Examining Interrater Reliability and Validity of a Paediatric Cardiopulmonary Physiotherapy Discharge Tool
Bibliographic record
Abstract
PURPOSE: To determine the interrater reliability (IRR) of the individual items in the Paediatric Cardiopulmonary Physiotherapy (CPT) Discharge Tool. This tool identifies six critical items that physiotherapists should consider when determining a paediatric patient's readiness for discharge from CPT after upper-abdominal, cardiac, or thoracic surgery: oxygen saturation, mobility, secretion retention, discharge planning, auscultation, and signs of respiratory distress. METHODS: A total of 33 paediatric patients (ages 2 to <19 years) who received at least 1 day of CPT following cardiac, thoracic, or upper-abdominal surgery were independently assessed using the Paediatric CPT Discharge Tool by two designated assessors, who assessed each patient within 4 hours of each other. RESULTS: Kappa analysis showed the following levels of interrater agreement for the six items of the Paediatric CPT Discharge Tool: Oxygen Saturation, excellent (κ=0.80); Mobility, substantial (κ=0.62); Secretion Clearance, moderate (κ=0.39); Discharge Planning, fair (κ=0.37); and Auscultation and Respiratory Distress, poor (κ=0.24 and κ=-0.08, respectively). CONCLUSION: Several of the items in the Paediatric CPT Discharge Tool demonstrate good IRR. The discharge tool is ready for further psychometric testing, specifically validity testing.
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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 | 0.064 | 0.159 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".