Pleasant Visual Stimuli Decrease Sensitivity To Pain But Only Among Highly Sensitive Adults
Bibliographic record
Abstract
Purpose: In recent years (VSS 13,14,15, 18), our lab has examined the interactions among different sensory modalities, namely whether there are relationships between various measures of vision, hearing, and pain sensitivity. One of the surprising findings was that there appears to be some link between visual and haptic (pain and touch) threshold sensitivity in individual adults. Here, we examine the interactions more directly by measuring the additive effect of visual involvement on pain sensitivity. In particular, we were interested in examining whether pleasant visual stimuli can attenuate pain responses in individuals with low vs. high pain thresholds. Methods: The left hand index finger of 60 young adults was exposed to a pressure algometer and measures of pain threshold and tolerance obtained under standard controlled conditions. Pain measurements were then repeated with exposure to two different types of positive/pleasant visual stimuli (money, nature scene). Order of all 3 conditions was counterbalanced across adults, and a standard refractory period of 1 minute was used between tests. Results: Adults were divided into 2 equal groups (high vs. low pain sensitivity) based on measurements of threshold in the control condition. Paired t-tests showed that compared to control, adults with high pain sensitivity (thresholds < 450 g) showed increased pain threshold and tolerance when exposed to visual stimuli. Conversely, those with low sensitivity (>450 g) showed no increases in pain measures for both positive visual stimuli. Floor and ceiling effects were not apparent within the data. Conclusions: Our results imply that positive (pleasant) visual stimuli have a modulating effect on adult pain sensitivity. However, this analgesic effect is small and appears limited to those adults who are already more highly sensitive (have lower thresholds) to pain. This result likely explains the equivocal findings from previous studies examining this issue
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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) | 0.005 | 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".