Additional Supervisors: Prof Daniel Smith (University of Glasgow) & Dr Donald MacIntyre (University of Edinburgh)
Over 200 million children under five years old are estimated to be developmentally lagging globally, with about 32% being in India . A number of pregnancy and early life risk factors along with insufficiently stimulating home environments have been implicated with these alarming rates. The effects of sub-optimal development are reflected in behavioural characteristics during childhood, poor schooling and problematic adolescence, and ultimately varied socio-economic difficulties pertaining into adulthood. Long term consequences of suboptimal development are shared with children diagnosed with Neurodevelopmental Disorders (NDDs). These include a range of conditions that affect mental, emotional, and behavioural growth of children such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and Learning Disability (LD), amongst others.
The clear majority of children diagnosed with NDDs in India do not receive timely and effective intervention and treatment, which has the potential to mitigate symptoms and improve wellbeing. Unfortunately, the scale of the problem and the state of the interventions is aggravated by: a) low community awareness about disabilities affecting children, b) lack of parental knowledge of NDDs, which leads to delayed care-seeking and delayed commencement of any intervention; c) deep-rooted and pervading social stigma around NDDs, and d) limited scientific evidence on interventions that work which are applicable within the local context. The limited interventions which are occasionally applied, focus on a limited set of symptoms which cannot be adequately addressed within a single discipline (e.g. by a paediatrician, occupational therapist, or speech therapist). However, NDDs impact children across different domains of development: physical (motor), cognitive, emotional, and behavioural; there is increasing evidence of the existence of a vicious cycle of mental disorders with physical behaviour and sleep, highlighting the complexity of the problem and the need to develop more holistic approaches towards effective long-term management . Moreover, it has been shown there may be common latent variables underpinning many mental disorders which are not sufficiently well quantified using the hitherto established instruments , which suggests mining large datasets with a range of disorders might elucidate underlying similarities to facilitate cross-referencing and the development of treatment pathways.
New Horizons is a social venture working in the area of early childhood development, impairment and health. The New Horizons Child Development Centre (NHCDC) provides developmental services through a business model and the New Horizons Health and Research Foundation (NHHRF), which is the registered non-profit wing, conducts research, community based rehabilitation, and training programs on non-profit basis. Founded in 2003, it currently has five centers operating in Mumbai, India. It offers developmental services under one therapeutic center through a multi-disciplinary team, and has piloted a system with structured, goal-oriented intervention. Each child undergoes a detailed trans-departmental evaluation, which enables the planning of a tailored intervention program which is systematically documented and monitored. In total, there are 30,000 treatment sessions every year on average, with a ratio of one therapist to one child in each treatment session lasting about 45 minutes. This gives rise to a unique, rich source of longitudinal data, and provides an excellent opportunity to gain insight into NDDs.
This study will be the first independent evaluation of the largest sample of longitudinal intervention data on NDDs within a multi-disciplinary intervention model in India. The analysis will evaluate the long-term effectiveness of this model and will generate codes for a range of variables across different diagnostic conditions and across treatment protocols. Pre-treatment and post-treatment differences will be quantified, identifying latent variables and the extent of overlap across conditions. Relationships between specific components of intervention and the rates of change in various neurodevelopmental profiles of children will be measured. Descriptive and multivariable machine learning algorithms will be used to develop predictive models.
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location:
Please note, you must apply to one of the projects and you are encouraged to contact the primary supervisor prior to making your application. Additional information on the application process if available from the link above.
For more information about Precision Medicine visit:
Start: September 2018
Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualifications, in an appropriate science/technology area.
Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £14,553 (RCUK rate 2017/18) for UK and EU nationals that meet all required eligibility criteria.
Full eligibility details are available: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
Enquiries regarding programme: [Email Address Removed]
1. S. Grantham-McGregor, Y.B. Cheung, S. Cueto, P. Glewwe, L. Richter, B. Strupp, and the International Child Development Steering Group, Developmental potential in the first 5 years for children in developing countries, Lancet, Vol. 369(9555), pp. 60-70, 2007
2. B. Sheaves, K. Porcheret, A. Tsanas, C. Espie, R. Foster, D. Freeman, P.J. Harrison, K. Wulff, G.M. Goodwin: Insomnia, nightmares, and chronotype as markers of risk for severe mental illness: results from a student population, Sleep, Vol. 39(1), pp. 173-181, 2016
3. A. Tsanas, K.E.A. Saunders, A.C. Bilderbeck, N. Palmius, G.M. Goodwin, M. De Vos: Clinical insight into latent variables of psychiatric questionnaires for mood symptom self-assessment, JMIR Mental Health, Vol. 4, No. 2, pp. e15, 2017