Developmental Medicine & Child Neurology | 2021
Cerebral palsy and the data of pain
Abstract
Pain is a notoriously elusive, but vitally important area of research. While pain (and chronic pain in particular) has profound effects on quality of life, it frequently proves difficult to understand and treat. Clinical assessments of pain necessarily depend on its translation by proxies, given how pain belongs ‘to an invisible geography’ deep inside the body. Yet identifying adequate proxies is itself fraught because pain exists within particular ‘relational, environmental contexts’ that can thwart attempts at generalization or standardization. Relying on quantification and big data in the face of these challenges runs the risk of moving away from pain’s human, embodied specificity. Nonetheless, when thoughtfully done, large population-based examinations of pain have a crucial role to play in deepening understandings of pain’s complexities, as well as revealing trends about how it is distributed and treated. Engaging with pain is especially consequential and difficult in the case of individuals with developmental disabilities. Its presence can be overlooked in the clinic due to communicative challenges and other ways in which disability alters the way pain is expressed and read. As a result, the presence of pain in individuals with cerebral palsy (CP) has been overlooked and under-researched in the past. New scholarship, however, has drawn attention to its prevalence. For example, the Study of Participation of Children with Cerebral Palsy Living in Europe (SPARCLE) suggested that pain was much more common in young people with CP than in the general population. Corroborating these findings, McKinnon et al.’s recent study of children and adolescents with dyskinetic or mixed (dyskinetic/spastic) CP found that pain was prevalent in 85% of participants and was chronic in 77%. Garcia Jalon et al.’s research is significant in identifying pain prescription as a proxy for pain. Without claiming, of course, that it is comprehensive or an adequate diagnostic marker, this proxy is a valuable analytical tool that opens the door to future large-scale, population-based studies. Such studies are clearly needed given the prevalence of pain in people with CP. Moreover, instead of obfuscating pain’s entanglement in social context beyond the clinic, Garcia Jalon et al.’s big data approach helps draw attention to environmental factors imbricated in pain and pain prescription. Significant insights that emerged from this study were the uneven distribution of pain prescription within the CP population based on sex (females had higher odds of being prescribed medication than males) and socioeconomic status (individuals living in deprived areas were more likely to be prescribed medication than those in more affluent communities). Additionally, data about which pain medications were prescribed most frequently may have important clinical implications. For example, while individuals with CP had more than twice the odds of receiving opioids compared to the general population, they were less likely to be prescribed antidepressants than would be expected. While further research is clearly needed to shed light on some of the mechanisms behind these findings, this study is a key contribution that demonstrates how big data can be mobilized to support nuanced, complex investigations of pain and its treatment in the CP population and beyond.