Emotional awareness and expression difficulties in relation to pain experiences in people with brain injury and chronic pain: preliminary investigation
Bibliographic record
Abstract
OBJECTIVES: Preliminary examination of emotional awareness/expression relationships with pain in people with traumatic brain injury (TBI) and chronic pain (CP) and exploration of psychological factors as mediators or moderators of these relationships. METHODS: = 59) with chronic TBI and CP using Toronto Alexithymia Scale-20 Difficulty Identifying and Describing Feelings subscales; Ambivalence over Emotional Expressiveness Questionnaire; Emotional Approach Coping Scale; PROMIS Pain Intensity and Pain Interference scales, Michigan Body Map (pain widespreadness); headache frequency; Pain Catastrophizing Scale; Brief Symptom Inventory-18 (psychological distress), and Post-traumatic Stress Checklist-Civilian. RESULTS: Difficulty Identifying Feelings was positively associated with pain intensity, pain interference, and headache frequency. Difficulty Describing Feelings was positively correlated with pain interference and headache frequency. Emotional Approach Coping was inversely correlated with headache frequency. Emotional awareness/expression relationships with pain outcomes were mediated by Pain Catastrophizing; Difficulty Describing Feelings relationships with Pain Interference and headache frequency were mediated by psychological distress; and Difficulty Describing Feelings associations with Pain Interference were mediated by post-traumatic stress. No moderators were identified. CONCLUSION: These preliminary findings suggest that emotional awareness/expression is linked to pain in adults with TBI and CP, which may be connected via pain catastrophizing and psychological distress. If longitudinal studies with larger samples produce similar findings, researchers should explore training emotional awareness/expression for possible pain management after TBI.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".