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The authors study the complete convergence and complete moment convergence for weighted sums of m-extended negatively dependent (m-END) random variables. The results obtained in this paper extend and improve the corresponding results of Wu, Zhai and Peng [Y. F. Wu, M. Q. Zhai and J. Y. Peng, On the complete convergence for weighted sums of extended negatively dependent random variables, Journal of Mathematical Inequalities, 13 (1) (2019), 251–260] and Zarei and Jabbari [H. Zarei and H. Jabbari, Complete convergence of weighted sums under negative dependence, Statistical Papers, 52 (2011), 413–418]. [ABSTRACT FROM AUTHOR]

This article aims to introduce the inverse new XLindley distribution, a further extension of the new XLindley distribution. The article explores various properties of the proposed model, such as the quantile function, stochastic orders, entropies, fuzzy reliability, moments, and stress–strength estimation. The paper also compares different methods of estimating the parameters of the proposed model and evaluates their performance using a simulation study. Moreover, the paper demonstrates the usefulness of the proposed model by applying it to two real datasets. The article shows that the proposed model fits the data better than seven existing models based on model selection criteria, goodness-of-fit test statistics, and graphical visualizations. The paper concludes that the new model can be a valuable tool for modeling and analyzing hazard functions or survival data in various fields and contributing to probability theory and statistical inferences. [ABSTRACT FROM AUTHOR]

The paper presents a novel class (family) of statistical distributions termed Odd Transmuted Rayleigh-X (OTRX) that was created through a transform-transformer (T-X) approach. The CDF and PDF of the OTR-X family were derived. The available statistical literature studied earlier highlighted that almost all generalized distributions (in which one or more parameters were added) performed well and have better presentation of data than their counterparts with less number of parameters. This has motivated us to developed new family that is capable of producing new distributions. The research paper also presented a clear mathematical formula for several characteristics of the OTR-X family, such as the ordinary moments, moment generating, quantile, and reliability function. In order to find the estimate of the corresponding parameters of the OTR-X family, the technique of maximum likelihood is used in the study. A new sub-model Odd Transmuted Rayleigh Inversed Exponential Distribution (OTRIED) was generated from the OTR-X class and compared its performance to Transmuted Inversed Exponential Distribution (TIED), Exponential Inversed Exponential Distribution (EIED), and Inversed Exponential Distribution using two different datasets. The results have shown that the proposed distribution out performed its competitors when using two different real-world datasets. Furthermore, the proposed distribution can be practicalized to any skewed dataset. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper provides a review of statistical methods for tumor-agnostic clinical trials. In particular, the review focuses on basket trials and provides methodological insights into various Bayesian approaches. The key concept of borrowing information through Bayesian hierarchical models is emphasized, and some novel trial designs are introduced. The review is expected to provide oncology and biostatistics researchers with more exposure to powerful Bayesian methods for the design and analysis of tumor-agnostic clinical trials. Basket trials allow simultaneous evaluation of a single therapy across multiple cancer types or subtypes of the same cancer. Since the same treatment is tested across all baskets, it may be desirable to borrow information across them to improve the statistical precision and power in estimating and detecting the treatment effects in different baskets. We review recent developments in Bayesian methods for the design and analysis of basket trials, focusing on the mechanism of information borrowing. We explain the common components of these methods, such as a prior model for the treatment effects that embodies an assumption of exchangeability. We also discuss the distinct features of these methods that lead to different degrees of borrowing. Through simulation studies, we demonstrate the impact of information borrowing on the operating characteristics of these methods and discuss its broader implications for drug development. Examples of basket trials are presented in both phase I and phase II settings. [ABSTRACT FROM AUTHOR]

This paper is concerned with the asymptotic analysis of sojourn times of random fields with continuous sample paths. Under a very general framework we show that there is an interesting relationship between tail asymptotics of sojourn times and that of supremum. Moreover, we establish the uniform double-sum method to derive the tail asymptotics of sojourn times. In the literature, based on the pioneering research of S. Berman the sojourn times have been utilised to derive the tail asymptotics of supremum of Gaussian processes. In this paper we show that the opposite direction is even more fruitful, namely knowing the asymptotics of supremum of random processes and fields (in particular Gaussian) it is possible to establish the asymptotics of their sojourn times. We illustrate our findings considering i) two dimensional Gaussian random fields, ii) chi-process generated by stationary Gaussian processes and iii) stationary Gaussian queueing processes. [ABSTRACT FROM AUTHOR]

Multiclass probability estimation is the problem of estimating conditional probabilities of a data point belonging to a class given its covariate information. It has broad applications in statistical analysis and data science. Recently a class of weighted Support Vector Machines (wSVMs) has been developed to estimate class probabilities through ensemble learning for K-class problems (Wu et al., 2010; Wang et al., 2019), where K is the number of classes. The estimators are robust and achieve high accuracy for probability estimation, but their learning is implemented through pairwise coupling, which demands polynomial time in K. In this paper, we propose two new learning schemes, the baseline learning and the One-vs-All (OVA) learning, to further improve wSVMs in terms of computational efficiency and estimation accuracy. In particular, the baseline learning has optimal computational complexity in the sense that it is linear in K. Though not the most efficient in computation, the OVA is found to have the best estimation accuracy among all the procedures under comparison. The resulting estimators are distribution-free and shown to be consistent. We further conduct extensive numerical experiments to demonstrate their finite sample performance. [ABSTRACT FROM AUTHOR]

Recurrent events—outcomes that an individual can experience repeatedly over the course of follow-up—are common in epidemiologic and health services research. Studies involving recurrent events often focus on time to first occurrence or on event rates, which assume constant hazards over time. In this paper, we contextualize recurrent event parameters of interest using counterfactual theory in a causal inference framework and describe an approach for estimating a target parameter referred to as the mean cumulative count. This approach leverages inverse probability weights to control measured confounding with an existing (and underutilized) nonparametric estimator of recurrent event burden first proposed by Dong et al. in 2015. We use simulations to demonstrate the unbiased estimation of the mean cumulative count using the weighted Dong-Yasui estimator in a variety of scenarios. The weighted Dong-Yasui estimator for the mean cumulative count allows researchers to use observational data to flexibly estimate and contrast the expected number of cumulative events experienced per individual by a given time point under different exposure regimens. We provide code to ease application of this method. [ABSTRACT FROM AUTHOR]

Given a probability distribution p := {pk}k=1∞ on the positive integers, there are two natural ways to construct a random permutation in Sn or a random permutation of N from IID samples from p. One is called the p-biased construction and the other the p-shifted construction. In the first part of the paper we consider the case that the distribution p is the geometric distribution with parameter 1 - q ∈ (0, 1). In this case, the p-shifted random permutation has the Mallows distribution with parameter q. Let Pnb;Geo(1-q) and Pns;Geo(1-q) denote the biased and the shifted distributions on Sn. The expected number of inversions of a permutation under Pns;Geo(1-q) is greater than under Pnb;Geo(1-q), and under either of these distributions, a permutation tends to have many fewer inversions than it would have under the uniform distribution. For fixed n, both Pnb;Geo(1-q) and Pns;Geo(1-q) converge weakly as q → 1 to the uniform distribution on Sn. We compare the biased and the shifted distributions by studying the inversion statistic under ... and ... for various rates of convergence of qn to 1. In the second part of the paper we consider p-biased and p-shifted permutations for the case that the distribution p is itself random and distributed as a GEM(θ)-distribution. In particular, in both the GEM(θ)-biased and the GEM(θ)-shifted cases, the expected number of inversions behaves asymptotically as it does under the Geo(1 - q)-shifted distribution with θ = q / 1-q . This allows one to consider the GEM(θ)-shifted case as the random counterpart of the Geo(q)-shifted case. We also consider another p-biased distribution with random p for which the expected number of inversions behaves asymptotically as it does under the Geo(1 - q)-biased case with θ and q as above, and with θ → ∞ and q → 1 [ABSTRACT FROM AUTHOR]

Simple Summary: In the modern era, characterized by parenchymal-sparing procedures, in some cases pneumonectomy remains the only therapeutic approach to achieving oncological radicality. One of the most feared complications is undoubtedly respiratory failure and ARDS. Its cause after pneumonectomy is still unclear, and the study of risk factors is a subject of debate. In this paper, we evaluate the main risk factors for ARDS of a large cohort of patients and we classify them in four classes of growing risk in order to quantify their postoperative risk of ARDS and facilitate their global management. (1) Background: The cause of ARDS after pneumonectomy is still unclear, and the study of risk factors is a subject of debate. (2) Methods: We reviewed a large panel of pre-, peri- and postoperative data of 211 patients who underwent pneumonectomy during the period 2014–2021. Univariable and multivariable logistic regression was used to quantify the association between preoperative parameters and the risk of developing ARDS, in addition to odds ratios and their respective 95% confidence intervals. A backward stepwise selection approach was used to limit the number of variables in the final multivariable model to significant independent predictors of ARDS. A nomogram was constructed based on the results of the final multivariable model, making it possible to estimate the probability of developing ARDS. Statistical significance was defined by a two-tailed p-value < 0.05. (3) Results: Out of 211 patients (13.3%), 28 developed ARDS. In the univariate analysis, increasing age, Charlson Comorbidity Index and ASA scores, DLCO < 75% predicted, preoperative C-reactive protein (CRP), lung perfusion and duration of surgery were associated with ARDS; a significant increase in ARDS was also observed with decreasing VO2max level. Multivariable analysis confirmed the role of ASA score, DLCO < 75% predicted, preoperative C-reactive protein and lung perfusion. Using the nomogram, we classified patients into four classes with rates of ARDS ranking from 2.0% to 34.0%. (4) Conclusions: Classification in four classes of growing risk allows a correct preoperative stratification of these patients in order to quantify the postoperative risk of ARDS and facilitate their global management. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer (PCa) is the most common cancer and the second leading cause of cancer-related mortality among males in the US. Definitive radiation therapy (RT) plays an important role in curative-intent treatment for localized PCa and can be delivered with several different techniques, depending on the availability of resources and patient-specific criteria. With an analysis of the extensive National Cancer Database, this paper investigates trends in utilization, survival probability, and factors associated with overall survival of six common RT modalities utilized for the treatment of PCa patients—stratified by the three risk groups. Background: In this study, the utilization rates and survival outcomes of different radiotherapy techniques are compared in prostate cancer (PCa) patients stratified by risk group. Methods: We analyzed an extensive data set of N0, M0, non-surgical PCa patients diagnosed between 2004 and 2015 from the National Cancer Database (NCDB). Patients were grouped into six categories based on RT modality: an intensity-modulated radiation therapy (IMRT) group with brachytherapy (BT) boost, IMRT with/without IMRT boost, proton therapy, stereotactic body radiation therapy (SBRT), low-dose-rate brachytherapy (BT LDR), and high-dose-rate brachytherapy (BT HDR). Patients were also stratified by the National Comprehensive Cancer Network (NCCN) guidelines: low-risk (clinical stage T1–T2a, Gleason Score (GS) ≤ 6, and Prostate-Specific Antigen (PSA) < 10), intermediate-risk (clinical stage T2b or T2c, GS of 7, or PSA of 10–20), and high-risk (clinical stage T3–T4, or GS of 8–10, or PSA > 20). Overall survival (OS) probability was determined using a Kaplan–Meier estimator. Univariate and multivariate analyses were performed by risk group for the six treatment modalities. Results: The most utilized treatment modality for all PCa patients was IMRT (53.1%). Over the years, a steady increase in SBRT utilization was observed, whereas BT HDR usage declined. IMRT-treated patient groups exhibited relatively lower survival probability in all risk categories. A slightly better survival probability was observed for the proton therapy group. Hormonal therapy was used for a large number of patients in all risk groups. Conclusion: This study revealed that IMRT was the most common treatment modality for PCa patients. Brachytherapy, SBRT, and IMRT+BT exhibited similar survival rates, whereas proton showed slightly better overall survival across the three risk groups. However, analysis of the demographics indicates that these differences are at least in part due to selection bias. [ABSTRACT FROM AUTHOR]

Copyright of Revista de la Facultad de Medicina Humana is the property of Instituto de Investigaciones en Ciencias Biomedicas de la Universidad Ricardo Palma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to solve the arterial input function (AIF) determination in dynamic contrast-enhanced MRI (DCE-MRI), an important linear ill-posed inverse problem, using the maximum entropy technique (MET) and regularization functionals. In addition, estimating the pharmacokinetic parameters from a DCE-MR image investigations is an urgent need to obtain the precise information about the AIF–the concentration of the contrast agent on the left ventricular blood pool measured over time. For this reason, the main idea is to show how to find a unique solution of linear system of equations generally in the form of y = A x + b , named an ill-conditioned linear system of equations after discretization of the integral equations, which appear in different tomographic image restoration and reconstruction issues. Here, a new algorithm is described to estimate an appropriate probability distribution function for AIF according to the MET and regularization functionals for the contrast agent concentration when applying Bayesian estimation approach to estimate two different pharmacokinetic parameters. Moreover, by using the proposed approach when analyzing simulated and real datasets of the breast tumors according to pharmacokinetic factors, it indicates that using Bayesian inference—that infer the uncertainties of the computed solutions, and specific knowledge of the noise and errors—combined with the regularization functional of the maximum entropy problem, improved the convergence behavior and led to more consistent morphological and functional statistics and results. Finally, in comparison to the proposed exponential distribution based on MET and Newton's method, or Weibull distribution via the MET and teaching–learning-based optimization (MET/TLBO) in the previous studies, the family of Gamma and Erlang distributions estimated by the new algorithm are more appropriate and robust AIFs. [ABSTRACT FROM AUTHOR]

A central issue in assessing the airborne risk of COVID-19 infections in indoor spaces pertains to linking the viral load in infected subjects to the lung deposition probability in exposed individuals through comprehensive aerosol dynamics modelling. In this paper, we achieve this by combining aerosol processes (evaporation, dispersion, settling, lung deposition) with a novel double Poisson model to estimate the probability that at least one carrier particle containing at least one virion will be deposited in the lungs and infect a susceptible individual. Multiple emission scenarios are considered. Unlike the hitherto used single Poisson models, the double Poisson model accounts for fluctuations in the number of carrier particles deposited in the lung in addition to the fluctuations in the virion number per carrier particle. The model demonstrates that the risk of infection for 10-min indoor exposure increases from 1 to 50% as the viral load in the droplets ejected from the infected subject increases from 2 × 108 to 2 × 1010 RNA copies/mL. Being based on well-established aerosol science and statistical principles, the present approach puts airborne risk assessment methodology on a sound formalistic footing, thereby reducing avoidable epistemic uncertainties in estimating relative transmissibilities of different coronavirus variants quantified by different viral loads. [ABSTRACT FROM AUTHOR]

In this paper, a measure of extropy is obtained for concomitants of m-generalized order statistics in the Morgenstern family. The cumulative residual extropy (CREX) and negative cumulative extropy (NCEX) are presented for the rth concomitant of m-generalized order statistics. In addition, the problem of estimating the CREX and NCEX is studied utilizing the empirical method in concomitants of m-generalized order statistics. Some applications of these results are given for the concomitants of order statistics and record values. [ABSTRACT FROM AUTHOR]

This article uses the theory of probability and statistics to evaluate the thinking dynamics of college students to understand the psychological state of college students. First, the paper uses a web crawler to crawl and analyze the official micro articles. Using the method of probability statistics and the K-mean clustering method, we can understand the psychological state of college students in real time. The results of this experiment show that the current hot topics can be obtained within a certain period by using the statistical method of vocabulary display and clustering. The purpose of this paper is to propose corresponding countermeasures and approaches for the ideological and political work of college graduates. This model has a positive effect on cultivating college students’ values and ways of thinking.

Owing to probabilistic uncertainties associated with seasonal forecasts, especially over areas such as southern Africa where forecast skill is limited, non-climatologists and users of such forecasts frequently prefer them to be presented or distributed in terms of the likelihood (expressed as a probability) of certain categories occurring or thresholds being exceeded. Probabilistic forecast verification is needed to verify such forecasts. Whilst the resulting verification statistics can provide clear insights into forecast attributes, they are often difficult to understand, which might hinder forecast uptake and use. This problem can be addressed by issuing forecasts with some understandable evidence of skill, with the purpose of reflecting how similar forecasts may have performed in the past. In this paper, we present a range of different probabilistic forecast verification scores, and determine if these statistics can be readily compared to more commonly known and understood ‘ordinary’ correlations between forecasts and their associated observations – assuming that ordinary correlations are more intuitively understood and informative to seasonal forecast users. Of the range of scores considered, the relative operating characteristics (ROC) was found to be the most intrinsically similar to correlation. [ABSTRACT FROM AUTHOR]

In this paper we exemplify the types of Plithogenic Probability and respectively Plithogenic Statistics. Several applications are given. The Plithogenic Probability of an event to occur is composed from the chances that the event occurs with respect to all random variables (parameters) that determine it. Each such a variable is described by a Probability Distribution (Density) Function, which may be a classical, (T,I,F)-neutrosophic, I-neutrosophic, (T,F)-intuitionistic fuzzy, (T,N,F)-picture fuzzy, (T,N,F)-spherical fuzzy, or (other fuzzy extension) distribution function. The Plithogenic Probability is a generalization of the classical MultiVariate Probability. The analysis of the events described by the plithogenic probability is the Plithogenic Statistics. [ABSTRACT FROM AUTHOR]

In these cases getting accurate confidence intervals is of first order importance, and the methods Ignatiadis and Wager develop are likely to be useful. I want to congratulate Nikolaos Ignatiadis and Stefan Wager on a very stimulating paper on a timely and important topic. [Extracted from the article]

The use of technology in teaching and learning the topic of probability and statistics in the educational system in our country, Albania, has the potential to be encouraged in different level of classes in the educational system. Lee and Hollebrands (2011) have done better characterization of teaching probability and statistics with the help of technology, through the integration of Statistical Knowledge, Technological Statistical Knowledge, and Technological Pedagogical Statistical Knowledge. Also, we have integrated this framework with Pedagogical Knowledge as a very important factor. In this paper is given as a case study, the process of mastering the concepts of probability and statistics, with students of a lower secondary school in our country to understand the role of technology in the process of teaching and learning, realized concretely during the lessons, specifically throughout a project-based learning by demonstrating the results of the project by the students themselves. Our students recognize and analyze the data, then collect and represent it, to provide graphical presentation Thus, we focus on the potential advantages of using technology in teaching and learning the topics of probability and statistics in school mathematics during different levels of educational process in our country and beyond. [ABSTRACT FROM AUTHOR]

INTRODUCTION While tobacco Quitlines are effective in the promotion of smoking cessation, the majority of callers who wish to quit still fail to do so. The aim of this study was to determine if 12-month tobacco Quitline smoking cessation rates could be improved with re-engagement of callers whose first Quitline treatment failed to establish abstinence. METHODS In an adaptive trial, 614 adult smokers, who were active duty, retired, and family of military personnel with TRICARE insurance who called a tobacco Quitline, received a previously evaluated and efficacious four-session tobacco cessation intervention with nicotine replacement therapy (NRT). At the scheduled follow-up at 3 months, callers who had not yet achieved abstinence were offered the opportunity to re-engage. This resulted in three caller groups: 1) those who were abstinent, 2) those who were still smoking but willing to re-engage with an additional Quitline treatment; and 3) individuals who were still smoking but declined re-engagement. A propensity score-adjusted logistic regression model was generated to compare past-7-day point prevalence abstinence at 12 months post Quitline consultation. RESULTS Using a propensity score adjusted logistic regression model, comparison of the three groups resulted in higher odds of past-7-day point prevalence abstinence at follow-up at 12 months for those who were abstinent at 3 months compared to those who re-engaged (OR=9.6; 95% CI: 5.2-17.8; Bonferroni adjusted p<0.0001), and relative to those who declined re-engagement (OR=13.4; 95% CI: 6.8-26.3; Bonferroni adjusted p<0.0001). There was no statistically significant difference in smoking abstinence between smokers at 3 months who re-engaged and those who declined re-engagement (OR=1.39; 95% CI: 0.68-2.85). CONCLUSIONS Tobacco Quitlines seeking to select a single initiative by which to maximize abstinence at follow-up at 12 months may benefit from diverting additional resources from the re-engagement of callers whose initial quit attempt failed, toward changes which increase callers' probability of success within the first 3 months of treatment. TRIAL REGISTRATION This study is registered at clinicaltrials.gov (NCT02201810). [ABSTRACT FROM AUTHOR]

Copyright of Revista Técnica Energía is the property of Centro Nacional de Control de Energia CENACE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Drawing on prospective data from the National Health and Nutrition Examination Survey (NHANES), our goal was to construct and validate a 5-year survival prediction model for individuals with cognitive impairment (CI). Methods: This study entailed a prospective cohort design utilizing information from the 2011-2014 NHANES dataset, encompassing individuals aged 40 years or older, with updated mortality status as of December 31, 2019. Predictive models within the derivation and validation cohorts were assessed using logistic proportional risk regression, column-line plots, and least absolute shrinkage and selection operator (LASSO) binomial regression models. Results: The study enrolled a total of 1,439 participants (677 men, mean age 69.75 ± 6.71 years), with the derivation and validation cohorts consisting of 1,007 (538 men) and 432 (239 men) individuals, respectively. The 5-year mortality rate stood at 16.12% (n = 232). We devised a 5-item column-line graphical model incorporating age, race, stroke, cardiovascular disease (CVD), and blood urea nitrogen (BUN). The model exhibited an area under the curve (AUC) of 0.772 with satisfactory calibration. Internal validation demonstrated that the column-line graph model displayed strong discrimination, yielding an AUC of 0.733, and exhibited good calibration. Conclusion: To sum up, our study successfully developed and internally validated a 5-item nomogram integrating age, race, stroke, cardiovascular disease, and blood urea nitrogen. This nomogram exhibited robust predictive performance for 5-year mortality in individuals with CI, offering a valuable tool for prognostic evaluation and personalized care planning. [ABSTRACT FROM AUTHOR]

Pasteurised donor human milk is recommended for very low birthweight infants who do not have access to their mother's milk. Although the use of donor milk continues to increase, little is known about the donation experiences of milk bank donors. We aimed to describe and compare enablers, barriers and patterns of human milk donation and identify factors predicting donation volume in a convenience sample of approved milk bank donors in the United Kingdom and the United States. A cross‐sectional online survey was conducted from August 2022 to December 2022. Approved milk bank donors (n = 556) from three milk banks in the United States (n = 369, Mothers' Milk Bank of Florida, Mother's Milk Bank of North Texas and Northwest Mothers Milk Bank) and one milk bank in the United Kingdom (n = 187, Hearts Milk Bank) completed the survey. A substantial portion of donors in both settings reported participating in other forms of milk exchange (51% of U.S. donors vs. 39% of UK donors, p = 0.009). Top donation barriers reported in both settings were completing the serological screening and having enough space to store collected milk. Most donors started donating when their infant was 3 months old or older and reported donating mature milk. The most common source of information related to milk banking in each setting was the internet (United Kingdom–70% vs. United States ‐ 63%, p = 0.112). Variables that predicted lifetime donation volume differed between the United States and the United Kingdom, highlighting the importance of setting‐specific milk banking research. Key messages: Milk bank donors in the United Kingdom and the United States reported primarily receiving milk banking information from the internet and not their health care provider.A substantial portion of human milk bank donors in the United Kingdom and the United States participate in other forms of milk exchange, including sharing with a peer.Participating in other forms of milk exchange did not predict lower milk bank donation volumes.Barriers to donation and predictors of donation volume differed between donors in the United Kingdom and the United States, suggesting setting‐specific research is warranted to improve the donation process globally. [ABSTRACT FROM AUTHOR]

Background: A negative attitude towards abortion among health care providers providing abortion services could be an obstacle even under a law, which permits abortion on request. Healthcare providers are expected to perform and be change agents of abortion services. However, little information is known about the attitude toward safe abortion among healthcare providers in Ethiopia. Objective: This study aimed to assess health care provider's attitudes towards safe abortion care and its associated factors at the public health facilities of Bahir Dar City, Northwest Ethiopia. Methods: A health facility-based cross-sectional study was employed from March 1 to 30/2021 among 416 health-care providers. The data were collected by computer-based generated simple random sampling technique, entered, coded, and cleaned using Epi data version 4.2 and analyzed using Statistical Package of Social Sciences version 25.0. Bivariate and multivariable logistic regression analyses were employed to estimate the crude and adjusted odds ratio with a confidence interval of 95% and a P-value of less than 0.05 considered statistically significant. Results: The response rate of the study was 99.3%, and 70.2% [95% CI: 65.6–74.6] of health-care providers had a favorable attitude towards safe abortion care. Multivariable analysis indicated that health care providers who are found in the age group of 25–29, 30–34, and ≥ 35 years [AOR = 3.34, 95% CI = 1.03–10.85], [AOR = 4.58, 95% CI = 1.33- 15.83] and [AOR = 5.30, 95% CI = 1.43–19.66] respectively, male health care providers [AOR = 3.20, 95% CI = 1.55–6.60], midwives [AOR = 6.50, 95% CI = 2.40–17.44], working at hospital [AOR = 4.77, 95% CI = 1.53–14.91], ever trained on safe abortion [AOR = 5.09, 95% CI = 2.29–11.32], practicing of an abortion procedure [AOR = 2.52, 95%, CI = 1.13–5.60], knowledge of abortion [AOR = 7.35, 95% CI = 3.23–16.71], awareness on revised abortion law [AOR = 6.44, 95% CI = 3.15–13.17] and need further legalization of abortion law [AOR = 11.78, 95% CI = 5.52–24.26] were associated with a favorable attitude towards safe abortion care. Conclusions: Healthcare providers who had a favorable attitude toward safe abortion care were relatively high compared to the previous studies. Age, sex, profession, workplace, training, knowledge, and practice-related factors were associated with a favorable attitude toward safe abortion. This study indicated that, a need for intervention to help improve the attitude of healthcare providers toward safe abortion care, especially for those working in the maternity care units. [ABSTRACT FROM AUTHOR]

Background: Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030. Methods: We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030. Results: The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil's municipalities was observed, with a persistent sex differential. Conclusion: Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning. [ABSTRACT FROM AUTHOR]

(1) Background: This study aimed to determine whether standard-dose vitamin D supplementation could provide adequate levels in exclusively breastfed infants born with different cord 25(OH)D levels and to evaluate related neonatal morbidities. (2) Methods: A prospective cross-sectional study was designed in term infants. Three groups were formed based on cord 25(OH)D levels; Group1 Deficiency:25(OH)D < 12 ng/mL, Group2 Insufficiency:25(OH)D = 12–19 ng/mL, and Group3 Optimum:25(OH)D = 20–100 ng/mL. Cord and 1st month 25(OH)D levels, after receiving standard-dose vitamin D prophylaxis, neonatal outcomes and anthropometric measurements were compared. (3) Results: The study involved 86 infants. Group1 Deficiency had also significantly lower 25(OH)D levels at 1st month compared to the others (p < 0.001). There was a significant positive correlation between cord and 1st month 25(OH)D levels (r = 0.78, p < 0.001). Despite the fact that the mother's age and clothing style were similar, Group1 Deficiency mothers had higher parity numbers and used less vitamin D during pregnancy (p = 0.03, p = 0.04). Neonatal outcomes analysis revealed that newborns in Group1 Deficiency experienced more respiratory distress, transient tachypnea, and early-onset sepsis, as well as more and longer hospital stays in the first-month of life (p < 0.05). (4) Conclusions: Infants with low cord 25(OH)D levels had also lower 25(OH)D values in the 1st month of life and experienced higher rates of neonatal morbidities. Given its numerous biological activities and impact on neonatal morbidities, determining an individualized dose of vitamin D supplementation may be more accurate than using the standard approach. [ABSTRACT FROM AUTHOR]

Focusing on the global integrity monitoring performance of the BDS-3, the integrity failure model and effect analysis (IFMEA) of the system space segment and the ground control segment were carried out, and the system integrity risk tree model was established according to the IFMEA results. To evaluate the system's integrity risk probability more reasonably, this paper establishes an abnormal event prediction model with a Bayesian method, based on actual operation data, under a situation in which the BDS-3 just opened service. With statistical analysis results of system anomalies since 27 December 2018—which is the date the BDS-3 began providing basic service—according to the anomaly prediction model, the system's integrity risk probability under the 95% confidence limit was calculated to be approximately 0.9e-7/h, meeting the design index requirements of 1e-7/h. The analysis results also show that the main risk factors affecting the integrity of BDS-3 are 'pseudorange measurement anomaly' and 'miss-detection of satellite autonomous integrity monitoring'. The results are important references with practical engineering significance for improving the integrity performance of BDS-3. [ABSTRACT FROM AUTHOR]

This paper presents two data-driven virtual sensors to estimate the time-series of the probability of high-concentration occurrence of naturally occurring radioactive materials (NORMs; 238U and 222Rn) in groundwater based on the in-situ groundwater quality monitoring data and geological information. The random forest was applied to estimate the NORM concentration based on the actual in-situ groundwater quality data, rock type, and the aquifer depth. Additionally, this study proposes three data sampling techniques (i.e., under-sampling, synthetic minority over-sampling, and a complex sampling) to improve the model applicability and accuracy. The developed models were validated using the actual data acquired from 201 locations in South Korea. The models for 238U and 222Rn showed estimation accuracies of 85% and 80%, respectively; the models with over-sampling showed better performance. All the results verified the usefulness of the developed models as virtual sensors for providing immediate information on the in-situ presence of NORMs in groundwater. [Display omitted] • Naturally occurring radioactive material (NORMs) in groundwater can be problematic. • Virtual sensor for in-situ estimating the probability of high-concentration of NORMs. • Major geochemical factors for NORMs were evaluated using statistical analyses. • Methods for solving data imbalance problem in training virtual sensor were proposed. • Major factors for the estimation were consistent with the statistical analysis result. [ABSTRACT FROM AUTHOR]

The straddle monorail tourist transportation system (MTTS) has developed rapidly in recent years, and its structure is an elevated steel structure with a beam–column system, and the design is executed according to the Safety Code for Large Amusement Rides (GB 8408-2018). However, the impact coefficient value of this code is deemed partially unreasonable. Based on this, relying on the Seven Colors Yunnan Happy World project, the dynamic response test is carried out; using the finite element (FEM) software ANSYS (2021) and multibody dynamics (MBD) software SIMPACK (2021x) combined with the monorail unevenness spectra based on the measured monorail, the straddle monorail vehicle–bridge coupling vibration model is established, and mutual verification is carried out with the measured data. A continuous random variable probability model is adopted for the regularity study of impact coefficient samples, combined with probability statistics and the function fitting method to analyse the calculation results and derive the MTTS displacement impact coefficient calculation formula with beam span and driving speed as variables. The results show that the calculated values of the finite element model are in good agreement with the measured data, and the MTTS impact coefficients conform to the extreme value I-type distribution in the probability distribution law, which is inversely proportional to the span and is directly proportional to the traveling speed. Considering a multi-factor MTTS displacement impact coefficient fitting formula of high fit can better reflect the impact coefficient, monorail girder span, and train speed of the interrelationship for related research and design reference, in order to ensure safety and, at the same time, to improve the economy. [ABSTRACT FROM AUTHOR]

Video gamers can play to negate the psychological impact of stress, which may become problematic when users over-rely on the stress relief potential of gaming. This study used a repeated measures experimental design to investigate the relationships between stress, video gaming, and problematic video gaming behaviours in a convenience sample of 40 students at a UK university. The results indicated that positive affect increased and negative affect decreased, whilst a biological stress measure (instantaneous pulse rate) also decreased after a short video gaming session (t(36) = 4.82, p < 0.001, d = 0.79). The results also suggested that video gaming can act as a short-term buffer against the physiological impact of stress. Further research should focus on testing individuals who have been tested for gaming disorder, as opposed to the general population. Research could also utilise variations of the methodological framework used in this study to examine the intensity of a stress relief effect under different social situations. The study's findings in relation to published works are also discussed. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations. [ABSTRACT FROM AUTHOR]

Background: Refinements are very common in clear aligner treatments. The aim of this study is to assess whether the predictability of deep overbite correction is similar over several refinements using clear aligners (Invisalign, Align Technology, San Jose, Calif) and examine the accuracy of vertical movement and inclination change of individual teeth. Methods: This retrospective study included 20 deep bite patients (7M and 13F; 32.63 ± 11.88 years old; an initial overbite of 5.09 ± 0.98 mm), consecutively treated from September 2016 and March 2023, who completed at least two sets of aligners, including refinements. The initial, predicted, and achieved models were exported from ClinCheck or OrthoCAD (Cadent Inc, Carlstadt, NJ) and superimposed via best-fit surface-based registration using SlicerCMF (version 4.9.0; cmf.slicer.org). We also examined 15 out of 20 patients who completed treatments. The overbite correction and changes in vertical movement and inclination for individual teeth were measured. Descriptive statistics and a paired t-test or Wilcoxon signed-rank test were performed. P < 0.05 was considered statistically significant. Results: The mean accuracy of overbite correction was 37.63% after 1st set, followed by 11.19%, 6.32%, and 13.80% (2nd-4th sets), respectively. There were statistically significant differences between the predicted and achieved vertical movements and inclination changes for all teeth for the 1st and 2nd sets. For the completed cases, the mean overbite correction was 38.54% compared to the initially planned overbite correction, which is similar to one of the 1st set. Still, the vertical movements and inclination changes of all teeth present statistically significant differences between the initially planned and finally achieved movements except for maxillary lateral incisor torque. Conclusions: The most overbite correction occurs during the 1st set of aligners, and refinement treatment does not significantly improve the deep bite correction. [ABSTRACT FROM AUTHOR]

Background. Few studies have analyzed the negative outcomes of disruptive behaviors in the nurse-physician relationship in patient care and their impact on patient safety. These multicausal studies significantly relate to organizational, institutional, and professional attitudinal risk factors. Aim. Analyze healthcare professionals' perceptions of disruptive behavior and factors associated with patient safety climate in the nurse-physician relationship at the hospital level. Methods. A multicenter cross-sectional study was conducted with a sample of 370 nurses and physicians assigned to different public hospitals in the Murcia/Spain region, applying the adapted and validated Spanish version of the Nurse-Physician Relationship Scale: Impact of Disruptive Behavior on Patient Care. The analysis used proportions or means (standard deviation (SD)), univariate and multivariate linear regression models, and the chi-square test. Results. Disruptive behavior was more prevalent in the ICU (81.6%) and the emergency department (67.8%). Professionals indicate that fear of reprisals is the main barrier to the reporting system. Likewise, stress and frustration are more associated with disruptive behavior and influence the safety climate. Conclusion. Professionals indicate that disruptive behaviors can have a negative impact on clinical outcomes. Age and type of service were identified as the most relevant socio-occupational factors. Stress, frustration, and communication problems are the factors that most influence the safety climate. [ABSTRACT FROM AUTHOR]

Introduction: Teaching inhaler techniques to nursing students is crucial. Objective: This study aimed to investigate the effect of simulation-based education on patient training correct inhaler technique in nursing students. Methods: This is a single-blind, randomized controlled trial in which nursing students are randomly allocated into two groups of control (n = 41) and intervention (n = 40). The students' mean score of correct inhaler technique was measured before and one week after intervention, using checklists of inhaler techniques. Results: The mean score of control group was significantly lower than the intervention group (p <.001). The results also revealed that there was no significant difference in students' level of confidence regarding the ability to educate patients on inhaler techniques before the intervention, while all students were shown to have higher levels of confidence in this term after the intervention. Conclusions: Simulation is an effective way to train nursing students in the correct inhaler techniques. [ABSTRACT FROM AUTHOR]

Background: Stroke is caused by a disruption in blood flow to the brain. Some people die from a stroke, while others are left with disabilities that reduce their self-care, requiring assistance from others to meet their daily needs. The family becomes a crucial source of support when a patient is at home. Purpose: This study examines the correlation between family support and self-care in stroke patients. Methods: The study employed an analytic observational design with a cross-sectional approach. The samples included families and stroke patients. Samples were selected using non-probability purposive sampling, with a sample size of 75 for each group. The instruments used for data collection were the Family Support Questionnaire and the Barthel Index Questionnaire. Data was analyzed using descriptive analysis and Spearman’s rank test. Results: The characteristics of stroke patients indicate an average age of 52 years, with an average time since suffering a stroke being 4.1 months. The gender distribution among patients is nearly equal. Family caregivers, with an average age of 43 years, also show a balanced gender distribution and the majority (49.3%) are partners. Concerning the support received from family caregivers, patients commonly receive emotional support, appreciation support and instrumental support. The analysis revealed a Spearman’s correlation coefficient of p < 0.05 between family support and self-care. Conclusion: This study illustrates the importance of family support in helping improve self-care for patients with stroke undergoing outpatient care and receiving home care from family caregivers. Implications for Nursing: Discharge planning for stroke patients receiving outpatient care needs to highlight the significance of family competence in assisting with home care to enhance patient self-care. [ABSTRACT FROM AUTHOR]

Background: Previous studies have examined anesthetics to improve postoperative prognosis after knee arthroscopic surgery. However, it is currently unknown whether perioperative anesthetics can influence postoperative hospital stay. We investigated the impact of esketamine after knee arthroscopic surgery on post-operative length of stay, fever and surgical site infection. Methods: This study included 455 patients who underwent knee surgery between January2020 and August 2021at a tertiary hospital in China. Patient characteristics, preoperative laboratory values, intra-operative anesthetic data, and postoperative outcomes were collected. Univariate and multivariate logistic regression analyses with or without propensity score matching were performed to identify factors related to post-operative discharge within 3 days(PD3). Results: A total of 297 cases met our inclusion criteria. The mean age of patients was 42 ± 14 years, mean body mass index, 24.1 ± 3.5 kg/m2, 157(53%) patients were male. Meniscus-related procedures accounted for the most part of all the procedures with a percentage of 40.4%, followed by combined procedures of 35.4%. After we adjusted for demographic and intraoperative characteristics with propensity score matching, esketamine use was significantly associated with PD3 with the highest odds ratio of 2.28 (95% confidence interval (CI): 1.18–4.41, p = 0.014). Conclusion: Esketamine use was associated with PD3 in patients underwent knee arthroscopic surgery. The findings of this study will be useful to anesthesiologists in making informed decisions regarding the choice of anesthetics for knee joint diseases. Trial registration: This study was approved by the Ethics Committee (Approval No.:2023-041-01) of the Eighth Affiliated Hospital, Sun Yat-sen University and retrospectively registered. Key message: This study explored the relationship between perioperative anesthetics and postoperative discharge within 3 days(PD3) in patients underwent knee arthroscopic surgery. Esketamine use is an independent factor influencing PD3 in patients underwent knee arthroscopic surgery. [ABSTRACT FROM AUTHOR]

Introduction: Gap in knowledge and fear of infection with negative attitude towards human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) are common in different cities across Saudi Arabia. The objectives of this study were to determine knowledge and attitude regarding HIV/AIDS among general population in Hail, Northern city in Saudi Arabia. Material and methods: A cross-sectional study was conducted among general population of Hail, Northern city of Saudi Arabia. A total of 388 participants were selected through multi-stage cluster sampling from different districts of the city. A validated and structured questionnaire was used to determine the knowledge and attitude levels, and logistic regression analysis was applied to define the association of knowledge and attitude levels with sociodemographic characteristics. A p-value < 0.005 was considered statistically significant. Results: Out of 388 study participants, the majority presented inappropriate knowledge (42.5%) and negative attitude (54.4%). In univariate analysis, age group of 16-25 years and unmarried (OR: 1.93, 95% CI: 1.27-2.92%, p = 0.002; and OR: 1.90; 95% CI: 1.23-2.92%, p = 0.003, respectively) were significantly associated with inappropriate knowledge level. Age group of 16-25 years, unmarried, and female gender (OR: 2.54, 95% CI: 1.77-3.86.92%, p = 0.000; OR: 1.84, 95% CI: 1.22-2.76%, p = 0.003; and OR: 2.42; 95% CI: 1.56-3.74%, p = 0.000, respectively) were significantly associated with negative attitude towards HIV/AIDS. After adjustment of covariates, age group of 16-25 years and female gender (OR: 2.54, 95% CI: 1.25-5.14%, p = 0.009; and OR: 2.14, 95% CI: 1.56-3.30%, p = 0.001, respectively) were significantly associated with negative attitude toward HIV/AIDS. Conclusions: The present study found that general population had negative attitude toward HIV/AIDS. Extensive health education campaign should be provided to the vulnerable groups of the society for rationale control and management of HIV/AIDS. [ABSTRACT FROM AUTHOR]

Copyright of Revista de la Facultad de Medicina Humana is the property of Instituto de Investigaciones en Ciencias Biomedicas de la Universidad Ricardo Palma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aimed to analyze the different types of emotional regulation in first and second year high school students according to sex and age. Many adolescents do not meet the minimum WHO recommendations, at a critical stage in which habits that will later be maintained are established. For this reason, physical education is an important means to promote these habits and an understanding of the reasons for their participation in physical education. For this purpose, PLOC-2 was used. The Kolmogorov–Smirnov test was used to determine the characteristics of the data, the ANOVA test to explore the differences between sexes, and the Spearman test for correlations between the type of regulation and age. The results showed significant differences in several items and emotional regulation by sex and an inverse correlation between age and demotivation. There are differences between the reasons why both sexes perform physical activity, and we have determined that boys have more intrinsic regulation than girls do. [ABSTRACT FROM AUTHOR]

In the first part of this article, we discuss and generalize the complete convergence introduced by Hsu and Robbins in 1947 to the r-complete convergence introduced by Tartakovsky in 1998. We also establish its relation to the r-quick convergence first introduced by Strassen in 1967 and extensively studied by Lai. Our work is motivated by various statistical problems, mostly in sequential analysis. As we show in the second part, generalizing and studying these convergence modes is important not only in probability theory but also to solve challenging statistical problems in hypothesis testing and changepoint detection for general stochastic non-i.i.d. models. [ABSTRACT FROM AUTHOR]

Background. As part of the efforts being made to achieve universal health coverage, Ethiopia plans to introduce a social health insurance scheme for the formal sector. Although the contribution will be collected as 3% of an employee's gross salary from both the employee and employer, there is a concern that the premium may not be affordable for the majority of civil servants and that there could be limited interest in joining the scheme. As a result, the purpose of this study was to assess public servants' awareness, willingness to join, and affordability of social health insurance in Arba Minch, south Ethiopia. Methods and Materials. A cross-sectional study design was used with 713 randomly chosen public employees from Arba Minch town from January 1 to 30, 2019. The survey participants were selected based on a multistage stratified random sampling method. Descriptive statistics were used to summarize awareness and affordability of the scheme, and both bivariate and multivariable logistic regressions were used to examine factors driving the outcome variables. Variables that had a p value of less than 0.25 in bivariate analysis were changed to multivariate analysis, and a p value of less than 0.05 was cutoff point for multivariate analysis. The odds ratio and 95% CI were used to report the findings. Result. In this study, 692 people voluntarily participated, which corresponds to a response rate of 97%. As the results revealed, 347 (50.1%) respondents had never heard of SHI before, 607 (87.7%) were able to afford the 3% of gross salary per month as a scheme premium, and 254 (36.7%) were willing to join the scheme. Working sector, regularly listening for health information through mass media, and social network participation were significantly associated with awareness of the SHI scheme. Also, educational status, family size, and net income were found to be significant factors associated with the affordability of the SHI scheme. On the other hand, awareness of SHI, family size, regularly listening for health information, and participation in social networks were significantly associated with willingness to join SHI during multivariate analysis. Conclusion. Half of the participants were unaware of social health insurance, suggesting that the program is not well known. Although only one-third of respondents were willing to join and pay for the program, the majority were able to afford the proposed contribution of 3% of gross wages per month. [ABSTRACT FROM AUTHOR]

Developing new ways to estimate probabilities can be valuable for science, statistics, engineering, and other fields. By considering the information content of different output patterns, recent work invoking algorithmic information theory inspired arguments has shown that a priori probability predictions based on pattern complexities can be made in a broad class of input-output maps. These algorithmic probability predictions do not depend on a detailed knowledge of how output patterns were produced, or historical statistical data. Although quantitatively fairly accurate, a main weakness of these predictions is that they are given as an upper bound on the probability of a pattern, but many low complexity, low probability patterns occur, for which the upper bound has little predictive value. Here, we study this low complexity, low probability phenomenon by looking at example maps, namely a finite state transducer, natural time series data, RNA molecule structures, and polynomial curves. Some mechanisms causing low complexity, low probability behaviour are identified, and we argue this behaviour should be assumed as a default in the real-world algorithmic probability studies. Additionally, we examine some applications of algorithmic probability and discuss some implications of low complexity, low probability patterns for several research areas including simplicity in physics and biology, a priori probability predictions, Solomonoff induction and Occam's razor, machine learning, and password guessing. [ABSTRACT FROM AUTHOR]

(1) Background: Water drinking is essential to reduce obesity in children, but effective means for implementation remain controversial. Our study assesses students' and teachers' use of and attitudes towards drinking fountains in two urban secondary schools. (2) Methods: In a cross-sectional study, answers from students and teachers to a 28- and 19-item questionnaire, respectively, containing closed- and open-ended questions and short interviews with the schools' two principals were described and analysed using the question-specific number of responses as the denominator. (3) Results: Questionnaires of one hundred sixty-two students and ten teachers were analysed; 36.1% of students responded. Students viewed the schools' two fountains as a good idea (73.3%, n = 118), recommended them to other schools (73.1%, n = 117), and felt able to distinguish healthy from unhealthy drinks (70.5%, n = 110). In contrast, 55.7% (n = 88) reported using the fountains regularly; over a week, 39.8% (n = 47) used them less than once; 26.3% (n = 31) used them one to two times. Only about a third (26.5%, n = 43) reported consuming more water since the fountains' installation. Teachers' responses were similar to students'; principals stressed planning and costs. (4) Conclusions: A discrepancy between a good attitude towards and actual use of drinking fountains may exist; school communities may need to look for measures to overcome it. [ABSTRACT FROM AUTHOR]

Background Delirium is a common complication clinically and is associated with the poor outcomes, yet it is frequently unrecognised and readily disregarded. Although the 3-minute diagnostic interview for confusion assessment method-defined delirium (3D-CAM) has been used in a variety of care settings, a comprehensive evaluation of its accuracy in all available care settings has not been performed. Objective This study aimed to evaluate the diagnostic test accuracy of the 3D-CAM in delirium detection through a systematic review and meta-analysis. Methods We systematically searched PubMed, EMBASE, the Cochrane Library, Web of Science, CINAHL (EBSCO) and ClinicalTrials.gov published from inception to 10 July 2022. The quality assessment of the diagnostic accuracy studies-2 tool was applied to evaluate methodological quality. A bivariate random effects model was used to pool sensitivity and specificity. Results Seven studies with 1,350 participants and 2,499 assessments were included, which were carried out in general medical wards, intensive care units, internal medical wards, surgical wards, recovery rooms and post-anaesthesia care units. The prevalence of delirium ranged from 9.1% to 25%. The pooled sensitivity and specificity were 0.92 (95% confidence interval [CI] 0.87–0.95) and 0.95 (95% CI 0.92–0.97), respectively. The pooled positive likelihood ratio was 18.6 (95% CI 12.2–28.2), the negative likelihood ratio was 0.09 (95% CI 0.06–0.14) and the diagnostic odds ratio was 211 (95% CI 128–349). Moreover, the area under the curve was 0.97 (95% CI 0.95–0.98). Conclusions The 3D-CAM has good diagnostic accuracy for delirium detection in different care settings. Further analyses illustrated that it had comparable diagnostic accuracy in older adults and patients with dementia or known baseline cognitive impairment. In conclusion, the 3D-CAM is recommended for clinical delirium detection. [ABSTRACT FROM AUTHOR]

Many factors influence structural reliability in practice engineering. Some factors can be measured to obtain lots of data, but others are difficult to acquire statistical data. In view of this situation, a new structural reliability analysis method is proposed using chance theory, which is composed of probability theory and uncertainty theory and can reflect random uncertainty and cognitive uncertainty simultaneously. The performance function of a structural mechanical element is defined, and when it is a random uncertain variable, the chance distribution is established. Then the calculated method of failure measures and reliability measures for the structural mechanical element is put forward. Furthermore, considering the series system and parallel system, the performance function of the structural system is proposed, and the calculated method of failure measure is determined by theoretical proof. The results can provide a new approach to analyzing structural reliability under the uncertain circumstance of lack of statistical data. [ABSTRACT FROM AUTHOR]

Why you should read this article: • To learn the rationale for complementing or replacing a P-value with a Bayesian inference • To understand the basic concepts and compelling statistical and practical benefits of Bayesian analysis • To learn about the two Bayesian approaches increasingly advocated as alternatives or complements to commonly applied P-value statistics • To identify user-friendly software available for Bayesian analysis Background: The statistical shortcomings of null hypothesis significance testing (NHST) are well documented, yet it continues to be the default paradigm in quantitative healthcare research. This is due partly to unfamiliarity with Bayesian statistics. Aim: To highlight some of the theoretical and practical benefits of using Bayesian analysis. Discussion: A growing body of literature demonstrates that Bayesian analysis offers statistical and practical benefits that are unavailable to researchers who rely solely on NHST. Bayesian analysis uses prior information in the inference process. It tests a hypothesis and yields the probability of that hypothesis, conditional on the observed data; in contrast, NHST checks observed data – and more extreme unobserved data – against a hypothesis and yields the long-term probability of the data based on repeated hypothetical experiments. Bayesian analysis provides quantification of the evidence for the null and alternative hypothesis, whereas NHST does not provide evidence for the null hypothesis. Bayesian analysis allows for multiplicity of testing without corrections, whereas NHST multiplicity requires corrections. Finally, it allows sequential data collection with variable stopping, whereas NHST sequential designs require specialised statistical approaches. Conclusion: The Bayesian approach provides statistical, practical and ethical advantages over NHST. Implications for practice: The quantification of uncertainty provided by Bayesian analysis – particularly Bayesian parameter estimation – should better inform evidence-based clinical decision-making. Bayesian analysis provides researchers with the freedom to analyse data in real time with optimal stopping when the data is persuasive and continuing when data is weak, thereby ensuring better use of the researcher's time and resources [ABSTRACT FROM AUTHOR]

Objective. To establish and validate a nomogram to predict the overall survival (OS) and cancer-specific survival (CSS) in patients with nasopharyngeal carcinoma (NPC) receiving radiotherapy by integrating multiple independent prognostic factors. Materials and Methods. Data from 5663 patients with NPC who received definite radiotherapy between 2004 and 2018 were included and divided into training and validation cohorts. Univariate and multivariate Cox regression analyses were performed to determine the independent prognostic factors of patients with NPC after radiotherapy. Thereafter, the predictive accuracy of the nomogram model was evaluated. Results. Age, race, marital status, pathological type, tumor size, T stage, N stage, M stage, American Joint Committee on Cancer stage, and chemotherapy were independent factors affecting the prognosis of patients with NPC receiving radiotherapy. Nomograms with a concordance index of 0.726 (95% confidence interval (CI): 0.675–0.777) and 0.732 (95% CI: 0.680–0.785) were able to predict OS and CSS, respectively. The area under the curve showed excellent predictive performance. Additionally, the calibration curve indicated that the predicted survival rate was consistent with the actual survival rate, and the decision curve indicated its clinical value. The established risk stratification system was able to accurately stratify patients receiving radiotherapy for NPC into three risk subgroups with significant differences in prognosis (P < 0.05). Conclusions. The constructed nomogram had good prognostic performance and could be used as an effective tool to evaluate the prognosis of patients with NPC after radiotherapy. This nomogram could be further used to guide clinical decisions and personalized treatment plans. [ABSTRACT FROM AUTHOR]

Copyright of Acta Paulista de Enfermagem is the property of Universidade Federal de Sao Paulo, Escola Paulista de Enfermagem and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Generalizing earlier work of Delbaen & Haezendonck for given compound mixed renewal process S under a probability measure P, we characterize all those probability measures Q on the domain of P such that Q and P are progressively equivalent and S remains a compound mixed renewal process under Q with improved properties. As a consequence, we prove that any compound mixed renewal process can be converted into a compound mixed Poisson one through a change of measures. [ABSTRACT FROM AUTHOR]