HOW A DIGNITY CARE INTERVENTION CAN IMPROVE CARE BY COMMUNITY NURSES TO PEOPLE IN THE LAST MONTHS OF LIFE
Bibliographic record
Abstract
Background This study has developed, implemented and tested a complex intervention, the Dignity Care Intervention (DCI), providing an evidence based approach to providing person centred dignity conserving, palliative care to patients and their families receiving end-of-life care at home by community nurses (CNs). Aims The primary aim was to explore the feasibility and acceptability of the DCI from the patients' and carers' perspectives. A secondary aim was to explore the ability of the DCI to allow individual dignity related needs to be assessed and subsequently met, by community nurses. Methods A qualitative, evaluation design underpinned by the philosophy of Merlau-Ponty was employed for the evaluation of the DCI. Data collection included focus groups with CNs (39) at the beginning and end of the study; individual interviews with patients (30); informal carers (4). Interview data were analysed using framework analysis. Results The analysis of the interviews resulted in four theme categories and 16 subthemes. Experience of DCP; responding to my illness concerns, how illness affects me as a person and how illness concerns affect my relationships. Patients and family members identified that the use of the DCI by nurses beneficial, as they were given the opportunity to discuss concerns that might have not been raised otherwise. Conclusions The DCI helps CNs deliver psychosocial care, previously identified as a difficult area for CNs in practice. CNs use of the DCI helps patients receive individualised care, which directly relates to the issues they have identified as most distressing and/or important and their preferred measures to address these issues, allowing increased information and support to carers. The use of the PDI facilitated patient's communication of their dignity-related needs to community nurses, which highlighted increased satisfaction with the support they received.
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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 | 0.003 |
| 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 | 0.001 |
| 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".