The different lived experience journeys here illustrate the challenge faced by pain science and are helpful in shaping a direction for our future research. We recognise that in scientific research pain is often reduced to numbers and washed off the impact it has in individual people’s lives. This is often necessary: for example, to understand the breadth of the way pain exists across different populations of people, we need to assemble large amounts of data that is individually very simple. If we want to understand how the brain processes pain, we often need highly controlled laboratory conditions that allow us to tease apart different circuits and functions. But all of this is usually far removed from the pain that people really suffer from.
So how can lived experience stories such as these shape our science?
One thing they do illustrate how pain extends to the space between the individual and their environment. It is shaped by their home, their workplace, the people around them, even their pets. It is intricately tied up with the things they do, from rest to movement. It spans timescales from the instantaneous to the prolonged. And so we need to understand the ‘human ecology’ of pain – how it exists as part of our rich, complex, active and multisensory lives.
We are trying to bridge this in two ways: first, by using tools such as virtual and augmented reality to recreate real world environments in which we can accurately study pain in the laboratory. At the same time, we’re also taking the laboratory to the individual home, using tools such as remote sensing, wearables, and online devices, to conduct ‘field experiments’ in people’s homes. Overall, our challenge is to now take the laboratory precision we’ve developed so far to real-life pain experiences – a new endeavour we call Computational Ecology.
Another thing these lived experiences do is show how pain rarely exists as an isolated symptom, but is intricately wound up with sleep, mood, fatigue, anxiety, appetite. In the NHS we often treat these as different conditions, with different appointments in different clinics, and then talk about patients’ ‘multiple health problems’ as if there’s something innate about that individual which makes them prone to lots of (usually mental health) conditions.
But this doesn’t necessarily stack up with the science, and one of our challenges is to understand how the control of pain by the brain exists alongside its control of sleep, energy balance, motivation, threat perception and so on. It means there must be a template in the brain that sits above these symptoms and orchestrates them according to some primitive rules that we likely share with other animals. We call this template the Homeostatic Map, and one of our goals is to find out where and how this map exists in the brain. Uncovering this would hopefully identify new targets which could control multiple symptoms ‘at source’.
These lived experiences also illustrate the need for new treatments. There is an urgent need for innovation – can we use new technologies to target pain processing? Can we use AI to help us? What has made pain such a hard thing to treat is that it is essentially ‘felt but not seen’, and the fact that it is usually detached from observable signs of bodily damage gives rise to the problem of being believed, and of finding ways to effectively communicate our perception of pain.
But we know pain must exist as a hard biological reality, albeit obscurely, in our brain activity, therefore we need to design technologies that can both objectively read our pain, as well as treat it. We are now focusing on this ‘biomarker’ problem, recognising that it would open the door to new engineering technologies and AI-assisted approaches that can accelerate our search for next generation treatments.
This project is funded by the National Institute for Health and Care Research (NIHR) Oxford Health Biomedical Research Centre, Pain Theme. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The project is also part funded by EPSRC EP/W03509X/1, Wellcome 214251/Z/18/Z, and MRC/Versus Arthritis (MR/W027593/1)
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