Risk and Resistance Factors in Chronic Pain

The majority of research examining adjustment to chronic pain has focused on intra-individual risk predictors of poorer outcomes. Less research has explored ways that risk and resistance factors interact to influence pain adjustment outcomes. In the context of the current research, a risk factor is a variable that is associated with a worsened adjustment outcome; a resistance factor is a variable associated with enhanced adjustment outcomes. To address these deficits in the literature, Wallander and Varni’s (Wallander et al., 1989; Wallander & Varni, 1998) generic risk-resistance model of adjustment to chronic paediatric health conditions was adapted to the chronic pain context. It offered a theory-driven approach to explore a range of effects likely relevant to chronic pain adjustment processes. Improved understanding of ways that a range of predictors directly and indirectly influence chronic pain outcomes will improve specificity of therapeutic targets.
   
   Three studies were completed. The first explored direct and indirect influences of risk and resistance factors on pain-related disability, using pain clinic data obtained from 352 individuals. The second, qualitative study examined factors associated with improved adjustment via interviews with people perceived to be living well with chronic pain. Study Three was informed by Studies One and Two. It tested an expanded version of the model to examine direct and indirect influences of risk and resistance factors on pain-related disability and quality-of-life (QOL) in a community-based sample of 281 pain-affected adults.
   
   Results: The qualitative study identified a range of positive processes that appeared to promote an improved capacity to live with pain. These factors were included in the Study Three model. Pain severity and pain self-efficacy were identified in both Studies One and Three as significant predictors of pain-related disability. In the Study One sample, negative affect and partner responses to pain were also significant predictors of disability. A number of risk and resistance factors were identified as significant predictors of QOL. In all regression models, resistance factors explained additional variance in pain-related disability and QOL over and above that explained by the risk factors, highlighting that strengthening resistance factors in rehabilitation is important.
   
   Mediation effects were explored using both single and parallel mediator models. In single mediator models, a number of pain appraisal and coping factors mediated relationships between predictors and adjustment outcomes. In parallel mediator models predicting pain-related disability, only pain self-efficacy mediated these relationships. In parallel mediator models predicting QOL, several resistance factors mediated these relationships. Moderation analyses identified that those reporting high levels of pain acceptance and values reported the lowest overall levels of pain-related disability, however the relationships between pain severity and negative affect with pain-related disability were stronger for those reporting high levels of the moderators compared to lower levels.
   
   Conclusions: This research extends previous work by exploring direct and indirect influences of risk and resistance factors on pain-related disability and QOL. Pain severity and pain self-efficacy were critical factors associated with pain-related disability while a number of risk and resistance factors were associated with QOL. These factors all represent important therapeutic targets. Moderator analyses demonstrated some resistance factors strengthen risk-outcome relationships at the same time that they provide overall protective effects for adjustment. This highlights the importance of specific and individualised treatment plans.