This is a proposal for a partnership between engineering and physical science (EPS) researchers - initially in the Universities of Manchester, Nottingham, Sheffield, Lancaster and York - and the MindTech Healthcare Technology Cooperative. The aim is to explore the potential for technology to transform the management and treatment of mental health conditions, identifying underpinning EPS research challenges, and working together to address them. Mental health already accounts for 13% of the NHS budget (the highest proportion for any disease area, and growing rapidly) and is a major cause of reduced quality of life. Most care is in the community, but most of the cost is associated with unplanned hospital admissions resulting from inadequate/ineffective care. There is great potential for technology to transform care in the community - improving diagnosis/stratification, supporting self-care, involving family and friends more effectively, and providing timely prompts and alerts for healthcare professionals. If this potential is to be realised, there are, however, significant EPS challenges to be addressed - in sensing systems, information management, data analytics and human-computer interaction. The model we propose aims to build an integrated community of EPS researchers and users, who will co-develop an EPS research agenda grounded in a clear clinical need, informed by the perspectives, experiences and needs of patients/carers, healthcare commissioning/provider organisations, healthcare professionals and industry (both technology and healthcare, ranging from SMEs to large multinational companies). The partnership will focus on four broad clinical areas of major societal importance, aligned with the MindTech HTC agenda: serious mental illness, mood and affective disorder, dementia, and developmental disorders - each with clinical leadership - drawing on mental health expertise in both Nottingham (the MindTech HTC) and Manchester. We currently identify four areas of challenging EPS research required to underpin the development of effective technologies for managed self-care of mental health conditions: sensing systems for acquiring rich, 'real-time' longitudinal data (new sensing technologies, sensor systems); information management methods for incrementally integrating and linking heterogeneous information and data (integrating and linking data from different sources, information representation); data analytics for extracting predictive outcome models, particularly from temporal data (modelling longitudinal data, modelling populations of temporal models, image computing; and human-computer interaction methods for the managed self-care setting (collaborative decision-support).

Global and local (UK) populations are ageing and this has contributed to an increase in demand for health and welfare services. Chronic and long-term conditions are also on the increase, leading to increased costs of health and social care and wide-ranging changes to the nature of health interventions. As a result, it is increasingly desirable to keep people out of hospital, treating people nearer to, or in their home. For reasons of cost, convenience and dignity it is also sometimes desirable that patients engage in self-care or carer-delivered care. Care independence has long been a feature of some diagnosis and treatment regimes: most medications are taken by the patient themselves; diabetic patients regularly monitor blood sugar levels and inject themselves. This work aims to extend these concepts of self care to a boarder range of health conditions, and their associated technologies, that are not currently expected to be delivered by the patient or their carer. The network consists of four academic centres: * Cambridge Engineering Design Centre, University of Cambridge; * CHI+MED, Collaboration led by University College London (UCL); * Loughborough Design School, Loughborough University and * Helen Hamlyn Centre for Design, Royal College of Art and three Healthcare Technology Cooperatives (HTCs) * Devices for Dignity, (D4D) Sheffield Teaching Hospitals NHS Foundation Trust; * MindTech HTC, Nottinghamshire Healthcare NHS Trust and Institute of Psychiatry and * Brain Injury HTC, Cambridge Universities Hospitals NHS Foundation Trust. This network of design researchers and healthcare technology specialists will carry out a series of design-led pilot projects to explore solutions to care independence challenges. The aim of the pilot projects is to encourage innovation in order to find radical new ways of using technologies to allow sustainable patient independence while maintaining clinical quality, safety and patient and carer experience while reducing costs. The pilot projects will be need driven and will be selected as part of the networking with NIHR Healthcare Technology Cooperatives. The pilot project outputs will be conceptual designs that can be further developed (not funded by the network) or definitions of research need that can be developed into research proposals.

One in ten children in the UK are affected by a mental health problem, causing significant distress to them and their families. Where these problems endure, they can hold children back from reaching their potential in school and the workplace, and from experiencing good physical and mental health into adulthood. Financially, the personal cost of mental illness is £41.8 billion per year in England. In light of this burden to children, families, and society, there is a pressing need for a pathway that can prevent mental health problems as early as possible. We now know that many of the factors that shape risk and resilience to mental health problems have their roots in the first years of life. Children who start off more vulnerable can go on to develop initial difficulties, which can then progress into more established problems. Developing better ways to identify which children and families are likely to benefit from support would help professionals to work with families to take a proactive approach early on. By supporting families to provide responsive, consistent care, we can help to build a strong foundation for mental health. Doing this in the first years of life, when children's development is especially responsive to their early experiences, relationships, and environment, could unlock huge potential to shape the course of children's long-term mental health. Research also suggests that investing early makes economic sense as children are less likely to need more intensive supports later on in life. This promise of a strong start in life has made children's first 1001 days a global health priority, as reflected in the recent World Health Organisation 'Nurturing Care' framework for early childhood development. Yet the insights we have from decades of research in child development have not translated into the public health strategies we need to promote early mental health in the UK. There are two critical factors underlying this gap. Firstly, we lack a way to identify early risk and resilience for mental health problems in very young children that is quick, effective and acceptable to families and professionals. Secondly, early childhood programmes that show promise in preventing problems when they are tested in controlled research studies typically fail to show the same success when they are delivered in real-world services. Although these programmes have been carefully developed they are often too complicated and expensive to deliver at scale. This fellowship will use cutting-edge techniques in epidemiology and data science to develop a tool to identify early mental health needs in very young children and a pathway for more personalised supports. It will bring together the best evidence available from previous studies of early interventions so we can identify which practices and strategies in these programmes tend to be most effective. Stripping these programmes back to their most important building blocks will allow us to work together with families and professionals to redesign how they are delivered so they fit better into family life, respond to families' needs and priorities, and are feasible and practical to deliver. This will be done by testing different approaches out quickly, figuring out what does and doesn't work, and adapting the approach based on this learning. We will do this in the UK as well as undertaking initial piloting in South Africa to ensure the principles and approaches we develop are flexible and can be adapted appropriately to different resource and cultural contexts. The ultimate goal of this research is to co-develop a flexible prevention pathway for early mental health problems that is relevant to the challenges facing families and communities and is responsive to the needs of family life and the services in which they are delivered. This research has the potential to provide the breakthrough impacts needed to change the course of children's mental health.

Currently in the UK, it is estimated that over 2.5 million of neurodiverse adults have not received a diagnosis and therefore struggle to access care. The most common neurodevelopmental conditions, attention deficit hyperactivity disorder (ADHD) and autism (ASD), affect 5% and 1% of children and adults in the UK - on average one child per classroom. Nowadays, the understanding of autism and ADHD has greatly increase. However, a lot of adults and children have not received a diagnosis. Within the UK healthcare system, without a diagnosis, these patients cannot access the care they need. Having ADHD or autism often negatively impacts many aspects of life such as employment, relationship, or school. Studies have shown that adults with undiagnosed and untreated ASD/ADHD are more likely to have educational problems, mental health issues, depression and anxiety, are more likely to commit crimes and abuse substances, are more likely to divorce, be unemployed or commit suicide. These aspects are worse when ASD/ADHD is not diagnosed but can be reduced with early identification and effective support. Diagnosing ASD/ADHD as early as possible is of utmost importance in reducing some of these long terms risks for adults living with these conditions. Recent governmental reports have highlighted the importance of having access to diagnosis and care for these conditions. In order to successfully address these priorities, it is important that research first identifies the costs of living with undiagnosed ASD/ADHD. Previous studies which have looked into the cost and impact of undiagnosed mental health on the individuals, society and economy have shown that the cost of not diagnosing and treating mental health issues was higher than the cost of running services for these issues. This led to the creation of a national NHS service (IAPT), a service helping adults with mental health issues. No research to date has been done on the cost of undiagnosed ASD/ADHD. This new study will highlight the economic and societal cost of undiagnosed ASD/ADHD in order to give policy makers and healthcare providers the necessary information to justify funding appropriate services. Most specifically, the project will answer two questions: 1. What are the long-term risks and impacts (for instance: higher rate of divorce, substance abuse, unemployment) associated with undiagnosed ASD/ADHD? 2. What are the individual, societal and economic costs of these associated risks? To answer these questions, first a literature review of published science articles will summarise the studies which looked into the risks associated with undiagnosed ASD/ADHD. Then I will conduct questionnaires and interviews with adults with ASD/ADHD to see whether the risks highlighted in the literature review reflect real life struggles. These two studies will create a comprehensive summary of the risks associated with undiagnosed ASD/ADHD. Once this summary is completed, an economic evaluation of the costs of these risks will be conducted with undiagnosed adults. In order to understand what these costs mean, they will be compared to three groups, one groups of adults diagnosed with ASD/ADHD in childhood, one group of adults diagnosed in childhood and one group of adults diagnosed in adulthood. This will allow us to establish the true cost of the impact of receiving a diagnosis as early as possible. A group of adults with ASD/ADHD will feedback on all the different tasks of this project to ensure it represents real-life experiences. Many people argue that having conditions such as ASD/ADHD cost a lot more to society than neurotypical individuals (for example, extra support in class). However, this study argues that the cost of not identifying individuals with such difficulties, is likely to cost more in the long term (for example while extra support in class has a cost, school underachievement and unemployment will cost much more to an individual and society in the long run).

The current extent of ill mental health is estimated to cost the UK economy £105 billion per year in healthcare expenditure and lost revenue. Addressing mental health is therefore a clearly articulated priority for government. The broad use of ICT services, social media and smartphone applications has an increasingly important role to play in the delivery of clinical mental health services and in supporting societal mental health and wellbeing more generally. Indeed, for large sections of the population, and younger people in particular, the use of Social Computing technologies such as Facebook, Twitter and YouTube is already informally entwined with every facet of everyday life including health and wellbeing. The expectation by the healthcare community, and by commercial software developers, therefore is that digital mobile and social technology can provide compelling, scalable and convenient access to information, social and peer support, as well as therapy and shared self-monitoring tools and services. However, there are a numerous difficult challenges associated with the design, deployment, use and evaluation of such technology in mental health settings which must be solved using multidisciplinary, rigorous and scientific methods. The research field of Social Computing broadly focusses on the user-centred design, implementation, use, and evaluation of technologies that consider social context in an increasingly digitally-connected society. The UK's Social Computing research community therefore has a wealth of experience and expertise that is relevant to, but not typically directed at, mental health services and systems. This network will address issues of support, coordination and collaboration in this context and bring together two communities: (i) engineering and physical sciences (EPS) researchers under the broad, and inclusive, banner of Social Computing covering sub-fields of Human Computer Interaction (HCI), ubiquitous and mobile computing, and web science (ii) clinical scientists, healthcare professionals, commercial partners, charities, user groups and patients who are concerned with mental health and wellbeing. The network will work closely with the NIHR MindTech Healthcare Technology Co-operative (HTC) centre to engage in a range of coordinated scientific, technological, management and clinical activities to realise its overarching aim of pump-priming future UK capacity to deliver internationally-leading research at the boundaries between social computing and mental healthcare.