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1 – 10 of over 2000
Article
Publication date: 8 August 2022

Williams E. Nwagwu and Omwoyo Bosire Onyancha

This paper aims to examine the global pattern of growth and development of eHealth research based on publication headcount, and analysis of the characteristics, of the keywords…

Abstract

Purpose

This paper aims to examine the global pattern of growth and development of eHealth research based on publication headcount, and analysis of the characteristics, of the keywords used by authors and indexers to represent their research content during 1945–2019.

Design/methodology/approach

This study adopted a bibliometric research design and a quantitative approach. The source of the data was Elsevier’s Scopus database. The search query involved multiple search terms because researchers’ choice of keywords varies very significantly. The search for eHealth research publications was limited to conference papers and research articles published before 2020.

Findings

eHealth originated in the late 1990s, but it has become an envelope term for describing much older terms such as telemedicine, and its variants that originated much earlier. The keywords were spread through the 27 Scopus Subject Areas, with medicine (44.04%), engineering (12.84%) and computer science (11.47%) leading, while by Scopus All Science Journal Classification Health Sciences accounted for 55.83% of the keywords. Physical sciences followed with 30.62%. The classifications social sciences and life sciences made only single-digit contributions. eHealth is about meeting health needs, but the work of engineers and computer scientists is very outstanding in achieving this goal.

Originality/value

This study demonstrates that eHealth is an unexplored aspect of health literature and highlights the nature of the accumulated literature in the area. It further demonstrates that eHealth is a multidisciplinary area that is attractive to researchers from all disciplines because of its sensitive focus on health, and therefore requires pooling and integration of human resources and expertise, methods and approaches.

Details

Global Knowledge, Memory and Communication, vol. 73 no. 3
Type: Research Article
ISSN: 2514-9342

Keywords

Article
Publication date: 20 September 2022

Jillian Cavanagh, Timothy Bartram, Matthew Walker, Patricia Pariona-Cabrera and Beni Halvorsen

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector…

Abstract

Purpose

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector. There are over 16,000 medical scientists (AIHW, 2019) in Australia responsible for carrying out pathology testing to help save the lives of thousands of patients every day. However, there are systemic shortages of medical scientists largely due to erratic rostering practices and workload issues. The purpose of this paper is to integrate evidence-based human resource management (EBHRM), the LAMP model and HR analytics to enhance line manager decision-making on rostering to support the wellbeing of medical scientists.

Design/methodology/approach

Using a qualitative methodological approach, the authors conducted 21 semi-structured interviews with managers/directors and nine focus groups with 53 medical scientists, making a total 74 participants from four large public hospitals in Australia.

Findings

Across four health services, manual systems of rostering and management decisions do not meet the requirements of the enterprise agreement (EA) and impact negatively on the wellbeing of medical scientists in pathology services. The authors found no evidence of the systematic approach of the organisations and line managers to implement the LAMP model to understand the root causes of rostering challenges and negative impact on employees. Moreover, there was no evidence of sophisticated use of HR analytics or EBHRM to support line managers' decision-making regarding mitigation of rostering related challenges such as absenteeism and employee turnover.

Originality/value

The authors contribute to HRM theory by integrating EBHRM, the LAMP model (Boudreau and Ramstad, 2007) and HR analytics to inform line management decision-making. The authors advance understandings of how EBHRM incorporating the LAMP model and HR analytics can provide a systematic and robust process for line managers to make informed decisions underpinned by data.

Details

Personnel Review, vol. 53 no. 1
Type: Research Article
ISSN: 0048-3486

Keywords

Article
Publication date: 8 July 2022

Uzair Khan, Hikmat Ullah Khan, Saqib Iqbal and Hamza Munir

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in…

Abstract

Purpose

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in the research domains of object detection, Biomedical Imaging and Semantic segmentation. In this study, a bibliometric analysis of publications related to image processing in the Science Expanded Index Extended (SCI-Expanded) has been performed. Several parameters have been analyzed such as annual scientific production, citations per article, most cited documents, top 20 articles, most relevant authors, authors evaluation using y-index, top and most relevant sources (journals) and hot topics.

Design/methodology/approach

The Bibliographic data has been extracted from the Web of Science which is well known and the world's top database of bibliographic citations of multidisciplinary areas that covers the various journals of computer science, engineering, medical and social sciences.

Findings

The research work in image processing is meager in the past decade, however, from 2014 to 2019, it increases dramatically. Recently, the IEEE Access journal is the most relevant source with an average of 115 publications per year. The USA is most productive and its publications are highly cited while China comes in second place. Image Segmentation, Feature Extraction and Medical Image Processing are hot topics in recent years. The National Natural Science Foundation of China provides 8% of all funds for Image Processing. As Image Processing is now becoming one of the most critical fields, the research productivity has enhanced during the past five years and more work is done while the era of 2005–2013 was the area with the least amount of work in this area.

Originality/value

This research is novel in this regard that no previous research focuses on Bibliometric Analysis in the Image Processing domain, which is one of the hot research areas in computer science and engineering.

Article
Publication date: 5 January 2024

Manuel Goyanes, Márton Demeter, Gergő Háló, Carlos Arcila-Calderón and Homero Gil de Zúñiga

Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender…

Abstract

Purpose

Gender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic.

Design/methodology/approach

Based on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender.

Findings

Results indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document.

Originality/value

This study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions.

Details

Online Information Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 15 December 2022

Majid Balaei-Kahnamoei, Mohammad Al-Attar, Mahdiyeh Khazaneha, Mahboobeh Raeiszadeh, Samira Ghorbannia-Dellavar, Morteza Bagheri, Ebrahim Salimi-Sabour, Alireza Shahriary and Masoud Arabfard

Acute and chronic obstructive pulmonary disease (COPD) is a common and progressive lung disease that makes breathing difficult over time and can even lead to death. Despite this…

Abstract

Purpose

Acute and chronic obstructive pulmonary disease (COPD) is a common and progressive lung disease that makes breathing difficult over time and can even lead to death. Despite this, there is no definitive treatment for it yet. This study aims to evaluate the studies on single and combined herbal interventions affecting COPD.

Design/methodology/approach

In this study, all articles published in English up to 2020 were extracted from the Web of Science (WoS) database and collected using Boolean tools based on keywords, titles and abstracts. Finally, the data required for bibliographic analysis, such as the author(s), publication year, academic journal, institution, country of origin, institution, financial institution and keywords were extracted from the database.

Findings

A total of 573 articles were analyzed. The number of papers in the lung disease field showed an upward trend from 1984 to 2021, and there was a surge in paper publications in 2013. China, Korea and Brazil published the highest number of studies on COPD, and Chinese medical universities published the most papers. Three journals that received the highest scores in this study were the Journal of Ethnopharmacology, International Immunopharmacology and Plos One. In the cloud map, expression, activation and expression were the most frequently researched subjects. In the plus and author keywords, acute lung injury was the most commonly used word. Inflammation, expression of various genes, nitric oxide-dependent pathways, NFkappa B, TNFalpha and lipopolysaccharide-dependent pathways were the mechanisms underlying COPD. Scientometric analysis of COPD provides a vision for future research and policymaking.

Originality/value

This study aimed to evaluate the studies on single and combined herbal interventions affecting COPD.

Details

Library Hi Tech, vol. 42 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 8 January 2024

Amrollah Shamsi, Ting Wang, Narayanaswamy Vasantha Raju, Arezoo Ghamgosar, Golbarg Mahdizadeh Davani and Mohammad Javad Mansourzadeh

By distorting the peer review process, predatory journals lure researchers and collect article processing charges (APCs) to earn income, thereby threatening clinical decisions…

99

Abstract

Purpose

By distorting the peer review process, predatory journals lure researchers and collect article processing charges (APCs) to earn income, thereby threatening clinical decisions. This study aims to identifying the characteristics of predatory publishing in the dermatology literature.

Design/methodology/approach

The authors used Kscien's list to detect dermatology-related predatory journals. Bibliometric parameters were analyzed at the level of journals, publishers, documents and authors.

Findings

Sixty-one potential predatory dermatology publishers published 4,164 articles in 57 journals from 2000 to 2020, with most publishers claiming to be located in the United States. Most journals were 1–5 years old. Six journals were indexed in PubMed, two in Scopus and 43 in Google Scholar (GS). The average APC was 1,049 USD. Skin, patient, cutaneous, psoriasis, dermatitis and acne were the most frequently used keywords in the article's title. A total of 1,146 articles in GS received 4,725 citations. More than half of the journals had <10 citations. Also, 318 articles in Web of Science were contaminated by the most cited articles and 4.49% of the articles had reported their funding source. The average number of authors per article was 3.7. India, the United States and Japan had the most articles from 119 involved countries. Asia, Europe and North America had the most contributed authors; 5.2% of articles were written through international collaboration. A majority of authors were from high- and low-middle-income countries. Women contributed 43.57% and 39.66% as the first and corresponding authors, respectively.

Research limitations/implications

The study had limitations, including heavy reliance on Kscien's list, potential for human error in manual data extraction and nonseparation of types of articles. Journals that only published dermatology articles were reviewed, so those occasionally publishing dermatology articles were missed. Predatory journals covering multiple subjects (Petrisor, 2016) may have resulted in overlooking some dermatology papers. This study did not claim to have covered all articles in predatory dermatology journals (PDJs) but evaluated many of them. The authors accept the claim that Kscien's list may have made a mistake in including journals.

Originality/value

The wide dispersion of authors involved in PDJs highlights the need to increase awareness among these authors.

Details

Online Information Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1468-4527

Keywords

Open Access
Article
Publication date: 6 April 2023

Haifa Mohammad Algahtani, Haitham Jahrami and Mariwan Husni

The COVID-19 pandemic has had a significant impact on medical education and training, with many medical schools and training programs having to adapt to remote or online learning…

Abstract

Purpose

The COVID-19 pandemic has had a significant impact on medical education and training, with many medical schools and training programs having to adapt to remote or online learning, social distancing measures and other challenges. This paper aimed to examine the disruption for clinical training, as it has reduced the opportunities for students and trainees to gain hands-on experience and interact with patients in person.

Design/methodology/approach

The ethnographic qualitative research design was chosen as the research methodology. Using Gibbs' reflective cycle, the researcher explored the psychiatry clerks' (final-year medical students) reflections on the disruption of their clinical training during the COVID-19 pandemic.

Findings

The findings demonstrated that the students had a significant psychological impact on their coping capacities as the crisis progressed from shock and depression to resilience. The students being the key stakeholders provided a concrete foundation for the development of a framework for improving practices during uncertain times.

Originality/value

Students' reflections provided valuable insight into the pandemic’s impact on their psychosocial lives with uncertainty and incapacity to cope up with changing stressful dynamics. The results will assist in planning how to best support medical students' well-being during interruptions of their educational process brought about by similar future crises.

Details

Arab Gulf Journal of Scientific Research, vol. 42 no. 2
Type: Research Article
ISSN: 1985-9899

Keywords

Open Access
Article
Publication date: 19 December 2023

Qinxu Ding, Ding Ding, Yue Wang, Chong Guan and Bosheng Ding

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive…

1041

Abstract

Purpose

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Design/methodology/approach

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

Findings

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

Practical implications

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

Originality/value

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

Details

Journal of Electronic Business & Digital Economics, vol. 3 no. 1
Type: Research Article
ISSN: 2754-4214

Keywords

Open Access
Article
Publication date: 4 December 2023

Mariona Espaulella-Ferrer, Felix Jorge Morel-Corona, Mireia Zarco-Martinez, Alba Marty-Perez, Raquel Sola-Palacios, Maria Eugenia Campollo-Duquela, Maricelis Cruz-Grullon, Emma Puigoriol-Juvanteny, Marta Otero-Viñas and Joan Espaulella-Panicot

Older people living in nursing homes have complex care needs and frequently need specialists’ advice and support that can be challenging to deliver in a rural setting. The aim of…

Abstract

Purpose

Older people living in nursing homes have complex care needs and frequently need specialists’ advice and support that can be challenging to deliver in a rural setting. The aim of this paper is to describe a model of integrated care in a rural area supported by a nurse case manager.

Design/methodology/approach

A real-world evidence study of people living in Ribes de Freser nursing home, was conducted between specific timeframes in 2019 and 2022, comparing the casemix and outcomes of a traditional care model with the integrated interdisciplinary model.

Findings

The integrated care model led to a significant reduction in transfers to the emergency department, hospitalisations, outpatient medical visits and a reduction in the number of medicines. In addition, the number of residents receiving end-of-life care at the nursing home showed a substantial increase.

Originality/value

This case study contributes valuable evidence supporting the implementation of an integrated model of nurse case manager support in nursing homes, particularly in the rural contexts, where access to specialist medical staff may be limited. The findings highlight the potential benefits of person-centred integrated care for older adults, addressing their complex needs and improving end-of-life care in nursing home settings.

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