Yoxas/statistical_literacy huggingface dataset:
Duchenne Muscular Dystrophy (DMD) is a progressive genetic disease with a prevalence of 1 per 3,600-6,000 male births. Individuals with DMD are typically diagnosed at age 4-7 years; median survival is 30 years. They require multidisciplinary care, personal assistance, and often special education. The aim was to assess the burden of disease in DMD in Denmark. This includes incidence, prevalence, use of healthcare services, labour market participation, educational outcomes, and overall attributable costs due to DMD. Impact on the closest relatives (siblings and parents) was also investigated. The comprehensive Danish national health and administrative registers were used to assess the burden of disease following individuals with DMD and closest relatives from five years before, and up to 20 years after DMD diagnosis. Individuals with DMD (and relatives) from 1994-2021 were included. All outcomes were compared to matched control groups without the disease drawn from the Danish population. 213 unique individuals with DMD were identified. They had lower grades in school, required more special education and more healthcare and home care compared to their control group. The extra costs of special education summed to EUR 180,900 over the course of 11 years elementary school. They had an annual average productivity loss of EUR 20,200 between the age of 18 to 30. The extra healthcare costs of DMD in the 20 years after diagnosis were estimated to EUR 1,524,000. If an individual with DMD lives to be 30, total extra costs sum to EUR 2,365,800. Using national register data this study presented detailed results on the burden of disease of DMD, including impact on closest relatives. With 60 additional hospital admissions and 200 extra outpatient contacts in 20 years healthcare costs, but also costs of home care and special education, increases as disease progresses.
Due to advancements in research, the concept of oral health literacy (OHL) has become rich in connotations, with over 250 definitions present in the literature and government and organizational reports. The diversity of OHL definitions and connotations not only produces conflicting results but also limits the production of accurate OHL measurement and assessment tools while simultaneously hindering the construction of health literacy intervention policies. To clarify the connotations of OHL and establish a scientific basis for evaluation, we conducted a systematic review, searching and analyzing the literature related to the conceptual connotations of OHL. Additionally, we extracted basic, methodological, and OHL conceptual connotation information from the literature. With reference to the review framework, we classified the conceptual connotations of OHL into antecedents of OHL, the core of OHL, mediators, and outcomes of OHL. The comprehensive conceptual connotations of OHL were obtained through a systematic review and concept mapping based on the related literature. Our analysis revealed that the antecedents of OHL can be classified in two categories: personal factors and external factors. The core conceptual connotations of OHL include three core dimensions (with 16 subdimensions): (1) basic skills-literacy, reading comprehension, numeracy, hearing, oral expression, communication, and knowledge; (2) information-related abilities-information acquisition, information understanding, information communication, information evaluation, information utilization, and information decision-making; and (3) oral health maintenance abilities-interpersonal skills, self-regulation, and goal achievement. The mediator of these connotations is oral health behaviors, with oral health being the result of OHL. This study further clarifies the conceptual connotations of OHL, serving as a reference for future OHL-related studies.
Due to digitization in the medical sector, many healthcare interactions are switched to online services. This study assessed the acceptance of video consultations (VCs) in cancer care, and determined drivers and barriers of acceptance. A cross-sectional online-based survey study was conducted in Germany from February 2022 to February 2023. Recruitment took place at oncology outpatient clinics, general practitioners, oncology practices and via cancer-related social media channels. Inclusion criteria were a cancer diagnosis, cancer treatment and internet access. Sociodemographic, medical data, eHealth-related data were acquired via an online assessment. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the acceptance of VC and its predictors. Of N = 350 cancer patients, 56.0% (n = 196) reported high acceptance of VC, 28.0% (n = 98) stated moderate acceptance and 16.0% (n = 56) indicated low acceptance. Factors influencing acceptance were younger age (β = -.28, p < .001), female gender (β = .35, p = .005), stage of disease (β = .11, p = .032), high digital confidence (β = .14, p = .010), low internet anxiety (β = -.21, p = .001), high digital overload (β = -.12, p = .022), high eHealth literacy (β = .14, p = .028), personal trust (β = -.25, p < .001), internet use (β = .17, p = .002), and the UTAUT predictors: performance expectancy (β = .24, p < .001), effort expectancy (β = .26, p < .001), and social influence (β = .34, p < .001). Patients' acceptance of VC in cancer care is high. Drivers and barriers to acceptance identified should be considered for personalized applications. Considering the growing demand for cancer care establishing digital healthcare solutions is justified.
Due to health and/or financial limitations, older migrants may become especially dependent on their neighborhoods, highlighting the importance of investigating their experiences. We explored older Moroccan adults' views on the relative importance of neighborhood resources for aging in place. Thirty Moroccans aged ≥ 65 years residing in Amsterdam, Rotterdam, The Hague, and Utrecht were interviewed and asked to perform a ranking task developed with the combined quantitative and qualitative Q methodology. They ranked the relative importance of 38 statements representing the World Health Organization's eight global age-friendly cities domains, with explanation of their reasoning. By-person factor analysis was performed to identify factors representing distinct viewpoints, which were interpreted with reference to the interviewees' comments. Four viewpoints were identified: "home sweet home"; "connected, well-informed, and engaged"; "suitable and affordable living"; and "a lively neighborhood." The perceived importance of neighborhood resources for aging in place differed among viewpoints. Older Moroccan adults prioritize different neighborhood resources for aging in place. Our findings suggest that their diverse needs can be satisfied by enabling family to live in close proximity, providing diverse, inclusive neighborhoods with affordable, suitable housing, understandable information, social/cultural activities, and care services for vulnerable groups. Future studies may build on our findings to explore older (migrant) adults' views on needs for aging in place in the Netherlands and other western countries.
Due to high rates of unintended pregnancies in Delaware, the state launched a public health initiative in 2014 to increase access to contraceptive services. This study was designed to assess the practice-level barriers and facilitators to providing contraceptive care, particularly long-acting reversible contraceptives (LARCs), to adolescents in primary care settings. This qualitative study was part of a larger process evaluation of the Delaware Contraceptive Access Now (DelCAN) initiative. In-depth, semi-structured qualitative interviews were conducted with 16 practice administrators at 13 adolescent-serving primary care sites across the state of Delaware. A process of open, axial, and selective coding was used to analyze the data. Despite the interest in LARC among their adolescent patients, administrators described numerous barriers to providing LARC for adolescents including confidentiality in patient visits and billing, preceptorship, and provider discomfort and assumptions about the need for contraception among adolescent patients. Findings from this study reveal substantial barriers to providing contraception to adolescents, even in primary care practices that were committed to comprehensive contraceptive access for their adolescent patients. This study supports the need for contraceptive care to be integrated into training of pediatricians at every stage of their education. Such training must go beyond education about contraceptive options and the clinical skills necessary for LARC insertion and removal, to include counseling skills based in a reproductive justice framework. Additional changes in policies and practices for adolescent patients would further increase access to contraceptive care.
Due to its effect on patient health and healthcare resources, the study of diabetic foot is essential. Despite the existence of classification and grading systems, further evidence is required. Current systems are prone to a lack of validation in specific populations, inadequate consideration of regional variations, and an incomplete evaluation of risk factors and outcomes. The prevalence and complications of diabetes, such as diabetic foot, are on the rise worldwide, necessitating regionally specific research. To fill these gaps, this study focuses on a Southeast Asian subpopulation. The study aims to evaluate the clinical characteristics of diabetic foot patients using the WIfI classification system, and to develop a risk calculator for patients to predict and evaluate potential outcomes. A retrospective analysis was conducted on the medical records of patients with diabetic foot who visited a tertiary hospital in Vietnam between December 2021 and July 2022. Demographic data, clinical characteristics, and outcomes were collected and classified according to the WIfI (Wound, Ischemia, and foot Infection) classification system. Descriptive statistics were used to analyze the data, and a multivariable logistic regression model was employed to develop a risk calculator. The study included 60 patients with diabetic foot. Gender distribution was similar (56.7% male), with a mean age of 44 years. Most patients had ulcers of varying degrees, while ischemia contributed to higher grades, placing 43.3% at moderate-to-high risk of amputation (stages 3 and 4). HbA1c positively correlated with amputation risk (p<0.05), while ABI, TBI, and TP showed inverse correlations (p<0.001). The amputation risk equation based on the WIfI scale was: risk=3.701-0.788ABI-1.260TP. A risk calculator was developed using these predictors to estimate adverse outcomes. In diabetic foot patients, early identification and management of risk factors are crucial. The findings of this study highlight the importance of ischemia and its association with amputation risk. Incorporating HbA1c, ABI, and TP, the risk calculator enables personalized assessments of amputation risk, thereby assisting healthcare professionals in treatment planning. Further validation and refinement of the risk calculator is required for broader clinical application.
Due to its frequent misuse, the p value has become a point of contention in the research community. In this editorial, we seek to clarify some of the common misconceptions about p values and the hazardous implications associated with misunderstanding this commonly used statistical concept. This article will discuss issues related to p value interpretation in addition to problems such as p-hacking and statistical fragility; we will also offer some thoughts on addressing these issues. The aim of this editorial is to provide clarity around the concept of statistical significance for those attempting to increase their statistical literacy in Orthopedic research.
Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS. Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves. A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723-0.742) as well as the three residents was equal (AUC 0.842-0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts' ratings using the MR BI-RADS scale (p ≤ 0.05). The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical "problem solving MRI" setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience. • Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical "problem solving MRI" setting. • The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.
Due to low susceptibility of coronavirus disease of 2019 (COVID-19) in children, limited studies are available regarding COVID-19 in the pediatric population in Tunisia. The current study evaluated the incidence, clinical characteristics, and outcomes of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection among children hospitalized at Béchir Hamza Children's Hospital. A retrospective cohort analysis was conducted using the hospital database between March 2020 and February 2022 with children aged ≤15 years with SARS-CoV-2 infection (confirmed by RT-PCR). A total of 327 COVID-19 hospitalized patients with a mean age of 3.3 years were included; the majority were male. Neurological disease (20%) was the most common comorbidity, while fever (95.3%) followed by cough (43.7%) and dyspnea (39.6%) were the most frequent symptoms reported. Severe disease with oxygen requirement occurred in 30% of the patients; 13% were admitted in the Intensive Care Unit. The overall incidence rate of COVID-19 hospitalization (in Tunis governorates) was 77.02 per 100,000 while the inpatient case fatality rate was 5% in the study population. The most prevalent circulating variant during our study period was Delta (48.8%), followed by Omicron (26%). More than 45% of the study population were <6 months and one-fourth (n = 25, 26.5%) had at least one comorbidity. Thus, the study findings highlight the high disease burden of COVID-19 in infants.
Due to the authorization of the Mpox vaccines, we aimed to identify determinants of the intention to get vaccinated, actively trying to receive vaccination, and for successfully receiving a vaccination in Germany employing the 5 C model of vaccination readiness. Data stem from a cross-sectional online survey that was available online from August 13, 2022 to August 31, 2022. To assess the influence of the 5 C Model on vaccination behavior, we conducted a multinomial logistic regression. 3,338 participants responded to the survey, with 487 already vaccinated and 2,066 intending to receive a vaccination. Confidence and collective responsibility were positively associated with intention to get vaccinated, while complacency was negatively correlated. A higher score on the calculation scale increased the odds of intention to receive vaccination but not with actively having tried to receive a vaccination. Fewer perceived constraints were associated with higher odds to be vaccinated. Patients in practices that focus on HIV treatment were more likely to intend to get vaccinated, to have tried to get vaccinated and to be vaccinated, regardless of indication. While level of education had no impact, having an indication to get vaccinated was a strong predictor of vaccination behavior in all groups. Future vaccination campaigns should aim to reduce specific constraints of the target group and make vaccines widely available in primary care institutions beyond HIV-focused practices.
Due to the changing conditions of education, research, and treatment in the world, especially the recent pandemic, and more use of virtual space, there is a need for evaluation of digital professionalism in faculty members as the most influential people who have a direct and deep impact on the next generation. In this analytical cross-sectional study that was conducted in 2023 on 149 faculty members of Iran University of Medical Sciences, they were invited to participate in the study through various methods (SMS, E-mail, and media messages). The link to the Persian standardized questionnaire was made available for participants. If a person received less than 70% of the score in each area, he/she would receive solutions to improve his/her situation in that area at the end of answering the questions. The self-administered questionnaire has 5 fields and 33 questions. Maximum scores were 10 points. Spearman and Pearson correlation coefficients and statistical tests consisting of chi-square, t-test, Mann-Whitney U, one-way ANOVA, and Kruskal-Wallis H were used in the analysis. The mean overall score of people in principles of digital professionalism was 0.8. Women and basic sciences faculties had a significantly better status than men and clinical faculties in the principles of digital professionalism as a whole (P = 0.001 and P = 0.049, respectively). The domain of "knowledge management and information literacy" had significantly lower scores in professors in comparison with other degree (instructors, assistant professors, and associate professors (P = 0.039). The mean score of the principles of digital professionalism is acceptable at 80%. Coherent, timely, and up-to-date training to ensure the effective, safe and appropriate use of digital technology, especially for men, professors and clinical faculty members who had a lower score than others, should be done.
Due to the complex nature of healthcare professionals' roles and responsibilities, the education of this workforce is multifaceted and challenging. It relies on various sources of learning from teachers, peers, patients and may focus on Work Integrated Learning (WIL). The COVID-19 pandemic has impacted many of these learning opportunities especially those in large groups or involving in person interaction with peers and patients. Much of the curriculum has been adapted to an online format, the long-term consequence of which is yet to be recognized. The changed format is likely to impact learning pedagogy effecting both students and teachers. This requires a systematic approach to evaluation of online teaching and learning adaptation, in comparison to the previous format, where, in person education may have been the focus. The proposed study is a broad based evaluation of health professional education in a major Australian University. The protocol describes a mixed methods convergent design to evaluate the impact of online education on students and teachers in health professional courses including Medicine, Nursing, Allied Health and Biomedical Science. A framework, developed at the university, using Contribution Analysis (CA), will guide the evaluation. Quantitative data relating to student performance, student evaluation of units, quantity of teaching activities and resource utilization will be collected and subjected to relevant statistical analysis. Data will be collected through surveys (500 students and 100 teachers), focus groups (10 groups of students) and interviews of students and teachers (50 students beyond graduation and 25 teachers, for long term follow up to 12 months). Application of CA will be used to answer the key research questions on the short term and long-term impact of online education on teaching and learning approaches. The protocol describes the study, which will be widely implemented over the various courses in Health Professional Education and Biomedical Science. It will evaluate how students and teachers engage with the online delivery of the curriculum, student performance, and resources used to implement these changes. It also aims to evaluate longitudinal outcome of student learning attributes and impact on graduate outcomes, which is poorly reported in educational literature.
Due to the complex nature of the chemical compositions of ignitable liquids (IL) and the interferences from fire debris matrices, interpreting chromatographic data poses challenges to analysts. In this work, artificial intelligence (AI) was developed by transfer learning in a convolutional neural network (CNN), GoogLeNet. The image classification AI was fine-tuned to create intelligent classification systems to discriminate samples containing gasoline residues from burned substrates. All ground truth samples were analyzed by headspace solid-phase microextraction (HS-SPME) coupled with a gas chromatograph and mass spectrometer (GC/MS). The HS-SPME-GC/MS data were transformed into three types of image presentations, that is, heatmaps, extracted ion heatmaps, and total ion chromatograms. The abundance and mass-to-charge ratios of each scan were converted into image patterns that are characteristic of the chemical profiles of gasoline. The transfer learning data were labeled as "gasoline present" and "gasoline absent" classes. The assessment results demonstrated that all AI models achieved 100 ± 0% accuracy in identifying neat gasoline. When the models were assessed using the spiked samples, the AI model developed using the extracted ion heatmap obtained the highest accuracy rate (95.9 ± 0.4%), which was greater than those obtained by other machine learning models, ranging from 17.3 ± 0.7% to 78.7 ± 0.7%. The proposed work demonstrated that the heatmaps created from GC/MS data can represent chemical features from the samples. Additionally, the pretrained CNN models are readily available in the transfer learning workflow to develop AI for GC/MS data interpretation in fire debris analysis.