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A theoretically guided approach to identifying predictors of treatment outcome in Contextual Cognitive Behavioural Therapy for chronic pain

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)354-366
Number of pages13
JournalEuropean Journal of Pain (United Kingdom)
Volume23
Issue number2
Early online date24 Sep 2018
DOIs
Publication statusPublished - 1 Feb 2019

King's Authors

Abstract

Background: Psychological treatments are known to be effective for chronic pain, but little is understood about which patients are most likely to benefit from which ones. Methods: The study reported here included 609 people who attended a residential, interdisciplinary, pain management programme based on Acceptance and Commitment Therapy between January 2012 and August 2014. A flexible and theoretically guided approach to model building based on fractional polynomials was used to identify potential predictors of outcome in domains of emotional, physical and social functioning and pain intensity. Variables considered for inclusion were baseline demographic variables along with measures reflecting processes of psychological flexibility, including acceptance, cognitive defusion and committed action. Results: Employment status, level of distress, decentring (a process like cognitive defusion) and acceptance significantly contributed to the model above and beyond the effects of other baseline variables. The unique effects of these were small but may be clinically relevant. Conclusions: Future research should continue to investigate moderators of treatment outcome and to explicitly link these to treatment mechanisms. Taking a flexible, theoretically driven approach to modelling continuous outcomes may be valuable in furthering our understanding of which patients might respond best to which treatments. Significance: Further research is needed to better understand who benefits most from psychological treatments for chronic pain. This study suggests that a flexible, multivariate and theoretical approach to identifying predictors of outcome may be valuable in furthering research in this area.

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