The Role of Infant Pain Behaviour in Predicting Parent Pain Ratings
Bibliographic record
Abstract
BACKGROUND: Research investigating how observers empathize or form estimations of an individual experiencing pain suggests that both characteristics of the observer ('top down') and characteristics of the individual in pain ('bottom up') are influential. However, experts have opined that infant behaviour should serve as a crucial determinant of infant pain judgment due to their inability to self-report. OBJECTIVE: To predict parents' immunization pain ratings using archival data. It was hypothesized that infant behaviour ('bottom up') and parental emotional availability ('top down') would directly predict the most variance in parent pain ratings. METHODS: Healthy infants were naturalistically observed during their two-, four-, six- and⁄or 12-month immunization appointments. Cross-sectional latent growth curve models in a structural equation model context were conducted at each age (n=469 to n=579) to examine direct and indirect predictors of parental ratings of their infant's pain. RESULTS: At each age, each model suggested that moderate amounts of variance in parent pain report were accounted for by models that included infant pain behaviours (R2=0.18 to 0.36). Moreover, notable differences were found for older versus younger infants with regard to parental emotional availability, infant sex, caregiver age and amount of variance explained by infant variables. CONCLUSIONS: The results of the present study suggest that parent pain ratings are not predominantly predicted by infant behaviours, especially before four months of age. Current results suggest that recognizing infant pain behaviours during painful events may be an important area of parent education, especially for parents of very young infants. Further work is needed to determine other factors that predict parent judgments of infant pain.
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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 | 0.065 | 0.005 |
| 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".