Long-Term Modelling Tools for Adolescent Mental Health and Wellbeing Research

青少年经常遇到心理健康和幸福方面的困难。如果这种困难持续存在或随着时间的推移不断升级，就会给青少年及其家庭带来痛苦，给教育、卫生和福利服务造成巨大成本，并对增加失业、犯罪、身体疾病和过早死亡等许多其他不良后果的风险产生终生影响。它们还与儿童早期的不良经历有关，如贫困和忽视，这可能使收入、健康和福祉方面的不平等在代际传递。然而，干预预防和管理青少年心理健康问题是具有挑战性的。研究可以通过试验来评估不同干预措施对心理健康的影响。然而，不幸的是，试验通常只有一到三年的随访数据。因此，很难知道长期影响会持续到什么程度，以及这种影响在不同环境下的不同青少年之间会有什么不同。推断长期影响的标准研究方法没有考虑到新出现的科学知识，即心理健康困难的长期持久性和后果可能在不同情况下对不同的青少年产生不同的影响。对于一些青少年来说，随着时间的推移，心理健康的短期改善会迅速消失，最终几乎不会产生任何好处。但对于其他人来说，改善会持续下去，并积累成巨大的终身收益和公共成本节省。我们建议开发一种更好的方法来长期模拟干预对青少年心理健康和福祉的影响。我们将开发一个通用和可重复使用的计算机程序，以预测青少年从11岁到17岁的健康和幸福感将如何发展，适用于不同家庭、邻里和学校环境中的不同类型青少年，称为“微观模拟模型”。这一模型将以2000年出生儿童千年队列研究中10,000多名青少年的生活的详细数据为基础，并在必要时补充进一步的数据。我们还将把新的模型与现有的儿童(0至11岁)和成年(17岁以上)的微观模拟模型联系起来，这些模型捕捉了青少年心理健康和幸福困难的主要儿童早期原因和终生后果。然后，我们将测试综合模型能否很好地解决使用标准长期建模方法无法回答的各种研究问题，方法是进行以下实例研究：(I)全校反欺凌计划的长期影响，(Ii)减少儿童贫困的税收优惠改革方案对青少年心理健康和福祉的长期影响，以及(Iii)青少年心理健康问题对成年后收入、健康、福祉和公共成本的终身影响。我们将让年轻人参与进来，确保我们的计算机模型有意义地捕捉青少年的经历，并产生与年轻人相关的信息。我们将与布拉德福德的青少年社会工作学徒和六年级学生合作，在整个项目的一系列研讨会上进行合作。布拉德福德是一个贫困地区，青少年精神健康问题的发生率相对较高。我们还将通过咨询青少年心理健康和福祉研究领域的多个学科的专家，以及政府各部门的教育、福利和卫生政策制定者，确保科学可信度和政策相关性。为了帮助青少年心理健康和福祉研究人员在未来使用和改进我们的方法，我们将在英国五所不同大学的研究团队之间进行合作，并通过用户友好的基于网络的平台使我们的工具易于访问。

Adolescents often experience mental health and wellbeing difficulties. When such difficulties persist or escalate over time, they cause misery to adolescents and their families, impose substantial costs on education, health and welfare services, and have lifelong effects on increasing the risk of numerous other bad outcomes including unemployment, crime, physical illness and premature death. They are also linked to adverse experiences in early childhood such as poverty and neglect that can perpetuate intergenerational transmission of inequalities in income, health and wellbeing.Intervening to prevent and manage adolescent mental health problems is challenging, however. Research can help by using trials to evaluate the effects of different interventions on mental health. Unfortunately, however, trials typically only have one to three years of follow-up data. It is thus hard to know how far effects will persist in the long-term and how this will vary between different adolescents in different circumstances. Standard research methods for extrapolating long-term effects do not take into account emerging scientific knowledge about how the long-term persistence and consequences of mental health difficulties may vary for different adolescents in different circumstances. For some adolescents, short-term improvements in mental health fade out rapidly over time, ultimately yielding little or no benefit. But for others, improvements persist and accumulate into large lifelong benefits and public cost savings. We propose to develop a better approach to long-term modelling of intervention effects on adolescent mental health and wellbeing. We will develop a versatile and reusable computer programme for predicting how adolescent health and wellbeing will develop from age 11 to 17 for different kinds of adolescents in different family, neighbourhood and school environments, known as a "microsimulation model". This model will be based on detailed data about the lives of more than 10,000 adolescents in the Millennium Cohort Study of children born in the year 2000, supplemented with further data where necessary. We will also link the new model to existing microsimulation models of childhood (age 0 to 11) and adulthood (age 17+) that capture the main early childhood causes and lifelong consequences of adolescent mental health and wellbeing difficulties. We will then test how well the integrated model can address a diverse range of research questions that cannot be answered using standard long-term modelling approaches, by conducting example studies of (i) the long-term effects of whole-school anti-bullying programmes, (ii) the long-term effects on adolescent mental health and wellbeing of tax-benefit reform options for reducing poverty in childhood, and (iii) the lifelong consequences of adolescent mental health problems for income, health, wellbeing and public cost in adulthood. We will engage young people to ensure that our computer model meaningfully captures adolescent experiences and produces information relevant to young people. We will collaborate with youth social work apprentices and sixth formers in Bradford, a deprived area with relatively high rates of adolescent mental health problems, in a series of workshops throughout the project. We will also ensure scientific credibility and policy relevance by consulting experts from multiple disciplines across the adolescent mental health and wellbeing research field and with education, welfare and health policymakers across government. To help adolescent mental health and wellbeing researchers use and refine our approach in future, we will collaborate across research teams at five different UK universities and make our tool readily accessible via user-friendly web-based platforms.