Title: A network meta-analysis of complex interventions to prevent mental-ill-health in children and young people: evaluation of effective and cost-effective intervention components.
Funder: Department of Health and Social Care

Abstract: Lifetime trajectories of mental ill-health are established early in childhood. 10% of young people aged 5-16 have a clinically-diagnosed mental health disorder. For some, mental health problems continue into adulthood; half of adults with mental ill-health report their first symptoms occurring before age 14. Young people with mental ill-health are at greater risk of suicide, self-harm, substance mis-use, risky sexual behaviour, anti-social behaviour and experience poorer educational outcomes. The mental health of young people has been the focus of multiple preventative interventions which have been compared in systematic reviews and meta-analyses. Many systematic reviews do not provide a quantitative assessment of effectiveness. Those that do suggest modest effects of prevention programmes for young people, however statistical heterogeneity is high and comparisons are restricted to direct, head-to-head evidence alone (e.g. “targeted prevention intervention” vs control). This ‘lumping’ over diverse interventions in meta-analysis can conceal the complexity of mental health interventions which are usually made up of multiple, well-defined components. Knowledge of the effect of specific components is important for practitioners when commissioning, or designing, an intervention, since identifying ‘key’ components enables locally adaptive implementation and value for money. To date, no review has quantified the effectiveness of specific intervention components for use in economic evaluation. The effect of intervention components (individually or in combination) can be modelled in meta-analysis using meta-regression methods. In our research we will identify the most effective and cost-effective intervention component(s), or combination of components, for universal and targeted prevention of mental health problems in children and young people. We will produce a taxonomy of components to characterise the preventive mental health interventions identified by the systematic review. We will work with third sector representatives, clinical and public health experts to ‘sense-check’ the identified intervention components. The analysis will use a random effects, component-based network meta-analysis (NMA). A network meta-analysis is an extension of standard meta-analysis which enables the simultaneous comparison of multiple interventions in a single model, whilst retaining the distinct identity of each intervention analysed. Economic evaluation will be conducted to determine the most cost effective component, or combinations of components, for common mental ill-health problems in young people. All analyses will be conducted in a Bayesian framework using OpenBUGS software. Three population age groups will be distinguished and evaluated separately: primary, secondary and university-aged children and young people. Eligible interventions are those which are primarily school- and university-based. We will work with young people, their parents, service commissioners and third-sector representatives to identify outcomes of interest. This feedback will also inform the economic evaluation. Using an established methodology, these outcomes will be mapped to those reported in the literature. Primary outcomes identified in scoping searches include self-report depression, self-report anxiety, self-report emotional well-being, suicidal ideation and behaviour; self-harm and inequalities in mental health.

Lay abstract: The research question: what are the most effective and cost-effective intervention components, or combination of components, for prevention of mental health problems in children and young people? 10% of young people between 5 and 16 years have a clinically-diagnosed mental health problem, such as depression or anxiety. This is approximately 1.1 million young people in the UK. Many more do not seek help from doctors. For many young people mental ill-health continues into adulthood; half of adults with an ongoing mental health issue first experienced their symptoms before age 14. Research suggests preventing mental illnesses developing before adulthood provides the largest benefit for the individual, society and the economy. This project aims to compare the relative effectiveness and cost-effectiveness of interventions designed to prevent mental illness from developing in the first instance. In the first stage of our project we will consult with young people, health professionals and charities to identify the mental health and social outcomes of greatest interest to them and whether these are similar to outcomes measured by the studies we identify in the second stage of the project. In stage two we will systematically review existing literature to identify studies evaluating preventive mental health interventions for primary, secondary and university aged children and young people. These interventions are typically made up of multiple and distinct elements or components, however standard statistical and economic analyses evaluate them as a homogeneous whole, often due to the small numbers of trials involved. As such, researchers can only answer the general question “are preventive interventions effective?” This is of limited use for a public health decision maker since they do not commission an average, "one-size-fits-all" intervention but a specific intervention tailored to the needs, setting and context of their population of interest. In the third stage of this project we will examine specific components of mental ill-health prevention interventions. We will extract information from the studies we identified during the first stage to produce a classification system, or taxonomy, of components. This classification will then inform the fourth and fifth project stages; the statistical and economic analyses. We will use a recent statistical development called network meta-analysis which allows multiple interventions to be evaluated in a single analysis and produces effect estimates of each intervention compared to every other, even if they have not been directly compared in head-to-head trials. Unlike a standard statistical analysis we will use the intervention components as the input to the analyses and not the ‘whole’ intervention. This will allow us to identify the most effective and cost-effective component, or combinations of components, for preventive mental ill-health interventions. This knowledge will help those who design or commission mental health services to provide the best intervention for their community/ population and ensure it is value for money.

Research activity codes: 3.1 PRIMARY PREVENTION INTERVENTIONS TO MODIFY BEHAVIOURS OR PROMOTE WELL-BEING
Health categories: MENTAL HEALTH