• B F Dear, M Gandy, E Karin, T Ricciardi, N Langman, L G Staples, V J Fogliati, L Sharpe, L F McLellan, and N Titov.
• aeCentreClinic, Department of Psychology, Macquarie University, Sydney, New South Wales, 2006, Australia bDepartment of Psychology, University of Sydney, 2109, Australia cThe Centre for Emotional Health, Department of Psychology, Macquarie University, Sydney, New South Wales, 2006, Australia.
• Pain. 2016 Oct 1; 157 (10): 2257-68.

AbstractThere is significant interest in the potential of Internet-delivered pain management programs for adults with chronic pain. Understanding the characteristics of people who do and do not benefit from Internet-delivered programs will help to guide their safe and effective use. Using a large sample from a previous randomised controlled trial of an established Internet-delivered pain management program, the Pain Course, this study (n = 463) examined whether several demographic, clinical, psychological, and treatment-related variables could be used to predict clinical response in levels of disability, depression, anxiety, or average pain. Multiple univariate and multivariate stepwise logistic regressions were used to identify unique predictors of clinical improvement, which, consistent with recommendations, was defined as a ≥30% reduction in symptoms or difficulties from baseline. Several unique predictors of clinical improvement were found. However, no particularly decisive or dominant predictors emerged that were common across time points or across the outcome domains. Reflecting this, the identified predictors explained only 18.1%, 13.7%, 7.6%, and 9.5% of the variance in the likelihood of making a clinical improvement in disability, depression, anxiety, and average pain levels, respectively. The current findings suggest that a broad range of patients may benefit from emerging Internet-delivered pain management programs and that it may not be possible to predict who will or will not benefit on the basis of patients' demographic, clinical, and psychological characteristics.

14 keywords...

hide…