Poor mental health is the biggest health problem we face. Historic stigma, privacy concerns and ignorance have resulted in systematic underfunding of research hampering innovation. Consequently, there is an absence of consistent systematic data on which to base research and exploit new approaches e.g., AI techniques. Sylvie, Co-Opts product, is a potential solution that can improve mental health therapies. Co-Opts, with the help from the Aster Foundation, found that service-users, as well as friends and family of service-users in mental health therapies, thought that Sylvie could improve their experience of mental health therapies. Sylvie's initial focus was on helping clinicians' productivity. Service-users were getting the data only as a by-product of GDPR implications. This project's focus is to use design-thinking and user engagement to examine the implications of using Sylvie as part of mental health therapy from service-users and clinicians' perspective. We will explore three key issues with these two groups of users: 1. The impact of design choices on the device (e.g. shape, size, colour, patterns and hardware features) on the therapeutic alliance, with the aim to design a device that minimises any impact on this alliance. 2. How to present the data from one session to both groups without limiting ways of using the data. We have found that service-users and their family/friends creatively suggested a wide range of approaches and ways they might use the data, far more than we expected for the sample size. A key design objective is to encourage this adaptation. It is also clear that as treatment progresses service-users may prefer different presentations. Clinicians may also wish to present treatment data over time to the service user in different ways, depending on various factors (e.g. treatment points, goals, etc.). 3. How the data might be presented through time. This is important because the service-user's motivation to recover is perhaps the most critical factor in determining outcomes. Our research suggests that being able to see the progress on Sylvie is important for maintaining motivation, particularly after poor sessions, for service-users. We expect that the design, thinking, learning, and lessons we will take from this project will serve us well into the future as we do not expect this to be a one-off exercise, but rather become an integral part of the company's engagement with service-users and clinicians.

Poor mental health is the biggest health problem we face. Historic stigma, privacy concerns and ignorance have resulted in systematic underfunding of research hampering innovation. Consequently, there is an absence of consistent systematic data on which to base research and exploit new approaches e.g., AI techniques. Sylvie, Co-Opts product, is a potential solution that can improve mental health therapies. Co-Opts, with the help from the Aster Foundation, found that service-users, as well as friends and family of service-users in mental health therapies, thought that Sylvie could improve their experience of mental health therapies. Sylvie's initial focus was on helping clinicians' productivity. Service-users were getting the data only as a by-product of GDPR implications. This project's focus is to use design-thinking and user engagement to examine the implications of using Sylvie as part of mental health therapy from service-users and clinicians' perspective. We will explore three key issues with these two groups of users: 1. The impact of design choices on the device (e.g. shape, size, colour, patterns and hardware features) on the therapeutic alliance, with the aim to design a device that minimises any impact on this alliance. 2. How to present the data from one session to both groups without limiting ways of using the data. We have found that service-users and their family/friends creatively suggested a wide range of approaches and ways they might use the data, far more than we expected for the sample size. A key design objective is to encourage this adaptation. It is also clear that as treatment progresses service-users may prefer different presentations. Clinicians may also wish to present treatment data over time to the service user in different ways, depending on various factors (e.g. treatment points, goals, etc.). 3. How the data might be presented through time. This is important because the service-user's motivation to recover is perhaps the most critical factor in determining outcomes. Our research suggests that being able to see the progress on Sylvie is important for maintaining motivation, particularly after poor sessions, for service-users. We expect that the design, thinking, learning, and lessons we will take from this project will serve us well into the future as we do not expect this to be a one-off exercise, but rather become an integral part of the company's engagement with service-users and clinicians.

We are looking at the steps required to build a hardware and software based service to record and summarise mental health therapy sessions. It's important for a number of reasons * Mental Health trust CEOs expect COVID-19 to induce a significant surge in demand but services have been running close to 100% capacity during the lockdown due to the adoption of telehealth but there's no surplus capacity * Current vacancy rates for medial personnel in the NHS mental trusts runs at 12.4%, double that for the rest of the NHS exacerbating the situation * Less than 2m of the 12m a year in the UK with a diagnosable mental health condition get professional help which translates to a estimated cost to the UK of £100Bn (Chief medical officer NHS 2014) Therapists currently spend 1½ -2 hours a day writing up their notes. Automating the generation of a summary immediately at the end of a session could save an hour a day. The therapist just needs to add their therapeutic notes to the automated summary rather than recall the full session. The time saved could allow therapists to offer at least 1 extra session a day which would be a 20% boost in productivity for the NHS. Other benefits are the notes would be more consistent across sessions as unlike therapists, computers are more consistent than humans at boring tasks. They're not subject to the problems of poor human recall, cognitive bias and noise in human decision making. Our technology addresses the problems of privacy and confidentiality by giving control to the people in the room and not some remote cloud based solution with vulnerabilities to hackers. One of the more exciting possibilities is there may be therapeutic effects but that needs to be explored in a subsequent project. This project is about extending the technology we have already developed and finding partners in the therapist community to collaborate with to test our assumptions and produce an experimental prototype and a project plan that could provide the basis for a custom designed device to provide a platform for mental health therapists and patients. That would offer the potential to revolutionise training, mental health practice and eventually to revolutionise mental heath care the world over.