Paper Title
THERABOTICS: A MULTI-TASK AI-DRIVEN DIGITAL PSYCHOLOGICAL INTERVENTION SYSTEM WITH CALIBRATED RISK MODELING AND PRIORITY-BASED COUNSELOR SCHEDULING
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Registration ID: IJNRD_322038
Published ID: IJNRD2603290
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Keywords
Digital Mental Health, Multi-Task Learning, Risk Calibration, Conversational AI, Priority Queue Scheduling, University Mental Health, Anonymous Intervention Systems, Large Language Models, GloVe Embeddings, Clinical Assessment Automation.
Abstract
The deterioration of mental health among university students has reached a significant level worldwide, with research indicating that nearly 20% of students face clinically relevant symptoms of depression or anxiety. Although there is a broad range of digital health resources available, current systems predominantly operate as standalone conversational agents, lacking integration with institutional processes, continuous monitoring of risk, or smart routing to counselors. This paper introduces Therabotics, an anonymous, web-based mental health intervention platform created specifically for college settings. The platform features an innovative Multi-Task Inference Engine that concurrently conducts six psychological analysis tasks: emotion classification, estimation of emotion intensity, risk probability assessment, intent detection, evaluation of model confidence, and generation of therapeutic responses, all in a single call to a large language model. A custom sigmoid-based risk calibration layer refines raw probabilistic outputs by incorporating emotion intensity and longitudinal trend signals, producing clinically meaningful severity scores. Three validated clinical instruments, namely the PHQ-9, GAD-7, and GHQ-12, are natively embedded within the conversational interface, enabling passive and active psychological assessment without requiring formal clinical intake. A min-heap priority queue algorithm ensures that students with the highest clinical severity receive counselor appointments first, while a custom ten-dimensional GloVe embedding model clusters anonymous peer forum posts into five emotionally coherent support communities. A confidence-gated crisis detection mechanism prevents false-positive emergency escalations arising from ambiguous natural language inputs. Deployed on Vercel and Render with a Supabase PostgreSQL backend, Therabotics demonstrates that seamless integration of calibrated multi-task AI inference, priority-driven scheduling, and full anonymity preservation constitutes a technically feasible and clinically responsible approach to digital mental health intervention in academic institutions.
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How To Cite (APA)
Omaima, Safoora Saher, & 3Sania Mehwish Fatima (March-2026). THERABOTICS: A MULTI-TASK AI-DRIVEN DIGITAL PSYCHOLOGICAL INTERVENTION SYSTEM WITH CALIBRATED RISK MODELING AND PRIORITY-BASED COUNSELOR SCHEDULING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(3), c819-c850. https://ijnrd.org/papers/IJNRD2603290.pdf
Issue
Volume 11 Issue 3, March-2026
Pages : c819-c850
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Paper Reg. ID: IJNRD_322038
Published Paper Id: IJNRD2603290
Research Area: Other area not in list
Author Type: Indian Author
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2603290.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2603290
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