Yoxas/statistical_literacy huggingface dataset:
Geriatric disaster nursing simulation curriculum use scenarios with trauma-based topics that may contribute to lack of psychological safety in learners. This learning condition lowers students' self-efficacy, so supportive debriefing is needed to provide psychological safety for learners. The aims of this study are to develop and apply a geriatric disaster nursing simulation and to evaluate the effectiveness of a supportive debriefing model on psychological safety, learning self-efficacy, and counseling self-efficacy. A geriatric nursing simulation scenario, checklists, and a standardized patient were developed based on the Analysis-Design-Development-Implementation-Evaluation model. Nursing students were recruited as participants and randomly assigned to either the experimental group, conventional group, or control group. All 3 groups participated in the same geriatric disaster nursing simulation scenario, after which the experimental group used a supportive debriefing model-the SENSE (share-explore-notice-support-extend) model. The conventional group used a common debriefing model, the GAS (gathering-analyzing-summarizing) model, and the control group received simple comments with no debriefing model. The effects of the debriefing models on psychological safety, learning self-efficacy, and counseling self-efficacy were measured by self-report questionnaires. The aggregate scores of the measures were 222 for counseling self-efficacy, 70 for learning self-efficacy, and 50 for psychological safety. Higher scores within these measures corresponded to heightened capabilities. The mean score of counseling self-efficacy in the SENSE model group was significantly increased after the simulation with the supportive debriefing from 142.80 ± 11.43 to 164.53 ± 15.48 (Z = -3.411, P = 0.001). In addition, the SENSE model group and the GAS model group had significantly higher scores in counseling self-efficacy, learning self-efficacy, and psychological safety than those of the control group. However, the SENSE model group had a significantly higher score in psychological safety than that of the GAS model group. The SENSE debriefing model is recommended as a supportive debriefing model to foster students' psychological safety in disaster nursing simulations.
German university otorhinolaryngology has a need for digital teaching content. Case-based e‑learning represents a digital teaching methodology. The data on student use of case-based e‑learning in university teaching of ENT medicine are limited. The aim of this work was to determine the extent to which voluntary case-based e‑learning is used by otolaryngology students and what influence the quality of the e‑learning has on motivation to use e‑learning and on the interest in otolaryngology. Fifteen voluntary e‑learning cases were created based on the content of the ENT lecture in the winter semester 2022/2023. Subsequently, a descriptive evaluation of the usage statistics of the cases of 157 students was conducted. Likewise, an evaluation of the quality of the e‑learning as well as the motivation to complete it and the interest in otorhinolaryngology was carried out using a voluntary questionnaire. Voluntary case-based e‑learning was used to varying degrees by 66% of the students. The quality of e‑learning correlated significantly with the motivation and the interest in otolaryngology. The teaching content of otorhinolaryngology can be implemented sufficiently in case-based e‑learning and is characterized by satisfactory student acceptance. Integration should be accomplished in a high-quality manner to increase motivation and interest in otorhinolaryngology.
Germany's high density of under-equipped hospitals and anticipated surge in orthopedic and trauma surgery-related diseases by 2030, combined with personnel shortages, are expected to increase patient transfers between hospitals, an issue that urgently needs standardized protocols. Despite some existing cooperative agreements, such as between joint-replacement centers or within the Trauma Network DGU®, these measures do not adequately address the full range of patient-transfer cases, including those due to a lack of specialization or staff shortages, resulting in delayed treatment and potential health risks. This study aims to dissect the intricacies of interhospital transfers in orthopedics and trauma surgery across Germany, focusing on understanding the underlying reasons for transfers, comparing the operational structures of small and large hospitals, and laying the groundwork for future standardized protocols to enhance patient care. A cross-sectional study was conducted in the form of an online survey via SoSci Survey, which was directed at orthopedic surgeons and trauma surgeons working in hospitals in Germany. The 22-question survey gathered information on participants' clinic roles, departmental details, transfer processes, frequent diagnoses, perceptions of transfer quality, and improvement areas. The survey was sent to orthopedic and trauma surgeons in Germany by the specialist society. The data were analyzed using descriptive and inferential statistics to ensure a comprehensive insight into interhospital transfer practices. The study involved 152 participants from various hospital ranks and located in different hospital sizes and types across rural and urban areas. A significant difference was observed between the care structures of basic/regular care and central/maximum care hospitals, especially regarding the available facilities and specialties. These findings suggest improvements such as better patient documentation, increased digital communication, optimized patient distribution, and standardization of transfer requests, among others. This study highlights the urgent need for improved protocols and resource allocation to eliminate inequalities in transfers between hospitals in orthopedics and trauma surgery in Germany.
Gestational diabetes mellitus (GDM) affects a significant and growing proportion of pregnant women each year. The condition entails additional monitoring, self-management and healthcare use during pregnancy, and some women also join GDM support groups on Facebook. Little is known about the practices inside these groups, but examining them may elucidate support needs, women's experience of healthcare and improve overall outcomes. The aims of this study were to explore motivations for joining GDM Facebook groups and the perceived value and benefits of such spaces. A cross-sectional design using a web-based survey collected data from two peer-led GDM Facebook groups; relevant quantitative and qualitative data were extracted from open and closed questions, and analysed using descriptive statistics and content analysis. A total of 340 women responded to the survey, with 306 (90%) tendering their motivations to join a GDM Facebook group. Their answers were classified into six categories: peer support; information and practical advice; lived experiences; community; a safe place to ask questions and being recommended. The most commonly reported benefits of membership were 'reading about food ideas' and 'finding helpful information and tips'. Respondents reported finding their group strongly sympathetic, sincere, compassionate, heart-felt, tolerant, sensitive, warm and supportive. GDM Facebook groups are valuable for informational and emotional support, and the sharing and perusal of lived experiences; another key benefit for women is feeling belonging to a community. GDM Facebook groups provide women with access to more tailored and readily available support, filling gaps not addressed by healthcare providers. This study was led by a person with lived experience of GDM, and the survey was pilot tested with women who had also experienced GDM, which contributed to its development.
Gestational diabetes mellitus (GDM) is a glucose intolerance that shows its first onset during pregnancy. In India, GDM affects as many as 5 million women annually. The interprofessional collaborative educational intervention is crucial for GDM management. This study illustrates the collaborative effort in developing and validating an interprofessional health education module designed for healthcare professionals during consultation sessions with GDM patients. The investigation involved three stages: 1) needs assessment for module contents and objectives, 2) health education module development by an interprofessional team, and 3) module validation. We received ethics approval from the institution's ethics committee. The interprofessional team developed and validated the evidence-based English-printed module. The module had 27 units and covered six topics: an introduction to GDM and its management, dietary recommendations for GDM, exercise, yoga recommendations for GDM, weight control, and postpartum care. The interprofessional team developed the educational module, wherein there is an integration of the domains of exercise and yoga along with medicines and nutrition therapy. The module was developed based on local requirements and evidence-based practices. Healthcare professionals can use the interprofessional health education module when advising diabetic pregnant patients.
Gestational diabetes mellitus (GDM) is a heterogeneous condition. Given such variability among patients, the ability to recognise distinct GDM subgroups using routine clinical variables may guide more personalised treatments. Our main aim was to identify distinct GDM subtypes through cluster analysis using routine clinical variables, and analyse treatment needs and pregnancy outcomes across these subgroups. In this cohort study, we analysed datasets from a total of 2682 women with GDM treated at two central European hospitals (1865 participants from Charité University Hospital in Berlin and 817 participants from the Medical University of Vienna), collected between 2015 and 2022. We evaluated various clustering models, including k-means, k-medoids and agglomerative hierarchical clustering. Internal validation techniques were used to guide best model selection, while external validation on independent test sets was used to assess model generalisability. Clinical outcomes such as specific treatment needs and maternal and fetal complications were analysed across the identified clusters. Our optimal model identified three clusters from routinely available variables, i.e. maternal age, pre-pregnancy BMI (BMIPG) and glucose levels at fasting and 60 and 120 min after the diagnostic OGTT (OGTT0, OGTT60 and OGTT120, respectively). Cluster 1 was characterised by the highest OGTT values and obesity prevalence. Cluster 2 displayed intermediate BMIPG and elevated OGTT0, while cluster 3 consisted mainly of participants with normal BMIPG and high values for OGTT60 and OGTT120. Treatment modalities and clinical outcomes varied among clusters. In particular, cluster 1 participants showed a much higher need for glucose-lowering medications (39.6% of participants, compared with 12.9% and 10.0% in clusters 2 and 3, respectively, p<0.0001). Cluster 1 participants were also at higher risk of delivering large-for-gestational-age infants. Differences in the type of insulin-based treatment between cluster 2 and cluster 3 were observed in the external validation cohort. Our findings confirm the heterogeneity of GDM. The identification of subgroups (clusters) has the potential to help clinicians define more tailored treatment approaches for improved maternal and neonatal outcomes.
Gestational diabetes mellitus (GDM) is a serious health issue for both mother and child. As GDM is common worldwide, healthcare providers pay attention while screening and managing pregnant women to ensure good outcomes for both mother and child. This study aims to identify the risk factors associated with developing GDM in pregnant women attending antenatal care clinics in Prince Sultan Military Medical City (PSMMC) in Riyadh, Saudi Arabia. This is a case-control study that utilized patients' medical records for data collection. The study included 317 pregnant Saudi women who attended antenatal care clinics and antenatal diabetic clinics in PSMMC from May 2022 to May 2023. Cases were defined as women who met the inclusion and exclusion criteria and had a positive oral glucose tolerance test (OGTT) result, while controls were defined as women in the same age group and gravidity who had negative OGTT. Analysis was conducted using SPSS Statistics version 29.0 (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 29.0. Armonk, NY: IBM Corp.) Results: The total number of cases was 132 out of 313 total samples, representing 42.2% of the total sample. Three factors were associated with an increased risk of developing GDM, including a family history of diabetes (p-value <0.001), a history of GDM (p-value <0.001), and macrosomia (p-value = 0.020). The study also found higher BMI and advanced maternal age were risk factors for GDM (p-value = 0.004, 0.007), respectively. However, the study did not find a significant association between GDM and other factors, such as chronic disease prevalence, history of miscarriage, or history of fetal death. The study identified several risk factors associated with an increased risk of GDM including family history of diabetes, history of GDM, macrosomia, overweight/obesity, and advanced maternal age. It is recommended that antenatal care providers screen for GDM risk factors and closely monitor overweight, obese, or older women. Education and counseling on healthy lifestyle habits, such as maintaining a healthy weight and engaging in physical activity, may also be beneficial for preventing GDM. Further research is needed to confirm and identify additional risk factors for GDM.
Gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes, including adverse outcomes for both the mother and the fetus. Different diagnostic criteria are used for GDM, and it is not clear how these affect the reported prevalence of adverse pregnancy outcomes. This protocol is for a systematic review to describe and compare the prevalence of adverse pregnancy outcomes in GDM using the different diagnostic criteria applied in various countries/regions of the world. A systematic review and meta-analysis will be carried out. A comprehensive search of observational studies that report the outcomes of interest to this review from 2010 to 2021 will be conducted. We will search the major electronic databases such as PubMed, Scopus, CINHAL and Google Scholar, and screen references of included studies for additional studies. Meta-analyses will be performed, if there is low heterogeneity, and pooled estimates per outcome reported. We will use the bias-adjusted inverse variance heterogeneity model and random effects models, depending on the heterogeneity observed, to pool prevalence estimates and perform subgroup analyses by region, by age group, by diagnostic criteria and by GDM screening method if sufficient data are available. We will also compare the prevalence of adverse outcomes by diagnostic method and report prevalence ratios. We will report 95% confidence estimates for all estimates. Ethical approval is not required as the review uses published data. Findings will be published in peer-reviewed journals and presented at conferences. CRD42020155061.
Giant cell arteritis is an age-related vasculitis that mainly affects the aorta and its branches in individuals aged 50 years and older. Current options for diagnosis and treatment are scarce, highlighting the need to better understand its underlying pathogenesis. Genome-wide association studies (GWAS) have emerged as a powerful tool for unravelling the pathogenic mechanisms involved in complex diseases. We aimed to characterise the genetic basis of giant cell arteritis by performing the largest GWAS of this vasculitis to date and to assess the functional consequences and clinical implications of identified risk loci. We collected and meta-analysed genomic data from patients with giant cell arteritis and healthy controls of European ancestry from ten cohorts across Europe and North America. Eligible patients required confirmation of giant cell arteritis diagnosis by positive temporal artery biopsy, positive temporal artery doppler ultrasonography, or imaging techniques confirming large-vessel vasculitis. We assessed the functional consequences of loci associated with giant cell arteritis using cell enrichment analysis, fine-mapping, and causal gene prioritisation. We also performed a drug repurposing analysis and developed a polygenic risk score to explore the clinical implications of our findings. We included a total of 3498 patients with giant cell arteritis and 15 550 controls. We identified three novel loci associated with risk of giant cell arteritis. Two loci, MFGE8 (rs8029053; p=4·96 × 10-8; OR 1·19 [95% CI 1·12-1·26]) and VTN (rs704; p=2·75 × 10-9; OR 0·84 [0·79-0·89]), were related to angiogenesis pathways and the third locus, CCDC25 (rs11782624; p=1·28 × 10-8; OR 1·18 [1·12-1·25]), was related to neutrophil extracellular traps (NETs). We also found an association between this vasculitis and HLA region and PLG. Variants associated with giant cell arteritis seemed to fulfil a specific regulatory role in crucial immune cell types. Furthermore, we identified several drugs that could represent promising candidates for treatment of this disease. The polygenic risk score model was able to identify individuals at increased risk of developing giant cell arteritis (90th percentile OR 2·87 [95% CI 2·15-3·82]; p=1·73 × 10-13). We have found several additional loci associated with giant cell arteritis, highlighting the crucial role of angiogenesis in disease susceptibility. Our study represents a step forward in the translation of genomic findings to clinical practice in giant cell arteritis, proposing new treatments and a method to measure genetic predisposition to this vasculitis. Institute of Health Carlos III, Spanish Ministry of Science and Innovation, UK Medical Research Council, and National Institute for Health and Care Research.
Giardiosis is a parasitic disease caused by the protozoa Giardia lamblia (also known as Giardia intestinalis and Giardia duodenalis), which causes gastrointestinal symptoms. Infection usually occurs through the ingestion of contaminated water/food or through contact with an infected person. In Poland, giardiasis is notifiable disease, acoording to the EU deffinition implement in the polish surveillance system. The aim of this study is to asses epidemiological situation of giardiasis in Poland in 2021 and compare it to the previous years. The assessment of the epidemiological situation of giardiasis in Poland in 2021 was performed on the basis of data from the annual bulletins "Infectious diseases and poisoning in Poland" for the years 2008-2021, data on individual cases collected for the purposes of epidemiological surveillance in the EpiBaza system and data from food-born outbreak investigations recorded in the Registry of Epidemic Outbreaks (ROE). In 2021, 559 cases of giardiasis were reported in Poland (558 confirmed case, 1 probable case). There was an increase in the number of reported cases in comparision to 2020 by 56% and decrease to 2019 by 29%. Cases of giardiasis were reported in all voivodeships, with the highest incidence rate in Podlaskie voivodeship (9.1/100 000), incidence rate for Poland was 1.5/100 000. Giardiasis was diagnosed in patiens in all age group, the largest group of patiens were children (age groups 0-4 and 5-9). The hospitalization rate of patients diagnosed with giardiasis was 9.7% and was lower than in 2020, when it was 12.4%. As in previous years, no deaths from giardiasis were reported. The number of cases of giardiasis has increased compared to 2020, but has not reached pre-pandemic levels. As in previous years, differences in the incidence by age and sex of people with the disease were noted when comparing data reported from Poland and EU/EEA countries.
GIS technology can provide reasonable and sustainable data support for landscape planning and ecological development and make wetland landscape planning consider the spatial layout of landscape and the optimal allocation of resources more. The key technologies of cross media intelligence mainly focus on intelligent information retrieval, analysis and reasoning, knowledge map construction, and intelligent storage. Convolutional neural network (CNN), as one of the representative algorithms of deep learning, plays an important role in retrieving landscape data and extracting image and text features across media. Further retrieval of media data, in-depth text processing, and image feature data extraction are realized by using deep learning technology, and comprehensive in-depth analysis is carried out by combining landscape plane images, three-dimensional images, and vector information in GIS technology. Provide quantitative information for the evaluation system of human landscape, economy, history, and region, so as to formulate a scientific and reasonable performance evaluation system.
Given that both children and adults struggle with fractions in mathematics education, we investigated the processing of nonsymbolic fractions in a continuous form of part-of-the-whole. Continuous features of nonsymbolic numbers (e.g., the size of dots in an array) were found to influence numerosity judgment, but it should be noted that the (continuous) size of a part can be processed relative to a whole or as an absolute size. This study tested which of these size types (i.e., absolute and relative) influences comparison of parts. In two Stroop-like comparison tasks, we measured the interference of each size type on the processing of the other. In Experiment 1, stimuli were three-dimensional-like partially filled glasses of water. In both tasks, congruent trials (in which the larger absolute size was also the larger part-of-the-whole) were processed more efficiently than incongruent trials (in which the larger absolute size was the smaller part-of-the-whole). In Experiment 2, where stimuli were two-dimensional rectangles, this result was replicated under improved experimental control. We conclude that both absolute size and relative size of a part are automatically processed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Given that unsafe human actions are the main cause of accidents, it is essential to comprehend the attitudes of medical students toward the risks of road accidents, particularly given their potential influence as future healthcare professionals. Therefore, this study was carried out to investigate the attitudes of medical students towards road accidents. This cross-sectional study was conducted on 300 Zahedan University of Medical Sciences students in 2021 as available sampling. The required information was collected using a researcher-made questionnaire with a content validity ratio of 0.9, a content validity index of 0.9-0.8, and a reliability (α) of 0.79, which was presented online in the university systems. Statistical analysis was done using SPSS 23 software, data description was done as frequency and percentage, and analytical analysis was done with the χ2 test. The average age of the participants was 21.7 (4.2) years; 45.7% of the participants were male and 11.3% were married; 79.7% had less than 300 km of driving experience; 76% had less than 3 years since receiving their license; 14% stated that they drive faster than others; 18.3% reported a history of fines; and 28.3% reported an accident history. The most incorrect attitudes of students regarding low-risk using mobile phones (86%), text sending (84.3%), eating and drinking while driving (74.6%), driving after consuming alcohol or drugs (73%), and driving when tired and sleepy (85.4%) were reported. Based on the results, it is suggested to plan to correct wrong attitudes, especially among young and educated drivers, through education and culture, so that we can move in the direction of reducing accidents.