2018 Max Perutz Science Writing Competition – winner announced!

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The winner of the Medical Research Council’s (MRC) 2018 Max Perutz Science Writing Competition has been announced. The competition, now in its 21st year, was open to all PhD students funded by the MRC and entrants were tasked with writing about their own research, explaining to non-scientists why their research matters in just 800 words. Since the competition started in 1998, more than 1,000 researchers have submitted entries and taken their first steps into science communication.

Natasha Clarke winner of the 2018 Max Perutz Science Writing competition

This year’s winner is Natasha Clarke of St George’s, University of London with her article: ‘How artificial intelligence, and a cup of tea, could help diagnose Alzheimer’s disease’. Briet Bjarkadottir, of the Nuffield Department of Women’s and Reproductive Health at the University of Oxford was the runner up with her article: ‘Stopping the conveyor belt – cancer and fertility’. Fraser Shearer, of the Centre for Cardiovascular Science at the University of Edinburgh, was commended for his article ‘Keep calm and carry to term’.

Andy Ridgway, a Senior Lecturer within the Science Communication Unit, was among this year’s judges that also included the MRC’s Executive Chair, Professor Fiona Watt, Dr Claire Ainsworth, freelance journalist and science writer; Stephen Curry, journalist and science writer; Dr Roger Highfield, MRC Council member and director of external affairs at the Science Museum Group and Jennifer Rohn, journalist, novelist and scientist at University College London.

 

Andy said: “What really shone though in the shortlisted entries was the power of telling a relatable, human story when explaining the importance of medical research. By showing how a disease or condition impacts an individual and how this new treatment will change their lives, it conveys the impact of the research in a powerful, engaging way.

“It was a pleasure to read all the shortlisted entries and there are some gifted writers in the field.”

The awards were announced at a ceremony at the Royal Institution on 25 October by the MRC’s Executive Chair and Chair of the judging panel Professor Fiona Watt, alongside Professor Robin Perutz, son of the late Max Perutz.

Fiona said: “It has been a great pleasure to chair the judging panel of this year’s Max Perutz Award.

“The competition is a great way to highlight to early-career scientists the importance of science communication and to showcase their work.  This year we received a record number of entries, from about 10% of MRC-funded PhD students.

“The topics of the winning articles are artificial intelligence and Alzheimer’s disease; cancer and fertility; mental health, depression and stress. I’d like to thank everyone who entered the competition – the judges had a tough time making the selection. Our PhD students do a brilliant job at bringing their research to life – using everyday language, rhetorical devices and personal anecdotes.”

All of the short-listed articles, including Natasha’s winning entry, are now published.

 

Never say never again…

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After my PhD viva in 2004, I promised myself I’d never again study for a qualification. Having gone straight from A-levels through a degree to a doctorate, I felt as if I just couldn’t learn anything more. But a decade later, I found myself at a career crossroads trying to figure out what to do at the end of my maternity leave.

Inspired by my elder daughter’s curiosity, I set up a blog, Simple Scimum, to answer questions about science and nature. Slowly, as the blog gathered followers, my confidence grew; and when one of my daughter’s friends asked if I would answer her science questions too, I knew I had to turn science writing into something more than a hobby.

I began searching for jobs that involved writing about science and quickly realised that a qualification in science communication would be an advantage. So, I googled ‘sci comm Bristol’ and found UWE’s MSc in Science Communication, which sounded brilliant but was more than I could manage whilst working part-time and looking after two young children. However, the Postgraduate Certificate in Practical Science Communication was exactly what I was looking for: a one-year, part-time course with intensive teaching blocks, offering hands-on experience and links to industry. I applied for the September 2016 intake and won a bursary towards my tuition fees: I was going back to university!

I felt nervous about returning to study after such a long break but I knew that this was just the first step along a new career path.

The ‘Writing Science’ module was an obvious choice, with the opportunity to create a magazine and develop a portfolio just too good to miss. I learned the essential elements of journalistic practice and wrote a bylined article for UWE’s Science Matters magazine. But the real highlight was a three-hour workshop on ‘how to write a book’ – I’d love to write science storybooks for children, and came away bursting with ideas, enthusiasm and an action-plan to turn my dream into reality. (Roll on NaNoWriMo…!)

But it was through the ‘Science in Public Spaces’ module that I discovered just how strongly I want to inspire young children and engage them with research. I designed ‘Simon’s Box’ to talk about genetic disease and genome editing with GCSE pupils in local schools. And I had the best time in the Explorer Dome learning about science shows for young audiences. Seeing how to encourage children to learn through stories and play was a fantastic experience and a seminal moment in my desire to become a science communicator.

At times I found it hard to juggle study, work and childcare but the intensive teaching blocks made it easier for me to attend lectures and workshops. I paid for my younger daughter to go to nursery for an extra morning each week and used that time for reading and research. Still, I often found myself studying between 8pm and 10pm, when the kids were tucked up in bed, and I was grateful for 24-hour online access to UWE’s library facilities. But now the hard work is over and I’m just waiting for my final results.

Over the past year, I’ve been part of a supportive cohort of students who are committed to science communication. I’ve developed the confidence to pursue a new career path and given up my old job to become a Research Fellow in UWE’s Science Communication Unit. Before the PGCert, I dreamed of working in science communication but now I’m actually doing it.

Kate Turton

Researching images on social media – nuts and bolts

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Images and videos are pervasive online, these days, web articles include at least one image or video. On Twitter, Facebook and Snapchat these visual contents are even more common, and social media platforms such as YouTube, Vimeo, Vine, Instagram, and Pinterest are entirely dedicated to their sharing.

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Images can emphasise textual messages, or even convey a message without text at all (Hankey et al., 2013), and they can increase the visibility of a tweet and how often it is shared (Yoon and Chung, 2013). There are so many images on social media that these platforms have become picture databases, and these have become subject to research. For example, Vis et al. (2013) explored images production and sharing practices on Twitter during the UK riots in 2011; Tiggemann and Zaccardo (2016) analysed Instagram images related to the #fitspiration movement, addressing their potential inspiration for viewers and negative effects on viewers’ body image; and Guidry et al. (2015) investigated the content and the engagement of pro- and anti-vaccine images shared on Pinterest.

My Ph.D. research uses one of these databases – it focuses on vaccine images used for advocacy that are shared on Twitter. Sourcing the images that are my data may sound simple, after all, I only need to download my data from Twitter, right? However, it is rather more complex than that. To start with, there are many different communities on Twitter, and they share images on a range of different topic. They may also share images on the same topic from different angles; for example, if we search #health on Twitter, we will see pictures related to healthy food, obesity, fitness, losing weight, public health policy, etc. So, the biggest challenges are how to find the communities of interest and then to develop a data analysis strategy that uncovers how they use their pictures.

To help me narrow the potential field of image research for my PhD, I asked the following questions:

  1. What topic am I interested in? Which communities do I want to study?
  2. Which social media outlets would I find most interesting/useful for my research?
  3. Each social media platform is used by different audiences, so it is important to think about the overall question we are asking. For example, young adults use Facebook, whereas teenagers prefer Snapchat, and Chinese people may be on Weibo.
  4. Where are these communities from? Which language(s) do they use?
  5. If we focus our research on Europe, we have to take into account that Europeans speak different languages. If we focus on English language, we have to consider that our images will come from all over the world, but especially from the US, UK and Australia.

Afterward this initial sifting, I had more questions to answer:

  1. What keywords should I use to search on my chosen social platform (in my case, Twitter)?
  2. Each topic and each community has its own “slang” or “dialect” and therefore keywords. On Twitter, for example, users in favour of vaccinations tweet their content including the hashtag #vaccineswork, whereas people against vaccines use mainly the hashtag #vaxxed and/or #CDCwhistleblower.
  3. How can I find the relevant keywords?
  4. Previous research on social media can suggest some terms; in my case, keywords such as vaccine(s), vaccination(s), vaccinate(d) and immunes(z)ation (Love et al., 2013; Salathé et al., 2013). Searching for these generic words, I found both tweets with and without hashtags that talked about vaccines. However, some communities use specific keywords which may not include these terms (e.g. #vaxxed) and they may use these keywords to label their tweets as relevant to the topic. For example, a tweet claiming “They’re poisoning our children #CDCwhislteblower” and showing an image with a child whilst being vaccinated, would be relevant to vaccinations even if it did not mention “vaccine” or “vaccination”. This tweet would not appear in my research if I set my data collection using only generic words, thus I needed to search for relevant hashtags as well.
  5. How do I find relevant hashtags?
  6. A first step would be considering which hashtags previous studies used, then searching Twitter for generic hashtags and see which other hashtags people use. There are also some online tools that can be helpful, such as Hashtagify.me, Get Tags and RiteTag.com. These online software packages suggest correlated hashtags and their popularity.

Answering these questions helps us define the criteria for data collection, but they also show how complicated research on images shared on social media is. As with any data collection method, planning, defining and developing are key for research drawing on online images. We need to be able to justify the approach we took and show that the data collection process is robust. This means, as with many other types of data collection, that we need to pilot and test our data collection methods ensuring that they deliver the material we anticipate and which will validly help us to address our research question. There are so many pictures online, uploaded, downloaded, edited and shared, that the choice of image collection methods becomes key to ensuring the quality of the study overall.

 

Elena Milani

 

References

Hankey, S., Longley, T., Tuszynski, M. and Indira Ganesh, M. (2013). Visualizing Information for Advocacy. Nederlands: Tactical Technology Collective.

Love, B., Himelboim, I., Holton, A. and Stewart, K. (2013) Twitter as a source of vaccination information: content drivers and what they are saying. American Journal of Infection Control [online]. 41(6), pp. 568-570.

Guidry, J.P., Carlyle, K., Messner, M. and Jin, Y. (2015) On pins and needles: How vaccines are portrayed on Pinterest. Vaccine [online]. 33(39), pp. 5051-5056.

Salathé, M., Vu, D.Q., Khandelwal, S. and Hunter, D.R. (2013) The dynamics of health behavior sentiments on a large online social network. EPJ Data Science [online]. 2(1), pp. 1-12.

Tiggemann, M. and Zaccardo, M. (2016) ‘Strong is the new skinny’: A content analysis of #fitspiration images on Instagram. Journal of Health Psychology [online].

Vis, F., Faulkner, S., Parry, K., Manyukhina, Y. and Evans, L. (2013) Twitpic-ing the riots: analysing images shared on Twitter during the 2011 UK riots. In: Weller, K., Bruns, A., Burgess, J., Mahrt, M. and Puschmann, C. (2013) Twitter and Society. New York: Peter Lang Publishing Inc., pp. 385-398.

Yoon, J. and Chung, E. (2013) How images are conversed on twitter? Proceedings of the American Society for Information Science and Technology [online]. 50(1), pp. 1-5.