Exploring What Factors Mediate Treatment Effect: Example of the STarT Back Study High-Risk Intervention

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Mansell, Gemma ; Hill, Jonathan C. ; Main, Chris ; Vowles, Kevin E. ; van der Windt, Daniëlle (2016)
  • Publisher: Churchill Livingstone
  • Journal: The Journal of Pain, volume 17, issue 11, pages 1,237-1,245 (issn: 1526-5900, eissn: 1528-8447)
  • Related identifiers: pmc: PMC5123895, doi: 10.1016/j.jpain.2016.08.005
  • Subject: Anesthesiology and Pain Medicine | Mediation analysis | psychological intervention | low back pain | Clinical Neurology | Original Report | Neurology | RA

Interventions developed to improve disability outcomes for low back pain (LBP) often show only small effects. Mediation analysis was used to investigate what led to the effectiveness of the Stratified Targeted Treatment (STarT) Back trial, a large primary care-based trial that treated patients consulting with LBP according to their risk of a poor outcome. The high-risk subgroup, randomized to receive either psychologically-informed physiotherapy (n = 93) or current best care (n = 45), was investigated to explore pain-related distress and pain intensity as potential mediators of the relationship between treatment allocation and change in disability. Structural equation modeling was used to generate latent variables of pain-related distress and pain intensity from measures used to identify patients at high risk (fear-avoidance beliefs, depression, anxiety, and catastrophizing thoughts). Outcome was measured using the Roland–Morris Disability Questionnaire. Change in pain-related distress and pain intensity were found to have a significant mediating effect of .25 (standardized estimate, bootstrapped 95% confidence interval, .09–.39) on the relationship between treatment group allocation and change in disability outcome. This study adds to the evidence base of treatment mediation studies in pain research and the role of distress in influencing disability outcome in those with complex LBP. Perspective Mediation analysis using structural equation modeling found that change in pain-related distress and pain intensity mediated treatment effect in the STarT Back trial. This type of analysis can be used to gain further insight into how interventions work, and lead to the design of more effective interventions in future.
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