Yoxas/statistical_literacy huggingface dataset:
A systematic review and meta-analysis was designed in order to ascertain the effectiveness of respiratory syncytial virus (RSV) vaccination in preventing lower respiratory tract diseases (LRTD) in older adults (age ≥ 60 years). Studies reporting on randomized controlled trials (RCTs) were searched for in three databases (PubMed, Embase, and Scopus) and the preprint repository medRxiv until 31 March 2024. A total of nine studies were eventually included, two of which were conference proceedings. Our analysis included five RCTs on five RSV vaccines (RSVpreF, RSVPreF3, Ad26.RSV.preF, MEDI7510, and mRNA-1345). The meta-analysis documented a pooled vaccine efficacy of 81.38% (95% confidence interval (95% CI) 70.94 to 88.06) for prevention of LRTD with three or more signs/symptoms during the first RSV season after the delivery of the vaccine. Follow-up data were available for RSVPreF3 (2 RSV seasons), RSVpreF (mid-term estimates of second RSV season), and mRNA-1345 (12 months after the delivery of the primer), with a pooled VE of 61.15% (95% CI 45.29 to 72.40). After the first season, the overall risk for developing RSV-related LRTD was therefore substantially increased (risk ratio (RR) 4.326, 95% CI 2.415; 7.748). However, all estimates were affected by substantial heterogeneity, as suggested by the 95% CI of I2 statistics, which could be explained by inconsistencies in the design of the parent studies, particularly when dealing with case definition. In conclusion, adult RSV vaccination was quite effective in preventing LRTD in older adults, but the overall efficacy rapidly decreased in the second season after the delivery of the vaccine. Because of the heterogenous design of the parent studies, further analyses are required before tailoring specific public health interventions.
A systematic review of studies that focused on the executive functions of problem solving, planning, organising and multitasking by adults with traumatic brain injury (TBI) was performed through 2004. Qualitative and quantitative methods were used to evaluate the 15 studies that met inclusion criteria. Demographic variables, design and intervention features, and impairment and activity/participation outcomes (ICF) (World Health Organization, 2001) were documented. Five randomised control treatment (RCT) studies used step-by-step, metacognitive strategy instruction (MSI) and outcomes were evaluated in a meta-analysis. Effect sizes (ESs) from immediate impairment outcomes after MSI and "control" intervention were similar to each other, and both were significantly larger than chance. ESs from immediate activity/participation outcomes after MSI were significantly larger than the ESs from control intervention, and both were significantly larger than chance. These results, along with positive outcomes from the other group, single-subject design and single case studies, provided sufficient evidence to make the clinical recommendation that MSI should be used with young to middle-aged adults with TBI, when improvement in everyday, functional problems is the goal (Level A) (American Academy of Neurology, 2004). Although maintenance effects were generally positive, there was insufficient data quantitatively to evaluate this. Furthermore, there was insufficient evidence to make clinical recommendations for children or older adults. Intervention that trained verbal reasoning and multi-tasking was promising, although the evidence is insufficient to make clinical recommendations at this time. Additional research needs were highlighted.
A systematic review of the literature was conducted to identify course-based undergraduate research experiences (CUREs) in science, technology, engineering, and math (STEM) courses within the years 2000 through 2020. The goals of this review were to 1) create a resource of STEM CUREs identified by their discipline, subdiscipline, and level; 2) determine the activities included in each CURE, particularly the primary components listed in the CURE definition as well as specific science practices we identified as key to scientific reasoning; and 3) identify the next steps needed in CURE creation and implementation. Our review found 242 CURE curricula described in 220 total articles, with most described in biology, although STEM disciplines, including chemistry and biochemistry, have begun to publish CURE curricula as well. We also found that most CUREs include the primary components. However, when we look at the specific science practices essential to scientific reasoning, we found that these are less common in many CUREs and are implemented differently. We encourage CURE authors to consider including these science practices and potentially measuring their impact on student outcomes. The present work provides a summary of the current published CUREs, their disciplines, course levels, primary components, and specific science practices.
A systematic review was conducted to evaluate the time delays in the management of diabetic foot and explore influencing factors of these delays and potential outcomes. The researchers searched several electronic databases (Pubmed, Web of Science, Cochrane Library, EMbase, CNKI, WanFang, CBM and VIP) for English and Chinese studies that examined time delays in the management pathway of diabetic foot. Two authors independently screened and extracted data, and assessed the quality of the included studies using the Newcastle-Ottawa Scale and the Agency for Health Research and Quality checklist. Due to heterogeneity among the studies, descriptive analysis was performed. The review included 28 articles, comprising 20 cohort studies and 8 cross-sectional studies, that met the inclusion criteria. Among these, 14 were deemed of high quality. The median times from symptom onset to primary health care or specialist care varied from 3 to 46.69 days. The median delay in referral by primary care specialists ranged from 7 to 31 days, and subsequent median times to definitive treatment ranged from 6.2 to 56 days. Multiple complex factors were found to contribute to these delays, including patient demographics (older age, lower education level and income level) and poor patient health-seeking behaviors (inaccurate self-treatment, incorrect recognition and interpretation of symptoms), inaccurate assessment or initial treatment by health primary professionals, complex referral pathways and clinical characteristics of diabetic foot (number of foot ulcers, Wagner grade scale, and hemoglobin A1c index). Negative outcomes associated with these delays included increased risk of major amputation and mortality, decreased wound healing rate, prolonged hospital stay, and increased hospital costs. Time delays in the diabetic foot management pathway were both common and serious, contributing to negative health outcomes for patients with diabetic foot. Many complex factors related to patient's poor patient health-seeking behaviors, health system, and clinical characteristics of diabetic foot are responsible for these delays. Therefore, it is necessary to develop new strategies for standard referral practices and strengthen patient awareness of seeking care.
A tibial fracture is an uncommon, yet severe injury that occurs in professional athletes within all major sports leagues. These injuries are often debilitating for professional athletes and can require extensive rehabilitation prior to returning to play. The purpose of this study is to investigate the impact of a tibial fracture on athletic performance in all four major United States sports leagues. A publicly available professional sports database, Pro Sports Transactions, was queried for tibial injuries from January 01, 2015, to May 31, 2023. The search included all four major U.S. sports leagues. To quantify and compare athletic ability before and after injury, performance-based statistics were collected from standardized player ratings in periods surrounding the date of injury. The percent change in player performance was measured and stratified. The Pearson correlation test was used to analyze player demographics. There were a total of 24 professional athletes who suffered 28 confirmed tibial fractures across all leagues. Upon return, there was a 14.7% decrease in overall player performance across all leagues. National Basketball Association, National Football League, and National Hockey League athletes had a decrease of 34.5%, 29.1%, and 14.2%, respectively, following their return to play. Major League Baseball players demonstrated an 8.1% increase in player performance following their recovery from tibial fracture. Players who suffer tibial fractures often undergo immediate surgery and, in unfortunate cases, may require multiple subsequent procedures. Additionally, athletes spend several months recovering prior to their return. Upon return, athletes' performance may be decreased; however, further study is required to strengthen the association between player performance and tibial fracture recovery.
A timely diagnosis of dementia can be beneficial for providing good support, treatment, and care, but the diagnostic rate remains unknown and is probably low. To determine the dementia diagnostic rate and to describe factors associated with diagnosed dementia. This registry linkage study linked information on research-based study diagnoses of all-cause dementia and subtypes of dementias, Alzheimer's disease, and related dementias, in 1,525 participants from a cross-sectional population-based study (HUNT4 70+) to dementia registry diagnoses in both primary-care and hospital registries. Factors associated with dementia were analyzed with multiple logistic regression. Among those with research-based dementia study diagnoses in HUNT4 70+, 35.6% had a dementia registry diagnosis in the health registries. The diagnostic rate in registry diagnoses was 19.8% among home-dwellers and 66.0% among nursing home residents. Of those with a study diagnosis of Alzheimer's disease, 35.8% (95% confidence interval (CI) 32.6-39.0) had a registry diagnosis; for those with a study diagnosis of vascular dementia, the rate was 25.8% (95% CI 19.2-33.3) and for Lewy body dementias and frontotemporal dementia, the diagnosis rate was 63.0% (95% CI 48.7-75.7) and 60.0% (95% CI 43.3-75.1), respectively. Factors associated with having a registry diagnosis included dementia in the family, not being in the youngest or oldest age group, higher education, more severe cognitive decline, and greater need for help with activities of daily living. Undiagnosed dementia is common, as only one-third of those with dementia are diagnosed. Diagnoses appear to be made at a late stage of dementia.
A tradition that goes back to Sir Karl R. Popper assesses the value of a statistical test primarily by its severity: was there an honest and stringent attempt to prove the tested hypothesis wrong? For "error statisticians" such as Mayo (1996, 2018), and frequentists more generally, severity is a key virtue in hypothesis tests. Conversely, failure to incorporate severity into statistical inference, as allegedly happens in Bayesian inference, counts as a major methodological shortcoming. Our paper pursues a double goal: First, we argue that the error-statistical explication of severity has substantive drawbacks; specifically, the neglect of research context and the specificity of the predictions of the hypothesis. Second, we argue that severity matters for Bayesian inference via the value of specific, risky predictions: severity boosts the expected evidential value of a Bayesian hypothesis test. We illustrate severity-based reasoning in Bayesian statistics by means of a practical example and discuss its advantages and potential drawbacks.
A validity approach is proposed that uses processing times to collect validity evidence for the construct interpretation of test scores. The rationale of the approach is based on current research of processing times and on classical validity approaches, providing validity evidence based on relationships with other variables. Within the new approach, convergent validity evidence is obtained if a component skill, that is expected to underlie the task solution process in the target construct, positively moderates the relationship between effective speed and effective ability in the corresponding target construct. Discriminant validity evidence is provided if a component skill, that is not expected to underlie the task solution process in the target construct, does indeed not moderate the speed-ability relation in this target construct. Using data from a study that follows up the German PIAAC sample, this approach was applied to reading competence, assessed with PIAAC literacy items, and to quantitative reasoning, assessed with Number Series. As expected from theory, the effect of speed on ability in the target construct was only moderated by the respective underlying component skill, that is, word meaning activation skill as an underlying component skill of reading competence, and perceptual speed as an underlying component skill of reasoning. Accordingly, no positive interactions were found for the component skill that should not underlie the task solution process, that is, word meaning activation for reasoning and perceptual speed for reading. Furthermore, the study shows the suitability of the proposed validation approach. The use of time information in association with task results brings construct validation closer to the actual response process than widely used correlations of test scores.
A variety of deep learning-based and iterative approaches are available to predict Tracer Kinetic (TK) parameters from fully sampled or undersampled dynamic contrast-enhanced (DCE) MRI data. However, both the methods offer distinct benefits and drawbacks. To propose a hybrid algorithm (named as 'Greybox'), using both model- as well as DL-based, for solving a multi-parametric non-linear inverse problem of directly estimating TK parameters from undersampled DCE MRI data, which is invariant to undersampling rate. The proposed algorithm was inspired by plug-and-play algorithms used for solving linear inverse imaging problems. This technique was tested for its effectiveness in solving the nonlinear ill-posed inverse problem of generating 3D TK parameter maps from four-dimensional (4D; Spatial + Temporal) retrospectively undersampled k-space data. The algorithm learns a deep learning-based prior using UNET to estimate the Ktrans$\mathbf {K_{trans}}$ and Vp$\mathbf {V_{p}}$ parameters based on the Patlak pharmacokinetic model, and this trained prior was utilized to estimate the TK parameter maps using an iterative gradient-based optimization scheme. Unlike the existing DL models, this network is invariant to the undersampling rate of the input data. The proposed method was compared with the total variation-based direct reconstruction technique on brain, breast, and prostate DCE-MRI datasets for various undersampling rates using the Radial Golden Angle (RGA) scheme. For the breast dataset, an indirect estimation using the Fast Composite Splitting algorithm was utilized for comparison. Undersampling rates of 8× , 12× and 20× were used for the experiments, and the results were compared using the PSNR and SSIM as metrics. For the breast dataset of 10 patients, data from four patients were utilized for training (1032 samples), two for validation (752 samples), and the entire volume of four patients for testing. Similarly, for the prostate dataset of 18 patients, 10 patients were utilized for training (720 samples), five for validation (216 samples), and the whole volume of three patients for testing. For the brain dataset of nineteen patients, ten patients were used for training (3152 samples), five for validation (1168 samples), and the whole volume of four patients for testing. Statistical tests were also conducted to assess the significance of the improvement in performance. The experiments showed that the proposed Greybox performs significantly better than other direct reconstruction methods. The proposed algorithm improved the estimated Ktrans$\mathbf {K_{trans}}$ and Vp$\mathbf {V_{p}}$ in terms of the peak signal-to-noise ratio by up to 3 dB compared to other standard reconstruction methods. The proposed hybrid reconstruction algorithm, Greybox, can provide state-of-the-art performance in solving the nonlinear inverse problem of DCE-MRI. This is also the first of its kind to utilize convolutional neural network-based encodings as part of the plug-and-play priors to improve the performance of the reconstruction algorithm.
A wealth of data has consistently demonstrated that a diverse faculty maximizes productivity and innovation in the research enterprise and increases the persistence and success of groups that are underrepresented in STEM. While the diversity of students in graduate programs has steadily increased, faculty diversity, particularly in the biomedical sciences, continues to remain relatively flat. Several issues contribute to this mismatch between the pipeline and the professoriate including biases in search and hiring practices, lack of equity and equal opportunities for individuals from underrepresented backgrounds, and unwelcoming campus climates that lead to marginalization and isolation in academic life. A comprehensive approach that addresses these challenges is necessary for institutions of higher education to achieve their faculty diversity goals and create a climate where individuals from all groups feel welcomed and succeed. This article focuses on the first step in this approach-diversifying faculty recruitment through adopting search practices that generate an applicant pool that matches national availability, ensures equity in evaluation and hiring practices, and promotes inclusion and belonging in the hiring experience. These strategies have been recently used at the University of California, Irvine's School of Biological Sciences and while the long-term impact remains unknown, short-term outcomes in recruitment and hiring have demonstrated significant improvement over previous years.
A well-functioning anti-doping system relies on being perceived by athletes as effective, fair, and practically feasible to implement. While research has highlighted the views of Olympic athletes on anti-doping over the past decade, the experiences and perceptions of Para athletes have not been extensively explored. The purpose of this study was to examine Swedish elite Para athletes' experiences and perceptions of the policy and practice of the anti-doping system. A quantitative cross-sectional approach was used, with a web survey elaborated from a survey with Olympic athletes adjusted for Para athletes with physical, visual, and intellectual impairments. The sample consisted of 66 active Para athletes competing at national or international level (response rate 71%). Data were analyzed using descriptive statistics and differences between subgroups were examined Fisher's exact test. Thematic analysis was employed to analyze open-ended questions. Most of the respondents expressed a positive outlook on the anti-doping system, advocating for comprehensive efforts. A significant portion (35%) had not received anti-doping education, with those who did reporting increased confidence in avoiding unintentional doping. Despite their elite status, half of the respondents had not undergone doping control. Mistrust regarding the system's effectiveness and fairness was identified, with over half of the participants emphasizing the need for new technical solutions to enhance procedures specifically tailored for Para athletes. The athletes in this study advocate for a Para sports-focused approach in the anti-doping system, emphasizing equal testing opportunities, procedural adjustments for independence and privacy, and increased access to education. The findings illuminate the unique conditions faced by athletes with impairments within the anti-doping system, offering valuable insights for policymaking in the development of anti-doping strategies tailored to Para athletes and their various impairments.
A well-known complication of laparoscopic management of gynaecologic masses and cancers is the need to perform an intraoperative conversion to laparotomy. The purpose of this study was to identify novel patient risk factors for conversion from minimally invasive to open surgeries for gynaecologic oncology operations. This was a retrospective cohort study of 1356 patients ≥18 years of age who underwent surgeries for gynaecologic masses or malignancies between February 2015 and May 2020 at a single academic medical centre. Multivariable logistic regression was used to study the effects of older age, higher body mass index (BMI), higher American Society of Anaesthesiologist (ASA) physical status, and lower preoperative haemoglobin (Hb) on odds of converting from minimally invasive to open surgery. Receiver operating characteristic (ROC) curve analysis assessed the discriminatory ability of a risk prediction model for conversion. A total of 704 planned minimally invasive surgeries were included with an overall conversion rate of 6.1% (43/704). Preoperative Hb was lowest for conversion cases, compared to minimally invasive and open cases (11.6 ± 1.9 vs 12.8 ± 1.5 vs 11.8 ± 1.9 g/dL, p<.001). Patients with preoperative Hb <10 g/dL had an adjusted odds ratio (OR) of 3.94 (CI: 1.65-9.41, p=.002) for conversion while patients with BMI ≥30 kg/m2 had an adjusted OR of 2.86 (CI: 1.50-5.46, p=.001) for conversion. ROC curve analysis using predictive variables of age >50 years, BMI ≥30 kg/m2, ASA physical status >2, and preoperative haemoglobin <10 g/dL resulted in an area under the ROC curve of 0.71. Patients with 2 or more risk factors were at highest risk of requiring an intraoperative conversion (12.0%). Lower preoperative haemoglobin is a novel risk factor for conversion from minimally invasive to open gynaecologic oncology surgeries and stratifying patients based on conversion risk may be helpful for preoperative planning.