Does readiness to change influence pain-related outcomes after an educational intervention for people with chronic pain? A pragmatic, preliminary study
Bibliographic record
Abstract
Background: There is a strong association between chronic pain and unhelpful pain cognitions. Educating patients on pain neuroscience has been shown to reduce pain catastrophization, kinesiophobia, and self-perceived disability. This study investigated whether a group-based pain neuroscience education (PNE) session influenced pain-related outcomes, and whether readiness to change moderated these outcomes.Method: In a pragmatic pre-post-intervention study using a convenience sample, adults with chronic pain participated in one, 90–120 minute PNE session. Pain-related outcomes (i.e. pain catastrophization, kinesiophobia, disability, and pain neuroscience knowledge) and the Pain Stage of Change Questionnaire (PSOCQ) were assessed at baseline and immediately post-intervention. Paired t-tests evaluated pre-post changes in outcomes, and linear regression examined the impact of PSOCQ score changes on PNE-induced changes in clinical outcomes.Results: Sixty-five participants were recruited. All outcomes showed positive intervention effects (p < .01). Relationships between changes in PSOCQ subscale scores and change in post-intervention pain-related outcomes were found; ‘Pre-Contemplation’ was positively associated with pain catastrophization (p = .01), and ‘Action’ was negatively associated with kinesiophobia (p = .03).Conclusion: Consistent with previous research, there were improvements in outcomes associated with chronic pain after PNE. Some of these improvements were predicted by changes in PSOCQ scores, however, these findings are preliminary and require further investigation using controlled research designs.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".