Dinamika Pemanfaatan Artificial Intelligence dalam Deteksi Dini Kesehatan Mental Peserta Didik Global 2019–2025
DOI:
https://doi.org/10.62710/jppsb.pffnxn50Keywords:
Artificial intelligence, Education, Early detection, Mental health, StudentsAbstract
Mental health challenges among students have intensified in the digital age, particularly after the widespread adoption of online learning during and following the COVID-19 pandemic. Recent advancements in Artificial Intelligence (AI) present promising opportunities for the early identification of mental health risks by examining patterns in behavior, physiological responses, and language use. This study seeks to examine research trends between 2019 and 2025 concerning the application of AI for early mental health detection in educational contexts. A Systematic Literature Review (SLR) was carried out in accordance with PRISMA standards, involving the analysis of 70 peer-reviewed articles sourced from leading academic databases. The findings indicate four primary AI-based approaches: conversational AI systems, machine learning-driven behavioral monitoring, wearable-based sensing technologies, and emotion recognition through text analysis. The results demonstrate a notable growth in AI-focused mental health studies starting in 2020, reaching the highest volume in 2022–2023. Despite this progress, critical issues related to data protection, algorithmic fairness, and institutional preparedness continue to hinder practical implementation. This review underscores the importance of developing culturally sensitive AI frameworks, establishing robust ethical protocols, and aligning AI technologies with existing school counseling services to support responsible and effective adoption in educational settings.
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