A self-guided and monitored innovative AI-driven parental support intervention (mobile app), for families caring for a young one that self-harms: feasibility study

令人震惊的是，五分之一的青少年自残[Monto，2018]，英国8至17岁儿童的自残住院率在2023年上升了22%。为了解决这些家庭的长期供应短缺问题，Oryx Health正在开发一种产品，使用基于过程的治疗方法为父母解决青少年自我伤害问题。它们使父母具备社区、知识和技能，以支持他们的年轻人进入和通过康复。父母驾驭年轻人情感脆弱性的能力，管理自己的能力，支持他们制定/维持替代应对策略和积极的日常生活对于孩子的康复至关重要[Berk，2020]。随着平均发病年龄的下降，以父母为中心的解决方案，重点是恢复的关键标志物，是打破这一循环的必要条件。目前，Oryx使用基于流程的手动方法，其中入职，评估和干预匹配都是由人为主导的。这使用了Oryx临床团队的关键人力资源，该团队可以专注于干预。为了缓解这一问题，Oryx正在为创建机器学习算法奠定基础，该算法可以通过评估和入职流程支持临床有效的决策。具体来说，他们将使用自动预测模型对父母进行聚类，并将其与最合适的临床路径相匹配，以提高效率，规模和有效性。Oryx Health的方法已经被证明是成功的，92%的父母都在使用。然而，可用的细分市场将随着从手动入门和分类过程到算法过程的转变而急剧扩大。目前市场上还没有这样的过程，这将导致更准确的匹配，使干预措施更有效，接触和支持更多的患者。所附的资金申请是为了使Oryx能够安全可靠地构建这一过程，以便机器学习算法可以支持临床决策和1\。引导父母到适当的路径，2\。全面评估家庭的需要和3\.该项目将支持Oryx开发其产品和研发，发展以支持广泛而多样化的父母群体，并达到里程碑，以帮助他们获得未来的投资。

Alarmingly, 1 in 5 teenagers self-harm \[Monto, 2018\] and self-harm hospital admissions for children aged 8 to 17 in the UK jumped 22% in 2023\. To address the chronic shortfall in provisions for these families, Oryx Health is pioneering a product using process-based therapy for parents to address adolescent self-harm. They equip parents with the community, knowledge and skills to support their young people into and through recovery. A parents' ability to navigate their young person's emotional vulnerability, manage their own, support them to develop/maintain alternative coping strategies and positive routines is essential for their child's recovery \[Berk, 2020\]. With the average age of onset decreasing, parent-centric solutions focusing on key markers of recovery are essential to break this cycle. At present, Oryx uses a manual Process-Based approach whereby onboarding, assessment and intervention matching are human-led. This uses critical human resources from the Oryx Clinical Team which could be focused on intervention. To relieve this, Oryx is building the foundations to create a Machine Learning algorithm that can support clinically effective decision-making through the assessment and onboarding process. Specifically, they will use an automated predictive model to cluster parents and match them with the most appropriate clinical pathway for higher efficiency, scale and effectiveness. Oryx Health's method has already proven successful with 92% of onboarded parents. However, available market segments will be dramatically widened with a move from a manual onboarding and classification process to an algorithmic one. Such a process does not currently exist in the market and would result in more accurate matching, making interventions more effective, reaching and supporting a greater number of patients. The enclosed funding application is to enable Oryx to safely and robustly build this process, such that a machine learning algorithm can support in clinical decision making and1\. direct parents to the appropriate pathways,2\. comprehensively assess family's needs and3\. flag for risk This project will support Oryx in developing their product and R&D, grow to support a wide and diverse group of parents and reach milestones to help them secure future investment.