Risk and Resistance Factors in Chronic Pain
2017
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.
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