Barriers to wound debridement: Results of an online survey
Bibliographic record
Abstract
This paper presents the results of an online survey that investigated healthcare professionals’ knowledge of wound debridement and the techniques used. The survey, using purposive sampling, was distributed to healthcare professionals working within tissue viability services (n=252) via Survey Monkey across the UK to investigate healthcare professionals’ knowledge of wound debridement and the techniques used. Response rate was 31% representing 77 participants practicing in wound care within various healthcare organisations throughout the UK. The majority of respondents (72; 93.5%) reported that they debrided wounds with seventy one respondents (95.9%) reporting they were aware of the TIME concept of which 52 stated they used TIME in their wound management approach. The findings demonstrate that healthcare professionals are aware of the importance of preparing the wound bed for the healing process with the majority of respondents using the TIME (Tissue, Infection/Inflammation, Moisture, Epithelial Edges) concept to support their assessment of wounds. However the knowledge of wound debridement was limited. There was no consensus regarding whether or not health professionals recognised the differences between the terms desloughing and debridement. The majority of healthcare professionals identified time and lack of knowledge and skills as barriers to effective wound debridement techniques.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".