A smartphone version of the Faces Pain Scale‐Revised and the Color Analog Scale for postoperative pain assessment in children
Bibliographic record
Abstract
BACKGROUND: Effective pain assessment is essential during postoperative recovery. Extensive validation data are published supporting the Faces Pain Scale-Revised (FPS-R) and the Color Analog Scale (CAS) in children. Panda is a smartphone-based application containing electronic versions of these scales. OBJECTIVES: To evaluate agreement between Panda and original paper/plastic versions of the FPS-R and CAS and to determine children's preference for either Panda or original versions of these scales. METHODS: ASA I-III children, 4-18 years, undergoing surgery were assessed using both Panda and original versions of either the FPS-R or CAS. Pain assessments were conducted within 10 min of waking from anesthesia and 30 min later. RESULTS: Sixty-two participants, median (range) age 7.5 (4-12) years, participated in the FPS-R trial; Panda scores correlated strongly with the original scores at both time points (Pearson's r > 0.93) with limits of agreement within clinical significance (80% CI). Sixty-six participants, age 13 (5-18) years, participated in the CAS trial. Panda scores correlated strongly with the original scores at both time points (Pearson's r > 0.87); mean pain scores were higher (up to +0.47 out of 10) with Panda than with the original tool, representing a small systematic bias, but limits of agreement were within clinical significance. Most participants who expressed a preference preferred Panda over the original tool (81% of FPS-R, 76% of CAS participants). CONCLUSION: The Panda smartphone application can be used in lieu of the original FPS-R and CAS for assessment of pain in children. Children's preference for Panda may translate to improved cooperation with self-report of 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 | 0.007 | 0.001 |
| 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".