Clinical relevance of attentional biases in pediatric chronic pain: an eye-tracking study
Bibliographic record
Abstract
ABSTRACT: Attentional biases have been posited as one of the key mechanisms underlying the development and maintenance of chronic pain and co-occurring internalizing mental health symptoms. Despite this theoretical prominence, a comprehensive understanding of the nature of biased attentional processing in chronic pain and its relationship to theorized antecedents and clinical outcomes is lacking, particularly in youth. This study used eye-tracking to assess attentional bias for painful facial expressions and its relationship to theorized antecedents of chronic pain and clinical outcomes. Youth with chronic pain (n = 125) and without chronic pain (n = 52) viewed face images of varying levels of pain expressiveness while their eye gaze was tracked and recorded. At baseline, youth completed questionnaires to assess pain characteristics, theorized antecedents (pain catastrophizing, fear of pain, and anxiety sensitivity), and clinical outcomes (pain intensity, interference, anxiety, depression, and posttraumatic stress). For youth with chronic pain, clinical outcomes were reassessed at 3 months to assess for relationships with attentional bias while controlling for baseline symptoms. In both groups, youth exhibited an attentional bias for painful facial expressions. For youth with chronic pain, attentional bias was not significantly associated with theorized antecedents or clinical outcomes at baseline or 3-month follow-up. These findings call into question the posited relationships between attentional bias and clinical outcomes. Additional studies using more comprehensive and contextual paradigms for the assessment of attentional bias are required to clarify the ways in which such biases may manifest and relate to clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.015 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".