Towards Sustainable Workplace Mental Health: A Novel Approach to Early
  Intervention and Support
David W. Vinson Mihael Arcan David-Paul Niland Fionn Delahunty
Employee well-being is a critical concern in the contemporary workplace, as
highlighted by the American Psychological Association's 2021 report, indicating
that 71% of employees experience stress or tension. This stress contributes
significantly to workplace attrition and absenteeism, with 61% of attrition and
16% of sick days attributed to poor mental health. A major challenge for
employers is that employees often remain unaware of their mental health issues
until they reach a crisis point, resulting in limited utilization of corporate
well-being benefits. This research addresses this challenge by presenting a
groundbreaking stress detection algorithm that provides real-time support
preemptively. Leveraging automated chatbot technology, the algorithm
objectively measures mental health levels by analyzing chat conversations,
offering personalized treatment suggestions in real-time based on linguistic
biomarkers. The study explores the feasibility of integrating these innovations
into practical learning applications within real-world contexts and introduces
a chatbot-style system integrated into the broader employee experience
platform. This platform, encompassing various features, aims to enhance overall
employee well-being, detect stress in real time, and proactively engage with
individuals to improve support effectiveness, demonstrating a 22% increase when
assistance is provided early. Overall, the study emphasizes the importance of
fostering a supportive workplace environment for employees' mental health.