Acceptance and disengagement: temporal, energetic and pain recovery effects as the costs of control in coping with pain
Bibliographic record
Abstract
Two studies examined the hypothesis that acceptance and control-based interventions for pain have specific self-regulatory costs and benefits. Both studies consisted of volunteers from a sample derived from the pool of psychology students at the University of Manitoba. Relative to control-based coping, acceptance was predicted to be associated with: 1) Normalization of time distortion; 2) Faster post-stimulus pain recovery 3) Preservation of self-regulatory energy required for acts of self-control; 4) Stronger pain coping self-efficacy beliefs, relative to two control-based coping strategies: suppression and distraction, and 5) improved pain tolerance. Study I (N=180) showed no group differences for pain tolerance, retrospective duration judgments or self-efficacy ratings, and weak evidence of differential pain recovery effects. As predicted, temporal speed ratings were slower for the suppression condition relative to the distraction condition. In Study II the pattern of condition effects for temporal speed was replicated though the statistical main effect only approached significance. In Study II (N=190), between-group differences were detected for pain tolerance, pain recovery, retrospective duration judgments and self-efficacy belief variables. As predicted the distraction group showed higher pain tolerance than the suppression group. Contrary to prediction, the difference between distraction and acceptance for pain tolerance was not significant. Contrary to predictions the greatest normalization of retrospective duration distortion occurred in the distraction condition. As predicted, post-intervention self-efficacy ratings were higher for acceptance than suppression but the difference between acceptance and distraction was not significant. Predicted pain recovery effects were also detected in Study II such that pain ratings for the suppression and distraction conditions were higher than for the acceptance condition at 60 and 120 seconds post-tolerance. Hypothesized between-group differences for self-regulatory-strength depletion were not confirmed. Possible reasons for lack of difference between acceptance and distraction on pain tolerance ratings and ego depletion measures, as well as possible future research directions were discussed.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".