Yoxas/statistical_literacy huggingface dataset:
Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40-84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0-29, extending to those aged 30-59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45-54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations.
Registered (equine) veterinary nurses (R(E)VNs) typically provide few client-facing services. Better utilising R(E)VN skills could help address workforce shortages, improve morale and benefit patient health. The aim of this study was to explore horse owner perceptions of R(E)VN roles. An online cross-sectional survey of horse owners gathered data on their understanding of R(E)VN roles, their experiences of R(E)VNs their openness to further R(E)VN services and perceived facilitators of and barriers to such services. Participants were recruited via practices, social media and snowball sampling. Descriptive analysis of the quantitative data and manifest content analysis of the qualitative data were conducted. Three hundred and forty-seven useable responses were received. Eighty-one percent (282/347) had heard the term R(E)VN. Most talked positively about their experiences with R(E)VNs. Eighty-seven percent (285/326) were open to an R(E)VN visiting their horse under the direction of a veterinary surgeon, with more than 90% being extremely or somewhat comfortable with R(E)VN visits for bandaging and suture removal. It is unclear how closely respondents' perceptions reflect those of the wider UK horse owner population. Horse owners appear to be open to further nursing services, with key procedures such as bandaging being a potential starting point. Understanding the career goals of the individual nurses and the needs of the practice will be key to the successful implementation of these services.
Registered nurses working on the frontline during the COVID-19 pandemic encountered significant challenges, including exposure to critical incidents. Critical incidents refer to sudden unexpected clinical events that surpass an individual's ability to cope, leading to considerable psychological distress, which could potentially result in the development of post-traumatic stress disorder symptoms. Research has shown a high prevalence of post-traumatic stress disorder symptoms among healthcare workers, particularly those in close contact with COVID-19 patients. To assess the levels of post-traumatic stress symptoms among registered nurses in relation to exposure to working conditions during the COVID-19 pandemic, such as how much their work was affected by the pandemic, re-deployment, working hours hindering sufficient recovery between shifts and critical incidents. Cross sectional study. The registered nurses working in multiple health care services covering all 21 geographic regions in Sweden. A total of 1,923 registered nurses, who are part of a Swedish national cohort and have been followed since their nursing education, were invited to participate in a survey in late September 2021 (15 to 19 years post graduation). The data were analyzed using descriptive statistics, unpaired t-tests, and one-way analysis of variance. Cohen's d was employed to quantify differences in mean levels between subgroups. The response rate were 56.5 %. Over 50 % of experienced registered nurses reported significant disruptions to their work environments. In total, 85 % of registered nurses were exposed to at least one critical incident in their work during the pandemic, with 60 % facing organisational changes and nearly 50 % experiencing emotionally distressing situations. The exposure to work situations involving critical incidents consistently demonstrated strong associations with higher levels of post-traumatic stress disorder symptoms compared to those not exposed, with effect sizes ranging from moderate to high. This study underscores the profound impact that working conditions, such as redeployment and exposure to critical incidents, have on the mental health of registered nurses. We offer valuable insights into registered nurses' pandemic-related challenges, highlighting the need for support and interventions to prevent and manage critical incidents, ultimately promoting their well-being. We also highlight the significance of thorough workforce readiness planning for future pandemics and other challenging health care scenarios, such as staff shortage.
Regression discontinuity design (RDD) is a quasi-experimental approach to study the causal effect of an exposure on later outcomes by exploiting the discontinuity in the exposure probability at an assignment variable cut-off. With the intent of facilitating the use of RDD in the Developmental Origins of Health and Disease (DOHaD) research, we describe the main aspects of the study design and review the studies, assignment variables and exposures that have been investigated to identify short- and long-term health effects of early life exposures. We also provide a brief overview of some of the methodological considerations for the RDD identification using an example of a DOHaD study. An increasing number of studies investigating the effects of early life environmental stressors on health outcomes use RDD, mostly in the context of education, social and welfare policies, healthcare organization and insurance, and clinical management. Age and calendar time are the mostly used assignment variables to study the effects of various early life policies and programs, shock events and guidelines. Maternal and newborn characteristics, such as age, birth weight and gestational age are frequently used assignment variables to study the effects of the type of neonatal care, health insurance, and newborn benefits, while socioeconomic measures have been used to study the effects of social and welfare programs. RDD has advantages, including intuitive interpretation, and transparent and simple graphical representation. It provides valid causal estimates if the assumptions, relatively weak compared to other non-experimental study designs, are met. Its use to study health effects of exposures acting early in life has been limited to studies based on registries and administrative databases, while birth cohort data has not been exploited so far using this design. Local causal effect around the cut-off, difficulty in reaching high statistical power compared to other study designs, and the rarity of settings outside of policy and program evaluations hamper the widespread use of RDD in the DOHaD research. Still, the assignment variables' cut-offs for exposures applied in previous studies can be used, if appropriate, in other settings and with additional outcomes to address different research questions.
Regressions, or backward saccades, are common during reading, accounting for between 5% and 20% of all saccades. And yet, relatively little is known about what causes them. We provide an information-theoretic operationalization for two previous qualitative hypotheses about regressions, which we dub reactivation and reanalysis. We argue that these hypotheses make different predictions about the pointwise mutual information or pmi between a regression's source and target. Intuitively, the pmi between two words measures how much more (or less) likely one word is to be present given the other. On one hand, the reactivation hypothesis predicts that regressions occur between words that are associated, implying high positive values of pmi. On the other hand, the reanalysis hypothesis predicts that regressions should occur between words that are not associated with each other, implying negative, low values of pmi. As a second theoretical contribution, we expand on previous theories by considering not only pmi but also expected values of pmi, E[pmi], where the expectation is taken over all possible realizations of the regression's target. The rationale for this is that language processing involves making inferences under uncertainty, and readers may be uncertain about what they have read, especially if a previous word was skipped. To test both theories, we use contemporary language models to estimate pmi-based statistics over word pairs in three corpora of eye tracking data in English, as well as in six languages across three language families (Indo-European, Uralic, and Turkic). Our results are consistent across languages and models tested: Positive values of pmi and E[pmi] consistently help to predict the patterns of regressions during reading, whereas negative values of pmi and E[pmi] do not. Our information-theoretic interpretation increases the predictive scope of both theories and our studies present the first systematic crosslinguistic analysis of regressions in the literature. Our results support the reactivation hypothesis and, more broadly, they expand the number of language processing behaviors that can be linked to information-theoretic principles.
Regular participation in physical activity (PA) benefits children's health and well-being and protects against the development of unhealthy body weight. A key factor in children's PA participation is their motor competence (MC). The comprehensive school physical activity program (CSPAP) framework offers a way to classify existing PA interventions that have included children's MC development and understand the potential avenues for supporting children's MC. However, there have been no systematic reviews or meta-analyses of PA interventions and their effects on the MC of elementary school children (aged 5-12 years) from a CSPAP perspective. This study was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We searched seven electronic databases (PubMed/Medline, Embase, ERIC, SPORTDiscus, CINAHL, Web of Science, and PsycINFO) for articles on 29 November 2021. The CSPAP framework was used to categorize the different intervention approaches. This review was registered with PROSPERO (CRD42020179866). Twenty-seven studies were included in the review, and twenty-six studies were included in the meta-analysis. A wide range of PA intervention approaches (e.g., single component or multicomponent) within the context of the CSPAP framework appear to be promising pathways in enhancing children's MC. The results of the aggregate meta-analysis presented that effect sizes for the development of MC from pre-and post- intervention ranged from moderate to large (Hedges' g = 0.41-0.79). The analysis revealed that the predicted moderators, including study length, delivery agent, and study design, did not result in statistically significant moderate variations in MC outcomes. There was, however, considerable heterogeneity in study design, instruments, and study context, and studies were implemented in over 11 countries across diverse settings. This study uniquely contributes to the literature through its primary focus on the effectiveness of PA interventions on elementary children's MC. This review emphasizes the importance of customizing CSPAP to fit the specific characteristics of each school setting, including its environmental, demographic, and resource attributes. The effectiveness of CSPAP, particularly its physical education (PE) component, is significantly enhanced when these programs are adapted to address the unique needs of each school. This adaptation can be effectively achieved through targeted professional teacher training, ensuring that PE programs are not only contextually relevant but also optimized for maximum impact in diverse educational environments. Researchers and practitioners should pursue how to effectively translate the evidence into practice to better conceptualize CSPAPs designed for children's MC development.
Regularity of menstrual cycles is an important indicator of women's health and fertility, and female workers are exposed to several factors, such as sleep disorders, stress, and shift work, that affect their menstrual regularity. This makes it necessary to comprehensively identify the determinants of menstrual regularity. Therefore, this study identified the factors affecting menstrual regularity among female workers from physiological, psychological, and situational dimensions based on the theory of unpleasant symptoms. This was a secondary analysis of the 2010-2012 Korea National Health and Nutrition Examination Survey and utilized the data of 2418 female workers. Based on the theory of unpleasant symptoms, physiological factors included age, age at menarche, childbirth experience, body mass index, and sleep duration. Psychological factors included stress level, depressive mood, and suicidal ideation. Situational factors included education level, household income, consumption of alcohol, engagement in smoking, and work schedule. The χ²-test and hierarchical logistic regression analysis were performed, reflecting the complex sample design. Age at menarche, childbirth experience, and body mass index among physiological factors and education level and work schedule among situational factors were found to be related to menstrual regularity. A higher risk of menstrual irregularities was found among those who had given birth (versus those who had not), had a high age at menarche (versus those with a low age at menarche), were obese (versus those who had a normal body mass index), had elementary school-level or lesser educational achievements (versus those with college graduate-level or higher educational achievements), and who had a shift work schedule (versus those with a fixed schedule). Intervention is needed for female workers who have these risk factors, and special attention must be paid to female workers who have a shift work schedule. Additionally, since body mass index can be controlled, intervention concerning body mass index is necessary to reduce menstrual irregularity.
Regulation of antibiotic prescription and consumption remains a major public health burden in low- and middle- income countries. This study aimed to describe the antibiotic consumption of patients who had a positive antibiotic culture in a reference laboratory. A retrospective descriptive study was conducted among 113 participants with positive antibiograms with a documented history of antibiotics intake at the Yaoundé University Teaching Hospital in Cameroon between January 2016 and June 2021. Data were stored and analyzed using the Census and Survey Processing System version 7.3 and Statistical Package for Social Science version 25.0. Descriptive statistics were used to estimate the indicators. Of the 113 patients enrolled, 105 had a history of drug use; 56 participants (53.3%) had taken at least 2 antibiotics prior to sampling. Cephalosporins were the most consumed antibiotics (41%), followed by nitroimidazols (28.6%) and penicillins (28.6%). According to the World Health Organization classification, 55 (52.4%) took major priority antibiotics. We are on the alert and there is an urgent need to raise awareness among clinicians and patients alike by providing them with good clinical practice guidelines.
Regulatory factor X 6 (RFX6) is crucial for pancreatic endocrine development and differentiation. The RFX6 variant p.His293LeufsTer7 is significantly enriched in the Finnish population, with almost 1:250 individuals as a carrier. Importantly, the FinnGen study indicates a high predisposition for heterozygous carriers to develop type 2 and gestational diabetes. However, the precise mechanism of this predisposition remains unknown. To understand the role of this variant in beta cell development and function, we used CRISPR technology to generate allelic series of pluripotent stem cells. We created two isogenic stem cell models: a human embryonic stem cell model; and a patient-derived stem cell model. Both were differentiated into pancreatic islet lineages (stem-cell-derived islets, SC-islets), followed by implantation in immunocompromised NOD-SCID-Gamma mice. Stem cell models of the homozygous variant RFX6-/- predictably failed to generate insulin-secreting pancreatic beta cells, mirroring the phenotype observed in Mitchell-Riley syndrome. Notably, at the pancreatic endocrine stage, there was an upregulation of precursor markers NEUROG3 and SOX9, accompanied by increased apoptosis. Intriguingly, heterozygous RFX6+/- SC-islets exhibited RFX6 haploinsufficiency (54.2% reduction in protein expression), associated with reduced beta cell maturation markers, altered calcium signalling and impaired insulin secretion (62% and 54% reduction in basal and high glucose conditions, respectively). However, RFX6 haploinsufficiency did not have an impact on beta cell number or insulin content. The reduced insulin secretion persisted after in vivo implantation in mice, aligning with the increased risk of variant carriers to develop diabetes. Our allelic series isogenic SC-islet models represent a powerful tool to elucidate specific aetiologies of diabetes in humans, enabling the sensitive detection of aberrations in both beta cell development and function. We highlight the critical role of RFX6 in augmenting and maintaining the pancreatic progenitor pool, with an endocrine roadblock and increased cell death upon its loss. We demonstrate that RFX6 haploinsufficiency does not affect beta cell number or insulin content but does impair function, predisposing heterozygous carriers of loss-of-function variants to diabetes. Ultra-deep bulk RNA-seq data for pancreatic differentiation stages 3, 5 and 7 of H1 RFX6 genotypes are deposited in the Gene Expression Omnibus database with accession code GSE234289. Original western blot images are deposited at Mendeley ( https://data.mendeley.com/datasets/g75drr3mgw/2 ).
Rehabilitation is an important and necessary part of local and global healthcare services along with treatment and palliative care, prevention of disease, and promotion of good health. The rehabilitation process helps older and young adults even children to become as independent as possible in activities of daily life and enables participation in useful living activities, recreation, work, and education. The technology of Artificial Intelligence (AI) has evolved significantly in recent years. Many activities related to rehabilitation have been getting benefits from using AI techniques. The objective of this review study is to explore the advantages of AI for rehabilitation and how AI is impacting the rehabilitation process. This study aims at the most critical aspects of the rehabilitation process that could potentially take advantage of AI techniques including personalized rehabilitation apps, rehabilitation through assistance, rehabilitation for neurological disorders, rehabilitation for developmental disorders, virtual reality rehabilitation, rehabilitation of neurodegenerative diseases and Telerehabilitation of Cardiovascular. We presented a survey on the newest empirical studies available in the literature including the AI-based technology helpful in the Rehabilitation process. The novelty feature included but was not limited to an overview of the technological solutions useful in rehabilitation. Seven different categories were identified. Illustrative examples of practical applications were detailed. Implications of the findings for both research and practice were critically discussed. Most of the AI applications in these rehabilitation types are in their infancy and continue to grow while exploring new opportunities. Therefore, we investigate the role of AI technology in rehabilitation processes. In addition, we do statistical analysis of the selected studies to highlight the significance of this review work. In the end, we also present a discussion on some challenges, and future research directions.
Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ), reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787). Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG), followed by meta-analysis (N>6500) at the single marker level. Twin modelling showed RC is highly heritable (67%), has considerable genetic overlap with IQ (59%), and is a major component of genetic covariation between reasoning and working memory (72%). At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB), and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.