Registered Nurses' beliefs about end-of-life care: A mixed method study

AIMS

To examine registered nurses' (RNs) behavioural, normative and control beliefs about end-of-life care for patients who are diagnosed with advanced and life-limiting illnesses; and to identify the barriers and facilitators they experience when providing end-of-life care.

DESIGN

A sequential explanatory mixed methods study.

METHOD

An online cross-sectional survey was conducted using the Care for Terminally Ill Patient tool among 1293 RNs working across five hospitals in the Kingdom of Saudi Arabia. Online individual semi-structured interviews with a subgroup of survey respondents were then undertaken. Data were collected between October 2020 to February 2021.

RESULTS

A total of 415 RNs completed the online survey, with 16 of them participating in individual interviews. Over half of the participants expressed the belief that end-of-life care is most efficiently delivered through multidisciplinary team collaboration. The majority of participants also believed that discussing end-of-life care with patients or families leads to feelings of hopelessness. Paradoxically, the study revealed that more than half of the participants held the negative belief that patients at the end of life should optimally receive a combination of both curative and palliative care services. The results showed that nurses' beliefs were significantly associated with their age, religion, ward type, level of education and frequency of providing end-of-life care. Data from the qualitative interviews identified four themes that explored RNs' beliefs and its related factors. The four themes were 'holistic care', 'diversity of beliefs', 'dynamics of truth-telling' and 'experiences of providing end-of-life care.'

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Wherever possible, patients at the end-of-life should be cared for in specialist settings by multidisciplinary teams to ensure effective, high-quality care. Where this is not possible, organisations should ensure that teams of multidisciplinary staff, including nurses, receive education and resources to support end-of-life care in non-specialist settings. Hospitals that employ foreign-trained nurses should consider providing targeted education to enhance their cultural competence and reduce the impact of different beliefs on end-of-life care.

Memory T Cells Discrepancies in COVID-19 Patients

The immune response implicated in Coronavirus disease 2019 (COVID-19) pathogenesis remains to be fully understood. The present study aimed to clarify the alterations in CD4+ and CD8+ memory T cells' compartments in SARS-CoV-2-infected patients, with an emphasis on various comorbidities affecting COVID-19 patients. Peripheral blood samples were collected from 35 COVID-19 patients, 16 recovered individuals, and 25 healthy controls, and analyzed using flow cytometry. Significant alterations were detected in the percentage of CD8+ T cells and effector memory-expressing CD45RA CD8+ T cells (TEMRA) in COVID-19 patients compared to healthy controls. Interestingly, altered percentages of CD4+ T cells, CD8+ T cells, T effector (TEff), T naïve cells (TNs), T central memory (TCM), T effector memory (TEM), T stem cell memory (TSCM), and TEMRA T cells were significantly associated with the disease severity. Male patients had more CD8+ TSCMs and CD4+ TNs cells, while female patients had a significantly higher percentage of effector CD8+CD45RA+ T cells. Moreover, altered percentages of CD8+ TNs and memory CD8+CD45RO+ T cells were detected in diabetic and non-diabetic COVID-19 patients, respectively. In summary, this study identified alterations in memory T cells among COVID-19 patients, revealing a sex bias in the percentage of memory T cells. Moreover, COVID-19 severity and comorbidities have been linked to specific subsets of T memory cells which could be used as therapeutic, diagnostic, and protective targets for severe COVID-19.

Registered Nurses' attitudes towards end-of-life care: A sequential explanatory mixed method study

AIMS

To examine registered nurses' attitudes about end-of-life care and explore the barriers and facilitators that influence the provision of high-quality end-of-life care.

DESIGN

A sequential explanatory mixed methods research design was used.

METHODS

An online cross-sectional survey was distributed to 1293 registered nurses working in five different hospitals in the Kingdom of Saudi Arabia. The Frommelt Attitudes Towards Care of the Dying Scale was used to assess nurses' attitudes towards end-of-life care. Following the survey, a subset of registered nurses were interviewed using individual semi-structured interviews.

RESULTS

Four hundred and thirty-one registered nurses completed the online survey, and 16 of them participated in individual interviews. Although nurses reported positive attitudes towards caring for dying patients and their families in most items, they identified negative attitudes towards talking with patients about death, their relationship with patients' families and controlling their emotions. The individual interview data identified the barriers and facilitators that registered nurses experience when providing end-of-life care. Barriers included a lack of communication skills and family and cultural and religious resistance to end-of-life care. The facilitators included gaining support from colleagues and patients' families.

CONCLUSION

This study has identified that while registered nurses hold generally favourable attitudes towards end-of-life care, they have negative attitudes towards talking with patients and families about death and managing their emotional feelings.

RELEVANCE TO CLINICAL PRACTICE

Education providers and leaders in healthcare settings should consider developing programmes for undergraduate nurses and nurses in clinical practice to raise awareness about the concept of death in a cross-section of cultures. Nurses' attitudes towards dying patients will be enhanced with culture-specific knowledge which will also enhance communication and coping methods.

REPORTING METHOD

This study used the Mixed Methods Article Reporting Standards (MMARS).

Enhancing Prediction of Brain Tumor Classification Using Images and Numerical Data Features

Brain tumors, along with other diseases that harm the neurological system, are a significant contributor to global mortality. Early diagnosis plays a crucial role in effectively treating brain tumors. To distinguish individuals with tumors from those without, this study employs a combination of images and data-based features. In the initial phase, the image dataset is enhanced, followed by the application of a UNet transfer-learning-based model to accurately classify patients as either having tumors or being normal. In the second phase, this research utilizes 13 features in conjunction with a voting classifier. The voting classifier incorporates features extracted from deep convolutional layers and combines stochastic gradient descent with logistic regression to achieve better classification results. The reported accuracy score of 0.99 achieved by both proposed models shows its superior performance. Also, comparing results with other supervised learning algorithms and state-of-the-art models validates its performance.