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Bibliographic analysis of psychiatric publications in Taiwan: An analysis of Web of Science subject category from 1970 to 2023

BACKGROUND

Mental diseases continue to rank among the top 10 leading causes of global burden. Psychiatric research is a crucial avenue through which mental healthcare can be enhanced. Taiwanese academics have constantly concentrated their efforts on psychiatric research and published their findings. A systematic examination of these papers will provide an assessment of the present state and contribute to the formulation of future policies for psychiatric research in Taiwan. We assessed psychiatric papers from Taiwan using the Web of Science (WoS) database.

METHODS

Academic papers in the Psychiatry category of the WoS database from Taiwan were retrieved and evaluated. The analysis included papers published in Science Citation Index-Expanded and Social Science Citation Indexed journals between 1970 and 2023, excluding meeting abstracts and corrections.

RESULTS

Of the 1 049 281 papers published globally in the Psychiatry category of the WoS system between 1970 and 2023, 6117 (0.58%) were published in Taiwan. Taiwan ranked 26th globally in terms of number of papers published. These publications have received 150 519 citations. Over the past 53 years, both the annual number of psychiatric papers from Taiwan and their citations received have significantly and rapidly increased. However, the average impact factor of publications remained constant over time.

CONCLUSION

Over the last five decades, the number of psychiatric publications from Taiwan has increased. However, the average impact factor of these published papers did not increase over time. Investing in advanced research infrastructure and interdisciplinary projects may improve the quality and relevance of Taiwanese psychiatric research publications, potentially increasing their global citations and impact.

Bibliometric and visual analysis in the field of two-dimensions nano black phosphorus in cancer from 2015 to 2023

This study aims to provide a comprehensive summary of the status and trends of Two-Dimensional Nano Black Phosphorus (2D nano BP) in cancer research from 2015 to 2023, offering insights for future studies. To achieve this, articles from the Web of Science database published between 2015 and 2023 were analyzed using R and VOSviewer software. The analysis included 446 articles, revealing a consistent increase in publication rates, especially between 2017 and 2019. China emerged as a leader in both publication volume and international collaborations. Prominent journals in this field included ACS Applied Materials & Interfaces and Advanced Materials, while key researchers were identified as Zhang Han, Tao Wei, and Yu Xuefeng. The analysis highlighted common keywords such as drug delivery, photothermal therapy, photodynamic therapy, and immunotherapy, indicating the major research focuses. The findings suggest that 2D nano BP holds significant promise in cancer treatment research, with a growing global interest. This study thus serves as a valuable reference for future investigations, providing a detailed analysis of the current state and emerging trends in this promising field.

A Systematic Review of Visualization Techniques and Analysis Tools for Eye-Tracking in 3D Environments

This systematic literature review presents an update on developments in 3D visualization techniques and analysis tools for eye movement data in 3D environments. With the introduction of affordable and non-intrusive eye-tracking solutions to the mass market, access to users' gaze is now increasingly possible. As a result, the adoption of eye-tracking in virtual environments using head-mounted displays is expected to increase since the trend is to incorporate gaze tracking as part of new technical solutions. The systematic literature review presented in this paper was conducted using the Scopus database (using the period 2017 to 17th of May 2022), which after analysis, resulted in the inclusion of 15 recent publications with relevance in eye-tracking visualization techniques for 3D virtual scenes. First, this paper briefly describes the foundations of eye-tracking and traditional 2D visualization techniques. As background, we also list earlier 3D eye-tracking visualization techniques identified in a previous review. Next, the systematic literature review presents the method used to acquire the included papers and a description of these in terms of eye-tracking technology, observed stimuli, application context, and type of 3D gaze visualization techniques. We then discuss the overall findings, including opportunities, challenges, trends, and present ideas for future directions. Overall the results show that eye-tracking in immersive virtual environments is on the rise and that more research and developments are needed to create novel and improved technical solutions for 3D gaze analysis.

A Systematic Literature Review of Learning-Based Traffic Accident Prediction Models Based on Heterogeneous Sources

Statistics affirm that almost half of deaths in traffic accidents were vulnerable road users, such as pedestrians, cyclists, and motorcyclists. Despite the efforts in technological infrastructure and traffic policies, the number of victims remains high and beyond expectation. Recent research establishes that determining the causes of traffic accidents is not an easy task because their occurrence depends on one or many factors. Traffic accidents can be caused by, for instance, mechanical problems, adverse weather conditions, mental and physical fatigue, negligence, potholes in the road, among others. At present, the use of learning-based prediction models as mechanisms to reduce the number of traffic accidents is a reality. In that way, the success of prediction models depends mainly on how data from different sources can be integrated and correlated. This study aims to report models, algorithms, data sources, attributes, data collection services, driving simulators, evaluation metrics, percentages of data for training/validation/testing, and others. We found that the performance of a prediction model depends mainly on the quality of its data and a proper data split configuration. The use of real data predominates over data generated by simulators. This work made it possible to determine that future research must point to developing traffic accident prediction models that use deep learning. It must also focus on exploring and using data sources, such as driver data and light conditions, and solve issues related to this type of solution, such as high dimensionality in data and information imbalance.

Emotional Intelligence Measures: A Systematic Review

Emotional intelligence (EI) refers to the ability to perceive, express, understand, and manage emotions. Current research indicates that it may protect against the emotional burden experienced in certain professions. This article aims to provide an updated systematic review of existing instruments to assess EI in professionals, focusing on the description of their characteristics as well as their psychometric properties (reliability and validity). A literature search was conducted in Web of Science (WoS). A total of 2761 items met the eligibility criteria, from which a total of 40 different instruments were extracted and analysed. Most were based on three main models (i.e., skill-based, trait-based, and mixed), which differ in the way they conceptualize and measure EI. All have been shown to have advantages and disadvantages inherent to the type of tool. The instruments reported in the largest number of studies are Emotional Quotient Inventory (EQ-i), Schutte Self Report-Inventory (SSRI), Mayer-Salovey-Caruso Emotional Intelligence Test 2.0 (MSCEIT 2.0), Trait Meta-Mood Scale (TMMS), Wong and Law’s Emotional Intelligence Scale (WLEIS), and Trait Emotional Intelligence Questionnaire (TEIQue). The main measure of the estimated reliability has been internal consistency, and the construction of EI measures was predominantly based on linear modelling or classical test theory. The study has limitations: we only searched a single database, the impossibility of estimating inter-rater reliability, and non-compliance with some items required by PRISMA.

Privacy Assessment in Android Apps: A Systematic Mapping Study

Android apps are daily installed by billions of users worldwide, who grant access to an extensive set of sensitive personal data. Different techniques have been developed over the years to understand how apps protect or harm their users’ privacy. However, these results have been produced in different research domains and addressing privacy from different perspectives, resulting in a growing but scattered body of knowledge. To bridge this gap, we have carried out a systematic mapping study to provide practitioners and researchers with an overview of the state-of-the-art technique, published between 2016 and 2020, to assess privacy in Android apps. In this paper, we highlight the most relevant findings, identify and analyse the most pressing gaps, and discuss the promising research directions.

Leveraging Capabilities of Technology into a Circular Supply Chain to Build Circular Business Models: A State-of-the-Art Systematic Review

The recent technological inclusions in supply chains are encouraging practitioners to continuously rethink and redesign these supply chains. Organizations are trying to implement sustainable manufacturing and supply chain practices to utilize their resources to the full extent in order to gain a competitive advantage. Circular supply chain management acts as the main pathway to achieve optimal circular business models; however, research in this area is still in its infancy and there is a need to study and analyze how the benefits of technology can be leveraged in conventional models to impact circular supply chains and build smart, sustainable, circular business models. To gain better familiarity with the future research paradigms, a detailed systematic literature review was conducted on this topic to identify the dynamics of this field and domains deserving further academic attention. A holistic and unique review technique was used by the authors to capture maximal insights. A total of 96 publications from 2010 to 2021 were selected from the Web of Science core collection database through strict keyword search codes and exclusion criteria, with neat integration of systematic and bibliometric analyses. The findings of this study highlight the knowledge gaps and future research directions, which are presented at the end of this paper.

Construction of H5-Index for Conference Ranking Indicator and its Correlation to ERA

This paper develops the Scopus H5-Index rankings, using the field of computer science as a case study. The challenge begins with the inconsistency of conference names. The rule-based approach is invented to automatically clean up duplicate conferences and assign unique pseudo ID for each conference. This data cleansing process is applied on conference names retrieved from both Scopus and ERA/CORE, in order to share common pseudo IDs for the sake of correlation analysis. The proposed data cleansing process is validated using ERA 2010 and CORE 2018 as references and reports the very small errors of 0.6% and 0.4%, respectively. Then, the Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018 rankings are constructed and compared with the existing ERA 2010 and CORE 2018 rankings, respectively. The results show that the correlation within the Scopus H5-Index rankings (i.e. Scopus H5-Index 2006–2010 and Scopus H5-Index 2014–2018) is at the top of the moderate correlation band, where the correlation within the ERA/CORE rankings (ERA 2010 and CORE 2018) is at the top of the strong correlation band. While the correlations across ranking systems (i.e. Scopus H5-Index 2006–2010 vs. ERA 2010, and Scopus H5-Index 2014–2018 vs. CORE 2018) are at the bottom and middle of the moderate correlation band. It can be said that the quality assessment using the Scopus H5-Index ranking is more dynamic and quickly up-to-date when compared with the ERA/CORE ranking. Also, these two ranking systems are moderately correlated with each other for both periods of 2010 and 2018.

The Sustainable Management of Land and Fisheries Resources Using Multicriteria Techniques: A Meta-Analysis

In recent years modern societies have attached a multifunctional requirement to the use of renewable resources, making their optimal sustainable management more complex. In the last decades, in many cases, this complexity is addressed by formulating management models with the help of the concepts and methods belonging to the well-known multicriteria decision-making (MCDM) paradigm. The purpose of this paper was to undertake a hermeneutic meta-analysis of the literature provided in primary journals on issues related to the management of these resources with the help of the MCDM paradigm. In this way, the paper aimed to obtain new, basic insights with considerations that might improve the efficiency of future research in the field studied. The meta-analysis was implemented by formulating and testing a battery of hypotheses of how the MCDM methods have been used in the past for the formulation of management models for the type of resource analyzed.

Systematic review of bibliometric studies on SARS-CoV-2

Objective: To perform a systematic review of articles that evaluated the scientific production on SARS-CoV-2 through bibliometric analyzes. Methods: Scopus, Web of Science and Google Scholar databases were used. After applying the pre-established inclusion criteria, 30 articles were included. Results. The total number of articles found in the bibliometric studies on SARS-CoV-2 varied widely from 153 to 21,395 articles and an average equal to 4,279 (± 5,510). A total of 17 countries published within the scope of this study, but only six published more than one article, emphasizing authors from Chinese institutions (17%). Scopus was the most used database in bibliometric studies (50%, n = 15). The articles used 72 different keywords with emphasis on: COVID-19 (15%), SARS-CoV-2 (12%) and 2019-nCoV (9%). Conclusion. We are facing an unprecedented scenario of information about SARS-CoV-2 and this has required a collective scientific effort reflected in the daily publication of hundreds of studies (articles, pre-prints, clinical guides, protocols). Bibliometric methods are being increasingly used by the scientific community to systematize this information. Therefore, the systematic review carried out in this study provided an overview of the bibliometric literature on the SARS-CoV-2 virus.

Detecting bursty terms in computer science research

Research topics rise and fall in popularity over time, some more swiftly than others. The fastest rising topics are typically called bursts; for example “deep learning”, “internet of things” and “big data”. Being able to automatically detect and track bursty terms in the literature could give insight into how scientific thought evolves over time. In this paper, we take a trend detection algorithm from stock market analysis and apply it to over 30 years of computer science research abstracts, treating the prevalence of each term in the dataset like the price of a stock. Unlike previous work in this domain, we use the free text of abstracts and titles, resulting in a finer-grained analysis. We report a list of bursty terms, and then use historical data to build a classifier to predict whether they will rise or fall in popularity in the future, obtaining accuracy in the region of 80%. The proposed methodology can be applied to any time-ordered collection of text to yield past and present bursty terms and predict their probable fate.

Análisis de la producción científica del Ecuador e impacto de la colaboración internacional en el periodo 2006-2015

La producción científica del Ecuador en relación con otros países latinoamericanos ha sido históricamente baja, en gran parte debido a la falta de cultura científica y políticas adecuadas que promuevan la investigación, además del descuido en priorizar la investigación en las universidades. Sin embargo, en los últimos 10 años, el gobierno ha implementado diversas políticas para ayudar a remediar esta situación. Presentamos un análisis bibliométrico de la producción de la investigación ecuatoriana durante el período 2006-2015. Los resultados muestran que la producción científica de Ecuador ha aumentado 5.16 veces en los últimos años, lo que supera el crecimiento latinoamericano. Más del 80% de las publicaciones ecuatorianas incluyen colaboración internacional, principalmente con EE.UU., España, el Reino Unido, Alemania, Francia, Brasil y Colombia. Se discuten las implicaciones de política pública.

Specialist Bibliographic Databases

Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and database vendors, such as EBSCOhost and ProQuest, facilitate advanced searches supported by specialist keyword thesauri. Searches of items through specialist databases are complementary to those through multidisciplinary research platforms, such as PubMed, Web of Science, and Google Scholar. Familiarizing with the functional characteristics of biomedical and nonbiomedical bibliographic search tools is mandatory for researchers, authors, editors, and publishers. The database users are offered updates of the indexed journal lists, abstracts, author profiles, and links to other metadata. Editors and publishers may find particularly useful source selection criteria and apply for coverage of their peer-reviewed journals and grey literature sources. These criteria are aimed at accepting relevant sources with established editorial policies and quality controls.

Citation success of different publication types: a case study on all references in psychology publications from the German-speaking countries (D-A-CH-L-L) in 2009, 2010, and 2011

Scientometric data on the citation success of different publication types and publication genres in psychology publications are presented. Data refer to references that are cited in these scientific publications and that are documented in PSYNDEX, the exhaustive database of psychology publications from the German-speaking countries either published in German or in English language. Firstly, data analyses refer to the references that are cited in publications of 2009 versus 2010 versus 2011. With reference to all cited references, the portion of journal articles ranges from 57 to 61 %, of books from 22 to 24 %, and of book chapters from 14 to 15 %, with a rather high stability across the three publication years analysed. Secondly, data analyses refer to the numbers of cited references from the German-speaking countries, which are also documented in PSYNDEX. These compose about 11 % of all cited references indicating that nearly 90 % of the references cited are of international and/or interdisciplinary publications not stemming from the German-speaking countries. The subsample shows the proportion of journal articles, books, and chapters, and these are very similar to the percentages identified for all references that are cited. Thirdly, analyses refer to document type, scientific genre, and psychological sub-discipline of the most frequently cited references in the psychology publications. The frequency of top-cited references of books and book chapters is almost equal to that of journal articles; two-thirds of the top-cited references are non-empirical publications, only one-third are empirical publications. Top-cited references stem particularly from clinical psychology, experimental psychology, as well as tests, testing and psychometrics. In summary, the results point to the fact that citation analyses, which are limited to journal papers, tend to neglect very high portions of references that are cited in scientific publications.

Chemical bibliographic databases: the influence of term indexing policies on topic searches

How many articles can we retrieve from a topic search in chemical bibliographic databases?