Abstract
Overview and Aims The current thesis is part of the Ph.D. research endeavor, XXXVII cycle, con- ducted in partnership with the Padova Neuroscience Center and the Depart- ment of General Psychology at the University of Padova. The work conducted for the present Ph.D. research is to be intended as part of the broader and multi- centered EXPERIENCE project (The ”Extended-Personal Reality”: augmented recording and transmission of virtual senses through artificial-intelligence), funded by the European Union’s Horizon 2020 research and innovation program (grant agreement No. 101017727). The EXPERIENCE project has the general aim of developing an affordable and easy-to-use hardware and software technology allowing anyone to create their own virtual reality (VR) environment. Further- more, the University of Padova leads the work package focused on evaluating the clinical application of the EXPERIENCE technology in supporting the diag- nosis and treatment of mental disorders. Within this framework, I contributed to designing the experimental protocols, interpreting and disseminating the find- ings, and was responsible for data collection, processing, and analysis. The present Ph.D. research aims to develop innovative, multi-modal diag- nostic tools that address the complexities and heterogeneity of depression. The research work presented here seeks to advance the field of mental health diag- nostics by combining VR and psychophysiological methods, with the aim to cre- ate a more nuanced and effective framework for diagnosing depression, paving the way for more personalized interventions and improved patient outcomes. OVERVIEW AND AIMS This brief overview provides a summary of the content that will be explored in greater detail in each chapter of this dissertation. Chapter 1 provides an ex- ploration of the challenges and limitations in the current diagnostic methods for depressive conditions, and introduces innovative approaches aimed at im- proving the accuracy and objectivity of depression diagnostics. Depression, be- ing a highly heterogeneous and complex condition, often escapes precise de- tection with traditional methods such as clinical interviews and self-reported questionnaires. These approaches, while validated, suffer from inherent biases that can result in misdiagnosis and inappropriate treatment. The chapter begins by defining depression, and discusses its current epidemiology, underlining its widespread prevalence, recurrent nature, and global impact. The limitations of traditional diagnostic methods are then examined, emphasizing the inadequa- cies of broad diagnostic categories in capturing the diversity of depressive symp- toms and the frequent reliance on subjective measures. This is compounded by issues in primary care settings, where under-recognition and over-diagnosis of depression are prevalent. In response to these limitations, the chapter intro- duces novel methods that leverage advancements in psychophysiological tech- niques. These techniques, by capturing real-time, objective data, hold promise for enhancing the precision of depression diagnoses. Furthermore, the chapter highlights the potential of integrating virtual reality (VR) with psychophysio- logical measures to create controlled, immersive environments that can offer deeper insights into behavioral and emotional responses. In Chapter 2, the potential of VR as a groundbreaking tool in mental health is explored. The chapter begins with the definition and historical development of VR technology, tracing its origins from early devices like the stereoscope in the 19th century to modern innovations such as the Oculus Rift. It highlights VR’s immersive capabilities, explaining how sensory feedback mechanisms (e.g., vi-...