A Systematic Review of Faces Scales for the Self-report of Pain Intensity in Children
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Bibliographic record
Abstract
CONTEXT: Numerous faces scales have been developed for the measurement of pain intensity in children. It remains unclear whether any one of the faces scales is better for a particular purpose with regard to validity, reliability, feasibility, and preference. OBJECTIVES: To summarize and systematically review faces pain scales most commonly used to obtain self-report of pain intensity in children for evaluation of reliability and validity and to compare the scales for preference and utility. METHODS: Five major electronic databases were systematically searched for studies that used a faces scale for the self-report measurement of pain intensity in children. Fourteen faces pain scales were identified, of which 4 have undergone extensive psychometric testing: Faces Pain Scale (FPS) (scored 0-6); Faces Pain Scale-Revised (FPS-R) (0-10); Oucher pain scale (0-10); and Wong-Baker Faces Pain Rating Scale (WBFPRS) (0-10). These 4 scales were included in the review. Studies were classified by using psychometric criteria, including construct validity, reliability, and responsiveness, that were established a priori. RESULTS: From a total of 276 articles retrieved, 182 were screened for psychometric evaluation, and 127 were included. All 4 faces pain scales were found to be adequately supported by psychometric data. When given a choice between faces scales, children preferred the WBFPRS. Confounding of pain intensity with affect caused by use of smiling and crying anchor faces is a disadvantage of the WBFPRS. CONCLUSIONS: For clinical use, we found no grounds to switch from 1 faces scale to another when 1 of the scales is in use. For research use, the FPS-R has been recommended on the basis of utility and psychometric features. Data are sparse for children below the age of 5 years, and future research should focus on simplified measures, instructions, and anchors for these younger children.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it