Yoxas/statistical_literacy huggingface dataset:
Nanomaterials can intensively scatter and/or reflect radiation. Such processes and materials are of theoretical and practical interest. Here, we study the quasi-specular reflections (QSRs) of cold neutrons (CNs) and the reflections of very cold neutrons (VCNs) from nanodiamond (ND) powders. The fluorination of ND increased its efficiency by removing/replacing hydrogen, which is otherwise the dominant cause of neutron loss due to incoherent scattering. The probability of the diffuse reflection of VCNs increased for certain neutron wavelengths by using appropriate ND sizes. Based on model concepts of the interaction of CNs with ND, and in reference to our previous work, we assume that the angular distribution of quasi-specularly reflected CNs is narrower, and that the probability of QSRs of longer wavelength neutrons increases if we increase the characteristic sizes of NDs compared to standard detonation nanodiamonds (DNDs). However, the probability of QSRs of CNs with wavelengths below the cutoff of ~4.12 Å decreases due to diffraction scattering on the ND crystal lattice. We experimentally compared the QSRs of CNs from ~4.3 nm and ~15.0 nm ND. Our qualitative conclusions and numerical estimates can help optimize the parameters of ND for specific practical applications based on the QSRs of CNs.
Narrative approaches and storytelling are emerging as powerful health promotion tools that can spark interest, increase understanding of determinants of health, and translate complex science. A Story of Health, a multimedia e-book with continuing education credits was designed to harness the power of storytelling to increase environmental health literacy. Health professionals are a key audience. They recognize that patients may be suffering from preventable illnesses of environmental origin but often feel ill-equipped to educate individuals and families about risks associated with common exposures. A Story of Health seeks to fill this gap and help readers develop the competencies they need in order to help patients make informed choices, reduce health risks, improve quality of life, and protect the environment. Americans rate nurses and medical doctors as having the highest honesty and ethical standards of all professions. These medical professionals can play a key role in changing patterns of patient behavior and influencing public policies. The e-book provides an easily accessible method of developing environmental health competency. The multimedia format with graphical interpretations allows for quick reviews of topics or for more in-depth analysis via links to additional resources. The CE evaluations have been overwhelmingly positive.
Narrative Medicine (NM), a contemporary medical concept proposed in the 21st century, emphasizes the use of narrative as a literary form in medicine. This study aims to explore the understanding about NM and willingness to learn NM among medical students in our hospital. A questionnaire survey was conducted among 130 students at Xiangya Medical College of Central South University. The findings revealed that a small percentage of students (3.1%) were familiar with narrative medicine and its training methods. Knowledge about the treatment skills (77.7%) and core content (55.4%) of narrative medicine was limited among the students. Despite this, a majority (63.1%) expressed a lack of interest in further understanding and learning about narrative medicine. Surprisingly, the survey indicated that students possessed a high level of narrative literacy, even without formal training in narrative medicine. Additionally, over half of the surveyed students (61.5%) believed that narrative medicine could benefit their clinical practice. This study serves as a preliminary basis for the future development of narrative medicine education in China. It highlights the need to prioritize medical humanities education and provide medical students with more opportunities to access information on narrative medicine. By doing so, we can strive to enhance the visibility and promote the integration of narrative medicine into medical humanities education in China.
Narrative medicine can serve as a tool to empathize with human beings' predicament and suffering. The research intended to examine whether the use of narrative medicine to form an empathetic connection could bring any positive impacts on health professions students. A two-group quasi-experimental design was adopted to examine whether the intervention of narrative medicine to form an empathetic connection could demonstrate differences between the experimental group (35 students) and the control group (32 students) with regard to professional identity, self-reflection, emotional catharsis, and reflective writing competency. These 67 participants were health professions students in a medical university (mean age = 20.02; SD = 0.23), with varied majors in health disciplines. The 16-week intervention was the use of narrative medicine to form an empathetic connection with those suffering, via the three stages of narrative medicine: attention → representation → affiliation. The quantitative instruments included a professional identity scale (PIS-HSP), a reflective thinking scale (RTS-HSP), and an emotional catharsis scale (ECS-IN), as well as an analytic reflective writing scoring rubric (ARWSR-HSP). To triangulate the quantitative results, the study also used the student interviews. The SPSS software was used to analyze the data. The quantitative results demonstrated that the narrative medicine-based intervention could bring positive effects on the health professions students. After going through the intervention, the students in the experimental group had stronger professional identity, a higher reflective thinking level, more emotional catharsis, and greater improvement in reflective writing competency than those not receiving the intervention, though some subscales not reaching statistical significance. This research results proved that the use of narrative medicine to form an empathetic connection could bring positive impacts on health professions students regarding professional identity, self-reflection, emotional catharsis, and self-reflective writing competency.
Narrative production is an important part of the diagnostic process for autism. Most existing research on narrative production by autistic people has focused on cisgender men and boys. Members of other genders (i.e., nonbinary people, transgender men, and trans and cisgender women) are underrepresented in the research literature. Research with non-autistic adults consistently reports gender differences in narrative production. When adults whose genders are underrepresented seek autism diagnosis as adults, they may be misdiagnosed due to misconceptions about autistic communication that are based on cisgender male speakers. Twenty autistic adults of various genders each told four narratives: two based on a picture and two about their personal experiences. Dependent variables measured narrative length, grammatical complexity, vocabulary diversity, filled pauses, and internal state terms. Researchers used nonparametric statistics to compare groups of (1) cisgender men and all other participants, (2) participants assigned male at birth and those assigned female, and (3) self-identified women, nonbinary people, and men. Women used significantly less diverse vocabulary than men. Women used more terms to refer to internal states than both nonbinary people and men, but this finding was not significant after correction for multiple comparisons. All other comparisons were not statistically significant. Autistic narrators of diverse genders have more linguistic similarities than differences. Autistic women may be more likely to talk about emotions and other internal states than autistic men. Gender-based expectations for spoken communication about internal states should be carefully reconsidered. More research is necessary to determine whether the results of this small study will generalize to larger samples of autistic people whose genders are currently underrepresented in the research literature.
Narrative written feedback given to students by faculty often fails to identify areas for improvement and recommended actions to lead to this improvement. When these elements are missing, it is challenging for students to improve and for medical schools to use narrative feedback in promotion decisions, to guide coaching plans and to pass on meaningful information to residency programs. Large-group faculty development has improved narrative written feedback, but less is known about individualised faculty development to supplement large-group sessions. To fill this gap, we built a curriculum with general and individualised faculty development to improve narrative written feedback from Internal Medicine faculty to clerkship students. We used Kern's steps to build a curriculum with general and individualised one-on-one faculty development to improve the problem of inadequate narrative written feedback. We used a novel narrative feedback rubric for pre and post-intervention faculty scores. Through general and individualised one-on-one faculty development with peer comparison scores, we were able to improve narrative written feedback from 3.7/6 to 4.6/6, for an increase of 23%. We found our faculty development program effective in improving feedback and was easy to implement. Our rubric was easy to use, and faculty were receptive to feedback in one-on-one meetings. We plan to extend this work locally to other divisions/departments and into graduate medical education; it should also be easily extended to other medical disciplines or health professions.
National cancer organizations recommend provision of nutrition, physical activity, and mental health supportive services to cancer survivors. However, the availability of these services across diverse community oncology settings remains unclear. The National Cancer Institute Community Oncology Research Program (NCORP) is a national network of community oncology practices engaged in cancer research. The 2022 NCORP Landscape Assessment (5UG1CA189824) assessed individual practices' establishment of survivorship clinics and nutrition, physical activity, and mental health services, resources, and/or referrals. Descriptive statistics summarized and logistic regression quantified the association between services, practice, and patient characteristics. Of 46 NCORP community sites, 45 (98%) responded to the survey, representing 259 adult practice groups. A total of 41% had a survivorship clinic; 96% offered mental health, 94% nutrition, and 53% physical activity services, resources, and/or referrals. All 3 services were offered in various formats (eg, in-house, referrals, education) by 51% and in-house only by 25% of practices. Practices with advanced practice providers were more likely to have a survivorship clinic (odds ratio [OR] = 3.19, 95% confidence interval [CI] = 1.04 to 9.76). Practices with at least 30% Medicare patients (OR = 2.54, 95% CI = 1.39 to 4.66) and more oncology providers (OR = 1.02, 95% CI = 1.01 to 1.04) were more likely to have all 3 services in any format. Practices with at least 30% Medicare patients (OR = 3.41, 95% CI = 1.50 to 7.77) and a survivorship clinic (OR = 2.84, 95% CI = 1.57 to 5.14) were more likely to have all 3 services in-house. Larger oncology practices and those caring for more survivors on Medicare provided more supportive services, resources, and/or referrals. Smaller practices and those without survivorship clinics may need strategies to address potential gaps in supportive services.
National data on dental caries and dental service use among immigrant children in U.S. are limited. It is not known whether race/ethnicity would interact with immigration status to increase these disparities. Using a nationally representative sample, this study assessed the interaction effects of immigrant generation status and race/ethnicity on dental caries and dental visits among children in the U.S. Data were from the 2020 and 2021 National Survey of Children's Health. All data were self-reported by parents/guardians. The 2 outcomes were (1) dental caries (yes/no) in the past 12 months and (2) preventive dental visits (yes/no) in the past 12 months. Racial/ethnic groups included non-Hispanic White, Black, Hispanics, and Asian Americans. The analytical sample included 66,167 children aged 2-17 years, including 1,243 first-generation immigrant children; 11,017 second-generation immigrant children; and 53,907 nonimmigrant children. Study authors ran separate multiple logistic regression models for the 2 outcome variables. All analyses accounted for the survey design of National Survey of Children's Health. First-generation immigrant children were more likely to have dental caries than nonimmigrant children (AOR=1.44). The interaction of race/ethnicity and immigrant generation status was significant (p=0.04) in the preventive dental visits model, indicating increased challenges in getting dental visits among minority immigrant children in comparison with that among non-Hispanic White immigrant children, especially among first-generation immigrant children of Asian Americans (AOR=0.41) and non-Hispanic Black immigrant children (AOR=0.37). First-generation immigrant children were less likely to see a dentist and more likely to have dental caries than nonimmigrants. Moreover, first-generation immigrant children from minority racial/ethnic groups were the least likely to seek dental services. To further reduce disparities in oral health and dental use among children in the U.S., culturally sensitive health promotion is warranted to improve oral health literacy and reduce barriers to dental care for immigrants, especially immigrant children of the minority groups.
National household data suggest that more than four million women in India have experienced nonspousal rape. Fewer than 1.5% of victims of sexual violence in India report their assaults to police, though there is some indication of increased rape reporting to police following a very high-profile fatal gang rape in Delhi in December 2012. This study examines effects of the Delhi gang rape on rape reporting to police in India, and assesses the roles played by geography, media access, and women's status and protection factors in that reporting. Triangulated data from Indian crime, census, and police bureau records were used to assess trends in rape reporting to police at national and district levels from 2005 to 2016, using regressions, spatial mapping, and graphical trend analyses. Nationally, there was a 33% increase in annual rapes reported to police after 2012. Subnationally, there was substantial variation in trends; these district-level changes were particularly affected by distance from Delhi (0.2 fewer rapes reported to police/100,000 women for each 100 km from Delhi), literacy sex ratio (0.6 more rapes for every increase of 0.1 in male: female literacy ratio), and the presence of a women's police station (1.0 fewer rapes reported to police/100,000 women relative to districts with no women's police station). The 2012 Delhi gang rape significantly affected rape reporting to police in India, with greater increases seen closer to Delhi and in districts with compromised gender equity. Further work to support the rights and safety of women is needed, including bolstering an enabling environment for reporting, legal protections, and responsive criminal justice.
National physical activity (PA) policy processes are only beginning to be studied in Latin America, and little attention has focused at the subnational level. This study examined national-subnational relations in the policy process (agenda setting, policy formulation, adoption, implementation, and evaluation) in selected Latin American countries. The Global Observatory for Physical Activity's (GoPA!) INTEGRATE-PA-Pol tool was applied in Colombia, Costa Rica, Ecuador, and Mexico. Data were collected in matched pairs of the capital plus one noncapital city among national and subnational policymakers (n = 27), previously identified by the GoPA! Country Contacts. PA policy development and implementation were assessed using descriptive statistics. Twenty-three (response rate = 85.2%) informants provided data, mainly from the health sector (52.2%), followed by the sport (26.1%), transport (13.0%), and education (8.7%) sectors. Most informants reported that their countries had a current PA policy embedded within noncommunicable diseases prevention plans (46.2%), other plans (46.2%), or obesity prevention/management/control plans (7.7%). Respondents at the subnational level rated PA promotion as central (64.3%), while the national-level role was important but not central (75.0%). National and subnational policymakers indicated low-to-little involvement in the other level's PA policy processes across the 5 policy stages. This study demonstrated that collecting national and subnational PA policy data across countries with the active collaboration of the GoPA! network was feasible. We also successfully identified governmental interactions throughout the PA policy process, suggesting suboptimal engagement between national and subnational levels.
Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting. We systematically searched publications related to EM research and NLP across databases including MEDLINE, Embase, Scopus, CENTRAL, and ProQuest Dissertations & Theses Global. Independent reviewers screened, reviewed, and evaluated article quality and bias. NLP usage was categorized into syndromic surveillance, radiologic interpretation, and identification of specific diseases/events/syndromes, with respective sensitivity analysis reported. Performance metrics for NLP usage were calculated and the overall area under the summary of receiver operating characteristic curve (SROC) was determined. A total of 27 studies underwent meta-analysis. Findings indicated an overall mean sensitivity (recall) of 82%-87%, specificity of 95%, with the area under the SROC at 0.96 (95% CI 0.94-0.98). Optimal performance using NLP was observed in radiologic interpretation, demonstrating an overall mean sensitivity of 93% and specificity of 96%. Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management.
Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinical documentation to be integrated in ways that facilitate data analysis, data interpretation and formation of individualized medical and obstetrical care. In this cross-sectional study, we identified all births during the study period carrying the radiology-confirmed diagnosis of fibroid uterus in pregnancy (defined as size of largest diameter of >5 cm) by using an NLP platform and compared it to non-NLP derived data using ICD10 codes of the same diagnosis. We then compared the two sets of data and stratified documentation gaps by race. Using fibroid uterus in pregnancy as a marker, we found that Black patients were more likely to have the diagnosis entered late into the patient's chart or had missing documentation of the diagnosis. With appropriate algorithm definitions, cross referencing and thorough validation steps, NLP can contribute to identifying areas of documentation gaps and improve quality of care.
Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.
Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems. This paper demonstrates the usefulness of such algorithms for solving a variety of challenging optimization problems in statistics using a nature-inspired metaheuristic algorithm called competitive swarm optimizer with mutated agents (CSO-MA). This algorithm was proposed by one of the authors and its superior performance relative to many of its competitors had been demonstrated in earlier work and again in this paper. The main goal of this paper is to show a typical nature-inspired metaheuristic algorithmi, like CSO-MA, is efficient for tackling many different types of optimization problems in statistics. Our applications are new and include finding maximum likelihood estimates of parameters in a single cell generalized trend model to study pseudotime in bioinformatics, estimating parameters in the commonly used Rasch model in education research, finding M-estimates for a Cox regression in a Markov renewal model, performing matrix completion tasks to impute missing data for a two compartment model, and selecting variables optimally in an ecology problem in China. To further demonstrate the flexibility of metaheuristics, we also find an optimal design for a car refueling experiment in the auto industry using a logistic model with multiple interacting factors. In addition, we show that metaheuristics can sometimes outperform optimization algorithms commonly used in statistics.