Akademik Veri Yönetim Sistemi
İZMİR AKADEMİ DERNEĞİ (IZMIR ACADEMY ASSOCIATION), İzmir, 2026
Behavioral addictions have become one of the defining public health and societal challenges of the digital age. Problematic gaming, gambling, compulsive social media engagement, online shopping dependency, and other technology-mediated addictive behaviors increasingly affect individuals across all age groups and socioeconomic backgrounds. Unlike substance-related disorders, behavioral addictions are often deeply embedded within everyday digital ecosystems, making them more difficult to identify, regulate, and manage through conventional clinical approaches alone. Their consequences extend far beyond the individual level, influencing family structures, educational performance, workplace productivity, psychological well-being, and broader social resilience. At the same time, rapid advances in digital technologies and artificial intelligence have opened unprecedented opportunities for addressing these challenges. The convergence of wearable sensing systems, mobile health applications, digital therapeutics, conversational AI, virtual and augmented reality, multimodal behavioral analytics, and adaptive intervention systems is fundamentally reshaping how behavioral addictions can be detected, monitored, prevented, and treated. These developments have created a new interdisciplinary landscape in which psychology, psychiatry, neuroscience, computer science, data science, human-computer interaction, and public health increasingly intersect. This book was developed with the aim of providing a comprehensive and integrated perspective on this rapidly evolving field. It brings together the clinical foundations of behavioral addictions with contemporary computational and technological approaches that are transforming addiction management. Throughout the chapters, the reader will encounter discussions ranging from neurobiological reward mechanisms and cognitive-behavioral models to artificial intelligence-driven risk prediction systems, reinforcement learningbased intervention strategies, digital phenotyping, conversational agents, telehealth platforms, and multimodal data fusion architectures. Ethical, legal, economic, and societal dimensions are also examined in depth, recognizing that technological capability alone cannot ensure effective or responsible healthcare transformation. A particularly meaningful context for this book is the growing global awareness surrounding addiction prevention and digital mental health policies. In this regard, Türkiye’s declaration of 2026 as the “Year of Independence” within the national fight against addiction represents a significant and symbolic milestone. This initiative reflects a broader societal commitment to strengthening individual resilience, promoting healthy digital behaviors, supporting preventive healthcare strategies, and mobilizing interdisciplinary solutions against various forms of dependency. The emphasis on “independence” extends beyond substance addiction and highlights the importance of psychological, social, and digital well-being in modern societies. The vision underlying this declaration aligns closely with the themes explored throughout this book: empowering individuals through early intervention, personalized care, community support, and responsible technological innovation. The preparation of this book was motivated by the recognition that behavioral addiction management can no longer be approached solely through traditional clinical frameworks. Modern intervention ecosystems increasingly require scalable, data-driven, and continuously adaptive systems capable of supporting individuals in real-world environments. Artificial intelligence and digital technologies offer immense promise in this regard, yet they also introduce important challenges involving privacy, transparency, algorithmic bias, explainability, accessibility, and long-term engagement. Therefore, a balanced perspective is essential one that neither overstates technological capabilities nor overlooks their transformative potential. Another important objective of this book is to encourage interdisciplinary collaboration. Researchers developing machine learning algorithms, clinicians working directly with patients, policymakers shaping national health strategies, and technology developers building digital health platforms often operate within separate domains despite pursuing highly interconnected goals. By presenting concepts, methods, opportunities, and limitations within a unified framework, this book seeks to foster dialogue across vi disciplines and contribute to the development of more human-centered, ethical, and effective digital addiction management ecosystems. The future of behavioral addiction management will likely be shaped by increasingly intelligent and personalized systems capable of understanding human behavior in dynamic contexts. Generative AIsupported therapeutic agents, multimodal digital twins, adaptive behavioral intervention systems, and proactive public health infrastructures may soon become integral components of everyday mental healthcare. However, technological progress must remain guided by clinical validity, ethical responsibility, inclusiveness, and societal benefit. The ultimate goal should not merely be technological sophistication, but the enhancement of human well-being, autonomy, and quality of life. It is hoped that this book will serve as a valuable resource for researchers, clinicians, graduate students, healthcare professionals, policymakers, and practitioners interested in the intersection of behavioral addictions, digital health, and artificial intelligence. More importantly, it is hoped that the discussions presented here will contribute to the broader global effort to build healthier, safer, and more resilient digital societies.