The TIMELY Team is working to build clinically useful digital tools to predict mental health problems in children and young people and support
prevention pathways. The project brings together multi-agency, de-identified data to provide a complete picture of children and young people's mental health, at a national level.
Background
Mental health disorders have become a pressing global health issue, affecting a substantial proportion of the population and imposing significant economic costs. According to the World Health Organization (WHO, 2022), approximately 1 in 8 people worldwide, or 970 million individuals, were living with a mental health condition in 2019. This prevalence has profound implications for healthcare systems and societies as a whole.
The economic burden of mental health disorders is substantial. A study by James et al. (2018) highlighted the critical strain they place on health systems worldwide. Moreover, the early onset of many mental health conditions, with half beginning by age 14 and three-quarters by age 24 (Kessler et al., 2005), exacerbates the problem, particularly given the large proportion of young people in the global population (Fusar-Poli et al., 2021).
The rising prevalence of child mental illness is particularly concerning. Rates have increased by 40% between 2017 and 2020, resulting in 20% of children having a diagnosable mental health disorder (Newlove-Delgado et al., 2022). These children face higher morbidity and mortality rates, which translates to a reduction in life expectancy by 10-20 years (Harris & Barraclough, 1998; Hawton et al., 2020). Projections indicate that anxiety and depression will see the most rapid increases in the 10% most deprived areas, making mental illness one of the three largest contributors to observed health inequalities (Raymond et al., 2024).
The project brings together multi-agency, de-identified data to provide a complete picture of children and young people's mental health, at a national level. This complete picture can support the development of AI-driven digital tools. Importantly, the team are exploring how this can be achieved in a manner suitable to professionals, patients, and patents/caregivers. In a manner that is ethical and tackles inequality.
Project Aims
The TIMELY Team is working to build clinically useful digital tools to predict mental health problems in children and young people and support prevention pathways.
Project Activity
- Patient and public involvement and engagement (PPIE) supporting many of the work packages. Including establishing a national PPI community with ~200 members: Children and Adolescents Research Involvement for the Next Generation (CA:RING).
- Qualitative exploration of care pathway experiences and perception of data-driven digital solutions from the perspective of patients and carers.
- Qualitative exploration of care pathway experiences and perception of data-driven digital solutions from the perspective of professions.
- Establishing a national, multi-site, de-identified data resource bringing together education data, health care data, social care data, and genomic data to provide a more complete picture of children and young people's mental health.
- Exploring the use of multi-agency, largescale data resources to develop innovative AI-driven tools to support the predict mental health problems in children and young people and support prevention pathways.
Anticipated or actual outputs
Actual outputs to-date:
- A multi-agency, de-identified data resource in Cambridge (inclusive of a information governance framework and PPIE strategy).
- Initiation of the first national site to support the national framework for data.
- The CA:RING PPI community with ~200 members.
Intended near-term outputs:
- A PPIE toolkit for recruiting, engaging, and upskilling children and young people, and their parents/carers, in initiatives with health-data and digital concepts.
- A co-designed blueprint for digitally enabled pathways for early identification and prevention of mental health problems among children and adolescents, with an initial focus on Cambridgeshire and Peterborough.
- A network of national data sites, utilising de-identified, multi-agency data to support federated analysis and insights regarding a more complete picture of children and young people's mental health.
Who is involved?
Institution: University of Cambridge, Department of Psychiatry
PI: Dr Anna Moore Winter
Research Team:
- Dr Rachel Sippy
- Dr Robert Pralat
- Anna Wiedemann
- Carolina Álvarez
- X. Kunyi Ding
- Martin Burchell
- Jad Sbai
PPIE Lead:
Jessica Young
