Doubling Your Payoff: Winning Pain Relief Engages Endogenous Pain Inhibition
Bibliographic record
Abstract
When in pain, pain relief is much sought after, particularly for individuals with chronic pain. In analogy to augmentation of the hedonic experience ("liking") of a reward by the motivation to obtain a reward ("wanting"), the seeking of pain relief in a motivated state might increase the experience of pain relief when obtained. We tested this hypothesis in a psychophysical experiment in healthy human subjects, by assessing potential pain-inhibitory effects of pain relief "won" in a wheel of fortune game compared with pain relief without winning, exploiting the fact that the mere chance of winning induces a motivated state. The results show pain-inhibitory effects of pain relief obtained by winning in behaviorally assessed pain perception and ratings of pain intensity. Further, the higher participants scored on the personality trait novelty seeking, the more pain inhibition was induced. These results provide evidence that pain relief, when obtained in a motivated state, engages endogenous pain-inhibitory systems beyond the pain reduction that underlies the relief in the first place. Consequently, such pain relief might be used to improve behavioral pain therapy, inducing a positive, perhaps self-amplifying feedback loop of reduced pain and improved functionality.
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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 | 0.000 | 0.001 |
| 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 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".