Music interferes with expectation-induced pain modulation: a controlled cross-over experimental study
Bibliographic record
Abstract
Abstract Introduction: Music reduces pain and anxiety in various contexts, but the possible effect on pain anticipatory mechanisms remains unclear. Objectives: This study examines the effects of a standardized musical intervention (Music Care) on pain perception and on pain modulation induced by expectations of low or high pain. Methods: Healthy participants were tested in an experimental study using a crossover design involving the musical intervention counterbalanced with an active auditory control condition (audiobook) and a silent control condition. Pain perception was assessed using contact heat stimulation, and expectations were manipulated using prestimulus anticipatory cues signalling high or low pain. Results: Perceived pain intensity, measured using a visual analog scale, was decreased during the music intervention and the audiobook compared to silence ( P's < 0.001). Music was more effective than the audiobook control, especially at the higher pain stimulation level ( P < 0.001). Anticipatory cues modulated pain and anxiety in the expected direction across all conditions ( P's < 0.001). Music and the audiobook produced comparable reduction in (1) expectation-induced (1a) hypoalgesic and (1b) hyperalgesic effects (all P's < 0.005) and in (2) pain anticipatory anxiety (all P's < 0.05). Overall, music was more effective than the active auditory control to reduce pain but both forms of auditory distraction partly blocked the modulatory effects of low and high pain expectations. Conclusion: This study highlights the multiplicity of processes contributing to music-induced analgesia and suggests that music may help improve pain management in the context of high pain expectation and anxiety. However, music may also interfere with pain-relieving strategies involving the induction of low pain expectations.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".