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AnteayerJournal of Nursing Scholarship

What Is a Good Death in South Asia? A Systematic Review and Narrative Synthesis

ABSTRACT

Introduction

To deliver palliative care, it is important to understand what a “good death” means to the relevant people. Such studies have mostly occurred in high-income settings that usually live by Western ideals. What matters to people is likely to vary across different regions of the world, influenced by multiple factors. Although there is a great need for palliative care in South Asia, there is a lack of comprehensive understanding of what a good death means in this setting. This study aimed to increase understanding of what is considered a good death in South Asia.

Design

Systematic review and narrative synthesis.

Method

A systematic search was conducted across eight databases, an Advanced Google search, and a bibliography search of selected articles. A data-based convergent synthesis was performed, along with quality appraisal.

Results

Twenty-five empirical studies were selected for analysis from India, Pakistan, Bangladesh, Sri Lanka, and Bhutan. Four themes emerged. Mutual care and connection support a continued sense of self: contributing to others, while receiving connection through relationships and spiritual practices, was important for patients and supported by families and healthcare workers. Freedom to choose—privilege or burden?: the choice to participate in care was necessary for some patients but a burden for others, who preferred the family to lead their care. Severe uncontrolled pain and financial distress precluded choice for some patients, who felt death was the only option. Decisions regarding artificial prolongation of life were complex for patients and healthcare workers. Opportunities in the last days: when actively dying, there was general agreement on the importance of being pain-free, feeling safe, and having family present. Home was not always the preferred place of death. For family, it was critical to perform last rites. After death matters: What happens after death—influenced by leaving a legacy and religious beliefs—affected all parties before, during, and post-death.

Conclusions

To our knowledge, this is the first review of what a good death means in South Asia. There is a dearth of research from most South Asian countries. Although the South Asian perspective has similarities with the Western perspective, we note important nuances around decision-making, prolongation of life, prognostic awareness, and wanting to end one's life, moderated by culture, religion, and poverty. We support policies that account for these variations. Ongoing work is required to provide good symptom management, thus increasing opportunities for patient participation in care. Further research is needed in areas of ethics and religion at the end of life in South Asia.

Nurses' work environment and health promotion in relation to psychological distress symptoms, and sleep disturbance: A structural equation modeling approach

Abstract

Background

The healthcare work environment has numerous stressors that can contribute to distress and poor health outcomes among nurses. The impact of distress can be detrimental, resulting in nurses leaving the profession. Thus, it is critical to explore factors in the work environment that contribute to the distress symptoms and behaviors that promote nurses' health.

Objective

This study aimed to examine the constructs associated with the conceptual model of distress, such as the work environment, specifically workload and the practice environment (quality of care, salary, staffing, time, and satisfaction) and associations with psychological distress, sleep disturbance, and health promotion behaviors in nurses, using structural equation modeling.

Design

This study was a cross-sectional survey design collected as part of the Nurse Worklife and Wellness Study (NWWS) using balanced stratified sampling methods.

Methods

A confirmatory factor analysis tested the factorial structure of the latent constructs using weighted least squares estimation with missing data (WLSMV) for the sample (n = 1170). A structural equation modeling approach examined the direct and indirect associations between workload, practice environment, health promotion behaviors, psychological distress symptoms, sleep disturbance, and health.

Results

Based on the confirmatory factor analysis, the measurement model reported adequate model fit (CFI = 0.96; TLI = 0.95; SRMR = 0.048 and RMSEA = 0.039). The structural model showed that the workload was related to significantly increased psychological distress (β = 1.47, p < 0.001), sleep disturbance (β = 1.22, p < 0.01), and decreased overall health (β = −1.36, p < 0.01). Similarly, a positive practice environment was associated with significantly higher psychological distress (β = 1.61, p < 0.001), sleep disturbance (β = 1.31, p < 0.01), and lower overall health (β = −1.51, p < 0.01). Workload and the practice environment were associated with significantly increased health promotion behaviors such as interpersonal relations, spiritual growth, stress management, physical activity, and nutrition. A statistically significant indirect relationship was found between workload and psychological distress, mediated by health promotion behaviors. Psychological and physical health promotion had restorative effects in relation to decreasing the impact of distress and sleep disturbance while increasing overall health.

Conclusions

Our results highlight the need to improve the work environment by decreasing the nurses' workload and using health promotion behaviors to mitigate nurses' psychological distress. Future studies should focus on exploring distress in the context of non-pandemic work conditions and finding ways to promote coping behaviors in nurses. In addition, healthcare organizations should develop policies and strategies to incentivize nurses' participation in health promotion behaviors to promote their well-being and ultimately stabilize the nursing workforce.

Empowering nurses to champion Health equity & BE FAIR: Bias elimination for fair and responsible AI in healthcare

Abstract

Background

The concept of health equity by design encompasses a multifaceted approach that integrates actions aimed at eliminating biased, unjust, and correctable differences among groups of people as a fundamental element in the design of algorithms. As algorithmic tools are increasingly integrated into clinical practice at multiple levels, nurses are uniquely positioned to address challenges posed by the historical marginalization of minority groups and its intersections with the use of “big data” in healthcare settings; however, a coherent framework is needed to ensure that nurses receive appropriate training in these domains and are equipped to act effectively.

Purpose

We introduce the Bias Elimination for Fair AI in Healthcare (BE FAIR) framework, a comprehensive strategic approach that incorporates principles of health equity by design, for nurses to employ when seeking to mitigate bias and prevent discriminatory practices arising from the use of clinical algorithms in healthcare. By using examples from a “real-world” AI governance framework, we aim to initiate a wider discourse on equipping nurses with the skills needed to champion the BE FAIR initiative.

Methods

Drawing on principles recently articulated by the Office of the National Coordinator for Health Information Technology, we conducted a critical examination of the concept of health equity by design. We also reviewed recent literature describing the risks of artificial intelligence (AI) technologies in healthcare as well as their potential for advancing health equity. Building on this context, we describe the BE FAIR framework, which has the potential to enable nurses to take a leadership role within health systems by implementing a governance structure to oversee the fairness and quality of clinical algorithms. We then examine leading frameworks for promoting health equity to inform the operationalization of BE FAIR within a local AI governance framework.

Results

The application of the BE FAIR framework within the context of a working governance system for clinical AI technologies demonstrates how nurses can leverage their expertise to support the development and deployment of clinical algorithms, mitigating risks such as bias and promoting ethical, high-quality care powered by big data and AI technologies.

Conclusion and Relevance

As health systems learn how well-intentioned clinical algorithms can potentially perpetuate health disparities, we have an opportunity and an obligation to do better. New efforts empowering nurses to advocate for BE FAIR, involving them in AI governance, data collection methods, and the evaluation of tools intended to reduce bias, mark important steps in achieving equitable healthcare for all.

Interprofessional collaboration in telemedicine for long‐term care: An exploratory qualitative study

Abstract

Background

Widespread and sustained adoption of telemedicine in long-term residential care is emerging. Nursing home (NH) nurses play a key role in collaborating with remote physicians to manage residents' medical conditions through videoconferencing. Therefore, understanding of interprofessional collaboration and effective communication between nurses and physicians is critical to ensure quality of care and safety during teleconsultations.

Aims

To explore NH nurses' and physicians' experiences of interprofessional collaboration and communication during teleconsultations.

Methods

A qualitative descriptive design was adopted. Purposive sampling was conducted to recruit 22 physicians and nurses involved in NH teleconsultations. Semi-structured online interviews were conducted, and data were thematically analyzed.

Results

Three themes were identified: (1) Manner of communication in telemedicine, (2) sociocultural influences in collaborative practice, and (3) role expectations in telemedicine. Both nurses and physicians recognized the importance of building and maintaining trust as physicians heavily depended on nurses for provision of objective information for clinical decision-making. However, practice differences were observed between nurses and physicians during teleconsultations. Sociocultural influences such as power relations and language barriers also affected the nurse–physician relationship and interpersonal communication. Additionally, different performance expectations were identified between nurses and physicians.

Conclusion

Interprofessional collaboration in teleconsultations is challenging because of lack of in-person assessment and dependence on nurses for clinical information. In addition, expectations and communication styles differ among healthcare professionals. This study called for interprofessional telemedicine training with incorporation of shared mental models to improve role clarity and communication. Given the international-dominated healthcare workforce in long-term care, the development of cultural competency could also be considered in telemedicine training to enhance nurse–physician collaborative practice.

Clinical Relevance

Telemedicine is increasingly adopted in long-term care settings, where multidisciplinary healthcare professionals from different health institutions are involved in resident care. Interprofessional collaboration should be incorporated into telehealth education for enhanced clinical practice in this care delivery model.

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