Yoxas/statistical_literacy huggingface dataset:
The intricate hormonal and physiological changes of the menstrual cycle can influence health on a daily basis. Although prior studies have helped improve our understanding of the menstrual cycle, they often lack diversity in the populations included, sample size, and the span of reproductive and life stages. This paper aims to describe the dynamic differences in menstrual cycle characteristics and associated symptoms by age in a large global cohort of period-tracking application users. This work aims to contribute to our knowledge and understanding of female physiology at varying stages of reproductive aging. This cohort study included self-reported menstrual cycle and symptom information in a sample of Flo application users aged 18-55. Cycle and period length and their variability, and frequency of menstrual cycle symptom logs are described by the age of the user. Based on data logged by over 19 million global users of the Flo app, the length of the menstrual cycle and period show clear age-associated patterns. With higher age, cycles tend to get shorter (Cycle length: D¯ = 1.85 days, Cohen's D = 0.59) and more variable (Cycle length SD: D¯ = 0.42 days, Cohen's D = 0.09), until close to the chronological age (40-44) suggesting menopausal transition, when both cycles and periods become longer (Cycle length: D¯ = 0.86 days, t = 48.85, Cohen's D = 0.26; Period length: D¯ = 0.08, t = 15.6, Cohen's D = 0.07) and more variable (Cycle length SD: D¯ = 2.80 days, t = 111.43, d = 0.51; Period length SD: D¯ = 0.23 days, t = 67.81, Cohen's D = 0.31). The proportion of individuals with irregular cycles was highest in participants aged 51-55 (44.7%), and lowest in the 36-40 age group (28.3%). The spectrum of common menstrual cycle-related symptoms also varies with age. The frequency of logging of cramps and acne is lower in older participants, while logs of headache, backache, stress, and insomnia are higher in older users. Other symptoms show different patterns, such as breast tenderness and fatigue peaking between the ages of 20-40, or mood swings being most frequently logged in the youngest and oldest users. The menstrual cycle and related symptoms are not static throughout the lifespan. Understanding these age-related differences in cycle characteristics and symptoms is essential in understanding how best to care for and improve the daily experience for menstruators across the reproductive life span.
The intricate interaction of natural and anthropogenic factors drives changes in land and water in response to societal demands and climate change. However, there has been insufficient information on the feedback effects in dryland hotspots altered by land change dynamics. This research compared two transboundary inland lakes, the Lake Chad basin (LCB) in Africa and the Aral Sea basin (ASB) in Central Asia, using remote sensing and geographic information system techniques to analyze and quantify present and future land cover dynamics, resilience, and their feedback effects. The study integrated Cellular Automata, Markov Chain, and Multilayer Perceptron models to predict LULC changes up to 2030. Descriptive statistics, ordinary least squares regression, hotspot Gi-Bin, trend analysis, and advanced geostatistical methods were utilized to identify relationships, patterns, magnitudes, and directions of observed changes in the feedback effects. From 2000 to 2030, the analysis unveils intriguing trends, including an increase in cropland from 48% to 51% and a decrease in shrubland from 18% to 15% in the LCB. The grassland increased from 21% to 22%, and the settlement expanded from 0.10 to 0.60% in the ASB. Water bodies remained stable at 1.60 % in LCB, while in ASB, it declined from 3% to 2%. These changes were significantly influenced by population, elevation, and temperature in both basins, with irrigation also playing a significant role in the ASB and slope in LCB. The study further revealed discernible shifts in normalized difference vegetation index, temperature, and precipitation linked to specific land cover conversions, suggesting alterations in surface properties and vegetation health. This study underscores the complex interplay between land cover dynamics, resilience, climate variability, and feedback mechanisms in LCB and ASB.
The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.
The introduction of internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell-derived cortical organoids in two different settings: Using microscopy to monitor organoid growth in an introductory tissue culture course, and using high density multielectrode arrays to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.
The introduction of statistical analysis in biomedical journals should be attributed to Dunn and Greenwood in the 1930s, who reflect the concepts of statistical analysis and interpretation. The aim of this study was to analyze the use of different statistical tests and the level of accessibility analysis-dependent and article-dependent of the original articles published in the journal Medicina (B Aires) in the period 2008-2017. A bibliometric, descriptive, observational, cross-sectional study was carried out, in which the original articles were evaluated according to the scale proposed by Mora Ripoll et al. From the 301 articles in Spanish reviewed, 96% presented statistical analyses. Among the 215 articles that used some inferential statistics technique, 49.7% used the chi-square test, z tests for proportions, the Fisher exact test or the McNemar test; 29.2% used student t-tests and z-tests, including the use of these techniques or the use of confidence intervals for medium-conformance contrasts, and/or median-homogeneity (two samples), in paired or independent samples. The results indicate that a reader who knows about the tests included in Level II will have statistical access to 75% of the original articles published. It was found that it is not necessary to have advanced knowledge of statistics to access most publications, but it is important that these contents are developed with emphasis on statistical reasoning over the application and use of software or the choice of the appropriate test.
The introduction of ultrasound (US) courses into medical undergraduate courses is usually met with a particularly high level of student motivation. The reasons for this are unclear. The aim of this study was to investigate the factors that contribute to undergraduate medical students' motivation to learn US skills. Understanding what motivates students to learn US will inform the efforts of faculty to foster students' motivation to learn. We carried out in-depth semi-structured one-to-one interviews with medical students participating in an optional US course at two Swiss universities. The interview guide consisted of 10 main questions. The content was informed by experts in the field of medical education and US, as well as by a literature review of motivation theories for learning, in particular by self-determination theory (SDT). SDT was used to guide the development of the interview guide and to reflect on the resulting themes in the discussion section. The interview guide was piloted with two medical students. The interviews lasted an average of 45 min and were audio recorded and transcribed. Thematic analysis was used to analyse the data. Fourteen undergraduate medical students in their preclinical (year 3) and clinical studies (years 4 and 5) elaborated on a wide range of reasons for their high motivation to learn US. They were motivated for US training because of the positive nimbus of the US modality, emphasising the advantages of visualisation. Students acknowledged the potential professional benefits of learning US and described it as a fun, exciting group activity. The four themes we found in our analysis can all be related to the three universal needs described in SDT. The strong focus on the visual aspect and the positive nimbus of the modality goes beyond that and reflects the visuo-centric Zeitgeist, which claims the superiority of visual information over other data. Educators should be aware that motivation to learn is affected by the Zeitgeist and ensuing preconceptions, such as the perception of the positive nimbus surrounding a topic. Other key elements that can be implemented to motivate students are just-in-time feedback, enabling group experiences and creating awareness of the clinical relevance of learning content.
The investigation of physical literacy (PL) and physical activity (PA) should be done in an ecological context because the socio-cultural situation can encourage or inhibit children's activity. The present study aimed to study the role of the cultural environment in the development of PL and PA in Iranian children. The statistical population consisted of Iranian children aged 8 to 12, of whom 270 students were recruited by cluster sampling from six provinces. They complete the Canadian Assessment of Physical Literacy 2 (CAPL-2) and the International Physical Activity Survey. To examine the cultural environment, the components of geographic location (west, south, central, east, and northwest), place of residence (downtown, suburban, and village), and gender (boys and girls) were used. A multivariate ANOVA analysis was used to analyze the data. From the geographic location, the findings showed that students inhabit in the west and east of Iran have significantly higher scores than their counterparts living in the central, south, and northwest at PA and PL (P < 0.001). From the place of residence, we observed a higher level of PA and PL in children living in the village than in those living in the suburbs and downtown (P < 0.001). In terms of gender, boys have higher PL and PA scores (P < 0.001). The findings demonstrate that socio-cultural factors, geographic location, place of residence, and gender have different impacts on children's PL and physical activity. Therefore, we suggest using ecologically appropriate decentralized planning in a physical education curriculum.
The invisibility of the transgender population within official records, combined with other socio-economic factors, impacts oral health status among transgender people. Hence, our systematic review and meta-analysis aim to generate a pooled estimate of the oral health status of the transgender community in India. A systematic search was performed across four databases. The studies included a quantitative research design conducted in India and involved self-identified transgender individuals. The pooled prevalence was determined at a 95% confidence interval (CI). Q-statistics and the I2 test were utilized to evaluate the source of heterogeneity. Leave-one-out analysis and Baujat plots were used to detect outliers within the studies. A Doi plot and LFK index were employed to assess the publication bias. A total of 12 studies comprising 1566 transgender participants were included. The pooled prevalence of toothbrush use among transgenders in India was found at 83% (95% CI: 0.73-0.91), smoking = 12% (CI: 0.03-0.26), smokeless tobacco = 53% (CI = 0.38-0.68), dental caries = 78% (CI: 67%-88%), calculus = 65% (CI: 0.4-0.86), and bleeding 18% (CI:0.08-0.32). Oral health disparities among Indian transgender individuals are evident in the low toothbrush usage, an elevated prevalence of tobacco use, and dental disorders such as calculus, cavities, and bleeding. Tailored dental health programs that include inclusive healthcare services and awareness are essential. CRD42023468872.
The involvement of patients and their families in the redesign of healthcare services is an important option in providing a service that addresses the patients' needs and improves health outcomes. However, it is a resource-intensive approach, and it is currently not clear when it should be used, and what should be the reasoning behind this decision. Some health systems of international standing have created a patient engagement program as a selling point. This paper discusses how co-led redesign can be beneficial in improving health service and more effectively engaging patients. Potential barriers for patient involvement are discussed. Patient involvement can be integrated into the health system at three main levels of engagement: direct care, organizational design and governance, and policy-making. The aim of this paper is to describe how co-led redesign is compatible with different levels of patient involvement and to address the challenges in delivering a co-led redesign in healthcare. Co-led redesign not only involves the collection of quantitative data for assessing the current systems but also the collection of qualitative data through patient, family, and staff interviews to determine the barriers to patient satisfaction. Co-led redesign is a resource-rich process that requires expertise in data collection and a clinical group that is devoted to implementing recommended changes. Currently, a number of countries have utilized co-led redesign for many different types of healthcare services. Resource availability and cost, process time, and lack of outcome measures are three major limiting factors.
The irreversible and progressive atrophy by Alzheimer's Disease resulted in continuous decline in thinking and behavioral skills. To date, CNN classifiers were widely applied to assist the early diagnosis of AD and its associated abnormal structures. However, most existing black-box CNN classifiers relied heavily on the limited MRI scans, and used little domain knowledge from the previous clinical findings. In this study, we proposed a framework, named as PINet, to consider the previous domain knowledge as a Privileged Information (PI), and open the black-box in the prediction process. The input domain knowledge guides the neural network to learn representative features and introduced intepretability for further analysis. PINet used a Transformer-like fusion module Privileged Information Fusion (PIF) to iteratively calculate the correlation of the features between image features and PI features, and project the features into a latent space for classification. The Pyramid Feature Visualization (PFV) module served as a verification to highlight the significant features on the input images. PINet was suitable for neuro-imaging tasks and we demonstrated its application in Alzheimer's Disease using structural MRI scans from ADNI dataset. During the experiments, we employed the abnormal brain structures such as the Hippocampus as the PI, trained the model with the data from 1.5T scanners and tested from 3T scanners. The F1-score showed that PINet was more robust in transferring to a new dataset, with approximatedly 2% drop (from 0.9471 to 0.9231), while the baseline CNN methods had a 29% drop (from 0.8679 to 0.6154). The performance of PINet was relied on the selection of the domain knowledge as the PI. Our best model was trained under the guidance of 12 selected ROIs, major in the structures of Temporal Lobe and Occipital Lobe. In summary, PINet considered the domain knowledge as the PI to train the CNN model, and the selected PI introduced both interpretability and generalization ability to the black box CNN classifiers.
The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.
The issue of child physical abuse (CPA) is complex and challenging to study. According to World Health Organization fact sheets for 2020, about 3 in 4 children between 2 and 4 years of age regularly face physical maltreatment by parents or caregivers. It may cause a lifelong impact on physical and mental health. To assess the parents' knowledge and to evaluate the effectiveness of the structured teaching program (STP) regarding child physical abuse (CPA) among parents. The pre-experimental, "One-group Pre-test Post-test design" was adopted for this study. Parents of children who were admitted for treatment in the child psychiatry centre (CPC) of a tertiary care referral center between January 2019 and January 2020 were recruited for this study. Thirty parents were recruited with a convenience sampling technique. The study was conducted through an online platform (Zoom). Pre-test and post-tests were conducted through Google survey form. Data were collected with a self-developed knowledge questionnaire on CAP. An online structured teaching program (STP) was administered for three alternative days after the pre-test assessment. The post-test assessment was conducted at a two-point time, that is immediately after the STP and after the one-week gap. Descriptive and inferential statistics were used to analyze the data. "One-group Pre-test Post-test design" was adopted for this study. Parents of children who were admitted for treatment in the child psychiatry centre (CPC) of a tertiary care referral center between January 2019 and January 2020 were recruited for this study. Thirty parents were recruited with a convenience sampling technique. The study was conducted through an online platform (Zoom). Pre-test and post-tests were conducted through Google survey form. Data were collected with a self-developed knowledge questionnaire on CAP. An online structured teaching program (STP) was administered for three alternative days after the pre-test assessment. The post-test assessment was conducted at a two-point time, that is immediately after the STP and after the one-week gap. Descriptive and inferential statistics were used to analyze the data. The pre-test knowledge assessment means score regarding child physical abuse was found to be 12, with a standard deviation of 1.73. In the post-test one, 17.30 ± 1.39 and in the post-test two, 16 ± 1.55 with P < 0.001. Analysis revealed statistically significant improvement was found in the post-test knowledge regarding child physical abuse among the parents. There was no significant (p < 0.05) relationship found between the socio-demographic variables of the participants and their pre-intervention knowledge scores on child physical abuse. The study findings reveal that parents have a fair knowledge of CPA and the STP was effective and feasible to administer in improving the subjects' knowledge regarding child physical abuse.
The issue of culture is becoming ever more interesting, especially when interconnected with other business factors like finance. Although intriguing, the relationship between culture and finance has long been neglected. Unlike existing research, this article aims at assessing the impact of culture on financial inclusion and financial literacy among Cameroonian small business managers. In this quantitative investigation, the indices are built using Principal Component Analysis (PCA), and the estimation is done using Ordinary Least Squares (OLS). The data used is from a research survey on 161 small enterprises in the cities of Douala, Bafoussam, Foumban, Foumbot, and Dschang. The findings demonstrate that organizational culture, in contrast to its social component, is positively and strongly associated with financial literacy and financial inclusion. Additionally, firm and manager variables like age, turnover variation, and education level significantly explain these financial variables. Thus, it is essential to promote organizational culture in Cameroonian businesses.