[PDF] Digital Mental Health Research Understanding Participant Engagement And Need For User Centered Assessment And Interventional Digital Tools eBook
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Mental health researchers are increasingly looking towards digital health tools to gather day-to-day lived experiences of people living with mental health conditions, by using apps and wearable devices complementing episodic clinical assessments. One of the key goals of collecting longitudinal real-world multimodal data (RWD) is to help build personalized computational models that may help explain the heterogeneity in clinical outcomes, mechanisms of action, and pathophysiology of mental health disorders across individuals.
Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future presents the foundations of digital therapeutics with a broad audience in mind, ranging from bioengineers and computer scientists to those in psychology, psychiatry and social work. Sections cover cutting-edge advancements in the field, offering advice on how to successfully implement digital therapeutics. Readers will find sections on evidence for direct-to-consumer standalone digital therapeutics, the efficacy of integrating digital treatments within traditional healthcare settings, and recent innovations currently transforming the field of digital therapeutics towards experiences which are more personalized, adaptable and engaging. This book gives a view on current limitations of the technology, ideas for problem-solving the challenges of designing this technology, and a perspective on future research directions. For all readers, the content on cultural, legal and ethical dimensions of digital mental health will be useful. Gives a comprehensive overview of the field of digital therapeutics and research on their efficacy, effectiveness, scalability and cost-effectiveness Introduces novel directions in which digital therapeutics are currently being extended, including personalized interventions delivered in real-time Reviews important considerations surrounding digital therapeutics, including how they can be monetized and scaled, ethical issues, cultural adaptations, privacy and security concerns, and potential pitfalls
Author : Marc N. Potenza Publisher : Oxford University Press, USA Page : 517 pages File Size : 40,69 MB Release : 2020 Category : Medical ISBN : 0190218053
"This book provides an academically oriented and scientifically based description of how technological advances may have contributed to a wide range of mental health outcomes, covering the spectrum from problems and maladies to improved and expanded healthcare services"--
Psychotic disorders are a group of severe mental disorders which affects 2-3% of the population and constitutes one of the leading causes of disability worldwide. Early intervention (EI) represents a major paradigm shift in psychiatric service and has been demonstrated to be effective in outcome improvement for first-episode psychosis (FEP) and at-risk mental state (ARMS). However, despite the promising findings, evidence has shown that a significant proportion of early psychosis patients still experience suboptimal clinical outcomes (such as high relapse risk, partial remission, early-onset treatment resistance, persistent negative symptoms, etc.), functional impairment and cognitive dysfunction. Further research clarifying the complex inter-relationships among symptomatology, psychosocial functioning, and cognitive deficits in the early illness course as well as evaluating effects of EI on further improvement on clinical, functional, and cognitive outcomes in patients with early psychosis would therefore facilitate development of next-generation EI service to enhance short-term treatment outcomes and long-term prognosis. This Research Topic aims to further our understanding of the complex relationships between symptomatology, psychosocial functioning and cognitive impairment in the early course of psychotic disorders, including first-episode psychosis (FEP) and at-risk mental state and to evaluate the effects of early intervention, either in terms of specific treatment modalities or in the comprehensive service framework, on further improvement in clinical, functional, and cognitive outcomes in patients with early psychosis.
Digital health is the convergence of digital technologies with health to enhance the efficiency of healthcare delivery and make healthcare more personalized and precise. These technologies generally focus on the development of interconnected health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to help healthcare professionals and their patients manage illnesses and health risks, as well as promote health and well-being. Digital tools play a central role in the most promising future healthcare innovations and create tremendous opportunities for a more integrated and value-based system along with a stronger focus on patient outcomes, and as such, having access to the latest research findings and progressions is of paramount importance. Digital Therapies in Psychosocial Rehabilitation and Mental Health introduces the latest digital innovations in the mental health field and points out new ways it can be used in patient care while also delving into some of the limits of its application. It presents a comprehensive state-of-the-art approach to digital mental health technologies and practices within the broad confines of psychosocial and mental health practices and also provides a canvas to discuss emerging digital mental health solutions, propelled by the ubiquitous availability of personalized devices and affordable wearable sensors and innovative technologies such as virtual and augmented reality, mobile apps, robots, and intelligent platforms. It is ideal for medical professors and students, researchers, practitioners of healthcare companies, managers, and other professionals where digital health technologies can be used.
The number of patients with chronic conditions, the costs for modern treatments, and life expectancy have been rising. At the same time, physician shortages are anticipated. These developments put a burden on current health systems. Digital health technologies can make health care systems more efficient, more personalized, and contribute to reaching underserved populations. Essential for the success of digital health technologies is large-scale and rigorous digital health data that facilitates health promotion, prevention, early diagnosis, and management of diseases. Digital health data empowers individuals to make better-informed decisions about their health. However, current health technologies often fail to engage users to generate, share, and understand health data. In this thesis, from the perspective of Human-Computer Interaction, we explore users' needs when interacting with digital health data. We introduce the relevance of digital health data, describe our contributions from four papers, and discuss the implications of our findings for HCI and digital health. We present the Digital Health Data Engagement Model (DHD-EM) and practical implications in the form of gulfs and bridges. Our model comprises the four stages lapse, generate, share, and understand. In the lapse stage, we identify reasons for a lapse of traditional health care and a shift towards digital health. This potentially happens when the health needs of patients are not fulfilled by health providers and patients consult online health communities for informational and emotional support. Our qualitative analysis of such communities showed when and how sub-communities for specific diseases emerge. In the generate stage, we explore physical and mental needs during the generation of health data. In three studies, a survey, a qualitative field study, and a usability study, we investigated the generation of medical images from the user perspective. The results suggest that carefully considering user preferences, e.g., in relation to sensitive body parts, and adhering to design principles paves the way for easy-to-use and trustworthy applications. In the share stage, we investigate motivations to share health data. Common barriers to health data sharing are a lack of motivation and technical difficulties. From a citizen science perspective, we show that, in times of crises, collective motives are prevalent and present design implications for fostering participation. Lastly, in the understand stage, we describe how individuals make sense of health data. In online health communities, sense-making processes are mainly facilitated in long threads about specific diseases. In digital health apps, disease-related background information increases the trustworthiness in the diagnosis provided by the app. Based on our studies, we identify gulfs in users' experience when engaging with their health data. We map each of the gulfs to one stage of the DHD-EM. To overcome those gulfs, we provide bridges with concrete guidance to improve the design of technologies for emerging digital health areas, such as mobile health, wearables, and online health communities. Our findings increase the impact of digital health technologies by allowing for a more nuanced understanding of the specific stages of users' engagement with digital health data. We foster the agency of an empowered patient who wants to understand their health and participate in decision-making. Adhering to this user-centered perspective, we argue that the proposed model and practical implications improve users' motivation and ability to share digital health data.