11, 2023, from https://www.who.int/news-room/fact-sheets/detail/mental-disorders
11. Smith, J. (2023). The Mental Health Crisis in Corporate America. California Business Journal. https://calbizjournal.com/the-mental-health-crisis-in-corporate-america/
12. Balcombe, L. (2023, October 27). AI Chatbots in Digital Mental Health. Informatics, 10(4), 82. https://doi.org/10.3390/informatics10040082
13. van der Schyff, E. L., Ridout, B., Amon, K. L., Forsyth, R., & Campbell, A. J. (2023, June 19). Providing Self-Led Mental Health Support Through an Artificial Intelligence–Powered Chat Bot (Leora) to Meet the Demand of Mental Health Care. Journal of Medical Internet Research, 25, e46448. https://doi.org/10.2196/46448
14. Dosovitsky, G., Pineda, B. S., Jacobson, N. C., Chang, C., Escoredo, M., & Bunge, E. L. (2020, November 13). Artificial Intelligence Chatbot for Depression: Descriptive Study of Usage. JMIR Formative Research, 4(11), e17065. https://doi.org/10.2196/17065
15. Rebelo, A. D., Verboom, D. E., dos Santos, N. R., & de Graaf, J. W. (2023, August). The impact of artificial intelligence on the tasks of mental healthcare workers: A scoping review. Computers in Human Behavior: Artificial Humans, 1(2), 100008. https://doi.org/10.1016/j.chbah.2023.100008
16. The Lancet Regional Health – Southeast Asia. (2022, October). Early intervention in mental health: The best bet. The Lancet Regional Health - Southeast Asia, 5, 100090. https://doi.org/10.1016/j.lansea.2022.100090
17. Le Glaz, A., Haralambous, Y., Kim-Dufor, D. H., Lenca, P., Billot, R., Ryan, T. C., Marsh, J., DeVylder, J., Walter, M., Berrouiguet, S., & Lemey, C. (2021). Machine Learning and Natural Language Processing in Mental Health: Systematic Review. Journal of medical Internet research, 23(5), e15708. https://doi.org/10.2196/15708