Understanding risk and resilience factors for mental health and neurodiversity with BERRI in children and adolescents

Supervised by Professor Peter Tino and Dr Stephane de Brito together with Dr Miriam Silver from BERRI

To apply for this project, please include ‘Tino & BERRI’ as the project descriptor in the subject heading of your email. 

This PhD project aims to validate the efficacy of the BERRI tool in identifying early neurodevelopmental and mental health markers in children and adolescents, potentially predictive of adverse outcomes later in life. By leveraging machine learning techniques, the research seeks to elucidate the trajectory of symptom profiles over time and explore strategies for effectively mitigating identified risks across clinical, educational, and community settings.

Led by Dr De Brito from psychology and Professor Tino from computer science, in collaboration with Consultant Clinical Psychologist, Dr Miriam Silver, the creator of the BERRI tool, this interdisciplinary project bridges the gap between psychological assessment and computational analysis. The PhD researcher will be embedded in the clinical psychology service at BERRI, as well as the Centre-UB, giving a unique opportunity to integrate science and practice in a project that will directly benefit the wellbeing of vulnerable children and families. 

The BERRI tool, developed through extensive consultations with professionals and caregivers, offers a comprehensive assessment covering behaviour, emotional well-being, risk, relationships, and indicators of psychiatric or neurodevelopmental conditions. It provides a user-friendly platform for identifying children's needs and tracking changes over time, empowering caregivers to make informed choices to improve children's functioning and well-being. 

While BERRI has demonstrated sensitivity and validity in assessing children known to social care services, its potential in clinical and community settings remains largely untapped. This PhD project aims to fill this gap through several linked studies: 

  1. Evaluations of CAMHS Referrals: Investigating the utility of BERRI in aiding triage choices for children referred to NHS CAMH services, with a focus on identifying those at risk and tracking their evolving needs over time. 
  1. Longitudinal Study of Maltreated Children: Examining longitudinal BERRI data for maltreated children to understand the impact of maltreatment on impulsivity and its relationship with behavioural and mental health challenges. 
  1. Neurodiversity and Mental Health Assessment: Analysing BERRI data for neurodiverse children and comparing it with diagnostic interviews to explore the relationship between neurodevelopmental, behavioural, and mental health needs, as well as associated risks. 
  1. Comparison of Maltreated and Community Samples: Investigating the relationship between maltreatment, neurodiversity, and mental health by comparing data from maltreated children with a non-maltreated community sample. 

Methodologically, the project involves recruiting participants from NHS trusts, staffed settings, and Birmingham schools, with data analysis employing machine learning techniques and structural equation modelling to identify early markers of risk and resilience. 

Anticipated outcomes include multiple publications across various research themes, contributing to our understanding of neurodevelopment, mental health, and predictive factors for adverse outcomes. Practically, the research holds implications for informing clinical practice and enhancing early intervention strategies in child mental health. By evaluating the impact of early insights and advice provided by BERRI, the project aims to influence long-term outcomes and potentially save public funds. Moreover, by enhancing the efficiency of CAMHS referrals, the research addresses a critical need in child mental health services, particularly in light of pandemic-related challenges. 

We are looking for a highly talented, dedicated, and mathematically minded PhD student with a 1st class or high 2:1 degree in the field of psychology or neuroscience. An MSc degree in a relevant area is desirable though not necessary. Numerical skills and some programming experience are highly desirable. Previous experience with working with clinical populations and/or children who have experienced childhood adversity is desirable. 

Informal enquiries about the project prior to application can be directed to Dr Stephane De Brito, Centre for Human Brain Health (s.a.debrito@bham.ac.uk)