Dialogue Analysis for Early Screening and Tailored Integrated Support of Students at Risk for Emotional and Behavioral Difficulties: A Systematic Review

This project aims to systematically review existing research on the use of dialogue analysis for the early identification of students at risk for emotional and behavioral difficulties and the development of tailored, integrated support strategies. Emotional and behavioral difficulties among children and adolescents can negatively affect psychological well-being, academic performance, interpersonal relationships, and school adjustment. Early identification and timely intervention are therefore essential. Conventional screening approaches often rely on standardized questionnaires, self-reported symptoms, teacher observations, and periodic psychological assessments. Recent advances in artificial intelligence (AI), particularly machine learning and natural language processing (NLP), have created new opportunities to identify psychological and behavioral indicators from linguistic and conversational data. This systematic review will examine how dialogue-based approaches, including counseling conversations, interviews, written communication, and digital interactions, have been used to identify emotional and behavioral difficulties among school-aged children and adolescents. Particular attention will be given to the types of dialogue data analyzed, computational and analytical methods employed, psychological and behavioral indicators identified, and the reported effectiveness of these approaches. The review will also investigate how findings from dialogue analysis may inform individualized interventions, school-based mental health services, and integrated support systems involving teachers, counselors, families, and mental health professionals. Relevant studies will be identified through a systematic literature search, screened according to predefined eligibility criteria, and synthesized using an appropriate evidence synthesis approach. The review process will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. The expected outcomes include a comprehensive synthesis of current evidence, identification of methodological strengths and limitations, and recommendations for future research and practice. Ultimately, this review seeks to provide an evidence-based foundation for developing dialogue-informed early screening approaches and tailored, integrated support systems for students experiencing emotional and behavioral difficulties.