A network analysis of chronic pain rehabilitation program registry data: Structure, change, and responder analyses

Background: Efforts to identify specific variables most related to outcomes in interdisciplinary pain rehabilitation are challenged by the complexity of chronic pain. Methods to manage this complexity are needed. In this study we apply network analysis to a large sample of people seeking interdisciplinary pain treatment. The purpose of the study was to determine the network structure entailed in the set of variables, examine change, and look at potential predictors of outcome, from a network perspective. Methods: Participants in this research (N = 2,421, age M = 43.8 years, % women = 82.2%) were all those consecutive cases providing pre- and post treatment data in the Swedish Quality Registry for Pain Rehabilitation (SQRP). Variables analyzed include pain intensity, pain interference, extent of pain, depression, anxiety, insomnia, and psychological variables from cognitive behavioral models of chronic pain. Network estimation, plotting, accuracy, and changes were call calculated in R. Results: We found Acceptance, Pain Interference, and Depression to be key, “central,” variables in the network of self-reported clinical variables. Interestingly, there were few changes in the network structure following treatment, particularly with respect to which variables appeared most central. On the other hand, Catastrophizing, Depression, Anxiety, and Pain Interference each became less central. The variables where changes were most strongly related to changes in the remainder of the network as a whole were Life Control, Acceptance, and Anxiety. Finally, no network differences were found between treatment responders and non-responders. Conclusions: Further application of a network approach to pain rehabilitation data is recommended. Future studies may improve upon the current results by selecting variables for analysis in a theoretically guided fashion and approaching the data ideographically, to detect unique individual differences in potential treatment processes.