Yoxas/statistical_literacy huggingface dataset:
Rapid recent advances in information technology have opened the door for artificial intelligence (AI)-related technologies to be applied extensively across many industries. The Ministry of Education has emphasized the importance of cultivating advanced-level professionals in diverse fields, particularly in smart machinery, the Asia-Silicon Valley sector, green energy technology, biotechnology, national defense, new agricultural, and circular economy industries, to enhance innovation and promote industrial competitiveness (Kuo, 2019). While interdisciplinary talent in AI and digital innovation is being actively developed elsewhere, nursing education remains in the exploratory phase of AI and digital technology talent cultivation. Although AI is now a well-known term, the competencies required for its application in nursing remain unclear. Moreover, most nursing professionals are unfamiliar with how to best integrate AI into nursing expertise or practice settings. With the application of AI in the healthcare industry now unstoppable, it is vital to consider how to help nursing students adapt to healthcare's new technology landscape (Huang et al., 2021). AI facilitates the digital simulation of human thought patterns, logic, and behaviors with the goal of assisting human users solve problems, especially those that are time-consuming and require repetitive processing. The development of AI requires interdisciplinary collaboration among domain experts, data scientists, software engineers, robotics experts, and computer programmers. Such collaboration is essential to developing products able to meet the demands of the times and to help students become competent future nursing professionals (Murray, 2018). Nurses spend the most time interacting with patients and are thus best able to understand the perceptions and challenges of patients and their families. Collaborating with professionals from interdisciplinary fields is the best strategy for achieving optimal healthcare outcomes. However, nursing schools have yet to provide a clear response to the impact of AI on nursing education. Nursing educational institutions must enable nursing students to comprehend the concepts and principles of AI and equip them with AI literacy to allow them to unleash their potential, continuously innovate, and stay abreast with the times (Ng et al., 2021). In this issue, experts and scholars currently engaged in AI-related research in the nursing discipline share their research findings in the realms of machine learning, deep learning, emotional recognition, and natural language application. These articles offer insights into the implications of AI, suggest how nursing education may best respond to emerging AI trends, and provide the authors' perspectives on nursing education reform. The editor hopes readers will be inspired to explore new concepts, gain a deeper understanding of the application and significance of AI, and apply AI to address clinical and educational challenges to foster competent nursing professionals for tomorrow.
Rapid response system (RRS) activations resulting in emergency transfers (ETs) and codes outside the ICU are associated with increased mortality and length of stay. We aimed to evaluate the patient and care team characteristics of RRS activations resulting in ETs and codes outside the ICU (together classified as "deterioration events") versus those that did not result in a deterioration event. For each RRS activation at our institution from 2019 to 2021, data were gathered on patient demographics and medical diagnoses, care team and treatment factors, and ICU transfer. Descriptive statistics, bivariate analyses, and multivariable logistic regression using a backward elimination model selection method were performed to assess potential risk factors for deterioration events. Over the 3-year period, 1765 RRS activations were identified. Fifty-three (3%) activations were deemed acute care codes, 64 (4%) were noncode ETs, 921 (52%) resulted in nonemergent transfers to an ICU, and 727 (41%) patients remained in an acute care unit. In a multivariable model, any complex chronic condition (adjusted odds ratio, 6.26; 95% confidence interval, 2.83-16.60) and hematology/oncology service (adjusted odds ratio, 2.19; 95% confidence interval, 1.28-3.74) were independent risk factors for a deterioration event. Patients with medical complexity and patients on the hematology/oncology service had a higher risk of deterioration events than other patients with RRS activations. Further analyzing how our hospital evaluates and treats these specific patient populations is critical as we develop targeted interventions to reduce deterioration events.
Rapidly and accurately grasp the change of soil organic carbon content in farmland, which is of great significance in guiding the timely and effective mastery of farmland soil fertility and improvement of soil physical properties. In this study, an ASD FieldSpec 4 spectrometer was used to collect spectral reflectance data on 128 agricultural soil samples taken from Jingbian County, Yulin City, Shaanxi Province, China. Firstly, descriptive statistics of the SOC in the study area were performed, and secondly, after 10 spectral transformations were performed, the correlation analysis and the Boruta algorithm were used to extract the characteristic wavebands of soil organic carbon, respectively, in order to reduce the redundancy of the data. Finally, by comparing the accuracies of different strategies, we constructed a spectral prediction model of soil organic carbon in farmland of the Northwest Agricultural and Animal Husbandry Intertwined Zone that integrates the optimal preprocessing, feature selection strategy and modelling method. The results indicate that: 1) The mean SOC content of the farmland in the study area was low and at the nutrient deficient level, with the standard errors and coefficients of variation for the modelling and validation sets were 1.596 g kg-1, 1.457 g kg-1, 54 % and 52 %, respectively; 2) The shape and trend of spectral special curves with different SOC contents show consistency, and the SOC content is negatively correlated with spectral reflectance; 3) CA selects more feature bands, but the feature bands are more homogeneous, while the Boruta algorithm can effectively remove irrelevant variables and improve the SOC feature selection effect; 4) The SOC prediction model based on Boruta-FD-RF can be better for soil organic carbon estimation, with R2 of 0.899 and 0.748 for the training set and validation set, respectively, RMSE of 1.432 g kg-1 and 1.967 g kg-1, and RPD of 2.557 and 1.647, respectively. The results show that the SOC model established by integrating optimal spectral pre-processing, feature selection strategy and chemometrics strategy has obvious improvement in prediction accuracy and stability, and this study provides an important reference for the fast and accurate estimation of SOC content in farmland of Agro-pastoral Transitional zone in northwest China.
Rare cancers are those that exhibit an incidence of less than six per 100,000 in a year. On average, the five-year relative survival for patients with rare cancers is worse than those with common cancers. The traumatic experience of cancer can be further intensified in patients with rare cancers due to the limited clinical evidence and the lack of empirical evidence for informed decision-making. With rare cancers cumulatively accounting for up to 25% of all cancers, coupled with the rising burden of rare cancers on societies globally, it is necessary to determine the psychological outcomes of patients with rare cancers. This PRISMA-adherent systematic review (PROSPERO: CRD42023475748) involved a systematic search of PubMed, Embase, Cochrane and PsycINFO for all peer-reviewed English language studies published since 2000 to 30th January 2024 that evaluated the prevalence, incidence and risk of depression, anxiety, suicide, and post-traumatic stress disorder (PTSD) in patients with rare cancers. Two independent reviewers appraised and extracted the summary data from published studies. Random effects meta-analyses and meta-regression were used for primary analysis. We included 32 studies with 57,470 patients with rare cancers. Meta-analyses indicated a statistically significant increased risk-ratio (RR) of depression (RR = 2.61, 95% CI: 1.43-4.77, I2 = 97%) and anxiety (RR = 2.66, 95% CI: 1.27-5.55, I2 = 92%) in patients with rare cancers compared to healthy controls. We identified a high suicide incidence (315 per 100,000 person-years, 95% CI: 162-609, I2 = 95%), prevalence of depression (17%, 95% CI: 14-22, I2 = 88%), anxiety (20%, 95% CI: 15-25, I2 = 96%) and PTSD (18%, 95% CI: 9-32, I2 = 25%). When compared to patients with common cancer types, suicide incidence, and PTSD prevalence were significantly higher in patients with rare cancers. Systematic review found that having advanced disease, chemotherapy treatment, lower income, and social status were risk factors for negative psychological outcomes. We highlight the need for early identification of psychological maladjustment in patients with rare cancers. Additionally, studies to identify effective interventions are imperative. This study was supported by the National Medical Research Council Transition Award, SingHealth Duke-NUS Oncology Academic Clinical Programme, the Khoo Pilot Collaborative Award, the National Medical Research Council Clinician Scientist-Individual Research Grant-New Investigator Grant, the Terry Fox Grant and the Khoo Bridge Funding Award.
Rare coding variants that significantly impact function provide insights into the biology of a gene1-3. However, ascertaining their frequency requires large sample sizes4-8. Here, we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. 23% of the Regeneron Genetics Center Million Exome data (RGC-ME) comes from non-European individuals of African, East Asian, Indigenous American, Middle Eastern, and South Asian ancestry. This catalogue includes over 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss-of-function, we identify 3,988 loss-of-function intolerant genes, including 86 that were previously assessed as tolerant and 1,153 lacking established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions depleted of missense variants despite being tolerant to pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this important resource of coding variation from the RGC-ME accessible via a public variant allele frequency browser.
rare diseases (RD) are extremely complex health conditions. Persons affected by these conditions in Cameroon are often neglected in society and health systems through the inexistence of policies and programs. In Cameroon, there exists no program or policy conceived to address their needs in terms of access to quality health care, timely and reliable diagnosis, treatments, education, etc. The consequence is that persons living with a RD (PLWRD) and their families do not participate in social life. The unique fate of PLWRD reveals that the principle of social justice and equity is flawed in Cameroon. However, patients, in order to survive in society, rely on patients' organizations (PO) to improve their quality of life (QoL) and advocate for a better consideration in the society. The aim of this paper is to highlight how initiatives from a grassroot perspective like POs can inform decision-makers to address the needs of PLWRD and their families. the study associated a systematic literature review and semi-structured interviews with parents of children suffering from a RD and who are members of a PO. Through the systematic literature review we highlighted the impact POs have in the development of research on RDs, patient literacy, patient empowerment and advocacy while semi-structured interviews brought out the needs of patients and their families. findings, on the one hand show that, in Cameroon PLWRD face a number of challenges like the incurability of their condition, catastrophic medical expenses, stigmatization and marginalization, etc. and though in POs their QoL still remains poor. On the other hand, where POs are empowered they are key actors in research on RDs and help decision-makers on having a better insight into the type of RD that exists across a geographical area, the sociodemographic profile of patients, etc. for a better management of PLWRD. the study suggests that the ministry of public health should create a network with existing RD POs to adequately meet the needs of PLWRD.
Rare diseases are often complex, chronic and many of them life-shortening. In Germany, healthcare for rare diseases is organized in expert centers for rare diseases. Most patients additionally have regional general practicioners and specialists for basic medical care. Thus, collaboration and information exchange between sectors is highly relevant. Our study focuses on the patient and caregiver perspective on intersectoral and interdisciplinary care between local healthcare professionals (HCPs) and centers for rare diseases in Germany. The aims were (1) to investigate patients' and caregivers' general experience of healthcare, (2) to analyse patients' and caregivers' perception of collaboration and cooperation between local healthcare professionals and expert centers for rare diseases and (3) to investigate patients' and caregivers' satisfaction with healthcare in the expert centers for rare diseases. In total 299 individuals of whom 176 were patients and 123 were caregivers to pediatric patients participated in a survey using a questionnaire comprising several instruments and constructs. Fifty participants were additionally interviewed using a semistructured guideline. Most patients reported to receive written information about their care, have a contact person for medical issues and experienced interdisciplinary exchange within the centers for rare diseases. Patients and caregivers in our sample were mainly satisfied with the healthcare in the centers for rare diseases. The qualitative interviews showed a rather mixed picture including experiences of uncoordinated care, low engagement and communication difficulties between professionals of different sectors. Patients reported several factors that influenced the organization and quality of healthcare e.g. engagement and health literacy in patients or engagement of HCPs. Our findings indicate the high relevance of transferring affected patients to specialized care as fast as possible to provide best medical treatment and increase patient satisfaction. Intersectoral collaboration should exceed written information exchange and should unburden patients of being and feeling responsible for communication between sectors and specialists. Results indicate a lack of inclusion of psychosocial aspects in routine care, which suggests opportunities for necessary improvements.
Rasch measurement can provide a much needed solution to scaling teacher ability. Typically, decisions about teacher ability are based on dichotomously scored certification tests focused on knowledge of content or pedagogy. This paper presents early developmental work of a partial-credit teacher-ability scale of 42 tasks (performances and products) with 348 rated items or criteria. The tasks and criteria are aligned with national and state standards for expected teacher knowledge and skills. These tasks are being used in about two-thirds of Florida school districts and are spreading to colleges of education. Over time there will be many variations in both tasks and criteria, but here we focus on the initial system and the Rasch model as part of the plan for development of the system.
Rationing of nursing care is referred to as overlooking aspects of required patient care. Its result is incomplete or delayed services provided to the patient. Anesthesia nurses employed in an intensive care unit are exposed to a significant workload. Particularly heavy is the psychological burden leading in many cases to the onset of burnout syndrome and a decrease in job satisfaction. Was to determine the relationship between occupational burnout, job satisfaction and rationing of care among anesthesia nurses employed in intensive care units. The study group consisted of 477 anesthesia nurses employed in intensive care units in Poland. The study was conducted between December 2022 and January 2023. The research tools were BERNCA-R questionnaire, Job Satisfaction Scale questionnaire and Maslach Burnout Inventory questionnaire, which were distributed to selected hospitals with a request to be forwarded to intensive care units and completed. In the statistical analysis, correlations were calculated using Spearman's rho coefficient, reporting the intensity of the relationship and its positive or negative direction. The analysis was performed using the IBM SPSS 26.0 package with the Exact Tests module. The mean score of the BERNCA questionnaire was 1.65 ± 0.82. The mean score of occupational burnout was 60.82 ± 10.46. The level of emotional exhaustion, which significantly affects occupational burnout, was 26.39 ± 6.07, depersonalization was 14.14 ± 3.21 and lack of personal achievement was 20.29 ± 4.70. All the scores obtained exceeded the threshold of 50% of total points, which indicates the presence of occupational burnout at a significant level. The job satisfaction of the nurses surveyed was above mean at 23.00 ± 5.2 out of 35 total points. The results proved that there is a statistically significant, although with a weak strength of association, correlation between occupational burnout and rationing of care by anesthesia nurses. As the limitation of anesthesia nurses' ability to perform certain activities increases, their job satisfaction decreases. In a work environment that is conducive to nurses, there are fewer job responsibilities that are unfulfilled. Therefore, it is essential to create a friendly work environment for nursing staff that will promote the provision of services at the highest possible level.
Reading has been widely discussed, mainly due to the published results of international performance tests of schoolchildren. The gaps generated in literacy hinder the development of basic skills necessary for reading, which will have a negative impact on the teaching-learning process from elementary school to high school. This study aimed to compare the reading performance of the students in public and private schools through tests of the Brazilian reading processes-PROLEC-SE-R. Cross-sectional study. The Brazilian adaptation of the PROLEC-SE-R was administered to 436 students: 221 from the state school (G1 6th year, n = 30; G2 7th year, n = 33; G3 8th year, n = 35; G4 9th year, n = 31; G5 1st year, n = 32; G6 2nd year, n = 30; G7 3rd year, n = 30) e 215 private schools (G8 6th year, n = 31; G9 7th year, n = 31; G10 8th year, n = 30; G11 9th year, n = 31; G12 1st year, n = 30; G13 2nd year, n = 31; G14 3rd year, n = 31). Tools of descriptive and bivariate analysis were used. Superior performance of the private school students on spelling tests helps their reading as evidenced by their scores for syntactic and semantic processes. When the knowledge of the use of the word in text, extraction of meaning and its understanding was needed, the difficulty of access to the mental lexicon of the studied population became evident. The PROLEC-SE-R, in addition to establishing the reading profile of elementary and high school students, shows that the gaps in teaching and learning, which exist between public and private education in the literacy period, accompany students throughout the basic education cycle. Knowing the reading profile and in which process there is a disruption is important so that the teaching of specific strategies can be promoted throughout the entire schooling process, especially in primary and secondary education.
Real-world evidence (RWE) is increasingly used for medical regulatory decisions, yet concerns persist regarding its reproducibility and hence validity. This study addresses reproducibility challenges associated with diversity across real-world data sources (RWDS) repurposed for secondary use in pharmacoepidemiologic studies. Our aims were to identify, describe and characterize practices, recommendations and tools for collecting and reporting diversity across RWDSs, and explore how leveraging diversity could improve the quality of evidence. In a preliminary phase, keywords for a literature search and selection tool were designed using a set of documents considered to be key by the coauthors. Next, a systematic search was conducted up to December 2021. The resulting documents were screened based on titles and abstracts, then based on full texts using the selection tool. Selected documents were reviewed to extract information on topics related to collecting and reporting RWDS diversity. A content analysis of the topics identified explicit and latent themes. Across the 91 selected documents, 12 topics were identified: 9 dimensions used to describe RWDS (organization accessing the data source, data originator, prompt, inclusion of population, content, data dictionary, time span, healthcare system and culture, and data quality), tools to summarize such dimensions, challenges, and opportunities arising from diversity. Thirty-six themes were identified within the dimensions. Opportunities arising from data diversity included multiple imputation and standardization. The dimensions identified across a large number of publications lay the foundation for formal guidance on reporting diversity of data sources to facilitate interpretation and enhance replicability and validity of RWE.
Real-world problems are important in math instruction, but they do not necessarily trigger students' task motivation. Personalizing real-world problems by (1) matching problems to students' shared living environment (context personalization) and (2) asking students to pose their own problems (active personalization) might be two interventions to increase students' task motivation. In the current study, we investigated the effects of context personalization and active personalization on students' self-efficacy expectations, intrinsic value, attainment value, utility value, and cost. The participants were 28 fifth- and sixth-grade students who voluntarily took part in a six-month afterschool program in which they posed problems with the aim of creating a math walk in their hometown. Using a within-subjects design, at the end of the afterschool program, the students rated their self-efficacy expectations and task values for four self-developed problems associated with their hometown, four peer-developed problems associated with their hometown, and four instructor-provided problems associated with unfamiliar locations. Students reported higher self-efficacy expectations, intrinsic value, attainment value, and utility value for active-personalized than non-personalized problems. To a lesser extent, context personalization promoted intrinsic value and attainment value. No effect was found for cost. Active personalization (i.e. asking students to pose their own real-world problems) is suited to enhance students' task motivation, specifically their self-efficacy expectations, intrinsic value, attainment value, and utility value. Context personalization still boosts students' intrinsic value and attainment value. Implementation in classroom instruction is discussed.