Yoxas/statistical_literacy huggingface dataset:
A low risk of gastrointestinal disorders in the adult population has long been linked to consuming a Mediterranean diet (MD). The study aims to evaluate the effects of the Mediterranean diet educational program on employee's knowledge regarding functional gastrointestinal disorders. A quasi-experimental study design of two study groups (pre-test and post-test) was carried out at four colleges in the University of Baghdad, Iraq of the period between January 10, 2022 and May 31, 2022. A purposive (non-probability) sample was used with a sample size of (160) employees divided into two groups (80 employees each). The study group of 80 employees was exposed to the Mediterranean Diet educational program while the control group with was not. The results showed a positive effect of the Mediterranean diet educational program on the employees' functional gastrointestinal disorders (FGIDs) knowledge in the study group. The study results indicated that there are highly significant mean differences between the study and control groups in the pre-test and the post-test in the specific and general knowledge area of employees' functional gastrointestinal disorders (t = 17.002, df = 158; t = 24.19, df = 158; P value ≤ 0.01). Findings indicated that there were no significant statistical relationships between the level of knowledge of functional gastrointestinal disorders and demographic characteristics except employees' level of education with a high significant association P value ≤ 0.01). The Mediterranean diet educational program effectively improves the employees' knowledge of functional gastrointestinal disorders. These results support the benefit of establishing educational programs for adult employees on the Mediterranean diet to improve individuals' knowledge about the gastrointestinal diseases.
A low socioeconomic status is associated with a vulnerable health status (VHS) through the accumulation of health-related risk factors, such as poor lifestyle behaviors (eg, inadequate nutrition, chronic stress, and impaired health literacy). For pregnant women, a VHS translates into a high incidence of adverse pregnancy outcomes and therefore pregnancy-related inequity. We hypothesize that stimulating adequate pregnancy preparation, targeting lifestyle behaviors and preconception care (PCC) uptake, can reduce these inequities and improve the pregnancy outcomes of women with a VHS. A nudge is a behavioral intervention aimed at making healthy choices easier and more attractive and may therefore be a feasible way to stimulate engagement in pregnancy preparation and PCC uptake, especially in women with a VHS. To support adequate pregnancy preparation, we designed a mobile health (mHealth) app, Pregnant Faster, that fits the preferences of women with a VHS and uses nudging to encourage PCC consultation visits and engagement in education on healthy lifestyle behaviors. This study aimed to test the feasibility of Pregnant Faster by determining usability and user satisfaction, the number of visited PCC consultations, and the course of practical study conduction. Women aged 18-45 years, with low-to-intermediate educational attainment, who were trying to become pregnant within 12 months were included in this open cohort. Recruitment took place through social media, health care professionals, and distribution of flyers and posters from September 2021 until June 2022. Participants used Pregnant Faster daily for 4 weeks, earning coins by reading blogs on pregnancy preparation, filling out a daily questionnaire on healthy lifestyle choices, and registering for a PCC consultation with a midwife. Earned coins could be spent on rewards, such as fruit, mascara, and baby products. Evaluation took place through the mHealth App Usability Questionnaire (MAUQ), an additional interview or questionnaire, and assessment of overall study conduction. Due to limited inclusions, the inclusion criterion "living in a deprived neighborhood" was dropped. This resulted in the inclusion of 47 women, of whom 39 (83%) completed the intervention. In total, 16 (41%) of 39 participants visited a PCC consultation, with their main motivation being obtaining personalized information. The majority of participants agreed with 16 (88.9%) of 18 statements of the MAUQ, indicating high user satisfaction. The mean rating was 7.7 (SD 1.0) out of 10. Points of improvement included recruitment of the target group, simplification of the log-in system, and automation of manual tasks. Nudging women through Pregnant Faster to stimulate pregnancy preparation and PCC uptake has proven feasible, but the inclusion criteria must be revised. A substantial number of PCC consultations were conducted, and this study will therefore be continued with an open cohort of 400 women, aiming to establish the (cost-)effectiveness of an updated version, named Pregnant Faster 2. RR2-10.2196/45293.
A major challenge in health professions education is to equip graduates with essential teamwork skills, addressing cognitive, motivational, and emotional barriers that hinder effective collaboration among students from diverse backgrounds. The Teamwork Baseline Assessment Tool (TBAT) was developed as an innovative solution to teach collaboration and teamwork, focusing on growth mindsets, reactions to challenging scenarios, and ideal team player attributes. Implemented during the orientation for new first-year students, TBAT facilitated early engagement in teamwork discussions, with students receiving personalised reports to aid in self-reflection and development. Key lessons included the importance of initiating teamwork conversations early, the value of personalised feedback in promoting self-awareness and peer understanding, and the effectiveness of TBAT in providing instructors with insights into students' teamwork aptitudes. Expanding TBAT across various student populations and integrating it into the curriculum aims to provide continuous opportunities for applying and reinforcing teamwork and collaboration skills. This strategy will support the development of targeted instructional approaches, fostering a collaborative learning environment and preparing students for the teamwork challenges in healthcare settings.
A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.
A manual approach to case investigation and contact tracing can introduce delays in response and challenges for field teams. Go.Data, an outbreak response tool developed by the World Health Organization (WHO) in collaboration with the Global Outbreak Alert and Response Network, streamlines data collection and analysis during outbreaks. This study aimed to characterize Go.Data use during COVID-19, elicit shared benefits and challenges, and highlight key opportunities for enhancement. This study utilized mixed methods through qualitative interviews and a quantitative survey with Go.Data implementors on their experiences during COVID-19. Survey data was analyzed for basic univariate statistics. Interview data were coded using deductive and inductive reasoning and thematic analysis of categories. Overarching themes were triangulated with survey data to clarify key findings. From April to June 2022, the research team conducted 33 interviews and collected 41 survey responses. Participants were distributed across all six WHO regions and 28 countries. While most implementations represented government actors at national or subnational levels, additional inputs were collected from United Nations agencies and universities. Results highlighted WHO endorsement, accessibility, adaptability, and flexible support modalities as main enabling factors. Formalization and standardization of data systems and people processes to prepare for future outbreaks were a welcomed byproduct of implementation, as 76% used paper-based reporting prior and benefited from increased coordination around a shared platform. Several challenges surfaced, including shortage of the appropriate personnel and skill-mix within teams to ensure smooth implementation. Among opportunities for enhancements were improved product documentation and features to improve usability with large data volumes. This study was the first to provide a comprehensive picture of Go.Data implementations during COVID-19 and what joint lessons could be learned. It ultimately demonstrated that Go.Data was a useful complement to responses across diverse contexts, and helped set a reproducible foundation for future outbreaks. Concerted preparedness efforts across the domains of workforce composition, data architecture and political sensitization should be prioritized as key ingredients for future Go.Data implementations. While major developments in Go.Data functionality have addressed some key gaps highlighted during the pandemic, continued dialogue between WHO and implementors, including cross-country experience sharing, is needed ensure the tool is reactive to evolving user needs.
A mathematical model of the reaction between primary antibody and epitope is described using the Law of Mass Action to define the reaction quantitatively. The model explains some of the peculiar properties of immunohistochemical preparations. It also predicts that antibody excess over epitope will not increase staining intensity for very avid primary antibodies. This property can be exploited to measure the amount of epitope in histological sections. The assumptions of the model are not specific to immunohistochemistry, and such reasoning should be widely applicable to tests based on highly avid detection systems with high amplification of the initial signal.
A meaningful engagement of learners is critical in the quality teaching and learning of mathematics at school level. Learner engagement has been an ongoing issue in mathematics classrooms in Nepal and elsewhere. In this context, this study aimed to examine the level of engagement (behavioral, social, emotional, and cognitive activities) and their association with learning mathematics through the virtual mode of instruction during the pandemic. The cross-sectional online survey design was employed among 402 secondary-level mathematics teachers in Nepal. Descriptive statistics, correlation, and structural equation modeling were the major statistical techniques used in research. The findings indicate that the level of behavioral, social, emotional, and cognitive engagement of students was found to be high in the online mode of instruction. Additionally, cognitive engagement has significant highest impact on social, behavior, and emotional engagement.
A mechanism-based reasoning and case-control study. To introduce correction target of clivo-axial angle (CXA) in quantitative surgical reduction of basilar invagination (BI). The exact mechanism of BI with or without atlantoaxial dislocation is still unclear. Sagittal deformity is a key feature of BI. Correction of CXA directly influences subaxial cervical lordosis (increase of CXA equals the decrease of cervical lordosis). However, a quantitative reference for correction surgery has not been established. CXA was divided by Chamberlain line into clivus tilt (CT) and axial tilt (AT). Patients diagnosed with BI were retrospectively included. Patients with degenerative cervical spine diseases or vascular diseases (without BI) were included as controls. CT, AT, and other common parameters were measured and analyzed with t test and multiple linear regression. Demonstration case was presented. A total of 42 BI patients and 23 controls were included. Normal references for CXA, AT, and CT were 162.3±7.1, 93.8±6.5, and 68.6±3.8 degrees, respectively. BI patients had a 30.3-degree smaller CXA, a 15.5-degree smaller AT, and a 14.9-degree smaller CT. Basal angle (P=0.002) independently had a significant influence on extent of BI, while CT and AT did not. Demonstration case showed that CT was fixed and correcting AT to an ideal 94 degrees was optimal for an individual patient. Proper quantitative correction of CXA needs to be individualized in consideration of CT and AT. The difference between actual AT and its ideal value (about 94 degrees) is the optimal target of CXA correction to decompress neural elements ventrally and recover better subaxial cervical lordosis. Level IV.
A mechanism-based reasoning and retrospective cohort study. To establish a quantitative relationship between the change of clivo-axial angle (CXA) and the change of subaxial cervical lordosis (CL) in correction surgery of atlantoaxial dislocation (AAD). The evolving understanding of mechanism has dramatically improved the treatment modality of AAD. Cervical sagittal alignment is another important aspect of the surgery, in addition to reduction of odontoid process. However, a quantitative reference for correction surgery has not been established. Frankfort-axial angle (FXA) was introduced. Based on two assumptions, (1) sagittal alignment of the spine aims at keeping horizontal gaze and (2) deformities at craniovertebral junction make little impact on slope of T1 vertebra, we deduced that the change of CXA equaled change of CL (ΔCXA = -ΔCL). We retrospectively reviewed our case cohort to validate this finding with linear regression analysis. Sixteen cases (eight male and eight female, mean age 40.4±12.5 yr old) were included. Liner fitting equation for ΔFXA and ΔCXA is y=1.005x (coefficient of determination, R=0.966; significance of the estimated coefficients P<0.001, t-statistics) and that for ΔCL and ΔCXA is y=-1.023x (R=0.976, P<0.001). These results support our deduction that ΔCXA = -ΔCL, which can be used as a guidance of quantitative correction of sagittal deformity in AAD. Correction of CXA will influence the subaxial cervical lordosis (ΔCXA = -ΔCL) of AAD patients. This equation can serve as a quantitative reference for preoperative planning and intraoperative refining of the correction of cervical sagittal deformity in AAD. 4.
A medical student's career choice directly influences the physician workforce shortage and the misdistribution of resources. First, individual and contextual factors related to career choice have been evaluated separately, but their interaction over time is unclear. Second, actual career choice, reasons for this choice, and the influence of national political strategies are currently unknown in Switzerland. The overall objective of this study is to better understand the process of Swiss medical students' career choice and to predict this choice. Our specific aims will be to examine the predominately static (ie, sociodemographic and personality traits) and predominately dynamic (ie, learning context perceptions, anxiety state, motivation, and motives for career choice) variables that predict the career choice of Swiss medical school students, as well as their interaction, and to examine the evolution of Swiss medical students' career choice and their ultimate career path, including an international comparison with French medical students. The Swiss Medical Career Choice study is a national, multi-institution, and longitudinal study in which all medical students at all medical schools in Switzerland are eligible to participate. Data will be collected over 4 years for 4 cohorts of medical students using questionnaires in years 4 and 6. We will perform a follow-up during postgraduate training year 2 for medical graduates between 2018 and 2022. We will compare the different Swiss medical schools and a French medical school (the University of Strasbourg Faculty of Medicine). We will also examine the effect of new medical master's programs in terms of career choice and location of practice. For aim 2, in collaboration with the Swiss Institute for Medical Education, we will implement a national career choice tracking system and identify the final career choice of 2 cohorts of medical students who graduated from 4 Swiss medical schools from 2010 to 2012. We will also develop a model to predict their final career choice. Data analysis will be conducted using inferential statistics, and machine learning approaches will be used to refine the predictive model. This study was funded by the Swiss National Science Foundation in January 2023. Recruitment began in May 2023. Data analysis will begin after the completion of the first cohort data collection. Our research will inform national stakeholders and medical schools on the prediction of students' future career choice and on key aspects of physician workforce planning. We will identify targeted actions that may be implemented during medical school and may ultimately influence career choice and encourage the correct number of physicians in the right specialties to fulfill the needs of currently underserved regions. DERR1-10.2196/53138.
A methodological approach based on rare earth elements analysis was developed to observe human activities in the stratigraphic sequence of Alagankulam. The site was one of the main ancient ports in south-eastern India and one of the transoceanic connecting points between East and West during the Classical Period. The sampled sediments where collected from vertical profiles, areas with traces of firing activities and filled deposits. Major, minor and trace element concentrations were measured by the means of spectroscopic and spectrometric techniques. Data from multielemental analysis were then cross-referenced together with archaeological evidence to map the variability within the site and its association with the detected anthropic activities. The matching of the interpretation of the archaeological record and the analytical data has allowed a combined mapping of visible and invisible traces of human activities in the site, giving a deeper insight of the Alagankulam occupational history.
A methodology is developed to describe time-dependent phenomena associated with nonlocal transport in complex, two-dimensional geometries. It is an extension of the ''iterative method" introduced previously to solve steady-state transport problems [Maggs and Morales, Phys. Rev. E 99, 013307 (2019)10.1103/PhysRevE.99.013307], and it is based on the ''jumping particle" concepts associated with the continuous-time random walk (CTRW) model. The method presented explicitly evaluates the time integral contained in the CTRW master equation. A modified version of the Mittag-Leffler function is used for the waiting-time probability distributions to incorporate memory effects. Calculations of the propagation of ''anomalous transport waves" in various systems, with and without memory, illustrate the technique.
A migraine attack aggregates a range of different symptoms, besides pain, that contribute to attack-related disability. Cognitive dysfunction is an unacknowledged part of the migraine attack. To provide a profile of the frequency and character of migraine attack-related cognitive symptoms occurring during the headache phase of the attack. Cross-sectional survey. Clinical-based sample of episodic migraine patients. Sequential patients were screened about the occurrence of cognitive symptoms during migraine attacks using an open-ended question followed by a self-fulfilled symptom checklist. Of 165 migraine patients (15 men, age average 37.3 ± 10.7 years), 89.7% described cognitive symptoms during the headache phase of the migraine attack. On average 2.5 ± 1.6 symptoms were reported per patient, uninfluenced by demographic or disease-related variables. The most common spontaneous symptoms related to executive functions, such as poor ability to concentrate (37%), difficulty in reasoning (25%), and thinking (23%). The pattern of responses on the symptoms checklist corroborated with those reported spontaneously and quantitative scores of the checklist were higher in patients with spontaneous symptoms. Open-ended questions tend to overestimate frequency; data accuracy may be influenced by the population chosen (clinical-based, some using prophylactic treatment). This study detailed the frequency and characteristics of migraine attack-related subjective cognitive symptoms and found its frequency to be similar to reports of other migraine defining symptoms (ex. nausea, photophobia) in recent clinical series. Patients' reports were consistent and dominated by complaints of attention difficulties, diminished cognitive efficiency, and processing speed impairment.