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Efficient delivery of integrated healthcare requires solid alliances and collaboration with stakeholders on a regular basis. Due to coronavirus disease 2019 (COVID-19), it has become necessary to explore new ways of delivering integrated healthcare, and virtual clinics have offered one solution and are likely to continue due to the uncertainty with COVID-19. This study aims to explore clinicians’ experiences of how efficient virtual elective knee clinics (VEKC) are in an orthopaedic setting in comparison to traditional face-to-face clinics.

The study utilised a mixed-methods study to obtain qualitative and quantitative data. This involved an anonymous online survey in addition to in-depth qualitative interviews conducted with a purposive sample of multidisciplinary colleagues who work with the VEKC in an acute hospital.

Three overarching themes and nine sub-themes emerged in the qualitative analysis. Overall, clinicians in both the quantitative and qualitative aspects of the study highlighted several ways that virtual clinics are efficient from both the patient and health service perspective. However, participants also highlighted barriers in relation to virtual clinics not being suitable for certain cohorts of patients and pathologies.

This is the first study in Ireland to provide valuable insights into the experiences of multidisciplinary clinicians using VEKC and their efficiency compared to traditional face-to-face clinics.

This chapter contributes to the Public Value (PV) literature in relation to accounting by providing evidence on its content's operationalization through performance measurement. In particular, it establishes the link with Sustainable Development Goals (SDGs), which may work as guiding principles of a public organization’s action. Accordingly, organizations embedding SDGs include them in their strategic decisions and disclose them through performance measurement and narratives.

The SDGs' presence is explored in the PV of a sample of Italian health institutes through documentary analysis of their performance plans. The aim is to verify if and how SDGs are pursued and whether the COVID-19 pandemic has affected PV content.

Besides Goal No. 3 (Health), the PV content of the investigated institutes contains various SDGs. Before the pandemic, their PV was aligned with SDGs mainly related to prosperity, economic growth and social inclusion. In the following period, the number of SDGs increased, introducing planet and environmental protection dimensions. No one explicitly mentions pursuing SDGs, revealing a non-institutionalized sensitivity of managers towards SDGs. The analysis distinguishes between ‘core’ SDGs, revealed mostly by traditional performance measures disclosing the achievement of institutes' mission, and ‘complementary’ SDGs, expressed mostly through narratives. This can derive from performance measurement, which employs the language of performativity, while the contribution to society is relegated in the narratives, making them less incisive.

The purpose of this paper is to conceptualise a research study to examine leadership as a relational concept between leaders and followers. The context is within surgical practice examining how motivated consultant surgeons are to lead junior doctors and which type of leadership style they use. From a follower perspective, the motivation of junior doctors will be explored, and their leadership preferences will be correlated with those of the actual style of consultant surgeons.

In this paper, the authors provide a detailed description of the methods for an international quantitative research study, exploring sequentially how motivated consultant surgeons are to lead and how leadership styles impact on the motivation of junior doctors. The objectives, method and data collection of this study are explained, and the justification for each method is described.

The findings for this outline study illustrate how critical it is to redefine leadership as a relational concept of leader and follower to ensure adequate support is provided to the next generation of consultant surgeons. Without consideration of the relational model of leadership, attrition will continue to be a critical issue in the medical workforce.

The research limitations are that this is a proposed quantitative study due to the need to collect a large sample of data from surgeons across the UK, Egypt and Germany. This research will have immense implications in developing new knowledge of leadership as a relational concept in medicine and healthcare. This study additionally will impact on how leadership is conceptualised in the curriculum for specialist surgical practice.

The practical implications are that relational leadership is supportive of generating a supportive leadership culture in the workplace and generating more effective teamwork.

To the best of the authors’ knowledge, this is the first study of its kind to look at a relational model of leadership in surgical practice between consultant surgeons and surgical trainees. This study will also identify any specific country differences between the UK, Germany and Egypt.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

This research theoretically proposed and empirically validated a Customer-Based Brand Equity (CBBE) scale specifically for Medical Tourism for emerging economies including recent findings from tourism theories such as gravity model and signalling theory, but more specifically accommodating political, cultural, economic, legal and social influences.

In-depth literature reviews from tourism, medical tourism, healthcare and hospitality domains are used to propose the theoretical model. The authors have used the lavaan package in R for the empirical analysis and model verification.

The research included, tested and verified the established latent variables such as “brand awareness”, “brand association”, “perceived quality” and “loyalty”, along with new observed variables for the CBBE scale from the theoretical perspectives of this research. “Infrastructure” has emerged as a new scale construct and “culture” was found to be a moderating variable for “perceived quality” in the CBBE scale, which are novel additions to the literature.

The research contributed to scale refining, latent construct assessment, and fine-tuning of the observed variables for the mentioned theoretical gaps.

The consolidation process and morphology evolution in ceramics-based additive manufacturing (AM) are still not well-understood. As a way to better understand the ceramic selective laser sintering (SLS), a dynamic three-dimensional computational model was developed to forecast thermal behavior of hydroxyapatite (HA) bioceramic.

AM has revolutionized automotive, biomedical and aerospace industries, among many others. AM provides design and geometric freedom, rapid product customization and manufacturing flexibility through its layer-by-layer technique. However, a very limited number of materials are printable because of rapid melting and solidification hysteresis. Melting-solidification dynamics in powder bed fusion are usually correlated with welding, often ignoring the intrinsic properties of the laser irradiation; unsurprisingly, the printable materials are mostly the well-known weldable materials.

The consolidation mechanism of HA was identified during its processing in a ceramic SLS device, then the effect of the laser energy density was studied to see how it affects the processing window. Premature sintering and sintering regimes were revealed and elaborated in detail. The full consolidation beyond sintering was also revealed along with its interaction to baseplate.

These findings provide important insight into the consolidation mechanism of HA ceramics, which will be the cornerstone for extending the range of materials in laser powder bed fusion of ceramics.

The study aims to evaluate PubMed publications on ChatGPT or artificial intelligence (AI) involvement in scientific or medical writing and investigate whether ChatGPT or AI was used to create these articles or listed as authors.

This scoping review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. A PubMed database search was performed for articles published between January 1 and November 29, 2023, using appropriate search terms; both authors performed screening and selection independently.

From the initial search results of 127 articles, 41 were eligible for final analysis. Articles were published in 34 journals. Editorials were the most common article type, with 15 (36.6%) articles. Authors originated from 27 countries, and authors from the USA contributed the most, with 14 (34.1%) articles. The most discussed topic was AI tools and writing capabilities in 19 (46.3%) articles. AI or ChatGPT was involved in manuscript preparation in 31 (75.6%) articles. None of the articles listed AI or ChatGPT as an author, and in 19 (46.3%) articles, the authors acknowledged utilizing AI or ChatGPT.

Researchers worldwide are concerned with AI or ChatGPT involvement in scientific research, specifically the writing process. The authors believe that precise and mature regulations will be developed soon by journals, publishers and editors, which will pave the way for the best usage of these tools.

This scoping review expressed data published on using AI or ChatGPT in various scientific research and writing aspects, besides alluding to the advantages, disadvantages and implications of their usage.

The present study investigates the mechanical properties of three types of Ti6Al4V ELI bone screws realized using the laser powder bed fusion (LPBF) process: a fully threaded screw and two groups containing differently arranged sectors made of lattice-based Voronoi (LBV) structure in a longitudinal and transversal position, respectively. This study aims to explore the potentialities related to the introduction of LBV structure and assess its impact on the implant’s primary stability and mechanical performance.

The optimized bone screw designs were realized using the LPBF process. The quality and integrity of the specimens were assessed by scanning electron microscopy and micro-computed tomography. Primary stability was experimentally verified by the insertion and removal of the screws in standard polyurethane foam blocks. Finally, torsional tests were carried out to compare and assess the mechanical strength of the different designs.

The introduction of the LBV structure decreases the elastic modulus of the implant. Longitudinal LBV type screws demonstrated the lowest insertion torque (associated with lower bone damage) while still displaying promising torsional strength and removal force compared with full-thread screws. The use of LBV structure can promote improved functional performances with respect to the reference thread, enabling the use of lattice structures in the biomedical sector.

The paper fulfils an identified interest in designing customized implants with improved primary stability and promising features for secondary stability.

Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.

The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R²) and mean absolute error (MAE).

Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.

The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.

This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.

This study investigated demographic factors, attitude and knowledge of persons with special needs towards COVID-19 in Nigeria between 12 May and 25 May 2020. This cross-sectional online survey was conducted among 72 persons with special needs purposively selected from the six geo-political zones in Nigeria. A questionnaire comprising questions on demographic information (three), knowledge (24) and attitude (28) towards COVID-19 was completed via Google forms by the participants (r=0.78). There were more males (51, 70.8%) than females (21, 29.2%) and the most common age group was 34-44 years (37.5%). The number of participants with a hearing impairment was 34 (47.2%) and the number with a visual impairment was 26 (36.1%). The results indicate adequate knowledge about the characteristics of COVID-19. It was found that 98.6% of the participants had heard about COVID-19; 94.4% were aware that COVID-19 is a contagious disease, 91.7% stated that COVID-19 is a virus and 88.9% reported correctly that the incubation period is 3-14 days. The knowledge about symptoms of COVID-19 among participants was high (x=2.63; participants obtained 87.8% of the total achievable score for these questions). The knowledge about prevention and control of COVID-19 among participants needs was very high (x=2.77; participants obtained 92.3% of the total achievable score for these questions). Attitude of participants towards the COVID-19 outbreak was positive and above average (x=2.84). However, participants reported that it is hard to get palliatives or financial support from others during COVID-19 lockdown (52.8%) and that they feel frustrated by the uncaring attitude of the government towards them during COVID-19 lockdown (55.6%). On this basis, counselling and social policy implications were suggested including the provision of palliatives by the government and the need for widespread enlightenment among individuals with special needs on prevention of COVID-19.