Yoxas/statistical_literacy huggingface dataset:
The high rate of early marriage, teenage pregnancy, and teenage mothers increases the prevalence of emotional and mental disorders, depression, parenting stress, and child stunting. Parenting coaching is among the effective ways to overcome parenting stress and improve parents' knowledge, skills, and behaviors, thereby avoiding child stunting. However, studies on parenting coaching are not widely conducted, particularly in Indonesia. This study aimed to present the current status of parenting stress among teenage mothers and assess whether parenting coaching effectively reduces parenting stress among teenage mothers. A quasi-experimental design was used. The participants were randomly selected into two groups: the intervention group receiving parenting coaching intervention and the control group receiving standard education using a leaflet. Data were collected in June 2021 in Takalar Regency, South Sulawesi, Indonesia. Statistical Program for Social Science version 21 (Armonk, NY, USA) was employed for all statistical analyses. The parenting coaching intervention had a significant effect on parenting stress (p <0.001), with significant positive changes in knowledge, attitude (p <0.001), behavior (p <0.001), self-efficacy (p <0.001), and maternal function (p <0.001). Additionally, a significant difference in the achievement of z-score values was observed between the intervention and control groups based on Body Weight/Age (BW/A) (p <0.001) and Body Length/Age (BL/A) (p <0.001). However, Body Weight/Body Length (BW/BL) did not show a significant difference in the achievement of z-score (p = 0.34) in the third month. Parenting coaching can reduce parenting stress among teenage mothers and improve their knowledge, attitudes, behavior, self-efficacy, and maternal function; hence, this intervention can be used as a reference in the nursing process to reduce parenting stress and prevent child stunting.
The highest incidence of overweight among adults is found among women, predominantly middle-aged women. While it has been demonstrated that being overweight increases mortality by compromising physical and mental health, it also imposes substantial costs on the healthcare system. Lack of physical activity is a primary contributing factor to becoming overweight. The majority of inactive adults are women, particularly middle-aged women. Consequently, this study investigated the training program for overweight women based on the health belief model (HBM) and social support approach. A randomized, controlled trial involving 73 overweight middle-aged women (control group: 37, intervention group: 36) was conducted using simple random sampling. The intervention group participated in six 120-min sessions per week for 6 weeks of a training program based on HBM and social support through physical activity, group discussion, role play, and media. Data were collected using the Physical Activity Questionnaire (IPAQ), Bandura's Exercise Self-Efficacy Scale (Bandura's ESE), and a researcher-made questionnaire before and 4 weeks after the training. The collected data were analyzed using descriptive and inferential statistics via SPSS 27 software. p-values <0.05 were considered statistically significant. A training program based on HBM and social support led to improved perceived benefits (p < 0.001), cues to action (p = 0.03), and self-efficacy (p < 0.001) of physical activity; decreased perceived barriers (p = 0.001); increased social support (p = 0.001); and increased physical activity (p < 0.001). In addition, the BMI of the intervention group decreased after the training program (p = 0.01). The findings of the study demonstrate the efficacy of the training program based on HBM and the social support approach in improving social support and physical activity of women. In addition, the study evaluates the long-term outcome in populations with varying social, economic, and cultural standings. https://clinicaltrials.gov/, (IRCT201706236261N17).
The HIV epidemic in Ghana is characterized as a mix of a low-level generalized epidemic with significant contributions from transmission among female sex workers (FSW) and their clients. This study seeks to identify and describe key characteristics and sexual behaviors of FSW and estimate the prevalence of HIV, syphilis, gonorrhea, chlamydia, and hepatitis B virus (HBV) among FSW in Ghana. A total of 7,000 FSW were recruited for the study using Time Location Sampling (TLS) approach with 5,990 (85.6%) participants completing both biological and the behavioral aspects of the study. A structured questionnaire was administered to respondents to assess several factors, such as background characteristics, sexual risk behaviors, condom usage, HIV/AIDS knowledge, opinions, and attitudes. Trained staff conducted face-to-face interviews using mobile data collection software (REDCap) after provision of specimens for HIV and STI testing. Descriptive statistics such as medians, ranges, charts, and percentages are performed and presented. Also included, are bivariate analyses to establish relationships between FSW type and other relevant characteristics of the study. Among the 7,000 (100%) FSW sampled from all regions, 6,773 took part in the behavioral and 6,217 the biological. There were 783 (11.2%) respondents who took part only in the behavioral and 227 (3.2%) only in the biological. Most were young, with a median age of 26 years, majority had never been married or were widowed/divorced and a quarter had no education or had only primary education. Majority (74.8%) of FSW first sold sex at age 25 years or less with a median age of 20 years. Most (84.8%) of the FSW indicated that they entered sex work for money, either for self or family and had an average of eleven (11) sexual partners per week. More than half (55.2%) of the FSW were new entrants who had been in sex work for less than 5 years before the study. Consistent condom use with paying clients was generally unsatisfactory (71%), and was however, very low (24%) with their intimate partners or boyfriends. Only about half (54.6%) of FSW have been exposed to HIV prevention services in the last three months preceding the survey, and this varies across regions. Overall, comprehensive knowledge about HIV and AIDS was low. Only 35% of FSW had comprehensive knowledge. HIV prevalence was 4.6% and was higher among seaters (brothel-based) and older FSW who had been sex work for a longer period. The HIV prevalence from the previous bio-behavioral survey (BBS) in 2015 and 2011 were estimated to be 6.9 and 11.1%, respectively. Compared to the results from the previous studies, the findings give an indication that Ghana is making significant progress in reducing the burden of HIV among FSW in the country. However, risky behaviors such as low consistent condom use, low coverage of HIV services across the regions, and low comprehensive knowledge could reverse the gains made so far. Immediate actions should be taken to expand coverage of HIV services to all locations. Efforts must be made to reach out to the new entrants while also addressing strongly held myths and misconceptions about HIV.
The home language and literacy environment (HLLE) in infancy has been associated with subsequent pre-literacy skill development and HLLE at preschool-age has been shown to correlate with white matter organization in tracts that subserve pre-reading and reading skills. Furthermore, childhood socioeconomic status (SES) has been linked with both HLLE and white matter organization. It is important to understand whether the relationships between environmental factors such as HLLE and SES and white matter organization can be detected as early as infancy, as this period is characterized by rapid brain development that may make white matter pathways particularly susceptible to these early experiences. Here, we hypothesized that HLLE (1) relates to white matter organization in pre-reading and reading-related tracts in infants, and (2) mediates a link between SES and white matter organization. To test these hypotheses, infants (mean age: 8.6 ± 2.3 months, N = 38) underwent diffusion-weighted imaging MRI during natural sleep. Image processing was performed with an infant-specific pipeline and fractional anisotropy (FA) was estimated from the arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF) bilaterally using the baby automated fiber quantification method. HLLE was measured with the Reading subscale of the StimQ (StimQ-Reading) and SES was measured with years of maternal education. Self-reported maternal reading ability was also quantified and applied to our statistical models as a proxy for confounding genetic effects. StimQ-Reading positively correlated with FA in left AF and to maternal education, but did not mediate the relationship between them. Taken together, these findings underscore the importance of considering HLLE from the start of life and may inform novel prevention and intervention strategies to support developing infants during a period of heightened brain plasticity.
The home learning environment includes what parents do to stimulate children's literacy and numeracy skills at home and their overall beliefs and attitudes about children's learning. The home literacy and numeracy environments are two of the most widely discussed aspects of the home learning environment, and past studies have identified how socioeconomic status and parents' own abilities and interest in these domains also play a part in shaping children's learning experiences. However, these studies are mostly from the West, and there has been little focus on the situation of homes in Asia, which captures a large geographical area and a wide diversity of social, ethnic, and linguistic groups. Therefore, this paper aims to review extant studies on the home literacy and numeracy environments that have been conducted in different parts of Asia, such as China, the Philippines, India, Iran, Turkey, and the United Arab Emirates. Specifically, we explore how parents in these places perceive their roles in children's early literacy and numeracy development, the methods they regard as effective for promoting young children's literacy and numeracy learning, and the frequency with which they engage their young children in different types of home literacy and numeracy activities. We also examine studies on the relationship of the home literacy and numeracy environment with young children's developmental outcomes, and the effectiveness of parent training programs to improve the home literacy and numeracy environments in these contexts. By examining potential trends in findings obtained in different geographical areas, we can initially determine whether there are characteristics that are potentially unique to contexts in Asia. We propose future research directions that acknowledge the role of cultural values and social factors in shaping the home learning environment, and, by extension, in facilitating children's early literacy and numeracy development.
The Home Visiting Program for Childcare Support (HV-CCS; "Yoiku Shien Homon Jigyo" in Japanese) has targeted families in need of parenting support and those at risk of child maltreatment in Japan. The aim of this study was to explore the needs and perceptions of benefits of home visitors in HV-CCS. Sixteen home visitors agreed to participate in the interview. This study conducted 1-hour semi-structured interviews with 16 home visitors and analyzed approximately 18 h of interview data using thematic analysis. The findings suggested that home visitors required training to enhance individual skills and knowledge about mental health of caregivers or children. Additionally, they required environmental support, particularly for transportation expenses and parking places. Multidisciplinary communicative support is also necessary, as well as system to improve the process of support. Home visitor perceived the HV-CCS as beneficial in preventing child maltreatment by improving parenting skills and home environment, providing psychological support for mothers, and entering families' intimate spaces. To ensure the continuity and improvement of home visits for parents and children in Japan, it is essential to address the identified needs of home visitors.
The human ability to reason about the causes behind other people' behavior is critical for navigating the social world. Recent empirical research with both children and adults suggests that this ability is structured around an assumption that other agents act to maximize some notion of subjective utility. In this paper, we present a formal theory of this Naïve Utility Calculus as a probabilistic generative model, which highlights the role of cost and reward tradeoffs in a Bayesian framework for action-understanding. Our model predicts with quantitative accuracy how people infer agents' subjective costs and rewards based on their observable actions. By distinguishing between desires, goals, and intentions, the model extends to complex action scenarios unfolding over space and time in scenes with multiple objects and multiple action episodes. We contrast our account with simpler model variants and a set of special-case heuristics across a wide range of action-understanding tasks: inferring costs and rewards, making confidence judgments about relative costs and rewards, combining inferences from multiple events, predicting future behavior, inferring knowledge or ignorance, and reasoning about social goals. Our work sheds light on the basic representations and computations that structure our everyday ability to make sense of and navigate the social world.
The human brain processes language to optimise efficient communication. Studies have shown extensive evidence that the brain's response to language is affected both by lower-level features, such as word-length and frequency, and syntactic and semantic violations within sentences. However, our understanding on cognitive processes at discourse level remains limited: How does the relationship between words and the wider topic one is reading about affect language processing? We propose an information theoretic model to explain cognitive resourcing. In a study in which participants read sentences from Wikipedia entries, we show information gain, an information theoretic measure that quantifies the specificity of a word given its topic context, modulates word-synchronised brain activity in the EEG. Words with high information gain amplified a slow positive shift in the event related potential. To show that the effect persists for individual and unseen brain responses, we furthermore show that a classifier trained on EEG data can successfully predict information gain from previously unseen EEG. The findings suggest that biological information processing seeks to maximise performance subject to constraints on information capacity.
The human Ether-à-go-go-Related Gene (hERG) is a transmembrane protein that regulates cardiac action potential, and its inhibition can induce a potentially deadly cardiac syndrome. In vitro tests help identify hERG blockers at early stages; however, the high cost motivates searching for alternative, cost-effective methods. The primary goal of this study was to enhance the Pred-hERG tool for predicting hERG blockage. To achieve this, we developed new QSAR models that incorporated additional data, updated existing classificatory and multiclassificatory models, and introduced new regression models. Notably, we integrated SHAP (SHapley Additive exPlanations) values to offer a visual interpretation of these models. Utilizing the latest data from ChEMBL v30, encompassing over 14,364 compounds with hERG data, our binary and multiclassification models outperformed both the previous iteration of Pred-hERG and all publicly available models. Notably, the new version of our tool introduces a regression model for predicting hERG activity (pIC50). The optimal model demonstrated an R2 of 0.61 and an RMSE of 0.48, surpassing the only available regression model in the literature. Pred-hERG 5.0 now offers users a swift, reliable, and user-friendly platform for the early assessment of chemically induced cardiotoxicity through hERG blockage. The tool provides versatile outcomes, including (i) classificatory predictions of hERG blockage with prediction reliability, (ii) multiclassificatory predictions of hERG blockage with reliability, (iii) regression predictions with estimated pIC50 values, and (iv) probability maps illustrating the contribution of chemical fragments for each prediction. Furthermore, we implemented explainable AI analysis (XAI) to visualize SHAP values, providing insights into the contribution of each feature to binary classification predictions. A consensus prediction calculated based on the predictions of the three developed models is also present to assist the user's decision-making process. Pred-hERG 5.0 has been designed to be user-friendly, making it accessible to users without computational or programming expertise. The tool is freely available at http://predherg.labmol.com.br.
The human insular cortex supports multifunctional integration including interoceptive, sensorimotor, cognitive and social-emotional processing. Different concepts of the underlying microstructure have been proposed over more than a century. However, a 3D map of the cytoarchitectonic segregation of the insula in standard reference space, that could be directly linked to neuroimaging experiments addressing different cognitive tasks, is not yet available. Here we analyzed the middle posterior and dorsal anterior insula with image analysis and a statistical mapping procedure to delineate cytoarchitectonic areas in ten human postmortem brains. 3D-probability maps of seven new areas with granular (Ig3, posterior), agranular (Ia1, posterior) and dysgranular (Id2-Id6, middle to dorsal anterior) cytoarchitecture have been calculated to represent the new areas in stereotaxic space. A hierarchical cluster analysis based on cytoarchitecture resulted in three distinct clusters in the superior posterior, inferior posterior and dorsal anterior insula, providing deeper insights into the structural organization of the insula. The maps are openly available to support future studies addressing relations between structure and function in the human insula.
The human microbiome exists throughout the body, and it is essential for maintaining various physiological processes, including immunity, and dysbiotic events, which are associated with autoimmunity. Peptidylarginine deiminase (PAD) enzymes can citrullinate self-proteins related to rheumatoid arthritis (RA) that induce the production of anti-citrullinated protein antibodies (ACPAs) and lead to inflammation and joint damage. The present investigation was carried out to demonstrate the expression of homologs of PADs or arginine deiminases (ADs) and citrullinated proteins in members of the human microbiota. To achieve the objective, we used 17 microbial strains and specific polyclonal antibodies (pAbs) of the synthetic peptide derived from residues 100-200 of human PAD2 (anti-PAD2 pAb), and the recombinant fragment of amino acids 326 and 611 of human PAD4 (anti-PAD4 pAb), a human anti-citrulline pAb, and affinity ACPAs of an RA patient. Western blot (WB), enzyme-linked immunosorbent assay (ELISA), elution, and a test with Griess reagent were used. This is a cross-sectional case-control study on patients diagnosed with RA and control subjects. Inferential statistics were applied using the non-parametric Kruskal-Wallis test and Mann-Whitney U test generated in the SPSS program. Some members of phyla Firmicutes and Proteobacteria harbor homologs of PADs/ADs and citrullinated antigens that are reactive to the ACPAs of RA patients. Microbial citrullinome and homolog enzymes of PADs/ADs are extensive in the human microbiome and are involved in the production of ACPAs. Our findings suggest a molecular link between microorganisms of a dysbiotic microbiota and RA pathogenesis.
The human microbiome, consisting of diverse bacte-rial, fungal, protozoan and viral species, exerts a profound influence on various physiological processes and disease susceptibility. However, the complexity of microbiome data has presented significant challenges in the analysis and interpretation of these intricate datasets, leading to the development of specialized software that employs machine learning algorithms for these aims. In this paper, we analyze raw data taken from 16S rRNA gene sequencing from three studies, including stool samples from healthy control, patients with adenoma, and patients with colorectal cancer. Firstly, we use network-based methods to reduce dimensions of the dataset and consider only the most important features. In addition, we employ supervised machine learning algorithms to make prediction. Results show that graph-based techniques reduces dimen-sion from 255 up to 78 features with modularity score 0.73 based on different centrality measures. On the other hand, projection methods (non-negative matrix factorization and principal component analysis) reduce dimensions to 7 features. Furthermore, we apply supervised machine learning algorithms on the most important features obtained from centrality measures and on the ones obtained from projection methods, founding that the evaluation metrics have approximately the same scores when applying the algorithms on the entire dataset, on 78 feature and on 7 features. This study demonstrates the efficacy of graph-based and projection methods in the interpretation for 16S rRNA gene sequencing data. Supervised machine learning on refined features from both approaches yields comparable predictive performance, emphasizing specific microbial features-bacteroides, prevotella, fusobacterium, lysinibacillus, blautia, sphingomonas, and faecalibacterium-as key in predicting patient conditions from raw data.