Yoxas/statistical_literacy huggingface dataset:
Self-rated health (SRH) has been identified in many studies as a valid predictor of mortality and healthcare utilization. There is limited research on SRH and dietary intake. This study aimed to investigate the association between healthy eating index (HEI) and SRH in adults living in Tehran. This cross-sectional study was carried out among 850 adult men and women aged 20-59 years who visited health centers in Tehran from 2021 to 2022. Dietary intake was assessed using a validated and reliable semiquantitative food frequency questionnaire with 168 food items, and SRH was assessed with one question: "In general, how do you rate your health?". We categorized SRH into excellent/very good, good, and fair/poor. In the descriptive statistics part, we used mean ± standard deviation or number (ratio) for quantitative and qualitative variables, respectively. The chi-squared test and one-way analysis of variance were used to calculate the percentage and mean for demographic characteristics across tertiles of SRH. An analysis of covariance was used to compare the means of energy, macronutrients, the HEI, and its component variables across the tertiles of SRH. The final sample included 795 participants (68.2% female; mean ± standard deviation age: 44.81 ± 10.62 years) whose 40% reported excellent/very good SRH, and 30% reported good and fair/poor SRH separately. There was no association between body mass index, physical activity, education, health status, smoking, and sleep duration with SRH. After adjustment, the total HEI score and its component scores did not differ across the tertiles of SRH status. However, participants with good SRH had a higher intake of total energy (mean difference (MD): 180.33 Kcal, P value < 0.001), total fat (MD: 8.15 gr, P value = 0.002), and total carbohydrates (MD: 20.18 gr, P value = 0.004) than those with fair/poor SRH. According to our findings, fair/poor SRH was associated with a lower consumption of total energy, total fat, and total carbohydrates in Iranian adults. Additional observational studies would be necessary to clarify these findings.
Self-reflection is a valuable method that nurse educators can use to develop clinical judgment skills among prelicensure nursing students. Little research exists on improving clinical judgment in second-degree nursing students in the clinical setting. To determine the implications of increasing clinical judgment skills in prelicensure nursing students using a shared structured reflection teaching innovation within a required baccalaureate clinical course. This educational innovation used qualitative descriptive methods to evaluate its effectiveness in the clinical setting among students in the final semester of an accelerated prelicensure nursing program. Students reported increased accountability for their learning, a sense of intentionality with their nursing practice, and a deeper sense of community with their peers. Shared reflective practices in the clinical setting show promise for increasing clinical judgment and supporting a competency-based curriculum.
Self-regulated learning (SRL) is gaining widespread recognition as a vital competency that is desirable to sustain lifelong learning, especially relevant to health professions education. Contemporary educational practices emphasize this aspect of undergraduate medical education through innovative designs of teaching and learning, such as the flipped classroom and team-based learning. Assessment practices are less commonly deployed to build capacity for SRL. Assessment as learning (AaL) can be a unique way of inculcating SRL by enabling active learning habits. It charges students to create formative assessments, reinforcing student-centered in-depth learning and critical thinking. This study aimed to explore, from the learners' perspectives, the feasibility and perceived learning impact of student-generated formative assessments. This study relied on a convergent mixed methods approach. An educational intervention was deployed on a cohort of 54 students in the second year of a 6-year undergraduate medical program as part of a single-course curriculum. The AaL intervention engaged students in generating assessments using peer collaboration, tutor facilitation, and feedback. The outcomes of the intervention were measured through quantitative and qualitative data on student perceptions, which were collected through an anonymized web-based survey and in-person focus groups, respectively. Quantitative survey data were analyzed using SPSS (IBM), and qualitative inputs underwent thematic analysis. The students' overall score of agreement with the AaL educational intervention was 84%, which was strongly correlated with scores for ease and impact on a 5-point Likert-type scale. The themes that emerged from the qualitative analysis included prominent characteristics, immediate gains, and expected long-term benefits of engagement. The prominent characteristics included individuals' engagement, effective interdependencies, novelty, and time requirements. The identified immediate gains highlighted increased motivation and acquisition of knowledge and skills. The expected long-term benefits included critical thinking, problem solving, and clinical reasoning. As a form of AaL, student-generated assessments were perceived as viable, constructive, and stimulating educational exercises by the student authors. In the short term, the activity provided students with a fun and challenging opportunity to dive deeply into the content, be creative in designing questions, and improve exam-taking skills. In the long term, students expected an enhancement of critical thinking and the inculcation of student-centered attributes of self-regulated lifelong learning and peer collaboration, which are vital to the practice of medicine.
Self-regulated learning in higher education has increasingly attracted attention in recent years. This study involved a survey of nursing students using an originally developed tool called the Self-regulated Learning Strategy Scale for Undergraduate Nursing Students (SRLSS-NS). We aimed to elucidate factors relating to the promotion of self-regulated learning while confirming the reliability and validity of the novel scale. A cross-sectional survey design was adopted. School of Health Science, Faculty of Medicine. Participants included first- to fourth-year undergraduate nursing students. Descriptive statistics were used to ascertain participant characteristics. We confirmed the criterion-related validity of the survey through exploratory factor analysis and Pearson's product-moment coefficient with external criteria. Reliability was calculated using Cronbach's α coefficient. To examine stability, we confirmed the correlation between the first and second surveys. Multiple regression analysis was performed using the SRLSS-NS score as the objective variable and basic attributes/individual factors, learning-related factors, and cognitive factors as explanatory variables. The statistical significance level was defined as 5 %. The scale consisted of 12 items related to three factors-construct validity, internal consistency, and stability-which were confirmed. Regarding factors related to the SRLS of undergraduate nursing students, the SRLSS-NS score was greater for items such as, "I feel that university education gives me confidence in learning" (β = 0.255, p < 0.001), "I like/find interest in things I am learning" (β = 0.228, p < 0.001), "I feel that university education teaches me how to learn" (β = 0.198, p = 0.003), and "Self-esteem as a professional" (β = 0.143, p = 0.023). As more efforts are made to improve undergraduate nursing students' SRLS, the importance of education for increasing confidence, promoting intrinsic motivation, teaching learning methods, and fostering occupational identity is emphasized.
Semantic intrusion errors on memory tests may represent very early cognitive changes associated with elevated Alzheimer's disease pathology within the brain, including amyloid-β (Aβ). Subscales that measure proactive semantic interference (PSI) and intrusions related to PSI on the Loewenstein Acevedo Scales of Semantic Interference and Learning (LASSI-L) have been associated with high levels of brain amyloid load, structural changes on brain MRI in Hispanic and non-Hispanic groups. It is presently unknown whether intrusion errors or other measures of the LASSI-L can differentiate between African-American (AA) older adults diagnosed with amnestic mild cognitive impairment (aMCI) or classified as cognitively normal (CN). This study examined the extent to which a high percentage of semantic intrusion errors on LASSI-L subscales susceptible to PSI and other LASSI-L measures could differentiate between AA aMCI and CN groups. Forty-eight AA older adults were recruited (27 CN and 21 aMCI) and received a through clinical and neuropsychological evaluation. The LASSI-L was administered independent of diagnostic classification. With and without statistical adjustment for literacy, AA aMCI participants scored lower on all LASSI-L measures. ROC analyses revealed an area under the curve exceeding 90% and correctly classified 86% of AA aMCI with 82% specificity for AA CN participants. Percentage of intrusion errors on the LASSI-L subscales susceptible to PSI differentiated AA aMCI from AA CN. This adds to emerging evidence indicating that the LASSI-L may be culturally appropriate and can differentiate between aMCI and CN in diverse ethnic/cultural groups.
Semantic segmentation has achieved great progress by effectively fusing features of contextual information. In this article, we propose an end-to-end semantic attention boosting (SAB) framework to adaptively fuse the contextual information iteratively across layers with semantic regularization. Specifically, we first propose a pixelwise semantic attention (SAP) block, with a semantic metric representing the pixelwise category relationship, to aggregate the nonlocal contextual information. In addition, we improve the computation complexity of SAP block from O(n²) to O(n) for images with size n. Second, we present a categorywise semantic attention (SAC) block to adaptively balance the nonlocal contextual dependencies and the local consistency with a categorywise weight, overcoming the contextual information confusion caused by the feature imbalance within intra-category. Furthermore, we propose the SAB module to refine the segmentation with SAC and SAP blocks. By applying the SAB module iteratively across layers, our model shrinks the semantic gap and enhances the structure reasoning by fully utilizing the coarse segmentation information. Extensive quantitative evaluations demonstrate that our method significantly improves the segmentation results and achieves superior performance on the PASCAL VOC 2012, Cityscapes, PASCAL Context, and ADE20K datasets.
Senegal has certainly made significant efforts in adult literacy and in the fight against maternal and infant mortality. However, a large proportion of the female population is illiterate, and the country's maternal and infant mortality rates are still higher than WHO recommendations. This article examined the effect of women's literacy on maternal and child health in Senegal. Data were extracted from the last Senegal Demographic and Health Surveys (DHS) collected in 2019. A binary logistic model was performed to assess the effect of women's literacy on ten outcomes of maternal and child health indicators. Results indicate that women's literacy has a positive and significant effect on nine of key indicators outcomes. For instance, women's literacy increases the odds of contraceptive use by 1.29 (95% Confidence Interval [CI], 1.13-1.48; p < 0.01), compliance with the number of prenatal visits by 1.57 (95% CI, 1.35-1.83; p < 0.01) and consultation in the first trimester of pregnancy by 1.52 (95% CI, 1.31-1.78; p < 0.01). Literacy is associated with increased odds of breastfeeding up to six months (Odds Ratio [OR], 1.17; 95% CI, 0.97-1.42; p < 0.1) and healthy birth interval (OR, 1.18; 95% CI, 0.97-1.44; p < 0.1) only in rural areas. Women literacy reduces the risk of stunting by 0.81 (95% CI, 0.68-0.96; p < 0.05) and the risk of underweight by 0.72 (95% CI, 0.59-0.87; p < 0.01) among children under five years. The mother's ability to read and write favors compliance with the increase of odds of DPT vaccination record of her children, especially in rural areas (OR, 1.69; 95% CI, 1.05-2.74; p < 0.05). Moreover, there are serval other factors influencing positively the maternal and child health, like health insurance access, media exposure, and clean water and improved sanitation facilities access. This study emphasizes on the need to strengthen adult literacy programs, especially for women in rural areas. Indeed, this could help generalize health insurance by income-sensitive premiums or exemptions for the poor as well as increased awareness campaigns to promote reproductive and maternal health benefits, via the radio or television. Furthermore, improving access to clean water supply and improved sanitation facilities would greatly ameliorate maternal and child health.
Senegal has demonstrated catalytic improvements in national coverage rates for early childhood vaccination, despite lower development assistance for childhood vaccines in Senegal compared with other low-income and lower-middle income countries. Understanding factors associated with historical changes in childhood vaccine coverage in Senegal, as well as heterogeneities across its 14 regions, can highlight effective practices that might be adapted to improve vaccine coverage elsewhere. Childhood vaccination coverage rates, demographic information and health system characteristics were identified from Senegal's Demographic and Health Surveys (DHS) and Senegal national reports for years 2005-2019. Multivariate logistic and linear regression analyses were performed to determine statistical associations of demographic and health system characteristics with respect to childhood vaccination coverage rates. The 14 administrative regions of Senegal were chosen for analysis. DHS women's survey respondents with living children aged 12-23 months for survey years 2005-2019. Immunisation with the third dose of the diphtheria-tetanus-pertussis vaccine (DTP3), widely used as a proxy for estimating immunisation coverage levels and the retention of children in the vaccine programme. Factors associated with childhood vaccination coverage include urban residence (β=0.61, p=0.0157), female literacy (β=1.11, p=0.0007), skilled prenatal care (β=1.80, p<0.0001) and self-reported ease of access to care when sick, considering travel distance to a healthcare facility (β=-0.70, p=0.0009) and concerns over travelling alone (β=-1.08, p<0.0001). Higher coverage with less variability over time was reported in urban areas near the capital and the coast (p=0.076), with increased coverage in recent years in more rural and landlocked areas. Childhood vaccination was more likely among children whose mothers had higher literacy, received skilled prenatal care and had perceived ease of access to care when sick. Overall, vaccination coverage is high in Senegal and disparities in coverage between regions have decreased significantly in recent years.
Sensitivity to pain varies considerably between individuals and is known to be heritable. Increased sensitivity to experimental pain is a risk factor for developing chronic pain, a common and debilitating but poorly understood symptom. To understand mechanisms underlying pain sensitivity and to search for rare gene variants (MAF<5%) influencing pain sensitivity, we explored the genetic variation in individuals' responses to experimental pain. Quantitative sensory testing to heat pain was performed in 2,500 volunteers from TwinsUK (TUK): exome sequencing to a depth of 70× was carried out on DNA from singletons at the high and low ends of the heat pain sensitivity distribution in two separate subsamples. Thus in TUK1, 101 pain-sensitive and 102 pain-insensitive were examined, while in TUK2 there were 114 and 96 individuals respectively. A combination of methods was used to test the association between rare variants and pain sensitivity, and the function of the genes identified was explored using network analysis. Using causal reasoning analysis on the genes with different patterns of SNVs by pain sensitivity status, we observed a significant enrichment of variants in genes of the angiotensin pathway (Bonferroni corrected p = 3.8×10(-4)). This pathway is already implicated in animal models and human studies of pain, supporting the notion that it may provide fruitful new targets in pain management. The approach of sequencing extreme exome variation in normal individuals has provided important insights into gene networks mediating pain sensitivity in humans and will be applicable to other common complex traits.
Sentence-based mathematics problem-solving skills are essential as the skills can improve the ability to deal with various mathematical problems in daily life, increase the imagination, develop creativity, and develop an individual's comprehension skills. However, mastery of these skills among students is still unsatisfactory because students often find it difficult to understand mathematical problems in verse, are weak at planning the correct solution strategy, and often make mistakes in their calculations. This study was conducted to identify the challenges that mathematics teachers face when teaching sentence-based mathematics problem-solving skills and the approaches used to address these challenges. This study was conducted qualitatively in the form of a case study. The data were collected through observations and interviews with two respondents who teach mathematics to year four students in a Chinese national primary school in Kuala Lumpur. This study shows that the teachers have faced three challenges, specifically low mastery skills among the students, insufficient teaching time, and a lack of ICT infrastructure. The teachers addressed these challenges with creativity and enthusiasm to diversify the teaching approaches to face the challenges and develop interest and skills as part of solving sentence-based mathematics problems among year four students. These findings allow mathematics teachers to understand the challenges faced while teaching sentence-based mathematics problem solving in depth as part of delivering quality education for every student. Nevertheless, further studies involving many respondents are needed to understand the problems and challenges of different situations and approaches that can be used when teaching sentence-based mathematics problem-solving skills.
Sentic computing relies on well-defined affective models of different complexity-polarity to distinguish positive and negative sentiment, for example, or more nuanced models to capture expressions of human emotions. When used to measure communication success, even the most granular affective model combined with sophisticated machine learning approaches may not fully capture an organisation's strategic positioning goals. Such goals often deviate from the assumptions of standardised affective models. While certain emotions such as Joy and Trust typically represent desirable brand associations, specific communication goals formulated by marketing professionals often go beyond such standard dimensions. For instance, the brand manager of a television show may consider fear or sadness to be desired emotions for its audience. This article introduces expansion techniques for affective models, combining common and commonsense knowledge available in knowledge graphs with language models and affective reasoning, improving coverage and consistency as well as supporting domain-specific interpretations of emotions. An extensive evaluation compares the performance of different expansion techniques: (i) a quantitative evaluation based on the revisited Hourglass of Emotions model to assess performance on complex models that cover multiple affective categories, using manually compiled gold standard data, and (ii) a qualitative evaluation of a domain-specific affective model for television programme brands. The results of these evaluations demonstrate that the introduced techniques support a variety of embeddings and pre-trained models. The paper concludes with a discussion on applying this approach to other scenarios where affective model resources are scarce.
Sentiments and opinions regarding COVID-19 and the COVID-19 vaccination on Indonesian-language Twitter are scarcely reported in one comprehensive study, and thus were aimed at our study. We also analyzed fake news and facts, and Twitter engagement to understand people's perceptions and beliefs that determine public health literacy. We collected 3,489,367 tweets data from January 2020 to August 2021. We analyzed factual and fake news using the string comparison method. The difflib library was used to measure similarity. The user's engagement was analyzed by averaging the engagement metrics of tweets, retweets, favorites, replies, and posts shared with sentiments and opinions regarding COVID-19 and COVID-19 vaccination. Positive sentiments on COVID-19 and COVID-19 vaccination dominated, however, the negative sentiments increased during the beginning of the implementation of restrictions on community activities (PPKM). The tweets were dominated by the importance of health protocols (washing hands, keeping distance, and wearing masks). Several types of vaccines were on top of the word count in the vaccine subtopic. Acceptance of the vaccination increased during the studied period, and the fake news was overweighed by the facts. The tweets were dynamic and showed that the engaged topics were changed from the nature of COVID-19 to the vaccination and virus mutation which peaked in the early and middle terms of 2021. The public sentiment and engagement were shifted from hesitancy to anxiety towards the safety and effectiveness of the vaccines, whilst changed again into wariness on an uprising of the delta variant. Understanding public sentiment and opinion can help policymakers to plan the best strategy to cope with the pandemic. Positive sentiments and fact-based opinions on COVID-19, and COVID-19 vaccination had been shown predominantly. However, sufficient health literacy levels could yet be predicted and sought for further study.