Yoxas/statistical_literacy huggingface dataset:
In recent decades, the rise of zoonotic diseases has emerged as a significant human health concern, highlighting the interconnectedness of human and animal health within the framework of the "One Health" (OH) concept. This study, conducted in Italy in 2023, sought to gauge the general population's awareness of OH and zoonotic diseases while identifying influencing factors. Additionally, it aimed to assess awareness of an Mpox virus vaccine, particularly pertinent due to the 2022 outbreak across Europe. The online cross-sectional study encompassed 1058 participants, revealing that 54.26% were unfamiliar with OH and zoonoses. Median knowledge scores were 12 points (IQR = 9-15) for zoonoses and 8 points (IQR = 6-11) for OH. Notably, factors such as age, economic situation, healthcare employment, educational level, and health literacy significantly influenced knowledge scores. Merely 26.8% of participants were aware of the existence of an Mpox vaccine, with healthcare workers, individuals engaged in animal-related work, and non-heterosexual men demonstrating higher awareness. The findings underscored a limited public understanding of zoonotic diseases and One Health, with variations observed across specific demographic groups. Given the potential impact on public health, urgent educational initiatives are warranted. Moreover, the study highlighted a low awareness of the Mpox vaccine, emphasizing the necessity for targeted awareness campaigns directed at both professionals and the general public.
In recent era, digitalization in the dental sciences has been observed in wide ranges. This cross-sectional study aimed to assess knowledge and practice of additive manufacturing (AM) in dentistry among university teaching faculty in Saudi Arabia. A questionnaire was prepared and validated to distribute to the different dental colleges in Saudi Arabia. The questionnaire was divided into three parts: demographic information, knowledge and practices of AM among the dental teaching faculty. After receiving all the responses, descriptive statistics were used for the frequency distribution of all the responses. A total of 367 responses were received from the different faculty members. Most of the participants were male (67.30%), holding assistant professor (52.50%) positions in the field of prosthodontics (23.40%). In terms of knowledge, even though most of the participants were aware of AM (64.30%); however, do not understand the AM techniques (33.50). Moreover, 71.90% of the participants had no experience working with AM and only 13.60% of participants used AM in their respective dental colleges. AM techniques are not commonly used in the field of dentistry in Saudi Arabia; therefore, more platforms should have created to enhance the knowledge and practice of AM in the current population.
In recent times, digital mental health interventions (DMHIs) have been proven to be efficacious; however, most are available only for English speakers, leaving limited options for non-English languages like Spanish. Research shows that mental health services in one's dominant language show better outcomes. Conversational agents (CAs) offer promise in supporting mental health in non-English populations. This study compared a culturally adapted version of an artificial intelligence (AI)-led mental health app, called Wysa, in Spanish and English. To compare user engagement patterns on Wysa-Spanish and Wysa-English and to understand expressions of distress and preferred language in both versions of Wysa. We adopted a cross-sectional retrospective exploratory design with mixed methods, analyzing users from 10 Spanish-speaking countries between 1 February and 1 August 2022. A quantitative sample A (n = 2767) was used for descriptive statistics, including user engagement metrics with a Wilcoxon test. A subset qualitative sample B (n = 338) was examined for word count differences based on valence, and a content analysis was conducted to examine idioms of distress. Compared to Wysa-English, Wysa-Spanish had more sessions (P < .001, d = 0.18) and a greater volume of disclosure of distress. In Wysa-Spanish, the average length of a conversation was significantly longer than in Wysa-English (P < .001, d = 0.44). Users preferred interventions with free text responses ("Thought recording") in Spanish (P < .01, d = 0.41), and Spanish messages were significantly longer (P < .01, d = 0.24). Wysa-Spanish saw more frequent expressions of negative emotions and feelings of self-harm and suicide. Given the high engagement within the Spanish version of Wysa, the findings demonstrate the need for culturally adapted DMHIs among non-English populations, emphasizing the importance of considering linguistic and cultural differences in the development of DMHIs to improve accessibility for diverse populations.
In recent years, a significant shift toward remote work, virtual education, and social distancing measures was witnessed, thereby leading people to increasingly depend on digital devices for communication, work, and entertainment. This increased exposure to screens has raised concerns regarding its potential impact on cognitive function. This study investigated the relationship between screen time and cognitive function among healthy young adults. One hundred forty-five healthy individuals (mean age 21.55 ± 2.84 years) participated in this cross-sectional study. Sociodemographic information including age, sex, height, weight, and level of education were obtained. Participants reported screen time using a screen time questionnaire. Cognitive function tests including, Paced Auditory Serial Addition Task (PASAT), Montreal Cognitive Assessment (MoCA) and Symbol Digit Modalities Test (SDMT) were conducted. Multilinear regression analyses were used to examine the associations between age, sex, level of education, screen time, and cognitive function. One hundred thirty-nine participants (76 women) completed the study. Increased night screen time, bachelor's educational level, and women were associated with lower PASAT scores (R2=0.258; p≤0.047). Moreover, increased night screen time was associated with lower MoCA scores (R2=0.029; p=0.035). However, no associations were found between night screen time and SDMT scores. Participants who had higher night screen exposure had lower cognitive scores in the information speed processing, working memory, calculation, and attention domains. Considering these findings, this study emphasizes on the importance of setting a future recommended screen time guidelines for young adults as well as to promote healthy cognitive habits in order to preserve cognitive function and reduce the risk of developing neurodegenerative disease in the future. Future prospective cohort studies involving a more diverse age range is needed.
In recent years, advancements in the treatment landscape for hematological malignancies, such as acute myeloid leukemia and acute lymphoblastic leukemia, have significantly improved disease prognosis and overall survival. However, the treatment landscape is changing and the emergence of targeted oral therapies and immune-based treatments has brought forth new challenges in evaluating and preventing invasive fungal diseases (IFDs). IFD disproportionately affects immunocompromised hosts, particularly those undergoing therapy for acute leukemia and allogeneic hematopoietic stem cell transplant. This review aims to provide a comprehensive overview of the pretransplant workup, identification, and prevention of IFD in patients with hematological malignancy. The pretransplant period offers a critical window to assess each patient's risk factors and implement appropriate prophylactic measures. Risk assessment includes evaluation of disease, host, prior treatments, and environmental factors, allowing a dynamic evaluation that considers disease progression and treatment course. Diagnostic screening, involving various biomarkers and radiological modalities, plays a crucial role in early detection of IFD. Antifungal prophylaxis choice is based on available evidence as well as individual risk assessment, potential for drug-drug interactions, toxicity, and patient adherence. Therapeutic drug monitoring ensures effective antifungal stewardship and optimal treatment. Patient education and counselling are vital in minimizing environmental exposures to fungal pathogens and promoting medication adherence. A well-structured and individualized approach, encompassing risk assessment, prophylaxis, surveillance, and patient education, is essential for effectively preventing IFD in hematological malignancies, ultimately leading to improved patient outcomes and overall survival.
In recent years, China has adjusted its fertility policies to optimize the population structure by implementing the two-child and three-child policies. Some patients with systemic lupus erythematosus (SLE) are considering the possibility of having a second child. The issue is whether the offspring from the second childbirth will have favorable long-term developmental outcomes. The research aims to investigate the long-term physical, neurological, and social-emotional development outcomes of children born to mothers with SLE at different parities. This study aims to offer valuable insights and references for SLE patients who are considering subsequent pregnancies and require information about potential developmental outcomes for their future children. The study conducted a follow-up of children born to SLE mothers who were admitted to the obstetrics department between January 1, 2016, and September 30, 2021. The SLE patients were categorized into two groups based on their history of live delivery: the primiparity group and the multiparity group. The physical development status, including weight, height (length), and other relevant factors, was evaluated in both groups. The Ages and Stages Questionnaires, Third Edition (ASQ-3) was utilized to assess the neurological development in five domains, encompassing communication, gross motor, fine motor, problem solving and personal-social. Social-emotional development was assessed using the Ages and Stages Questionnaires: Social-Emotional (ASQ:SE). The weight, height (length), body mass index, and ASQ-3 domain scores were standardized into Z-scores to enable comparison across various ages and genders. The study revealed that the weight Z-score and BMI Z-score of the children in the multiparity group were significantly higher compared to those in the primiparity group. However, there were no statistically significant differences in the proportions of overweight and obesity between the two groups. In terms of neurological developmental outcomes, the Z-scores of the communication and gross motor domains in the ASQ-3 assessment were significantly higher in the multiparity group compared to those in the primiparity group. The proportion of abnormal screening for social and emotional development in the children of the multiparity group was lower than that of the primiparity group, although this difference did not reach statistical significance. The long-term weight development, communication and gross motor development of children born to SLE patients in the multiparity group were better than those in the primiparity group. However, there was no significant difference in social-emotional development between the two groups.
In recent years, concern has grown about the inappropriate application and interpretation of P values, especially the use of P<0.05 to denote "statistical significance" and the practice of P-hacking to produce results below this threshold and selectively reporting these in publications. Such behavior is said to be a major contributor to the large number of false and non-reproducible discoveries found in academic journals. In response, it has been proposed that the threshold for statistical significance be changed from 0.05 to 0.005. The aim of the current study was to use an evolutionary agent-based model comprised of researchers who test hypotheses and strive to increase their publication rates in order to explore the impact of a 0.005 P value threshold on P-hacking and published false positive rates. Three scenarios were examined, one in which researchers tested a single hypothesis, one in which they tested multiple hypotheses using a P<0.05 threshold, and one in which they tested multiple hypotheses using a P<0.005 threshold. Effects sizes were varied across models and output assessed in terms of researcher effort, number of hypotheses tested and number of publications, and the published false positive rate. The results supported the view that a more stringent P value threshold can serve to reduce the rate of published false positive results. Researchers still engaged in P-hacking with the new threshold, but the effort they expended increased substantially and their overall productivity was reduced, resulting in a decline in the published false positive rate. Compared to other proposed interventions to improve the academic publishing system, changing the P value threshold has the advantage of being relatively easy to implement and could be monitored and enforced with minimal effort by journal editors and peer reviewers.
In recent years, concerns about internet addiction (IA) among children have been increasing. This study focused on the awareness of IA in elementary school teachers. A web-based anonymous survey was conducted in November 2021. The participants completed an original questionnaire about their awareness of IA. The participants were divided into three groups based on their positions in the classroom: class teachers, support teachers, and administrative teachers. Out of 283 participants, over 70% had not approached students with IA and had little practical knowledge about the disorder. Support and administrative teachers had more opportunities to interact with students with IA than class teachers (p < 0.001 in both cases). Support teachers had more opportunities to ask their colleagues about IA than class teachers (p < 0.01); similarly, administrative teachers also had more opportunities to discuss IA with colleagues than class teachers (p = 0.04). Preventive interventions are recommended for people who communicate with children with IA. Students with IA might cause anxiety among teachers; therefore, preventive education strategies should be implemented with the cooperation of psychiatrists, psychologists, and public health nurses.
In recent years, dental education has witnessed significant advancements and curriculum shifts in response to evolving healthcare needs, technological advances, and changing societal demands. As a result, dental universities worldwide have undergone substantial curriculum changes to ensure the adequate education and training of future dental professionals. The purpose of this study was to delineate the curriculum innovations over the past 20 years, with a focus on content within the current dental curriculum at universities worldwide. The articles reviewed for this manuscript were published from 2000 to June 2023. Search queries were conducted in four databases: Embase, PubMed, Web of Science, and ERIC, yielding 367 unique studies. Of these, 31 were included in the final synthesis. The nine principal subject matter themes identified in the thematic analysis of these articles were critical scientific thinking, computational thinking, global mindset, geriatric dental care, interprofessional teamwork, transition to practice, local community, integration, and lifelong learning. The themes were modeled and mapped in a three-axis figure, elucidating the interconnections between the themes. The identified themes signify the trajectory that dental education has taken and provide insights into the future course of the dental profession.
In recent years, English as a foreign language (EFL) reading instruction has emerged as a prominent and recurring research theme in the realm of education. Despite this growing interest, prior studies have not outlined the research status of EFL reading instruction from a bibliometric lens. Addressing this gap, the present study aims to provide valuable insights into the research landscape of EFL reading instruction by using scientific mapping analysis on documents sourced from the Web of Science Database between 1994 and 2023. The study found that: 1) The analysis of publication trends suggests that the field of EFL reading instruction continues to evolve, with a foreseeable ongoing increase in research output. 2) Asian countries, specifically Iran, China, and Saudi Arabia emerge as leading contributors and collaborators in terms of research on EFL reading instruction. 3) Authors mainly from Asian countries demonstrate the highest levels of productivity and citation impact. 4) The most productive and cited journals primarily originate from developed countries, notably the United Kingdom and the United States. 5) The research foci identified cover various aspects such as "technology-based instruction," "critical thinking," and "literacy skills." However, there is an emerging shift in research focus towards themes "English proficiency," "Covid-19," "technology," "blended learning" and "mobile-assisted language learning (MALL)." By shedding light on the significant concepts and trends of the research field, this study adds to the burgeoning body of literature and provides valuable guidance to new scholars seeking to enrich their knowledge and perspectives on this particular topic.
In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models.
In recent years, Malaysia has seen a surge in stem cell therapy for various medical conditions. However, the regulation of stem cell research and therapy in Malaysia faces several challenges such as the emergence of unregulated clinics and a lack of specific legislation. Some urgent measures, including enactment of specific laws, strengthened monitoring, as well as increased public awareness and education, are crucial. Therefore, stem cell therapy regulation requires concerted efforts by the policymakers, regulator bodies and healthcare professionals. This commentary discusses the current guidelines and challenges in Malaysian stem cell therapy regulation and proposes some future recommendations that could pave the way for responsible progress of stem cell research and therapy globally.
In recent years, multiple-choice Visual Question Answering (VQA) has become topical and achieved remarkable progress. However, most pioneer multiple-choice VQA models are heavily driven by statistical correlations in datasets, which cannot perform well on multimodal understanding and suffer from poor generalization. In this paper, we identify two kinds of spurious correlations, i.e., a Vision-Answer bias (VA bias) and a Question-Answer bias (QA bias). To systematically and scientifically study these biases, we construct a new video question answering (videoQA) benchmark NExT-OOD in OOD setting and propose a graph-based cross-sample method for bias reduction. Specifically, the NExT-OOD is designed to quantify models' generalizability and measure their reasoning ability comprehensively. It contains three sub-datasets including NExT-OOD-VA, NExT-OOD-QA, and NExT-OOD-VQA, which are designed for the VA bias, QA bias, and VA&QA bias, respectively. We evaluate several existing multiple-choice VQA models on our NExT-OOD, and illustrate that their performance degrades significantly compared with the results obtained on the original multiple-choice VQA dataset. Besides, to mitigate the VA bias and QA bias, we explicitly consider the cross-sample information and design a contrastive graph matching loss in our approach, which provides adequate debiasing guidance from the perspective of whole dataset, and encourages the model to focus on multimodal contents instead of spurious statistical regularities. Extensive experimental results illustrate that our method significantly outperforms other bias reduction strategies, demonstrating the effectiveness and generalizability of the proposed approach.
In recent years, numerous studies have examined the chemical compounds of petrol and petrol data for forensic research. Standard quantitative methods often assume that the variables or compounds do not have compositional constraints or are not part of a constrained whole, operating within an Euclidean vector space. However, chemical compounds are typically part of a whole, and the appropriate vector space for their analysis is the simplex. Biased and arbitrary results result when statistical analysis are applied on such data without proper pre-processing of such data. Compositional analysis of data has not yet been considered in forensic science. Therefore, we compare classical statistical analysis as applied in forensic research and the new proposed paradigm of compositional data analysis (CoDa). It is demonstrated how such analysis improves the analysis in petrol and forensic science. Our study shows how principal component analysis (PCA) and classification results are affected by the preprocessing steps performed on the raw data. Our results indicate that results from a log ratio analysis provides a better separation between subgroups of the data and leads to an easier interpretation of the results. In addition, with a compositional analysis a higher classification accuracy is obtained. Even a non-linear classification method - in our case a random forest - was shown to perform poorly when applied without using compositional methods. Moreover, normalization of samples due to laboratory/unit-of-measurement effects is no longer necessary, since the composition of an observation is in compositional thinking equivalent to a multiple of it, because the used (log) ratios on raw and log ratio transformed data are equal. Petrol data from different petrol stations in Brazil are used for the demonstration. This data is highly susceptible to counterfeit petrol. Forensic analysis of its chemical elements requires non-biased statistical analysis designed for compositional data to detect fraud. Based on these results, we recommend the use of compositional data methods for gasoline and petrol chemical element analysis and gasoline product characterization, authentication and fraud detection in forensic sciences.