The project tackles how the pandemic has impacted the lives and treatment of those with Multiple Sclerosis (MS). Combining a plethora of multi-media elements and data journalism, the piece highlights the individual challenges MS patients have faced. The overriding focus was to show how the pandemic has worsened the quality of life. Also to raise important questions concerning the future of treatment for neurological disease.
The main impact of the project was showing the individual hardship of MS patients to a wider audience. Furthermore, to reveal the real-life consequences of a pandemic that has impacted treatment in so many ways. Neurology is an area that does not gain much media traction, but the severity of how people’s lives have changed was an important story to tell. The project also made full use of social media to raise awareness and tell the story differently. The long-form investigation and Twitter threads allowed me to reach a variety of audiences and tap into MS communities.
The data for MRI scans and neurological appointments were acquired through Freedom of Information requests. Requests were sent to hospitals in the North West after speaking to case studies about what aspects of their treatment had been lost.
Once I had the data, it was cleaned and then analysed. The bulk of the analysis used formulas in Google Sheets. Part of the process was preparing the data for visualisation. I achieved this and used story-telling techniques such as scrollytelling. Charts animated and emphasised the significant drop in face-to-face appointments and scans. Focusing on simplicity, the combination of line and bar charts conveyed the data in a meaningful way.
Overall, the project brings together a range of coding languages and the power of words to create a data-driven investigation.
What was the hardest part of this project?
One of the biggest challenges was revealing the people behind the numbers. This should always be the aim of data journalism but it’s not easy to achieve. Once I had the data, I had to find case studies. I knew that scans had dropped, but could I get the people behind those data points into the piece? This meant going through charities to find MS patients. I conducted several interviews and told the story of those who had not seen their MS nurse or had an MRI scan in years.
My main target was to humanise the data. I wanted to take the attention away from the data itself. So, while the charts and interaction helped tell the story, it was the words of the people that was the driving force. It was a challenging experience as a young journalist approaching a delicate topic.
What can others learn from this project?
Journalists can use the project as an example of how to shine a line on a single data point among thousands. It is possible to find the humans behind the numbers and that produces the purest form of data journalism. Choosing to display the data is also something to consider. The project brings together many different media elements. This was purposefully done to aid accessibility and storytelling. This is something other journalists can learn too. Data journalism, particularly coding, can help make articles more user-friendly.