MindPulse: Employee Mental Health Detection and Attrition Prediction App

Abstract

Employee mental health problems and excessive
turnover are challenges that impact organizations at levels beyond
work quality, including productivity, workforce stability,
and overall morale. Conventional methods tend to be ineffective
in pre-emptively predicting and managing these problems with
any consistency because there are no accurate predictive tools
available. MindPulse is a machine learning (ML) and natural
language processing (NLP) application that uses AI to analyze
the well-being of employees and attrition risk. With BERT-based
sentiment analysis, it analyzes social media information to identify
initial indicators of mental distress, and gradient boosting models
analyze employee-specific m etrics t o f orecast a ttrition patterns.
By combining these insights, MindPulse allows organizations to
make timely interventions, creating a healthier workplace and
minimizing turnover. This new methodology improves workforce
retention efforts by delivering actionable, data-driven insights,
making it an essential tool for contemporary businesses.