Yoxas/statistical_literacy huggingface dataset:
Since fall 2020, mobile health (mHealth) apps have become an integral part of the German health care system. The belief that mHealth apps have the potential to make the health care system more efficient, close gaps in care, and improve the economic outcomes related to health is unwavering and already partially confirmed. Nevertheless, problems and barriers in the context of mHealth apps usually remain unconsidered. The focus groups and interviews conducted in this study aim to shed light on problems and barriers in the context of mHealth apps from the perspective of patients. Guided focus groups and individual interviews were conducted with patients with a disease for which an approved mHealth app was available at the time of the interviews. Participants were recruited via self-help groups. The interviews were recorded, transcribed, and subjected to a qualitative content analysis. The content analysis was based on 10 problem categories ("validity," "usability," "technology," "use and adherence," "data privacy and security," "patient-physician relationship," "knowledge and skills," "individuality," "implementation," and "costs") identified in a previously conducted scoping review. Participants were asked to fill out an additional questionnaire about their sociodemographic data and about their use of technology. A total of 38 patients were interviewed in 5 focus groups (3 onsite and 2 web-based) and 5 individual web-based interviews. The additional questionnaire was completed by 32 of the participants. Patients presented with a variety of different diseases, such as arthrosis, tinnitus, depression, or lung cancer. Overall, 16% (5/32) of the participants had already been prescribed an app. During the interviews, all 10 problem categories were discussed and considered important by patients. A myriad of problem manifestations could be identified for each category. This study shows that there are relevant problems and barriers in the context of mHealth apps from the perspective of patients, which warrant further attention. There are essentially 3 different areas of problems in the context of mHealth apps that could be addressed to improve care: quality of the respective mHealth app, its integration into health care, and the expandable digital literacy of patients.
Since its public release in November 2022, ChatGPT has gained a widespread attention and received mixed responses in the academia. Promising applications of ChatGPT in university education has been suggested; however, several concerns were raised. The aim of this descriptive study was to investigate the pros and cons of ChatGPT use in medical, dental, pharmacy, and public health education. Based on expert panel discussion and review of the existing literature, specific and concise ChatGPT prompts were constructed and the responses were generated on 25 February 2023. Out data suggested that in medical education, ChatGPT benefits included the possibility of improving personalized learning, clinical reasoning and understanding of complex medical concepts. The benefits listed in the context of dental education included improved skills through step- by-step instructions and interactive content, with instant feedback on student techniques. In pharmacy education, the advantages included possible explanations of complex subjects and the deployment of interactive tools aiding to develop skills for patient counselling. In public health education, the listed benefits included providing explanations and case scenarios, besides improved skills in data analysis and literature review. The limitations listed based on ChatGPT-generated content were common across all of the investigated healthcare disciplines and included data privacy issues, risk of generating biased and inaccurate content, and the risk of deterioration of critical thinking and communication skills among healthcare students. The ChatGPT-generated content in the context of healthcare education was deemed partially helpful by the expert panel. However, several important points regarding the pros and cons of ChatGPT use in medical, dental, pharmacy and public health education were missed by ChatGPT- generated content including: the risk of plagiarism, copyright issues, the risk of academic dishonesty, and the lack of personal and emotional interactions necessary for developing proper communication skills in healthcare education. In conclusion, despite the promising prospects of ChatGPT in healthcare education, several drawbacks should be addressed with implementation of guidelines for proper use to ensure exploiting the benefits of this innovative technology.
Since learning with high educational quality requires an advanced intervention. This study seeks to answer how many puzzles game-based training can improve knowledge and cognitive function of surgical technology students in CABG surgery and its sequence, as well as the tools and equipment used in each stage of surgery and the sequence of their preparation. This study was carried out as a quasi-experimental single-group pre-test-post-test, during which, after designing a puzzle game including various stages of surgery (from the preparation of the patient for surgical sutures and the necessary equipment to perform each stage), 18 people from third-year surgical technology students who met the inclusion criteria were entered in the study by convenience sampling method and based on the sample size determined using a similar study and they participated in the test of knowledge and cognitive function, that the validity and reliability were measured, before the intervention and 14 days after the intervention (using a puzzle game). Data were analyzed using descriptive and Wilcoxon statistical tests. After the withdrawal of 2 people, 15 person (93.80 per cent) of the students were female, the average age of students was 21.87 ± 0.71 years, and 50% (8 people) of them were 22 years old. Also, the average score of the end-of-semester exam of the heart surgery technology course was 15.19 ± 2.30 (the lowest score was 11.25, and the highest score was 18.63), and the score of 43.80% (7 people) of them were in the range of 15.01-17.70, and their average of grade point average was 17.31 ± 1.10 (the lowest grade point average is 15 and the highest grade point average is 19.36) and grade point average 75% (11 people) of students were 16-18. The average scores of knowledge(5.75 ± 1.65 vs. 2.68 ± 0.79) and cognitive performance(6.31 ± 2.57 vs. 2.00 ± 1.09) of students in the post-intervention phase were significantly higher than the pre-intervention phase (P < 0.0001). The results of the present study showed that the use of puzzle games in CABG surgery training led to a significant improvement in the knowledge and cognitive performance of surgical technology students regarding the stages of CABG surgery and its sequence, as well as the tools and equipment used in each stage of surgery and the sequence of their preparation.
Since mixed doubles have been set up in the table tennis competition of the 2020 Tokyo Olympic Games, coaches and players have paid increasing attention to mixed doubles matches. This study aims to compare and analyse male and female performance in the different contexts of table tennis mixed doubles as well as the impact of their performance on the probability of winning matches. 100 matches between the top 30 mixed doubles were selected (based on the world rankings for 2019 to 2021) as samples. According to the stroke order of a mixed doubles match, the players are divided into four groups: male versus male (Pm-m), male versus female (Pm-f), female versus male (Pf-m) and female versus female (Pf-f). Then, new methods with concepts are proposed to analyse stroke performance by four groups of players in various competition contexts of mixed doubles. (1) The stroke performance in the first four strokes was much better than that in the after four strokes (P < 0.05), and males performed better than female players in the first four strokes (P < 0.05). (2) The stroke performance of each group for winning matches was significantly better than that for losing matches (P < 0.01). (3) Players in each group performed better (P < 0.01) in the ahead and under control states than in the behind and lost control states. However, most stroke performance within the four groups was not significantly different in different states. (4) The impact of scoring rates by different groups on the winning probability of a mixed doubles match from high to low was Pm-f > Pf-f > Pm-m > Pf-m. (5) In the actual competition, the percentage of female players serving first in each game is 79.64%, and the percentage of the stroke group of female players serving to female players receiving (Pf-f) is 58.25%. This study considers several competition contexts to analyse the performance of male and female players in table tennis mixed doubles. We propose that the stroke performance of male versus female players is the most important factor affecting the results of mixed doubles matches. In addition, selecting the first server or first receiver in each game reasonably and analysing the stroke orders emphatically are also very important in mixed doubles.
Since schools increasingly use digital platforms that provide educational data in digital formats, teacher data use, and data literacy have become a focus of educational research. One main challenge is whether teachers use digital data for pedagogical purposes, such as informing their teaching. We conducted a survey study with N = 1059 teachers in upper secondary schools in Switzerland to investigate teacher digital data use and related factors such as the available technologies in schools. Descriptive analysis of the survey responses indicated that although more than half of Swiss upper-secondary teachers agreed with having data technologies at their disposal, only one-third showed a clear tendency to use these technologies, and only one-quarter felt positively confident in improving teaching in this way. An in-depth multilevel modeling showed that teachers' use of digital data could be predicted by differences between schools, teachers' positive beliefs towards digital technologies (will), self-assessed data literacy (skill), and access to data technologies (tool) as well as by general factors such as frequency of using digital devices in lessons by students. Teacher characteristics, such as age and teaching experience, were minor predictors. These results show that the provision of data technologies needs to be supplemented with efforts to strengthen teacher data literacy and use in schools.
Since the beginning of the COVID-19 pandemic, the prevalence of mental disorders in children and adolescents has increased significantly. Evidence shows that childhood mental disorders can have serious consequences on psychosocial, cognitive, and physical development. Approaches from Positive Education go further than the urgently needed prevention of mental disorders by aiming directly at promoting subjective, psychological, and social wellbeing. The present study describes the implementation of a brief program to promote wellbeing in 15 elementary schools. For this purpose, in a regular university seminar, students of teaching and educational science were instructed to give 11 "happiness lessons" for fourth graders in a team of two and in the presence of the class teacher over the course of 3 months. Quantitative data were collected from children and parents in the treatment group classes and in the parallel classes serving as the waiting control group at four measurement points (pre, post, 1- and 2-month follow-up). We assessed psychological wellbeing, negative emotions and moods, parent support and home life, perception of the school environment, and self-esteem of the children with established instruments with versions for children and their parents and the frequency of positive and negative emotions of the children in self-report only. Additionally, we applied ad hoc items on subjective perception of the project and open questions in the treatment group. Data were analyzed with EffectLiteR using multigroup structural equation models. Results showed a small significant effect for negative emotions with the children's data and a medium effect for psychological wellbeing in the perception of the parents at the 1-month follow-up. Interaction effects suggest that lower baseline levels in parent support and home life and self-esteem would increase the treatment effect for these constructs. The need for more grounded framework in positive education and the inclusion of more qualitative methods as well as suggestions to improve the program in the sense of a whole school approach are discussed.
Since the beginning of the COVID-19 pandemic, the use of telehealth was rapidly implemented without previous evidence. The ONCOTELEMD study aimed to evaluate the opinion of patients attended via telemedicine during this period and to study factors that condition patient preferences on its use. Included patients had a confirmed cancer diagnosis and were contacted by telephone between 13 March and 30 April 2020, in the Medical Oncology Service of Hospital Parc Taulí, Sabadell. A 12-question survey was presented to them between 4 February and 19 April 2021. Statistical analysis was carried out using chi-square and multivariable logistic regression tests. Six hundred forty-six patients were included; 487 responded to the survey. The median age was 68 years (27-90), 55.2% were female. Most patients had a surveillance visit (65.3%) and were diagnosed with colorectal or breast cancer (43% and 26.5%, respectively); 91.8% of patients were satisfied, and 60% would accept the use of telemedicine beyond the pandemic. Patients aged more than 50 years (OR 0.40; 95% CI, 0.19-0.81; p = 0.01) and diagnosed with breast cancer (OR 0.45; 95% CI, 0.26-0.69; p < 0.001) were less predisposed to adopt telehealth in the future. Patients agreed to be informed via telehealth of scan or lab results (62% and 84%, respectively) but not of new oral or endovenous treatments (52% and 33.5%, respectively). Additionally, 75% of patients had a medium or low-null technologic ability, and 51.3% would only use the telephone or video call to contact health professionals. However, differences were found according to age groups (p < 0.0001). In total, patients surveyed were satisfied with telemedicine and believed telehealth could have a role following the COVID-19 pandemic. Moreover, our results remark on the importance of individualizing the use of telehealth, showing relevant data on patient preferences and digital literacy.
Since the beginning of the COVID-19 pandemic, vitamin D has attracted interest due to its immunomodulatory properties. Numerous studies show a correlation between vitamin D levels and COVID-19 cases and mortality. Therefore, we conducted a meta-analysis in order to assess the relationship between vitamin D3 supplementation and COVID-19 severity. We included 13 randomized clinical trials that contained the analyzed endpoints: length of COVID-19 hospitalization, number of intensive care unit (ICU) admissions, length of stay in the ICU, number of cases requiring any supplemental oxygenation, duration of any supplemental oxygenation, number of overall mortality and number of deaths associated with COVID-19. The relative risk with 95% confidence interval (CI) and the mean difference with 95% CI were calculated to compare the effect. A random effects model was used to calculate effect sizes. Our meta-analysis showed a positive effect of vitamin D3 supplementation on ICU admission (RR = 0.73; 95% CI [0.57; 0.95], p = 0.02, I2 = 19.6%) and mortality associated with COVID-19 among patients (RR = 0.56; 95% CI [0.34; 0.91]; p = 0.02; I2 = 0%). Vitamin D3 supplementation may potentially reduce the risk of ICU admission and death associated with COVID-19.
Since the COVID-19 (coronavirus disease 2019) pandemic is a global phenomenon, many scientists and research organizations create thematic maps to visualize and understand the spatial spread of the disease and to inform mankind. Nowadays, Geographic Information Systems (GIS) and web mapping technologies enable people to create digital maps on demand. This fosters the permanent update of COVID-19 map products, even by non-cartographers, and their publication in news, media and scientific publications. With the ease and speed of map-making, many map creators seem to forget about the fundamental principles of good and easy-to-read thematic choropleth maps, which requires geo-spatial data literacy. Geo-spatial data literacy is an important skill, to be able to judge the reliability of spatial data, and to create ingenuous thematic maps. This contribution intends to make people of disciplines other than those that are map-related aware of the power of thematic maps and how one can create trustworthy thematic maps instead of misleading thematic maps which could, in a worst case,  lead to misinterpretation.
Since the COVID-19 pandemic, an increase in fentanyl-combined drugs has led to a surge in opioid overdose deaths in the United States. Higher opioid overdose mortality rates are problematic in rural communities, and there are few prevention, treatment, and recovery resources for individuals experiencing opioid use disorder. This exploratory project aimed to investigate a hands-on naloxone training for rural clinicians and staff. Rural clinicians and staff at two behavioral health centers were recruited to participate in a 30-min lecture and 30-min hands-on intranasal naloxone training using a low-fidelity mannequin. A pre-post opioid knowledge questionnaire, rubric based on the Substance Abuse and Mental Health Services Administration toolkit, and investigator-generated survey were used to evaluate opioid knowledge and response, demonstration of intranasal naloxone administration, and participants' perceptions of the training. Enrollment characteristics were summarized using descriptive statistics and paired t-tests were used to assess mean differences. Of the nine participants in the project, seven (87.5%) were female and six (75.0%) were Black. Four participants assumed a therapist role, attained a MS or MA degree, and had 5 or more years of experience working in healthcare. The total mean rubric score for all participants was 96.0 (SD = 8.8). No significant pre-post mean differences among opioid knowledge, overdose risk, and overdose response categories were found, all p > 0.05. However, post-intervention mean scores were slightly higher in all categories except overdose risk. Most participants (77.8%) responded that they felt comfortable handling an opioid situation and teaching the training to community members. Open-ended responses indicated that participants liked the demonstrations, examples used, hands-on nature of the training, and the presentation materials. A hands-on naloxone training is beneficial for training rural clinicians and staff to respond to opioid overdose. This training may be a promising solution to reduce response time between recognition of opioid symptoms and administration of the life-saving medication, naloxone. Future studies should examine the efficacy of this training in larger samples with the inclusion of rural interdisciplinary teams, trusted community leaders, and family and friends of those impacted by opioid use disorder. This innovative hands-on naloxone training is designed for rural clinicians and residents who are most likely to witness individuals experiencing opioid toxicity. The primary goal is to reduce response time between recognition of signs and symptoms and administration of the life-saving medication, Naloxone.
Since the early 1960s, the paradigm of learning automata (LA) has experienced abundant interest. Arguably, it has also served as the foundation for the phenomenon and field of reinforcement learning (RL). Over the decades, new concepts and fundamental principles have been introduced to increase the LA's speed and accuracy. These include using probability updating functions, discretizing the probability space, and using the "Pursuit" concept. Very recently, the concept of incorporating "structure" into the ordering of the LA's actions has improved both the speed and accuracy of the corresponding hierarchical machines, when the number of actions is large. This has led to the ϵ -optimal hierarchical continuous pursuit LA (HCPA). This article pioneers the inclusion of all the above-mentioned phenomena into a new single LA, leading to the novel hierarchical discretized pursuit LA (HDPA). Indeed, although the previously proposed HCPA is powerful, its speed has an impediment when any action probability is close to unity, because the updates of the components of the probability vector are correspondingly smaller when any action probability becomes closer to unity. We propose here, the novel HDPA, where we infuse the phenomenon of discretization into the action probability vector's updating functionality, and which is invoked recursively at every stage of the machine's hierarchical structure. This discretized functionality does not possess the same impediment, because discretization prohibits it. We demonstrate the HDPA's robustness and validity by formally proving the ϵ -optimality by utilizing the moderation property. We also invoke the submartingale characteristic at every level, to prove that the action probability of the optimal action converges to unity as time goes to infinity. Apart from the new machine being ϵ -optimal, the numerical results demonstrate that the number of iterations required for convergence is significantly reduced for the HDPA, when compared to the state-of-the-art HCPA scheme.
Since the Hamas attacks in Israel on 7 October 2023, the Israeli military has launched an assault in the Gaza Strip, which included over 12,000 targets struck and over 25,000 tons of incendiary munitions used by 2 November 2023. The objectives of this study include: (1) the descriptive and inferential spatial analysis of damage to critical civilian infrastructure (health, education, and water facilities) across the Gaza Strip during the first phase of the military campaign, defined as 7 October to 22 November 2023 and (2) the analysis of damage clustering around critical civilian infrastructure to explore broader questions about Israel's adherence to International Humanitarian Law (IHL). We applied multi-temporal coherent change detection on Copernicus Sentinel 1-A Synthetic Aperture Radar (SAR) imagery to detect signals indicative of damage to the built environment through 22 November 2023. Specific locations of health, education, and water facilities were delineated using open-source building footprint and cross-checked with geocoded data from OCHA, OpenStreetMap, and Humanitarian OpenStreetMap Team. We then assessed the retrieval of damage at and with close proximity to sites of health, education, and water infrastructure in addition to designated evacuation corridors and civilian protection zones. The Global Moran's I autocorrelation inference statistic was used to determine whether health, education, and water facility infrastructure damage was spatially random or clustered. During the period under investigation, in the entire Gaza Strip, 60.8% (n = 59) of health, 68.2% (n = 324) of education, and 42.1% (n = 64) of water facilities sustained infrastructure damage. Furthermore, 35.1% (n = 34) of health, 40.2% (n = 191) of education, and 36.8% (n = 56) of water facilities were functionally destroyed. Applying the Global Moran's I spatial inference statistic to facilities demonstrated a high degree of damage clustering for all three types of critical civilian infrastructure, with Z-scores indicating < 1% likelihood of cluster damage occurring by random chance. Spatial statistical analysis suggests widespread damage to critical civilian infrastructure that should have been provided protection under IHL. These findings raise serious allegations about the violation of IHL, especially in light of Israeli officials' statements explicitly inciting violence and displacement and multiple widely reported acts of collective punishment.