Yoxas/statistical_literacy huggingface dataset:
As a subset of genetic abnormalities, subtelomeric deletions have been found in 7-10% of individuals with mental retardation (MR). One subtelomeric deletion, Wolf-Hirschhorn syndrome (WHS), causes mild to severe MR, but the cognitive-behavioral features of individuals with WHS have not been studied systematically. To that end, we administered a comprehensive cognitive-behavioral battery to 12 children with WHS, ages 4-17 years, who also had some expressive language. Using the Stanford-Binet (4th Edition), we found cognitive deficits ranged from mild to severe, with mean IQ = 44.1. Interviewing parents with the Vineland Adaptive Behavior Scales, we found mean adaptive behavior score (DQ) = 37.3, with females exhibiting slightly higher scores than males. Cognitive profiles indicated relative strengths in Verbal and Quantitative Reasoning. Adaptive behavior profiles noted significant relative strengths in the Socialization Domain. These cognitive-behavioral profiles differed from children with other subtelomeric deletion syndromes, 2q37 or 8p23. Attention deficits and hyperactivity (ADHD) were observed in 7/12 (58%) of the children we tested. One child attained a score on the Child Autism Rating Scale (CARS) suggestive of mild autism. We conclude that different genetic disorders, which cause MR, produce diverse cognitive-behavioral profiles. Consequently, cognitive-behavioral profiles of children with MR need to be assessed more comprehensively.
As acceptance of AI platforms increases, more patients will consider these tools as sources of information. The ChatGPT architecture utilizes a neural network to process natural language, thus generating responses based on the context of input text. The accuracy and completeness of ChatGPT3.5 in the context of Inflammatory Bowel Disease remains unclear. In this prospective study, 38 questions worded by IBD patients were inputted into ChatGPT3.5. The following topics were covered: 1) CD, UC and malignancy, 2) maternal medicine 3) infection and vaccination 4) complementary medicine. Responses given by Chat GPT were assessed for accuracy (1 - completely incorrect to 5 - completely correct) and completeness (3-point Likert scale; range 1 - incomplete to 3 - complete) by 14 expert gastroenterologists, in comparison with relevant ECCO guidelines. In terms of accuracy, most replies (84.2%) had a median score of ≥4 (IQR:2) and a mean score of 3.87 (SD: +/- 0.6). For completeness, 34.2% of the replies had a median score of 3 and 55.3 % had a median score of between 2 and <3. Overall, the mean rating was 2.24 (SD: +/- 0.4, Median:2 IQR :1). Though group 3 and 4 had a higher mean for both accuracy and completeness, there was no significant scoring variation between the 4 question groups (Kruskal-Wallis test p:>0.05). However, statistical analysis for the different individual questions revealed a significant difference both for accuracy (p<0.001) and completeness (p<0.001). The questions which rated the highest for both accuracy and completeness were related to smoking, while the lowest rating was related to screening for malignancy and vaccinations especially in the context of immunosuppression and family planning. This is the first study to demonstrate the capability of an AI-based system to provide accurate and comprehensive answers to real-world patient queries in IBD. AI systems may serve as a useful adjunct for patients, in addition to standard of care in clinic and validated patient information resources. However, responses in specialist areas may deviate from evidence-based guidance and the replies need to give more firm advice.
As an education model that focuses on the cultivation of students' creativity and practical ability, the integration of maker education and the development of artificial intelligence is of great significance. In order to analyze and study the application effect of artificial intelligence in maker education, based on this, this study adopts the method of questionnaire and case analysis to investigate and analyze students from three dimensions: learning experience, learning attitude and learning emotion, learning effect and transfer. The survey results show that, on the whole, the integration of artificial intelligence technology into maker education can significantly improve students' learning feelings and attitudes, and enhance the enthusiasm of learning emotions. The research also finds that it has a positive impact on students' learning effect and transfer ability. Learning experience, learning attitude and learning emotion, learning effect and learning transfer are related to gender, teaching time, teaching subjects or majors. Therefore, the article will suggest creating a maker cultural atmosphere, creating a maker resource space, and improving the maker education system. This provides a valuable reference for further promoting the development of maker education courses in the field of artificial intelligence.
As an important part of China's higher education, higher vocational education occupies an extraordinarily important position in China's higher education system. In order to clarify the literacy of higher vocational students, carry forward their excellent quality, and correct their bad habits, a quantitative evaluation and optimization decision-making research on the cultivation of humanistic literacy of higher vocational students based on data mining technology is proposed. By using data mining technology, the important data of students can be obtained quickly; by using advantages of information integration, the cultivation of humanistic quality of higher vocational students is evaluated from a correct perspective; by strengthening the education of campus culture construction, students' moral quality can be enhanced, students' enthusiasm for learning can be mobilized, the advantages of new media's public opinion orientation can be given full play, and a humanistic and healthy growth environment for vocational students can be created. Through experiments, it is proved that data mining can better evaluate the humanistic quality of students. During the learning process, the humanistic quality evaluation of female college students reaches 95%, and the overall quality of male and female gradually rises to 80%.
As an inherent part of epidemiologic research, practical decisions made during data collection and analysis have the potential to impact the measurement of disease occurrence as well as statistical and causal inference from the results. However, the computational skills needed to collect, manipulate, and evaluate data have not always been a focus of educational programs, and the increasing interest in "data science" suggest that data literacy has become paramount to ensure valid estimation. In this article, we first motivate such practical concerns for the modern epidemiology student, particularly as it relates to challenges in causal inference; second, we discuss how such concerns may be manifested in typical epidemiological analyses and identify the potential for bias; third, we present a case study that exemplifies the entire process; and finally, we draw attention to resources that can help epidemiology students connect the theoretical underpinning of the science to the practical considerations as described herein.
As artificial intelligence (AI) continues to evolve rapidly, its integration into nursing education is inevitable. This article presents a narrative exploring the implementation of generative AI in nursing education and offers a guide for its strategic use. The exploration begins with an examination of the broader societal impact and uses of artificial intelligence, recognizing its pervasive presence and the potential it holds. Thematic analysis of strengths, weaknesses, opportunities, and threats collected from nurse educators across the southeastern United States in this case-based descriptive study used four codes: time, innovation, critical thinking, and routine tasks. Findings from the qualitative analysis revealed the overarching themes that AI can serve as both a tool and a tyrant, offering opportunities for efficiency and innovation while posing challenges of transparency, ethical use, and AI literacy. By establishing ethical guidelines, fostering AI literacy, and promoting responsible implementation in nursing education with a clear articulation of expectations, nurse educators can guide and guard the use of generative AI. Despite the concerns, the transformative potential of generative AI to enhance teaching methodologies and prepare students for the interprofessional health-care workforce provides a multitude of innovative opportunities for teaching and learning.
As cancer patients increasingly use chatbots, it is crucial to recognize ChatGPT's potential in enhancing health literacy while ensuring validation to prevent misinformation. This study aims to assess ChatGPT-3.5's capability to provide appropriate staging and treatment recommendations for head and neck mucosal malignancies for vulnerable populations. Forty distinct clinical vignettes were introduced into ChatGPT to inquire about staging and treatment recommendations for head and neck mucosal malignancies. Prompts were created based on head and neck cancer (HNC) disease descriptions (cancer location, tumor size, lymph node involvement, and symptoms). Staging and treatment recommendations according to the 2021 National Comprehensive Cancer Network (NCCN) guidelines were scored by three fellowship-trained HNC surgeons from two separate tertiary care institutions. HNC surgeons assessed the accuracy of staging and treatment recommendations, such as the completeness of surgery and the appropriateness of treatment modality. Whereas ChatGPT's responses were 95% accurate at recommending the correct first-line treatment based on the 2021 NCCN guidelines, 55% of the responses contained inaccurate staging. Neck dissection was incorrectly omitted from treatment recommendations in 50% of the cases. Moreover, 40% of ChatGPT's treatment recommendations were deemed unnecessary. This study emphasizes ChatGPT's potential in HNC patient education, aligning with NCCN guidelines for mucosal malignancies, but highlights the importance of ongoing refinement and scrutiny due to observed inaccuracies in tumor, nodal, metastasis staging, incomplete surgery options, and inappropriate treatment recommendations. Otolaryngologists can use this information to caution patients, families, and trainees regarding the use of ChatGPT for HNC education without expert guidance.
As compared to other parts of the country, vaccination coverage and literacy rate in district Mewat, State Haryana (India) had been low, that is, 20.8-27% and 54%, respectively. National immunization program of the country was being implemented primarily through the field workers, and accredited social health activists (ASHAs) were one of the key grass root level link workers. Hence, this study was carried out with the objective to identify barriers to childhood vaccination by field staff in field practice area of SHKM Govt Medical College Nalhar, Mewat as perceived by ASHAs and health workers. The current study was a qualitative research which was conducted in the field practice area attached to SHKM Government Medical College Nalhar Mewat. Focus Group Discussions (FGDs) were carried out among health workers (MPHW-F/M) and ASHAs. None. The barriers to childhood vaccination as identified in the study are pain during vaccination and other side effects, additional expenditure on treatment of side effects, worsening of interpersonal relations of the functionaries (workers/ASHAs) with the beneficiaries, extra work burden, unawareness of the benefits of vaccination, myth/belief of potential risk of impotency in adulthood, denial by elders, lack of cash benefits, inaccessibility to vaccination services due to remote work places, people's beliefs in supernatural causes of childhood diseases, delayed BCG vaccination, etc., The barriers to childhood vaccination from the perspective of ASHAs and health workers are explored and identified which can be utilized in tailoring the efforts and strategies to improve the vaccination coverage.
As countries strive to achieve sustainable development goal 3.2, high-quality medical education is crucial for high-quality neonatal care. Women are encouraged to deliver in health units attended by a skilled team. Traditionally, the team is doctors and nurses, but they are members of a large group of interdependent experts from other disciplines. Each discipline trains separately, yet the goal of good neonatal care is common to all. The use of interprofessional education breaks down these professional silos improving collaborative practice and promoting excellent clinical care. Introduction of new educational materials and training requires a rigorous approach to ensure sustainability. An extensive needs assessment identified gaps in neonatal training. Specifically, there was a lack of inclusion of medical devices used in clinical care. In each country, national key stakeholders came together to develop and revise their own neonatal curricula, trainings or guidelines. A core writing education team were tasked to develop evidence-based materials on pertinent medical devices to include in these national materials. These then underwent internal and external review. A provider course for biomedical engineers and technicians was introduced. Skills labs were established to improve practical skills teaching. To improve the quality of teaching, a NEST360 generic instructors course (GIC) was developed. Twenty modules, 14 scenarios, 17 job aids and 34 videos have been published to date. Materials have been embedded into neonatal curricula and national trainings. Forty-one skills labs were installed in pre-service learning institutions and, up to June 2022, have been used by 7281 students. Pre- and in-service interprofessional training was implemented at all NEST360 institutions (clinical and biomedical). GIC courses were conducted at least twice a year in all countries. Three hundred seventeen nurses, biomedical and clinical staff have undertaken the GIC in all four countries. GIC participants report that the course has very positively influenced their teaching practice. Inclusion of key stakeholders throughout has ensured training is embedded within the four countries. Use of interprofessional education and inclusion of biomedical engineers and technicians has been very successful. Introduction of the GIC has developed a pool of high-quality educators for neonatal care. This approach has ensured that high-quality interprofessional neonatal training is included within national agendas for neonatal care and beyond.
As digital health expands, reliance on digital endpoints is rapidly increasing to improve diagnostic accuracy and management in the healthcare field. Digital endpoints are beneficial to monitor how patient's clinical information is processed outside of a clinical setting. Implications of cardiac digital endpoints play a role in allowing patients to track their clinical data outside of a clinical setting. Advances in cardiac digital endpoints involve advanced devices and implants, trackers, and artificial intelligence. We will explore further digital endpoints within cardiology and threats as well as security concerns for policies to focus on the maintenance of safe patient health data analysis, transmission, and processing. As digital endpoints evolve and expand, policymakers must ensure there is adequate cybersecurity surrounding them. We believe guidelines should be in place to make sure data is accessed solely on a secure connection and access to digital literacy for patients should be readily available.
As digital health services are increasingly developing and becoming more interactive in Serbia, a comprehensive instrument for measuring eHealth literacy (EHL) is needed. This study aimed to translate, culturally adapt, and investigate the psychometric properties of the Serbian version of the eHealth Literacy Questionnaire (eHLQ); to evaluate EHL in the population of primary health care (PHC) users in Serbia; and to explore factors associated with their EHL. The validation study was conducted in 8 PHC centers in the territory of the Mačva district in Western Serbia. A stratified sampling method was used to obtain a representative sample. The Translation Integrity Procedure was followed to adapt the questionnaire to the Serbian language. The psychometric properties of the Serbian version of the eHLQ were analyzed through the examination of factorial structure, internal consistency, and test-retest reliability. Descriptive statistics were calculated to determine participant characteristics. Differences between groups were tested by the 2-tailed Students t test and ANOVA. Univariable and multivariable linear regression analyses were used to determine factors related to EHL. A total of 475 PHC users were enrolled. The mean age was 51.0 (SD 17.3; range 19-94) years, and most participants were female (328/475, 69.1%). Confirmatory factor analysis validated the 7-factor structure of the questionnaire. Values for incremental fit index (0.96) and comparative fit index (0.95) were above the cutoff of ≥0.95. The root mean square error of approximation value of 0.05 was below the suggested value of ≤0.06. Cronbach α of the entire scale was 0.95, indicating excellent scale reliability, with Cronbach α ranging from 0.81 to 0.90 for domains. The intraclass correlation coefficient ranged from 0.63 to 0.82, indicating moderate to good test-retest reliability. The highest EHL mean scores were obtained for the understanding of health concepts and language (mean 2.86, SD 0.32) and feel safe and in control (mean 2.89, SD 0.33) domains. Statistically significant differences (all P<.05) for all 7 eHLQ scores were observed for age, education, perceived material status, perceived health status, searching for health information on the internet, and occupation (except domain 4). In multivariable regression models, searching for health information on the internet and being aged younger than 65 years were associated with higher values of all domain scores except the domain feel safe and in control for variable age. This study demonstrates that the Serbian version of the eHLQ can be a useful tool in the measurement of EHL and in the planning of digital health interventions at the population and individual level due to its strong psychometric properties in the Serbian context.
As dynamic graphs have become indispensable in numerous fields due to their capacity to represent evolving relationships over time, there has been a concomitant increase in the development of Temporal Graph Neural Networks (TGNNs). When training TGNNs for dynamic graph link prediction, the commonly used negative sampling method often produces starkly contrasting samples, which can lead the model to overfit these pronounced differences and compromise its ability to generalize effectively to new data. To address this challenge, we introduce an innovative negative sampling approach named Enhanced Negative Sampling (ENS). This strategy takes into account two pervasive traits observed in dynamic graphs: (1) Historical dependence, indicating that nodes frequently reestablish connections they held in the past, and (2) Temporal proximity preference, which posits that nodes are more inclined to connect with those they have recently interacted with. Specifically, our technique employs a designed scheduling function to strategically control the progression of difficulty of the negative samples throughout the training. This ensures that the training progresses in a balanced manner, becoming incrementally challenging, and thereby enhancing TGNNs' proficiency in predicting links within dynamic graphs. In our empirical evaluation across multiple datasets, we discerned that our ENS, when integrated as a modular component, notably augments the performance of four SOTA baselines. Additionally, we further investigated the applicability of ENS in handling dynamic graphs of varied attributes. Our code is available at https://github.com/qqaazxddrr/ENS.
As education systems worldwide begin to accept and implement computational thinking, the educators of both elementary and higher education are considering the cultivation of students' computational thinking abilities. It is hoped that students effectively analyze and deconstruct all kinds of complex issues with computational thinking, and seek computer-executable ways to solve real-world problems. Through the integration of program education, students can learn and develop the abilities to practically apply their theoretical learning in information technology education. With the promotion of the concept of multicultural education, an increasing number of educational arenas are gradually introducing the concept of multicultural education to inculcate in students respect for different ethnic cultures via multicultural integration. In this study, unmanned aerial vehicle (UAV) technology was used to introduce culturally responsive teaching. The objective was to build a UAV-assisted culturally responsive teaching environment for multi-ethnic students that is based on their different thinking mechanisms formed by their respective cultures and living environments. Multi-ethnic students can attempt to solve problems employing computational thinking that is implemented when programing to control UAV. With the influence of culturally responsive teaching, the UAV-assisted learning strategies helped students and teachers of multi-ethnic groups understand different cultures and learn through mutual aid and cooperation. This study discussed the computational thinking abilities via different dimensions: logical thinking, programming ability, and cultural respect. The results showed that the introduction of UAV-assisted culturally responsive teaching method benefits not only indigenous students. For Han Chinese students as well, owing to the influence of cultural understanding, their overall learning effectiveness and cultural respect will be strengthened. Thus, this method improves the learning effectiveness in programming of multi-ethnic students, as well as of students with weaker prior programming ability. The method can also enhance the cognition and comprehension of different cultures in multicultural education.