I am in the season of life where the time when I am not at work is busy family time. I spend a lot of my weekends cooking, and I make a lot of household food from scratch. Having done my PhD in musculoskeletal pain before moving to MS research, I’m very aware of the time I spend sitting every day at work, and how this is not good for my muscles and joints. I took up ballet as an adult - it keeps me moving and forces my brain to think in a different way.

I worked alongside many scientists at the Menzies Institute for Medical Research who were involved in MS research, even though I wasn’t at that time. I saw how much opportunity there was in the field of MS. The field is moving so fast with so much progress being made in understanding how the disease works and what might make a difference for people living with MS. So, when an opportunity arose to work in MS research, I embraced it. The MS community continues to inspire me. They have clear goals about the sort of research they value and want done, and they are willing to work with researchers to further this agenda. The passion for research and supporting researchers is what scientists need to keep going when the work is full of challenges and never finished.

Recent epidemiological research on US military recruits conclusively showed that being infected with Epstein-Barr virus is a necessary (but not sufficient) cause of MS. For epidemiologists, showing that something really does cause a disease of interest is the holy grail.

I love the idea that one day a vaccine will be available for the Epstein-Barr virus, preventing people from developing MS in the first place. Then, the work that scientists like me do in terms of working out how best to treat or manage symptoms of MS won’t be needed.

The goal of my research project is to focus on the different ways we can collect information on sleep and MS symptoms in people living with MS. I will assess whether information on sleep collected from research-grade Fitbits adds value to information we collect from standard sleep questionnaires, as well as asking people to use a symptom tracker app. Previous research suggests that the information collected from devices might really be different to that collected using questionnaires. After all, no one knows what is happening when they are asleep, and if they don’t know, they can’t tell researchers in surveys. That’s where devices can do some of the sleuthing for us. Importantly, we want to know whether collecting information in this way is feasible and acceptable.

Sleep is one of those things that people don’t think is important until they are not getting enough. People living with MS are twice as likely to have sleep in the clinically poor range than other people living in the community, so poor sleep is a significant problem in people living with MS. My research has already shown that poor sleep is associated with poor quality of life over and above the effect other MS symptoms have on their quality of life.

My current research project will help us decide what information is most important when considering sleep and MS symptoms. Figuring out what the best combination of questions and other information is will help us be more efficient when asking research questions. This might involve identifying treatment targets in clinical trials sooner or perhaps requiring fewer participants in clinical trials. Ultimately, this may mean that in the future, poor sleep is a much smaller burden for people living with MS than it is now.

The goal of my research program is to improve sleep in people living with MS, by collecting better data on sleep and MS symptoms and to create a pathway to treatments for poor sleep and possibly other MS symptoms. I will determine what objective data on sleep (from research-grade Fitbits) adds value to the data we would usually collect (using standard sleep questionnaires), and symptom data from an app. I also want to assess what changes in sleep are usual over time using data from MS Australia’s Australian MS Longitudinal Study, and what factors predict changes in sleep over time, and therefore need to be accounted for in future clinical trials. I will also be using data from a current clinical trial to assess whether magnetic brain stimulation (vs sham therapy) improves sleep quality and promotes remyelination in a current clinical trial.

Sleep is one of those things that people don’t think is important until they are not getting enough. People living with MS are twice as likely to have sleep in the clinically poor range than people living in the community, so poor sleep is a significant problem in people living with MS. My research has already shown that poor sleep is associated with poor quality of life independent of other symptoms. My current research program will provide context, and ideally a treatment pathway for identifying suitable treatments for sleep that can be tested in clinical trials. This may mean that in the future, poor sleep is a much smaller burden for people living with MS than it is now.

As an epidemiologist, my laptop is my laboratory. I use data from large datasets (including MS Australia’s “Australian MS Longitudinal Study”), which I analyse using a statistical program to generate research findings. I enjoy the challenge of working with data from real people, including the satisfaction of getting the coding right to create my datasets, and the joy of seeing new results and working with colleagues to figure out what the numbers are telling us. I enjoy thinking about how we work with this type of data to figure out what part of people’s symptom experience matters most in terms of predicting clinically relevant outcomes, such as MS progression or quality of life over time.