Congratulations to Lara Johnson!

Please join us in congratulating ACRC Academy student Lara Johnson on her successful viva. Lara defended her thesis 'Understanding Frailty Through the Cumulative Deficit Model: Exploring Dimensionality and Temporality in Routine and Survey Data' on the 19^th of November 2025 at the Usher Building, Edinburgh BioQuarter.

We would like to extend our gratitude to examiners Dr Ahmar Shah of the School of Population Health Sciences, and Dr Peter Hanlon of the School of Health & Wellbeing, University of Glasgow.

We would also like to thank Lara’s supervisors – principal supervisor Dr Sohan Seth (School of Informatics) and assistant supervisors Dr Atul Anand (School of Neurological & Cardiovascular Sciences) and Prof Alan Marshall (School of Social and Political Science.)

We asked Lara the following questions about her thesis and viva experience.

What tip would you share for getting through a viva?

As someone who loves data, I looked up the statistics: around 97% of candidates pass their viva. The reason this rate is so high is because PhD supervisors will only let candidates submit their dissertation when they believe they are ready. If you’ve already reached the viva stage, you’ve almost certainly already done enough to pass.  The real preparation for the viva therefore happens throughout the PhD, long before the day itself.

The examiners at the viva have to ascertain two things:

1. That the work is genuinely yours.  They might test your understanding of core concepts, methods and the decisions you made along the way.
2. That your work makes a novel contribution to the field and is of publishable quality.

My strategy from the start of my PhD was to publish as I went along.  This helped in three ways. 

First, writing up the actual thesis became much easier, as I could directly insert published papers.  

Second, the peer review process itself demonstrates the novelty and quality of the work.  My thesis contained two published papers, one paper under review and one manuscript in preparation.  

Third, published papers are not subject to thesis corrections, which I hoped would increase my chances of receiving minor rather than major corrections.

I approached the viva not as an ordeal but as an opportunity to reflect on my PhD journey with examiners who had read my work closely and were ready to discuss it in depth. 

If you can give advice to yourself from the start of your PhD, what would you tell yourself?

A PhD is a long and at times intense journey, where you bear the sole responsibility for driving things forward. Despite your best planning, progress is not necessarily linear and there will be times you get stuck, hit a dead end and think you are close to the summit only to turn the corner and find another climb ahead. Even when I submitted my final paper – what I thought was the “summit” – there was still a huge amount of work left in writing the thesis – it may have been downhill but it was still arduous.

Because of this, both pacing yourself and keeping yourself fuelled is critical. One of the most important things you can do is develop a strong peer support network – people that you can turn to for questions, support and to discuss developments in the field.  Your supervisors are there to provide feedback but their time is limited, and you need to develop your own networks.  

I was very fortunate to find support from within my cohort, the wider ACRC, my supervisor’s lab group, the Informatics community and my Turing Enrichment cohort.  I am very grateful for all the discussions I have had with these people and for their generosity with their time. This kept me going.

What tip would you give to anyone who may be considering an interdisciplinary PhD?

An interdisciplinary PhD is a great way to develop communication skills, specifically how to explain technical concepts clearly to people from different disciplines. This is a useful skill, particularly when managing people or teams from different technical backgrounds.  I also learned a lot about problem formulation and building consensus around shared goals.

However, a challenge of interdisciplinary research is finding the right outlets for publishing.  Sometimes your work can sit between fields in a way that makes it hard to find the right audience.  For example, during my PhD I explored statistical machine learning methods and their application to frailty data.  The machine learning community is not interested in the substantive interpretation of the findings for understanding frailty, while the frailty community doesn’t need all the technical detail about the methods.  This can make publishing harder.