Yoxas/statistical_literacy huggingface dataset:
Thermodynamics is regarded as a universal but not foundational theory because its laws for macroscopic quantities have not been derived from microscopic entities. Thus, to root thermodynamics into the fundamental substance, atomism is revived, thinking that the light quantum is the indivisible and permanent element. Assuming the same basic building blocks constitute everything, the state of any system can be quantified by entropy, the logarithmic probability measure multiplied by Boltzmann's constant. Then, the change in entropy expresses the system's evolution toward thermodynamic balance with its surroundings. These natural processes consuming free energy in the least time accumulate sigmoidally, resulting in skewed distributions found throughout nature. In this way, thermodynamics makes sense of phenomena across disciplines and provides a holistic worldview to address questions such as what the world is, how we know about it, what is the meaning of life and how we should live. This article is part of the theme issue ''Thermodynamics 2.0: Bridging the natural and social sciences (Part 1)'.
Thirty-day readmissions often occur in rehabilitation patients and can happen for many reasons. One of those reasons is when patients do not fully understand how to effectively manage their health after discharge. The purpose of this evidence-based quality improvement project was to determine if implementing the teach-back intervention from the Agency for Healthcare Research and Quality's (AHRQ) Health Literacy Universal Precautions Toolkit would impact 30-day readmission rates among adult rehabilitation patients. Data were collected from the electronic health record of rehabilitation patients. The comparative group included all rehabilitation admissions for 8 weeks prior to the intervention. The implementation group was composed of the rehabilitation admissions for 8 weeks post-implementation. All patients were then followed for 30 days postdischarge to capture readmissions. The total sample size was 79 ( n = 43 in the comparative group, n = 36 in the implementation group). There was a 45% decrease in the mean percentage of the 30-day readmission rate in the implementation group as compared with the comparative group. Based on the results, using the teach-back intervention from AHRQ's Health Literacy Universal Precautions Toolkit may impact 30-day readmission rates.
This academic article discusses the historical underrepresentation of female in science, with a focus on Latin America. It highlights the importance of both technical and non-technical skills in the medical-surgical field, particularly the role of research skills. The study aims to quantify and characterize the scientific output of Latin American female researchers over the past decade, providing insights into the challenges and opportunities in low and middle-income countries. A retrospective cross-sectional bibliometric study was conducted in 2023, focusing on pediatric surgical science journals in Scopus and PubMed. It assessed Latin American female participation, journal details, and interaction networks, using SPSS and Gephi software. The period analyzed was from January 2012 to December 2022. Between 2012 and 2022, 727 articles with Latin authorship in pediatric surgery were analyzed across 304 journals. Of these, 63.69% had female co-authors. The majority were original articles (53.13%), with contributions from Brazil, Mexico, and Chile. Notable journals included the Journal of Pediatric Surgery and Child's Nervous System. Keywords like Laparoscopy and Cardiac surgery were common. A growth trend in female Latin American publications was observed, despite temporary declines. This study highlights a growing trend in Latin American females' scientific contributions to pediatric surgery from 2012 to 2022, although a gender gap persists. The research mainly consists of primary data studies, with a focus on Brazil and Mexico from public institutions. The Journal of Pediatric Surgery featured prominently, and common topics included Laparoscopy, Cardiac surgery, Liver transplant, Congenital heart defects, and COVID-19. IV.
This analysis sought to identify disparities in social determinants of health (SDOH) outcomes at a Texas pediatric hospital. This retrospective study used electronic health records of pediatric patients families surveyed August -December 2022. Outcomes for health literacy, social support, food, transportation, energy, digital, and housing insecurity, and tobacco exposure were analyzed across demographic categories. Among 15,294 respondents to the survey (mean child age, 8.73 years; 43.68% Hispanic, 29.73% non-Hispanic White, 18.27% non-Hispanic Black, 6.79% other race/ethnicity; 53.95% male), 50.25% of respondents reported at least one SDOH, whereas 23.39% reported two or more SDOH. The most prevalent SDOH was lack of social support (3,456, 23.91%). Hispanic, non-Hispanic Black, and other race/ethnicity respondents, non-English speakers, and public insurance users had higher odds of reporting almost all SDOH in logistic regression models adjusted for age, race/ethnicity, language, gender, and insurance type. Race/ethnicity, language, and insurance type disparities were identified for all SDOH.
This article addresses the limitations of existing statistical models in analyzing and interpreting highly skewed miRNA-seq raw read count data that can range from zero to millions. A heavy-tailed model using discrete stable distributions is proposed as a novel approach to better capture the heterogeneity and extreme values commonly observed in miRNA-seq data. Additionally, the parameters of the discrete stable distribution are proposed as an alternative target for differential expression analysis. An R package for computing and estimating the discrete stable distribution is provided. The proposed model is applied to miRNA-seq raw counts from the Norwegian Women and Cancer Study (NOWAC) and the Cancer Genome Atlas (TCGA) databases. The goodness-of-fit is compared with the popular Poisson and negative binomial distributions, and the discrete stable distributions are found to give a better fit for both datasets. In conclusion, the use of discrete stable distributions is shown to potentially lead to more accurate modeling of the underlying biological processes.
This article aims to examine how users' involvement in value co-creation influences the development and orchestration of well-being ecosystems to help tackle complex societal challenges. This research contributes to the public management literature and answers recent calls to investigate novel public service governances by discussing users' involvement and value co-creation for novel well-being solutions. The authors empirically explore this phenomenon through a case study of a complex ecosystem addressing increased well-being, focussing on the formative evaluation stage of a longitudinal evaluation of Sweden's first support centre for people affected by cancer. Following an abductive reasoning and action research approach, the authors critically discuss the potential of user involvement for the development of well-being ecosystems and outline preconditions for the success of such approaches. The empirical results indicate that resource reconfiguration of multi-actor collaborations provides a platform for value co-creation, innovative health services and availability of resources. Common themes include the need for multi-actor collaborations to reconfigure heterogeneous resources; actors' adaptive change capabilities; the role of governance mechanisms to align the diverse well-being ecosystem components, and the engagement of essential actors. Although using a longitudinal case study approach has revealed stimulating insights, additional data collection, multiple cases and quantitative studies are prompted. Also, the authors focus on one country but the characteristics of users' involvement for value co-creation in innovative well-being ecosystems might vary between countries. The findings of this study demonstrate the value of cancer-affected individuals, with "lived experiences", acting as sources for social innovation, and drivers of well-being ecosystem development. The findings also suggest that participating actors in the ecosystem should utilise wider knowledge and experience to tackle complex societal challenges associated with well-being. Policymakers should encourage the formation of well-being ecosystems with diverse actors and resources that can help patients navigate health challenges. The findings especially show the potential of starting from the user's needs and life situation when the ambition is to integrate and innovate in fragmented systems. The proposed model proposes that having a user-led focus on innovating new solutions can play an important role in the development of well-being ecosystems.
This article aims to provide an evaluation of the psychometric properties of the instruments of oral health literacy in adults. An electronic search for instrument studies was performed in the PubMed, PubMed Central, ScienceDirect, Scopus, EMBASE, and PsycINFO databases to find articles published up to June 2021. The risk of bias of the included studies was assessed using the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) Risk of Bias checklist for systematic review. From an initial sample of 2617 articles, 14 instrument studies were included in the present review. Their sample sizes ranged from 177 to 1405 adults, and the number of items per measurement instrument ranged from 14 to 99. For structural validity, statistical techniques were performed using the classical test theory (exploratory and confirmatory factor analysis) and the item response theory (dichotomous and polytomous models). The Rapid Estimate of Adult Literacy in Dentistry 30, elaborated in the USA, was the measurement instrument that had the greatest number of cultural adaptations, having been validated in such countries as Saudi Arabia, Brazil, Turkey, and Romania. The evaluation of the risk of bias, undertaken using the COSMIN Risk of Bias checklist, showed that 6 of the 10 parameters had been evaluated. The psychometric properties that were evaluated in the present systematic review were structural validity, internal consistency, reliability (test-retest), and hypothesis testing for construct validity. To date, there is no gold standard measuring instrument to evaluate the criterion validity parameter.
This article aims to provide new insights about risk and uncertainty in law contexts, by incorporating ideas and principles of contemporary risk science. The main focus is on one particular aspect of the law: its operation in courts where a defendant has been charged with a violation of civil or criminal law. Judgements about risk and uncertainty-typically using the probability concept-and how these relate to the evidence play a central role in such situations. The decision on whether the defendant is liable/guilty or not may strongly depend on how these concepts are understood and communicated. Considerable work has been conducted to provide theoretical and practical foundations for the risk and uncertainty characterizations in these contexts. Yet, it can be argued that a proper foundation for linking the evidence and the uncertainty (probability) judgements is lacking, the result being poor communication in courts about risk and uncertainties. The present article seeks to clarify what the problems are and provide guidance on how to rectify them.
This article assesses evidence of and challenges to the development of inclusive education in Portugal, which is built on three pillars: access to, participation in, and achievement in education for all children and young people. It presents an overview of the present policy framework, followed by an analysis of available statistical data on Portuguese students with disabilities in mainstream schools. The article also discusses significant achievements at the policy and practice levels, namely the attempt to align curriculum and pedagogy and the presence of almost 100% of students with disabilities in mainstream schools. It also considers challenges, such as the issue of monitoring achievement (both at the student and system level) and investments in the system and in teacher education.
This article contributes to the scant literature exploring the determinants of methane emissions. A lot is explored considering CO2 emissions, but fewer studies concentrate on the other most long-lived greenhouse gas (GHG), methane which contributes largely to climate change. For the empirical analysis, a large dataset is used considering 192 countries with data ranging from 1960 up to 2022 and considering a wide set of determinants (total central government debt, domestic credit to the private sector, exports of goods and services, GDP per capita, total unemployment, renewable energy consumption, urban population, Gini Index, and Voice and Accountability). Panel Quantile Regression (PQR) estimates show a non-negligible statistical effect of all the selected variables (except for the Gini Index) over the distribution's quantiles. Moreover, the Simple Regression Tree (SRT) model allows us to observe that the losing countries, located in the poorest world regions, abundant in natural resources, are those expected to curb methane emissions. For that, public interventions like digitalization, green education, green financing, ensuring the increase in Voice and Accountability, and green jobs, would lead losers to be positioned in the winner's rankings and would ensure an effective fight against climate change.
This article covers recent research activities in educational psychology that have an interdisciplinary emphasis and that accommodate twenty-first-century skills in addition to the traditional foundations of literacy, numeracy, science, reasoning (problem-solving), and academic subject matter. We emphasize digital technologies because they are capable of tracking learning data in rich detail and reliably delivering interventions that are tailored to individual learners in particular sociocultural contexts. This is a departure from inflexible pedagogical approaches that previously have been routinely adopted in most classrooms and other contexts of instruction with no precise record of learning and instructional activities. A good design of educational technology embraces the principles of learning science, identifies the basic types of learning that are needed, implements relevant technological affordances, and accommodates feedback from different stakeholders. This article covers research in literacy, collaborative problem-solving, motivation, emotion, and science, technology, engineering, and mathematics (STEM) areas.
This article delineates a relatively unknown path in the history of medical philosophy and medical diagnosis. It is concerned with the phenomenon of vagueness in the physician's "style of thinking" and with the use of fuzzy sets, systems, and relations with a view to create a model of such reasoning when physicians make a diagnosis. It represents specific features of medical ways of thinking that were mentioned by the Polish physician and philosopher Ludwik Fleck in 1926. The paper links Lotfi Zadeh's work on system theory before the age of fuzzy sets with system-theory concepts in medical philosophy that were introduced by the philosopher Mario Bunge, and with the fuzzy-theoretical analysis of the notions of health, illness, and disease by the Iranian-German physician and philosopher Kazem Sadegh-Zadeh. Some proposals to apply fuzzy sets in medicine were based on a suggestion made by Zadeh: symptoms and diseases are fuzzy in nature and fuzzy sets are feasible to represent these entity classes of medical knowledge. Yet other attempts to use fuzzy sets in medicine were self-contained. The use of this approach contributed to medical decision-making and the development of computer-assisted diagnosis in medicine. With regard to medical philosophy, decision-making, and diagnosis; the framework of fuzzy sets, systems, and relations is very useful to deal with the absence of sharp boundaries of the sets of symptoms, diagnoses, and phenomena of diseases. The foundations of reasoning and computer assistance in medicine were the result of a rapid accumulation of data from medical research. This explosion of knowledge in medicine gave rise to the speculation that computers could be used for the medical diagnosis. Medicine became, to a certain extent, a quantitative science. In the second half of the 20th century medical knowledge started to be stored in computer systems. To assist physicians in medical decision-making and patient care, medical expert systems using the theory of fuzzy sets and relations (such as the Viennese "fuzzy version" of the Computer-Assisted Diagnostic System, CADIAG, which was developed at the end of the 1970s) were constructed. The development of fuzzy relations in medicine and their application in computer-assisted diagnosis show that this fuzzy approach is a framework to deal with the "fuzzy mode of thinking" in medicine.
This article describes a Diversity Dialogue Facilitator Training Program for Trainees, an innovative project that prepares psychology and psychiatry learners to facilitate diversity dialogues with healthcare professionals (i.e., clinical and research faculty, staff, and learners) in academic healthcare settings. Through participating in this program, trainees learn to facilitate discussions in which participants reflect upon oppression, discrimination, and disparities; explore their biases; connect and exchange views with colleagues regarding challenging societal events; and delineate action steps for advancing equity, inclusion, social responsivity, and justice in their professional and personal lives. After outlining contextual factors that informed project development, implementation, and dissemination, the iterative process of creating and implementing the training curriculum is detailed, with the aim of offering a model for other academic health center-based training programs interested in establishing a similar initiative. Lessons learned also are shared with the hope of contributing to future efforts to advance training in diversity dialogue facilitation and expand the role of psychologists in medical settings.
This article describes a methodology for the capture and analysis of hybrid data. A case study in the field of reasoning with multiple representations--specifically, in computer programming--is presented to exemplify the use of the methodology. The hybrid data considered comprise computer interaction logs, audio recordings, and data about visual attention focus. The capture of the focus of visual attention data is performed with software. The software employed tracks the user's visual attention by blurring parts of the stimuli presented on the screen and allowing the participant to see only a small region of it at any one time. These hybrid data are analyzed via a methodology that combines qualitative and quantitative approaches. The article describes the software tool employed and the analytic methodology, and also discusses data capture issues and limitations of the approach.
This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seven biomarker responses resulting from the exposure of TK6 cells to each of 126 diverse chemicals over a range of concentrations. Obviously, challenges associated with visualizing seven biomarker responses were further complicated whenever there was a desire to represent the entire 126 chemical data set as opposed to results from a single chemical. Scatter plots, spider plots, parallel coordinate plots, hierarchical clustering, principal component analysis, toxicological prioritization index, multidimensional scaling, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are each considered in turn. Our report provides a comparative analysis of these techniques. In an era where multiplexed assays and machine learning algorithms are becoming the norm, stakeholders should find some of these visualization strategies useful for efficiently and effectively interpreting their high-dimensional data.
This article describes how a series of randomized controlled trials (RCTs) were implemented in the Hector Children's Academy Talent Development Program with the goal of generating mutual benefits for research and practice. The Hector Children's Academy Program, founded in 2010 and located in one of the largest states in Germany, Baden-Württemberg, is a statewide enrichment program for talented primary school students, with a focus on STEMM topics. The program is financed by a private foundation, supervised by the Ministry of Education, and offered by 69 local sites that are hosted by local schools. About 15,000 primary school students (Grades 1-4) attend enrichment courses (more than 23,000 course participations) offered by the Hector Children's Academy Program every year. A unique element of the Hector Children's Academy Program is the role of empirical research in course development. The Hector Core Courses-offered by all local sites-undergo a strict quality assurance process in which RCTs are used to test their effectiveness with regard to central outcomes. After describing the Hector Children's Academy Program, we explain how the Hector Core Courses were developed and incorporated into the program, summarize key findings from the RCTs, and discuss mutual benefits for research and practice.
This article describes the adequacy of the Q methodology as a new option for the validation of nursing diagnoses related to subjective foci. Discussion paper about the characteristics of the Q methodology. This method has been used in nursing research particularly related to subjective concepts and includes both a quantitative and qualitative dimension. The Q methodology seems to be an adequate and innovative method for the clinical validation of nursing diagnoses. The validation of nursing diagnoses related to subjective foci using the Q methodology could improve the level of evidence and provide nurses with clinical indicators for clinical reasoning and for the planning of effective interventions. Descrever a adequação da metodologia Q como uma nova opção para a validação clínica de diagnósticos de enfermagem relacionados com focos subjetivos. MÉTODOS: Artigo de discussão sobre as características da metodologia Q. Este método tem sido utilizado na pesquisa em enfermagem relacionada com conceitos subjetivos e inclui em simultâneo uma vertente qualitativa e quantitativa. CONCLUSÕES: A metodologia Q parece ser uma opção metodológica adequada para a validação clínica de diagnósticos de enfermagem. IMPLICAÇÕES PARA A PRÁTICA: A utilização da metodologia Q na validação clínica de diagnósticos de enfermagem relacionados com focos subjetivos pode melhorar o nível e evidência e facilitar o raciocínio clínico dos enfermeiros, ao providenciar indicadores clínicos também necessários ao desenvolvimento de intervenções efetivas.
This article describes the current landscape of teaching literacy to Filipino Deaf students in a multilingual, multi-cultural classroom amid the pandemic. The article highlights the uniqueness of Filipino Deaf students as multilingual learners in a multi-cultural classroom and the lack of literature and research on Deaf multilingualism both locally and globally. Moreover, the article focuses on the role of Deaf teachers in teaching Filipino Deaf students, especially in their literacy development. The steps being done to ensure that the curriculum is inclusive of Deaf learners who use Filipino Sign Language (FSL), teacher preparation and materials development, and the challenges in the shift to distance learning amid the COVID-19 pandemic are also discussed. Future directions and recommendations include review of curriculum and adaptation, enhancement of teacher preparation, promotion of collaborative teaching and research efforts, and the production of more appropriate and accessible instructional materials for Deaf students.