Paper Key : IRJ************927
Author: Babatunde Stephen Adedeji
Date Published: 04 Jan 2025
Abstract
The convergence of Artificial Intelligence (AI) with therapeutic practices has opened new pathways for addressing complex challenges in trauma, addiction, and mental health management. This paper explores integrative strategies that combine the precision of AI-driven analytics with the empathy and adaptability of traditional and modern therapeutic interventions. As mental health crises continue to escalate globally, innovative solutions that enhance treatment efficacy, accessibility, and personalization are imperative. The study examines AI's role in revolutionizing mental health care, focusing on predictive modelling, natural language processing (NLP), and machine learning techniques for early diagnosis, personalized treatment planning, and continuous progress monitoring. AI-powered tools, such as chatbots and virtual therapists, provide scalable solutions for addressing mental health needs, particularly in under-resourced areas. These tools are integrated with evidence-based therapies, including Cognitive Behavioural Therapy (CBT), trauma-focused interventions, and addiction management protocols, to create hybrid treatment models. Additionally, the paper explores the ethical and practical considerations of deploying AI in mental health care, emphasizing the need for transparency, data privacy, and cultural sensitivity. Case studies illustrate successful applications of integrative strategies, such as AI-assisted relapse prediction in addiction recovery programs and real-time emotion analysis for trauma therapy. By synthesizing advancements in AI with therapeutic methodologies, this paper provides a framework for creating holistic, patient-centered approaches to mental health management. These integrative strategies promise to improve access, reduce stigma, and achieve better outcomes for individuals navigating trauma, addiction, and mental health challenges.
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