Open-access Database Research Articles

The Database of Byzantine Book Epigrams Project: Principles, Challenges, Opportunities

This paper presents an overview of the history, conceptualization, and development of the Database of Byzantine Book Epigrams, an ongoing research project hosted at Ghent University. It also offers a glimpse into current and future research threads carried out within the project, with an eye on long-term sustainability. The first part of the paper pinpoints the position of DBBE within the broad field of Digital Humanities and addresses the question of how and why Byzantine metrical paratexts have been collected in an open-access online database. In the second part of the article, we describe the main features of the relational database currently available, both from the perspective of its users and from a technical point of view. The third section of the paper includes the description of four subprojects connected to DBBE, which at present involve the development of a graph database complementary to the relational one, the implementation of natural language pre-processing applied to the DBBE corpus, the linguistic analysis of formulaicity in book epigrams, and the exploration of the broad implications of the study of book epigrams for a better understanding of Byzantine book culture.

METHODOLOGY AND MEANING OF THE 3D MODELLING OF THE LOST BAALSHAMIN TEMPLE IN PALMYRA

Abstract. The Baalshamin temple in Palmyra was completely destroyed by ISIL in 2015. To address this issue, the “Collart-Palmyre Project” at the University of Lausanne (UNIL) digitally published the scientific archive of Paul Collart who was in charge of the excavation of the temple in the 1950’. Since 2017, the Project makes the archives accessible on an online open access database (tiresias.unil.ch). A 3D reconstruction of the temple has been realized by the UNIL team in collaboration with ICONEM. The 3D models (including handily drawn elements) are now being integrated onto a PoTree platform ( https://github.com/potree/potree) that allows archival items to be geolocated, associating them with the architectural or archaeological objects they document.The challenge here was to access metadata on the 3D model and to ease access to the archives through online tools.We also published a diachronic 3D model showing the different periods of occupation of the site (from the second century BC to the ninth century AD). Partnership with NGO’s also permit the presentation of 3D models to displaced Syrian refugees in the Spirit of the Faro Convention. Last but not least, the Project follows the guidelines of the London Charter and the Sevilla principles for Virtual Archaeology and questions the broader facets of neo-colonialist, economic and nationalist agendas that emerges from the 'migration of digital heritage' as assets to be exploited. This project wants to explore how these digital assets provide a scaffold for the memories of migrants.

News from the European Journal of Therapeutics: A new issue and a new editorial board

News from the European Journal of Therapeutics: A new issue and a new editorial board

Application of Cardiogenic Shock Working Group-defined Society for Cardiovascular Angiography and Interventions (CSWG-SCAI) Staging of Cardiogenic Shock to the Medical Information Mart for Intensive Care IV (MIMIC-IV) database

BackgroundThe optimal parameters for defining stages of cardiogenic shock (CS) are not yet known. The Cardiogenic Shock Working Group-defined Society for Cardiovascular Angiography and Interventions (CSWG-SCAI) staging of CS was developed to provide simple and specific parameters for risk-stratifying patients. ObjectivesThe purpose of this study was to test whether the Cardiogenic Shock Working Group-defined Society for Cardiovascular Angiography and Interventions (CSWG-SCAI) staging is associated with in-hospital mortality, using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. MethodsWe utilized the open-access MIMIC-IV database, which includes >300,000 patients admitted between 2008 and 2019. We extracted the clinical profile of patients admitted with CS and stratified them into different SCAI stages at admission based on the CSWG criteria. We then tested the association between in-hospital mortality and parameters of hypotension, hypoperfusion, and overall CSWG-SCAI stage. ResultsOf the 2463 patients, CS was predominantly caused by heart failure (HF; 54.7 %) or myocardial infarction (MI; 26.3 %). Mortality was 37.5 % for the total cohort, 32.7 % for patients with HF, and 40 % for patients with MI (p < 0.001). Mortality was higher among patients with mean arterial pressure < 65 mmHg, lactate >2 mmol/L, ALT >200 IU/L, pH ≤ 7.2, and more than one drug/device support at baseline. Increasing CSWG-SCAI stages at baseline and maximum CSWG-SCAI stage achieved were significantly associated with in-hospital mortality (p < 0.05). ConclusionsThe CSWG-SCAI stages are significantly associated with in-hospital mortality and may be used to identify hospitalized patients at risk of worsening cardiogenic shock severity. Condensed abstractWe analyzed data from 2463 patients with cardiogenic shock using the MIMIC-IV database to investigate the relationship between the Cardiogenic Shock Working Group-defined Society for Cardiovascular Angiography and Interventions (CSWG-SCAI) staging and in-hospital mortality. The main causes of cardiogenic shock were heart failure (54.7 %) and myocardial infarction (26.3 %). The overall mortality rate was 37.5 %, with a higher rate among patients with myocardial infarction (40 %) compared to those with heart failure (32.7 %). Mean arterial pressure < 65 mmHg, lactate >2 mmol/L, ALT >200 IU/L, and pH ≤ 7.2 were significantly associated with mortality. Increasing CSWG-SCAI stages at baseline and maximum achieved stages were strongly associated with higher mortality (p < 0.05). Therefore, the CSWG-SCAI staging system can be used to risk-stratify patients with cardiogenic shock.

Small bowel capsule endoscopy examination and open access database with artificial intelligence: The SEE-artificial intelligence project.

Artificial intelligence (AI) may be practical for image classification of small bowel capsule endoscopy (CE). However, creating a functional AI model is challenging. We attempted to create a dataset and an object detection CE AI model to explore modeling problems to assist in reading small bowel CE. We extracted 18,481 images from 523 small bowel CE procedures performed at Kyushu University Hospital from September 2014 to June 2021. We annotated 12,320 images with 23,033 disease lesions, combined them with 6161 normal images as the dataset, and examined the characteristics. Based on the dataset, we created an object detection AI model using YOLO v5 and we tested validation. We annotated the dataset with 12 types of annotations, and multiple annotation types were observed in the same image. We test validated our AI model with 1396 images, and sensitivity for all 12 types of annotations was about 91%, with 1375 true positives, 659 false positives, and 120 false negatives detected. The highest sensitivity for individual annotations was 97%, and the highest area under the receiver operating characteristic curve was 0.98, but the quality of detection varied depending on the specific annotation. Object detection AI model in small bowel CE using YOLO v5 may provide effective and easy-to-understand reading assistance. In this SEE-AI project, we open our dataset, the weights of the AI model, and a demonstration to experience our AI. We look forward to further improving the AI model in the future.

HCM-associated ALMS1 variant: Allele drop-out and frequency in Italian Sphynx cats.

Hypertrophic cardiomyopathy (HCM) is the most common cardiomyopathy in domestic cats, and some inherited variants are available for genetic testing. A variant of the Alstrom syndrome protein 1 gene (ALMS1) was recently reported to be associated with HCM in the Sphynx cat breed (A3: g.92439157G>C). Genetic screening of the variant, promoted by the Osservatorio Veterinario Italiano Cardiopatie and Genefast Laboratory, was offered to Sphynx cat owners and breeders in Italy. Genotype data were initially obtained by Sanger sequencing. In one case where the samples of a trio were available, inconsistency in the vertical transmission of the variant suggested an allele dropout (ADO) of the wt allele. A new external primer pair was designed as an alternative to the original. The larger PCR product obtained was sanger sequenced, and five novel single nucleotide variants (SNVs) not yet annotated in open-access databases were detected. Three of these SNVs were within the original primer-binding regions and were assumed to have caused ADO. The haplotype, including the ADO SNVs, was detected in two cats belonging to different lineages. To accurately genotype ALMS1 g.92439157G>C in the samples, we set up a real-time TaqMan MGB assay while avoiding all surrounding SNVs. At g.92439157G>C, for 136 Sphynx cats, g.92439157 C variant was highly widespread (freq. >0.50). The present study reports five new variants surrounding ALMS1 g.92439157G>C that must be considered when designing the test. The study also indicates the need to verify the correspondence between the g.92439157 C variant frequency and the prevalence of HCM by increasing clinical visits and follow-ups and finally to promote genetic counselling for accurate management of mating plans in Italian Sphynx cats.

MEMOR: A database of archeological human remains collections from Flanders, Belgium.

The aim of this article is to describe a newly created open access database of archeological human remains collections from Flanders, Belgium. The MEMOR database (www.memor.be) was created to provide an overview of the current practices of loans, reburial, and the research potential of human skeletons from archeological sites currently stored in Flanders. In addition, the project aimed to provide a legal and ethical framework for the handling of human remains and was created around stakeholder involvement from anthropologists, geneticists, contract archeologists, the local, regional and national government agencies, local and national government, universities, and representatives of the major religions. The project has resulted in the creation of a rich database with many collections available for study. The database was created using the open-source Arches data management platform that is freely available for organizations worldwide to configure in accordance with their individual needs and without restrictions on its use. Each collection is linked to information about the excavation and the site the remains originate from, its size and time period. In addition, a research potential tab reveals whether any analyses were performed, and whether excavation notes are available with the assemblage. The database currently contains 742 collections, ranging in size from 1 to over 1000 individuals. New collections will continue to be added when new assemblages are excavated and studied. The database can also be expanded to include human remains collections from other regions and other material categories, such as archaeozoological collections.

Deep Comparisons of Neural Networks from the EEGNet Family

A preponderance of brain–computer interface (BCI) publications proposing artificial neural networks for motor imagery (MI) electroencephalography (EEG) signal classification utilize one of the BCI Competition datasets. However, these databases encompass MI EEG data from a limited number of subjects, typically less than or equal to 10. Furthermore, the algorithms usually include only bandpass filtering as a means of reducing noise and increasing signal quality. In this study, we conducted a comparative analysis of five renowned neural networks (Shallow ConvNet, Deep ConvNet, EEGNet, EEGNet Fusion, and MI-EEGNet) utilizing open-access databases with a larger subject pool in conjunction with the BCI Competition IV 2a dataset to obtain statistically significant results. We employed the FASTER algorithm to eliminate artifacts from the EEG as a signal processing step and explored the potential for transfer learning to enhance classification results on artifact-filtered data. Our objective was to rank the neural networks; hence, in addition to classification accuracy, we introduced two supplementary metrics: accuracy improvement from chance level and the effect of transfer learning. The former is applicable to databases with varying numbers of classes, while the latter can underscore neural networks with robust generalization capabilities. Our metrics indicated that researchers should not disregard Shallow ConvNet and Deep ConvNet as they can outperform later published members of the EEGNet family.

Global Pattern of Epizootic Ulcerative Syndrome Outbreaks in Freshwater Farmed and Wild Fish from 2005 to 2012

Epizootic ulcerative syndrome (EUS) is an infectious disease of freshwater farmed and wild fish caused by a fungus, Aphanomyces invadans. This disease is an important economic disease causing huge socio-economic losses to fish farmers across the world. While this is an important fish disease, its global epidemiology is poorly understood. The objective of this study is understand the global spatiotemporal epidemiology of EUS outbreaks from 2005 to 2022. The data were retrieved from open access database of the World Organization for Animal Health (WOAH). Results showed that there were a total of 277 outbreaks of EUS reported to WOAH from 2005 to 2022 from 15 countries and territories with 76% outbreaks reported from African countries. Democratic Republic of Congo reported the highest number of EUS outbreaks. Higher number of outbreaks were reported during 2014 to 2017. The observed epidemiological pattern might be biased due to the underreporting of the disease. Nevertheless, it offers important insights to understand the latest global pattern of EUS. We suggest to increase country level awareness on EUS so that outbreaks are reported in a timely manner.

Adverse sequelae of the COVID -19 pandemic on mental health services in Chile.

This study seeks to describe the adverse effects of the COVID-19 pandemic on mental health services in Chile. This study is part of ongoing multicountry research known as the Mental Health Care - Adverse Sequelae of COVID-19 study (or the MASC study) that includes seven countries. Chile is the only one in Latin America. This study used a convergent mixed methods design. The quantitative component analyzed data about public mental health care collected between January 2019 and December 2021 from the open-access database at the Ministry of Health. The qualitative component analyzed data collected from focus groups of experts that included professionals in charge of mental health services, policy-makers, service users and caregivers. Finally, the data synthesis was performed by triangulation of both components. By April 2020, mental health service provision had been reduced by 88% in primary care; moreover, secondary and tertiary levels had also reduced their mental health activities by, respectively, 66.3% and 71.3% of pre-COVID levels. Negative sequelae were described at the health systems level, and full recovery had not been achieved by the end of 2021. The pandemic affected the essential characteristics of community-based mental health services, with adverse impacts on the continuity and quality of care, reduced psychosocial and community support, and negative effects on health workers' mental health. Digital solutions were widely implemented to enable remote care, but challenges included the availability of equipment, its quality and the digital divide. The COVID-19 pandemic has had significant and enduring adverse effects on mental health care. Lessons learned can inform recommendations for good practices for the ongoing and future pandemics and health crises, and highlight the importance of prioritizing the strengthening of mental health services in response to emergencies.

A challenge to self-education: The purpose and potential of a database annotating works of art for adults who are existential exemplars for children

ABSTRACT How can an open access database annotating pictures, films, music and texts support adults as existential exemplars? This article explores the opportunities of a Norwegian database called the OE-database. Its target group is all adults who want to become better exemplars for children through encounters with art and conversations in small groups. Educational sources contain many annotations of art and literature for the education of children and youth, but material for adults’ self-education, published in databases and thus easily accessible for all, are lacking. The article invites readers to a critical conversation on the purpose and potential of the OE-database and to create similar databases in other languages. The narratives that provide the foundation of the OE-database are influenced by Aristotle, Thomas Aquinas and Søren Kierkegaard. The article highlights Kierkegaard’s concept ‘upbuilding’ (edification) and three stages in a process that encourage adults to let themselves be ‘built up’ as exemplars.

PEMETAAN STRATEGI PEMASARAN PERPUSTAKAAN DI GOOGLE SCHOLAR MELALUI PUBLISH OF PERISH

A large body of research on library marketing, published in open access journals and included in open access databases such as Google Scholar, needs to be evaluated. Bibliographic analysis becomes a parameter for evaluating research results to determine the relationship between science and technology, map a particular scientific field, and monitor the development of new knowledge in a particular scientific field. The purpose of this study is to map the evolution of library marketing research indexed in Google Scholar, analyze topics related to library marketing, and identify researchers who have worked on those topics. In this research, a qualitative method based on the theme analysis approach is adopted as a data analysis method. This study uses the Publish or Perish (PoP) application to collect research data obtained from studies indexed by the keyword "library marketing" in Google Scholar. This sample was determined by screening publications in the form of journal articles published between 2018 and 2023. Study data were analyzed using the VOSviewer application. The relationship between library marketing and strategy is illustrated by the keyword mapping results in the article titled "Library Marketing Mix Strategy for the Digital Age." It was also noted that a library marketing study was conducted by 20 researchers from 2019 to 2023.

MOSAIC - A Unified Trait Database to Complement Structured Population Models

Despite exponential growth in ecological data availability, broader interoperability amongst datasets is needed to unlock the potential of open access. Our understanding of the interface of demography and functional traits is well-positioned to benefit from such interoperability. Here, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data were digitised and curated through a combination of existing datasets and new trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC includes species-level phylogenies for 1,359 species and population-specific climate data. We identify how database integration can improve our understanding of traits well-quantified in existing repositories and those that are poorly quantified (e.g., growth determination, modularity). MOSAIC highlights emerging challenges associated with standardising databases and demographic measures.

Use of Periodicals among Libraryand Information SciencePostgraduate Students in UniversityLibraries in Nigeria

Rationale of Study – This paper investigated the use of periodicals among Libraryand Information Science (LIS) postgraduate students in university libraries inNigeria. The objectives were to explore the activities performed (use ofperiodicals) by postgraduate students in university libraries, ascertain the purposesof using periodicals, and determine the frequency at which postgraduate studentsuse periodicals.Methodology – The data for the study was gathered through a two-pagequestionnaire administered to 404 respondents who were accessible in the libraryand LIS departments. Three hundred eighty-eight (388) questionnaires wereretrieved, representing a 96% return rate. The data were analysed statistically.Findings – The survey results showed that searching for particular information,downloading from open-access databases, locating multiple sources fromperiodicals, and reading in the library are the activities performed by postgraduatestudents while using periodicals.Implications – The findings of this study may be used by the universitymanagement and librarians to develop policies that will improve the subscriptionof searchable databases that encourage the usage of periodicals and otherinformation resources among students within and outside the university libraries.Originality – Though other studies have dealt with library usage, little, or no study,has been conducted on the activities (interaction) performed by users. This paperis the outcome of original research that has not been submitted elsewhere forpublication.

Multidimensional immune profiling in Gastric Cancer Multiplex Immunohistochemistry Atlas from Peking University Cancer Hospital project informs PD-1/PD-L1 blockade efficacy

BackgroundImmunotherapy has resulted in impressive objective response rates and durable tumour remission, but only in a subset of gastric cancer (GC) patients. The PD-L1 combined positive score is the most widely used tissue-based biomarker for anti-PD-1/PD-L1 therapy; however, this unidimensional method has limitations. Next-generation exploration of tissue-based biomarkers for GC requires characterisation of various cellular markers and key immunoregulatory molecule expression in situ. Thus, a complete, stepwise solution covering the entire process from staining samples to cross-site utilisation of pathomics data is urgently needed. MethodsWith the advanced multispectral imaging analysis method, web-based data repository, and interactive sharing technology, we conducted a project entitled Gastric Cancer Multiplex Immunohistochemistry Atlas from Peking University Cancer Hospital (GMAP). We propose a standard pipeline covering sample collection, staining, scanning multispectral images, constructing a spectral library, identifying and phenotyping cells, positioning each element, and quantitatively extracting immune features. We designed an open-access relational database to explore tissue-based biomarkers to determine PD-1/PD-L1 blockade efficacy. ResultsThe GMAP project detected the functional status and spatial location of more than 50 million cells using 15 markers in 80 GC patients, based on which billions of cell pairs were recognised, highlighting the rich spatial arrangement information and the fine tumour microenvironment structure. We generated a tumour-immune atlas using the count and spatial features of 65 immune cell types. We eventually selected the indicators and built a comprehensive risk-scoring system. Patients with higher risk score showed superior immunotherapy-related progression-free survival (irPFS) (hazard ratio [HR]: 3.19; P < 0.001; median irPFS: 4.87 versus 19.87months, respectively) and immunotherapy-related overall survival (HR: 3.10; P = 0.001; median irPFS: 10.03 versus 24.87months, respectively) compared with lower risk patients, demonstrating their potential for guiding anti-PD-1/PD-L1-based immunotherapy. Importantly, an easy-to-use and versatile web server was built to promote tissue-based biomarker exploration in GC. ConclusionThe GMAP project highlighted the clinical value of tissue-based immune features as biomarkers for immunotherapeutic decision-making. We present a well-designed, detailed workflow for the orderly generation and use of a high-quality, spatially resolved pathological database.

A U-shaped protection of altitude against mortality and infection of COVID-19 in Peru: an ecological study

BackgroundThe COVID-19 pandemic has affected the world in multiple ways and has been a challenge for the health systems of each country. From the beginning, risk factors for the severity and mortality of the disease were considered, as the spread of the virus was related to the living conditions of each population.MethodsIn this ecological study we have evaluated the role of geography, precisely the altitude above sea level in the incidence and mortality of COVID-19 in Peru. Incidence and mortality data were taken from the open-access database of the government of Peru until March 2021. COVID-19 cases and COVID-19 mortality were treated as cases/density population and 1000 x cases/inhabitants while altitude was treated as continuous and as a categorical variable divided in 7 categories. The relationship between COVID-19 cases or deaths for COVID-19 and altitude as continuous variable was determined using Spearman correlation test. Meanwhile when altitude was considered as a categorical variable, Poisson regression or negative binomial analyses were applied.ResultsA significant inverse correlation was found between COVID-19 cases by population density and altitude (r=-0.37 p < 0.001). By altitude categories, the lowest risk for infection was observed between 3,000 and 3,500 m (IRR 0.08; 95% CI 0.05,0.12). Moreover, we found an inverse correlation between altitude and COVID-19 mortality (r=-0.39 p < 0.001). Also, the lowest risk for mortality was observed between 3,000 and 3,500 m (IRR 0.12; 95%CI 0.08; 0.18). Similar results were found when analyses were adjusted for inhabitants and stratified by sex.ConclusionThis study reports an inverse relationship between COVID-19 incidence and mortality with respect to the altitude of residence, particularly, a u-shaped protection is shown, with a highest benefit between 3000 and 3500 m. The possibility of using hypoxia as an alternative treatment requires more complex studies that should allow knowing the physiological and environmental mechanisms of the protective role.

Global Stress Detection Framework Combining a Reduced Set of HRV Features and Random Forest Model.

Approximately 65% of the worldwide adult population has experienced stress, affecting their daily routine at least once in the past year. Stress becomes harmful when it occurs for too long or is continuous (i.e., chronic), interfering with our performance, attention, and concentration. Chronic high stress contributes to major health issues such as heart disease, high blood pressure, diabetes, depression, and anxiety. Several researchers have focused on detecting stress through combining many features with machine/deep learning models. Despite these efforts, our community has not agreed on the number of features to identify stress conditions using wearable devices. In addition, most of the reported studies have been focused on person-specific training and testing. Thanks to our community's broad acceptance of wearable wristband devices, this work investigates a global stress detection model combining eight HRV features with a random forest (RF) algorithm. Whereas the model's performance is evaluated for each individual, the training of the RF model contains instances of all subjects (i.e., global training). We have validated the proposed global stress model using two open-access databases (the WESAD and SWELL databases) and their combination. The eight HRV features with the highest classifying power are selected using the minimum redundancy maximum relevance (mRMR) method, reducing the training time of the global stress platform. The proposed global stress monitoring model identifies person-specific stress events with an accuracy higher than 99% after a global training framework. Future work should be focused on testing this global stress monitoring framework in real-world applications.

The causal effects of age at menarche, age at first live birth, and estradiol levels on systemic lupus erythematosus: A two-sample Mendelian randomization analysis.

To determine whether age at menarche (AAM), age at first live birth (AFB), and estradiol levels are causally correlated with the development of systemic lupus erythematosus (SLE). A two-sample Mendelian randomization (MR) analysis was performed after data was collected from a dataset of genome-wide association studies (GWASs) related to SLE (as outcome), and from open access databases to find statistics related to AAM, AFB, and estradiol levels (as exposure). In our study, a negative causal correlation between AAM and SLE was confirmed by MR analysis (MR egger: beta = 0.116, SE = 0.948, p = 0.909; weighted median: beta = -0.416, SE = 0.192, p = 0.030; and IVW: beta = -0.395, SE = 0.165, p = 0.016). However, there were no genetic causal effects of AFB and the estradiol levels on SLE, based on the results of MR analysis as follows: AFB (MR egger: beta = - 2.815, SE = 1.469, p = 0.065; Weighted median: beta = 0.334, SE = 0.378, p = 0.377; and IVW: beta = 0.188, SE = 0.282, p = 0.505) and the estradiol levels (MR egger: beta = 0.139, SE = 0.294, p = 0.651; weighted median: beta = 0.063, SE = 0.108, p = 0.559; IVW: beta = 0.126, SE = 0.097, p = 0.192). Our findings revealed that AAM may be associated with increased risk of the development of SLE, while there were no such causal effects from AFB and estradiol levels.

Reproducibility in computational sleep research: a call for action.

Reproducibility is fundamental for scientific research, as scientific findings can be regarded as such only if they can be reproduced, i.e. if the same findings can be obtained again. While not consistently defined by the scientific community [1], researchers grappling with defining standards for reproducibility suggested a few definitions. For example, Kulkarni et al. [2], suggested that the availability of all used data and a clear description of the computational analysis workflow together constitute a reproducible study. Others have argued that while it may appear that reproducibility should be guaranteed when methods are written in code, a lack of sharing source code is limiting those opportunities to reproduce results [3]. Fields such as bioinformatics have raised awareness towards the “reproducibility crises,” showing that many published results cannot be reproduced [4, 5]. Researchers pointed out specific barriers for reproducibility such as available code not running properly [6], and suggested standards to follow to increase reproducibility [2], including the inclusion of data and code availability statements in published manuscripts, and the use of open-access databases to deposit data and code.

Factor Analysis Affecting English Speaking Proficiency Based Open Access Articles on ScienceDirect Database

This study explores the factors affecting the ability to speak English. The method used in this study is the systematic review with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) model. This study used the ScienceDirect database. The article search process uses the process of identification, screening, eligibility, and inclusion. First, the identification was used with the keyword “English-speaking” as the filter, then it was continued by the latest 5-years of article publication. The screening process is performed with open access and archive criteria, while the eligibility process is performed with research objectives conformity. The inclusion is the final stage for the article chosen based on the research focus. This study revealed that the factors affecting the ability to speak English are; gender, native-speaker teachers, self-efficacy, peers, culture, motivation, and English as a lingua franca. The weakness of this study is that the data was taken from articles based on ScienceDirect and open-access databases only. Therefore, other researchers are suggested to conduct systematic reviews using multi-databases such as Web of Science, Emerald, Wiley, and Sage.