Yoxas/statistical_literacy huggingface dataset:
Tinnitus is a quite common and bothersome disorder that results in a perceived sound or noise, without an external origin, often causing notable psychological distress. Some interconnections between tinnitus, bodily pain perception, and psychological well-being were previously reported, thus the relationships between tinnitus and temporomandibular joint (TMJ)-related muscle issues, resulting in somatosensory tinnitus, must be deeply investigated. This study aims to assess the prevalence of tinnitus in patients with temporomandibular disorders (TMD) and to examine the impact of treatment approaches for TMD in patients with and without tinnitus. In this cross-sectional study, a total of 37 adults with TMD symptoms were treated with cognitive behavioural psychological therapy, including relaxation and self-inspection, self-care education, and physiotherapy. Diagnostic data were collected before and after treatment using the Axis II of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and the Tinnitus Handicap Inventory (THI) questionnaire. Statistical analysis included descriptive assessments and significance was set at p < .05. Individuals with tinnitus and TMD reported a significantly higher number of body pain areas, indicating a link between tinnitus and increased bodily pain perception. Tinnitus did not significantly impact TMJ-related functions. Significantly higher levels of psychological distress were observed in individuals with tinnitus, as evidenced by elevated scores in depression, generalised anxiety and somatic symptoms. Tinnitus is a complex condition with significant effects on health and well-being, requiring an interdisciplinary approach for effective evaluation and care. The study provides deep insights into the prevalence of tinnitus in TMD patients, underscoring the need for comprehensive treatment strategies addressing both TMD and tinnitus.
To achieve ambitious energy-climate targets, all EU member states have introduced policies to support the market introduction of renewable energy sources (RES) generation. Motivated to close the gap of the merit order effect (MOE) in less mature Central and South East European electricity markets, we empirically confirm economic theory predictions that in the short run, an increase in RES generation reduces electricity prices. The merit order effect is initially econometrically confirmed and quantified. Different econometric model specifications are estimated to differentiate the MOE caused by wind and solar generation and to differentiate the MOE on high-load and low-load days. In addition, we simulate the adjustment of the realised day-ahead electricity prices to the no-RES generation scenario. Modern statistical methods are applied to bridge the gap in the limited public data availability to solve simulation models used in the power system or agent-based simulations. A family of data mining algorithms is applied for the merit order estimation used in the dynamic adaptation of the generation mix to the omitted RES generation. The estimated energy imbalance caused by the excluded RES generation is therefore compensated by the additional conventional generation dispatch according to the estimated power plant merit order. The estimated supply curves for each generation technology assist the reasoning behind the established MOE in econometric models. Based on our findings, policymakers should prioritise policies that facilitate the integration of RES into their electricity markets, which would in turn accelerate energy transition. With increasingly growing shares of renewables in the system, the governments need to rethink the support scheme, where the emphasis should be placed on efficiently integrating renewables in the power system by taking into account temporal and spatial dimensions.
To achieve consensus amongst an expert panel of prosthodontics/restorative dentistry academics on the best undergraduate teaching and assessments, and to develop recommendations regarding teaching and assessment of undergraduate prosthodontics. Semi-structured electronic questionnaires were used to collect data from senior clinical academics involved in the teaching of prosthodontics on three consecutive occasions (Delphi method). The questionnaires asked the experts' opinion on best teaching and assessment methods in the undergraduate prosthodontics curriculum. Invitation emails, with a hyperlink to the Round 1 questionnaire, were sent to 36 international dental academic experts. In later rounds, panellists were invited to consider their previous responses in light of the overall group response in attempt to bring the panel to a consensus. The group response was summarized using simple descriptive statistics, and the target level of consensus for each question was set at ≥ 70%. A response rate of at least 70% between rounds was deemed appropriate to maintain rigour. Twenty-three senior academic experts from eleven countries agreed to participate. Eighteen (representing nine different countries) completed the questionnaires in its entirety (response rate 78.3%). The number of statements that attained consensus agreement was much higher than the number of non-consensus statements-92.6%, 175 statements out of 189 over three iterative rounds. Only 14 statements did not obtain a consensus during this Delphi study. A total of 175 consensus statements represent the agreement expert views of participated senior academics in prosthodontics from nine different countries and across four continents. These consensus statements could be considered detailed guidelines and recommendations to improve future undergraduates' curriculum in prosthodontics. This Delphi study achieved a high consensus among a panel of senior academics in the teaching and assessment of undergraduate prosthodontics. This consensus could help minimise the current international and national divergence in dental schools' prosthodontics curricula, which could benefit future dentists and, subsequently, the patients.
To address health inequities, emergency physicians must understand the structural underpinnings of health disparities, including social determinants of health (SDoH), and must critically reflect on the integration of SDoH into clinical practice. SDoH education should include reflective knowledge acquisition, while incorporating systemic sociohistorical forces and individual factors, such as bias, which propagate inequities but are rarely emphasized in graduate medical education (GME). The health humanities (HH), an inclusive transdisciplinary field combining arts, humanities, and social justice, may represent a novel unexplored approach toward incorporating SDoH in GME. We sought to implement and evaluate a GME HH-based curriculum focused on SDoH. An interprofessional team applied Kern's framework to create a longitudinal HH curriculum integrating narrative medicine and visual thinking strategies with evidence-based practices for addressing SDoH in clinical practice. This curriculum was implemented for 52 residents in an EM program in 2019-2020; sessions were initially held in the classroom and community and then virtually during the COVID-19 pandemic. Objectives included encouraging (1) critical thinking about SDoH, (2) engagement with patients and communities, (3) self-reflection, and (4) translation of SDoH to patient care. Descriptive statistics and a constructivist paradigm were applied to results of a postcurriculum survey and focus group, respectively. A curriculum evaluation survey completed by 32/52 residents (61.5%) revealed agreement (75%-90%) that objectives were met. 93.1% of respondents thought humanities were important in residency training. Qualitative analysis of a focus group with 10 participants revealed additional impacts on individual growth, transformation of departmental culture, and transformation of patient care. Curriculum implementation was inexpensive and relied on interprofessional collaboration. The HH represent a promising collaborative framework for integrating SDoH in GME and may inspire transformation of learners' attitudes and practices in EM, though clinical impacts still need to be established.
To address low state physical education (PE) quantity and quality law implementation in elementary schools, the New York City Department of Education (NYCDOE) delivered a multilevel intervention (PE Works; 2015-2019), which included a district-led audit of school PE-law implementation, feedback, and coaching with principals. Using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) implementation science framework, we assessed the primary multilevel drivers of success for this approach in increasing adherence to PE quantity and quality law. We conducted in-depth, semi-structured interviews with district-level personnel (n=17), elementary school administrators (n=18), and PE teachers (n=6) in 2020-21. Interview results suggested several key RE-AIM drivers of successful PE law implementation. Reach: Ensure higher-need schools receive the necessary initial support to improve PE and later focus on lower-need schools. Provide support tailored to school needs, not penalties, to improve PE. Adoption: Increase the priority of PE at both district and school levels (e.g., audit and feedback, themselves, appear to elevate PE's priority). Streamline data collection and feedback reports; collecting/reporting too much information is burdensome and leads to lack of focus. Involve qualified (i.e., skilled in both school administration and PE programming/pedagogy) district-level personnel to work collaboratively with schools. Build strong, trusting district-school relationships. Maintenance: Provide ongoing district-level support to schools and involve parents to advocate for quality PE. PE audits, feedback, and coaching (PEAFC) can guide schools in establishing long-term plans for successfully implementing PE-related law. Future research should examine the impact of PEAFC elsewhere (e.g., secondary schools, other districts).
To address the challenges encountered by Chinese primary school students, particularly left-behind and migrant children, who exhibit a preference for animations, video games, and short videos over reading books and struggle with Chinese-English bilingual skills, this study introduces an educational robot AI-assisted method for simultaneous bilingual reading. To assess the effectiveness of this method, a 6-month Chinese-English bilingual extracurricular reading comparative experiment was conducted involving 85 grade 5 students from two classes in a primary school in Hangzhou, China. The AI-assisted class freely read 100 bilingual/English electronic picture books and 200 Chinese electronic classic serial picture books by employing the AI-assisted human-computer interactive electronic reading mode of the "Educational Robot+Audio Electronic Picture Book+Character-play Based Reading." In contrast, the paper book group read the same content presented in the traditional paper book format, following the "regular independent reading" mode. Post-experimental analyses were conducted employing t-tests and MANCOVA and the results revealed that: the primary factors influencing reading effectiveness are the choice of reading materials, reading tools, and reading mode, while reading time does not emerge as the principal influencing factor. Furthermore, students in the AI class demonstrated significant enhancements in bilingual reading motivation, reading amount, reading comprehension, independent learning ability, pronunciation proficiency, and test scores compared to their peers in the paper book class. The AI-assisted reading mode utilizing educational robots garnered positive feedback from teachers, parents, and students. It offers the potential to effectively substitute parental involvement in parent-child reading and English tutoring, while also enabling the simultaneous acquisition of bilingual proficiency in both Chinese and English. This approach proves to be highly effective, cost-efficient, and convenient, particularly for enhancing children's foreign language abilities. Moreover, it fosters positive reading habits and independent learning skills among primary school students, contributes to the establishment of lofty aspirations, and enhances bilingual performance. Overall, this innovative mode offers an effective means of facilitating children's acquisition of bilingualism and foreign language skills, as well as promoting reading education.
To address the health needs of refugees, health services must be culturally competent and facilitate this population's access to health care, especially in a context prone to the amplification of social inequities, such as the COVID-19 pandemic. However, few quantitative studies exist in the European Union, and to the extent of our knowledge, there are no published quantitative studies exploring refugees' access to health care during the pandemic in Portugal. The objective of this study is to describe the demographic and socioeconomic characteristics of refugees living in Lisbon and to explore their healthcare access patterns during the COVID-19 pandemic. We conducted a cross-sectional, descriptive, and quantitative study from May to November 2022. Using Levesque' s theory on health care access, we designed and applied a 38-item questionnaire through face-to-face interviews with refugees living in Lisbon for at least 12 months, and used descriptive statistics to characterize sociodemographic and healthcare access profiles during the pandemic. The mean age of the 36 recruited refugees was 35 years (SD = 10.24), the majority were male (56%), married (72%), had at least a secondary education (69%), were unemployed (77.8%), and had a median length of stay in Portugal of 17 months (IQR = 45). All were registered in a primary care center, and 94% used healthcare services during the pandemic. The majority never tested positive for the coronavirus (58%) and one out of the positive was admitted to hospital due to severe COVID-19. A total of 97% received COVID-19 vaccination, of which 69% had an incomplete schedule. A quarter of the participants did not have access to information about COVID-19 in a language they understood, and although 97% needed health care during the pandemic, more than half (63%) did not seek it because of structural and cultural barriers. Half of the respondents had difficulty getting medical advice by phone or email, and 39.4% could not afford a medical examination or treatment. Only 18.2% sought counseling services. A total of 58.8% of the participants felt like healthcare professionals did not always show respect towards their culture, and 64.7% reported that healthcare professionals did not always discuss treatment options with them. This study's findings highlight the need to endow inclusive communication, cultural competency, and patient involvement in health care, alongside improving the socioeconomic condition of refugees. Identified population characteristics and barriers to health care access by refugees in this study may inform future research on the health care needs of refugees in Portugal and ultimately assist in the devising of strategies to reduce inequalities in health care access.
To advance the goal of "Grand Convergence" in global health by 2035, this study tested the convergence hypothesis in the progress of the health status of individuals from 193 countries, using both standard and cutting-edge convergence metrics. The study used multiple data sources. The methods section is categorized into two parts. (1) Health inequality measures were used for estimating inter-country inequalities. Dispersion Measure of Mortality (DMM) is used for measuring absolute inequality and Gini Coefficient for relative inequality. (2) We tested the standard convergence hypothesis for the progress in Infant Mortality Rate (IMR) and Life Expectancy at Birth (LEB) during 1950 to 2015 using methods ranging from simple graphical tools (catching-up plots) to standard parametric (absolute β and σ-convergence) and nonparametric econometric models (kernel density estimates) to detect the presence of convergence (or divergence) and convergence clubs. The findings lend support to the "rise and fall" of world health inequalities measured using Life Expectancy at Birth (LEB) and Infant Mortality Rate (IMR). The test of absolute β-convergence for the entire period and in the recent period supports the convergence hypothesis for LEB (β = -0.0210 [95% CI -0.0227 - -0.0194], p<0.000) and rejects it for IMR (β = 0.0063 [95% CI 0.0037-0.0089], p<0.000). However, results also suggest a setback in the speed of convergence in health status across the countries in recent times, 5.4% during 1950-55 to 1980-85 compared to 3% during 1985-90 to 2010-15. Although inequality based convergence metrics showed evidence of divergence replacing convergence during 1985-90 to 2000-05, from the late 2000s, divergence was replaced by re-convergence although with a slower speed of convergence. While the non-parametric test of convergence shows an emerging process of regional convergence rather than global convergence. We found that with a current rate of progress (2.2% per annum) the "Grand convergence" in global health can be achieved only by 2060 instead of 2035. We suggest that a roadmap to achieve "Grand Convergence" in global health should include more radical changes and work for increasing efficiency with equity to achieve a "Grand convergence" in health status across the countries by 2035.
To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat, Nonchalant, Engaged/Worried, and Highest Threat. These classes were associated with characteristics measured at the beginning of students' first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes.
To alleviate the contradiction in healthcare resources, the Chinese government formally established the framework of a hierarchical medical system in 2015, which contains the following brief generalities: " separate treatment of emergencies and slows, first-contact care at the primary, two-way referral, and upper and lower linkage, ". This study systematically summarizes and models the connotations of China's hierarchical medical system and a sample of 11,200 chronic disease patients in Tianjin, the largest port city in northern China, was selected for the empirical study to investigate the relationship between chronic disease patients' policy perceptions of the hierarchical medical system and their preference for healthcare. We found that under the strategy of separate treatment, improving the healthcare accessibility, drug supply, and lowering the cost of medical care would have a positive impact on increasing the preference of patients with chronic diseases to go to the primary hospitals. Under the two-way triage strategy, improving the level of physician services, referral convenience and treatment Standards have a positive impact on chronic disease patients' preference for primary care; The impact of the hierarchical medical system on the preference for healthcare differed between groups, focusing on differences in health literacy level, age and household type; The role of " upper and lower linkage " is crucial in the hierarchical medical system and it plays a part in mediating the influence of the " separate treatment of emergencies and slows" design and the "two-way referral " order on the treatment preferences of chronic disease patients. The results of the study provide a reference for the further development of a scientific and rational hierarchical medical system in the future.
To analyse and compare the assessment and grading of human-written and machine-written formative essays. Quasi-experimental, qualitative cross-sectional study. Place and Duration of the Study: Department of Science of Dental Materials, Hamdard College of Medicine & Dentistry, Hamdard University, Karachi, from February to April 2023. Ten short formative essays of final-year dental students were manually assessed and graded. These essays were then graded using ChatGPT version 3.5. The chatbot responses and prompts were recorded and matched with manually graded essays. Qualitative analysis of the chatbot responses was then performed. Four different prompts were given to the artificial intelligence (AI) driven platform of ChatGPT to grade the summative essays. These were the chatbot's initial responses without grading, the chatbot's response to grading against criteria, the chatbot's response to criteria-wise grading, and the chatbot's response to questions for the difference in grading. Based on the results, four innovative ways of using AI and machine learning (ML) have been proposed for medical educators: Automated grading, content analysis, plagiarism detection, and formative assessment. ChatGPT provided a comprehensive report with feedback on writing skills, as opposed to manual grading of essays. The chatbot's responses were fascinating and thought-provoking. AI and ML technologies can potentially supplement human grading in the assessment of essays. Medical educators need to embrace AI and ML technology to enhance the standards and quality of medical education, particularly when assessing long and short essay-type questions. Further empirical research and evaluation are needed to confirm their effectiveness. Machine learning, Artificial intelligence, Essays, ChatGPT, Formative assessment.