Measuring distress in South African children during burns dressing changes: A pilot study
Bibliographic record
Abstract
OBJECTIVES: To establish and trial a practical, evidence-based, sensitive, language-fair, and culture-fair test battery to measure South African children's distress during burns dressing change. METHODS: We previously identified a broad test battery for pediatric procedural distress from the literature. This comprised child and parent heart rate; three instruments for observed distress behaviors-(1) Face, Legs, Activity, Cry, Consolability (FLACC); (2) Pain Behavior Check List (PBCL); and (3) Children's Hospital Eastern Ontario Pain Scale (CHEOPS); and dressing change time, number of nurses required, and nurses' perspectives of child's distress. A consecutive cohort of South African inpatient children with burns was recruited. In the first study, three observers independently piloted the broad set of measures on four children. This set was subsequently modified to increase practicality of application and measurement sensitivity. In the second study, the modified battery was tested on 16 children for sensitivity to different children's distress levels during burns dressing change phases. RESULTS: The modified test battery was comprised of the CHEOPS, dressing change time, number of nurses required, and nurses' qualitative perspectives of child's distress. In combination, these tests were practical and sensitive to children's distress. DISCUSSION: South African children's distress during burn dressing changes manifests in different ways. Adequate capture of it requires a comprehensive set of objective, observational, and qualitative measures, which are independent of language and culture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".