CHRONIC PAIN SELF-MANAGEMENT SUPPORT IN PRIMARY HEALTH CARE

Abstract

Chronic pain is one of the most frequent reasons for a primary health care visit and people with pain identify improved function as an important goal. Self-management support provides an opportunity to improve function for people with chronic pain, but existing evidence suggests negligible changes in function. This thesis includes five manuscripts with overarching objectives of improving the understanding of reductions in function related to pain and evaluating a new self-management program aimed at improving function for people with chronic pain. The first manuscript is a cross-sectional evaluation of factors associated with reduced function in people with chronic pain referred for self-management support in primary health care. The findings suggest number of medications, depressive symptoms, cognitive factors associated with pain, mechanical hyperalgesia, and duration of symptoms explain 63% of the variance in function in people with chronic pain, multiple comorbidities, and barriers to accessing healthcare. The second manuscript is a case-series describing the participation and outcomes of six participants in Chronic pain self-management support with pain science education and exercise (COMMENCE). This study contributes to the literature by detailing the COMMENCE intervention and describing the varied responses of six participants.

The third and fourth manuscripts are a protocol for a randomized controlled trial (RCT) and a completed RCT evaluating the effectiveness of COMMENCE in comparison to a wait-list control. The results suggest COMMENCE improves function for people with chronic pain (mean difference = -8.0 points on the Short Musculoskeletal Function Assessment; 95% confidence interval: -14.7 to -1.3). The fifth manuscript is a planned secondary analysis of the RCT described above. This study suggested people with a greater number of comorbidities are likely to have poorer function at the end of COMMENCE after controlling for age, gender, and baseline function. Together, these factors explained 63% of the variance in function.