Biased interpretations of ambiguous bodily threat information in adolescents with chronic pain
Bibliographic record
Abstract
Adult patients with chronic pain are consistently shown to interpret ambiguous health and bodily information in a pain-related and threatening way. This interpretation bias may play a role in the development and maintenance of pain and disability. However, no studies have yet investigated the role of interpretation bias in adolescent patients with pain, despite that pain often first becomes chronic in youth. We administered the Adolescent Interpretations of Bodily Threat (AIBT) task to adolescents with chronic pain (N = 66) and adolescents without chronic pain (N = 74). Adolescents were 10 to 18 years old and completed the study procedures either at the clinic (patient group) or at school (control group). We found that adolescents with chronic pain were less likely to endorse benign interpretations of ambiguous pain and bodily threat information than adolescents without chronic pain, particularly when reporting on the strength of belief in those interpretations being true. These differences between patients and controls were not evident for ambiguous social situations, and they could not be explained by differences in anxious or depressive symptoms. Furthermore, this interpretation pattern was associated with increased levels of disability among adolescent patients, even after controlling for severity of chronic pain and pain catastrophizing. The current findings extend our understanding of the role and nature of cognition in adolescent pain, and provide justification for using the AIBT task in longitudinal and training studies to further investigate causal associations between interpretation bias and 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 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".