# Towards Sustainable Workplace Mental Health: A Novel Approach to Early Intervention and Support

arXiv: https://arxiv.org/abs/2402.01592 · HTML: https://mlsanity.com/paper/2402.01592/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 2 Feb 2024.

## Builds on (most cited first, 2 of 2)

- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [OpenNMT: Open-source Toolkit for Neural Machine Translation](https://mlsanity.com/paper/1709.03815/) (2017)

## Built on by (most cited first, 2 of 2)

- [Evaluating Large Language Models for Anxiety, Depression, and Stress Detection: Insights into Prompting Strategies and Synthetic Data](https://mlsanity.com/paper/2511.07044/) (2025)
- [From Baselines to Preferences: A Comparative Study of LoRA/QLoRA and Preference Optimization for Mental Health Text Classification](https://mlsanity.com/paper/2604.00773/) (2026)

## Abstract (arXiv)

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.