Trauma and pain sensitization in youth with chronic pain
Bibliographic record
Abstract
Introduction: Chronic pain (pain lasting ≥3 months) co-occurs with internalizing mental health issues, such as posttraumatic stress symptoms (PTSS), at high rates in youth. The mechanisms underlying these relationships remain unclear. Posttraumatic stress symptoms, including re-experiencing (eg, intrusive memories), alterations in cognition and mood, hyperarousal, and avoidance could lead to altered neuronal processing, pain sensitization, and greater reports of pain. However, the relationships between PTSS and pain sensitization in youth with chronic pain are not known. Methods: Youth (n = 165) aged 10 to 18 years were recruited from outpatient multidisciplinary chronic pain programs. Symptoms of PTSS were assessed using psychometrically sound questionnaires. Youth also underwent a cold-pressor task, the most commonly used experimental pain induction technique. During this task, they reported on their expected pain, actual pain intensity, and pre- and post-state pain catastrophizing. Their pain threshold was recorded. A multivariate general linear model was used to examine the relationships between PTSS, ratings of pain intensity, state pain catastrophizing, and pain threshold, controlling for age, gender, ethnicity, anxiety, and depressive symptoms. Results: ≤ 0.05). Conclusions: Individuals with higher PTSS may avoid or dissociate from pain-inducing stimuli, thus leading to higher pain thresholds. However, individuals with higher PTSS also tend to catastrophize prior to and following exposure to pain. Avoidant and pain catastrophizing behaviors may serve to perpetuate chronic pain conditions. Future research is needed to determine how PTSS are related to pain sensitization prior to the development of chronic pain in at-risk youth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".