Developing a Physiotherapy-Specific Preliminary Clinical Decision-Making Tool for Oxygen Titration: A Modified Delphi Study
Bibliographic record
Abstract
PURPOSE: To develop and evaluate a preliminary clinical decision-making tool (CDMT) to assist physiotherapists in titrating oxygen for acutely ill adults in Ontario. METHODS: A panel of 14 experienced cardiorespiratory physiotherapists was recruited. Factors relating to oxygen titration were identified using a modified Delphi technique. Four rounds of questionnaires were conducted, during which the goals were to (1) generate factors, (2) reduce factors and debate contentious factors, (3) finalize factors and develop the preliminary CDMT, and (4) evaluate the usability of the tool in a clinical context. RESULTS: The panel reached consensus on a total of 89 factors, which were compiled to create the preliminary CDMT. The global tool reached consensus for sensibility, receiving a mean score of 6/7 on a 7-point Likert-type scale (1=unacceptable; 7=excellent). Five of the nine individual components of evaluation of the tool achieved scores ≥6.0; the remaining four had mean scores between 5.4 and 5.9. CONCLUSION: This study produced a preliminary CDMT for oxygen titration, which the panel agreed was highly comprehensible and globally sensible. Further research is necessary to evaluate the sensibility and applicability of the tool in a clinical setting.
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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 | 0.121 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".