Yoxas/statistical_literacy huggingface dataset:
This study aims to identify the prospective skill requirements for future radiographers practising in the United Arab Emirates (UAE). Such information will inform educational institutions, healthcare organisations, and policymakers in developing effective strategies. A cross-sectional study was conducted involving currently practising radiographers, nuclear medicine technologists, sonographers, and radiation therapists in the UAE (n =74). A comprehensive survey questionnaire was developed and validated through piloting and expert consultations. Ethical approval was obtained, and data were collected through purposive sampling. Descriptive statistics, reliability analysis, Chi-square tests, and factor analysis were employed in the data analysis. The results showed that 73%, 47.3%, 43.2%, 40.5%, 39.2%, 33.8% interested in radiology safety, image interpretation, interprofessional and interpersonal skills, research and managerial skills, Picture Archiving and Communication System (PACS) administration and AI (Artificial Intelligence) and, clinical supervision and assessment, respectively. The factor analysis showed four factors factor considered for CPD training are training settings (15.12), training topics (1.88), CPD credits (1.72) and, presenter and expenses (1.49). This study sheds light on the CPD requirements and aspirations of radiographers in the UAE, offering insights into their preferences and challenges. These findings can inform strategies for improving CPD opportunities and ensuring that radiographers are equipped to meet the evolving healthcare demands in the UAE, including performing enhanced practice. Development of flexible and comprehensive CPD programmes tailored to radiographers' career interests is required. Employers should provide financial support and flexibility in training options. Regulatory bodies should continue to mandate CPD, fostering a culture of lifelong learning. Supportive work environments, interdisciplinary collaboration, and technological fluency are crucial. Emphasising patient-centred care, research opportunities, and continuous assessment further enhances radiography practice.
This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h.
This study aims to integrate and use AI to teach core concepts in a medicinal chemistry course and to increase the familiarity of pharmacy students with AI in pharmacy practice and drug development. Artificial intelligence (AI) is a multidisciplinary science that aims to build software tools that mimic human intelligence. AI is revolutionizing pharmaceutical research and patient care. Hence, it is important to include AI in pharmacy education to prepare a competent workforce of pharmacists with skills in this area. AI principles were introduced in a required medicinal chemistry course for first-year pharmacy students. An AI software, KNIME, was used to examine structure-activity relationships for 5 drugs. Students completed a data sheet that required comprehension of molecular structures and drug-protein interactions. These data were then used to make predictions for molecules with novel substituents using AI. The familiarity of students with AI was surveyed before and after this activity. There was an increase in the number of students indicating familiarity with use of AI in pharmacy (before vs after: 25.3% vs 74.5%). The introduction of AI stimulated interest in the course content (> 60% of students indicated increased interest in medicinal chemistry) without compromising the learning outcomes. Almost 70% of students agreed that more AI should be taught in the PharmD curriculum. This is a successful and transferable example of integrating AI in pharmacy education without changing the main learning objectives of a course. This approach is likely to stimulate student interest in AI applications in pharmacy.
This study aims to introduce the development and psychometric properties of a brief generic cancer knowledge scale for patients (BCKS-10) that includes different elements of knowledge and skills (terminology, diagnosis, treatment, prevention, and numeracy). Although cancer knowledge is a central dimension of cancer literacy, most previous studies either investigated cancer knowledge among the general population, or among patients with a specific cancer diagnosis. Qualitative interviews (n = 11) and a quantitative survey (n = 267) among peer support group leaders were conducted to further develop the BCKS-10 after literature screening. n = 500 patients with cancer were recruited across Germany between October 2020 and February 2021. Construct validity, item discrimination and reliability were tested. ANOVA revealed no significant differences of the knowledge score between various cancer sites, a significant positive association with education, and a negative association with migration background by trend supporting construct validity. In terms of item discrimination, the corrected item-total correlation of 8 out of 10 items were above the threshold of 0.3. Cronbach's alpha of about 0.68 revealed an acceptable internal consistency as the tool is brief and consists of different dimensions. Overall, the findings show that the BCKS-10 is a suitable tool to briefly assess cancer knowledge among patients independent of cancer site. However, further surveys have to be conducted to validate the psychometric properties and enhance the BCKS-10.
This study aims to investigate eye tracking in the practical training of incontinence pad change, which is commonly required in older adult nursing. Some competencies possessed by skilled and experienced personnel are difficult to verbalize into textbooks. However, this is crucial for education, especially nursing practice education. Eye-gaze analysis is one such tool that can aid the efficient transfer of knowledge to students. Therefore, eye-gaze analysis, a novel technology for visualizing situational awareness and decision-making, has recently gained traction in healthcare. An observation study METHODS: Ten nursing faculty members and 13 nursing students with prior incontinence pad change experience participated in this study using an older adult simulator. There were two groups of students - S1 with more recent experience in older adult care and incontinence pad changing and S2 with less. Areas of interest (AOIs) during incontinence pad preparation and fitting were determined based on gaze fixation and the time spent fixating on these areas was compared. Students took longer than nursing faculty members. When visualizing the eye movements between the AOIs in the network, the faculty nurses and S1 alternated their gaze between the new incontinence pad and the buttocks and between other AOIs. Simultaneously, S2 tended to gaze or stare only at the new incontinence pad. The presented data may help interpret visual-based situational awareness and establish effective nursing education, especially in acquiring skills that are difficult to verbalize.
This study aims to investigate how online collaboration can support the learning of science, technology, engineering, and mathematics (STEM) in higher education. Empirical data were collected from 88 postgraduate students studying at the African Centre of Excellence for Innovative Teaching Learning Mathematics and Science (ACEITLMS) using online oral interviews and two five-point Likert scale questionnaires. Interviews were analysed through content analysis while data from the questionnaire were scanned through the Statistical Package for Social Scientists (SPSS) to compute descriptive statistics and Spearman rho correlation coefficient. The findings indicate that online collaborative learning through small group discussions prompt knowledge co-construction, and higher-order thinking skills in STEM subjects. Moreover, the findings demonstrate how several electronic multimedia tools (PhET simulations, animations, YouTube videos) can increase student retention and engagement in learning STEM. Though the students reported that they experienced challenges such as poor internet connection, lack of laboratory work, electricity shortage, and limited ICT skills, they managed to complete STEM learning activities by using free virtual laboratories, portable tethering hotspots from their smartphones, and smartphones where power was a problem and learnt the navigation of ICT tools from their peers. The study found moderate positive Spearman rho correlation coefficient, rs=0.69,P<0.01 which explains that 69% of the total variance in the students' successful performance is explained by the two variables, i.e., social and cognitive presence. The study recommends more training for course instructors and students. Efforts should be put in place to focus on ICT manipulation and curating interactive content. The researchers acclaim the expansion of internet coverage in University of Rwanda campuses. This action will enhance online and blended learning. Moreover, the study recommends the integration of ICT and the use of multimedia tools such as Bio-interactive and Physics Education Technology (PhET) interactive simulations in STEM subjects as supplementary resources. These tools support cognitive and affective domains in the teaching and learning process. Furthermore, universities can reduce the problem of expensive and inadequate laboratory equipment by adopting the use of virtual laboratories, especially for online STEM lessons.
This study aims to investigate nursing students' perspectives on virtual reality technologies and their self-directed learning skills, specifically focusing on how these variables interact and influence each other in the context of nursing education. We also discern potential disparities in these skills based on descriptive characteristics, using both traditional statistical and advanced machine learning approaches for a comprehensive analysis. Rapid developments in technology, particularly during the Covid-19 pandemic, have brought virtual reality technologies to the forefront of nursing education. However, there is a gap in understanding how nursing students' perceptions of these technological relate to their development of self-directed learning skills. A descriptive and cross-sectional study design is employed to both quantify nursing students' perspectives on virtual reality in their education and assess their self-directed learning skills. This approach integrates traditional statistical methods with advanced machine learning techniques, with the intention of offering a comprehensive and nuanced analysis to inform future teaching strategies in nursing. The study used a blend of survey scales and a tree-based machine learning model to measure and analyze nursing students' views, attitudes and self-directed learning levels. This dual approach allows for a more detailed assessment of the factors influencing self-directed learning abilities. Traditional statistical techniques were also applied to assess the reliability of the machine learning findings. Findings reveal that nursing students generally held positive views towards virtual reality technologies and exhibited a high level of self-directed learning skills. Notable differences in self-directed learning skills were influenced by gender on the overall scale (p <0.001), with male students scoring higher than their female counterparts in both specific sub-dimensions and on the overall scale, but not by academic year. The machine learning analysis provided deeper insights into these variations, highlighting subtle distinctions in student demographics that traditional statistical methods did not fully capture. The study offers valuable insights into interconnected nature of nursing students' views on virtual reality technologies and their self-directed learning skills. The results support the integration of virtual reality in nursing curriculum programs and underscore the importance of customizing teaching strategies based on insights gained from machine learning analyses. This approach has the potential to substantially improve both the learning experience and the overall quality of nursing education.
This study aims to investigate the characteristics of students who switch versus those who do not switch when they transition from upper secondary to higher education. The data from 1338 students randomly selected from 21 HEIs in Cambodia in 2020 found that upper secondary school students are more likely than not to switch academic majors when they enter higher education. The tendency to switch is more common for female students in science-track, most of whom chose non-STEM majors such as business, management, accounting and finance. Probit analysis revealed that the decision to switch is influenced by individual academic performance and interest in science and mathematics at upper secondary school, household's socioeconomic status, higher education institution (HEI)'s location and type. However, students whose like mathematics and physics and who have a higher technology readiness index score and those who were awarded scholarships are less likely to switch from science to non-STEM majors. Teaching approaches that create opportunities for students to engage in practical classroom activities and stimulate their curiosity in science and mathematics should be considered. Efforts to optimise learning experiences should therefore focus on creating a highly interactive teaching-learning environment as a cognitive-activation strategy for promoting students' interest and enjoyment of the subjects they are studying. Scholarship can also be an alternative to address the switching issue.
This study aims to promote interoperability in precision medicine and translational research by aligning the Observational Medical Outcomes Partnership (OMOP) and Phenopackets data models. Phenopackets is an expert knowledge-driven schema designed to facilitate the storage and exchange of multimodal patient data, and support downstream analysis. The first goal of this paper is to explore model alignment by characterizing the common data models using a newly developed data transformation process and evaluation method. Second, using OMOP normalized clinical data, we evaluate the mapping of real-world patient data to Phenopackets. We evaluate the suitability of Phenopackets as a patient data representation for real-world clinical cases. We identified mappings between OMOP and Phenopackets and applied them to a real patient dataset to assess the transformation's success. We analyzed gaps between the models and identified key considerations for transforming data between them. Further, to improve ambiguous alignment, we incorporated Unified Medical Language System (UMLS) semantic type-based filtering to direct individual concepts to their most appropriate domain and conducted a domain-expert evaluation of the mapping's clinical utility. The OMOP to Phenopacket transformation pipeline was executed for 1,000 Alzheimer's disease patients and successfully mapped all required entities. However, due to missing values in OMOP for required Phenopacket attributes, 10.2 % of records were lost. The use of UMLS-semantic type filtering for ambiguous alignment of individual concepts resulted in 96 % agreement with clinical thinking, increased from 68 % when mapping exclusively by domain correspondence. This study presents a pipeline to transform data from OMOP to Phenopackets. We identified considerations for the transformation to ensure data quality, handling restrictions for successful Phenopacket validation and discrepant data formats. We identified unmappable Phenopacket attributes that focus on specialty use cases, such as genomics or oncology, which OMOP does not currently support. We introduce UMLS semantic type filtering to resolve ambiguous alignment to Phenopacket entities to be most appropriate for real-world interpretation. We provide a systematic approach to align OMOP and Phenopackets schemas. Our work facilitates future use of Phenopackets in clinical applications by addressing key barriers to interoperability when deriving a Phenopacket from real-world patient data.
This study aims to quantify the areas of most concern in medical students in relation to their residency application in the setting of the COVID-19 pandemic and to identify risk factors for all that cause concern and specific areas of concern in a population with well-established high rates of anxiety at baseline. The COVID-19 pandemic introduced sweeping changes to medical education that had wide-ranging effects on medical students and their applications for medical residencies. In August 2020, we utilized a cross-sectional study to quantify student's areas of concern related to residency application related to the COVID-19 pandemic. We asked participants to rate their levels of concern in 15 different aspects related to medical residency applications and the perceived impact that COVID-19 had on each. The survey was distributed to 984 osteopathic medical students, with 255 complete responses. The three areas of greatest impact were shadowing opportunities (4.15), volunteer opportunities (4.09), and conferencing opportunities (4.09). The most salient demographic variables were year in school, sex, and locale. Females reported higher levels of concern across all categories in the study compared to males, with statistical significance across all categories (all p<0.05, Range d=0.16 to 0.43), except for letters of recommendation and sub-internships. The areas of most concern identified in our study were consistent with prior studies and may implicate the pressures that female medical students may feel compared to their male counterparts. The underlying cause(s) may be subject to future research.
This study aims to report the development of a preclinical simulation laboratory Demonstration Video Series (DVS) for the 2021-2022 academic year, measure its usage and usefulness, and compare these findings to the usage and usefulness of the existing didactic lecture videos. The DVS videos were intended to be viewed before each preclinical simulation laboratory session along with the pre-existing didactic lectures (DL) by University of California San Francisco (UCSF) learners. Usage measurements included the percentage of the class that viewed each video, the number of views that each video received, and the average duration of each video that was watched. Usefulness of the videos was measured by a survey that assessed learner perspective on knowledge and ability to apply that knowledge during the simulation lab exercises. Both usage and usefulness of the DVS were then compared to the usage and usefulness of the DL. Both descriptive statistics and independent sample hypothesis tests were performed to compare the differences in proportion between DVS and DL mediums. Statistically significant differences were found in terms of both usage and usefulness of the DVS compared to the DL, with DVS being utilized more overall. With an 81% response rate, survey analysis revealed statistically significant differences among the learners' perspectives on the usefulness of the DVS compared to the DL, with a clear preference for the DVS over the DL and an overwhelmingly positive perception of the DVS. The DVS was found to be a valuable addition to the preclinical laboratory sessions for first-year learners.
This study aims to retrospectively analyze the epidemiological and clinical characteristics of acute intussusception in a tertiary-care pediatric hospital in China over 4 years and evaluate the effectiveness and recurrence of fluoroscopy-guided pneumatic reduction (FGPR) and ultrasound-guided hydrostatic reduction (UGHR). This retrospective study was conducted from January 2019 to December 2022 involving children admitted and managed for acute intussusception in a tertiary-care pediatric hospital in China. The epidemiology, clinical features, and therapeutic effects were analyzed using IBM SPSS Statistics 20.0. The study included 401 boys (68.43%) and 185 girls (31.57%) aged from 2 months to 12 years. The most common symptoms reported were abdominal pain or paroxysmal crying (95.73%), vomiting (45.39%), and bloody stool (7.34%). Vomiting and bloody stool became atypical with increasing age (P < 0.001). The total success cases of reduction accounted for 563 cases (96.08%), and the recurrent cases accounted for 71 cases (12.12%). No significant difference was observed in the success or recurrence rates between FGPR and UGHR (P > 0.05). Abdominal pain was an independent protective factor for successful enema (P < 0.01, OR = 72.46), while bloody stool (P < 0.01, OR = 0.06) and older age were independent risk factors (P < 0.001, OR = 0.51). Of the 71 patients with recurrent intussusception, 29 were successfully reduced by enema, and the other 23 required surgical reduction. Twelve of the surgical cases were secondary intussusception, including three cases of Meckel's diverticulum, five cases of polyps, and four cases of non-Hodgkin lymphoma. The epidemiological characteristics of children with intussusception in Xiamen showed peculiarity with a higher male-to-female ratio, older age at diagnosis, and no significant seasonality. Both FGPR and UGHR were effective and safe for intussusception, and surgical reduction was essential for patients with failed enema reduction.
This study analyzed data from a community-based prostate cancer (PCa) education and screening program (Prostate Outreach Project; POP) to enhance PCa-related knowledge among medically underserved Asian American men. It also examined PCa screening history, clinical abnormalities based on prostate-specific antigen (PSA) tests and digital rectal examination (DRE) results, and follow-up and PCa diagnosis rates. Participants-521 Asian men (251 Vietnamese, 142 Chinese, and 128 South Asians)-were offered PCa screening using PSA tests and/or DRE and an educational session on PCa. Of these men, 277 completed PCa-related knowledge surveys before and after viewing an educational video. Significant between-group differences in PCa-related knowledge were found at pre-assessment (p < 0.001) but not at post-assessment (p = 0.11), at which time all groups showed improved PCa-related knowledge. Most participants (77.9%) had never received PCa screening, but Vietnamese men had the lowest previous screening rate (17.3%). Chinese men had elevated PSA values and the highest abnormal DRE rates. Of the 125 men with abnormal screening outcomes, only 15.2% had adequate follow-up. Of the 144 men diagnosed with PCa in POP, 11.1% were Asians (seven Chinese, six Vietnamese, and three South Asian). Despite the ethnic heterogeneity among Asian men, a community outreach program may successfully enhance their PCa-related knowledge.