Citation :

Kehinde Samuel Ikuyinminu, Francis Etang, 2024. "Evaluating the Effectiveness of AI in Data-Driven Interventions to Support Well-Being and Mental Health of Healthcare Workers" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 4: 33-40.

Abstract :

The well-being and mental health of healthcare workers are essential to the overall functionality of healthcare systems, yet they are often at risk due to the demanding nature of the profession. AI technologies, through predictive analytics, wearable devices, and natural language processing, offer continuous monitoring and early detection of mental health risks such as burnout. This article evaluates the effectiveness of artificial intelligence (AI)-driven, data-driven interventions aimed at supporting mental health and reducing stress-related issues in healthcare professionals and explores how AI systems can predict, prevent, and manage mental health challenges by analyzing physiological and behavioral data. Overall, the results indicate that AI has a great deal of promise to lessen mental health issues in healthcare settings; nevertheless, more investigation and ethical concerns are needed to maximize its use.

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Keywords :

Mental Health, Healthcare, AI Interventions.