Don’t judge a book by its cover: Exploring low self-reported distress and repressive coping in a pediatric chronic pain population
Bibliographic record
Abstract
Repression has been linked to greater illness, somatic symptoms, and poorer physical health, both in adult and pediatric populations. The current study examined psychological and pain profiles of children with chronic pain who may under-report levels of psychological distress at a first interdisciplinary chronic pain assessment. Children and their caregiver completed measures of psychopathology and pain intensity, while clinicians rated their levels of disability. Based on self-report measures, children were classified as "repressors" (low anxiety/high social desirability) or as "true low anxious" (low anxiety/low social desirability). Groups were then compared on psychological and pain characteristics. Compared to children with true low anxiety, repressors reported lower levels of depressive and somatic symptoms but provided higher ratings on pain intensity, pain-unpleasantness, and self-oriented perfectionism. Caregivers of repressors rated their children as having higher levels of adaptability compared to caregivers of children in the true low anxious group. Groups did not differ on clinician-rated level of disability. Children classified as repressors exhibited different profiles than children classified as having true low anxiety on both psychological outcomes and pain characteristics. Repression may be an important factor to consider for those assessing and treating children with chronic pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".