Yoxas/statistical_literacy huggingface dataset:
This paper aims to examine the psychometric properties of social capital indicators, comparing Black and White respondents to identify the extent of measurement invariance in social capital by race. We used data from the longitudinal study Midlife in the United States (MIDUS), waves 1 through 3 (1995-2016). Data were from 6513 respondents (5604 White and 909 Black respondents). Social capital indicators were social cohesion, contributions to community, and community involvement. We used Structural Equation Modeling and Item Response Theory methods to test for measurement invariance in social capital by race. We observed violations of longitudinal and multi-group measurement invariance (MI) at configural and metric levels on two scales. Factor structures and indicator loadings were inconsistent over time. In IRT analysis, 'Many people come for advice' exhibited Differential Item Functioning (DIF), indicating a consistent advantage for White respondents on the contributions to community scale. Despite similar social capital levels (P(χ2,2) = 0.00), DIF was found in all contributions to community items and some community involvement items when examining race and education interaction. Invariance issues in social capital items suggest potential biases in comparing Black and White respondents. Recognizing these biases is essential. Future social capital research should assess existing data assumptions and involve stakeholders from diverse communities in creating new items.
This paper aims to explore the change of learning mode of college students from physical courses to online courses due to the impact of the COVID-19 pandemic. The questionnaire survey method is used to conduct research on the behavior intentions of college students in online teaching under the pandemic. A total of 600 questionnaires are distributed, and 530 questionnaires are collected, for a recovery rate of 88%. A total of 493 supported questionnaires are received, for an effective recovery rate of 93%. Descriptive statistics of data analysis are used to analyze the distribution of background variables of college students, and a structural equation model is used to analyze and verify the impact of external variables (trust, convenience, perceived critical mass) on the technology acceptance model (perceived usefulness, perceived ease of use, attitude, and behavior intention). The results found no significant impact of the trust of college students in online teaching on the perceived usefulness, and significant impact of trust on the perceived ease of use. There is significant impact of convenience on perceived usefulness, and no significant impact of convenience on perceived ease of use. There is no significant impact of perceived critical mass on perceived usefulness, and significant impact of perceived critical mass on perceived ease of use. There is significant impact of perceived ease of use on perceived usefulness, and significant impact of perceived usefulness on attitude. There is significant impact of perceived ease of use on attitude, and significant impact of attitude on behavior intention. Based on the research results, practical suggestions and research suggestions are proposed in this research, which can be used as a reference for college students to use online courses for learning.
This paper aims to highlight the vital importance of investing in advanced practice nursing (APN) for enhancing emergency care throughout Africa. APN's role is increasingly recognized as pivotal in optimizing healthcare, particularly in emergency settings in Africa. It offers improved patient care quality and strengthens the healthcare workforce. Evidence is drawn from successful implementations of APN in various healthcare environments. This includes the development of APN-specific curricula and training, mentorship initiatives, clinical supervision, and defining advanced nursing roles within healthcare organizations. Investing in APNs in emergency care in Africa can lead to improved quality and access to care, cost-effectiveness, enhanced patient outcomes and satisfaction, and opportunities for professional development and career advancement in the healthcare workforce. Despite facing barriers in implementation, APN in emergency care presents innovative solutions. Investing in APN can help healthcare entities and policymakers surmount these challenges, providing specialized patient care and improving health outcomes. The discussion emphasizes the benefits such as enhanced access to care, reduced healthcare costs, and improved patient outcomes, alongside bolstering the healthcare workforce. The necessity and benefits of investing in APN for emergency care in Africa are clear. It is crucial for improving healthcare delivery and outcomes. APN investment leads to a more competent and efficient nursing workforce, capable of addressing complex emergencies and improving patient care. The paper advocates for policies that support APN development and integration into the healthcare system, emphasizing the need for research to assess APN's long-term impact and establish best practices for its implementation in emergency care across Africa.
This paper aims to propose an approach leveraging Artificial Intelligence (AI) to diagnose thalassemia through medical imaging. The idea is to employ a U-net neural network architecture for precise erythrocyte morphology detection and classification in thalassemia diagnosis. This accomplishment was realized by developing and assessing a supervised semantic segmentation model of blood smear images, coupled with the deployment of various data engineering techniques. This methodology enables new applications in tailored medical interventions and contributes to the evolution of AI within precision healthcare, establishing new benchmarks in personalized treatment planning and disease management.
This paper aims to solve the arterial input function (AIF) determination in dynamic contrast-enhanced MRI (DCE-MRI), an important linear ill-posed inverse problem, using the maximum entropy technique (MET) and regularization functionals. In addition, estimating the pharmacokinetic parameters from a DCE-MR image investigations is an urgent need to obtain the precise information about the AIF-the concentration of the contrast agent on the left ventricular blood pool measured over time. For this reason, the main idea is to show how to find a unique solution of linear system of equations generally in the form of [Formula: see text] named an ill-conditioned linear system of equations after discretization of the integral equations, which appear in different tomographic image restoration and reconstruction issues. Here, a new algorithm is described to estimate an appropriate probability distribution function for AIF according to the MET and regularization functionals for the contrast agent concentration when applying Bayesian estimation approach to estimate two different pharmacokinetic parameters. Moreover, by using the proposed approach when analyzing simulated and real datasets of the breast tumors according to pharmacokinetic factors, it indicates that using Bayesian inference-that infer the uncertainties of the computed solutions, and specific knowledge of the noise and errors-combined with the regularization functional of the maximum entropy problem, improved the convergence behavior and led to more consistent morphological and functional statistics and results. Finally, in comparison to the proposed exponential distribution based on MET and Newton's method, or Weibull distribution via the MET and teaching-learning-based optimization (MET/TLBO) in the previous studies, the family of Gamma and Erlang distributions estimated by the new algorithm are more appropriate and robust AIFs.
This paper assesses two different theories for explaining consciousness, a phenomenon that is widely considered amenable to scientific investigation despite its puzzling subjective aspects. I focus on Integrated Information Theory (IIT), which says that consciousness is integrated information (as ϕMax) and says even simple systems with interacting parts possess some consciousness. First, I evaluate IIT on its own merits. Second, I compare it to a more traditionally derived theory called Neurobiological Naturalism (NN), which says consciousness is an evolved, emergent feature of complex brains. Comparing these theories is informative because it reveals strengths and weaknesses of each, thereby suggesting better ways to study consciousness in the future. IIT's strengths are the reasonable axioms at its core; its strong logic and mathematical formalism; its creative "experience-first" approach to studying consciousness; the way it avoids the mind-body ("hard") problem; its consistency with evolutionary theory; and its many scientifically testable predictions. The potential weakness of IIT is that it contains stretches of logic-based reasoning that were not checked against hard evidence when the theory was being constructed, whereas scientific arguments require such supporting evidence to keep the reasoning on course. This is less of a concern for the other theory, NN, because it incorporated evidence much earlier in its construction process. NN is a less mature theory than IIT, less formalized and quantitative, and less well tested. However, it has identified its own neural correlates of consciousness (NCC) and offers a roadmap through which these NNCs may answer the questions of consciousness using the hypothesize-test-hypothesize-test steps of the scientific method.
This paper considers the appearance of indications of useful acoustic signals in the signal/noise mixture. Various information characteristics (information entropy, Jensen-Shannon divergence, spectral information divergence and statistical complexity) are investigated in the context of solving this problem. Both time and frequency domains are studied for the calculation of information entropy. The effectiveness of statistical complexity is shown in comparison with other information metrics for different signal-to-noise ratios. Two different approaches for statistical complexity calculations are also compared. In addition, analytical formulas for complexity and disequilibrium are obtained using entropy variation in the case of signal spectral distribution. The connection between the statistical complexity criterion and the Neyman-Pearson approach for hypothesis testing is discussed. The effectiveness of the proposed approach is shown for different types of acoustic signals and noise models, including colored noises, and different signal-to-noise ratios, especially when the estimation of additional noise characteristics is impossible.
This paper contributes to the debate about the role of Online Health Communities (OHCs) in the healthcare system by concentrating on the kind of information sought and shared by their members. The paper focuses on OHCs for diabetes and discusses the main findings of a qualitative study conducted in Italy and Poland. The Uses and Gratifications approach informed the study, while content analysis was used to perform the analysis. The findings show that OHCs' role goes beyond information and emotional support, which relies on expertise by experience. Indeed, the lack of basic knowledge constituting the essential diabetes literacy for self-management was partially compensated by peer exchange in the OHCs. This raises at least two problems: quality and reliability of the information shared online, and consequences in terms of the equity that a healthcare system provides.
This paper critically evaluates the current status of Information and Communication Technology (ICT) policies for gifted education in Australia, highlighting the lack of a comprehensive understanding and analysis of the heterogeneity across these policies. Despite the increasing recognition of the importance of ICT's importance in meeting the unique needs of gifted learners, there is a dearth of research systematically investigating the variations in policy frameworks, approaches to ICT integration, and their impact on educational outcomes for gifted students. This research problem necessitates an in-depth exploration of the heterogeneous nature of Australian ICT policies and their implications for promoting equitable access and fostering effective educational experiences. To address this gap, relevant policy documents and research articles on Australian ICT policies for gifted education were collected via Scopes, Web of Sciences, and Google Scholar. The search yielded six policy documents and 14 critical research articles. Our findings reveal that while Australia has definite policies for educating gifted students, these policy documents rarely mention ICT policies specifically related to gifted education. In fact, many elements of these policies only imply use of ICT as facilitation factors. Research articles highlight the inadequacies of sufficient ICT policies for gifted children in rural and remote locations, especially as they pertain to Aboriginal peoples, thereby violating the principles of equity in education. Moreover, the performance of gifted students on Science, Technology, Engineering, and Mathematics (STEM) subjects has been declining on international tests, indicating the inadequacies of Australian policies for the education of gifted students in these areas. Here, ICT policies can provide substantial solutions to address these challenges.
This paper describes a postgraduate training programme in child and adolescent mental health (CAMH) in Nigeria. It explains the background, curriculum development, teaching, evaluation and outcomes. By its 10th year the programme had trained 166 CAMH professionals from 14 African countries. Many of the graduates are running clinical CAMH services in their countries, mostly pioneered by them. They are also conducting CAMH training, including as faculty on the programme, and some are in international CAMH leadership roles. Key success elements of the programme that can be replicated in other low- and middle-income countries include international partnership, adopting a train-the-trainer approach, using a curriculum that covers clinical aspects of CAMH while also developing leadership and research skills, use of free-access training resources, and access to seed funding.
This paper describes an example of collaborative course development, in which occupational therapy faculty members designed a two-course sequence for teaching content related to occupational therapy with children and youth. They used a backward course design approach and performance-based learning objectives to create alignment between Accreditation Council for Occupational Therapy Education (ACOTE) standards, course assignments and instructional content. The authors present examples from their course design, along with evidence-based resources to guide educators working on developing new courses or revising existing courses. Outcomes achieved from four years of teaching and refining the developed courses are also described.
This paper describes some of the lessons learned during the COVID-19 pandemic from a study conducted with a group of clinical teachers and undergraduate dental students at the Faculty of Dentistry, Oral & Craniofacial Sciences (FoDOCS) at King's College London about the use of a combination of remote, online and in-person teaching methods that resumed from June 2020. In the narrative research, participants shared their experiences delivering online clinical workshops and their previous experiences delivering face-to-face sessions online, both during and before the pandemic. We conducted remote interviews with the participants via video conferencing, which were recorded, transcribed, and analysed using thematic analysis. Narrative accounts revealed commonalities organised into seven themes, highlighting some of the challenges encountered during the pandemic and providing insights into addressing different curricular constraints and concerns when utilising various delivery modes during emergency situations, such as pandemics. In our study, we concluded that students and teachers benefit from dissociating clinical learning from clinical treatment sessions to focus on the educational intent and content before applying them chairside with patients. Throughout the course, students and teachers were challenged by a lack of engagement. In addition, it is important to examine the online fatigue highlighted by both students and teachers and identify ways to improve time, literacy, and facilitation to create a more conducive learning environment.
This paper describes the cognitive interview phase of the development of two brief surveys, the Movement Behaviour Questionnaire-Baby (MBQ-B) and Movement Behaviour Questionnaire-Child (MBQ-C), which measure the duration of physical activity, screen time, and sleep of children aged 0-5 years. The aims were (1) review the format, content, and clarity of questionnaire items and response options, (2) understand how parents retrieve, encode, and formulate responses when asked about their child's movement behaviours, and (3) identify potential sources of response error and make appropriate modifications. Interviews with parents of children aged 0-5 years were conducted using concurrent think-aloud techniques and probing questions. Parents reviewed the MBQ-B and/or MBQ-C depending on the developmental stage of their child(ren). Twenty-nine interviews were conducted with 20 parents, over four iterative rounds. Participants recalled usual family routines and rules when estimating the duration/frequency of behaviours. To estimate active play, parents referred to the child's daily routine considering wake and bedtimes, naps, and mealtimes. Participants were influenced by the examples provided, being unable to interpret these as exemplars only. Decomposing general items into specific questions with examples was well received. Use of numeracy skills when estimating duration was evident. Interviews informed revisions to item wording, examples, and recall prompts, which will be taken forward into the MBQ-B and MBQ-C validation studies. Utilising cognitive interviewing can enhance confidence that questionnaire items are correctly interpreted and understood by participants.
This paper describes the implementation of curricula for Liberia's first-ever psychiatry training programme in 2019 and the actions of the only two Liberian psychiatrists in the country at the time in developing and executing a first-year postgraduate psychiatry training programme (i.e. residency) with support from international collaborators. It explores cultural differences in training models among collaborators and strategies to synergise them best. It highlights the assessment of trainees' (residents') basic knowledge on entry into the programme and how it guided immediate and short-term priority teaching objectives, including integrated training in neuroscience and neurology. The paper describes the strengths and challenges of this approach as well as opportunities for continued growth.
This paper describes the past, present, and future of medical education in Cambodia. Although doctor training began in 1902, the first medical school was not founded until 1946. Since the colonial era, the curriculum and teaching strategies have been strongly influenced by the French system, dominated by didactic lectures and the apprenticeship model. Three chronic issues have plagued medical education in the country following the Khmer Rouge regime: a shortage of doctors, poor-quality training, and lack of relevance to the current and future population needs. An increasing number of medical schools and yearly student enrollment have addressed the first issue. Today, the fundamental challenges have shifted from quantity to ensuring the quality and relevance of medical education. Competency-based medical education (CBME) has been adopted as a new curricular model to tackle the latter two issues. Active collaboration between government institutions, public universities, and development partners drives this curricular reform at the national and institutional levels. This paper further examines the challenges associated with medical education and proposes recommendations.
This paper describes the use of Interpretative Phenomenological Analysis (IPA) in qualitative research and its adaptability to medical research. Whilst presenting the main tenets of the approach, it also highlights its' strengths in helping medical professionals gain rich information about their service users' needs, symptoms and experiences, via research. It discusses the application of IPA on various levels such as by contextualising quantitative data or gaining insight into patients' understanding of clinical guidelines. The paper also describes methodological choices of the approach and the reasoning behind them. It outlines the sample, data collection tools and method of analysis utilised in IPA. To help researchers locate the particular use of this approach on the qualitative research landscape, this paper also compares its' use to that of other qualitative approaches. Finally, it discusses ways of evaluating IPA studies and hence, to ensure that such studies respect the philosophical roots of qualitative research in general, and those of IPA in particular.
This paper discusses regression analysis of interval-censored failure time data arising from semiparametric transformation models in the presence of missing covariates. Although some methods have been developed for the problem, they either apply only to limited situations or may have some computational issues. Corresponding to these, we propose a new and unified two-step inference procedure that can be easily implemented using the existing or standard software. The proposed method makes use of a set of working models to extract partial information from incomplete observations and yields a consistent estimator of regression parameters assuming missing at random. An extensive simulation study is conducted and indicates that it performs well in practical situations. Finally, we apply the proposed approach to an Alzheimer's Disease study that motivated this study.
This paper discusses the benefits of international collaborations for advanced practice nursing education. It identifies new perspectives and innovative practices to enhance cultural competency. Competent, well-trained advanced practice nurses (APNs) are necessary to provide high-quality and safe patient care, improve access to care, and address health disparities that are no longer geographically bound. In 2021, an international network of advanced practice educators established an active learning program to teach students their role in global citizenship and increase awareness of health disparities. APN students from Scotland, Wales, Minnesota, Houston, and Rotterdam participated in presentations, online discussions, and in-country scholarships. Growing health disparities have created the need for efficient international collaboration to develop new concepts, approaches, and bidirectional exchange of experiences, culture, and knowledge. Integrating global health into curricula engages students' curiosity and integrates education, research, practice, and leadership while improving cultural competency. Forty-two students participated in the international presentations. The students strongly believed in the benefit of international collaboration and the need for a universal role for the advanced practice nurse. They responded positively to sharing cultural and clinical experiences. The recent global health challenge supported the development of innovative methods to deliver education and created an opportunity for advanced practice students to develop cultural competence and critical thinking. Collaborative solutions are essential to education and healthcare as we move forward in the 21st century. Robust international collaborations have enabled the development of cultural competence and critical thinking. These are crucial elements for advanced practice roles.