Electronic Repositories Research Articles

Regional Prevalence of Hemoglobin C Across Saudi Arabia: An Epidemiological Survey

IntroductionHbC is a common structural hemoglobinopathy especially in West Africa. Prevalence and regional distribution of HbC in Saudi Arabia are widely undocumented. Patients with homozygous HbC disease may have mild hemolytic anemia whereas combination with hemoglobin S (HbS) leads to a clinically severe phenotype.AimThe current epidemiological study, considered the largest from Saudi Arabia, aimed to evaluate the regional prevalence of the HbC variant among the couples participating in the premarital screening program from 2011 to 2018.MethodsData from the PMSGC program were obtained for premarital screening and genetic counseling. The collected data were then entered into the SEHA platform, a centralized electronic repository for the 13 designated regions in Saudi Arabia. Hemoglobin electrophoresis samples are analyzed using either HPLC, capillary electrophoresis, or a combination of both methods to confirm the presence of abnormal hemoglobin bands.ResultsThis study included 1,871,184 individuals from 2011 to 2018. Of those, 49.8% were males and 50.2% were females. 112,618 (6.0%) had an abnormal test. Total number of Hb C cases were 778 (0.04%). HbC trait (HbAC) was detected in 764 participants while homozygous HbC (HbCC) and combined heterozygous (HbSC) were found in 9 and 5 cases, respectively. The regions near the Red Sea have higher rates than the central and eastern regions.ConclusionHbC is a rare variant in Saudi Arabia with varying regional frequencies. HbC variant is more common in Mecca and Madina regions. The geographic area of HbC distribution differs from the areas with high prevalence of HbS, which explains why HbSC disease cases are overwhelmingly rare.

Comparison of ticagrelor and clopidogrel in anemic patients with acute coronary syndrome: efficacy and safety outcomes over one year.

This retrospective study aimed to investigate the potential impact of ticagrelor and clopidogrel treatment on cardiovascular outcomes in patients with anemia and acute coronary syndrome (ACS) and to provide insights into the optimal therapeutic approach for this vulnerable patient population. A retrospective research design was employed, involving patients diagnosed with ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) between 2014 and 2021. Inclusion criteria required a hemoglobin level below 12mg/dL and a minimum 12-month P2Y12 inhibitor treatment. Comprehensive clinical, biochemical, and echocardiographic data were collected from the hospital's electronic repository. The primary efficacy endpoint was major adverse cardiovascular events (MACE), encompassing total mortality, cardiovascular mortality, reinfarction, ischemic stroke, and hemorrhagic stroke. Major hemorrhage was the primary safety endpoint. Secondary outcomes included total mortality, cardiovascular mortality, reinfarction, ischemic stroke, and hemorrhagic stroke, individually. Patients treated with ticagrelor (n = 118) and clopidogrel (n = 538) were compared. No significant difference was observed in major adverse cardiovascular events (MACE) and major bleeding between ticagrelor and clopidogrel treatment groups (MACE: clopidogrel 10.0% vs. ticagrelor 11.0%, p = 0.75; major bleeding: clopidogrel 2.8%, ticagrelor 2.5%, p = 0.88). Patients with hemoglobin levels ≤ 8mg/dL demonstrated significantly higher MACE and major bleeding rates in the ticagrelor group (p = 0.008 and p = 0.002, respectively). Among patients aged ≥ 75 years, ticagrelor treatment was associated with a higher risk of major bleeding (p = 0.04). Ticagrelor and clopidogrel exhibited comparable efficacy and safety outcomes in anemic ACS patients over a one-year period. Although ticagrelor demonstrated superiority in reducing ischemic events, it is crucial to recognize the limitations of retrospective studies in informing clinical practice. This study offers valuable insights into tailoring antiplatelet therapy for anemic ACS patients and provides guidance for personalized treatment strategies, acknowledging the hypothesis-generating nature of retrospective analyses.

Using a Natural Language Processing Approach to Support Rapid Knowledge Acquisition.

Implementing artificial intelligence to extract insights from large, real-world clinical data sets can supplement and enhance knowledge management efforts for health sciences research and clinical care. At Vanderbilt University Medical Center (VUMC), the in-house developed Word Cloud natural language processing system extracts coded concepts from patient records in VUMC's electronic health record repository using the Unified Medical Language System terminology. Through this process, the Word Cloud extracts the most prominent concepts found in the clinical documentation of a specific patient or population. The Word Cloud provides added value for clinical care decision-making and research. This viewpoint paper describes a use case for how the VUMC Center for Knowledge Management leverages the condition-disease associations represented by the Word Cloud to aid in the knowledge generation needed to inform the interpretation of phenome-wide association studies.

Electronic aggregated data collection on cervical cancer screening in Bangladesh since 2014: what the data tells us?

IntroductionTo reduce the high prevalence of cervical cancers among the Bangladeshi women, the Government of Bangladesh established a national cervical cancer screening programme in 2005 for women aged 30 to 60 years. The District Health Information System Version 2 (DHIS2) based electronic aggregated data collection system is used since the year 2013. This study summarises data from the year 2014 to 2022 to assess the effectiveness of the electronic data collection system in understanding the outcome of the screening programme.MethodsThis is a descriptive study based on secondary data extracted in MS Excel from the DHIS2-based electronic repository of the national cervical cancer screening programme of Bangladesh. The respondents were women aged 30–60 years, screened for cervical cancer using VIA (Visual Inspection of cervix with Acetic acid) method in 465 government health facilities. The data were collected on the participants’ residential location, month and year of screening, name and type of health facilities performing VIA, and VIA screening results.ResultsThe national screening programme reported a total 3.36 million VIA tests from 465 government hospitals in 8 years (2014 to 2022). The national average VIA-positivity rate was 3.6%, which varied from 1.4 to 9.5% among the districts. This national screening programme witnessed an exponential growth, year after year, with 83.3% increase in VIA test from 2014 to 2022. The primary and the secondary care hospitals were the highest collective contributors of VIA tests (86.2%) and positive cases (77.8%). The VIA-positivity rates in different hospital types varied widely, 7.0% in the medical university hospital, 5.7% in the medical college hospitals, 3.9% in the district/general hospitals, and 3.0% in the upazila health complexes.ConclusionsA national cervical cancer screening programme using VIA method and a DHIS2-based electronic data collection backbone, is effective, sustainable, and useful to understand the screening coverage, VIA positivity rate and geographic distribution of the participants and case load to initiate policy recommendations and actions. Decentralization of the screening programme and more efforts at the primary and secondary care level is required to increase screening performances.

Antimicrobial resistance in food-associated Escherichia coli in Mexico and Latin America.

The World Health Organization (WHO) considers antimicrobial resistance to be one of the critical global public health priorities to address. Escherichia coli is a commensal bacterium of the gut microbiota in humans and animals; however, some strains cause infections and are resistant to antibiotics. One of the most common ways of acquiring pathogenic E. coli strains is through food. This review analyzes multidrug-resistant E. coli isolated from food, emphasizing Latin America and Mexico, and the mobile genetic elements (MGEs) responsible for spreading antibiotic resistance determinants among bacteria in different environments and hosts. We conducted a systematic search of the literature published from 2015 to 2022 in open access databases and electronic repositories. The prevalence of 11 E. coli pathotypes was described, with diarrheagenic E. coli pathotypes being the most frequently associated with foodborne illness in different Latin American countries, highlighting the presence of different antibiotic resistance genes mostly carried by IncF-type plasmids or class 1 integrons. Although the global incidence of foodborne illness is high, there have been few studies in Mexico and Latin America, which highlights the need to generate updated epidemiological data from the "One Health" approach, which allows monitoring of the multidrug-resistance phenomenon in E. coli from a common perspective in the interaction of human, veterinary, and environmental health.

An Intelligent Healthcare System for Automated Diabetes Diagnosis and Prediction using Machine Learning

The progression of biotechnological and health science fields has instigated a substantial proliferation of data, encompassing high-throughput genetic information and extensive clinical data derived from expansive electronic health record repositories. In the domain of biosciences, the indispensability of machine learning and data mining methodologies has surged, attaining heightened significance for the purpose of converting extant information into usable knowledge. Diabetes mellitus is a metabolic condition that affects human health. Extensive research on diabetes (diagnosis, therapy, etc.) has generated vast volumes of data. Manual diagnosis of diabetes has always been a time-consuming task. Therefore, automatic detection and diagnosis of diabetes using artificial intelligence and machine learning is gaining prominence. In our work, we have devised a novel architecture using machine learning for the automatic diagnosis of diabetes. We implemented our model using many algorithms and found that random forest is the most optimized and accurate one for classification purposes. It produced the highest accuracy of 98.07%, precision, recall, F1-score of 98%, and logarithmic loss of 0.03 using the mRMR feature selection method and 0.2 test split. It produced a recall of 97%, the precision of 97%, an F1-score of 97%, an accuracy of 96.79%, and a log loss of 0.11 on 0.3 test split with mRMR feature selection. Also, the proposed model has performed better than most state-of-the-art models.

Leveraging oncology collaborative networks and biomedical informatics data resources to rapidly recruit and enroll rural residents into oncology quality of life clinical trials.

This study assesses the feasibility of biomedical informatics resources for efficient recruitment of rural residents with cancer to a clinical trial of a quality-of-life (QOL) mobile app. These resources have the potential to reduce costly, time-consuming, in-person recruitment methods. A cohort was identified from the electronic health record data repository and cross-referenced with patients who consented to additional research contact. Rural-urban commuting area codes were computed to identify rurality. Potential participants were emailed study details, screening questions, and an e-consent link via REDCap. Consented individuals received baseline questionnaires automatically. A sample minimum of n = 80 [n = 40 care as usual (CAU) n = 40 mobile app intervention] was needed. N = 1298 potential participants (n = 365 CAU; n = 833 intervention) were screened for eligibility. For CAU, 68 consented, 67 completed baseline questionnaires, and 54 completed follow-up questionnaires. For intervention, 100 consented, 97 completed baseline questionnaires, and 58 completed follow-up questionnaires. The CAU/intervention reached 82.5%/122.5% of the enrollment target within 2 days. Recruitment and retention rates were 15.3% and 57.5%, respectively. The mean age was 59.5 ± 13.5 years. The sample was 65% women, 20% racial/ethnic minority, and 35% resided in rural areas. These results demonstrate that biomedical informatics resources can be highly effective in recruiting for cancer QOL research. Precisely identifying individuals likely to meet inclusion criteria who previously indicated interest in research participation expedited recruitment. Participants completed the consent and baseline questionnaires with zero follow-up contacts from the research team. This low-touch, repeatable process may be highly effective for multisite clinical trials research seeking to include rural residents.

Transtornos mentais comuns em pacientes transplantados com células-tronco hematopoéticas: revisão de escopo

ABSTRACT Objective: to map common recurrent mental disorders in patients undergoing hematopoietic stem cell transplantation. Methods: this is a scoping review carried out in January 2022 in electronic databases and repositories of dissertations and thesis. Studies that answered the research question, met the objective of the study and were available in full electronically, in any language, were included. Results: the sample consisted of 28 studies, 14 of which were published in the United States of America. The common mental disorders found were depressive, anxiety, post-traumatic stress and mood disorders. Twenty symptoms were mentioned, among the most prevalent are fatigue and sleep disorders/insomnia. Conclusions: the difficulty and importance of carrying out the differential diagnosis of these disorders were highlighted, since their symptoms can be confused with other health problems and have a strong potential to interfere with patients’ evolution.

Product development strategy of non-heritage cultural and creative products under the fusion of traditional crafts and modern technology

Abstract In the contemporary digital era, the transformation of intangible cultural heritage (ICH) products represents a critical trend in their evolutionary trajectory. This study advocates for the synergistic integration of traditional craftsmanship with advanced technologies within the ICH sector. A standardized electronic image repository was established by scanning these items under uniform lighting conditions, forming the basis for generating non-heritage experimental datasets. Subsequently, a clustering algorithm was applied to extract color features from the images. Owing to its resilience against rotation, scale, and noise variations, the Scale-Invariant Feature Transform (SIFT) algorithm was utilized to delineate pattern features of non-heritage items. The analysis primarily focused on the predominant colors in contemporary ICH products, paving the way for innovative developments that incorporate augmented reality (AR) technology with non-heritage characteristics. Quantitative analyses indicated that the average hue of these products is 118.15°, predominantly within the warmer green spectrum of the color wheel. Moreover, the evaluation of pattern style similarity of non-heritage items, as determined by the SIFT algorithm, yielded an average of 88.36%. Further, regression analysis demonstrated a significant influence of hue, brightness, pattern, and texture on the effectiveness of product development, with regression coefficients of 0.276, 0.236, 0.237, and 0.159, respectively, at a significance level of P<0.001. This research highlights the potential of contemporary science and technology to invigorate traditional arts, thereby contributing significantly to the preservation and revitalization of valued cultural legacies.

Integrated health information system in the Republic of Serbia

The Republic of Serbia's integrated health information system (IHIS) serves as a central electronic repository for storing and processing various medical and health-related data. It encompasses patient records, institutional information, details of health interventions and services, electronic prescriptions, appointment scheduling for specialist consultations, diagnostic procedures, and surgical operations. The implementation of this system promises several benefits, including improved access to patient information, expedited diagnostics, enhanced medication selection processes, heightened patient safety measures, more comprehensive health-statistical reporting, and accelerated dissemination of biomedical knowledge. This paper aims to explore the advantages of employing information technologies in healthcare delivery within health institutions, contrasting it with traditional methods of data collection, analysis, and interpretation, specifically focusing on primary healthcare institutions. Drawing upon current professional and societal perspectives, the paper discusses the conceptual framework and objectives of IHIS, emphasizing the significance of leveraging information technologies in healthcare.

Comparison of efficiency and safety of open surgery, hybrid surgery and endovascular repair for the treatment of thoracoabdominal aneurysms: a systemic review and network meta-analysis.

The objective of this study was to perform a network meta-analysis (NMA) to assess the efficacy and safety of three different surgical interventions- open surgical repair (OSR), hybrid surgical repair (HSR), and endovascular repair (EVAR)- for the treatment of thoracoabdominal aortic aneurysms (TAAAs). Electronic repositories like PubMed, Embase, Web of Science, Scopus, ScienceDirect, the Cochrane library, Clinical trial, and China National Knowledge Infrastructure (CNKI) were systematically searched to identify studies that compared the efficacy of OSR, HSR, and EVAR with endografts for the treatment of TAAAs until December 24th, 2022. Random-effects and fixed-effects models were employed to analyze the data gathered in a network meta-analysis. The study's primary outcomes of interest encompassed in-hospital mortality, long-term survival rate, and postoperative complications. Eleven comparative studies meet inclusion criterias. There were 2,222 patients in OSR, 1,574 patients in EVAR and 537 patients in HSR. EVAR has lower one-month mortality than OSR (RR: 0.31; 95% CI: 0.17-0.70) and HSR (RR: 0.37; 95% CI: 0.22-0.71), and lower incident rate of renal complications than HSR (RR: 0.20; 95% CI: 0.08-0.43) and OSR (RR: 0.34; 95% CI: 0.16-0.65). Nonetheless, there was no noteworthy discrepancy identified in the long-term survival rates of these procedures. As compared with OSR, HSR, and EVAR, EVER has lower one-month mortality, and lower incident rates of complications. PROSPERO (CRD42022313829).

Palliative care in the treatment of women with breast cancer: A scoping review.

Recent studies on the quality of life in women with breast cancer show a high prevalence of signs and symptoms that should be the focus of palliative care (PC), leading us to question the current role they play in addressing breast cancer. Therefore, the objective of this review is to map the scope of available literature on the role of PC in the treatment of women with breast cancer. This is a methodologically guided scoping review by the Joanna Briggs Institute and adapted to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist for report writing. Systematic searches were conducted in 8 databases, an electronic repository, and gray literature. The searches were conducted with the support of a librarian. The study selection was managed through the RAYYAN software in a blind and independent manner by 2 reviewers. The extracted data were analyzed using the qualitative thematic analysis technique and discussed through textual categories. A total of 9,812 studies were identified, of which only 136 articles and 3 sources of gray literature are included in this review. In terms of general characteristics, the majority were published in the USA (35.7%), had a cross-sectional design (44.8%), and were abstracts presented at scientific events (19.6%). The majority of interventions focused on palliative radiotherapy (13.6%). Thematic analysis identified 14 themes and 12 subthemes. Our findings offer a comprehensive view of the evidence on PC in the treatment of breast cancer. Although a methodological quality assessment was not conducted, these results could guide professionals interested in the topic to position themselves in the current context. Additionally, a quick synthesis of recommendations on different palliative therapies is provided, which should be critically observed. Finally, multiple knowledge gaps are highlighted, which could be used for the development of future studies in this field.

Dropout rate and associated factors of community-based health insurance beneficiaries in Ethiopia: a systematic review and meta-analysis

BackgroundEthiopia aims to achieve universal healthcare using health insurance. To do so, it has been implementing community-based health insurance since 2011. However, the retention of members by the scheme has not yet been evaluated nationally. The systematic review and meta-analysis aimed to evaluate the dropout rate and associated factors among the scheme’s beneficiaries in Ethiopia.MethodsOn December 19, 2022, searches were conducted in Scopus, Hinari, PubMed, Semantic Scholar, and Google Scholar. Searches were also conducted on the general web and electronic repositories, including the Ethiopian Health Insurance Service, the International Institute for Primary Health Care-Ethiopia, and various higher education institutions. The Joanna Briggs Institute’s tools and the “preferred reporting items for systematic reviews and meta-analyses 2020 statement” were used to evaluate bias and frame the review, respectively. Data were analyzed using Stata 17 and RevMan 5. To assess heterogeneity, we conducted subgroup analysis and used a random model to calculate odds ratios with a p value less than 0.05 and a 95% CI.ResultsIn total, 14 articles were included in the qualitative synthesis, of which 12 were selected for the quantitative analysis. The pooled estimate revealed that the dropout rate of beneficiaries from the scheme was 34.0% (95% CI: 23-44%), provided that the renewal rate was 66.0%, and was found to be influenced by socio-demographic, health status, length of enrolment, knowledge, attitude, the scheme, and health service-related variables. The southern and Oromia regions reported the lowest and highest dropout rates, with 27.0% (95% CI: 24-29%) and 48.0% (95% CI: 18-78%), respectively. The dropout rates increased from 12.3% in 2012–2015 to 34.4% in 2020–2021.ConclusionMore than one-third of the scheme’s beneficiaries were found to have dropped out, and this has been found to increase over time, dictating that a community-based strategy and intervention, from the supply, insurer, and demand sides, seem indispensable in minimizing this huge dropout rate.

1269. Prospective Evaluation of a Machine Learning Model that Guides Indication for Antibiotics in Lower Respiratory Tract Infections

Abstract Background Over-prescribing of antibiotics for suspected acute bacterial lower respiratory tract infections (abLRTI) is prevalent. A classification model that can identify instances when antibiotics should be initiated or withheld was previously developed with promising results (80% accuracy). This, however, was based on a retrospective dataset. We conducted a prospective evaluation of this model in the hospital antimicrobial stewardship unit (ASU) to validate its performance and compare its effectiveness against current ASU strategies. Methods Inpatients audited by the hospital ASU between 10 January and 23 March 2023 (twice weekly) were enrolled into this study. Relevant patient information (e.g., clinical notes, radiology reports, vital signs) was extracted from our hospital’s electronic data repository for model inference. The presence of abLRTI as determined by the model, the patient’s primary care team and ASU review were compared. Cases that saw differing opinions between any of the three operators were subsequently reviewed by an independent Infectious Diseases physician, who provided the ground truth for that case. Results A total of 851 cases were included, of which 235 (27.6%) had true abLRTI. The model was most accurate in determining the presence versus absence of abLRTI (734/851, 86.3%), while ASU review and primary care team were correct in only 698 (82.0%) and 677 (79.6%) cases respectively. Primary care team demonstrated greatest sensitivity in the suspicion for abLRTI (91.9%); unfortunately, it also over-diagnosed abLRTI in 155 (42%) patients. Among these false-positive cases, the model rightly rejected presence of abLRTI in 126 (81.3%) patients whereas only 66 (64.1%) of them were identified by ASU. ASU outperformed the model in having a lower false-negative rate when abLRTI is suspected (17.3% vs. 22.0%). Conclusion The model displayed consistent performance in a prospective cohort. Findings support its value in guiding decisions on antibiotic initiation for suspected abLRTI. Deploying this model to augment current ASU capabilities should be strongly considered. Disclosures All Authors: No reported disclosures

Relationship between neutrophil to lymphocyte ratio and diabetic peripheral neuropathy: a systematic review and meta-analysis

BackgroundThe present study aims to review the existing scientific literature on the role of neutrophil to lymphocyte ratio (NLR) in diabetic peripheral neuropathy (DPN) to perform a meta-analysis on the available data.MethodsThe electronic repositories Web of Science, PubMed, and Scopus were systematically explored starting from their establishment up until June 9, 2022.ResultsFifteen articles were included in the meta‐analysis after multiple screening according to the PRISMA guidelines. The combined findings indicated that individuals with DPN had higher levels of NLR in comparison to those without DPN (SMD = 0.61; CI 95% = 0.40–0.81, p < 0.001). In the subgroup assessment based on ethnicity, it was observed that diabetic patients with DPN exhibited increased NLR levels in contrast to those without DPN in studies conducted in India (SMD = 1.30; CI 95% = 0.37–2.24, p = 0.006) and East Asia (SMD = 0.53; CI 95% = 0.34–0.73, p < 0.001) but not in studies conducted in Turkey (SMD = 0.30; CI 95% = − 0.06–0.67, p = 0.104) and Egypt (SMD = 0.34; CI 95% = -0.14–0.82, p = 0.165). The pooled sensitivity of NLR was 0.67 (95% CI = 0.49–0.81), and the pooled specificity was 0.70 (95% CI, 0.56–0.81). The pooled positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR) of NLR were 2.30 (95% CI = 1.71–3.09), 0.45 (95%CI = 0.30–0.67), and 5.06 (95% CI = 3.16–8.12), respectively.ConclusionNLR serves as a distinct marker of inflammation, and its rise in cases of DPN suggests an immune system imbalance playing a role in the development of the disease.

Leveraging electronic medical records for HIV testing, care, and treatment programming in Kenya—the national data warehouse project

BackgroundAggregate electronic data repositories and population-level cross-sectional surveys play a critical role in HIV programme monitoring and surveillance for data-driven decision-making. However, these data sources have inherent limitations including inability to respond to public health priorities in real-time and to longitudinally follow up clients for ascertainment of long-term outcomes. Electronic medical records (EMRs) have tremendous potential to bridge these gaps when harnessed into a centralised data repository. We describe the evolution of EMRs and the development of a centralised national data warehouse (NDW) repository. Further, we describe the distribution and representativeness of data from the NDW and explore its potential for population-level surveillance of HIV testing, care and treatment in Kenya.Main bodyHealth information systems in Kenya have evolved from simple paper records to web-based EMRs with features that support data transmission to the NDW. The NDW design includes four layers: data warehouse application programming interface (DWAPI), central staging, integration service, and data visualization application. The number of health facilities uploading individual-level data to the NDW increased from 666 in 2016 to 1,516 in 2020, covering 41 of 47 counties in Kenya. By the end of 2020, the NDW hosted longitudinal data from 1,928,458 individuals ever started on antiretroviral therapy (ART). In 2020, there were 936,869 individuals who were active on ART in the NDW, compared to 1,219,276 individuals on ART reported in the aggregate-level Kenya Health Information System (KHIS), suggesting 77% coverage. The proportional distribution of individuals on ART by counties in the NDW was consistent with that from KHIS, suggesting representativeness and generalizability at the population level.ConclusionThe NDW presents opportunities for individual-level HIV programme monitoring and surveillance because of its longitudinal design and its ability to respond to public health priorities in real-time. A comparison with estimates from KHIS demonstrates that the NDW has high coverage and that the data maybe representative and generalizable at the population-level. The NDW is therefore a unique and complementary resource for HIV programme monitoring and surveillance with potential to strengthen timely data driven decision-making towards HIV epidemic control in Kenya.Database link(https://dwh.nascop.org/).

The role of information communication technologies on African indigenous knowledge systems: Folktales

African Indigenous Knowledge Systems (AIKS) are values that were passed among African generations by word of mouth. Despite the Fourth Industrial Revolution's (4IR) facilitation of rapid communication for every aspect of society, many Africans have not embraced it to store AIKS, mainly due to concerns over biases and prejudices embedded in aspects like information and communication technologies (ICTs). Using decoloniality theory, this paper aims to show the importance of AIKS, which faces extinction due to the combined effects of the deaths of members of the old generation and acculturation. In the methodology section, Afrocentricity, which celebrates rootedness in African culture and history, was used together with storytelling as a means to examine the perceptions of Afrocentric scholars as revealed in their folktale works that were analyzed qualitatively. Results revealed that lack of exposure to ICTs is one of the main reasons for the scant AIKS virtual literature. Many African people do not have access to other needs like food, education, clothing, electricity, and shelter, which effectively renders ICTs ‘secondary, yet access to information and participation are fundamental rights. We urge stakeholders to implement policies that promote the preservation of AIKS in electronic repositories. Memory devices and other ICT accessories should be responsive to African cultures. Investment in ICT infrastructure and training, reliable electricity, and addressing all the basics are critical.

Electronic Repository of Educational Materials on the Topics “Rehabilitation in Post-COVID” and “Neurorehabilitation in Neuro-COVID”: Structure of the Course and Analysis of Learners’ Opinion

The pandemic of COVID-19 imposed the necessity to develop the competences of medical specialists and health professionals on the topic “COVID-Rehabilitation”. We prepared educational materials and an electronic repository, including these topics. The current article presents the structure of the course and the learners’ opinion on the benefits of the educational module.

Data Boxes as a Part of the Strategic Concept of Computerization of Public Administration in the Czech Republic

The paper focuses on the analysis of the computerization of public administration in the Czech Republic in the context of the implementation and operation of data mailboxes, which have been an integral and very important part of e-Government in that country since 2009. A data mailbox has been defined in the Czech legal system since 2009 as an electronic repository of a special type established under the relevant Act No. 300/2008 Coll., which is intended for delivering electronic documents between public authorities on the one hand and natural persons and legal entities on the other. The data mailbox is mandatory for public authorities, legal entities registered in the Commercial Register, and natural persons engaged in business and may also be established by individuals not engaged in business. Public authorities are obliged to send documents preferably to the data mailbox of an addressee, if the latter has set up one, and, considering the legal assumption of delivery, entities which have set up a data mailbox are de facto obliged to collect documents from it. The aim of the study is a detailed description and critical analysis of the data mailbox system in the Czech Republic. The study also focuses on understanding the specific aspects of the implementation of data mailboxes in the Czech Republic. The main methods used are description, thematic and comparative analysis, so this is a descriptive case study. The results of the analysis confirm a number of problems related to the operation of data mailboxes, whether they be technical problems, security risks, usability problems, legal and regulatory problems or other organizational and procedural problems. The forced “computerization” of communication of a number of legal entities in 2023 is also mentioned.

Palliative care in the treatment of women with breast cancer: a scoping review protocol

IntroductionCurrently, breast cancer ranks first among female malignancies; hence, there are strong recommendations for the early inclusion of these patients in palliative care. Palliative care aims to alleviate symptoms improving...