Children's shyness and frontal electroencephalogram delta–beta correlation in the pediatric surgical setting
Bibliographic record
Abstract
Abstract The prospect of surgery is a unique psychologically threatening context for children, often leading to experiences of preoperative anxiety. Recent research suggests that individual differences in children's temperament may influence responses to the surgical setting. In the present study, we examined whether individual differences in shyness were related to differences in frontal electroencephalogram (EEG) delta–beta correlation, a proposed neural correlate of emotion regulation and dysregulation, among children anticipating surgery. Seventy‐one children (36 boys, M age = 10.3 years, SD age = 1.7 years) undergoing elective surgery self‐reported on their own shyness, and their parents also reported on their child's shyness. Using a mobile, dry sensor EEG headband, frontal EEG measures were collected and self‐ and observer‐reported measures of state anxiety were obtained at the children's preoperative visit (Time 1) and on the day of surgery (Time 2). A latent cluster analysis derived classes of low shy ( n = 37) and high shy ( n = 34) children using the child‐ and parent‐reported shyness measures. We then compared the two classes on frontal EEG delta–beta correlation using between‐ and within‐subjects analyses. Although children classified as high versus low in shyness had higher self‐ and observer‐reported state anxiety across both time periods, frontal EEG delta–beta correlation increased from T1 to T2 only among low shy children using a between‐subjects delta–beta correlation measure. We discuss the interpretation of a relatively higher delta–beta correlation as a correlate of emotion regulatory versus dysregulatory strategies for some children in a “real‐world,” surgical context.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".