UpliftX a digital scalable mental health intervention AI-platform for remote group therapy with personalised client and clinician app

全世界约有五分之一的人患有心理健康问题。即使在英国也没有足够的治疗师，而在其他国家，情况要糟糕得多。我们的团队开发了第一个计算机化的心理健康应用程序，该应用程序被NICE批准用于NHS。然而，我们已经了解到，对大多数人来说，人类治疗师与个人应用程序的结合更有吸引力。我们还了解到，个性化干预（根据用户的个性，需求，偏好等）可以改善结果。最近，我们进行了研究，并在随机临床试验（RCTs）中证明，远程小组治疗可以非常划算。（有些，我们已经开发并在随机对照试验中进行了测试）成为一个尖端的心理健康数字平台，和个性化的远程团体治疗，包括：* 升级我们的数字平台AiLeap，实现远程团体治疗的创建和交付，使用AI/机器学习帮助治疗师和参与者/患者进行个性化治疗：* StratCare：将患者分为最有效的组（根据需求，个性，偏好，症状）。* AiOracle：在基线时监测患者的进展和反馈，并在每次治疗后为“未达标”患者提供建议和帮助。BioView通过分析面部变化（来自计算机/移动的摄像头的视频），包括来自肤色变化的心率变异性（HRV），监测参与者/患者的压力和情绪状态。它将为患者和治疗师提供反馈（例如，患者如何对特定刺激做出反应），也可以用作生物反馈。个性化应用程序：根据参与者/患者的需求，为他们的数字应用程序添加个性化技能。*使用人工智能/机器学习分析所有患者的数据，以发现哪种类型的特定方法/技能对特定类型的患者最有帮助;并改善未来的个性化。我们将通过进行两项RCT来测试/证明这一点。我们将分析第一个随机对照试验的数据（约5,000次），以创建个性化的干预措施，并在第二个随机对照试验中进行测试。一名治疗师将能够远程并行治疗多名患者，多次提高成本效益和结果。患者将在家中接受治疗。UpLiftX将吸引全球医疗保健提供者和保险公司，降低成本和等待名单，并实现更多的治疗。UpLiftX旨在适应英国和美国现有的医疗保健服务（例如NHS，美国退伍军人事务部）。它将在NHS信托设置与等待名单的病人进行测试。我们预计UpLiftX将使医疗保健提供者能够在相同数量的治疗师的情况下为更多的患者提供有效的治疗，并大大降低每位患者的成本。

About 1:5 worldwide suffers from mental health problems. Even in the UK there are not enough therapists, and in other countries the situation is much worse. Our team developed the first computerised mental-health application which was approved by NICE for the NHS. However, we have learnt that for most people a combination of a human therapist together with a personal app is more appealing. We've also learnt that personalised interventions (according to users' personality, needs, preferences, etc) can improve outcomes. Recently, we've researched, and proved in Randomised Clinical Trials (RCTs), that remote group therapy can be very cost-effective.In UpLiftX we'll be integrating several innovations (some, we've already developed and tested in RCTs) into a cutting-edge mental health digital platform, and personalised remote group therapy, including:* Upgrading our digital platform AiLeap, enabling creation and delivery of remote group therapy, with personalised app for each participant.Using Ai/Machine-learning to help therapists and participants/patients with personalised treatment by:* StratCare: stratifying patients to the most effective group (according to needs, personality, preference, symptoms).* AiOracle: monitoring patient progress and feedback at baseline, and following each session with recommendations and help for patients 'not-on-track'.* BioView for monitoring participants/patients' stress and emotional states by analysing facial changes (from their computer/mobile camera's video) including Heart-Rate-Variability (HRV) from changes in skin colour. It will provide feedback for both patients and therapists (e.g. how patients respond to specific stimuli) and can be used, also, as biofeedback.* Personalised App: Adding personalised skills-practises to participants/patients digital app according to their needs.* Analysis of all patients' data using Ai/Machine-learning to find what type of specific methods/skills-practises are most helpful for specific types of patients; and improve future personalisation. We'll test/demonstrate this by conducting two RCTs. We'll analyse first-RCT data (~5,000 sessions) to create personalised interventions, and test in second-RCT.One therapist will be able to treat remotely many patients in parallel, improving cost-effectiveness and outcomes many times over. Patients will receive treatments at home. UpLiftX will be attractive to healthcare providers and insurers worldwide, reducing costs and waiting lists, and enabling more treatments.UpLiftX is designed to fit into existing healthcare services in the UK and USA (e.g. NHS, USA Veteran Affairs) . It'll be tested within an NHS Trust settings with waiting list patients. We expect that UpLiftX will enable healthcare providers to deliver effective therapy to many more patients with the same number of therapists, and much-reduced cost-per-patient.