Design of an AI-Based Decision Support System for Stress Reduction and Workplace Spirituality Enhancement in Educational Institutions

Rising stress levels and a decline in workplace spirituality among educators and students demand sophisticated and holistic well-being interventions. Although the existing systems focus on wearable-based monitoring and workshop-based intervention, these are relatively freestanding and suffer from limited personalization, long lag times, and short-term benefits. The propose an AI-Based Decision Support System (AI-DSS) that uses gradient boosting and temporal transformer model modalities to predict stress and recommend adaptive interventions that combine spirituality practices with stress-reduction techniques. The proposed system was initially implemented over 16 weeks with 412 participants, resulting in 89.5 % accuracy, an F1-score of 0.78, and an AUC of 0.86. The traditional techniques resulted in a 27 % reduction in stress markers, a 19 % decrease in burnout, and a 22 % increase in workplace spirituality. The results indicate that artificial intelligence-based close, personalized, and continuous monitoring significantly increases well-being, engagement, and institutional synergy, establishing an observational, data-linked structure for continuous, sustainable educational improvement.