Yoxas/statistical_literacy huggingface dataset:
The study was designed to develop and validate the nutrition literacy assessment instrument for pregnant women in China (NLAI-P). The dimension, components and questions of NLAI-P were identified via literature review and expert consultation. A panel of experts evaluated the content validity. The construct validity was evaluated by using the exploratory factor analyses (EFA) and confirmatory factor analyses (CFA). Cronbach's α coefficient and split-half reliability were applied for examining the reliability. The NLAI-P was divided into 3 dimensions including knowledge, behavior and skill dimension. Findings showed NLAI-P possessed the satisfactory content validity (content validity index = 0.98, content validity ratio = 0.97), acceptable construct validity (χ2/df = 1.82, GFI = 0.86, AGFI = 0.84, RMSEA = 0.046) and good reliability (Cronbach's α coefficient = 0.82). The average scores of NLAI-P were 46.59 ± 9.27. With the adjustment of confounding factors, education level presented a significantly positive correlation with NLAI-P scores. In conclusion, NLAI-P were valid and reliable to inspect NL level of pregnant women in China. Poor NL was prevalent among Chinese pregnant women. Based on the education level, taking targeted propaganda and education measures would achieve the optimal effect. NLAI-P can be applied as the tool for monitoring and assessing NL of pregnant women, and facilitate the designation of targeted interventions policies.
The success of current policies and interventions on providing effective access to treatment for childhood illnesses hinges on families' decisions relating to healthcare access. In sub-Saharan Africa (SSA), there is an uneven distribution of child healthcare services. We investigated the role played by barriers to healthcare accessibility in healthcare seeking for childhood illnesses among childbearing women in SSA. Data on 223,184 children under five were extracted from Demographic and Health Surveys of 29 sub-Saharan African countries, conducted between 2010 and 2018. The outcome variable for the study was healthcare seeking for childhood illnesses. The data were analyzed using Stata version 14.2 for windows. Chi-square test of independence and a two-level multivariable multilevel modelling were carried out to generate the results. Statistical significance was pegged at p<0.05. We relied on 'Strengthening the Reporting of Observational Studies in Epidemiology' (STROBE) statement in writing the manuscript. Eighty-five percent (85.5%) of women in SSA sought healthcare for childhood illnesses, with the highest and lowest prevalence in Gabon (75.0%) and Zambia (92.6%) respectively. In terms of the barriers to healthcare access, we found that women who perceived getting money for medical care for self as a big problem [AOR = 0.81 CI = 0.78-0.83] and considered going for medical care alone as a big problem [AOR = 0.94, CI = 0.91-0.97] had lower odds of seeking healthcare for their children, compared to those who considered these as not a big problem. Other factors that predicted healthcare seeking for childhood illnesses were size of the child at birth, birth order, age, level of community literacy, community socio-economic status, place of residence, household head, and decision-maker for healthcare. The study revealed a relationship between barriers to healthcare access and healthcare seeking for childhood illnesses in sub-Saharan Africa. Other individual and community level factors also predicted healthcare seeking for childhood illnesses in sub-Saharan Africa. This suggests that interventions aimed at improving child healthcare in sub-Saharan Africa need to focus on these factors.
The success of deep-learning algorithms in analyzing complex structured and unstructured multidimensional data has caused an exponential increase in the amount of research devoted to the applications of artificial intelligence (AI) in medicine in the past decade. Public release of large language models like ChatGPT the past year has generated an unprecedented storm of excitement and rumors of machine intelligence finally reaching or even surpassing human capability in detecting meaningful signals in complex multivariate data. Such enthusiasm, however, is met with an equal degree of both skepticism and fear over the social, legal, and moral implications of such powerful technology with relatively little safeguards or regulations on its development. The question remains in medicine of how to harness the power of AI to improve patient outcomes by increasing the diagnostic accuracy and treatment precision provided by medical professionals. Military medicine, given its unique mission and resource constraints,can benefit immensely from such technology. However, reaping such benefits hinges on the ability of the rising generations of military medical professionals to understand AI algorithms and their applications. Additionally, they should strongly consider working with them as an adjunct decision-maker and view them as a colleague to access and harness relevant information as opposed to something to be feared. Ideas expressed in this commentary were formulated by a military medical student during a two-month research elective working on a multidisciplinary team of computer scientists and clinicians at the National Library of Medicine advancing the state of the art of AI in medicine. A motivation to incorporate AI in the Military Health System is provided, including examples of applications in military medicine. Rationale is then given for inclusion of AI in education starting in medical school as well as a prudent implementation of these algorithms in a clinical workflow during graduate medical education. Finally, barriers to implementation are addressed along with potential solutions. The end state is not that rising military physicians are technical experts in AI; but rather that they understand how they can leverage its rapidly evolving capabilities to prepare for a future where AI will have a significant role in clinical care. The overall goal is to develop trained clinicians that can leverage these technologies to improve the Military Health System.
The supply of health activity data by health regional governments does not have a current study of the issue. The aim of this study was to analyze and describe the indicators of hospital activity related to public health organizations (health departments in the Spanish National Health System) showing the most notable experiences in this regard. Observational study. General Internet search engines were used to find and evaluate institutional web portals (Ministry of Health, regional health governments) detailing existence, availability, accessibility and quality of information (aggregation, update, format, gender and age vision) of hospital management activity offered between 2015-2019. Descriptive statistics were used with estimation of inter-observer concordance. Generation of a list of 22 web portals for public health services. All the institutions evaluated had information on hospital activity. It is complex to find, freely available, disaggregated (14), updated (2018), in PDF format (15), gender vision: 2 (Catalonia and Madrid). No. of indicators per region: between 10 and 99 (average=54). Kappa agreement index (κ)=0.84. Notable contributions: Catalonia and Madrid, with other practices to highlight (Castilla y León, Murcia). The analysis of the management information offered by health regional governments shows a generic pattern of information that is difficult to access, disaggregated and updated at least two years from the time of the study, with a wide range of indicators, reduced contribution of the gender vision and in PDF format, which makes research and teaching difficult.
The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the existing algorithms, the SDO optimizer necessitates some enhancement to satisfy the required OPF characteristics integrating hybrid wind and solar powers. Thus, a SDO variant namely leader supply-demand-based optimization (LSDO) is proposed in this research. The LSDO is suggested to improve the exploration based on the simultaneous crossover and mutation mechanisms and thereby reduce the probability of trapping in local optima. The LSDO effectiveness has been first tested on 23 benchmark functions and has been assessed through a comparison with well-regarded state-of-the-art competitors. Afterward, Three well-known constrained IEEE 30, 57, and 118-bus test systems incorporating both wind and solar power sources were investigated in order to authenticate the performance of the LSDO considering a constraint handling technique called superiority of feasible solutions (SF). The statistical outcomes reveal that the LSDO offers promising competitive results not only for its first version but also for the other competitors.
The Support and Aid to Families Electronically (SAFE) pilot program was developed through a community-university partnership to support parents of elementary students in Ontario, while providing stable practicums for social work students in the midst of COVID-19 restrictions. Purpose: The aim of the current study was to examine the feasibility of the SAFE pilot program as a mental health support to families by examining three feasibility objectives: demand, acceptably, and implementation. Method: Qualitative data from interviews, focus groups, and qualitative surveys involving service users, social work students, referring school board and university professionals (n = 37) were examined. Results: Demand for SAFE extended beyond the pandemic. A high-level of acceptance of SAFE was identified. Areas of success and considerations for implementation are outlined. Discussion: This study provides practice guidance on implementing this unique program, with potential to address gaps in service provision and the ongoing crisis in field education.
The Supreme Court decision Dobbs v Jackson Women's Health Organization (Dobbs) overturned federal protections to abortion care and altered the reproductive health care landscape. Thus far, aggregated state-level data reveal increases in the number of abortions in states where abortion is still legal, but there is limited information on delays to care and changes in the characteristics of people accessing abortion in these states after Dobbs. To examine changes in abortion provision and delays to care after Dobbs. Retrospective cohort study of all abortions performed at an independent, high-volume reproductive health care clinic network in Washington state from January 1, 2017, to July 31, 2023. Using an interrupted time series, the study assessed changes in abortion care after Dobbs. Abortion care obtained after (June 24, 2022, to July 31, 2023) vs before (January 1, 2017, to June 23, 2022) Dobbs. Primary outcomes included weekly number of abortions and out-of-state patients and weekly average of gestational duration (days) and time to appointment (days). Among the 18 379 abortions during the study period, most were procedural (13 192 abortions [72%]) and funded by public insurance (11 412 abortions [62%]). The mean (SD) age of individuals receiving abortion care was 28.5 (6.44) years. Following Dobbs, the number of procedural abortions per week increased by 6.35 (95% CI, 2.83-9.86), but then trended back toward pre-Dobbs levels. The number of out-of-state patients per week increased by 2 (95% CI, 1.1-3.6) and trends remained stable. The average gestational duration per week increased by 6.9 (95% CI, 3.6-10.2) days following Dobbs, primarily due to increased gestations of procedural abortions. The average gestational duration among out-of-state patients did not change following Dobbs, but it did increase by 6 days for in-state patients (5.9; 95% CI, 3.2-8.6 days). There were no significant changes in time to appointment. These findings provide a detailed picture of changes in abortion provision and delays to care after Dobbs in a state bordering a total ban state. In this study, more people traveled from out of state to receive care and in-state patients sought care a week later in gestation. These findings can inform interventions and policies to improve access for all seeking abortion care.
The surge in digital media consumption, coupled with the ensuing consequences of digital addiction, has witnessed a rapid increase, particularly after the initiation of the COVID-19 pandemic. Despite some studies exploring specific technological addictions, such as internet or social media addiction, in Bangladesh, there is a noticeable gap in research focusing on digital addiction in a broader context. Thus, this study aims to investigate digital addiction among students taking the university entrance test, examining its prevalence, contributing factors, and geographical distribution using GIS techniques. Data from a cross-sectional survey were collected from a total of 2,157 students who were taking the university entrance test at Jahangirnagar University, Bangladesh. A convenience sampling method was applied for data collection using a structured questionnaire. Statistical analyses were performed with SPSS 25 Version and AMOS 23 Version, whereas ArcGIS 10.8 Version was used for the geographical distribution of digital addiction. The prevalence of digital addiction was 33.1% (mean score: 16.05 ± 5.58). Those students who are attempting the test for a second time were more likely to be addicted (42.7% vs. 39.1%), but the difference was not statistically significant. Besides, the potential factors predicted for digital addiction were student status, satisfaction with previous mock tests, average monthly expenditure during the admission test preparation, and depression. No significant difference was found between digital addiction and districts. However, digital addiction was higher in the districts of Manikganj, Rajbari, Shariatpur, and Chittagong Hill Tract areas, including Rangamati, and Bandarban. The study emphasizes the pressing need for collaborative efforts involving educational policymakers, institutions, and parents to address the growing digital addiction among university-bound students. The recommendations focus on promoting alternative activities, enhancing digital literacy, and imposing restrictions on digital device use, which are crucial steps toward fostering a healthier digital environment and balanced relationship with technology for students.
The surge of globalisation and the recognition of English as a lingua franca have propelled the worldwide advancement of English as a foreign language (EFL) education. Formative assessment can support the English language teaching and learning in classroom settings. This systematic review critically analyses recent research on formative assessment within K-12 EFL education, underscoring its substantial role in enhancing teaching efficacy and student outcomes. Specifically, it addresses three key aspects: the beliefs, perceptions and literacy of teachers and students regarding formative assessment, the effectiveness of different assessment practices on learners' performance and the contextual challenges in implementing these strategies. A comprehensive analysis of qualitative and quantitative studies reveals that the attitudes of teachers and students considerably influence the effectiveness of formative assessment. Innovative methods, such as technology-assisted and peer assessments, show promise in enhancing learner outcomes. However, the education system and cultural contexts present persistent challenges in implementing formative assessment in EFL classes. The findings highlight the importance of ensuring professional training for educators and raising student awareness regarding the benefits of formative assessment. This study emphasises the need for aligning adaptable assessment practices with diverse educational environments and calls for a closer integration of theoretical and practical approaches in EFL education. Moreover, this review provides valuable insights into formative assessment strategies in EFL learning, offering guidance for educators, policymakers and stakeholders in language education.
The survival rate among preterm infants has improved, and hospital stays have been prolonged, consistent with positive developments in perinatal and neonatal care. The aim of this study was to provide evidence-based information for healthcare professionals concerning the ideal time for discharge by evaluating the reasons for prolonged hospital stays. Six hundred eighty-one premature babies born at 24-35 weeks at the Mersin University Medical Faculty Hospital between January 2016 and May 2020 and admitted to the neonatal intensive care unit were included in the study following a retrospective file examination. Date of birth (gestational age) and discharge week (duration of hospital stay) calculated from the date of final discharge were recorded. Based on the literature, the ideal discharge time was determined to be 40 weeks according to postmenstrual age (week of birth + length of hospital stay). The primary variable was whether the infants were discharged before the ideal discharge week. The secondary variable was the effect of the presence of comorbidity on the length of hospital stay and ideal discharge time. The mean hospital stay of preterm neonate born at 250-7-260-7, 270-7-280-7 and 290-7-300-7 weeks was significantly shorter in the absence of comorbidity than in the presence of comorbidity (p = 0.001, 0.004, and 0.008, respectively). More than half (53.5%) were discharged before the expected date of birth as gestational weeks increased, despite the prolonged length of stay in the presence of comorbidity. Health professionals can inform families that, in the absence of comorbidity, discharge is possible at an average of 36 weeks for 250-7-280-7-week gestational ages, and at an average of 34 weeks for 290-7-320-7-week gestational ages.
The swallowability of solid oral dosage forms (SODFs) is crucial for medication safety and adherence. Both regulatory agencies and sponsors are concerned with bringing swallowable SODFs to patients. However, no best practices are available for assessing swallowability. Therefore, we conducted a comparative analysis of clinical swallowability assessments (CSAs) for SODFs in regulatory submissions to identify current study design practices. CSAs were identified from a "swallowability" keyword search of a Food and Drug Administration database. Notable design trends among the 17 CSAs were not assessing swallowability as a primary endpoint (76 %); enrolling pediatric patients (76 %); administering assessments post-screening (76 %); and utilizing questionnaires (100 %). A design trend with near equal frequency(∼50 %) was single- or multiple-doses of product administration. Study subjects were the primary questionnaire respondents (82 %), usually using a Likert scale (92 %, 12/13). CSAs generally dichotomized the responses for analysis (65 %) without pre-specified threshold values (59 %). Overall, while study designs exhibited trends, methodology variations may impact swallowability measurements affecting the interpretation of results. Thus, developing robust and valid assessment tools for swallowability is imperative to produce clinically relevant data and inform regulatory decision-making. Collaboration between regulatory agencies and sponsors is warranted to create best practices and ensure high quality swallowability data.
The SWOT (strengths, weaknesses, opportunities, and threats) analysis is a framework used to evaluate a company's competitive position and to develop strategic planning. In the competitive dental sector, it can aid dentists in identifying and analyzing internal strengths and weaknesses, as well as external opportunities and threats. This study focuses on senior dental students of the Department of Dentistry at the National and Kapodistrian University of Athens, Greece, aiming to scrutinize their use of SWOT analysis and assess its application as a tool for evaluating entrepreneurial goals and making career decisions in dental entrepreneurship. The research sample comprises 116 senior dental students (N1) in the final undergraduate year of their dental education, with data collection accomplished through the administration of an e-questionnaire during the obligatory course of "Organization and management of dental practices" in December 2023. The data extracted from the SWOT analysis encompass internal and external factors, gender distinctions, and outcomes derived from Stepwise Binary Logistic Regression concerning predictor markers. The results from the SWOT analysis of 114 valid questionnaires (N2), revealed that participants identified communication skills (50%) and organization skills (49.10%) as their primary strengths, followed by favorable personal traits contributing to goal success (36%). Weaknesses predominantly centered around emotional and personal traits like anxiety (41.20%) and other characteristics, alongside practical challenges such as lack of initial capital (24.60%). Main opportunities included collaboration with experienced dentists (33.30%) and access to training programs (27.20%), while economic instability in Greece (77.20%) and the saturated dentist profession (26.30%) were perceived as significant threats. Gender differences were notable, with female dentists more likely to report organization skills as a strength and anxiety as a weakness. Values such as industriousness, persistence, and ethics were commonly shared, with actions focusing on training programs (57.9%) and gaining experience with experienced dentists (29.8%). Cluster analysis identified two subgroups, with one emphasizing utilizing all available options (n = 49) and the other prioritizing on gaining professional skills and experience (n = 65). Logistic regression indicated that participants valuing industriousness were less likely to explore all available options, while those recognizing personal traits were more likely to do so. The study's outcomes highlight key predictor factors linked to a proactive orientation in career decision-making among senior dental students. These insights offer valuable implications for educational institutions and career counselors.