Yoxas/statistical_literacy huggingface dataset:
With increasing availability of immediate patient access to pathology reports, it is imperative that all physicians be equipped to discuss pathology reports with their patients. No validated measures exist to assess how pathology report findings are communicated during patient encounters. To pilot a scoring rubric evaluating medical students' communication of pathology reports to standardized patients. The rubric was iteratively developed using the Pathology Competencies for Medical Education and Accreditation Council for Graduate Medical Education pathology residency milestones. After a brief training, third- and fourth-year medical students completed 2 standardized patient encounters, presenting simulated benign and malignant pathology reports. Encounters were video recorded and scored by 2 pathologists to calculate overall and item-specific interrater reliability. All students recognized the need for pathology report teaching, which was lacking in their medical curriculum. Interrater agreement was high for malignant report scores (intraclass correlation coefficient, 0.65) but negligible for benign reports (intraclass correlation coefficient, 0). On malignant reports, most items demonstrated good interrater agreement, except for discussing the block (cassette) summary, explaining the purpose of the pathology report, and acknowledging uncertainty. Participating students (N = 9) felt the training was valuable given their limited prior exposure to pathology reports. This pilot study demonstrates the feasibility of using a structured rubric to assess the communication of pathology reports to patients. Our findings also provide a scalable example of training on pathology report communication, which can be incorporated in the undergraduate medical curriculum to equip more physicians to facilitate patients' understanding of their pathology reports.
With increasing numbers of patients and novel drugs for distinct causes of systolic and diastolic heart failure, automated assessment of cardiac function is important. We aimed to provide a non-invasive method to predict diagnosis of patients undergoing cardiac MRI (cMRI) and to obtain left ventricular end-diastolic pressure (LVEDP). For this modelling study, patients who had undergone cardiac catheterisation at University Hospital Heidelberg (Heidelberg, Germany) between July 15, 2004 and March 16, 2023, were identified, as were individual left ventricular pressure measurements. We used existing patient data from routine cardiac diagnostics. From this initial group, we extracted patients who had been diagnosed with ischaemic cardiomyopathy, dilated cardiomyopathy, hypertrophic cardiomyopathy, or amyloidosis, as well as control individuals with no structural phenotype. Data were pseudonymised and only processed within the university hospital's AI infrastructure. We used the data to build different models to predict either demographic (ie, AI-age and AI-sex), diagnostic (ie, AI-coronary artery disease and AI-cardiomyopathy [AI-CMP]), or functional parameters (ie, AI-LVEDP). We randomly divided our datasets via computer into training, validation, and test datasets. AI-CMP was not compared with other models, but was validated in a prospective setting. Benchmarking was also done. 66 936 patients who had undergone cardiac catheterisation at University Hospital Heidelberg were identified, with more than 183 772 individual left ventricular pressure measurements. We extracted 4390 patients from this initial group, of whom 1131 (25·8%) had been diagnosed with ischaemic cardiomyopathy, 1064 (24·2%) had been diagnosed with dilated cardiomyopathy, 816 (18·6%) had been diagnosed with hypertrophic cardiomyopathy, 202 (4·6%) had been diagnosed with amyloidosis, and 1177 (26·7%) were control individuals with no structural phenotype. The core cohort only included patients with cardiac catherisation and cMRI within 30 days, and emergency cases were excluded. AI-sex was able to predict patient sex with areas under the receiver operating characteristic curves (AUCs) of 0·78 (95% CI 0·77-0·78) and AI-age was able to predict patient age with a mean absolute error of 7·86 years (7·77-7·95), with a Pearson correlation of 0·57 (95% CI 0·56-0·57). The AUCs for the classification tasks ranged between 0·82 (95% CI 0·79-0·84) for ischaemic cardiomyopathy and 0·92 (0·91-0·94) for hypertrophic cardiomyopathy. Our AI models could be easily integrated into clinical practice and provide added value to the information content of cMRI, allowing for disease classification and prediction of diastolic function. Informatics for Life initiative of the Klaus-Tschira Foundation, German Center for Cardiovascular Research, eCardiology section of the German Cardiac Society, and AI Health Innovation Cluster Heidelberg.
With increasing pressure on placement capacity for allied health students, a need for novel and creative means through which students can develop foundational skills and prepare for practice-based learning opportunities has arisen. This study aimed to explore the experiences of domestic and international first-year students completing pre-clinical preparation programs, contrasting between in-person simulation and online options to contribute to best practice evidence for program design and delivery. First-year students from physiotherapy, podiatry and occupational therapy self-selected to either a one-weeklong in-person simulation program or an online preparation for placement program. An integrative mixed-methods approach was employed. Qualitative findings from student focus groups were analyzed by reflexive thematic analysis and complemented by quantitative pre-post questionnaires which were examined for patterns of findings. There were 53 student participants in the study (simulation n = 29; online n = 24). Self-selecting, international students disproportionately opted for the simulation program while older students disproportionately selected the online program. Students appeared to benefit more from the simulation program than the online program, with alignment of focus group findings to the quantitative questionnaire data. The in-person simulation allowed students to apply their learning and practice patient communication. All simulation students reported asubsequent increase in confidence, although this seemed particularly marked for the international students. By contrast, the online program was most effective at developing students' clinical reasoning and proficiency with documentation. Both programs faced minor challenges to student perceived relevance and skill development. Both online and in-person simulation preparation programs were perceived to enhance readiness and foundational skills development for novice allied health students, with the practical nature of simulation generating more advantageous findings. This study provides useful information on the benefits and challenges of both types of delivery for foundational skills development and/or clinical preparation of allied health students.
With many Western societies structured for adults to live longer and take responsibility for their health, it is valuable to investigate how older persons reason about this demand. Using mixed methods, this pilot studied how older persons reason about responsibility for health and their responsibility as a patient. Interviews with a small Swedish sample of 65-84 year olds were analyzed for qualitative characteristics and quantitative complexity in reasoning. Using adult development theory, we predicted at least three different stages of performance in reasoning. Results indicated four different stages: two where there is no actual reasoning about health and responsibility, and two where reasoning does occur, each qualitatively different. Results suggest a long-standing blind spot in health studies, that older people do not comprehend responsibility issues in the same way. There are significant implications for closing this gap between demand to take responsibility and capabilities to do so.
With mental anxiety caused by the COVID-19 pandemic, the trend of "lying down" has become increasingly prevalent among Chinese college students such as not thinking ahead, decadent abandonment, and being weak daily. Particularly, Chinese "Double Non" college students are more likely to face academic burnout (AB) due to lower school satisfaction and after-degree employment ratio, in comparison to "Double First-Class" college students. In view of this, the present study examined the structural relationships of physical exercise (PE), mobile phone addiction (MPA), learning engagement (LE), and AB among Chinese "Double Non" college students, aiming at exploring corresponding mechanism to provide supportive guidance for alleviating potential AB. This study adopted a cross-sectional survey approach among the sample of "Double Non" college students in China. We recruited 930 participants (272 men and 658 women) in the second half of the 2022-2023 academic year, all of whom completed questionnaires involving Physical Exercise Rating Scale, Mobile Phone Dependence Index Scale, Utrecht Work Engagement Scale-Student, and Maslach Burnout Inventory-Student Survey. A series of statistical analyses, including descriptive statistics, bivariate correlations, and direct and indirect effects among study variables, were proceeded based on the collected data. The results showed that PE can not only directly and negatively influence AB, but also indirectly and negatively influence AB through the mediation of MPA as well as the chain mediation of both MPA and LE. While PE had no significantly indirect effect on AB via LE. Physical exercise was proved to be an effective way to reduce MPA and then enhance LE, consequently leading to decreased AB in Chinese "Double Non" college students. The findings were discussed in light of related research, and implications and future directions were put forward for application in potential theoretical research and educational practice.
With more than two billion downloads since its launch, TikTok is the fastest-growing video-sharing platform in the world.&nbsp;Many people turn to TikTok for dermatologic medical information. However, there is limited data about psoriasis and psoriasis treatment&nbsp;content on this social media platform. To compare the viewer engagement, content quality, and viewer experience of psoriasis treatment TikTok videos between&nbsp;physicians and non-physicians. We searched the terms "psoriasis" and "psoriasis treatment" on TikTok. Video characteristics were collected. Content quality was evaluated using DISCERN. Viewer experience was assessed using the AVA. Viewer engagement did not significantly differ between physicians and non-physician content creators (0.033&nbsp;plus/minus 0.005 vs&nbsp;0.047&nbsp;plus/minus 0.001, P=0.066). Compared to non-physicians, physicians created videos of higher quality (DISCERN: 1.76&nbsp;plus/minus 0.058 vs 1.44&nbsp;plus/minus 0.032,&nbsp;P&lt;0.001) and of greater viewer experience (AVA: 2.55&nbsp;plus/minus 0.183 vs 1.96&nbsp;plus/minus 0.081, P=0.001). However, there is room for improvement in terms&nbsp;of creating videos of higher quality by both physicians and non-physicians. TikTok can be a powerful tool to promote health literacy and dispel misinformation. Dermatologists may consider focusing&nbsp;their efforts on creating comprehensive educational content and incorporating trending features to reach a wider audience. J Drugs Dermatol. 2024;23(2): doi:10.36849/JDD.7050e.
With ongoing gaps in obesity education delivery for health professions in Canada and around the world, a transformative shift is needed to address and mitigate weight bias and stigma, and foster evidence-based approaches to obesity assessment and care in the clinical setting. Obesity Canada has created evidence-based obesity competencies for medical education that can guide curriculum development, assessment and evaluation and be applied to health professionals' education programs in Canada and across the world. The Obesity Canada Education Action Team has seventeen members in health professions education and research along with students and patient experts. Through an iterative group consensus process using four guiding principles, key and enabling obesity competencies were created using the 2015 CanMEDS competency framework as its foundation. These principles included the representation of all CanMEDS Roles throughout the competencies, minimizing duplication with the original CanMEDS competencies, ensuring obesity focused content was informed by the 2020 Adult Obesity Clinical Practice Guidelines and the 2019 US Obesity Medication Education Collaborative Competencies, and emphasizing patient-focused language throughout. A total of thirteen key competencies and thirty-seven enabling competencies make up the Canadian Obesity Education Competencies (COECs). The COECs embed evidence-based approaches to obesity care into one of the most widely used competency-based frameworks in the world, CanMEDS. Crucially, these competencies outline how to address and mitigate the damaging effects of weight bias and stigma in educational and clinical settings. Next steps include the creation of milestones and nested Entrustable Professional Activities, a national report card on obesity education for undergraduate medical education in Canada, and Free Open Access Medication Education content, including podcasts and infographics, for easier adoption into curriculum around the world and across the health professions spectrum.
With only 13.75% of the identified Aboriginal and Torres Strait Islander population of northern Queensland accessing a billed 715 Health Assessment over a 12-month period, Northern Queensland Primary Health Network (NQPHN) is embarking on an ambitious 12-month program to dramatically improve access to health assessments, and integrated and coordinated care for First Nations' people within its region. By supporting primary care providers with targeted education, training, and digital health literacy bundles and tools, NQPHN aims to facilitate quality and culturally safe 715 Health Assessments to manage chronic conditions. Success of the program will be measured using regional and practice-level data, focusing on the number of Health Assessments and Management Plans for identified chronic conditions.
With rapid advances in information technology, massive datasets are collected in all fields of science, such as biology, chemistry, and social science. Useful or meaningful information is extracted from these data often through statistical learning or model fitting. In massive datasets, both sample size and number of predictors can be large, in which case conventional methods face computational challenges. Recently, an innovative and effective sampling scheme based on leverage scores via singular value decompositions has been proposed to select rows of a design matrix as a surrogate of the full data in linear regression. Analogously, variable screening can be viewed as selecting rows of the design matrix. However, effective variable selection along this line of thinking remains elusive. In this article, we bridge this gap to propose a weighted leverage variable screening method by utilizing both the left and right singular vectors of the design matrix. We show theoretically and empirically that the predictors selected using our method can consistently include true predictors not only for linear models but also for complicated general index models. Extensive simulation studies show that the weighted leverage screening method is highly computationally efficient and effective. We also demonstrate its success in identifying carcinoma related genes using spatial transcriptome data.
With recent advances in understanding racial, socioeconomic, and mental health issues in medicine and their relation to policy and legislation, medical professionals are increasingly involved in local and national advocacy efforts. At the frontlines of these initiatives are medical students who, in addition to completing required coursework and clinical training, devote themselves to serving patients through civic participation. The burgeoning evidence concerning health care disparities and inequity, along with greater awareness of racial and socioeconomic discrimination, have made advocacy an essential aspect of many students' medical training. Every year, thousands of medical students join national medical advocacy organizations, in addition to regional, state, and local groups. Despite the rich history of medical student involvement in advocacy, there remains much speculation and skepticism about the practice as an essential component of the medical profession. From early initiatives pushing for national health insurance after World War II to encouraging antidiscrimination policies and practices, medical students have been collectively working to create change for themselves and their patients. Through efforts such as banning smoking on airplanes, creating safe syringe programs, and protesting against police brutality, many medical students work tirelessly in advocacy despite minimal educational support or guidance about the advocacy process. Given that medical student advocacy continues to grow and has shown measurable successes in the past, the authors believe that these efforts should be rewarded and expanded upon. The authors examine historical examples of medical student advocacy to suggest ways in which advocacy can be integrated into core medical school curricula and activities. They call attention to opportunities to support students' development of knowledge and skills to facilitate legislative change, expansion of interprofessional collaborations and credit, and curricular updates to promote social and health equity.
With social transformation, rapid economic development and deepening awareness of psychological health in China, people's demand for psychological health services is becoming increasingly urgent. A key challenge for Chinese medical organizations is to train enough qualified psychological care nurses. A greater understanding of psychological care competences (PCC) can help in clinical nurse selection, training, and assessment. To develop a PCC framework for Chinese nurses and obtain a consensus on the framework among experts. A descriptive mixed methods study was designed consisting of a literature review and semi-structured interviews followed by three Delphi rounds. The experts (n = 16) involved were nurses, nursing managers and educators from nine Chinese provinces with a specific interest in psychological care. Descriptive statistics assisted in data analysis. Using the Iceberg Model as a theoretical foundation, five main dimensions and associated subdomains were integrated from 39 chosen articles. The semi-structured interviews with 24 nursing managers and nurses confirmed all of the themes from the literature review while generating new themes, both of which were incorporated into the initial PCC framework. After three Delphi rounds, the experts reached consensus on the PCC framework, including five domains (knowledge, skills, professional ethics, personal traits, internal motivations) and 22 subdomains with connotations. The response rate (RR) values for the three rounds of consultation were 80.00%, 87.50% and 92.86%, the composite reliability (Cr) values were 0.89-0.90, and the Kendall coordination coefficients were 0.155-0.200 (P < 0.05). On the basis of the Iceberg Model, literature review and qualitative research methods along with Delphi technique were used to develop a scientific and systematic PCC framework. The research methods were feasible and the results were reliable, thereby providing a basis for adopting this framework into nursing education. A formal assessment tool should be developed to test the PCC of nurses in clinical practice.
With suicide as a leading cause of death, the issue of children and adolescent suicide risks is in the spotlight today. To empower teachers in primary and secondary schools to serve as gatekeepers and to ensure the safety of children and adolescents, the systematically tailored and localized Life Gatekeeper suicide prevention program was designed for Chinese schools. With the ultimate goal of preventing child and adolescent suicide, we aim to outline a research protocol for examining outcomes of the recently created standardized school-based Life Gatekeeper program in reducing teachers' stigma, increasing their knowledge, willingness to intervene, and perceived competence. Participants will be recruited from eligible primary and secondary schools. Cluster sampling will be used to randomly assign each school to either the intervention group or the control group. The primary outcomes are stigma against suicide, suicide literacy, perceived competence, and willingness to intervene with suicidal individuals, which will be measured using the Stigma of Suicide Scale, the Literacy of Suicide Scale, and the Willingness to Intervene Against Suicide Questionnaire, respectively. Measurements will be taken at four time points, including pre-intervention, immediately after the intervention, 6-month follow-up, and 1-year follow-up. The current study features innovative implementation in the real world, by using a randomized controlled trial design to examine the effectiveness of a school-based gatekeeper program among primary and secondary school teachers, following a sequence of defined and refined steps. The research will also investigate the viability of a school-based gatekeeper program for primary and secondary school teachers that could be quickly and inexpensively implemented in a large number of schools.
With support from the American Society for Biochemistry and Molecular Biology (ASBMB), a community of biochemistry and molecular biology (BMB) scientist-educators has developed and administered an assessment instrument designed to evaluate student competence across four core concept and skill areas fundamental to BMB. The four areas encompass energy and metabolism; information storage and transfer; macromolecular structure, function, and assembly; and skills including analytical and quantitative reasoning. First offered in 2014, the exam has now been administered to nearly 4000 students in ASBMB-accredited programs at more than 70 colleges and universities. Here, we describe the development and continued maturation of the exam program, including the organic role of faculty volunteers as drivers and stewards of all facets: content and format selection, question development, and scoring.
With the advance of computer-based assessments, many process data, such as response times (RTs), action sequences, Eye-tracking data, the log data for collaborative problem-solving (CPS) and mouse click/drag becomes readily available. Findings from previous studies (e.g., Peng et al., Multivariate Behavioral Research, 1-20, 2021; Xu, The British Journal of Mathematical and Statistical Psychology, 73(3), 474-505, 2020; He & von Davier, Handbook of research on technology tools for real-world skill development (pp. 750-777). IGI Global, 2016; Man & Harring, Educational and Psychological Measurement, 81(3), 441-465, 2021) suggest a substantial relationship between this human-computer interactive process information and proficiency, which means these process data were potentially useful variables for psychological and educational measurement. To make full use of the process data, this paper aims to combine two useful and easily available types of process data, including the mouse click/drag traces and the response times, to the conventional cognitive diagnostic model (CDM) to better understand individual's response behavior and improve the classification accuracy of existing CDM. Then the full Bayesian analysis using Markov chain Monte Carlo (MCMC) was employed to estimate the proposed model parameters. The viability of the proposed model was investigated by an empirical data and two simulation studies. Results indicated the proposed model combing both types of process data could not only improve the attribute classification reliability in real data analysis, but also provide an improvement on item parameters recovery and person classification accuracy.