Catastrophizing and treatment outcome: differential impact on response to placebo and active treatment outcome
Bibliographic record
Abstract
Abstract Background: The primary objective of this study was to examine the differential impact of catastrophic thinking on response to placebo and active treatment in the context of a clinical trial for the treatment of neuropathic pain. Secondary objectives included examination of specific dimensions of catastrophic thinking that influence response to placebo and active treatment. Methods: A sample of 46 patients (26 men, 20 women) with neuropathic pain were randomly assigned to a placebo (n = 24) or treatment (amitriptyline + ketamine) condition (n = 22). All patients completed the Pain Catastrophizing Scale prior to treatment. Results: There were no significant differences between placebo and active treatment on pain reduction. In the placebo condition, high scores on the PCS were associated with greater pain reduction (r = 0.42, p < 0.05), while in the treatment condition, higher PCS scores were associated with less pain reduction (r = −0.51, p < 0.01). Additional analyses revealed that individuals in the active treatment condition reported slightly more side effects than individuals in the placebo condition, and that catastrophizing was significantly correlated with the report of side effects (r = 0.29, p < 0.05). Conclusion: Catastrophizing appears to have a differential impact on treatment response to placebo and active treatment. Given that side effects are more likely with active treatments than placebos, high levels of catastrophizing might impact negatively on active treatment effects but not necessarily on placebo effects. Discussion addresses how pain catastrophizing may contribute to null findings in clinical trials of interventions for pain disorders. Copyright © 2008 British Society of Experimental & Clinical Hypnosis. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".