Identification and Characterization of Pain Processing Patterns Among Patients with Chronic Primary Pain: A replication.

Abstract

To develop individual and effective treatment plans for patients with chronic pain, we aimed to replicate Grolimund et al's (2017) empirical categorization of chronic pain patients on a new and larger sample. Moreover, this work aimed to extend previous knowledge by considering various treatment outcomes and exploratorily analyzing which coping skills might be particularly relevant for treatment success in each subtype. Latent class analysis was used to identify homogenous subtypes with different pain processing patterns using the pain processing questionnaire (FESV). By analyzing 602 inpatients with chronic primary pain, we identified three subtypes: (1) severely burdened individuals with low coping skills, (2) mildly burdened individuals with high coping skills, and (3) moderately burdened individuals with moderate coping skills. Pain interference, psychological distress, cognitive and behavioral coping skills improved after treatment in all subtypes. Pain-related mental interference significantly improved only in subtypes (1) and (3). Only individuals of subtype (3) reported significant reductions in pain intensity after treatment. Exploratory regression analysis suggested that of subtype (1), the most promising targets in reducing pain interference and psychological distress post-treatment might be to foster relaxation techniques, counteractive activities, and cognitive restructuring. None of the FESV dimensions significantly predicted treatment outcomes among individuals of subtype (2). Individuals of subtype (3) might benefit the most from experiencing more competence during treatment. Our findings highlight the importance of identifying and characterizing subtypes of chronic primary pain patients and that these subtypes should be considered for individualized and effective treatment.