Cognitive-behavioural therapy, mindfulness- and acceptance-based interventions are empirically-supported psychological treatments for chronic pain. These interventions are theorised to elicit change through the unique mechanisms of pain catastrophizing, mindfulness and pain acceptance, respectively. However, in terms of the assessment of these processes, it is not known how unique the most widely-used measures of these constructs are, and what degree of overlap may exist. Hence, it is not known if empirically-supported treatments elicit benefit via the unique reasons specified by theory. This cross-sectional online survey study aimed to comprehensively investigate the associations between pain catastrophizing, mindfulness facets and pain acceptance, determine their relative contributions in affecting pain intensity and pain interference, and identify which construct was most crucial in influencing outcomes. Covariates of age, sex, anxiety, depression and sleep disturbance were also examined. Participants (N = 260) were undergraduate students reporting chronic or intermittent pain. Correlations, regression models, and boot-strap moderated mediation models were conducted. Results demonstrated that as expected, pain catastrophizing, mindfulness and pain acceptance were significantly correlated, however not so substantially as to indicate redundancy. Pain catastrophizing and facets of mindfulness were most important in influencing pain interference, and pain catastrophizing was a key influence of pain intensity. Further, sleep disturbance unexpectedly emerged as significant covariate and moderator of these relations. These results demonstrate that pain catastrophizing, mindfulness and acceptance are related, but unique constructs. Although replication in a clinical sample is needed, these findings highlight the importance of targeting pain catastrophizing and enhancing mindfulness to effectively treat pain. These results also demonstrate the clinical need to assess, and where appropriate treat, sleep disturbance in order to optimise patient care.