Whole versus hole: enabling community nurses to implement holistic wound care
Bibliographic record
Abstract
OBJECTIVE: To improve wound-related quality of life (QoL) in clients with hard-to-heal wounds in their lower limbs and to increase referrals to multidisciplinary teams in the management of care for these clients. METHOD: This was a quality improvement project with a two-group pretest-posttest interventional evaluation design. We implemented a package of interventions including the WounDS app, education related to wound care, and client engagement through a QoL self-assessment. Wound-related QoL was measured using the Cardiff Wound Impact Schedule and referrals to the multidisciplinary team were tracked through chart audits. We explored nurses' experiences with the interventions through semi-structured interviews. RESULTS: Clients' average ratings for 'wellbeing', 'physical symptoms and daily living', and 'overall QoL' improved by 27%, 38% and 54%, respectively. The number of referrals increased by 78% post intervention. Nurses described the interventions as effective strategies that motivated them to implement a holistic approach to care. CONCLUSION: The project was successful in creating a culture shift to practice holistic wound care. This package of interventions (WounDS app, education and client self-assessment of QoL) led to improvements in the QoL of clients with hard-to-heal wounds. Further studies are needed to generalise the findings. Strategies for sustainability include forming a champion group and providing the education and decision supports based on nurses' educational needs assessment.
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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) | 0.000 | 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) | 0.000 | 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".