Yoxas/statistical_literacy huggingface dataset:
The electron spin correlation is shown to be expressible in terms of a bona fide probability distribution function with an associated geometric representation. With this aim, an analysis is presented of the probabilistic features of the spin correlation within the quantum formalism, which helps clarify the concepts of contextuality and measurement dependence. The dependence of the spin correlation on conditional probabilities allows for a clear separation between system state and measurement context; the latter determines how the probability space should be partitioned in calculating the correlation. A probability distribution function ρ(ϕ) is then proposed, which reproduces the quantum correlation for a pair of single-particle spin projections and is amenable to a simple geometric representation that gives meaning to the variable ϕ. The same procedure is shown to be applicable to the bipartite system in the singlet spin state. This endows the spin correlation with a clear probabilistic meaning and leaves the door open for a possible physical picture of the electron spin, as discussed at the end of the paper.
The Electronic Personal Health Record (EPHR) provides an innovative service for citizens and professionals to manage health data, promoting patient-centred care. It enhances communication between patients and physicians and improves accessibility to documents for remote medical information management. The study aims to assess the prevalence of awareness and acceptance of the EPHR in northern Italy and define determinants and barriers to its implementation. In 2022, a region-wide cross-sectional study was carried out through a paper-based and online survey shared among adult citizens. Univariable and multivariable regression models analysed the association between the outcome variables (knowledge and attitudes toward the EPHR) and selected independent variables. Overall, 1634 people were surveyed, and two-thirds were aware of the EPHR. Among those unaware of the EPHR, a high prevalence of specific socio-demographic groups, such as foreign-born individuals and those with lower educational levels, was highlighted. Multivariable regression models showed a positive association between being aware of the EPHR and educational level, health literacy, and perceived poor health status, whereas age was negatively associated. A higher knowledge of the EPHR was associated with a higher attitude towards the EPHR. The current analysis confirms a lack of awareness regarding the existence of the EPHR, especially among certain disadvantaged demographic groups. This should serve as a driving force for a powerful campaign tailored to specific categories of citizens for enhancing knowledge and usage of the EPHR. Involving professionals in promoting this tool is crucial for helping patients and managing health data.
The Elementary School Motivation Scale (ESMS) is the only validated and adapted instrument to assess motivation in early ages and in specific domains using the Self-Determination Theory. The present study aims to validate the ESMS in Spanish population (ESMS-E). To this end, 1,190 students from the first half of Elementary education (6-10 years old) filled in the ESMS-E. To translate the instrument the back translation method was used. Internal consistency was assessed through composite reliability (CR), correlations among the dimensions and Confirmatory Factor Analysis (CFA) were used to analyze the theoretical structure proposed by the original instrument. Results showed optimal internal consistency in the different dimensions (CR = 0.701-0.901) and showed a great fit for the model (RMSEA = 0.064, CFI = 0.929, TLI = 0.913), confirming the original model with nine dimensions and the self-determination continuum. The ESMS-E is valid and reliable in the Spanish version. This validation offers a tool for researchers interested in exploring the motives that drive students in early stages in relation to specific learning domains (i.e., reading, writing and mathematics).
The emergence of artificial intelligence has made adaptive learning possible, but building an adaptive system requires a comprehensive understanding of students' cognition. The cognitive model provides a crucial theoretical framework to explore students' cognitive attributes, making it vital for learning assessment and adaptive learning. This study investigates 52 experts, including primary and secondary school teachers, mathematics education experts, and graduate students, based on the 16 cognitive attributes in the TIMSS 2015 assessment framework. Through an analysis of their attribute questionnaires, the Interpretive structural modeling (ISM) method is used to construct a five-level mathematical cognitive model. The model is then revised through oral reports and expert interviews, resulting in a final cognitive model ranging from "memorize" to "justify". The cognitive model describes the relationship between different attributes in detail, enabling the development of adaptive systems and aiding in the diagnosis of students' cognitive development and learning paths in mathematics.
The emergence of collective intelligence has been studied in much greater detail in small groups than in larger ones. Nevertheless, in groups of several hundreds or thousands of members, it is well-known that the social environment exerts a considerable influence on individual behavior. A few recent papers have dealt with some aspects of large group situations, but have not provided an in-depth analysis of the role of interactions among the members of a group in the creation of ideas, as well as the group's overall performance. In this study, we report an experiment where a large set of individuals, i.e., 789 high-school students, cooperated online in real time to solve two different examinations on a specifically designed platform (Thinkhub). Our goal of this paper 6 to describe the specific mechanisms of idea creation we were able to observe and to measure the group's performance as a whole. When we deal with communication networks featuring a large number of interacting entities, it seems natural to model the set as a complex system by resorting to the tools of statistical mechanics. Our experiment shows how an interaction in small groups that increase in size over several phases, leading to a final phase where the students are confronted with the most popular answers of the previous phases, is capable of producing high-quality answers to all examination questions, whereby the last phase plays a crucial role. Our experiment likewise shows that a group's performance in such a task progresses in a linear manner in parallel with the size of the group. Finally, we show that the controlled interaction and dynamics foreseen in the system can reduce the spread of "fake news" within the group.
The emergence of large real-world clinical databases and tools to mine electronic medical records has allowed for an unprecedented look at large data sets with clinical and epidemiologic correlates. In clinical cancer genetics, real-world databases allow for the investigation of prevalence and effectiveness of prevention strategies and targeted treatments and for the identification of barriers to better outcomes. However, real-world data sets have inherent biases and problems (eg, selection bias, incomplete data, measurement error) that may hamper adequate analysis and affect statistical power. Here, we leverage a real-world clinical data set from a large health network for patients with breast cancer tested for variants in BRCA1 and BRCA2 (N = 12,423). We conducted data cleaning and harmonization, cross-referenced with publicly available databases, performed variant reassessment and functional assays, and used functional data to inform a variant's clinical significance applying American College of Medical Geneticists and the Association of Molecular Pathology guidelines. In the cohort, White and Black patients were over-represented, whereas non-White Hispanic and Asian patients were under-represented. Incorrect or missing variant designations were the most significant contributor to data loss. While manual curation corrected many incorrect designations, a sizable fraction of patient carriers remained with incorrect or missing variant designations. Despite the large number of patients with clinical significance not reported, original reported clinical significance assessments were accurate. Reassessment of variants in which clinical significance was not reported led to a marked improvement in data quality. We identify the most common issues with BRCA1 and BRCA2 testing data entry and suggest approaches to minimize data loss and keep interpretation of clinical significance of variants up to date.
The emergence of newer SARS-CoV-2 variants of concern (VOCs) profoundly changed the ICU demography; this shift in the virus's genotype and its correlation to lethality in the ICUs is still not fully investigated. We aimed to survey ICU patients' clinical and laboratory parameters in correlation with SARS-CoV-2 variant genotypes to lethality. 503 COVID-19 ICU patients were included in our study beginning in January 2021 through November 2022 in Hungary. Furthermore, we implemented random forest (RF) as a potential predictor regarding SARS-CoV-2 lethality among 649 ICU patients in two ICU centers. Survival analysis and comparison of hypertension (HT), diabetes mellitus (DM), and vaccination effects were conducted. Logistic regression identified DM as a significant mortality risk factor (OR: 1.55, 95% CI 1.06-2.29, p = 0.025), while HT showed marginal significance. Additionally, vaccination demonstrated protection against mortality (p = 0.028). RF detected lethality with 81.42% accuracy (95% CI 73.01-88.11%, [AUC]: 91.6%), key predictors being PaO2/FiO2 ratio, lymphocyte count, and chest Computed Tomography Severity Score (CTSS). Although a smaller number of patients require ICU treatment among Omicron cases, the likelihood of survival has not proportionately increased for those who are admitted to the ICU. In conclusion, our RF model supports more effective clinical decision-making among ICU COVID-19 patients.
The emergence of non-communicable diseases (NCDs) has been well documented in recent literature which constitute a significant global burden of disease. Qatar which has a significantly high prevalence of NCDs with early on set. Epidemiological and health service utilization information plays a central role in facilitating informed decision making and application of the fundamental principles of PHC in planning and delivery of healthcare with aim to prevent and control NCDs. To enable this, the Department of Clinical Research at Primary Health Care Corporation (PHCC), Qatar's publicly funded and largest primary care provider designed the Health Assessment Linking Trends in Health Status, Risks, and Healthcare Utilization (HEALTHSIGHT) study. This paper describes the HEALTHSIGHT study protocol. The proposed study will use a cross sectional study design involving a random sample of participants enrolled across all 31 PHCC health centers. Individuals aged 18 and above years old registered with PHCC and hold a valid health card and contact information on PHCC's electronic medical records (EMR) will be eligible for inclusion. A stratified random sample not proportional to size sampling technique will be employed to obtain a representative sample size of the PHCC population (N = 6000). Participants will be scheduled for an appointment at a PHCC health centre where a data collector will obtain informed consent, collect vital sign information and administer a questionnaire. A phlebotomist will collect a blood sample. Health service utilization data will be extracted from PHCC's EMR. Epidemiological and health service utilization information is essential to plan and monitor primary care and public health services. The HEALTHSIGHT study, with the help of a randomly selected representative sample from Qatar's primary healthcare settings, provides a unique opportunity to capture this information. This study design will closely represent a real-world understanding of the health risk, status and utilisation and is likely to provide important data to guide primary care planning and delivery in Qatar. The proposed protocol provides an example of a robust nationwide study that be undertaken in short duration using limited resource which can be undertaken in other similar settings.
The emergence of SARS-CoV-2 mutants, waning immunity, and breakthrough infections prompted the use of booster doses of the COVID-19 vaccine to fight against the pandemic. India started booster doses in January 2022 and it is critical to determine the intention of booster dose uptake and its correlates. Therefore, the current cross-sectional study aimed to investigate booster dose acceptability and associated predictors among the Indian population. A convenience sampling technique was utilized to recruit a sample of 687 Indian residents. A 55-item psychometric validated survey tool was used to assess booster dose acceptability, vaccine literacy and vaccine confidence. Univariate, bivariate, and multivariate statistical methods were used to analyze the data. Over 50% of participants reported their willingness to take the booster dose. Among the group not willing to take the booster dose (n = 303, 44.1%), a significantly larger proportion of respondents were unvaccinated with the primary series (12.2% vs. 5.2%, p < 0.001), had an annual income below 2.96 lacs/annum (52.8% vs. 33.1, p < 0.001), were residents of rural areas (38.0% vs. 23.2%, p < 0.001), were not living with vulnerable individuals (78.5% vs. 65.2%, p < 0.001) and did not have family/friends who had tested positive for COVID-19 (54.6% vs. 35.1%, p = 0.001). Demographic, vaccine variables and multi-theory model subscales to predict the initiation of booster dose among hesitant participants were statistically significant, R2 = 0.561, F (26, 244) = 11.978, p < 0.001; adjusted R2 = 0.514. Findings of this study highlight the need to develop evidence-based interventions to promote vaccine uptake, particularly among hard-to-reach communities living in developing countries.
The emergence of the COVID-19 pandemic in December 2019 initiated a global transformation in healthcare practices, particularly with respect to hospital management. PCR testing mandates for medical treatment seekers were introduced to mitigate virus transmission. This study examines the impact of these changes on the management of patients with appendicitis. We conducted a retrospective analysis of medical records for 748 patients diagnosed with appendicitis who underwent surgery at a tertiary care hospital during two distinct periods, the pre-pandemic year 2019 and the post-pandemic year 2021. Patient demographics, clinical characteristics, laboratory data, surgical outcomes, and hospital stay duration were assessed. While no significant differences were observed in the general characteristics of patients between the two groups, the time from hospital visit to operation increased significantly during the pandemic. Unexpectedly, delayed surgical intervention was associated with shorter hospital stays but did not directly impact complication rates. There was no discernible variation in the type of surgery or surgical timing based on symptom onset. The pandemic also prompted an increase in appendicitis cases, potentially related to coronavirus protein expression within the appendix. The COVID-19 pandemic has reshaped the landscape of appendicitis management. This study underscores the complex interplay of factors, including changes in hospital protocols, patient concerns, and surgical timing. Further research is needed to explore the potential link between COVID-19 and appendicitis. These insights are valuable for informing healthcare practices during and beyond the pandemic.
The emerging adulthood is traditionally viewed as a time of optimal health, but also as a critical life span, characterized by changing life circumstances and the establishment of an individual lifestyle. Especially university life seems to hold several challenges impeding the manifestation of a health supporting manner, as many students tend to show a poorer health behavior and a higher amount of health-related problems than comparable age groups. This, along with a steady growth of the higher education sector, brings increased attention to the university setting in the context of prevention. To date, there are few empirical longitudinal and coherent cross-sectional data on the status of students' health literacy, health status, and health behaviors, and on the impact of the study format on students' health. The aim of this prospective cohort study is to reduce this research gap. Starting during winter semester 2020/21, the prospective cohort study collects data on health literacy, health status and health behavior on a semester-by-semester basis. All enrolled students of the IST University of Applied Sciences, regardless of study format and discipline, can participate in the study at the beginning of their first semester. The data are collected digitally via a specifically programmed app. A total of 103 items assess the subjectively perceived health status, life and study satisfaction, sleep quality, perceived stress, physical activity, diet, smoking, alcohol consumption, drug addiction and health literacy. Statistical analysis uses (1) multivariate methods to look at changes within the three health dimensions over time and (2) the association between the three health dimensions using multiple regression methods and correlations. This cohort study collects comprehensive health data from students on the course of study. It is assumed that gathered data will provide information on how the state of health develops over the study period. Also, different degrees of correlations of health behavior and health literacy will reveal different impacts on the state of students' health. Furthermore, this study will contribute to empirically justified development of target group-specific interventions. German Clinical Trials Register: DRKS00023397 (registered on October 26, 2020).
The emerging era of precision medicine is characterized by an increasing availability of targeted anticancer therapies and by the parallel development of techniques to obtain more refined molecular data, whose interpretation may not always be straightforward. Molecular tumor boards gather various professional figures, in order to leverage the analysis of molecular data and provide prognostic and predictive insights for clinicians. In addition to healthcare development, they could also become a tool to promote knowledge and research spreading. A growing body of evidence on the application of molecular tumor boards to clinical practice is forming and positive signals are emerging, although a certain degree of heterogeneity exists. This work analyzes molecular tumor boards' potential workflows, figures involved, data sources, sample matrices and eligible patients, as well as available evidence and learning examples. The emerging concept of multi-institutional, disease-specific molecular tumor boards is also considered by presenting two ongoing nationwide experiences.
The emerging field of robotics education (RE) is a new and rapidly growing subject area worldwide. It may provide a playful and novel learning environment for children to engage with all aspects of science, technology, engineering, and mathematics (STEM) learning. The purpose of this research is to examine how robotics learning activities may affect the cognitive abilities and cognitive processes of 6-8 years old children. The study adopted the mixed methods approach with a repeated measures design; three waves of data collection over 6 months, including quantitative data obtained from cognitive assessments and eye-tracking, and qualitative data from the interviews. A total of 31 children were recruited from an afterschool robotics program. To the best of our knowledge, this study is the first RE research that used a combination of eye-tracking, cognitive assessments, and interviews for examining the effect of RE on children. Using linear growth models, the results of cognitive assessments showed that children's visuospatial working memory as well as logical and abstract reasoning skills improved over time. The interview data were analyzed by a thematic analysis. The results revealed that children perceived RE activities as game play, which made children more engaged in their study; parents found their children to be more focused on activities comparing to six months ago. Additionally, the visualization of the eye-tracking data suggested that children became more focused on RE activities and got faster to process the information across six months in general, which echoed the findings in assessments and interviews. Our findings may help educators and policymakers better understand the benefits of RE for young children.
The emerging trend focuses on the need for an active agile method in the nursing curriculum. It helps to improve student engagement, the interaction between the students and teachers, higher-order thinking, teamwork, and practical skills. This study was done to assess the effectiveness of agile methodology on metacognitive ability and clinical performance among nursing students. In this interventional study, two groups of the pre-post design were adopted. Each college was considered a cluster. By using the chit method, the colleges (four) were randomly selected for the experimental and control groups. To avoid contamination, all the fourth-year students were included either in the experimental group (133) or the control groups (132), respectively. The pretest was conducted using a metacognitive awareness inventory (metacognitive ability (MA)) and an objective structured clinical examination (OSCE) tool (clinical performance (CP)) in the experimental and control groups. Leaders were selected using leader attribute inventory (leadership ability (LA) in the pretest and posttest 2 among the experimental and control groups before the agile teaching. By using agile methodology, the newborn course was taught for 21 days in the experimental group. To assess the effectiveness of agile methodology, the control group was not given any teaching. Posttests were conducted immediately and after 1 week to assess the MA and CP in the experimental and control groups. The control group had agile training for 10 days after the posttests to understand the newer agile methodology. The data were analyzed by using SPSS version 28. Descriptive and inferential statistics were used to assess the data for effectiveness. The result showed that there is an improvement in the metacognitive ability (MA) score and clinical performance score over time in the experimental group (P < 0.001). The study finding supports that incorporating agile methodology in education impacts the metacognitive ability and clinical performance among nursing students. However, the teacher must be familiar with the methodology while incorporating agile in teaching.