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Embedding trials in routine practice: identifying and overcoming barriers to using routinely collected data in studies with families affected by multiple long-term conditions or disadvantage

   Population Health Sciences Institute

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  Prof Dawn Teare, Dr Niina Kolehmainen, Dr Louise Coats, Dr Sunil Bhopal  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Background to Project: The period of early life, from conception to pregnancy to early childhood, offers a key window of opportunity for promoting health, wellbeing and functioning for families. During this period, there is increased contact with a range of professionals with potentially long-lasting impact. This is particularly true for families affected by multiple long-term conditions or disadvantage, often receiving a range of non-pharmacological interventions (NPIs). Yet, methodological challenges (e.g. in recruitment, data collection) and barriers to trial participation (e.g. families’ time scarcity) means there are relatively few trials in these populations.

Pragmatic trials are designed to be embedded in routine practice enabling broad inclusion criteria and to make the maximum use of registry data or electronic health care records as outcomes. Such designs are constrained by the availability of relevant or appropriate routine outcome data and at what level the routine data is available. Such constraints can be overcome with hybrid trials where additional outcomes can be collected. A key benefit of routine care embedded trials is that they provide a potentially more flexible method for involving these groups in trials, becoming increasingly common, provide a potentially efficient way forward, but there are practical and methodological challenges in their conduct.

What the Studentship will Encompass: The overall purpose is to advance methods in early-life trials embedded in routine care, especially the use of routinely collected data in evaluating long-term effect of NPIs. The focus is on families affected by multiple, complex disadvantages – including families affected by childhood-onset long-term conditions. The student’s work will consist of three work packages. WP1: A systematic evidence review and synthesis to: (i) summarise existing methodological research in early-life trials embedded in routine care; and (ii) identify exemplars of successfully embedded trials of non-pharmacological interventions. WP2: Pilot work with real data: review potential interventions, appropriate units of randomisation, approaches to consent and features/characteristics/limitations of the routine data available. WP3: Exploration of the potential for diverse statistical approaches to enhance the impact of existing early-life trials and cohort studies though linkage to routine longitudinal electronic health care data, including data on diverse long-term outcomes.

The lead supervisor is a senior biostatistician and triallist with nationally leading experience in various randomised trial designs and diverse experience in non-randomised longitudinal evaluations; and the Chair of the NIHR Methodology Incubator Steering Group. The co-supervisors are clinical academics in community paediatrics (Kolehmainen, Bhopal), public heath (Bhopal) and hospital-based congenital services (Coats) with experience of various complex NPI development and evaluation designs, including mixed (qual+quant) methods, trials, and epidemiology. Kolehmainen is also an active member of the NIHR Methodology Incubator Paediatric Workstream, which provides further linkage to national initiatives to advance research with families.

As case studies for the pilot work (WP2), co-supervisors will facilitate access to data of the student’s choice, which may include e.g. vaccinations in children in care, families affected by parent or child congenital heart disease, and community health records for under5s. For (WP3) access to the ActiveCHILD cohort (Kolehmainen) or larger hospital or community-based cohorts such as NCARDs.

The topic of increasing early-life research with families affected by long-term conditions or disadvantage has been identified as a key priority in several national PPI and stakeholder initiatives, for example the JLA PSP Multimorbidity. A regional, cross-sector task-and-finish group that included PPI representation further identified routine data use as a key priority for the next steps in advancing this agenda.

A relevant previous degree is essential, with experience in working with routine data desirable. A relevant degree might be e.g. in statistics, mathematics, data science or epidemiology. Relevant experience might be e.g. in trials using routing data, or epidemiological methods to evaluate interventions.


You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:

Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.

Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.

Before making an application, applicants should contact the project primary supervisor to find out more about the project and to discuss their interests in the research.

The deadline for applications is 4pm (GMT) 18 February 2022. Late applications will not be considered.

Completed application forms must be returned to: [Email Address Removed]

Informal enquiries may be made to [Email Address Removed]

Funding Notes

Studentships are funded by the Medical Research Council (MRC) for 3 years. Funding will cover tuition fees at the UK rate only, a Research Training and Support Grant (RTSG) and stipend (stipend to include London Weighting where appropriate). We aim to support the most outstanding applicants from outside the UK and are able to offer a limited number of bursaries that will enable full studentships to be awarded to international applicants. These full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.
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