The lived experience of the wound care nurse in caring for patients with pressure ulcers
Bibliographic record
Abstract
The aim of the study was to report the lived experience of the wound care nurse (WCN) in caring for patients with pressure ulcers (PU). WCN play an important role in caring for patients with PU, but the effect on caring for individuals with such wounds is poorly understood. A descriptive and interpretative study on the life worlds of spatiality, temporality, relationality and corporeality was carried out. Utilising the hermeneutic Heideggerian phenomenology, data were collected over a 3-month period in 2012 using in-depth interviews with five WCN. The interviews revealed eight themes: 'challenge', 'making sense of it all', 'coping and self-care', 'advocate of mine/making a difference', 'knowledge and technology', 'we have seen what can happen', 'holistic caring' and 'frustration'. Twenty-five sub-themes were also identified. WCN experienced a demanding and rewarding role of caring, influenced by the environment and the challenges with individuals living with PU. This study demonstrated an enriching yet challenging role. Recommendations for WCN, health care authorities and education providers include raising awareness of the importance of self-care, greater recognition of the effect of this role on patients with PU and changing education to include reflective practice and resilience strategies.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".