Facial Expression of Children Receiving Immunizations: A Principal Components Analysis of the Child Facial Coding System
Bibliographic record
Abstract
OBJECTIVE: To identify the structure of facial reaction to procedural pain and to determine the subset of facial actions that best describe the response. DESIGN: Observational. SETTING: Five rural and five urban physicians' offices. PATIENTS: One hundred twenty-three children aged 4 to 5 years undergoing routine diphtheria, pertussis, tetanus, and polio immunization. OUTCOME MEASURES: The Child Facial Coding System, comprising 13 discrete facial actions, was used to code each second of five 10-second phases from videotape: baseline, preneedle, needle, postneedle, and posthandling. Parents and a technician provided visual analog scale ratings of children's pain. Children provided a self-report using a Faces Pain Scale, and parents and nurses rated the children's pain and anxiety using visual analog scales. RESULTS: A "pain face" similar to that reported in adults emerged with the onset of pain. Principal component analyses revealed the frequency and intensity of facial action during the needle phase could be represented by components reflecting pain sensation, a "brave face," and the children's expectations for pain. Children's Faces Pain Scale and adult visual analog scale ratings were best predicted by components reflecting pain sensation and expectations of high pain. CONCLUSIONS: These results provide a preliminary indication that the Child Facial Coding System can be reduced to components that reflect several aspects of children's acute pain experience and predict self-reports and observer reports of children's pain.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".