Yoxas/statistical_literacy huggingface dataset:
The rapid spread of coronavirus disease 2019 (Covid-19) led the need to admit a large number of infected people to hospitals in a short period of time, turning them into one of the most important responsive organizations. This study aims to evaluate the performance of selected military hospitals because they carried out a military operation in Tehran in response to the recent pandemic. This is a descriptive-analytical study. The statistical population of this study consisted of military hospitals responding to Covid-19 pandemic in Tehran. A checklist to evaluate the performance of hospitals in response to Covid-19 pandemic (six areas, 23 sub-areas and 152 items) was used as a data collection tool in this study. This tool had six domains, including risk management and planning, coordination and communication, infection prevention and control, diagnosis and treatment, education and training, and resource management. The overall performance of selected hospitals was 63%, which indicated a good performance. The domain of coordination and communication obtained the lowest score. The investigated hospitals had good performance because they had a desirable access to resources. Periodic self-assessment and accreditation is recommended to improve the performance of these hospitals.
The rapid transition to online teaching during the COVID-19 pandemic created additional stress and workload issues for nurse faculty. Burnout has been reported in nurse faculty who cite workplace factors that influence satisfaction and work-life balance as major contributing factors. The purpose of this study was to examine life balance and professional quality of life among nurse faculty (N = 216) in 2021 during the first year of the COVID-19 pandemic and to describe the challenges of delivering virtual learning experiences. A cross-sectional design was utilized to survey nurse faculty using the Life Balance Inventory and the Professional Quality of Life Scale. Descriptive statistics and correlations were calculated. Nurse faculty reported an unbalanced life balance (median = 1.76), average compassion satisfaction (median = 40.00), average burnout (median = 24.00), and low secondary traumatic stress (median = 21.00). Narrative themes included (1) COVID-19 pandemic has made balance nearly impossible, (2) Intentional disconnection from work activities, (3) Challenging/changing priorities, (4) Promoting a healthy work environment, and (5) Moral distress and exhaustion. Understanding the factors that influence nurse faculty delivery of virtual learning experiences during the COVID-19 pandemic may provide opportunities to improve nurse faculty work-life balance and professional quality of life.
The Rasch Rating Scale Model (RSM) is widely used in questionnaire analysis, providing insights into how individuals respond to item-level stimuli. Existing software for Rasch RSM parameter estimation, while powerful, often presents a steep learning curve. An accessible online tool can greatly benefit novice users, particularly students and clinicians, by simplifying the analytical process. This study introduces an online tool, an intuitive online RSM analysis tool designed to facilitate questionnaire data analysis for applied researchers, students, and clinicians. The online tool employs the joint maximum likelihood method for estimation, yielding estimates, standard errors (SE), and fit statistics iteratively. A unique feature of the tool is its ability to visualize estimates on Google Maps with an opacity setting of 0, enhancing data interpretation through a user-friendly interface. This study outlines the estimation process and key features, employing data from 200 proxy participants who answered 20 5-point questions regarding doctor-patient and doctor-family interactions in pediatric consultations. Mobile computerized adaptive testing (CAT) was employed. The online tool offers 5 essential visual displays often utilized in Rasch analyses, including the Wright Map, KIDMAP, category probability curve, performance plot, and differential item functioning (DIF) graph. DIF analysis revealed that 2 items, concerning the doctor attentiveness and empathy toward the child illness, exhibited differences in female proxy participants' responses, indicating lower satisfaction with pediatricians. The online tool emerges as a user-friendly and efficient RSM analysis tool with notable advantages for newcomers, improving data visualization and comprehension. Its capacity to pinpoint key areas of concern, such as gender-related satisfaction disparities among proxy participants, enhances its utility in questionnaire analysis. The online tool holds promise as a valuable resource for researchers, students, and clinicians seeking accessible Rasch analysis solutions.
The rate of exchange of urea across the membranes of human erythrocytes (red blood cells) was quantified on the 1-s to 2-min timescale. (13)C-urea was hyperpolarized and subjected to rapid dissolution and the previously reported (partial) resolution of (13)C NMR resonances from the molecules inside and outside red blood cells in suspensions was observed. This enabled a stopped-flow type of experiment to measure the (initially) zero-trans transport of urea with sequential single-pulse (13)C NMR spectra, every second for up to ~2 min. Data were analyzed using Bayesian reasoning and a Markov chain Monte Carlo method with a set of simultaneous nonlinear differential equations that described nuclear magnetic relaxation combined with transmembrane exchange. Our results contribute to quantitative understanding of urea-exchange kinetics in the whole body; and the methodological approach is likely to be applicable to other cellular systems and tissues in vivo.
The rate of potentially preventable deaths (PPD) and preventable deaths (PD) can reach more than 20% of overall trauma mortality. Bleeding is the leading cause of preventable mortality. The aim of our study is to define the independent factors of preventable or potentially preventable mortality in our mature trauma system. We conducted a single-center retrospective study in the Sainte Anne Military Teaching Hospital, Toulon, France, including all severe trauma patients admitted to our trauma center and discharged alive as well as all severe trauma patients who died with a death considered preventable or potentially preventable from January 2013 to December 2020. We matched the two groups using a propensity score and searched for independent factors using a generalized linear model. 846 patients were included and analyzed. After matching, our cohort consisted of 245 patients in the survivor group and 49 patients in the preventable deaths group. Pre-hospital delays (73 min vs 54 min P = 0.003) as well as delays before incision in the operating room (80 min vs 52 min P < 0.001) were significantly longer in the PD group. These delays were independent factors of preventable mortality OR 10.35 (95% CI [3.44-31.11] P < 0.001) and OR 37.53 (95% CI [8.51-165.46] P < 0.001) as well as pelvic trauma OR 6.20 (95% CI [1.53-25.20] P = 0.011). Delays in pre-hospital care, delays in access to the operating room from arrival at the trauma center, and pelvic injuries are independent factors associated with an increased risk of preventable mortality in trauma.
The rate of readmission after hospitalisation for respiratory diseases has become a common and challenging clinical problem. Social and functional patient variables could help identify cases at high risk of readmission. The aim was to identify the nursing diagnoses that were associated with readmission after hospitalisation for respiratory disease in Spain. Case-control study within the cohort of patients admitted for respiratory disease during 2016-19 in a tertiary public hospital in Spain (n = 3781). Cases were patients who were readmitted within the first 30 days of discharge, and their controls were the remaining patients. All nursing diagnoses (n = 130) were collected from the electronic health record. They were then grouped into 29 informative diagnostic categories. Clinical confounder-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models. The readmission rate was 13.1%. The nursing diagnoses categories 'knowledge deficit' (OR: 1.61; 95%CI: 1.13-2.31), 'impaired skin integrity and risk of ulcer infection' (OR: 1.45; 95%CI: 1.06-1.97) and 'activity intolerance associated with fatigue' (OR: 1.56; 95%CI: 1.21-2.01) were associated with an increased risk of suffering an episode of hospital readmission rate at 30% after hospital discharge, and this was independent of sociodemographic background, care variables and comorbidity. The nursing diagnoses assigned as part of the care plan of patients during hospital admission may be useful for predicting readmissions.
The rates of coronary angiograms (CA) and related procedures (percutaneous intervention [PCI]) are significantly higher in Germany than in other Organisation for Economic Co-ordination and Development (OECD) countries. The current guidelines recommend non-invasive diagnosis of coronary heart disease (CHD); CA should only have a limited role in choosing the appropriate revascularisation procedure. The aim of the present study was to explore whether improvements in guideline adherence can be achieved through the implementation of regional treatment pathways. We chose four regions of Germany with high utilisation of CAs for the study. Here we report the results of the concomitant qualitative study. General practitioners and specialist physicians (cardiologists, hospital-based cardiologists, emergency physicians, radiologists and nuclear medicine specialists) caring for patients with suspected CHD were invited to develop regional treatment pathways. Four academic departments provided support for moderation, provision of materials, etc. The study team observed session discussions and took notes. After the development of the treatment pathways, 45 semi-structured interviews were conducted with the participating physicians. Interviews and field notes were transcribed verbatim and underwent qualitative content analysis. Pathway development received little support among the participants. Although consensus documents were produced, the results were unlikely to improve practice. The participants expressed very little commitment to change. Although this attempt clearly failed in all study regions, our experience provides relevant insights into the process of evidence appraisal and implementation. A lack of organisational skills, ignorance of current evidence and guidelines, and a lack of feedback regarding one's own clinical behaviour proved to be insurmountable. CA was still seen as the diagnostic gold standard by most interviewees. Oversupply and overutilisation can be assumed to be present in study regions but are not immediately perceived by clinicians. The problem is unlikely to be solved by regional collaborative initiatives; optimised resource planning within the health care system combined with appropriate economic incentives might best address these issues.
The rational for the Somaliland national harmonised curriculum (NHC) was driven by shared concern about the quality of medical education. The Ministry of Education and Science and the Ministry of Health Development produced a Medical Education Policy 2018. Policy objectives included the development of the NHC and accreditation for medical schools that met the standards of the World Federation for Medical Education (WFME). Two bodies were asked to oversee these aims: the National Health Professions' Commission (NHPC) and the National Commission of Higher Education (NCHE). Between 2018 and 2020, a collaborative approach between the Somaliland government, medical school stakeholders, King's Global Health Partnership's (KGHP) volunteers and the Tropical Health Education Trust (THET) team was used to design the 6-years NHC. The NHC structure, content and delivery were grounded by WFME standards, health needs of the local population, student focused and active learning methods, and feasibility of implementation in medical schools. The NHC comprises details about the educational outcomes, curriculum model and framework, educational principles, instructional and learning methods, core as well as optional content, and assessment strategy. The approach used to develop the NHC ensured it is bespoken for Somaliland. Ongoing evaluation of patient and population needs, each medical school's review of programme implementation and outcomes will inform continuous revision and renewal.
The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.
The readability of online bariatric surgery patient education materials (PEMs) often surpasses the recommended 6th grade level. Large language models (LLMs), like ChatGPT and Bard, have the potential to revolutionize PEM delivery. We aimed to evaluate the readability of PEMs produced by U.S. medical institutions compared to LLMs, as well as the ability of LLMs to simplify their responses. Responses to frequently asked questions (FAQs) related to bariatric surgery were gathered from top-ranked health institutions. FAQ responses were also generated from GPT-3.5, GPT-4, and Bard. LLMs were then prompted to improve the readability of their initial responses. The readability of institutional responses, initial LLM responses, and simplified LLM responses were graded using validated readability formulas. Accuracy and comprehensiveness of initial and simplified LLM responses were also compared. Responses to 66 FAQs were included. All institutional and initial LLM responses had poor readability, with average reading levels ranging from 9th grade to college graduate. Simplified responses from LLMs had significantly improved readability, with reading levels ranging from 6th grade to college freshman. When comparing simplified LLM responses, GPT-4 responses demonstrated the highest readability, with reading levels ranging from 6th to 9th grade. Accuracy was similar between initial and simplified responses from all LLMs. Comprehensiveness was similar between initial and simplified responses from GPT-3.5 and GPT-4. However, 34.8% of Bard's simplified responses were graded as less comprehensive compared to initial. Our study highlights the efficacy of LLMs in enhancing the readability of bariatric surgery PEMs. GPT-4 outperformed other models, generating simplified PEMs from 6th to 9th grade reading levels. Unlike GPT-3.5 and GPT-4, Bard's simplified responses were graded as less comprehensive. We advocate for future studies examining the potential role of LLMs as dynamic and personalized sources of PEMs for diverse patient populations of all literacy levels.
The real-time monitoring on the risk status of the vehicle and its driver can provide the assistance for the early detection and blocking control of single-vehicle accidents. However, complex risk coupling relationship is one of the main features of single-vehicle accidents with high mortality rate. On the basis of investigating the coupling effect among multi-risk factors and establishing a safety management database throughout the life cycle of vehicles, single-vehicle driving risk network (SVDRN) with a three-level threshold was developed, and its topology features were analyzed to assessment the importance of nodes. To avoid the one-sidedness of single indicator, the multi-attribute comprehensive evaluation model was applied to measure the comprehensive effect of characteristic indicators for nodes importance. A algorithm for real-time monitoring of vehicle driving risk status was proposed to identify key risk chains. The result revealed that improper operation, speeding, loss of vehicle control and inefficient driver management were the sequence of top four risk factors in the comprehensive evaluation result of nodes importance (mean value = 0.185, SD = 0.119). There were minor differences of 0.017 in the node importance among environmental factors, among which non-standard road alignment had the larger value. The improper operation and non-standard road alignment were the highest combination correlation of factors affecting road safety, with the support of 51.81% and the confidence of 69.35%. This identification algorithm of key risk chains that combines node importance and its risk state threshold can effectively determine the high-frequency risk transmission paths and risk factors through multi-vehicle test, providing a basis for centralization management of transport enterprises.
The real-world tuberculosis (TB) surveillance data was generally incomplete due to underreporting and underdiagnosis. The inventory study aimed to assess and quantify the incompletion of surveillance systems in southwestern China. The inventory study was conducted at randomly selected health facilities (HF) by multi-stage stratified cluster sampling. The participants were included in the period between August of 2020 in province-level and prefecture-level HF, and in the period between June to December of 2020 in other categories of HF respectively. The clinical committee confirmed medical records were matched to the National Notifiable Disease Reporting System (NNDRS) and the Tuberculosis Information Management System (TBIMS) to define the report and register status. The underreporting and under-register rates were evaluated based on the matched data, and factors associated with underreport and under-register were assessed by the 2-level logistic multilevel model (MLM). We enrolled 7,749 confirmed TB cases in the analysis. The province representative overall underreport rate to NNDRS was 1.6% (95% confidence interval, 95% CI, 1.3 - 1.9), and the overall under-register rate to TBIMS was 9.6% (95% CI, 8.9-10.3). The various underreport and under-register rates were displayed in different stratifications of background TB disease burden, HF level, HF category, and data source of the medical record in HF among prefectures of the province. The intraclass correlation coefficient (ICC) was 0.57 for the underreporting null MLM, indicating the facility-level cluster effect contributes a great share of variation in total variance. The two-level logistic MLM showed the data source of medical records in HF, diagnostic category of TB, and type of TB were associated with underreporting by adjusting other factors (p < 0.05). The ICC for under-register was 0.42, and the HF level, HF category, data source of medical records in HF, diagnostic category of TB and type of TB were associated with under-register by adjusting other factors (p < 0.05). The inventory study depicted incomplete TB reporting and registering to NNDRS and TBIMS in southwestern China. It implied that surveillance quality improvement would help advance the TB prevention and control strategy.
The reasons for increased cesarean section (CS) rates are complex and multifactorial. The goal of this study was to look at different social and economic factors that might be causing more cases of CS in the population. A retrospective population-based cohort study. Data was taken from the Perinatal Neonatal Outcomes Research study in the Arabian Gulf (PEARL study) registry. Data from 60,728 live births ≥ 24 weeks of gestation were analyzed. In this study, various socioeconomic factors, such as maternal nationality, religion, educational level, employment status, parental income, consanguinity, housing, preterm birth, and tall stature, were examined for women undergoing cesarean section (CS) and their economic outcomes. Women who underwent vaginal delivery (VD) were compared. There are risks associated with pregnancy, smoking, assisted conception, and prenatal care. 60,728 births ≥ 24 weeks gestation were included in the analysis. 17,535 women delivered by CS (28.9%). Women with university-level -education and above were more likely to deliver by CS (61%), as compared to illiterate women or women with basic education at elementary or secondary levels (OR 0.73, CI 95%: P: <0.0001). Working women were more likely to deliver by CS (OR 1.40, CI 95%, P value <0.0001). Women living in rented houses were less likely to achieve a normal delivery (71.8%) (OR 1.40, CI 95%; P: <0.0001) as compared to women living in owned houses (74.7%). Women over 20 years old tended to achieve more VD compared to women less than 20 years old. P value <0.0001. Smoking was associated with lower chances of VD, with 42.4% of smokers delivered by CS compared to 28.3% of non-smokers (OR 1.87, CI 95%; P: <0.0001). Assisted conception was associated with higher CS rates as compared to spontaneous conceptions (OR 0.39; P: <0.0001). We found no statistically significant differences in how babies were born based on the mother's nationality, the father's job, or the mother's income. Higher education, employed mothers, smoking, and living in rented houses were socioeconomic factors associated with a higher rate of CS in our population. Furthermore, women who had regular antenatal care were more at risk for delivery by cesarean section, which could be related to other comorbidities increasing the likelihood of cesarean birth rather than antenatal care itself. In our population, assisted reproduction was associated with a higher probability of cesarean delivery.