Specific Newborn Individualized Developmental Care and Assessment Program Movements Are Associated With Acute Pain in Preterm Infants in the Neonatal Intensive Care Unit
Bibliographic record
Abstract
OBJECTIVE: The Newborn Individualized Developmental Care and Assessment Program (NIDCAP) is widely used in neonatal intensive care units and comprises 85 discrete infant behaviors, some of which may communicate infant distress. The objective of this study was to identify developmentally relevant movements indicative of pain in preterm infants. METHODS: Forty-four preterm infants were assessed at 32 weeks' gestational age (GA) during 3 phases (baseline, lance/squeeze, and recovery) of routine blood collection in the neonatal intensive care unit. The NIDCAP and Neonatal Facial Coding System (NFCS) were coded from separate continuous bedside video recordings; mean heart rate (mHR) was derived from digitally sampled continuous electrographic recordings. Analysis of variance (phase x gender) with Bonferroni corrections was used to compare differences in NIDCAP, NFCS, and mHR. Pearson correlations were used to examine relationships between the NIDCAP and infant background characteristics. RESULTS: NFCS and mHR increased significantly to lance/squeeze. Eight NIDCAP behaviors also increased significantly to lance/squeeze. Another 5 NIDCAP behaviors decreased significantly to lance/squeeze. Infants who had lower GA at birth, had been sicker, had experienced more painful procedures, or had greater morphine exposure showed increased hand movements indicative of increased distress. CONCLUSIONS: Of the 85 NIDCAP behaviors, a subset of 8 NIDCAP movements were associated with pain. Particularly for infants who are born at early GAs, addition of these movements to commonly used measures may improve the accuracy of pain assessment.
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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 | 0.000 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".