Integrating SCAB and PRIS into Behaviour Classification for Online Mental Health Conversations

Abstract Background: The intersection of natural language processing (NLP), mental health, and online safety has become an urgent area of research, particularly as conversational AI systems are increasingly integrated into public and private digital spaces. The SafeSpacesNLP framework, enriched by the SCAB (Synthetic Consciousness Assessment Battery) protocol and the PRIS (Psychosis Risk Interaction Score) metric, offers new possibilities for evaluating ethical risk and harm potential in human–AI interactions. Objective: This paper examines the integration of human-in-the-loop (HITL) systems into SafeSpacesNLP, focusing on socio-behavioral analysis, risk detection, and the mitigation of conversational harms. The goal is to evaluate how SCAB and PRIS extend traditional NLP moderation methods by introducing structured behavioral monitoring and psychosis-risk detection. Methods: A multi-method design was employed, including a literature review of NLP and mental health corpora, comparative analysis of HITL approaches in clinical contexts, and case study evaluation of SafeSpacesNLP in online mental health forums. The SCAB protocol was applied across six behavioral domains (coherence, truthfulness, alignment, empathy, agency, harm), while PRIS introduced a session-level scoring system for psychosis-risk potential. Results: Findings indicate that HITL models augmented with SCAB and PRIS outperform conventional moderation pipelines in both sensitivity to harm signals and contextual accuracy. Case study analysis revealed early detection of delusional reinforcement loops and anthropomorphized AI responses that standard toxicity classifiers overlooked. Conclusion: Integrating SCAB and PRIS into SafeSpacesNLP creates a robust framework for balancing ethical safeguards, user trust, and computational efficiency. This hybrid model enables proactive detection of conversational risks while maintaining human oversight. Future directions include real-world deployment, cross-cultural adaptation, and the refinement of SCAB and PRIS for both consumer-facing and enterprise AI systems. Keywords: SafeSpacesNLP, SCAB, PRIS, human-in-the-loop, NLP, mental health, online safety, AI ethics