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Nosiness is an annoying behavior at the workplace that can lead to negative consequences. It is characterized by being overly curious about other people’s affairs. Specifically, this study aims to identify the factors contributing to nosiness among nurses.

We conducted an exploratory qualitative interview study involving 38 nurses in Iran. The participants were selected by purposive sampling.

We identified nine themes as the antecedents of nosiness among nurses: defamation motive, the need for certainty, the need for power, recreational motive, empathy, social comparison, the allure of the subject for the individual, having an employee-friendly workplace, and work environment and workload.

Understanding the antecedents of nosiness can help healthcare organizations curtail this phenomenon and foster a positive work environment, particularly in nursing where empathy, compassion, and attention to detail make them susceptible to nosiness.

This study explores the deep integration of digital technology and cultural heritage to promote the preservation and inheritance of cultural heritage. Focusing on Digital Cultural Heritage (DCH), this research investigates its key role in activating theoretical research and practical applications in cultural heritage.

This study conducted an extensive bibliometric analysis utilizing VOSviewer and Bibliometrix visualization software to meticulously examine DCH research. Insights were gleaned from a dataset comprising 2,997 DCH-related publications harvested from the Web of Science database.

The bibliometric analysis reveals several notable findings: driven by active contributions from Italy, China, Spain, and the USA, the number of DCH publications shows a linear upward trend. Consiglio Nazionale delle Ricerche in Italy emerges as a prominent institution, while the Journal of Cultural Heritage stands out as the most influential journal in the DCH field. Scholars such as Remondino, Guidi, Barazzetti, and Carrozzino have significantly impacted DCH research. Furthermore, an in-depth analysis of keyword co-occurrence networks elucidates six major research trajectories in the DCH field, covering various aspects from cultural heritage digitization to digital humanities.

The study emphasizes the value of global knowledge exchange, interdisciplinary collaboration, innovative technology applications, and digital content provision practices in advancing DCH research.

By delving into the multifaceted landscape of DCH research, this study brings forth original insights into the escalating trends, pivotal contributors, and burgeoning research directions.

This study used phenomenological narrative methodology to get insights into lived experiences of 10 Asian immigrant woman scholars in science, technology, engineering, and mathematics (STEM) in US institutions of higher learning. A feminist research approach overall guided the study. The concepts and theories of intersectionality, cultures of the academy, mindset, and mind tools framed the examination of the impacts of gender and work–family–community environments on the career pipeline of this group of women. The data were from two sources: (1) 48 documents on the participants and their institutions and (2) in-depth semi-structured interviews with these 10 participants. The findings show that gender and environment impacted the Asian women scholars’ career pipeline and advancement differently. On the negative side, barriers separately or jointly rooted in gender-based, racial, and hierarchical biases at stages of their career pipeline, from professional education to faculty appointment and leadership, challenged them. On the positive side, other gender-based and environmental agents and interventions supported them to overcome obstacles to their upward career mobility. This chapter has implications for how higher education institutions can improve their gender-based and environmental policies and praxis and facilitate the advancement of Asian immigrant women in STEM. It also has implications for how Asian women can prepare themselves to be successful in academic STEM careers.

Nurses work in a wide range of roles and settings, each with inherent stressors that can impact mental well-being. High levels of stress, burnout and clinical errors have been linked to the levels of support nurses have in their workplaces. Both consumers and health organisations benefit when nurses can engage in their work with support. Digital applications offer a promising option for supporting the mental well-being of nurses. This paper aims to provide analysis and synthesis of studies from the emerging field of research investigating the potential of digital applications to support the mental well-being of nurses.

An integrative literature review was conducted focused on studies published within the last ten years that employed digital applications specifically included to support nurses’ mental well-being. As part of the review inductive thematic analysis was then undertaken identifying four main themes diversity of digital applications; wide applicability across nursing; differing dimensions of well-being; and challenges to integration.

The study of digital applications used among nurses is a modern emerging field of research. Digital applications have considerable design variability and are being rolled out across multiple nursing specialities. They target differing aspects of mental well-being, offering promise despite the challenges to integration.

Digital applications are an emergent and promising option for supporting nurses' mental well-being. They have the potential to be personalised, cost-efficient and engaging platforms. The fast-paced technological advancement of digital applications will lead to the adoption of novel means of supporting nurses.

Paper aims to evaluate the efficiency of traditional chitosan, nano chitosan, and chitosan nanocomposites for consolidating aged papyrus samples. Cellulose-based materials, such as papyrus sheets and paper, which are the most common types of writing supports for works of art in many museums and archive. They are subjected to different types of deterioration factors that may lead to many conservation problems. Consolidation treatment is one of the most common conservation treatments, which should have perform after much testing to select the appropriate consolidants.

This research paper aims to evaluate the resistance of traditional chitosan, nanochitosan and chitosan/zinc oxide nanocomposite as an eco-friendly papyrus strengthening. Untreated and treated papyrus was thermally aged and characterized via scanning electron microscope (SEM) and Fourier transform infrared spectroscopy (FTIR). Antimicrobial activity of the papyrus specimens was also determined against four tested pathogenic bacteria by disc diffusion method: MRSA, Staphylococcus aureus, E. coli and P. aeruginosa.

The results revealed that chitosan nanocomposite showed a remarkable enhancement of papyrus tensile properties and presence of ZnO prevents the effects of biodeterioration.

Zinc oxide nanoparticles enhance the optical properties and increase the chemical reactions between the consolidating material and the treated papyrus.

This study examines innovation configurations (i.e. sets of product/service, social and business model innovations) and configuration linkages (i.e. factors that help to combine innovations) across six organizations as contingent upon organizational structure.

Using semi-structured interviews and available public information, qualitative data were collected and examined using content analysis to characterize innovation configurations and linkages in three local/private organizations and three foreign-led/public-private partnerships in Repiblik Ayiti (Haiti).

Organizations tend to combine product/service, social, and business model innovations simultaneously in locally founded private organizations and sequentially in foreign-based public-private partnerships. Linkages for simultaneous combination include limited external support, determined autonomy and shifting from a “beneficiary mindset,” and financial need identification. Sequential combination linkages include social need identification, community connections and flexibility.

The generalizability of our findings for this qualitative study is subject to additional quantitative studies to empirically test the suggested factors and to examine other health care organizations and countries.

Locally led private organizations in low- and middle-income settings may benefit from considering how their innovations are in service to one another as they may have limited resources. Foreign based public-private partnerships may benefit from pacing their efforts alongside a broader set of stakeholders and ecosystem partners.

This study is the first, to our knowledge, to examine how organizations combine sets of innovations, i.e. innovation configurations, in a healthcare setting and the first of any setting to examine innovation configuration linkages.

This viewpoint introduces a “Readiness Self-Assessment Guide” that can be used as a diagnostic tool to help health service governors and managers, particularly in Low-Middle Income Countries, or those in the early stages of developing their governance program.

The approach uses the conceptual framework for governance developed by Barbazza and Tello (2014).

The Guide is based on five foundational elements or components of governance that frame the actual governance activities. The self-assessment process uses a sequence of real-world examples to help users of the Guide assess their organization’s “readiness” or current capacity to strengthen quality. A simple scoring process allows users to rate their organization’s progress through potential evolutionary steps. The resulting analysis is intended to be the starting point of a structured discussion among team members about priorities, enabling factors and constraints.

Assessment of the institutional context is a fundamental step that will enable quality teams to select the appropriate tools for their priority concerns. This Readiness Self-Assessment Guide can be used as part of that diagnostic assessment.

This paper is empirically derived from the author’s experience as a consultant helping health service organizations and governing authorities to develop health governance programs in several countries.

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.

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.

The paper aims to investigate the practices facilitating the transformation of healthcare services, understanding the resulting outcomes in terms of well-being and uplifting changes. a systematic literature review (SLR) focusing on analyzing the healthcare sector under the transformative service research (TSR) theoretical domain is conducted to achieve this goal.

Employing a structured SLR developed based on the PRISMA protocol (Pickering and Byrne, 2014; Pickering et al., 2015) and using Scopus and WoS databases, the study identifies and analyzes 49 papers published between 2021 and 2022. Content analysis is used to classify and analyze the papers.

The SLR reveals four transformative practices (how) within the healthcare sector under the TSR domain, each linked to specific well-being outcomes (what). The analysis shows that both practices and outcomes are mainly patient-related. An integrative framework for transformative healthcare service is presented and critically examined to identify research gaps and define the trajectory for the future development of TSR in healthcare. In addition, managerial implications are provided to guide practitioners.

This research is among the first to analyze TSR literature in the context of healthcare. The study critically examines the TSR’s impact on the sector’s transformation, providing insights for future research and offering a roadmap for healthcare practitioners to facilitate uplifting changes.