Yoxas/statistical_literacy huggingface dataset:
Consuming foods high in iron benefits metabolic processes as well as the development of the neonatal and fetal brain. Despite the significance of eating foods high in iron for public health, Ethiopian practices are still limited when compared to the World Health Organization's (WHO) assessment of its consumption of such foods. This study used the Ethiopia Demographic and Health Survey (EDHS) to evaluate the consumption of iron-rich foods, regional clustering, and related characteristics among children aged 6-23 months. The information was taken from the typical EDHS 2019 dataset, which included a weighted sample of 1572 young children aged 6-23 months old in total. Utilizing Kuldorff's SaTScan version 9.6 software, spatial scan statistics were produced. Software from ArcGIS 10.8 was used to display the regional distribution of inadequate consumption of foods high in iron. Utilizing multilevel or mixed effects logistic regression analysis, the associated determinants for a healthy diet rich in foods containing iron were found. In the final model, a P-value of < 0.05 was announced as a statistical significance variable. Overall, in Ethiopia, children aged 6-23 months consumed iron-rich foods at a rate of 27.14% (95% CI 24.99-29.39). Poor intake of foods heavy in iron is concentrated in Ethiopia's regional states of Afar, a sizable portion of Amhara, Oromia, Tigray, Somali, Gambela, and SNNPS. Primary and secondary education (AOR = 1.73, CI 95%: 1.23, 2.41), and (AOR = 1.97,CI 95%: 1.25, 3.10), having ≥ 2 under five children, and current status of breastfeeding (AOR = 0.62 (CI 95%: 0.45, 0.84), and (AOR = 0.32, CI 95%: 0.23, 0.44), giving birth at health facilities (AOR = 1.51, CI 95%: 1.06, 2.13),being from Afar and Somali regions (AOR = 0.39, 95%: 0.17, 0.93), and (AOR = 0.26, CI 95%: 0.10, 0.69) have shown statistically significant association with the outcome variable respectively. In Ethiopia, providing high-iron meals and supplements to under-2-year-old children represents minimal, but persistent, public health expenses. Based on the identified determinants, the Ethiopian federal ministry of health and other stakeholders should pay special attention to the locations designated as hot spots for maternal and child health service enhancement to promote the consumption of iron-rich meals among children aged 6-23 months.
Contact plays a critical role in infectious disease transmission. Characterizing heterogeneity in contact patterns across individuals, time, and space is necessary to inform accurate estimates of transmission risk, particularly to explain superspreading, predict age differences in vulnerability, and inform social distancing policies. Current respiratory disease models often rely on data from the 2008 POLYMOD study conducted in Europe, which is now outdated and potentially unrepresentative of behavior in the US. We seek to understand the variation in contact patterns across spatial scales and demographic and social classifications, whether there is seasonality to contact patterns, and what social behavior looks like at baseline in the absence of an ongoing pandemic. We analyze spatiotemporal non-household contact patterns across 11 million survey responses from June 2020 - April 2021 post-stratified on age and gender to correct for sample representation. To characterize spatiotemporal heterogeneity in respiratory contact patterns at the county-week scale, we use generalized additive models. In the absence of pre-pandemic data on contact in the US, we also use a regression approach to produce baseline contact estimates to fill this gap. Although contact patterns varied over time during the pandemic, contact is relatively stable after controlling for disease. We find that the mean number of non-household contacts is spatially heterogeneous regardless of disease. There is additional heterogeneity across age, gender, race/ethnicity, and contact setting, with mean contact decreasing with age and lower in women. The contacts of white individuals and contacts at work or social events change the most under increased national incidence. We develop the first county-level estimates of non-pandemic contact rates for the US that can fill critical gaps in parameterizing disease models. Our results identify that spatiotemporal, demographic, and social heterogeneity in contact patterns is highly structured, informing the risk landscape of respiratory disease transmission in the US.
Contemporary college students not only face the pressure brought by their studies but also bear the pressure brought by society and their families. Helping college students correctly understand their mental health and effectively solve their' mental health diseases has become an important issue in education research. The cultivation of healthy psychological quality is inseparable from the cultivation of a humanistic spirit. Therefore, integrating excellent traditional culture into Chinese language and literature teaching and research and giving full play to and inheriting the educational role of excellent traditional culture can not only improve the literary quality of college students and benefit the construction of healthy mental of college students. The main purpose of this research is to analyze the effect of Chinese excellent traditional culture on the cultivation of college students' mental health, analyze the impact of traditional culture integration into Chinese language and literature teaching research on improving college students' mental health, and propose the valuable suggestion for integration of excellent traditional culture into Chinese language and literature teaching research. Firstly, we analyze the benefits of integrating traditional culture in literature to the construction of college students' healthy psychology; then, the current deficiencies of literature education are analyzed; next, through literature analysis and summary, the main factors affecting the mental health of college students were found and the importance of these factors was evaluated by questionnaire survey and mathematical statistics methods; finally, targeted opinions and suggestions are put forward. This research provides guidance and reference for inheriting excellent national culture through literature education and constructing university health psychology in the future.
Contemporary economic thinking does not acknowledge that the human economy is embedded in Nature; it instead treats humanity as a customer that draws on Nature. In this paper, we present a grammar for economic reasoning that is not built on that error. The grammar is based on a comparison between our demand for Nature's maintenance and regulating services and her ability to supply them on a sustainable basis. The comparison is then used to show that for measuring economic well-being, national statistical offices should estimate an inclusive measure of their economies' wealth and its distribution, not GDP and its distribution. The concept of 'inclusive wealth' is then used to identify policy instruments that ought to be used to manage such global public goods as the open seas and tropical rainforests. Trade liberalization without heed paid to the fate of local ecosystems from which primary products are drawn and exported by developing countries leads to a transfer of inclusive wealth from there to rich importing countries. Humanity's embeddedness in Nature has far-reaching implications for the way we should view human activities-in households, communities, nations and the world. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.
Contemporary midwifery curricula require that student midwives have insight and understanding of global health practice and intercultural sensitivity. The current mobility model excludes large numbers of students from engaging in transnational learning. 1) to evaluate midwifery students' experiences of blended mobility; 2) to investigate if the combination of virtual and physical mobility activities supported development of intercultural sensitivity and soft skills. Multi-centre mixed-methods study. Four European Higher Education Institutions located in England, Italy, Estonia and The Netherlands. Sixty-four midwifery students studying in one of the four partner institutions selected as study sites and who participated in the TOTEMM blended mobility scheme took part in the evaluation. Data were collected through two online surveys, face-to-face focus groups and learning analytics. Descriptive summary statistical analysis of survey data was undertaken. Focus group discussions were subjected to thematic analysis. Findings from the quantitative survey and qualitative focus groups were merged using a convergent mixed methods approach. Learning Analytics were interpreted as complementary to the above components, to further triangulate the findings. Both virtual and physical components were evaluated positively by students, with high engagement confirmed by learning analytics. A statistically significant increase in the mean of the Total Intercultural Sensitivity Scale score was seen between the pre- and post-mobility surveys, indicating participation in the TOTEMM mobility model was associated with enhanced intercultural sensitivity. Positive effects on confidence, open-mindedness, empathy, interaction and non-judgment were shared by participants. TOTEMM is an innovative inclusive approach to enable a diverse student group to benefit from transnational learning, including the development of intercultural sensitivity. The TOTEMM blended mobility model has potential for integration into future midwifery curricula and programmes in the four partner settings involved in TOTEMM and utility for the wider European context.
Contemporary validity testing theory holds that validity lies in the extent to which a proposed interpretation and use of test scores is justified, the evidence for which is dependent on both quantitative and qualitative research methods. Despite this, we hypothesise that development and validation studies for assessments in the field of health primarily report a limited range of statistical properties, and that a systematic theoretical framework for validity testing is rarely applied. Using health literacy assessments as an exemplar, this paper outlines a protocol for a systematic descriptive literature review about types of validity evidence being reported and if the evidence is reported within a theoretical framework. A systematic descriptive literature review of qualitative and quantitative research will be used to investigate the scope of validation practice in the rapidly growing field of health literacy assessment. This review method employs a frequency analysis to reveal potentially interpretable patterns of phenomena in a research area; in this study, patterns in types of validity evidence reported, as assessed against the criteria of the 2014 Standards for Educational and Psychological Testing, and in the number of studies using a theoretical validity testing framework. The search process will be consistent with the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Outcomes of the review will describe patterns in reported validity evidence, methods used to generate the evidence and theoretical frameworks underpinning validation practice and claims. This review will inform a theoretical basis for future development and validity testing of health assessments in general. Ethics approval is not required for this systematic review because only published research will be examined. Dissemination of the review findings will be through publication in a peer-reviewed journal, at conference presentations and in the lead author's doctoral thesis.
CONTEXT AND OBJECTIVE The cognitive processes relating to the development of clinical reasoning are only partially understood, which explains the difficulties in teaching this skill in medical courses. This study aimed to understand how clinical reasoning develops among undergraduate medical students. DESIGN AND SETTING Quantitative and qualitative exploratory descriptive study conducted at the medical school of Universidade Federal de Goiás. METHODS The focus group technique was used among 40 students who participated in five focus groups, with eight students from each year, from the first to fifth year of the medical school program. The material was subjected to content analysis in categories, and was subsequently quantified and subjected to descriptive statistical analysis and chi-square test for inferential statistics. RESULTS The content of the students' statements was divided into two categories: clinical reasoning - in the preclinical phase, clinical reasoning was based on knowledge of basic medical science and in the clinical phase, there was a change to pattern recognition; knowledge of basic medical science - 80.6% of the students recognized its use, but they stated that they only used it in difficult cases. CONCLUSION In the preclinical phase, in a medical school with a traditional curriculum, clinical reasoning depends on the knowledge acquired from basic medical science, while in the clinical phase, it becomes based on pattern recognition.
Context is of fundamental importance to both human and machine vision; e.g., an object in the air is more likely to be an airplane than a pig. The rich notion of context incorporates several aspects including physics rules, statistical co-occurrences, and relative object sizes, among others. While previous work has focused on crowd-sourced out-of-context photographs from the web to study scene context, controlling the nature and extent of contextual violations has been a daunting task. Here we introduce a diverse, synthetic Out-of-Context Dataset (OCD) with fine-grained control over scene context. By leveraging a 3D simulation engine, we systematically control the gravity, object co-occurrences and relative sizes across 36 object categories in a virtual household environment. We conducted a series of experiments to gain insights into the impact of contextual cues on both human and machine vision using OCD. We conducted psychophysics experiments to establish a human benchmark for out-of-context recognition, and then compared it with state-of-the-art computer vision models to quantify the gap between the two. We propose a context-aware recognition transformer model, fusing object and contextual information via multi-head attention. Our model captures useful information for contextual reasoning, enabling human-level performance and better robustness in out-of-context conditions compared to baseline models across OCD and other out-of-context datasets. All source code and data are publicly available at https://github.com/kreimanlab/WhenPigsFlyContext.
Context specificity and the impact that contextual factors have on the complex process of clinical reasoning is poorly understood. Using situated cognition as the theoretical framework, our aim was to evaluate the verbalized clinical reasoning processes of resident physicians in order to describe what impact the presence of contextual factors have on their clinical reasoning. Participants viewed three video recorded clinical encounters portraying straightforward diagnoses in internal medicine with select patient contextual factors modified. After watching each video recording, participants completed a think-aloud protocol. Transcripts from the think-aloud protocols were analyzed using a constant comparative approach. After iterative coding, utterances were analyzed for emergent themes with utterances grouped into categories, themes and subthemes. Ten residents participated in the study with saturation reached during analysis. Participants universally acknowledged the presence of contextual factors in the video recordings. Four categories emerged as a consequence of the contextual factors: (1) emotional reactions (2) behavioral inferences (3) optimizing the doctor patient relationship and (4) difficulty with closure of the clinical encounter. The presence of contextual factors may impact clinical reasoning performance in resident physicians. When confronted with the presence of contextual factors in a clinical scenario, residents experienced difficulty with closure of the encounter, exhibited as diagnostic uncertainty. This finding raises important questions about the relationship between contextual factors and clinical reasoning activities and how this relationship might influence the cost effectiveness of care. This study also provides insight into how the phenomena of context specificity may be explained using situated cognition theory.
Context: In the midst of the COVID-19 pandemic- with undulating statistics of new cases and deaths and with schools set to reopen in the fall of 2020 after a long hiatus- the objective was to address the needs and methods of preparing children for a safe return to school. Objective: To educate 1st - 5th grade elementary school children about proper health and safety precautions during the COVID-19 pandemic. Study Design and Setting: Three monthly virtual sessions via zoom were implemented with focuses on hygiene, physical activity, and healthy coping mechanisms during a pandemic. The hygiene lecture included interactive demonstrations on handwashing, coughing/sneezing precautions, and appropriate mask-wearing behavior. During the coping mechanisms session, children were asked to use art or free text to answer the question "How has COVID-19 changed my feelings?" The physical activity session discussed safe ways for children to stay active during the pandemic. Both quantitative (pre and post-knowledge assessment quizzes) and qualitative (free text, drawings) data were collected through electronic surveys. Quizzes were designed for the appropriate grade level and used a combination of multiple choice, free text, checkboxes, and pictures to address common themes. Population studied and Intervention: School-aged children (1st-5th grade) at the Raindrop Foundation of San Antonio participated in educational sessions about maintaining proper COVID-19 hygiene. Outcome Measures and Results: Final results show six 1st - 2nd graders and nine 3rd - 5th graders consistently participated in the project. The children involved could identify proper mask-wearing etiquette, safe coughing habits, and when and how to wash their hands. Emotions reported were both positive (ex. happy) and negative (ex. Sad, bored). Reported activities were indoor electronic games and work. Children reported missing friends and going to parks. Conclusions: These educational sessions were organized to teach children safe practices for their return to school, develop coping skills, and also help them adapt to physical activity while maintaining social distancing. Participant 1st - 5th graders answered most questions correctly and displayed the basics of COVID-19 safety knowledge. The children surveyed are experiencing mixed emotions during the pandemic due to feelings of social isolation.
Context: Patients over the age of 65 years are more likely to experience higher severity and mortality rates than other populations from COVID-19. Clinicians need assistance in supporting their decisions regarding the management of these patients. Artificial Intelligence (AI) can help with this regard. However, the lack of explainability-defined as "the ability to understand and evaluate the internal mechanism of the algorithm/computational process in human terms"-of AI is one of the major challenges to its application in health care. We know little about application of explainable AI (XAI) in health care. Objective: In this study, we aimed to evaluate the feasibility of the development of explainable machine learning models to predict COVID-19 severity among older adults. Design: Quantitative machine learning methods. Setting: Long-term care facilities within the province of Quebec. Participants: Patients 65 years and older presented to the hospitals who had a positive polymerase chain reaction test for COVID-19. Intervention: We used XAI-specific methods (e.g., EBM), machine learning methods (i.e., random forest, deep forest, and XGBoost), as well as explainable approaches such as LIME, SHAP, PIMP, and anchor with the mentioned machine learning methods. Outcome measures: Classification accuracy and area under the receiver operating characteristic curve (AUC). Results: The age distribution of the patients (n=986, 54.6% male) was 84.5□19.5 years. The best-performing models (and their performance) were as follows. Deep forest using XAI agnostic methods LIME (97.36% AUC, 91.65 ACC), Anchor (97.36% AUC, 91.65 ACC), and PIMP (96.93% AUC, 91.65 ACC). We found alignment with the identified reasoning of our models' predictions and clinical studies' findings-about the correlation of different variables such as diabetes and dementia, and the severity of COVID-19 in this population. Conclusions: The use of explainable machine learning models, to predict the severity of COVID-19 among older adults is feasible. We obtained a high-performance level as well as explainability in the prediction of COVID-19 severity in this population. Further studies are required to integrate these models into a decision support system to facilitate the management of diseases such as COVID-19 for (primary) health care providers and evaluate their usability among them.
Contextual approaches to high quality Early Childhood Education and Care (ECEC) seek to capture the complexity of children's lives, developing pedagogical approaches that are responsive to children's needs and interests. In 2020, the COVID-19 pandemic provided a complex layer to the question of what constitutes quality ECEC. A mixed methods appreciative inquiry of educators' and parents' views of quality in one ECEC setting in England, became an unexpected ethnographic exploration of quality ECEC in the time of a global pandemic. The findings indicate how features of quality, such as offering a range of learning environments and structuring the pedagogic environment to offer free-flowing play, had to be adapted to prevent the spread of COVID-19. The focus on quality shifted, prioritising the health and safety of families and staff, over the quality and variety of the curriculum. Greater emphasis was also placed on children's social and emotional well-being to support their ability to understand and manage the changes to routines in response to the pandemic. The findings demonstrate that the early years workforce remains central to understanding and supporting quality, concluding that quality ECEC is shaped by adaptability - adapting to the needs of children, families, staff, and the unprecedented context of COVID-19. The focus on adaptability seeks to highlight how educators frequently respond to unique contexts in juggling concepts of quality ECEC. Consequently, a recommendation is made for future educator training to consider the importance of adaptability, in providing a useful framework for reimaging quality ECEC post COVID-19.