Dispositional Mindfulness and Acute Heat Pain: Comparing Stimulus-Evoked Pain With Summary Pain Assessment
Bibliographic record
Abstract
OBJECTIVE: Dispositional mindfulness is associated with reduced pain in clinical and experimental settings. However, researchers have neglected the type of pain assessment, as dispositional mindfulness may have unique benefits for reduced pain sensitivity when relying on summary pain assessments, in contrast to assessing the pain of each noxious stimulus. Here, we test the association between dispositional mindfulness and pain using both trial-by-trial pain assessments and overall summary ratings after acute pain tasks. METHODS: One hundred thirty-one healthy adult volunteers (mean age = 29.09 [8.00] years, 55.7% female) underwent two experimental thermal pain paradigms. We tested whether dispositional mindfulness measured with the Mindful Attention Awareness Scale was related to a) heat-evoked pain sensitivity, as measured by pain threshold, pain tolerance, average pain, trial-by-trial ratings, and heat-evoked skin conductance response, and b) summary judgments of sensory and affective pain assessed using the McGill Pain Questionnaire (MPQ). RESULTS: Mindful Attention Awareness Scale ratings were associated with decreased pain on the MPQ sensory (B = -0.18, SE = 0.05, 95% confidence interval = -0.29 to -0.07, t = -3.28, p = .001) and affective (B = -0.11, SE = 0.03, 95% confidence interval = -0.18 to -0.05, t = -3.32, p = .001) dimensions but not with experimental thermal pain assessments, including threshold, tolerance, heat-evoked pain, or skin conductance response (p values ≥ .29). CONCLUSIONS: In this study, dispositional mindfulness mitigated acute thermal pain only when pain was assessed using the MPQ. These findings may reflect differences in immediate versus retrospective judgments or the type of pain assessed by each measure. Future research should examine regulation processes that may explain these differential analgesic benefits, such as attention, rumination, or reappraisal.
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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) | 0.001 | 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) | 0.019 | 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".