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Work engagement denotes to a state of positive and affective motivation of elevated power joined with high educational levels and a great concentration on occupation and it is negatively affected by psychological problems. This study aims to assess the stress and work engagement among Palestinian nurses working in intensive care units.

A cross-sectional design was adopted. A convenience sample consisting of 225 intensive care nurses from governmental hospitals was recruited to participate. Data collection used the Nursing Stress Scale and Utrecht Work Engagement Scale-9, and demographic data were used to gather data throughout the period from February 10 to March 30, 2023.

Findings demonstrated that nurses’ stress levels were high (M = 105.9 ± standard deviation [SD] = 11.91). Concerning work engagement, the nurses endorsed moderate work engagement levels with a mean of 3.7 (SD = 0.4). Regarding work engagement subscales, the mean of vigor was 3.7 (0.6), dedication with a mean of 3.7 (0.6) and absorption with a mean of 3.7 (0.6). Also, the findings showed that stress, gender and monthly income were predictors of work engagement (p < 0.05).

Despite the significant results, this study had the following limitations: the design was cross-sectional, which limits the ability to explore the cause and effect of the study variables, thus longitudinal studies are recommended. In addition, the study adopted a self-reported questionnaire based on participants’ understanding, culture and work context which could influence their responses.

The intensive care nurses had high stress levels and moderate work engagement. Stress, gender and monthly income were predictors of the work engagement. Thus, interventions should be encouraged to minimize stress, which has a significant influence on work engagement.

The objectives of the proposed model are: aiding nursing staff in documentation tasks, which can be onerous and stressful; and helping management by offering an estimate of the nursing workload, which can be considered for administrative purposes, such as staff scheduling.

An exploratory-descriptive study was conducted in order to identify, investigate, and describe the problem of documenting nursing activities and workload estimation in an intensive care unit. Technological solutions were explored, and models were proposed to address these issues.

Cross-dataset experiments were performed, and the model was able to offer an adequate estimate of the nursing workload. The results suggest that continuous retraining is essential for maintaining high accuracy. While the proposed model was considered in the context of an adult ICU, it can be adapted to other contexts, such as elderly care.

While the proposed solution seems promising, further research is required, such as deploying this system in an ICU and facing challenges in the areas of computer security, medical ethics, and patient data privacy. More patients’ variables could also be collected to improve the workload estimates.

Nursing workload assessment is critical to improve the cost-benefit ratio in health care, offer high-quality patient care, and reduce unnecessary expenses, and this process is usually manual. An automated device can automatically document the amount of time spent in patient care activities in a more transparent, efficient, and accurate manner, freeing staff for more urgent activities and keeping management better informed about day-to-day nursing operations.

This study aims to examine the effects of Internet of Things (IoT) technology on efficiency and patient care in Italian and Israeli intensive care units (ICUs). The goal is to study how IoT might improve care settings by controlling health dynamics and responding to life-threatening circumstances.

This survey-based research explores IoT use, challenges and adaptability in ICUs in both countries. Interviews and surveys of ICU health-care workers are used to get both quantitative and qualitative data on integrating experiences and perspectives.

The research found significant variations between Italy and Israel due to technology infrastructures and health-care practices. Israel shows a more concentrated deployment in a major medical centre with advanced but limited uptake, whereas Italy shows application throughout ICUs highlighting regional health-care system disparities. Interoperability, data security and IoT training are common difficulties.

This research has limitations. One drawback is the geographical dispersion of study sites, with a bigger sample size in Italy than in Israel. This discrepancy may affect findings applicability. However, these preliminary findings provide a foundation for further research into the complexities of deploying IoT in various health-care settings.

This study compares IoT integration in two national health-care systems, adding to health-care technology literature. Regional variations affect technology adoption, but IoT may enhance ICU operations and patient care, according to one research. This study helps health-care practitioners, academics and policymakers understand the pros and cons of IoT in health care.

Nurse turnover in critical care units (CCU) significantly affects patient outcomes and health systems worldwide. To safeguard patient care quality, hospitals must address the underlying reasons for turnover and strategize to retain their skilled nursing workforce. The study proposes a prescriptive framework to reduce nurse turnover in CCUs.

In this study, the integrated methodology of Delphi-AHP-Entropy was used for the comparative prioritization of factors and subfactors that influence nursing staff turnover in CCUs.

Study findings reveal that “Organizational factors” and “Individual factors” dictate critical care nurse attrition rate. At the subfactor level, staffing policy, chronic fatigue, and perceived career are the leading concerns for the decision of nurses whether to work or leave.

This study is valuable for both researchers and healthcare professionals. It examines whether actions related to nurse retention align with existing theory and identifies areas requiring further theoretical or applied studies to enhance understanding in this area. This insight can bolster the field’s knowledge base and integrate theoretical and applied knowledge effectively. Additionally, for healthcare professionals, the study provides an overview of key factors conducive to retaining nursing staff in the CCU, offering valuable guidance for implementing effective strategies.

This study uniquely positions itself by presenting a comprehensive and prescriptive framework for critical care nurse retention in the UAE.

A novel method has been proposed to reduce the false alarm rate of arrhythmia patients regarding life-threatening conditions in the intensive care unit. In this purpose, the atrial blood pressure, photoplethysmogram (PLETH), electrocardiogram (ECG) and respiratory (RESP) signals are considered as input signals.

Three machine learning approaches feed-forward artificial neural network (ANN), ensemble learning method and k-nearest neighbors searching methods are used to detect the false alarm. The proposed method has been implemented using Arduino and MATLAB/SIMULINK for real-time ICU-arrhythmia patients' monitoring data.

The proposed method detects the false alarm with an accuracy of 99.4 per cent during asystole, 100 per cent during ventricular flutter, 98.5 per cent during ventricular tachycardia, 99.6 per cent during bradycardia and 100 per cent during tachycardia. The proposed framework is adaptive in many scenarios, easy to implement, computationally friendly and highly accurate and robust with overfitting issue.

As ECG signals consisting with PQRST wave, any deviation from the normal pattern may signify some alarming conditions. These deviations can be utilized as input to classifiers for the detection of false alarms; hence, there is no need for other feature extraction techniques. Feed-forward ANN with the Lavenberg–Marquardt algorithm has shown higher rate of convergence than other neural network algorithms which helps provide better accuracy with no overfitting.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

In recent years, in research and policy circles, there is growing interest in the subject of speaking up (and silence) within the health sector, and there is a consensus that it is a major issue that needs to be addressed. However, there remain gaps in our knowledge and while scholars talk of a voice system – that is the existence of complementary voice channels designed to allow employees to speak up – empirical evidence is limited. We seek to explore the notion of a voice system in a healthcare organisation as comprising structures and cultures as seen from different stakeholder perspectives. What do they see and how do they behave and why? To what extent do the users see a voice system they can access and easily navigate?

Interviews and focus groups were conducted with a voice stakeholder group (e.g. designers of the system from senior management and HR, which comprised 23 staff members) as well as those who have to use the system, with 13 managers and 26 employees from three units within a metropolitan hospital: an oncology department, an intensive care unit and a community health service. Overall, a total of 62 staff members participated and the data were analysed using grounded theory to identify key themes.

This study revealed that although a plethora of formal voice structures existed, these were not always visible or accessible to staff, leading to confusion as to who to speak up to about which issues. Equally other avenues which were not designated voice platforms were used by employees to get their voices heard.

This papers looks at the voice system across the organisation rather than examining a specific scheme. In doing so it enables us to see the lived perceptions and experiences of potential users of these schemes and their awareness of the system as a whole.

The purpose of this paper is to demonstrate the close relationship between the disciplines of law and health-care studies. This interrelation has become particularly evident during the spread of the COVID-19 pandemic, when restrictive human rights provisions have been initiated by many states for the sake of public health. Research focuses on the notional proximity of the principle of proportionality and its health-care correlative: effectiveness. It also goes through the influence of acceptance rates for the application of restrictive measures.

Research focuses on interdisciplinary literature review, taking into consideration judicial decisions and data on acceptance rates of restrictive human rights measures in particular. Analysis goes in depth when two categories of restrictive human rights measures against the spread of the pandemic are examined in depth: restrictive measures to achieve social distancing and mandatory vaccination of professional groups.

Restrictive human rights measures for reasons of public health are strongly affected by the need for effective health-care systems. This argument is verified by judicial decision-making which relies to the necessity of health-care effectiveness to a great extent. The COVID-19 pandemic offers a laminate example of the two disciplines’ interrelation and how they infiltrate each other.

Further implications for research point at the need to institutionalize a cooperative scheme between legal and health-care decision-making, given that this interrelation is strong.

The originality of this paper lies on the interdisciplinary approach between law and health-care studies. It explains how state policies during the pandemic were shaped based on the concepts of effectiveness and proportionality.

This study aims to evaluate the health literacy level of the parents of children diagnosed with Down syndrome (DS) within one institution in Turkey.

A cross-sectional survey measuring demographics, information of the child and the parent and health literacy was administered to participants. The health literacy levels in the study were measured with the European Health Literacy Scale (EHLS), which consists of 47 questions.

Of the 65 participants who completed the questionnaire, 56.9% were mothers, 68.1% were diagnosed in the neonatal outpatient clinic examination after birth, and 58.5% stayed in the neonatal intensive care unit after birth. The mean score of the IHLS scale was 25.06 ± 6.59. Of the parents, 63.1% were found to be inadequate, 18.5% problematic-limited, and 18.5% adequate health literate. Any parent with excellent health literacy level was identified. High education level (p < 0.001), high income level (p < 0.001), living in the city center (p < 0.05), planned pregnancy (p < 0.05) and being a health worker (p < 0.001) were found to be statistically significant with a high EHSL score.

The presence of Down syndrome (DS) in a child also necessitates ongoing monitoring for a range of conditions, including eye diseases and heart disease. Some surgical procedures, such as heart or gastrointestinal surgeries, may also be required. Additionally, the child may require the administration of various medications. Finally, due to the potential lifelong need for assistance, the child may require the support of an adult throughout their lifetime. This is because of the child's inability to live independently due to their mental state. Therefore, parent education is the most important issue in the follow-up of the disease.

To the best of the authors’ knowledge, this is the first study to determine that parents of children diagnosed with DS have very limited knowledge of the disease and health literacy. Explanation of current diseases, treatments and training of parents should also be included in genetic counseling.

DS is a chromosomal disease that requires multidisciplinary care. Parents have to know the course of the disease and its complications.

The findings of this study indicate that parents of children with Down syndrome exhibit a profound lack of knowledge regarding the nature of their child's condition and the available healthcare options. It is therefore imperative that genetic counseling incorporates an explanation of the diagnosed diseases, treatments, and educational resources for parents.

To map nurses’ actions performed during the care transitions from hospital to home of Covid-19 patients.

A scoping review based on the Joanna Briggs Institute guidelines was carried out. We searched in seven databases: PubMed/MEDLINE, BDENF, LILACS, SciELO, Embase, Scopus, Web of Science and Google Scholar. A two-step screening process and data extraction was performed independently by two reviewers. The findings were summarized and analyzed using a content analysis technique.

Of the total 5,618 studies screened, 21 were included. The analysis revealed nurses’ actions before and after patient’ discharge, sometimes planned and developed with the interprofessional team. The nurses’ actions included to plan and support patients’ discharge, to adapt the care plan, to use screening tools and monitor patients’ clinical status and needs, to provide health orientation to patients and caregivers, home care and face-to-face visiting, to communicate with patients, caregivers and other health professionals with phone calls and virtual tools, to provide rehabilitation procedures, to make referrals and to orient patients and families to navigate in the health system.

The results provide a broader understanding of the actions taken and challenges faced by nurses to ensure a safe care transition for Covid-19 patients from hospital to home. The interprofessional integration to discharge planning and the clinical nursing leadership in post-discharge monitoring were highlighted.

The nurses’ actions for Covid-19 patients performed during care transitions focused on coordination and discharge planning tailored to the needs of patients and caregivers at the home setting. Nurses monitored patients, with an emphasis on providing guidance and checking clinical status using telehealth tools.