Title: Examining the aetiology, nature and consequences of depression in young people within a biosocial framework
Funder: Economic and Social Research Council

Abstract: The objectives of this Fellowship are to develop my publication track record, increase the understanding of adolescent mental health, enhance my skills as an interdisciplinary researcher through extensive training, disseminate findings (and methodologies) with academic and non-academic audiences, further my collaborative links with academics and non-academic stakeholders, and develop future grant and fellowship proposals. Upon the completion of this fellowship, I will have achieved the following objectives: 1.Maximised and consolidated the impact from my PhD and current research by publishing three peer-reviewed manuscripts in high impact journals. This includes two additional research components that were conducted within my PhD but were not published due to them maturing late in my PhD, and one related project following on from my PhD that is part of my current postdoctoral position. Publishing these will enhance my research portfolio. 2.Further increased understanding of the nature, aetiology and consequences of depression in adolescents and young people The work completed within this fellowship will further enhance our understanding of depression in young people and comes at an important time for mental health. This work will be published in peer reviewed journals, disseminated at national and international conferences, and conveyed to health/educational officials, policy makers, charities and the public through a series of knowledge exchange and impact activities. This will include brief lay summaries, videos on findings and data visualisation, and further development of resilience to depression workshops in youth populations. 3.Hosted a data science workshop on Advanced Quantitative Methods (AQM) for early career researchers in order to facilitate the use and training of AQM for social science research. This will be a free one-day data science workshop designed to introduce and demonstrate the use of AQM for early or unfamiliar researchers wishing to use AQM. Furthermore, I will develop and open access framework so that each research publication is accompanied with datasets, tutorials and training materials. This will ensure advanced training is in place for the next generation of social scientists. 4.Completed research visits to the USA and London to foster collaborations and develop new ideas This will include visits to Columbia University and Kings College London, two leading institutions with their own unique data on longitudinal mental health in young people. During these visits I will share findings, gather feedback, discuss potential collaborations and identify how data could be combined to create future funding proposals that build on this fellowship. 5.Undertaken a comprehensive training programme to develop my knowledge and research skills by attending a week-long course on longitudinal structural equation modelling course. This will ensure that I continue to enhance my research skills and remain a talented interdisciplinary research using AQM in a complex field. I will further develop research training by having fortnightly meetings with my mentors and quarterly meetings with leading experts through my external advisory committee. 6.Hosted a one-day knowledge exchange and impact workshop with academics, policy makers, health/education officials and charities to discuss fellowship findings This one-day workshop will bring together individuals with vested interests in improving mental health in young people. During this workshop, I will highlight findings from my PhD and this fellowship and discuss how this research can be used to make positive changes for mental health. 7.Developed and submitted at least one further grant or fellowship (as principle investigator) I will develop and submit at least one further large grant and fellowship that consolidates and builds upon the work from my PhD and this fellowship. These will be interdisciplinary in nature and targeted towards prestigious schemes.

Lay abstract: My research interests are identifying why some young people go on to have poor mental health, whilst others do not. I am interested in identifying the causes of these differences and what the consequences of poor mental health will be for individuals and society. My research uses longitudinal methods that track the same individuals over time and combines these methods with social science and biological data (i.e., genetics) to identify stages of development where preventions and interventions could be implemented to boost mental wellbeing. Depression is one of the most common mental health disorders affecting over 1 in 10 people in the UK. It is expected to be the highest global burden of disease by 2030 and is currently rising in young populations. Depression during adolescence is associated with lower educational attainment, poorer social relationships and increased risk of suicide. One third of individuals with depression first develop onset in adolescence so identifying the nature and causes of depression early could have major benefits in later life. Improving mental health research is one of the ESRC's priority investments and the government has recognised the importance of reducing depression in young people through the development of the Scottish Mental Health Strategy (https://www.gov.scot/publications/mental-health-strategy-2017-2027/). Likewise, many charities and policy makers are keen to further understand the long-term impact of depression in young people. This fellowship contains an interdisciplinary programme of complex statistical research using biological and social data (biosocial) designed to further enhance our understanding of the nature and background of depression in young people. This research will ultimately facilitate better wellbeing for individuals and society. This fellowship uses big data from a longitudinal population-based cohort of children born in the 1990's and their families, followed up over the last 30 years. It will investigate how depression starts and changes through important transitions in life (childhood to adolescence and young adulthood, starting secondary school, leaving school), and what the impact of depression during these periods has on wellbeing in adulthood. Advanced Quantitative Methods (AQM) will be used to highlight these changes over time, and identify when specific risk factors like childhood trauma, parental depression and low self-esteem could be having their greatest effect on depression in young people. Likewise, this fellowship will also demonstrate that depression at different stages of youth development could be important for different outcomes in later life (such as poorer physical health or increased substance misuse). The key point here is that risk factors like childhood trauma, parental depression and low self-esteem, as well as depression itself are modifiable, but it is important to know when and how they operate in order to design well timed interventions. The central aim of this fellowship is to further enhance our understanding of depression in young people through the dissemination of research conducted within my PhD and the further publication of two research projects that were not completed during my PhD and one through my current research. This fellowship provides a critical opportunity to capitalise on this important and timely research for maximum output through high impact publications, dissemination to policy makers, health officials, charities and the general public. A further aim of this fellowship is to further integrate social and biological data within the context of AQM. The ESRC has previously identified the use of AQM in social sciences and health as a priority area, and also acknowledged there is a shortage of researchers using genetic data within social sciences. This fellowship will help develop this framework and provide a platform for training the next generation of social scientists and researchers in the use of biosocial AQM.

Research activity codes: 2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH