Revisiting Chronic Pain Patient Profiling: An Acceptance-based Approach in an Online Sample

Over 116 million Americans experience chronic pain, incurring an annual cost of $635 bn in healthcare and lost work. Acceptance-based therapies have gained increasing recognition for improving functional outcomes. In our online chronic pain sample, we predicted that (1) patients would cluster into low, medium and high groups of chronic pain acceptance and (2) positive affect, negative affect and perceived disability scores would differ overall by cluster, with the most positive outcomes found in the high cluster and the least found in the low cluster. Participants completed the Chronic Pain Acceptance Questionnaire, Positive and Negative Affect Scales and the Pain Disability Index. A k-means cluster analysis was conducted using activity engagement (AE) and pain willingness (PW) totals from the Chronic Pain Acceptance Questionnaire. As predicted, cluster analysis specified three groups: low AE/low PW, high AE/high PW and medium AE/medium PW. Significant multivariate analysis of covariance results were obtained according to Wilks' λ (0.55), F(6,266) = 15.39, p < 0.01, and indicated differences in positive affect, negative affect and perceived disability within each cluster. Follow-up analyses of covariance revealed mean differences in the predicted directions: the high-high group showed the most positive affect and the least negative affect and perceived disability. Conversely, the low-low group displayed the least positive affect (M = 20.28, SD = 7.86), the most negative affect (M = 28.05, SD = 9.33) and perceived disability (M = 49.57, SD = 9.46). The presence of these clusters introduces key questions about the possibility of creating tailored interventions based on cluster profiles.

Higher levels of Acceptance are associated with better functional and affective outcomes for chronic pain patients. Lower Acceptance is associated with poorer functional and affective outcomes. Tailoring interventions using Acceptance-based profiling may improve chronic pain therapies.