Role of anxiety in young children's pain memory development after surgery
Bibliographic record
Abstract
Pediatric pain is common, and memory for it may be distressing and have long-lasting effects. Children who develop more negatively biased memories for pain (ie, recalled pain is higher than initial pain report) are at risk of worse future pain outcomes. In adolescent samples, higher child and parent catastrophic thinking about pain was associated with negatively biased memories for postsurgical pain. This study examined the influence of child and parent anxiety on the development of younger children's postsurgical pain memories. Seventy-eight children undergoing a tonsillectomy and one of their parents participated. Parents reported on their anxiety (state and trait) before surgery, and trained researchers observationally coded children's anxiety at anaesthesia induction. Children reported on their postsurgical pain intensity and pain-related fear for 3 days after discharge. One month after surgery, children recalled their pain intensity and pain-related fear using the same scales previously administered. Results revealed that higher levels of postsurgical pain and higher parent trait anxiety predicted more negatively biased memories for pain-related fear. Parent state anxiety and child preoperative anxiety were not associated with children's recall. Children who developed negatively biased pain memories had worse postsurgical pain several days after surgery. These findings underscore the importance of reducing parental anxiety and effective postsurgical pain management to potentially buffer against the development of negatively biased pain memories in young children.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".