Pain-Related Disability in Chronic Pain Patients: Examining the Roles of Pain Intensity, Pain Catastrophizing and Self-Efficacy through a Moderated Mediation Analysis
Bibliographic record
Abstract
Objective: The literature on chronic pain suggests that pain catastrophizing and self-efficacy are important psychological factors involved in chronic pain. The current study aimed to explore the role of pain catastrophizing and self-efficacy in the relationship between pain intensity and pain-related disability. A hypothetical model was proposed in order to investigate whether the association between pain intensity and pain-related disability was mediated by self-efficacy, as well as examining the potential moderator effects of pain catastrophizing on the direct association between pain intensity and pain-related disability, and on the possible mediation. Methods: Analyses were based on a sample of 3.739 outpatients from the Oslo University Hospital Pain Registry (OPR). The OPR is a comprehensive collection of self-reported data on pain characteristics, pain management and physical and mental health. A cross-sectional study was conducted using Baron and Kenny’s method of mediation and moderation to examine a simple mediation effect and simple moderation effects. Furthermore, Hayes’ conditional process analysis was applied in order to examine a possible moderated mediation effect (conditional indirect effect). The measures included a modified version of the Oswestry Disability Index to assess pain-related disability, a 0-10 Numeric Rating Scale to assess usual pain intensity, The General Self-Efficacy Scale to assess perceived self-efficacy, and The Pain Catastrophizing Scale to assess pain catastrophizing and negative orientation towards pain stimuli. Results: The results gave no indication of a moderated mediation effect nor any moderator effects. The simple mediation analysis revealed that self-efficacy partly mediates the association between pain intensity and pain-related disability. Conclusions: In accordance with previous research, the results indicated that self-efficacy partly mediates the association between pain intensity and pain-related disability. On the other hand, the results were in disfavor of pain catastrophizing operating as a moderator as proposed in the hypothesized model. The results could imply that there is a less complex association between pain intensity and pain-related disability than the one postulated in our hypothesized model, or that the examined variables relate to each other in a different way than what we postulated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".