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

Sourav Banerjee; Ayushi Agarwal; Ayush Kumar Bar

doi:doi:10.11648/j.ajsea.20241201.11

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

Sourav Banerjee^*, Ayushi Agarwal, Ayush Kumar Bar

Published in American Journal of Software Engineering and Applications (Volume 12, Issue 1)

Received: 18 December 2023 Accepted: 29 December 2023 Published: 11 January 2024

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Abstract

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.

Published in	American Journal of Software Engineering and Applications (Volume 12, Issue 1)
DOI	10.11648/j.ajsea.20241201.11
Page(s)	1-4
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

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

References

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[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
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[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
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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

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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

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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

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@article{10.11648/j.ajsea.20241201.11,
  author = {Sourav Banerjee and Ayushi Agarwal and Ayush Kumar Bar},
  title = {Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being},
  journal = {American Journal of Software Engineering and Applications},
  volume = {12},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.ajsea.20241201.11},
  url = {https://doi.org/10.11648/j.ajsea.20241201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20241201.11},
  abstract = {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.
},
 year = {2024}
}

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TY  - JOUR
T1  - Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being
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AU  - Ayushi Agarwal
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T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
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AB  - 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.

VL  - 12
IS  - 1
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Author Information

Sourav Banerjee

Datalabs, United We Care, Gurgaon, India

Contact Email
Ayushi Agarwal

Datalabs, United We Care, Gurgaon, India

Contact Email
Ayush Kumar Bar

Datalabs, United We Care, Gurgaon, India

Contact Email

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Plain Text BibTeX RIS

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

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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

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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

Copy | Download

@article{10.11648/j.ajsea.20241201.11,
  author = {Sourav Banerjee and Ayushi Agarwal and Ayush Kumar Bar},
  title = {Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being},
  journal = {American Journal of Software Engineering and Applications},
  volume = {12},
  number = {1},
  pages = {1-4},
  doi = {10.11648/j.ajsea.20241201.11},
  url = {https://doi.org/10.11648/j.ajsea.20241201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20241201.11},
  abstract = {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.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being
AU  - Sourav Banerjee
AU  - Ayushi Agarwal
AU  - Ayush Kumar Bar
Y1  - 2024/01/11
PY  - 2024
N1  - https://doi.org/10.11648/j.ajsea.20241201.11
DO  - 10.11648/j.ajsea.20241201.11
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 1
EP  - 4
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20241201.11
AB  - 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.

VL  - 12
IS  - 1
ER  -

Copy | Download