Enhancing end-of-life care in Ghana: nurse strategies and practices in addressing patient needs
Bibliographic record
Abstract
BACKGROUND: Globally, end-of-life care is vital for individuals in their final months or years, emphasizing comfort and dignity. However, the provision of palliative care in low-resource countries, such as Ghana, remains inadequately documented and poorly understood. This study aimed to identify the specific end-of-life care needs of patients and families and explore strategies to enhance end of life care practices among nurses in selected settings in Accra, Ghana. METHODOLOGY: This qualitative research utilized in-depth, one-on-one interviews using semi-structured interviews in a sample of N = 32 nurses working in two selected hospitals in Ghana. Thematic content analysis was used to analyze the data. Participants were purposively selected, with the sample size determined by data saturation. RESULTS: The analysis identified three main themes and eleven subthemes. The main themes were: providing dignity and comfort care, respecting ethical values, and perceptions of end-of-life care. The subthemes included: showing presence, demonstrating compassion, addressing challenges in end-of-life conversations, fostering autonomy and respect, managing gratitude and discontent, helping patients accept their condition, seeking additional training, building emotional connections, involving families, and respecting patients' cultural, social, and religious beliefs. The participants had cared for or were currently caring for patients aged 50-75 years with cancer, organ failures, Advanced Heart diseases and cognitive disorders. Participants described their efforts to make the last days of their patients and families memorable as possible. CONCLUSIONS: Nurses in Ghana provide compassionate care, addressing pain relief, ethical concerns, and patient expressions of gratitude and discontent, with their efforts influenced by religious and cultural factors. To enhance end of life care quality, policymakers should implement structured end-of-life care training for nurses and develop culturally aligned palliative care guidelines to meet the needs of patients receiving end of life care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".