Inter-subject variability of pleasant pain relief using a data-driven approach in healthy volunteers
Bibliographic record
Abstract
Background: The offset of a painful and unpleasant sensation can elicit pleasure. This phenomenon, namely pleasant pain relief (PPR), is attracting growing interest in research. While the cold pressor test (CPT) has been frequently used to study the inhibition of pain by the administration of another painful stimulation (inhibitory conditioned pain modulation; ICPM), a preliminary study from our research team has shown that CPT can also elicit a robust and long-lasting PPR. However, its effects on pain relief and inhibition vary greatly between subjects. Although substantial research has been carried out on inter-individual variability in the case of ICPM, the same cannot be said of PPR. Therefore, the current study sought to identify clusters of healthy volunteers with similar dynamic pain responses during the CPT, using a data-driven approach, and to investigate the inter-subject variability for PPR and ICPM. Methods: One hundred and twenty-two healthy volunteers were recruited. A sequential ICPM paradigm was carried out with CPT (water at 10°C) and a Peltier Thermode to evaluate pain intensity and unpleasantness. Moreover, PPR was measured for four minutes at CPT offset. Statistical analyses were performed using group-based trajectory modelling. Results: < 0.001). On the other hand, no differences were found between groups regarding ICPM efficacy (percentage pain inhibition). Discussion: This study has provided a first step into the investigation of PPR and ICPM interindividual variability. Using a data-driven approach, it was shown that PPR at CPT offset differs between clusters of participants identified based on dynamic pain intensity and unpleasantness responses from CPT. Thus, it was brought to light that both the levels of tonic pain and pain sensitization underlie individual differences in PPR. The lack of correlation between CPT pain trajectories and ICPM efficacy may be explained by the hypotheses that eliciting ICPM requires only a certain threshold of stimulation which doesn't need to be noxious. In the future, studies on the inter-subject variability of PPR in large samples of chronic pain patients are warranted.
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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 | 0.052 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".