Steps Of Data Extraction Research Articles

An automated data collection process for constructing graph data relying on LLMs

This paper introduces a process that is designed to harvest data automatically from a variety of online sources. The core of this process lies in its data-handling techniques, which include drawing, cleaning, deduplicating, extracting, and categorizing of raw data to convert unstructured data into a structured format represented and imported in a graph database. The data extraction step utilizes Large Language Model (LLMs) for Named Entity Recognition (NER). A case study on deploying course data collection illustrates the enhancements brought about by this automation, showcasing improvements in the accuracy, completeness, and timeliness of updates in the course data. An evaluation carried out on the extraction and matching methods shows that the F1-score and precision rates are high. Overall, this study contributes to advancement of the field by providing a methodology for automating the collection and processing of online data sources, significantly improving the quality of data collection from online sources.

Adults' perception of the act of cooking in the domestic food environment: a scoping review protocol

The weakening of the generational transmission of culinary skills has led to less confidence and autonomy among individuals in preparing their meals, and to a pattern of food consumption, consisting of ultra-processed foods, which do not require time or the use of these skills. This scoping review aim to identify and to map the perception of adults regarding the act of cooking in the domestic food environment, over the last five years, a time frame that includes the experience of the period of social distancing due to the Covid-19 Pandemic. Scope review protocol based on the methodology proposed by the Joanna Briggs Institute. The search will be carried out in the following databases: Scopus, Medline, SciElo, EMBASE, WOS, JSTOR and Lilacs. Sources of unpublished studies/gray literature will be searched on Google Scholar. The search, selection and data extraction steps will be carried out by four reviewers, and if there are disagreements, a fifth reviewer will be consulted. The process steps will be presented through the PRISMA-ScR flowchart. The extracted data will be organized to enable evaluation and descriptive analysis. The results will be presented in tables, tables and descriptively.

A Hybrid Semi-Automated Workflow for Systematic and Literature Review Processes with Large Language Model Analysis

Systematic reviews (SRs) are a rigorous method for synthesizing empirical evidence to answer specific research questions. However, they are labor-intensive because of their collaborative nature, strict protocols, and typically large number of documents. Large language models (LLMs) and their applications such as gpt-4/ChatGPT have the potential to reduce the human workload of the SR process while maintaining accuracy. We propose a new hybrid methodology that combines the strengths of LLMs and humans using the ability of LLMs to summarize large bodies of text autonomously and extract key information. This is then used by a researcher to make inclusion/exclusion decisions quickly. This process replaces the typical manually performed title/abstract screening, full-text screening, and data extraction steps in an SR while keeping a human in the loop for quality control. We developed a semi-automated LLM-assisted (Gemini-Pro) workflow with a novel innovative prompt development strategy. This involves extracting three categories of information including identifier, verifier, and data field (IVD) from the formatted documents. We present a case study where our hybrid approach reduced errors compared with a human-only SR. The hybrid workflow improved the accuracy of the case study by identifying 6/390 (1.53%) articles that were misclassified by the human-only process. It also matched the human-only decisions completely regarding the rest of the 384 articles. Given the rapid advances in LLM technology, these results will undoubtedly improve over time.

Making judgments based on reported observations of trainee performance: a scoping review in Health Professions Education.

Educators now use reported observations when assessing trainees' performance. Unfortunately, they have little information about how to design and implement assessments based on reported observations. The purpose of this scoping review was to map the literature on the use of reported observations in judging health professions education (HPE) trainees' performances. Arksey and O'Malley's (2005) method was used with four databases (sources: ERIC, CINAHL, MEDLINE, PsycINFO). Eligibility criteria for articles were: documents in English or French, including primary data, and initial or professional training; (2) training in an HPE program; (3) workplace-based assessment; and (4) assessment based on reported observations. The inclusion/exclusion, and data extraction steps were performed (agreement rate > 90%). We developed a data extraction grid to chart the data. Descriptive analyses were used to summarize quantitative data, and the authors conducted thematic analysis for qualitative data. Based on 36 papers and 13 consultations, the team identified six steps characterizing trainee performance assessment based on reported observations in HPE: (1) making first contact, (2) observing and documenting the trainee performance, (3) collecting and completing assessment data, (4) aggregating assessment data, (5) inferring the level of competence, and (6) documenting and communicating the decision to the stakeholders. The design and implementation of assessment based on reported observations is a first step towards a quality implementation by guiding educators and administrators responsible for graduating competent professionals. Future research might focus on understanding the context beyond assessor cognition to ensure the quality of meta-assessors' decisions.

Diagnostic performance of ultrasound-based artificial intelligence for predicting key molecular markers in breast cancer: A systematic review and meta-analysis.

Breast cancer (BC) diagnosis and treatment rely heavily on molecular markers such as HER2, Ki67, PR, and ER. Currently, these markers are identified by invasive methods. This meta-analysis investigates the diagnostic accuracy of ultrasound-based radiomics as a novel approach to predicting these markers. A comprehensive search of PubMed, EMBASE, and Web of Science databases was conducted to identify studies evaluating ultrasound-based radiomics in BC. Inclusion criteria encompassed research on HER2, Ki67, PR, and ER as key molecular markers. Quality assessment using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) was performed. The data extraction step was performed systematically. Our meta-analysis quantifies the diagnostic accuracy of ultrasound-based radiomics with a sensitivity and specificity of 0.76 and 0.78 for predicting HER2, 0.80, and 0.76 for Ki67 biomarkers. Studies did not provide sufficient data for quantitative PR and ER prediction analysis. The overall quality of studies based on the RQS tool was moderate. The QUADAS-2 evaluation showed that the studies had an unclear risk of bias regarding the flow and timing domain. Our analysis indicated that AI models have a promising accuracy for predicting key molecular biomarkers' status in BC patients. We performed the quantitative analysis for HER2 and Ki67 biomarkers which yielded a moderate to high accuracy. However, studies did not provide adequate data for meta-analysis of ER and PR prediction accuracy of developed models. The overall quality of the studies was acceptable. In future research, studies need to report the results thoroughly. Also, we suggest more prospective studies from different centers.

Efficacy of cell-based immunotherapies on patients with glioma: an umbrella review of systematic reviews and meta-analysis protocol

IntroductionGlial brain tumours are highly mortal and are noted as major neurosurgical challenges due to frequent recurrence or progression. Despite standard-of-care treatment for gliomas, the prognosis of patients with higher-grade...

Robust Event Classification Using Imperfect Real-World PMU Data

This paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

A comprehensive evaluation of SZZ Variants through a developer-informed oracle

Automatically linking bug-fixing changes to bug-inducing ones (BICs) is one of the key data-extraction steps behind several empirical studies in software engineering. The SZZ algorithm is the de facto standard to achieve this goal, with several improvements proposed over time. Evaluating the performance of SZZ implementations is, however, far from trivial. In previous works, researchers (i) manually assessed whether the BICs identified by the SZZ implementation were correct or not, or (ii) defined oracles in which they manually determined BICs from bug-fixing commits. However, ideally, the original developers should be involved in defining a labeled dataset to evaluate SZZ implementations. We propose a methodology to define a “developer-informed” oracle for evaluating SZZ implementations, without requiring a manual inspection from the original developers. We use Natural Language Processing (NLP) to identify bug-fixing commits in which developers explicitly reference the commit(s) that introduced the fixed bug. We use the built oracle to extensively evaluate existing SZZ variants defined in the literature. We also introduce and evaluate two new variants aimed at addressing two weaknesses we observed in state-of-the-art implementations (i.e., processing added lines and handling of revert commits).

Network Meta-Analysis (NMA) of Chimeric Antigen Receptor (CAR) T-Cell Therapy for the Treatment of Relapsed/Refractory Diffuse Large B-Cell Lymphoma (DLBCL) after 2 Prior Treatments Using Published Comparative Studies

INTRODUCTION Historically, the clinical prognosis for patients with relapsed/refractory (r/r) diffuse large B-cell lymphoma (DLBCL) has been poor, with limited curative treatment options. However, the introduction of chimeric antigen receptor CAR T-cell (CAR-T) therapy is changing how r/r DLBCL patients are treated. Regulatory approvals of axicabtagene ciloleucel (axi-cel), lisocabtagene maraleucel (liso-cel) and tisagenlecleucel (tisa-cel) in patients with DLBCL with two or more prior lines of treatment were based on their respective non-comparative trials: ZUMA-1, JULIET, and TRANSCEND NHL 001 (TRANSCEND). To understand the comparative efficacy of these CAR-T therapies, treatment comparisons across trials are necessary. In the absence of direct evidence, several matching-adjusted indirect comparisons (MAICs) have been conducted, but have led to conflicting results. This may be, in part, due to the lack of a common comparator. In parallel, to characterize the efficacy of CAR-T compared to other available treatment options, comparisons of these single-arm studies to external historical standard-of-care (SoC) cohorts have been published. Use of this evidence base allows the construction of a network to with a common comparator, which may reduce bias in between treatment estimates. We leveraged this available evidence to conduct an adjusted indirect comparison of axi-cel, liso-cel, and tisa-cel using published comparative studies of CAR-T products to historical SoC cohorts. METHODS On 17th September 2021, we systematically searched EMBASE and MEDLINE databases. Three additional conferences were searched. Eligible studies enrolled patients with r/r DLBCL and compared approved CAR-T therapies to SoC. Outcomes of interest were response and time-to-event outcomes. Safety outcomes were not reported in SCHOLAR-1 and published comparisons to SCHOLAR-1 so safety could not be explored in this analysis. The systematic search followed the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. All study selection and data extraction steps were conducted in dual and independently. For indirect treatment comparisons, network meta-analyses (NMA) were conducted using a Bayesian framework. For dichotomous outcomes, we used logistic regression with binomial link function. A linear regression on log-transformed hazard ratios (HR) were used for available time-to-event outcomes. The NMA used an anchored network with the historical SoC serving as the common comparator. RESULTS The search identified 467 publications, of which 3 were included in the evidence base (Figure 1). In the first study, axi-cel individual patient data (IPD) was compared to SCHOLAR-1 (a historical SoC cohort) IPD using propensity score methods. For the second, a matching adjusted indirect comparison (MAIC) was used to compare liso-cel IPD to SCHOLAR-1 summary data. For the third, tisa-cel IPD was compared to CORAL IPD, a historical SoC cohort (and a sub-cohort of SCHOLAR-1). The results from the ITT population of JULIET were used in this analysis. Available outcomes across all three studies included overall survival (OS) and overall response rate (ORR). Complete response (CR) was analyzed where possible. All three treatments were superior to SoC across all outcomes (Table 1). For OS, axi-cel had a significantly lower hazard ratio for death relative to liso-cel and tisa-cel. Both axi-cel and liso-cel had improved ORR relative to tisa-cel, but were not statistically different from one another. CONCLUSIONS Results of the analyses suggest that axi-cel leads to improved OS in r/r DLBCL relative to liso-cel and tisa-cel. Axi-cel and liso-cel were comparable with respect to response outcomes, showing favorable ORR relative to tisa-cel. These results are in line with MAIC results, where efficacy between CAR-T treatments have been directly compared, but offer the advantage of being able to include a common comparator in the absence of placebo controlled RCTs. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Environmental footprints of food consumption: Protocol for a systematic literature review.

Environmental footprints are indicators that can be used to estimate the impacts of diet on the environment. Since contemporary dietary practices are related to negative environmental impacts, this paper aims to describe a systematic review protocol to investigate the environmental footprints of food consumption by adults and elderly individuals worldwide. This protocol was developed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Search strategies and records of evidence searched in previously defined electronic databases will be defined. Original, population-based articles investigating the environmental footprints of food consumption by adults and the elderly will be included. Two independent reviewers will conduct the study selection and data extraction steps. Critical appraisal of the included studies will be based on the Newcastle-Ottawa Scale. For data synthesis, a narrative synthesis and, if possible, also a meta-analysis will be performed. The systematic review produced from this protocol will provide evidence for data synthesis of the environmental impact through environmental footprints of food consumption of the adult and elderly population from different territories and the footprint assessment tools used around the world. Therefore, it is a gap that needs to be filled because knowing these impacts will be important to inform the development of public policies that encourage healthy and sustainable food in the face of climate and epidemiological changes. PROSPERO registration number: CRD42021281488.

Fetal programming in sheep: Effects on pre- and postnatal organs and glands development in lambs

The present systematic review and meta-analysis aim to summarize the effects of maternal undernutrition or overnutrition during pregnancy on the absolute weight and relative weight of the organs (liver, kidneys, heart, spleen, and lung) and glands (adrenal, pancreas, and thyroid) measured during gestation, birth and the postnatal period in lambs. After completing the search, selection, and data extraction steps, the measure of effect was generated by the individual comparison of each variable response compared with the average of the control and treated group (undernutrition or overnutrition) using the DerSimonian and Laird method for random effects. The liver was the organ most affected by maternal undernutrition, as the absolute weight of the liver was reduced during pregnancy, birth, and the postnatal period. The extent of this effect is related to the duration of the intervention. Reductions in the absolute fetal weight of the lungs and spleen have also been observed. No change in organs weight were observed when the results were expressed as relative weight. For overnutrition, the fetal weight of the liver was reduced to both absolute and relative values. In contrast, the relative weight of the kidneys has been increased. For the glands analyzed, no changes in weight were observed in either scenario (absolute or relative weight). Thus, the organs are more likely to suffer weight changes, especially during pregnancy, as a result of maternal nutrition. However, this change in organ weight seems to be closely related to the reduction in body weight of the progeny as a whole.

Automatic data extraction to support meta-analysis statistical analysis: a case study on breast cancer

BackgroundMeta-analyses aggregate results of different clinical studies to assess the effectiveness of a treatment. Despite their importance, meta-analyses are time-consuming and labor-intensive as they involve reading hundreds of research articles and extracting data. The number of research articles is increasing rapidly and most meta-analyses are outdated shortly after publication as new evidence has not been included. Automatic extraction of data from research articles can expedite the meta-analysis process and allow for automatic updates when new results become available. In this study, we propose a system for automatically extracting data from research abstracts and performing statistical analysis.Materials and methodsOur corpus consists of 1011 PubMed abstracts of breast cancer randomized controlled trials annotated with the core elements of clinical trials: Participants, Intervention, Control, and Outcomes (PICO). We proposed a BERT-based named entity recognition (NER) model to identify PICO information from research abstracts. After extracting the PICO information, we parse numeric outcomes to identify the number of patients having certain outcomes for statistical analysis.ResultsThe NER model extracted PICO elements with relatively high accuracy, achieving F1-scores greater than 0.80 in most entities. We assessed the performance of the proposed system by reproducing the results of an existing meta-analysis. The data extraction step achieved high accuracy, however the statistical analysis step achieved low performance because abstracts sometimes lack all the required information.ConclusionWe proposed a system for automatically extracting data from research abstracts and performing statistical analysis. We evaluated the performance of the system by reproducing an existing meta-analysis and the system achieved a relatively good performance, though more substantiation is required.

The System of Awarding Degrees in Higher Education of Iran and United Kingdom: A Descriptive-Comparative Study With Focusing on the Internationalization of Health Education

The main indicators of higher education (HE) internationalization in the field of awarding degrees are the international development of disciplines and interdisciplinary sciences, new educational and learning methods, new and updated curricula, and their correct ways of sharing. This study aimed to examine the system of awarding degrees in health HE of Iran and the United Kingdom. This descriptive-comparative study focused on the field of medical sciences and its related disciplines. The vital information about the variables was collected by visiting the official websites of the UK universities and related or joint organizations. The related information to the Kerman University of Medical Sciences as a sample of Iran medical universities was obtained from the university’s Farabar system. All data extraction steps were performed manually. There were differences in the mechanism of setting up a new discipline and the process of students’ admission, diversity of degrees’ titles and curriculums, stability of disciplines over the time, creativity in creating competition between different disciplines, the reason for establishing a discipline and the requirements for certification and awarding of degrees in health sciences disciplines in Iran and the United Kingdom were described. Propelling of medical education in the health sciences area towards standard awarding degree systems can be responsible for the requirements of internationalization of higher education.

GPs’ involvement to improve care quality in care homes in the UK: a realist review

Background Organising health-care services for residents living in care homes is an important area of development in the UK and elsewhere. Medical care is provided by general practitioners in the UK, and the unique arrangement of the NHS means that general practitioners are also gatekeepers to other health services. Despite recent focus on improving health care for residents, there is a lack of knowledge about the role of general practitioners. Objectives First, to review reports of research and quality improvement (or similar change management) in care homes to explore how general practitioners have been involved. Second, to develop programme theories explaining the role of general practitioners in improvement initiatives and outcomes. Design A realist review was selected to address the complexity of integration of general practice and care homes. Setting Care homes for older people in the UK, including residential and nursing homes. Participants The focus of the literature review was the general practitioner, along with care home staff and other members of multidisciplinary teams. Alongside the literature, we interviewed general practitioners and held consultations with a Context Expert Group, including a care home representative. Interventions The primary search did not specify interventions, but captured the range of interventions reported. Secondary searches focused on medication review and end-of-life care because these interventions have described general practitioner involvement. Outcomes We sought to capture processes or indicators of good-quality care. Data sources Sources were academic databases [including MEDLINE, EMBASE™ (Elsevier, Amsterdam, the Netherlands), Cumulative Index to Nursing and Allied Health Literature, PsycInfo® (American Psychological Association, Washington, DC, USA), Web of Science™ (Clarivate Analytics, Philadelphia, PA, USA) and Cochrane Collaboration] and grey literature using Google Scholar (Google Inc., Mountain View, CA, USA). Methods Realist And Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) guidelines were followed, comprising literature scoping, interviews with general practitioners, iterative searches of academic databases and grey literature, and synthesis and development of overarching programme theories. Results Scoping indicated the distinctiveness of the health and care system in UK and, because quality improvement is context dependent, we decided to focus on UK studies because of potential problems in synthesising across diverse systems. Searches identified 73 articles, of which 43 were excluded. To summarise analysis, programme theory 1 was ‘negotiated working with general practitioners’ where other members of the multidisciplinary team led initiatives and general practitioners provided support with the parts of improvement where their skills as primary care doctors were specifically required. Negotiation enabled matching of the diverse ways of working of general practitioners with diverse care home organisations. We found evidence that this could result in improvements in prescribing and end-of-life care for residents. Programme theory 2 included national or regional programmes that included clearly specified roles for general practitioners. This provided clarity of expectation, but the role that general practitioners actually played in delivery was not clear. Limitations One reviewer screened all search results, but two reviewers conducted selection and data extraction steps. Conclusions If local quality improvement initiatives were flexible, then they could be used to negotiate to build a trusting relationship with general practitioners, with evidence from specific examples, and this could improve prescribing and end-of-life care for residents. Larger improvement programmes aimed to define working patterns and build suitable capacity in care homes, but there was little evidence about the extent of local general practitioner involvement. Future work Future work should describe the specific role, capacity and expertise of general practitioners, as well as the diversity of relationships between general practitioners and care homes. Study registration This study is registered as PROSPERO CRD42019137090. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 20. See the NIHR Journals Library website for further project information.

Managing overlap of primary study results across systematic reviews: practical considerations for authors of overviews of reviews

BackgroundOverviews often identify and synthesise a large number of systematic reviews on the same topic, which is likely to lead to overlap (i.e. duplication) in primary studies across the reviews. Using a primary study result multiple times in the same analysis overstates its sample size and number of events, falsely leading to greater precision in the analysis. This paper aims to: (a) describe types of overlapping data that arise from the same primary studies reported across multiple reviews, (b) describe methods to identify and explain overlap of primary study data, and (c) present six case studies illustrating different approaches to manage overlap.MethodsWe first updated the search in PubMed for methods from the MOoR framework relating to overlap of primary studies. One author screened the studies titles and abstracts, and any full-text articles retrieved, extracted methods data relating to overlap of primary studies and mapped it to the overlap methods from the MOoR framework. We also describe six case studies as examples of overviews that use specific overlap methods across the steps in the conduct of an overview. For each case study, we discuss potential methodological implications in terms of limitations, efficiency, usability, and resource use.ResultsNine methods studies were found and mapped to the methods identified by the MOoR framework to address overlap. Overlap methods were mapped across four steps in the conduct of an overview – the eligibility criteria step, the data extraction step, the assessment of risk of bias step, and the synthesis step. Our overview case studies used multiple methods to reduce overlap at different steps in the conduct of an overview.ConclusionsOur study underlines that there is currently no standard methodological approach to deal with overlap in primary studies across reviews. The level of complexity when dealing with overlap can vary depending on the yield, trends and patterns of the included literature and the scope of the overview question. Choosing a method might be dependent on the number of included reviews and their primary studies. Gaps in evaluation of methods to address overlap were found and further investigation in this area is needed.

An improved protection strategy based on PCC-SVM algorithm for identification of high impedance arcing fault in smart microgrids in the presence of distributed generation

High impedance Arcing faults (HIAFs) are normally caused by ruptured conductors, leaning of a tree with high impedance, and/or the presence of a high impedance object between the conductor and earth. In such cases, protections available in the microgrid may not be capable of detecting the HIAFs. Hence, to increase the safety level and reliability of the microgrid, it is essential to take action for fast and reliable detection of these types of faults. Therefore, the present study introduces an appropriate strategy to detect HIAFs using a pattern recognition approach. To this end, different scenarios are implemented in the training data extraction step considering the measurement units embedded in a 25 kV microgrid in the presence of Distributed Generations (DG) and Renewable Energy Sources (RESs) in the EMTP-RV software environment. Then, after the initial processing, the scenarios are scaled-down and compared using the Pearson Correlation Coefficient (PCC) and Principal Component Analysis (PCA) methods. Next, the processed data is classified using the Support Vector Machine (SVM) method by selecting the most appropriate kernel. Simulation results in EMTP-RV and MATLAB environments demonstrate that the proposed strategy is capable of fast detection of HIAFs in microgrids with a high level of accuracy.

Context, Input, Process, and Product Evaluation Model in medical education: A systematic review.

BACKGROUND:Evaluation is one of the most important tools for determining the quality of any educational program, which can lead to reformation, revision, or termination of programs. Quality in higher education requires assessment and judgment of goals and strategies, executive policies, operational processes, products, and outcomes. The Context, Input, Process, and Product (CIPP) model is a comprehensive perspective that attempts to provide information in order to make the best decisions related to CIPP. Due to the importance of this topic, the present study examined the application of the CIPP model in the evaluation of medical education programs through a systematic review.MATERIALS AND METHODS:In this systematic review, Persian databases including ISC, SID, Mag Iran, CivilicaL, and Noormags and English databases including PubMed, Web of Science, Scopus, ProQuest Dissertations, Embase, CINAHL, ERIC, and Google Scholar were searched using relevant keywords, such as evaluation, program evaluations, outcome and process assessment, educational assessment, and educational measurements. The search was done with no time limits and 41 papers were obtained until May 22, 2020. This systematic review was performed by following the data extraction steps and assessing the quality of the studies and findings. Critical Appraisal Skills Programs and Mixed-Methods Appraisal Tool checklists were used to check the quality of the papers.RESULTS:This systematic review was conducted on 41 studies, 40 of which were research papers and one was a review paper. From the perspective of the CIPP model of evaluation, most papers showed quite a good level of evaluation of educational programs although some studies reported poor levels of evaluation. Moreover, factors such as modern teaching methods, faculty members, financial credits, educational content, facilities and equipment, managerial and supervisory process, graduates’ skills, produced knowledge, and teaching and learning activities were reported as the factors that could influence the evaluation of educational programs.CONCLUSION:Due to the important role of evaluation in improvement of the quality of educational programs, policymakers in education should pay special attention to the evaluation of educational programs and removal of their barriers and problems. To promote the quality of educational programs, policymakers and officials are recommended to make use of the CIPP model of evaluation as a systemic approach that can be used to evaluate all stages of an educational program from development to implementation.

Application of health education and promotion theory-based interventions on patients with cardiovascular disease: A systematic review.

BACKGROUND:Adopting healthy behaviors can lead to better outcomes which can deeply impact cardiovascular diseases (CVDs) development; consequently, tailoring appropriate theory-based interventions may improve various outcomes among patients at CV risks. This study aimed to assess published researches on the application of health education and promotion of intrapersonal and interpersonal theories/models’ interventions on patients with CVD.MATERIALS AND METHODS:In this systematic review, PubMed, Web of Science, Google Scholar, Scopus, Science Direct, and SID, Magiran databases for English and Persian studies were searched using relevant keywords, respectively. We searched for interventional studies published with no time limits until the end of 2020 assessing the application of health education and promotion theories/models interventions on adult patients with CVDs. Two reviewers individually reviewed abstracts/full-text articles to assess inclusion according to predefined criteria. In case of discrepancy between the two researchers, a third expert was requested to assess papers, and final selection decision was made based on the agreement among the three evaluators. This systematic review was conducted using the following data extraction steps and assessing the quality of the studies and results.RESULTS:From 60 articles, 35 studies met inclusion criteria. Most interventions improved at least some educational including models constructs (20%), clinical (14.2%), and practical (88.5%) outcome related to CVDs. It is noted that attention to educational, practical, and clinical outcomes was focused in published papers, respectively. Furthermore, based on the study categorization using models, some CVDs and theories/models were more concerned compared to others.CONCLUSIONS:Health education and promotion theory-based interventions on patients with CVD appeared beneficial in the most published paper.

Feasibility study to measure the muon bremsstrahlung cross section with the energy loss profile using neutrino telescopes

Muons are the dominant event signature for neutrino telescopes like IceCube and they are the main background for neutrino searches. Furthermore, they are used to investigate extended air showers. In both cases, the stochasticity of the muon propagation plays a key role in the data extraction step and an accurate understanding, even of the edge cases, is crucial. The main process driving stochastic losses for TeV scale muons is bremsstrahlung.In this paper, a feasibility study is presented to measure the cross section of stochastic losses using neutrino-induced muons. The simulation study is based on the propagation of muons using the Monte-Carlo library PROPOSAL. For different reconstruction methods and resolutions, the energy loss distribution for different muon energies is used to estimate the sensitivity to measure the bremsstrahlung cross section. Two further systematic parameters, the detection efficiency, which scales the amount of detected light, and the spectral index are also estimated to analyze their correlation to the estimated bremsstrahlung normalization. The statistics of the simulated dataset correspond to 10 years of up-going muon neutrino data in IceCube.

Exploring Patient-Reported Costs Related to Hepatitis C on the Medical Crowdfunding Page GoFundMe®.

BackgroundSuccessful medical crowdfunding campaigns may alleviate or even eliminate the financial burden of expensive, cumulative medical bills. GoFundMe® crowdfunding pages for hepatitis C virus (HCV) patients were reviewed and analyzed to better understand the characteristics that contribute to a successful fundraising campaign in a disease often associated with patients with a lower social standing or stigma.MethodsA pilot cross-sectional study of all publicly available GoFundMe® crowdfunding pages was conducted for posts related to HCV on GoFundMe® in June 2019. Similar to data extraction steps in a systematic literature review, page data were reviewed to identify whether the source of the patient’s HCV infection was disclosed, if disclosed then how did the patient report contracting the disease, and all costs reported in the description as part of the rationale for requesting funds. Descriptive statistics of category and numeric variables were reported for the full sample, and exploratory analyses were conducted to determine any potential associations with categorical variables and the amount of donations received, categorized as small (< US$1000), moderate (US$1000–4999), and large (≥ US$5000).ResultsA total of 685 unique GoFundMe® pages were included in the analysis. Only 30% (206/685) of the pages disclosed the source of HCV infection. Of those that disclosed a virus source, 86% (177/206) described a source that appeared more socially desirable to our research team (blood transfusion, organ transplant, occupational exposure, etc.). In terms of actual donations received by a page, 46% (312/685) were less than US$1000, 38% (262/685) were between US$1000 and US$4999, and 16% (111/685) were US$5000 or more. Disclosing the virus source was associated with a higher donation category (p = 0.0099).ConclusionThese exploratory findings yield important insights, both for patients or caregivers seeking support on GoFundMe® crowdfunding websites and for researchers interested in exploring the types of costs self-reported by patients in their public requests for financial assistance.