Mental Health System Using Java, React.js and MySQL

Abstract

Mental health disorders such as stress, anxiety, emotional instability, and de-pression are increasing rapidly across different age groups due to academic pressure, workplace stress, financial instability, unhealthy lifestyle patterns, and excessive digital engagement. Early emotional monitoring and continuous psychological self-assessment are important for improving emotional well-being and preventing severe mental health conditions. This paper presents a full-stack Mental Health Monitor-ing and Sentiment Analysis System developed using Java Spring Boot, React.js, and MySQL. The proposed system allows users to perform daily mood tracking, main-tain emotional journals, complete self-assessment surveys, and receive personalized wellness recommendations based on emotional analysis. The system incorporates a sentiment analysis mechanism that evaluates textual journal entries using positive and negative emotional keywords. Based on emotional classification, the recommendation engine generates mindfulness activities, motivational exercises, relaxation techniques, and emotional wellness suggestions. The frontend interface is developed using React.js, while Java Spring Boot is used to implement RESTful backend services and business logic. MySQL database ensures secure and structured emotional data storage. Experimental evaluation conducted on multiple participants demonstrates that continuous mood tracking and journaling improve emotional awareness, reduce stress levels, and encourage healthier self-care habits. The proposed system offers a lightweight, privacy-focused, scalable, and accessible digital healthcare solution for emotional wellness monitoring and preventive mental healthcare support.

Introduction

Mental health is essential for emotional, psychological, and social well-being, influencing behavior, relationships, productivity, and decision-making. Modern challenges such as academic pressure, workplace stress, social isolation, financial difficulties, and unhealthy lifestyles have led to a rise in mental health issues. Many people avoid seeking professional help due to stigma, lack of awareness, financial constraints, or limited access to healthcare.

The proposed Full-Stack Mental Health Monitoring and Sentiment Analysis System, developed using Java Spring Boot, React.js, and MySQL, aims to provide a secure, accessible, and privacy-focused platform for preventive mental healthcare. It enables users to track daily moods, maintain emotional journals, analyze sentiments, visualize emotional trends, and receive personalized wellness recommendations while storing data securely in a local database.

The system addresses the limitations of existing mental health applications, such as dependence on cloud storage, privacy concerns, limited emotional analytics, lack of personalized recommendations, and poor offline accessibility. Its main objectives include emotional tracking, sentiment analysis, secure data management, dashboard visualization, and promoting self-awareness.

The research is supported by previous studies showing that mood tracking, emotional journaling, cognitive behavioral therapy (CBT), and sentiment analysis improve emotional regulation and mental well-being. The theoretical foundation combines mental healthcare, artificial intelligence, natural language processing, and full-stack web development to support preventive emotional wellness.

The system emphasizes the importance of continuous mental health monitoring, allowing users to identify emotional triggers, monitor mood changes, and improve stress management. Emotional journaling helps users express feelings, reduce stress, and gain self-awareness, while keyword-based sentiment analysis classifies journal entries into positive, neutral, or negative emotional states by calculating a sentiment score based on emotional keywords.

Conclusion

This paper presented a Full-Stack Mental Health Monitoring and Sentiment Analysis System developed using Java Spring Boot, React.js, and MySQL. The proposed system enables emotional self-monitoring through mood tracking, emotional journaling, senti-ment analysis, and dashboard visualization. The integration of full-stack web technologies with emotional analytics creates a scal-able and accessible digital healthcare platform that promotes emotional awareness and preventive mental healthcare practices. Experimental results indicate that continuous emotional tracking and journaling contribute positively toward emotional stability, stress reduction, and healthy emotional habits. The proposed system can serve as an effective digital emotional wellness platform while encouraging self-care and emotional self-awareness among users.

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Copyright

Copyright © 2026 Siddhi Umesh Kurhade, Vedant Santosh Kokane, Bhumika Sunil Temkar, Payal Ashok Ware, Prof. Khatal K. B. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.