AI-Driven Mental Health Assessment in the Evolving Workforce: Opportunities and Challenges
Keywords:
Artificial intelligence (AI), Mental health assessment, AI applications, Workplace mental health, Ethical considerations, Practical challenges, AI-driven assessment, Mental wellness, Evolving workforce and EmployerssAbstract
This literature survey research paper delves into the use of artificial intelligence (AI) for mental health assessment in the context of the evolving workforce. It provides an overview of the current state of AI applications in mental health assessment, examining the opportunities and challenges associated with its implementation. The paper reviews recent studies and developments in the field, discussing the potential benefits of AI-driven mental health assessment in the workplace, as well as the ethical and practical challenges that need to be addressed. The findings aim to contribute to a better understanding of the potential impact of AI in mental health assessment, offering insights for policymakers, healthcare professionals, and employers on how to effectively leverage AI to promote mental wellness in the evolving workforce.
References
1] D’Alfonso, Simon. "AI in mental health." Current Opinion in Psychology 36 (2020): 112-117.
[2] Abd-Alrazaq, Alaa, et al. "The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review." NPJ Digital Medicine 5.1 (2022): 87.
[3] Majumdar, Bishakha. "Mental Health and the Working Professional." Handbook of Health and Well-Being: Challenges, Strategies and Future Trends. Singapore: Springer Nature Singapore, 2022. 233-256.
[4] Bell, Sarah, et al. "Near-Term Digital Health Predictions: A Glimpse into Tomorrow’s AI-driven Healthcare." Telehealth and Medicine Today 8.5 (2023).
[5] Anuja Siba, et.al. “Mental Health and Well-being of School Students”. The National Council of Educational Research and Training https://ncert.nic.in/pdf/Mental_Health_WSS_A_Survey_new.pdf
[6] Rathnayaka, P., Mills, N., Burnett, D., De Silva, D., Alahakoon, D., & Gray, R. “A mental health chatbot with cognitive skills for personalized behavioral activation and remote health monitoring.” Sensors, (2022): 22(10), 3653.
[7] Kolenik, T., & Gams, M. “Intelligent cognitive assistants for attitude and behavior change support in mental health: state-of-the-art technical review.” Electronics, (2021): 10(11), 1250.
[8] Mehraj, T., & Baba, A. M. “Scrutinizing artificial intelligence-based career guidance and counselling systems: an appraisal.” International journal of interdisciplinary research and innovations, (2019) : 7(1), 402-411.
[9] Ayanouz, S., Abdelhakim, B. A., & Benhmed, M. “A smart chatbot architecture based NLP and machine learning for health care assistance.” In Proceedings of the 3rd international conference on networking, information systems & security , (2020, March) : (pp. 1-6).
[10] Ray, A., Halder, S., & Goswami, N. “Academic career development stress and mental health of higher secondary students-an Indian perspective.” International Journal of Educational Psychology, (2012).: 1(3), 257-277.
[11] Tewari, A., Chhabria, A., Khalsa, A. S., Chaudhary, S., & Kanal, H. “A survey of mental health chatbots using NLP.” In Proceedings of the International Conference on Innovative Computing & Communication (ICICC), (2021, April).
[12] Islam, M. N., Khan, S. R., Islam, N. N., Rezwan-A-Rownok, M., Zaman, S. R., & Zaman, S. R. “A mobile application for mental health care during covid-19 pandemic: Development and usability evaluation with system usability scale.” In Computational Intelligence in Information Systems: Proceedings of the Computational Intelligence in Information Systems Conference (CIIS 2020) (pp. 33-42). Springer International Publishing. (2021).
[13] Joshi, K., Goel, A. K., & Kumar, T. “Online career counsellor system based on artificial intelligence: An approach.” In 2020 7th International Conference on Smart Structures and Systems (ICSSS) (pp. 1-4). IEEE. (2020, July).
[14] Sau, A., & Bhakta, I. “Screening of anxiety and depression among seafarers using machine learning technology” Informatics in Medicine Unlocked, (2019).:16, 100228.
