Health Care Sciences Research Articles

World trends in health science student publications

Background: the training and promotion of new researchers as an essential contribution in the construction of science is now a crucial aspect in higher education. Aim: to characterize communication patterns and impact of medical science student scientific output worldwide. Methods: a bibliometric study was carried out on student scientific output in health sciences, using the Scopus database. It was defined as "article with student participation" those in which at least one author who declared in his affiliation to be a student of one of the careers in health sciences (Medicine, Dentistry or Nursing) appeared. Results: Were retrieved 21162 documents, 94,77 % were original, followed by reviews (8,25 %) and letters (5,30 %). The most productive region was the Middle East. The Biomedical categories prevailed in the study, headed by Medicine. Conclusions: the pattern of student scientific communication at a global level is characterized by a tendency to increase scientific output with a high leadership of authors from the Middle East and North America. These results reflect the rise of the scientific student movement in recent years, in terms of raising the scientific quality of graduates of health sciences careers

Mental health assessment – a 360° student experience

We have been developing 360° simulated practice videos for healthcare science students. The students who have taken part in the filming and watched the videos provided feedback on whether this would benefit their learning. We are doing this to continue to strive forward with innovations in virtual learning in line with Health Education England [1]. The simulation-based videos have been created to add to the healthcare sciences units to aid in ‘real-life’ teaching styles, to help build confidence and resilience in healthcare students, and to provide multidisciplinary, patient-focused scenarios that can be included in assessments [2]. First and third-year paramedic students took part in mass casualty scenarios filmed at our student’s union building. They worked with Critical Care Practitioners, Academics, Nurses in practice, and the National Ambulance Resilience Unit to create handover videos involving assessing casualties to create videos for other healthcare professionals. Follow-up videos were then filmed on the 360° cameras in the simulation suites to represent an accident and emergency environment as this is where mental health crisis assessments can take place. The adult psychosis presentation was filmed and shows ‘psychiatric liaison nurses’ played by second-year MSc and BSc mental health students assessing the person with suspected psychosis and making clinical decisions. The scenario mental state examination and the case study were scripted. Students could view the 360° videos using virtual reality headsets such as the Oculus Rift [3]. The student feedback evaluation data was collected via an online survey and focus group discussions (FGDs). A survey was completed with n=30 students across all fields of nursing students and paramedic students. The student FGD evaluations were very positive about alternative simulated learning styles with one student quoting ‘It will make an assessment of mental health patients a lot easier for students using appropriate tools and models’. Students found that simulation-based learning experience is an excellent addition to traditional learning approaches as it met the requirements for different learning styles. This research project brought together academics and practitioners from across practice and university. Future work should build on these resources based on feedback from students and service users. 1. National Health Service/Health Education England. 2020. A national vision for the role of simulation and immersive technologies in health and care. 2. ASPiH/HEE. 2016. Simulation-based Education in Healthcare Simulation-Based Education in Healthcare (aspih.org.uk) [Accessed on 17/06/2022] 3. Topal review: NHS. 2019. Preparing the healthcare workforce to deliver the digital future.

Machine Learning Prediction of the Transmission Function for Protein Sequencing with Graphene Nanoslit.

Protein sequencing has rapidly changed the landscape of healthcare and life science by accelerating the growth of diagnostics and personalized medicines for a variety of fatal diseases. Next-generation nanopore/nanoslit sequencing is promising to achieve single-molecule resolution with chromosome-size-long readability. However, due to inherent complexity, high-throughput sequencing of all 20 amino acids demands different approaches. Aiming to accelerate the detection of amino acids, a general machine learning (ML) method has been developed for quick and accurate prediction of the transmission function for amino acid sequencing. Among the utilized ML models, the XGBoost regression model is found to be the most effective algorithm for fast prediction of the transmission function with a very low test root-mean-square error (RMSE ∼0.05). In addition, using the random forest ML classification technique, we are able to classify the neutral amino acids with a prediction accuracy of 100%. Therefore, our approach is an initiative for the prediction of the transmission function through ML and can provide a platform for the quick identification of amino acids with high accuracy.

Definition and Contextual Factors of Nursing Home Residents' Mobility in a Holistic View: A Delphi Study.

Current definitions of older adults' mobility do not cover the full range of influencing factors and do not consider nursing home residents. The present study reports expert ratings from a Delphi study regarding factors influencing the mobility of long-term nursing home residents. We invited 129 professionals with expertise in a field relevant to research on mobility in older adults such as health care, medicine, or human movement science to participate in a Delphi study comprising 3 rounds of online questionnaires. Up to 40 experts participated in each round. In the first round, we used open-ended questions to solicit possible definitions, contextual factors, and assessment tools. In the second round, the participants used Likert scales (1-10) to rate their suitability. In the final round, we presented a definition based on consensus as well as the top-rated contextual factors and assessment tools from the first 2 rounds for a final rating of agreement. The experts showed broad agreement on the final version of the mobility definition, with 8.9 ± 1.4 (mean ± standard deviation) out of 10 points. The experts also showed broad consensus on the selected contextual factors, with 8.4 ± 1.8 points to 8.9 ± 1.2 points (out of 10 points). This was also the case for the top 3 assessment tools selected from results of previous rounds, which showed an agreement of 7 or more points (out of 10 points) by 81.6% to 100% of all experts in the different categories. Given that an interdisciplinary group of experts considered various hitherto neglected contextual factors as relevant, the Delphi survey and its results imply the need for an updated interdisciplinary and holistic understanding of mobility in nursing home residents and can provide a basis for putting it into practice.

Music as Medicine: A Concept Analysis.

Music is a powerful emotional tool that can be used as an effective coping mechanism, as "medicine." Musical interventions are used in many areas of health care and medical sciences to meet the physical, psychological, social, and emotional needs of individuals. This article provides a theoretical definition of the concept of music as medicine: The use of music as a non-pharmacological strategy for coping and healing, based on its therapeutic properties, using a modification of Walker and Avant's method to identify antecedents, attributes, consequences, and empirical referents. Music as a coping strategy involves the use of music intervention and is an example of an emotion-focused, adaptive, coping strategy. The article concludes with a discussion of the implications of music as medicine for practice and research. Increased awareness of the concept of music as medicine as a strategy to manage stress offers an inexpensive non-pharmacological intervention to many organizations such as nursing care facilities, schools, and hospitals.

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

Towards Integrated Bio Design-Related and Translational Platforms to Determine Co-Development for Adaptation of Innovative Biotechnologies and to Predict and to Prognosticate the Future of the Healthcare and Life Science Bioindustry

Towards Integrated Bio Design-Related and Translational Platforms to Determine Co-Development for Adaptation of Innovative Biotechnologies and to Predict and to Prognosticate the Future of the Healthcare and Life Science Bioindustry

Black maternal health scholars on fire: Building a network for collaboration and activism.

Black maternal health scholars on fire: Building a network for collaboration and activism.

Participatory peer research exploring the experience of learning during Covid-19 for allied health and healthcare science students.

The teaching and learning experience of allied health and healthcare science students has altered because of the Covid-19 pandemic. Limited research has explored the experience on the future healthcare workforce using participatory research design. The aim of this study was to explore the impact of a global pandemic on the clinical and academic experiences of healthcare student using a co-production approach with student peer researchers. A participatory research approach adopting online focus groups facilitated by students trained as peer researchers was adopted. First, second and final year students from occupational therapy, physiotherapy, podiatry, healthcare science, diagnostic radiography and imaging, radiotherapy and oncology, and speech and language therapy were recruited to six focus groups. Data generated through focus groups were analysed thematically using the DEPICT model to support a partnership approach. Twenty-three participants took part in six focus groups. The themes identified were: rapid changes to learning; living alongside Covid-19 and psychological impact. Students preferred blended learning approaches when available, as reduced peer interaction, studying and sleeping in the same space, and technology fatigue decreased motivation. Due to rapid changes in learning and the stress, anxiety and isolation created by the pandemic, managing study, personal life and placement resulted in a gap in confidence in clinical skills development for students. Students took their professional identity seriously, engaged in behaviours to reduce transmission of Covid-19 and employed a range of coping strategies to protect wellbeing. A challenge with the move to online delivery was the absence of informal peer learning and students indicated that moving forward they would value a hybrid approach to delivery. Higher Education should capitalise on innovative learning experiences developed during the pandemic however it is important to research the impact this has on student skill acquisition and learning experience.

Adolescent development and sexual health in the curriculum of health science careers

Adolescence is one of the most complex, profound and transitional stages of the life cycle, a time of interconnection in the biological, psychological, emotional, social, behavioral and cognitive dimensions until reaching maximum maturity; in response to this, society demands health professionals to contribute to the community in activities to promote health and prevent disease. In this sense, this study arises with the intention of determining the sexual health culture in sexually active adolescents. For this purpose, a qualitative, phenomenological type of research was carried out, in which interviews were conducted with previously structured open-ended questions to 4 adolescents who met the inclusion and exclusion criteria. After collecting the information, the results were subjected to analysis and interpretation through the process of categorization and coding, having obtained that: sexually active adolescents have little information on sexual health, sexual practice is generally monogamous, early onset, product of peer and acquaintance pressure, coupled with curiosity; there is condom use; however, the information comes from various sources and scarcely from the health unit.

The Responses of Rural Learner Nurses to Virtual Learning in a Covid-19 Era

Background: The COVID-19 pandemic resulted in many universities suspending their academic activities, making virtual learning an option for saving the disrupted academic year. The pandemic presented an opportunity to assess the implementation of virtual learning at this university, thus forcing rural-based universities to enhance their learning management system, including their clinical disciplines. This paper explores the use of virtual learning amongst learner nurses in a rural-based university by following the el-CDDO framework. Method: A quantitative descriptive design was applied to describe the barriers experienced to virtual learning, in a rural university. The purposive convenience sampling method was used to select learner nurses from the Faculty of Healthcare Sciences. An electronic survey questionnaire with both open and closed-ended questions sent via WhatsApp messenger was used to collect data. Data were analyzed using descriptive statistics with SPSS version 26. Results: The el-CDDO components affected in the study included the Context, Delivery, and Outcomes of virtual learning in a rural-based university. The Context demonstrated geographically disadvantaged learner nurses, which affects virtual learning delivery. Thus, the Outcomes included various barriers to virtual learning, such as weak networks for connecting to Blackboard, the lack of ICT facilities, such as laptops and tablets, by learner nurses, a lack of skills for using Blackboard, and ageing academics. Conclusion: The study findings provide a baseline reference for future digital health in the clinical area and the use of virtual learning in a rural-based university. Though we noted complex challenges such as the lack of gadgets, our findings provide a significant contribution to the planning for virtual learning in universities and the use of digital health in the clinical area. Addressing the virtual learning barriers discussed in this paper will be a significant step forward in equipping learner nurses as future healthcare professionals with digital knowledge and skills. There is a need to develop strategies to enhance virtual learning in rural-based universities to ensure future digital health.

Medical informatics and climate change: a framework for modeling green healthcare solutions.

The aim of this study was to develop a theory-based framework to enhance and accelerate development, selection, and implementation of solutions mitigating the climate impact of healthcare organizations. Existing frameworks were combined to develop the Green-MIssion (Medical Informatics Solutions) framework. It was further developed and refined by mapping solutions from project plans and reviewing it with an expert panel. The framework classifies solutions into three categories: (1) monitor and measure environmental impact of a healthcare setting; (2) help create and increase awareness among employees and patients; and (3) interventions to reduce environmental impacts. The framework combines concepts from healthcare information technology and environmental sciences and can be used to structure green medical informatics solutions for different healthcare settings. Furthermore, research should evaluate its application for measuring and assessing the impact of green medical informatics solutions on environmental sustainability and climate resilience.

Factors Affecting Artificial Intelligence and Management of Institutional Response to the Event of Coronavirus in Pakistan

With millions of people segregating around the globe, Coronavirus stands truly a global event. It ranges to the trajectories of states with miserable and wrecked health care systems. The transmission is aided by the wide-ranging response from the policy planning and state organizations. Experts are aware of the sternness and contamination of the infectious disease and its disastrous consequences that desire for inoculation of Artificial Intelligence (AI). The absence of an AI policy rejoinder may lead to increased fatalities for weathering the storm. Despite the wide range of responses, the up-to-date policy needs an organized way to track the inflexibility of state-run organizations’ frameworks to attain the objectives of AI organizational policy response. The study’s objectives include including key national institutions to understand perceptions and motivations to challenge the event of COVID-19 through common grounds of Artificial Intelligence. The data is obtained through an online survey from the foreign office, health care services, inter-coordination ministries, and science and technology ministry. The paper has unfolded the useless directions, impractical steps, uncertainty, ineffective communication, and social protection, which led to the rapid spread of infection. Refining each health indicator and reducing the progression of the pandemic through the AI archetype is conceivable only when officialdoms employ the AI-based approach.

Protocol for establishing and evaluating a public and patient panel for organisation science and management principles in healthcare

IntroductionPatient and public involvement (PPI) has not been used to its full potential when examining the organisational science and management principles side of healthcare. With more and more acknowledgement of...

Guest Editorial Advanced Machine Learning Algorithms for Biomedical Data and Imaging

The papers in this special section focus on advanced machine learning algorithms for biomedical data and image processing. Researchers in machine learning including those working in computer vision, image processing, biomedical analysis, and related fields when tied with experienced clinicians can play a significant role in understanding and working on complex medical data which ultimately improves patient care. Developing a novel machine-learning algorithm specific to medical data is a challenge and need of the hour. Healthcare and biomedical sciences have become data-intensive fields, with a strong need for sophisticated data mining methods to extract the knowledge from the available information. Biomedical data contains several challenges in data analysis, including high dimensionality, class imbalance, and low numbers of samples. Although the current research in this field has shown promising results, several research issues need to be explored as follows. There is a need to explore novel feature selection methods to improve predictive performance along with interpretation and to explore large-scale data in biomedical sciences.

ENTROPY BASED GREEDY UNSUPERVISED FEATURE SELECTION METHOD USING ROUGH SET THEORY FOR CLASSIFICATION

Feature selection technique attempts to select and remove irrelevant features while ensuring that an informative subset of features remains in the dataset. The performance of a classifier often depends on the feature subset used for the robust classification task. In the medical and healthcare application domain, classification accuracy plays a vital role. The higher level of false negatives in medical diagnosis systems may raise the risk of patients not employing the necessary treatment they need. In this article, we have proposed an unsupervised feature selection method that underlines the concepts of rough set theory for the task of classification of high-dimensional datasets. Experiments are carried out on seven public domain healthcare and life science related datasets. The obtained experimental results justify the significance of the proposed method over five other state-of-the-art feature selection methods.

Healthcare Science for Lifelong Health—Visualizing Biological Rhythms and Regulating Them on One’s Own

Healthcare Science for Lifelong Health—Visualizing Biological Rhythms and Regulating Them on One’s Own

Bioinspired shark skin-based liquid metal triboelectric nanogenerator for self-powered gait analysis and long-term rehabilitation monitoring

Real-time gait monitoring is crucial for neuromuscular diagnosis and rehabilitation of neuromuscular ailments. However, the existing wearable sensors for gait analysis suffer from several drawbacks, such as external power requirement, poor sensitivity, short-term stability, and professional operator requirement, which restrict their applicability outside clinical settings. Here, a next-generation self-powered solid-liquid triboelectric nanogenerator-based flexible wearable sensor is developed. The proposed sensor is composed of a highly resilient liquid metal encapsulated within an innovative bio-mimicked shark skin-like microstructure embedded on the Ecoflex surface. The unique surface morphology imparts hydrophobicity to the solid triboelectric layer, which prevents the liquid metal adhesion during sensing and facilitates highly sensitive real-time monitoring of signals and long-term stability. The as-designed low-cost, highly scalable self-powered sensor, which is also compatible with diverse detection strategies, provides an on-demand user-friendly point-of-care gait detection and rehabilitation monitoring system with significant applications in personalized health care and sports science.

Digital Marketing Strategies Driven by Wellbeing in Virtual Communities

In the new era ushered in by Covid-19, priority has been given to peoples’ wellbeing. Wellbeing in virtual communities was analysed from several perspectives, such as healthcare, technology, and social science: hence, the importance of a literature review that clarifies how studying health, happiness, comfort and quality of life of virtual communities’ members could guide firms to conceive their digital communication and marketing strategies. This work presents a literature review of papers spanning from 2010 to 2021, and which study digital marketing strategies driven by wellbeing in virtual communities. Results indicate a growing research interest after the pandemic regarding both positive and negative wellbeing dimensions, especially as drivers for digital segmentation, targeting and positioning strategies. Moreover, results highlight the remarkable increase of papers focusing on the tourism industry, game related strategies, and marketing analytics as relevant tools that support digital communication and influence strategies towards virtual communities. Finally, this literature review provides researchers with guidance for future studies in terms of relevant methodologies and areas of research not yet explored.

Bibliometric analysis of core competencies associated nursing management publications.

This study aimed to identify high-impact papers on global nursing to determine and analyse the publication of articles on core competencies in nursing-related journals and the research trends in the era of globalization. Bibliometrics has been shown to be an effective method for analysing publications. Through bibliometrics, nursing managers and researchers can understand the trends of high-impact international nursing core competencies research, identify mainstream research directions and obtain relevant knowledge and information, thereby facilitating the translation of research outcomes into nursing management practice. The study adopted bibliometric analysis and the VOSviewer software to explore dynamic publication trends and analyse the current situation of nursing research from a comprehensive development perspective, which was realized by searching for nursing core competencies papers in the Web of Science (WoS) database, calculating citations and determining the trends of the most influential papers. Nursing core competencies research grew rapidly between 1997 and 2022. Countries with the most core competencies publications were the United States, England, Australia and Canada. The Journal of Nursing Management has attracted substantial attention from researchers worldwide. Education, Management and Nurses were the most frequently used keywords in the study. A total of 534 papers were retrieved from the WoS database with the main research fields, including nursing, business economics, public environmental occupational health and health care science services. Equipping nursing graduates with core competencies has always been an important goal of global medical and nursing education. This study analysed papers across 35 years, most of which were published in the Journal of Nursing Management. In addition, the study identified some of the main research topics of nursing management, such as the integration of education with nursing management and the cultivation of nurses' core competencies. The study also provides a fresh review of highly cited articles. The results of the study show that high-quality articles play the role of improving both the quality and the quantity of related research. By analysing the trends of the research on core competencies, this study lays a bibliometric foundation for researchers regarding international journals, hot topics and relevant fields. In addition, the highly cited articles reveal new perspectives for the nursing field, providing inspiration for nursing management and education researchers. This study provides scholars and managers with an overview of the current situation of nursing management research and the development of benchmark journals. The study provides researchers not only with a better understanding of various international journals, allowing them to transition out of traditional thinking in the era of science and technology, but also with innovative thinking by combining research with nursing management. The results of this study invite nursing managers to study relevant topics of core competencies and integrate information technology to education, management and nurses, thereby contributing to nursing management and educational research.