Yoxas/statistical_literacy huggingface dataset:
With the high-quality development of biotechnology-related industries in China, the demand for talents and training quality in this field have received extensive attention. Several universities in Nanjing have conducted in-depth analysis on the shortcomings of talent training that does not closely match the needs of industries and enterprises. These universities have since effectively leveraged its professional characteristics, deepened university-enterprise cooperation, and encouraged the alignment of professional development with industrial growth. Biotechnology major has always focused on nurturing individuals with "right conduct, good learning, and strong ability", and capitalized on its comparative disciplinary advantages. These universities vigorously promoted and continuously optimized the model of university-enterprise collaborative training, highlighted the integration of science, industry and education, focused on innovative education teaching methods, as well as practical engineering practice to enhance its quality. The preliminary training results show that this model has promoted students' engineering practical abilities and comprehensive qualities, garnering recognition from employers and students alike.
With the imminent industrial growth and population increase, Nigeria will continue to experience significant shifts in the quality of water, with a rise in emerging contaminants. This will increase the irregularity and complexity of the water quality information. Therefore, using the PRISMA meta-analysis approach, this review systematically identified the commonly used water quality assessment techniques in Nigeria, the drawback in the application of these techniques as well as the gaps in the area of water quality assessment and monitoring from 2003 to 2023. Recommendations were also made based on the evaluation of a new research direction; through the review of the effectiveness of advanced techniques for monitoring water quality in Nigeria. Sixty-eight published articles were chosen for the meta-analysis while the VOSviewer program was used to perform bibliographic coupling and visualization. The review revealed that the application of machine learning in water quality prediction has not been well explored in Nigeria. This is attributed to limited data availability and poor funding by the government. It was found that southwestern Nigeria has a greater amount of research on groundwater quality monitoring and evaluation than other regions. The variability was explained by variations in the underlying geology, aquifer features; variability in anthropogenic activities, and level of literacy among various geopolitical zones. Further studies should focus on the application of soft-computing and integrated biomonitoring techniques for effective prediction and monitoring of emerging contaminants for improved water quality. Effective collaboration between environmental stakeholders and government agencies is recommended for effective water resource sustainability.
With the impending threat of future COVID-19 waves, it is imperative that teaching hospitals develop, implement, and evaluate a systematic training program to render HCW elastic in delivering COVID-19 related services. We present our experience in developing, implementing, and evaluating a sustainable and scalable COVID-19 patient management training package for healthcare workers. A mixed-methods study design was used. Rapid assessment to understand the need of the trainees and identify the available resources was done followed by planning of the training module and its implementation. The program was evaluated for effectiveness and sustainability. Data analysis was done using descriptive statistics and qualitative data generated from open-ended questions in the feedback forms and the discussions were analyzed using rapid content analysis. A total of 66.8% of the doctors and 18.9% of the nurses were trained by online synchronous mode while 55.0% of the nursing officers and 47.1% of the nursing orderlies and paramedical staff were trained in onsite skill development sessions. Need assessment identified that healthcare workers were ill-prepared to use medical devices such as Bipap machines, ventilators, and oxygen delivery devices. The participants mentioned that the multidisciplinary approach and video-based demonstrations facilitated their online learning while the incremental learning approach, easy-to-understand terminology and hands-on experience facilitated their onsite skill development sessions. The COVID-19 training package developed was multidisciplinary, effective, sustainable, and scalable in a resource-limited setting. We suggest that this model can be adapted by healthcare organizations to develop and implement such training packages for their healthcare workers.
With the increasing aging population there is a need for more gerontological social work practitioners; however, such training for social workers in Canada is limited. To help address this gap, one faculty of social work developed a graduate level clinical social work practice certificate with a specialization in gerontology. In this paper we explore students' and instructors' perspectives about the curriculum, delivery, and impact of this certificate, and provide recommendations for improvement, particularly with respect to the clinical nature of the courses. Eight students and four instructors participated in the study. Strengths and opportunities for enhancement were identified for curriculum and delivery. Study findings also indicated that further curriculum development should focus on enhancing clinical skill development and providing more practice experience. Implications arising from these findings included developing clinical skills through experiential learning, interprofessional education, and service learning.
With the increasing amount of elective spine fusion patients presenting with cardiac disease and congestive heart failure, it is becoming difficult to assess when it is safe to proceed with surgery. Assessing the severity of heart failure (HF) through ejection fraction may provide insight into patients' short- and long-term risks. The purpose of this study was to assess the severity of HF on perioperative outcomes of spine fusion surgery patients. This was a retrospective cohort study of the PearlDiver database. We enrolled 670,526 patients undergoing spine fusion surgery. Thirty-day and 90-day complication rates, discharge destination, length of stay (LOS), physician reimbursement, and hospital costs. Patients undergoing elective spine fusion surgery were isolated and stratified by preoperative HF with preserved ejection fraction (P-EF) or reduced ejection fraction (R-EF) (International Classification of Diseases-9: 428.32 [chronic diastolic HF] and 428.22 [chronic systolic HF]). Means comparison tests (Chi-squared and independent samples t-tests, as appropriate) compared differences in demographics, diagnoses, comorbidities, procedural characteristics, LOS, 30-day and 90-day complication outcomes, and total hospital charges between those diagnosed with P-EF and those not R-EF. Binary logistic regression assessed the odds of complication associated with HF, controlling for levels fused (odds ratio [OR] [95% confidence interval]). Statistical significance was set at P < 0.05. Totally 670,526 elective spine fusion patients were included. Four thousand and seventy-seven were diagnosed with P-EF and 2758 R-EF. Overall, P-EF patients presented with higher rates of morbid obesity, chronic kidney disease, chronic obstructive pulmonary disease, diabetes mellitus, and hypertension (all P < 0.001). In relation to No-HF, P-EF patients had higher rates of 30-day major complications including pulmonary embolism, pneumonia, cerebrovascular accident (CVA), myocardial infarctions (MI), sepsis, and death (all P < 0.001). Furthermore, P-EF was associated significantly with increased odds of pneumonia (OR: 2.07 [1.64-2.56], P < 0.001) and sepsis (OR: 2.09 [1.62-2.66], P < 0.001). Relative to No-HF, R-EF was associated with significantly higher odds of MI (OR: 3.66 [2.34-5.47]), CVA (OR: 2.70 [1.67-4.15]), and pneumonia (OR: 1.85 [1.40-2.40]) (all P < 0.001) postoperative within 30 days. Adjusting for prior history of MI, CAD, and the presence of a pacemaker R-EF was a significant predictor of an MI 30 days postoperatively (OR: 2.2 [1.14-4.32], P = 0.021). Further adjusting for history of CABG or stent placement, R-EF was associated with higher odds of CVA (OR: 2.11 [1.09-4.19], P = 0.028) and MI (OR: 2.27 [1.20-4.43], P = 0.013). When evaluating the severity of HF before spine surgery, R-EF was associated with a higher risk of major complications, especially the occurrence of a myocardial infarction 30 days postoperatively. During preoperative risk assessment, congestive HF should be considered thoroughly when thinking of postoperative outcomes with emphasis on R-EF.
With the increasing availability of data, computing resources, and easier-to-use software libraries, machine learning (ML) is increasingly used in disease detection and prediction, including for Parkinson disease (PD). Despite the large number of studies published every year, very few ML systems have been adopted for real-world use. In particular, a lack of external validity may result in poor performance of these systems in clinical practice. Additional methodological issues in ML design and reporting can also hinder clinical adoption, even for applications that would benefit from such data-driven systems. To sample the current ML practices in PD applications, we conducted a systematic review of studies published in 2020 and 2021 that used ML models to diagnose PD or track PD progression. We conducted a systematic literature review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines in PubMed between January 2020 and April 2021, using the following exact string: "Parkinson's" AND ("ML" OR "prediction" OR "classification" OR "detection" or "artificial intelligence" OR "AI"). The search resulted in 1085 publications. After a search query and review, we found 113 publications that used ML for the classification or regression-based prediction of PD or PD-related symptoms. Only 65.5% (74/113) of studies used a holdout test set to avoid potentially inflated accuracies, and approximately half (25/46, 54%) of the studies without a holdout test set did not state this as a potential concern. Surprisingly, 38.9% (44/113) of studies did not report on how or if models were tuned, and an additional 27.4% (31/113) used ad hoc model tuning, which is generally frowned upon in ML model optimization. Only 15% (17/113) of studies performed direct comparisons of results with other models, severely limiting the interpretation of results. This review highlights the notable limitations of current ML systems and techniques that may contribute to a gap between reported performance in research and the real-life applicability of ML models aiming to detect and predict diseases such as PD.
With the increasing integration of technology into society, it is advisable that researchers explore the effects of repeated digital media exposure on our most vulnerable population-infants. Excessive screen time during infancy has been linked to delays in language, literacy, and self-regulation. This study explores the awareness of and adherence to the American Academy of Pediatrics' (AAP) recommendations related to avoiding screen time for infants younger than 2 years and the motivational factors associated with screen time exposure. A mixed methods survey design was used to gather responses from 178 mothers of infants younger than 2 years. The measures included infant screen time use and duration, maternal awareness of screen time use recommendations, and motivations related to screen time exposure. A variety of statistical procedures were used to explore associations between caregiver awareness of and adherence to AAP guidelines for screen time exposure, motivations related to screen time for infants, and the duration of infant screen time exposure. The results indicated that 62.2% (111/178) of mothers were aware of the AAP screen time recommendations, but only 46.1% (82/178) could cite them accurately, and most mothers learned of them via the internet or from a medical professional. Mothers who were aware of the guidelines allowed significantly less screen time for infants than those who were unaware (P=.03). In addition, parents who adhered to the AAP guidelines reported significantly less infant screen time per day than those who did not adhere (P<.001). Among mothers who reported not adhering to the guidelines, the greatest motivation for allowing screen time was perceived educational benefits. Less educated mothers rated an infant's relaxation as a motivational factor in allowing screen time significantly higher than more highly educated mothers (P=.048). The regression analysis indicated that none of the parental motivation factors predicted daily infant screen time. These results indicate 2 key approaches to improving adherence to screen time recommendations. First, the awareness of the AAP recommendations needs to be increased, which tends to improve adherence. Second, the myth that screen time can be educational for infants needs to be dispelled.
With the increasing number of people with chronic diseases and disabilities, the number of family members as caregivers have also been growing. Despite the attention paid to caregiving in recent years, little is known about caregiving among young people, particularly its global prevalence. The lack of information has important implications for health policy and management, resulting in the inability to form appropriate evidence-based policies and managerial decision making. This study aims to derive an estimate of the prevalence of caregiving among young people through a systematic review of the current literature. The results of this study revealed a prevalence of caregiving among younger adolescents of between 1.1% (1.06-1.14%) and 12.0% (11.02-12.98%). However, the assessment of caregiving varies across studies, and all were conducted in developed countries. These results provide information on the burden of caregiving in young people and reveal the lack of global information, calling for more research on and attention to this specific population.
With the increasing numbers of refugees from Ukraine affected by the ongoing war, there is a high risk of trauma-related stress due to low local health and mental health literacy care. Perceived good health is a human right. Earlier studies show that intervention for refugees can reduce and prevent post-migration stress and anxiety. The present explorative study aimed to investigate the feasibility and effectiveness of a short, trauma-focused group intervention (in Swedish "hälsoskola") for Ukrainian-speaking refugees (EU's mass refugee directive). This intervention was part of an ESF project aiming to get the subjects closer to the labor market in Västernorrland County, Sweden. A mixed-methods design, a participatory methodology, and an evaluation were used. Data were obtained with a short questionnaire in Ukrainian. It included a visual analogue health-rating scale, an observation, and an oral evaluation in groups. For practical and ethical reasons, there was no control group. Each group met five times for 2 h, a total of 10 h excluding pre- and post-assessment. There were eight sets of five group sessions per set, a total of 40 sessions. Brief initial and concluding breathing exercises sought to reduce stress among the participants. Baseline data were obtained from 99 participants, mostly females. Data gathered directly after the group intervention from 57 participants who had filled in both the pre- and post-questionnaires showed that (1) perceived anxiety/stress was significantly reduced (chi-2 25,53, df = 4, p < 001). (2) The participants showed significantly better perceived health as assessed on a visual analogue scale (average change from 63.16 to 71.18, p < 0.001). This result was supported by the participants' questions, which were qualitatively evaluated using thematic content analysis. Five general themes stemmed from questions raised in dialogue with the participants plus observation with the respective local expert. The participants received answers to their questions, and their perceived negative attitudes to authorities changed to more positive ones. By dialogue between the participants' needs of knowledge and direct answers by the local expert, respectively, was feasible and effective as they perceived trust and health and mental health literacy increased. Implications for primary prevention are discussed.
With the increasing popularity of the internet, a growing number of patients and their companions are actively seeking health-related information online. The aim of this study was to assess the quality and readability of online information about Alzheimer's disease (AD) in China. A total of 263 qualified AD-related web pages from different businesses, governments, and hospitals were obtained. The quality of the web pages was assessed using the DISCERN tool, and the readability of the web pages was assessed using a readability measurement website suitable for the Chinese language. The differences in readability and quality between different types of web pages were investigated, and the correlation between quality and readability was analyzed. The mean overall DISCERN score was 40.93±7.5. The government group scored significantly higher than the commercial and hospital groups. The mean readability score was 12.74±1.27, and the commercial group had the lowest readability score. There was a positive correlation between DISCERN scores and readability scores. This study presents an evaluation of the quality and readability of health information pertaining to AD in China. The findings indicate that there is a need to enhance the quality and readability of web pages about AD in China. Recommendations for improvement are proposed in light of these findings.
With the increasingly severe aging of the population, the difficult and expensive medical treatment problems are becoming more and more prominent; the salary level of domestic doctors is not high, but the cost of training doctors is high, coupled with doctors' work pressure and mental pressure; the number of candidates for medical school is decreasing year by year; medical talent is rare; and the allocation of medical staff is scarce. Health care is the basic guarantee for people's good life, and the shortage of medical staff will have many impacts on health care. Human-computer interaction (HCI) is the study of people, computers, and their interaction. HCI refers to the communication between the user and the computer system, which is the two-way information exchange of various symbols and actions between the human and the computer. The purpose of this paper is to study a healthcare system with human-computer interaction through the client, apply the system to the teaching of physiology and medicine, and analyze its effects and functions in combination with various evaluation indicators. This paper selects teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction as evaluation indicators, and constructs an evaluation model for this. And it builds the physiology and medicine teaching system framework and healthcare system, and conducts tests and statistics on the teaching system. This paper combines online questionnaires, in-app survey feedback, and field visits to collect feedback from users and administrators. The final data show that the teaching system meets the requirements in four evaluation indicators: teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction. User satisfaction with these four aspects reached 86.33%, 95.17%, 63.83%, and 81.87%, respectively. It shows that the system is more popular and can meet the needs of most users.
With the introduction of medical psychology and medical sociology as examination subjects in the medical curriculum, as enacted by the year 1970 in Germany, medical faculties established professorships and departments for these disciplines. This raised the concern of how the two separate scientific cultures of the social and behavioural sciences and of medicine, rooted in basic sciences, could reconcile their teaching and research activities in a constructive way. It turned out that the quality and the thematic affinity of new research aligning with core medical interests were important preconditions of successful integration of the new disciplines. This paper exemplifies a respective success in case of a scientific development in medical sociology. Based on a theoretical model, a longstanding, internationally collaborating research program analysing social determinants of stress-related disorders resulted in a series of innovative insights. Furthermore, the paper illustrates close links between biographical luck and structural opportunities and constraints, and it emphasizes the important role of committed inter-disciplinary scientific collaboration.
With the learning characteristics of adults, such as self-directed learning, courses that are preferred in application and practice, this research explores the Problem-Based Learning (PBL) teaching method employed in adult keyboard music learning courses. This research established a research model and investigated the correlation of learning satisfaction with influencing factors such as teaching effectiveness, self-efficacy, and teamwork and verified teaching effectiveness, self-efficacy, and teamwork relationships. Research data has been collected from the keyboard music students of the two classes of the Arts & Culture Department in Open University of Kaohsiung (OUK). Data analysis was conducted in three stages: descriptive statistics, measurement model verification, and structural equation model. The results of the study found that teaching effectiveness has a significant impact on learning satisfaction. Teamwork also has a significant positive impact on learning satisfaction. However, the self-efficacy dimension has little effect on learning satisfaction. Finally, the results of the study found that teaching effectiveness and teamwork both have significant impacts on learning satisfaction. However, the self-efficacy dimension has little effect on learning satisfaction. The student-led presentations went smoothly and the results were quite remarkable, which became a reference for the implementation of other courses for adults in the future.
With the lifestyle change, users' demand for furniture has shown a trend for personalization and diversification. The customized furniture market is growing rapidly and gradually becoming an indispensable choice for lifestyle items. The present qualitative study sought to identify the influencing factors and relationships of user demand for customized furniture. This study constructed a 4E semi-structured interview guide, which means that interviews were conducted from 4 dimensions: essential information, information extraction, user experience, and product expectation. The interview results were coded and analyzed in combination with grounded theory. Based on the identified 38 concepts and 10 categories, we obtain 4 main categories: fundamental condition, operation behaviour, sensory value and emotional value. For the factors that affect the demand of customized furniture users, customized furniture enterprises can start from 2 levels of publicity and product design to meet user demand and improve the user purchase probability.