Yoxas/statistical_literacy huggingface dataset:
Dietary pattern analysis is a robust statistical procedure that efficiently characterize the dietary intakes of individuals. However, there is a lack of robust dietary intake evidence beyond nutrient intake in Ethiopia. This study was to answer, what are the major dietary consumption patterns and its predictors among pregnant women in Ethiopia. A facility-based survey among 380 randomly selected pregnant women using a contextualized food frequency questionnaire (FFQ) over 1 month recall was used. The frequency of food consumption was standardized to daily frequency equivalents, and a sequential exploratory factor analysis was used to derive major dietary patterns. A multivariable ordinary logistic regression model was fitted with all its assumptions. Three major dietary patterns ("fruits and animal-source foods," "cereals, tubers, and sweet foods," "legumes and vegetables"), explaining 65% of the total variation were identified. Women snacks (AOR = 1.93; 1.23-2.75), without food aversion (AOR = 1.59; 1.08-2.35), non-fasting (AOR = 0.75; 1.12-2.12), and receiving nutritional counseling (AOR = 1.96; 1.25-3.07) were significantly positively associated with a higher tercile of fruits and animal-source food consumption. Non-working mothers (AOR = 1.8;1.23-2.76), chronic disease (AOR = 1.88; 1.14-3.09), or received nutritional counseling (AOR = 1.33; 0.88-2.01), were fasting (AOR = 1.33;0.88-2.01), and no food cravings (AOR = 4.27;2.67-6.84), and aversion (AOR = 1.60;1.04-2.44) had significantly higher odds of consuming cereals, tubers, and sweet foods. Literacy (AOR = 1.87; 1.14-3.09), urban residence (AOR = 2.10; 1.10-3.93), low socioeconomic class (AOR = 2.68; 1.30-5.23), and skipping meals (AOR = 1.73; 1.15-2.62) were associated with higher odds of legume and vegetable consumption. Socioeconomic class, literacy, occupation, getting nutritional counseling, habits of food craving, food aversion, and fasting can predict a woman's dietary pattern.
Dietary patterns describe the dietary behaviour and habits of individuals. Unhealthy dietary patterns provide individuals with limited nutrients while increasing the risk of nutrition-related diseases. Unhealthy dietary patterns are high in urban areas, especially among low-income urban residents. This study examined dietary patterns in three low-income urban communities in Accra, Ghana, between 2011 and 2013. This study used Wave 2 and 3 data from the Urban Health and Poverty Survey (EDULINK 2011 and 2013). The sample size was 960 in 2011 and 782 in 2013. Dietary pattern was examined using factor analysis and the NOVA food classification system. Summary statistics were computed for sociodemographic characteristics and diet frequency and pattern. Differences in dietary behaviours between 2011 and 2013 were also estimated. Three logistic regression models were computed to determine the predictors of dietary patterns. The frequency of consumption of animal-source foods (ASF) and fruits was higher in 2013 compared with 2011. The intake of processed culinary ingredients (NOVA Group 2), processed foods (NOVA Group 3) and ultra-processed foods (NOVA Group 4) was higher in 2013 versus 2011. In 2013, 29% consumed ultra-processed foods compared to 21% in 2011. Three dietary patterns (rice-based, snack-based, and staple and stew/soup) were identified. About two out of every five participants consumed the food items in the rice (43%) and staple and sauce patterns (40%). The proportion of participants who consumed the food items in the snack pattern was 35% in 2011 but 41% in 2013. Respondents aged 25-34 and those with higher education often consumed the snack-based and rice-based dietary patterns. In 2013, participants in Ussher Town had a higher probability of consuming food items in the snack pattern than those living in Agbogbloshie. This study found that between 2011 and 2013, more participants consumed ASFs, fruits, and processed foods. A complex interplay of personal and socio-cultural factors influenced dietary intake. The findings of this study mirror global changes in diet and food systems, with important implications for the primary and secondary prevention of NCDs. Health promotion programs at the community level are needed to address the increasing levels of processed food consumption.
Dietary rationality and health concept have certain influence on individual health level. This study aims to explore the characteristics and existing problems of Chinese residents' health behaviors from both macro and micro perspectives, and explore the feasibility and realization path of Healthy China strategy. We utilized regression models to evaluate the correlation between diet and the risk of disease causes of death. By use of the linear regression analysis model, we distinguished the impact of each dimension on health literacy index at the individual level. Then, we explored the influential factors of the diet health index using the binary logit regression model. Increased consumption of animal-derived foods in China has contributed to the burden of non-communicable diseases. The individuals' health awareness is still weak, and the health literacy index is greatly affected by the diet, while the individual gender and age are positively correlated with the diet health index, and the individual body mass index (BMI) level is negatively correlated with the diet health index. This study provided a comprehensive understanding of existing problems of Chinese residents' health behaviors. We have proposed a path model for the implementation of the Healthy China strategy from the perspectives of "diet health, physical health, conceptual health and environmental health," which is also a great contribution to the world.
Different and contradictory results have been reported for nurses' caring behaviour and moral sensitivity. The present study aimed to examine the correlation between nurses' caring behaviour and moral sensitivity. The research was a descriptive, correlational study. Data were collected using moral sensitivity (range: 0-100) and caring behaviour (range: 24-144) questionnaires. A total of 250 nurses who worked in the clinical wards of Yasuj teaching hospitals in 2018, were selected by systematic random sampling. The collected data were analysed using SPSS version 19 for descriptive statistics and Pearson correlation tests. Seventy-four percent of nurses had moderate moral sensitivity (50-74). Nurses' moral sensitivity and caring behaviour mean scores were reported to be 59.5 ± 11.1 (range: 31-87) (Potential range 0--100) and 110.99 ± 17.99 (range: 69-94) (Potential range 22-144), respectively. The Pearson test showed a positive correlation between nurses' caring behaviour and moral sensitivity at a 99% level (p = 0.001). Nurses' moral sensitivity and caring behaviour were found to be moderate and good, respectively. Furthermore, there was a positive correlation between moral sensitivity and caring behaviour in nurses, that is, nurses provided better caring behaviour as levels of moral sensitivity increased.
Different clinical practice guidelines include recommendations on how to prevent and repair obstetric perineal trauma, as well as the use of episiotomy. To evaluate the variability in midwives' professional practices for preventing and repairing perineal trauma, as well as the professional factors that may be associated with the restrictive use of episiotomy. Observational cross-sectional study. Three hundred five midwives completed an anonymous questionnaire developed by the authors and distributed across various midwifery scientific societies. The main outcomes measured were the frequencies of adopting specific practices related to perineal injury prevention and repair, episiotomy technique and restrictive episiotomy use (<10%). Odds ratios (OR) and adjusted odds ratios (aOR) with 95% confidence intervals were estimated. Intrapartum perineal massage was not normally used by 253 (83%) of midwives, and 186 (61%) applied compresses soaked in warm water to the perineum. Regarding episiotomy, there was a great deal of variability, noting that 129 (42.3%) adopted a restrictive use of this procedure, 125 (41%) performed it between 10% and 20%, while 51 midwives (16.7%) performed it in more than 20% of cases. In addition, 165 (54.1%) midwives followed an incision angle of 60º. Concerning tears, 155 (50.8%) usually sutured first-degree tears and 273 (89.5%) always sutured second-degree tears. Midwives attending home births (aOR = 6.5; 95% CI: 2.69-15.69), working at a teaching hospital (aOR = 3.69; 95% CI: 1.39-9.84), and the ones who recently completed their professional training (aOR = 3.58; 95% CI: 1.46-8.79) were significantly more likely to adopt a restrictive use of episiotomy. There is a significant variability in Spanish midwives' practices for preventing and repairing perineal tears. Moreover, the restrictive use of episiotomy is associated with midwives attending home births, working in teaching hospitals and having recent professional training. No patient or public contribution.
Different curative treatment modalities need to be considered in case of localized prostate cancer, all comparable in terms of survival and recurrence though different in side effects. To better inform patients and support shared decision making, the development of a web-based patient decision aid including personalized risk information was proposed. This paper reports on requirements in terms of content of information, visualization of risk profiles, and use in practice. Based on a Dutch 10-step guide about the setup of a decision aid next to a practice guideline, an iterative and co-creative design process was followed. In collaboration with various groups of experts (health professionals, usability and linguistic experts, patients and the general public), research and development activities were continuously alternated. Content requirements focused on presenting information only about conventional treatments and main side effects; based on risk group; and including clear explanations about personalized risks. Visual requirements involved presenting general and personalized risks separately; through bar charts or icon arrays; and along with numbers or words, and legends. Organizational requirements included integration into local clinical pathways; agreement about information input and output; and focus on patients' numeracy and graph literacy skills. The iterative and co-creative development process was challenging, though extremely valuable. The translation of requirements resulted in a decision aid about four conventional treatment options, including general or personalized risks for erection, urinary and intestinal problems that are communicated with icon arrays and numbers. Future implementation and validation studies need to inform about use and value in practice.
Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.
Different studies identify mental health literacy as a protective factor for developing a mental health problem. The aim of this paper was to determine the degree of mental health literacy of the adolescent population of Barcelona, and its relationship with socio-demographic and educational variables. A cross-sectional study was carried out in Barcelona during the 2017-2018 academic year. A total of 1,032 young people between thirteen and seventeen years of age participated. The following variables were collected: sex, age, nationality, socioeconomic status (RDHpc) and average school grade. The aim was to determine the degree of mental health literacy (knowledge, stigma and help-seeking) of the adolescent population of Barcelona, and its relationship with socio-demographic and educational variables. Multiple linear regression analysis was performed adjusting for the effect of sociodemographic variables on the score of each scale. The mean score (standard deviation) of the EMHL test was 7.28 (1.27) and 4.24 (1.14) respectively, with higher scores obtained by girls, high RDHpc, excellent score and Spanish nationality. The greatest difference in EMHL scores, adjusting for the rest of the variables, corresponded to adolescents with an excellent mean score and a high RDHpc index (with respect to the baseline category, beta=0.72 and 0.52 respectively). The mean stigma score was 27.6 (4.47) for CAMI and 8.83 (3.36) for RIBS. The variables related to a greater difference in score with respect to the baseline category and adjusted for the rest of the variables were: gender (boy=1.54) and academic grade (excellent=-2.38) for CAMI, and nationality (foreign=0.82) and academic grade (excellent=-1.30) for RIBS. The mean RIBS score was 8.83 (3.36) with the largest difference in score from baseline being foreign nationality (beta=0.82) and having a grade of excellent (1.30). Help-seeking was higher in parents and friends, with differences according to gender and nationality. The level of mental health literacy is medium-low. While gender, nationality and educational attainment are the factors that are related to knowledge and stigma, socio-economic status is only related to mental health literacy.
Differential attainment is a well-known phenomenon in medical education. Despite a strong impetus for institutions and researchers to move away from a 'student deficit model' when exploring the attainment gap, little attention has been given to understanding the experiences of Black, Asian and Minority Ethnic (BAME) medical students. Informed by the social construction of learning theory, this is the first national study to explore how multiple dimensions of the medical school environment impact academic performance of BAME undergraduate medical students across the UK. Using a sequential explanatory mixed-methods approach, the authors conducted a survey and facilitated three focus groups across medical schools in the UK between 2020-2021. Participants self-identified as being from BAME backgrounds. Quantitative analyses included descriptive statistics and bivariate analyses. Qualitative data were analysed using thematic analysis, subsequently identifying inductive themes. Three hundred sixty-two respondents completed the Phase 1 survey, and 17 participants participated in the Phase 2 focus groups. Although both survey and focus group participants identified facilitators to learning such as supportive relationships, students reported facing numerous barriers that they felt impeded their learning and performance. These barriers included limited access to educational resources, and undiversified curricula and medical school populations. Students also described both experiencing and witnessing various forms of racism throughout their educational journeys. Students encountered various difficulties throughout their medical training that they felt impacted their learning and performance. This study offers novel insights into the experiences of BAME students and builds upon previous research. It also reveals the pervasive nature of racism within medical schools, highlighting the urgent need for institutional changes. Educators and institutions must go beyond merely recognising these barriers and facilitators; they must proactively innovate and adapt. In doing so, they pave the way for inclusive learning environments that truly foster a sense of belonging for BAME students.
Differential item functioning (DIF) is a standard analysis for every testing company. Research has demonstrated that DIF can result when test items measure different ability composites, and the groups being examined for DIF exhibit distinct underlying ability distributions on those composite abilities. In this article, we examine DIF from a two-dimensional multidimensional item response theory (MIRT) perspective. We begin by delving into the compensatory MIRT model, illustrating and how items and the composites they measure can be graphically represented. Additionally, we discuss how estimated item parameters can vary based on the underlying latent ability distributions of the examinees. Analytical research highlighting the consequences of ignoring dimensionally and applying unidimensional IRT models, where the two-dimensional latent space is mapped onto a unidimensional, is reviewed. Next, we investigate three different approaches to understanding DIF from a MIRT standpoint: 1. Analytically Uniform and Nonuniform DIF: When two groups of interest have different two-dimensional ability distributions, a unidimensional model is estimated. 2. Accounting for complete latent ability space: We emphasize the importance of considering the entire latent ability space when using DIF conditional approaches, which leads to the mitigation of DIF effects. 3. Scenario-Based DIF: Even when underlying two-dimensional distributions are identical for two groups, differing problem-solving approaches can still lead to DIF. Modern software programs facilitate routine DIF procedures for comparing response data from two identified groups of interest. The real challenge is to identify why DIF could occur with flagged items. Thus, as a closing challenge, we present four items (Appendix A) from a standardized test and invite readers to identify which group was favored by a DIF analysis.
Differential methylation (DM) is actively recruited in different types of fundamental and translational studies. Currently, microarray- and NGS-based approaches for methylation analysis are the most widely used with multiple statistical models designed to extract differential methylation signatures. The benchmarking of DM models is challenging due to the absence of gold standard data. In this study, we analyze an extensive number of publicly available NGS and microarray datasets with divergent and widely utilized statistical models and apply the recently suggested and validated rank-statistic-based approach Hobotnica to evaluate the quality of their results. Overall, microarray-based methods demonstrate more robust and convergent results, while NGS-based models are highly dissimilar. Tests on the simulated NGS data tend to overestimate the quality of the DM methods and therefore are recommended for use with caution. Evaluation of the top 10 DMC and top 100 DMC in addition to the not-subset signature also shows more stable results for microarray data. Summing up, given the observed heterogeneity in NGS methylation data, the evaluation of newly generated methylation signatures is a crucial step in DM analysis. The Hobotnica metric is coordinated with previously developed quality metrics and provides a robust, sensitive, and informative estimation of methods' performance and DM signatures' quality in the absence of gold standard data solving a long-existing problem in DM analysis.
Differentiated service delivery (DSD) for children and adolescents living with HIV can improve targeted resource use. We derived a mortality prediction score to guide clinical decision making for children and adolescents living with HIV. Data for this retrospective observational cohort study were evaluated for all children and adolescents living with HIV and initiating antiretroviral therapy (ART); aged 0-19 years; and enrolled at Baylor clinics in Eswatini, Malawi, Lesotho, Tanzania, and Uganda between 2005 and 2020. Data for clinical prediction, including anthropometric values, physical examination, ART, WHO stage, and laboratory tests were captured at ART initiation. Backward stepwise variable selection and logistic regression were performed to develop predictive models for mortality within 1 year of ART initiation. Probabilities of mortality were generated, compared with true outcomes, internally validated, and evaluated against WHO advanced HIV criteria. The study population included 16 958 children and adolescents living with HIV and initiated on ART between May 18, 2005, and Dec 18, 2020. Predictive variables for the most accurate model included: age, CD4 percentage, white blood cell count, haemoglobin concentration, platelet count, and BMI Z score as continuous variables, and WHO clinical stage and oedema, abnormal muscle tone and respiratory distress on examination as categorical variables. The area under the curve (AUC) of the predictive model was 0·851 (95% CI 0·839-0·863) in the training set and 0·822 (0·800-0·845) in the test set, compared with 0·606 (0·595-0·617) for the WHO advanced HIV criteria (p<0·0001). This study evaluated a large, multinational population to derive a mortality prediction tool for children and adolescents living with HIV. The model more accurately predicted clinical outcomes than the WHO advanced HIV criteria and has the potential to improve DSD for children and adolescents living with HIV in high-burden settings. National Institute of Health Fogarty International Center.
Difficulty identifying effective pharmacotherapies for cocaine dependence has led to suggestions that subgroup differences may account for some of the heterogeneity in treatment response. Well-attested methodological difficulties associated with these analyses recommend the use of Bayesian statistical reasoning for evaluation of salient interaction effects. A secondary data analysis of a previously published, double-blind, randomized controlled trial examines the interaction of decision-making, as measured by the Iowa Gambling Task, and citalopram in increasing longest sustained abstinence from cocaine use. Bayesian analysis indicated that there was a 99% chance that improved decision-making enhances response to citalopram. Given the strong positive nature of this finding, a formal, quantitative Bayesian approach to evaluate the result from the perspective of a skeptic was applied. Bayesian statistical reasoning provides a formal means of weighing evidence for the presence of an interaction in scenarios where conventional, Frequentist analyses may be less informative. [Supplementary materials are available for this article. Go to the publisher's online edition of The American Journal of Drug and Alcohol Abuse for the following free supplemental resource: Appendix 1].