Comparison of the Psychometric Properties of the FLACC Scale, the MBPS and the Observer Applied Visual Analogue Scale Used to Assess Procedural Pain
Bibliographic record
Abstract
Dianne Crellin,1– 3 Denise Harrison,1,2,4 Nick Santamaria,1 Franz E Babl2,3,5 1Department of Nursing, The University of Melbourne, Melbourne, VIC, Australia; 2Murdoch Children’s Research Institute, Melbourne, VIC, Australia; 3Royal Children’s Hospital, Melbourne, VIC, Australia; 4Children’s Hospital of Eastern Ontario and University of Ottawa, Ottawa, ON, Canada; 5Department of Paediatrics, The University of Melbourne, Melbourne, VIC, AustraliaCorrespondence: Dianne Crellinc/o Emergency Department, Royal Children’s Hospital, Flemington Road Parkville, Melbourne, VIC, 3052, AustraliaTel +61 39345 5331Fax +61 9345 5983Email dianne.crellin@rch.org.auPurpose: The purpose of this study was to compare the psychometric data and feasibility and clinical utility of the Face Legs, Activity, Cry and Consolability scale (FLACC), the Modified Behavioral Pain Scale (MBPS) and the Visual Analogue Scale for observers (VASobs) used to assess procedural pain in infants and young children.Patients and Methods: Twenty-six clinicians assessed videorecorded segments of 100 infants and young children who underwent a painful and/or distressing procedure in the emergency department using the FLACC scale, the MBPS and the VASobs pain and VASobs distress.Results: VASobs pain scores were lowest across all procedures and phases of procedures (p < 0.001). Inter-rater reliability was lowest for VASobs pain scores (ICC 0.55). Sensitivity and specificity were highest for FLACC scores (94.9% and 72.5%, respectively) at the lowest cut-off score (pain score two). Observers changed their MBPS scores more often than they changed FLACC or VASobs scores, but FLACC scores were more often incomplete. Reviewers did not consider any scale of use for procedural pain measurement.Conclusion: The reliability and sensitivity of the FLACC and MBPS were supported by study data but concerns about the capacity of these scales to distinguish between pain- and non-pain-related distress were raised. The VASobs cannot be recommended. Despite its limitations, the FLACC scale may be better suited than other scales for procedural pain measurement.Keywords: pain measurement, infants, validity, reliability
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".