Introduction: While pain self-management programs can significantly improve patient outcomes, poor adherence is common and the need for research on predictors of adherence has been noted. A potential, but commonly overlooked, predictor is cognitive function. Our aim, then, was to examine the relative influence of various cognitive functional domains on engagement with an online pain self-management program.
Method: A secondary analysis of a randomized controlled trial testing the impact of E-health (a 4-month subscription to the online Goalistics Chronic Pain Management Program) plus treatment as usual, relative to treatment as usual alone, on pain and opioid dose outcomes in adults receiving long-term opioid therapy of morphine equivalence dose ≥20 mg; 165 E-health participants who completed an on-line neurocognitive battery were included in this sub-analysis. A variety of demographic, clinical, and symptom rating scales were also examined. We hypothesized that better processing speed and executive functions at baseline would predict engagement with the 4-month E-health subscription.
Results: Ten functional cognitive domains were identified using exploratory factor analysis and the resultant factor scores applied for hypothesis testing. The strongest predictors of E-health engagement were selective attention, and response inhibition and speed domains. An explainable machine learning algorithm improved classification accuracy, sensitivity, and specificity.
Conclusions: The results suggest that cognition, especially selective attention, inhibitory control, and processing speed, is predictive of online chronic pain self-management program engagement. Future research to replicate and extend these findings seems warranted.
Clinicaltrials.gov registration number: NCT03309188.
Keywords: Chronic Pain Management Program; Pain; cognition; neuropsychology; opioid therapy.