Understanding the Experience of Geriatric Care Professionals in Using Telemedicine to Care for Older Patients in Response to the COVID-19 Pandemic: Qualitative Study (Preprint)

BACKGROUND Geriatric care professionals were forced to rapidly adopt the use of telemedicine technologies to ensure the continuity of care for their older patients in response to the COVID-19 pandemic. However, there is little current literature that describes how telemedicine technologies can best be employed to meet the needs of geriatric care professionals in providing care to frail older patients and their caregivers, and families. OBJECTIVE This study aimed to identify the benefits and challenges geriatric care professionals face when using telemedicine technologies with frail older patients, their caregivers, and families, and how to maximize the benefits of this method of providing care. METHODS We conducted a mixed methods study that recruited geriatric care professionals to complete an online survey regarding their personal demographics and experiences with using telemedicine and participate in a semi-structured interview. Interview responses were analyzed using the Consolidated Framework for Implementation Research (CFIR). RESULTS We obtained quantitative and qualitative data from 30 practicing geriatric care professionals (22 geriatricians, 5 geriatric psychiatrists, and 3 geriatric specialist nurses) recruited from across the Greater Toronto Area. Analysis of interview data identified 5 CFIR contextual barriers (Complexity, Design quality and packaging, Patient needs and resources, Readiness for implementation, and Culture) and 13 CFIR contextual facilitators (Relative Advantage, Adaptability, Tension for Change, Available Resources, Access to Knowledge, Network and Communications, Compatibility, Knowledge and Beliefs, Self-Efficacy, Champions, External Agents, Executing, and Reflecting and Evaluating). The CFIR concept of External Policy and Incentives was found to be a neutral construct. CONCLUSIONS This is the first known study to use the CFIR to develop a comprehensive narrative to characterize the experiences of geriatric care professionals using telemedicine technologies in providing care. Overall, telemedicine can significantly enable most of the geriatric care that is traditionally provided in person, but is less useful in providing specific aspects of geriatric care to frail older patients and their caregivers, and families.

NETME: on-the-fly knowledge network construction from biomedical literature

Background The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks.

Evaluation of Integrated Neuromuscular Training on the Recovery of Joint Injury: A Meta-Analysis and Systematic Review

Review question / Objective: This study will provide new evidence for the effect of integrated neuromuscular training on the recovery of joint injury. Information sources: According to the PICOS principle, the third and fourth authors of this paper searched PsycINFO, Science direct, PubMed, Eric, Willey, China Knowledge Network (CNKI) Academic Journal Online Publishing General Library and China Knowledge Network (CNKI) excellent doctoral thesis full-text database by computer to collect relevant research on the impact of INT on joint injury repair. The time limit of injury retrieval is from the establishment of the database to December 2021.

Incidence of breast cancer and methylation of PCDH gene: a single ratio meta analysis of single rate

IntroductionBreast cancer presents one of the highest rates of prevalence. With the development of genetics and biotechnology, we have learned that the occurrence and development of many cancers are closely related to abnormal gene expression. At present, some pieces of literature have reported that there may be a correlation between the expression of PCDH and the occurrence of breast cancer.Therefore, we selected some loci from PCDH gene to explore the correlation between the methylation of PCDH gene and breast cancer.Material and methodsThis research is a systematic review and critical appraisal, make a meta-analysis of prospective and retrospective cohort study. Research was conducted through computer Science, Wanfang and Chinese knowledge network databases PubMed, Embase and Network. In a literature search, seven cohort studies were identified. This I2 statistic is used to quantify heterogeneity. A fixed effect model was used to synthesize the results. Regression tests of linear funnel plot asymmetry were used to estimate potential publication bias.ResultsThe methylation rate of PCDH gene in breast cancer with lymph node metastasis was 75%, and that in breast cancer without lymph node metastasis was 70%. The methylation rate of PCDH gene was 75% in breast cancer group with high expression of the Ki-67 gene and 71% in breast cancer group with low expression of Ki-67 gene.ConclusionsAccording to previous studies, the positive rate of methylation of PCDH gene in breast cancer tissues is higher than that in adjacent tissues, and there is no obvious statistical difference in the correlation between lymphatic metastasis and Ki-67.

Mapping Trends and Hot-spots of Virtual Simulation Research in Nursing: A Bibliometric Analysis

Background: Virtual simulation has been widely used in nursing education and nursing training. This study aims to characterize the publications in terms of countries, institutions, journals, authors, collaboration relationships, and analyze the trends of virtual simulation in nursing research.Methods: Publications regarding virtual simulation in nursing were retrieved from Web of Science core collection. Microsoft Excel 2010, VOSviewer were used to characterize the contributions of the authors, journals, institutions, and countries. The trends, hot-spots and knowledge network were analyzed by Citespace and VOSviewer.Results: We identified 611 papers between 1999 and 2021. The number of publications grew slowly until 2019, after that, it got a sharp increase in 2020 and 2021. The USA, Canada and Australia were three key contributors to this field. Centennial College, University of Ottawa, and Ryerson University were three major institutions with a larger number of publications. Verkuyl M was the most productive and highest cited author. Clinical Simulation in Nursing, Nurse Education Today, Journal of Nursing Education were the three productive journals. "virtual patients," "nursing students," "clinical simulation," and "communication skills" were the frontier topics in recent years.Conclusion: Using the Virtual patients to train nursing students, developing more reliable and objective assessment methods to validate learning outcomes might be the recent and future hot-topics.

Data collection for outbreak investigations: process for defining a minimal data set using a Delphi approach

Background Timely but accurate data collection is needed during health emergencies to inform public health responses. Often, an abundance of data is collected but not used. When outbreaks and other health events occur in remote and complex settings, operatives on the ground are often required to cover multiple tasks whilst working with limited resources. Tools that facilitate the collection of essential data during the early investigations of a potential public health event can support effective public health decision-making. We proposed to define the minimum set of quantitative information to collect whilst using electronic device or not. Here we present the process used to select the minimum information required to describe an outbreak of any cause during its initial stages and occurring in remote settings. Methods A working group of epidemiologists took part in two rounds of a Delphi process to categorise the variables to be included in an initial outbreak investigation form. This took place between January–June 2019 using an online survey. Results At a threshold of 75 %, consensus was reached for nineteen (23.2%) variables which were all classified as ‘essential’. This increased to twenty-six (31.7%) variables when the threshold was reduced to 60% with all but one variable classified as ‘essential’. Twenty-five of these variables were included in the ‘Time zero initial case investigation’ ‘(T0)’ form which was shared with the members of the Rapid Response Team Knowledge Network for field testing and feedback. The form has been readily available online by WHO since September 2019. Conclusion This is the first known Delphi process used to determine the minimum variables needed for an outbreak investigation. The subsequent development of the T0 form should help to improve the efficiency and standardisation of data collection during emergencies and ultimately the quality of the data collected during field investigation.

Research Trend Analysis of Artificial Intelligence Rainfall Prediction Algorithms Based on Knowledge Networks

This research uses CiteSpace software as a tool to sort out the research results of artificial intelligence-based rainfall prediction models and algorithms in the China Knowledge Network Database (CNKI) and the “Web of Science” database, summarize relevant research hotspots and topics, and identify the latest research Trends, provide a reference for further advancement of rainfall prediction models and algorithms. Through knowledge network analysis, the following conclusions are drawn: (1) The literature based on rainfall prediction models and algorithms has shown an increasing trend over time. (2) It is scientific research institutions and colleges and universities of various countries that publish a large number of relevant documents. (3) The current research trend is deep learning and meteorological satellites. Neural networks tend to study a variety of data assimilation and hybrid models. (4) Global artificial intelligence-based rainfall prediction models and algorithms research results show that more emphasis is placed on deep learning algorithms Application trends.

Development, Innovation, and Circular Stimulation for a Knowledge-Based City: Key Thoughts

Practitioners of economic geography recognize innovation as the key factor in sustainable economic development and urging a city to evolve. Urban development evolves from manufacturing-based development to knowledge-based development. Identifying the future benefits of urban development is a research issue. This work analyzes development performance based on quantitative indices of critical knowledge and innovation that enhance economic growth and influence society and competitiveness. The research further identifies the possibility of knowledge dissemination and innovation. This work investigates the key factors encouraging the development of a knowledge-based city for Helsinki, Melbourne, and Hsinchu in terms of economy, society, environment, and management, and observes that the progressive and positive circular stimulation for a city requires not only the cultivation of human capital, but also the construction of social environment and internal relations to form a high-density knowledge network. This work demonstrates that Hsinchu Science Park acts as a highly stimulated and highly interactive knowledge engine by building a dynamic innovation model based on circular stimulation of knowledge feedback to construct an urban environment and series of talent networks. The city, ultimately, reaches a virtuous cycle for innovation and achieves critical factors for the evolution of a knowledge-based city.

Global knowledge centrality: co-inventor collaboration with China

PurposeThis paper examines the role of co-inventor collaboration with China and/or the USA on a country's increase in centrality in global knowledge networks. It also explores the role of specific institutional factors – corruption and intellectual property rights (IPR) protection – on this relationship.Design/methodology/approachIn the study, co-inventor data from the United States Patent and Trademark Office (USPTO) applications have been used to construct networks of technological knowledge collaboration at the country level over the years 2002–2015. Using eigenvector centrality as the dependent variable, the study uses fixed effect regression analyses on a panel of 171 countries, contributing to recent debates on knowledge networks and international cooperation.FindingsBuilding on research in economic development, innovation and social network theory, this research finds that co-patenting with Chinese inventors is positively related to a country's centrality in global knowledge networks and that this relationship is negatively moderated by collaboration with the current most central knowledge network – namely that of the USA – suggesting a substitution effect. It also finds a partial substitution between institutional factors, IPRs protection and transparency, and collaboration with China on a country's knowledge centrality.Practical implicationsRegarding policymakers, the findings can be used to encourage international collaboration for increased access to new sources of knowledge that fosters innovation while keeping a close eye on local institutions, especially emerging economies that want to increase their international knowledge network centrality.Originality/valueThis study creates a unique panel data set and extends the social networks approach in international business literature, focusing on institutional characteristics related to participation in knowledge networks.