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Null hypothesis significance testing (NHST) is the default approach to statistical analysis and reporting in marketing and the biomedical and social sciences more broadly. Despite its default role, NHST has long been criticized by both statisticians and applied researchers, including those within marketing. Therefore, the authors propose a major transition in statistical analysis and reporting. Specifically, they propose moving beyond binary: abandoning NHST as the default approach to statistical analysis and reporting. To facilitate this, they briefly review some of the principal problems associated with NHST. They next discuss some principles that they believe should underlie statistical analysis and reporting. They then use these principles to motivate some guidelines for statistical analysis and reporting. They next provide some examples that illustrate statistical analysis and reporting that adheres to their principles and guidelines. They conclude with a brief discussion. [ABSTRACT FROM AUTHOR]

Acute ketone monoester (KE) supplementation can alter exercise responses, but the performance effect is unclear. The limited and equivocal data to date are likely related to factors including the KE dose, test conditions, and caliber of athletes studied. We tested the hypothesis that mean power output during a 20-min cycling time trial (TT) would be different after KE ingestion compared to a placebo (PL). A sample size of 22 was estimated to provide 80% power to detect an effect size dz of 0.63 at an alpha level of.05 with a two-tailed paired t test. This determination considered 2.0% as the minimal important difference in performance. Twenty-three trained cyclists (N = 23; peak oxygen uptake: 65 ± 12 ml·kg−1 min−1; M ± SD), who were regularly cycling >5 hr/week, completed a familiarization trial followed by two experimental trials. Participants self-selected and replicated their diet and exercise for ∼24 hr before each trial. Participants ingested either 0.35 g/kg body mass of (R)-3-hydroxybutyl (R)-3-hydroxybutyrate KE or a flavor-matched PL 30 min before exercise in a randomized, triple-blind, crossover manner. Exercise involved a 15-min warm-up followed by the 20-min TT on a cycle ergometer. The only feedback provided was time elapsed. Preexercise venous [β-hydroxybutyrate] was higher after KE versus PL (2.0 ± 0.6 vs. 0.2 ± 0.1 mM, p <.0001). Mean TT power output was 2.4% (0.6% to 4.1%; mean [95% confidence interval]) lower after KE versus PL (255 ± 54 vs. 261 ± 54 W, p <.01; dz = 0.60). The mechanistic basis for the impaired TT performance after KE ingestion under the present study conditions remains to be determined. [ABSTRACT FROM AUTHOR]

A major problem in employee selection coalesces around convincing decision‐makers (e.g., hiring managers) to use analytically derived models. Existing recommendations in the literature largely focus on convincing executives to adopt analytical models and then exert their top‐down influence on lower‐level hiring decisions. In contrast to these solutions, we explore end user modifiability (i.e., allowing decision‐makers to modify a statistical model before use) as a bottom‐up approach for increasing hiring managers' implementation of analytical recommendations. From a utility standpoint, we consider how incorporating end user modifiability into hiring decisions will result in a less statistically valid, but potentially more valuable, organizational selection process. We explore these ideas in two studies. In Study 1, we experimentally test whether model modification increases decision‐maker reliance on a statistical model, as well as how much decision‐makers need to modify a model in order to use it. In Study 2, we examine the extent that modifiability introduces implicit biases that might adversely affect marginalized groups. Results suggest that modifiability can increase decision‐makers' perceived usefulness of a model and, importantly, that only a small amount of modifiability is needed to elicit this effect. Further, end user modifications were statistically insignificant predictors of hiring rates across race‐based subgroups, though supplementary analyses suggest important cautionary nuance. Given that analytical models are rarely perfectly or wholly implemented, end user modifiability may offer a viable solution for organizations seeking to increase the implementation of algorithmic guidance in selection decisions, even if it deviates modestly from a statistical optimality. [ABSTRACT FROM AUTHOR]

Background: Creating activity-friendly communities (AFCs) is an important strategy to increase physical activity (PA). While cross-sectional links between community environments and PA are well documented, their causal relationships remain insufficiently explored. Methods: Using the accelerometer and survey data collected from adults who moved to an AFC (cases) and similar non-AFC-residing adults who did not move (comparisons), this pre–post, case-comparison study examines if moving to an AFC increases PA. Data came from 115 participants (cases = 37, comparisons = 78) from Austin, Texas, who completed 2 waves of 1-weeklong data collection. Difference-in-difference analyses and fixed-effect models were used to test the significance of the pre–post differences in moderate-to-vigorous PA (MVPA) between cases and comparisons, for the full sample and the subsample of 37 pairs matched in key covariates using the Propensity Score Matching method. Results: Average treatment effect generated based on Propensity Score Matching and difference-in-difference showed that moving to this AFC led to an average of 10.88 additional minutes of daily MVPA (76.16 weekly minutes, P =.015). Fixed-effect models echoed the result with an increase of 10.39 minutes of daily MVPA after moving to the AFC. We also found that case participants who were less active at baseline and had higher income increased their MVPA more than their counterparts. Conclusions: This study showed that, among our study sample, moving to an AFC increased residents' PA significantly when compared to their premove level and the comparison group. This causal evidence suggests the potential of AFCs as sustainable interventions for PA promotion. [ABSTRACT FROM AUTHOR]

We study a nonparametric test procedure based on order statistics for testing the null hypothesis of equality of two continuous distributions. The exact null distribution of the proposed test statistic is obtained using an enumeration method and a novel combinatorial argument. A recurrence relation for the probability generating function and a sequential approach for computing the mean and variance of the distribution are given. Critical values and characteristics of the distribution for selected small sample sizes are presented. For the Lehmann alternative family, the exact power function of the new test is derived, and its power performance is examined. We also study the power performance of the proposed test under the location-shift and scale-shift alternatives using Monte Carlo simulations and observe its superior performance when compared to commonly used nonparametric tests under various scenarios. A generalization of the proposed procedure for unequal sample sizes is discussed. An illustrative example and some concluding remarks are provided. [ABSTRACT FROM AUTHOR]

Many segmentation or change‐point detection methods for homogenizing climate time series compare candidate station data with reference data to eliminate common climate signals and more efficiently detect spurious, non‐climatic changes. One drawback is that it is difficult to decide whether the detected change‐point is due to the candidate series or to the reference. A so‐called attribution procedure is typically applied in a post‐processing step for each detected change‐point. This article describes a new statistical method for the attribution of change‐points detected in Global Navigation Satellite System (GNSS) minus reanalysis series of integrated water vapour. It requires at least one nearby station with similar GNSS and reanalysis data. Six series of differences are formed from the four base series (BS) and are tested for a significant jump at the time of the change‐point detected in the candidate station. The six test results are analysed with a statistical predictive rule to attribute the change‐point to one, or several, of the four BS. Original aspects of our method are: (1) the significance test, which is based on a generalized linear regression approach, taking both heteroscedasticity and autocorrelation into account; (2) the predictive rule, which uses a machine learning method and is constructed from the test results obtained with the real data by using a resampling strategy. Four popular machine learning methods have been compared using cross‐validation and the best one was applied to a real data set (49 main stations with 114 change‐points). The results depend on the choice of the test significance level and the aggregation method combining the prediction results when several nearby stations are available. We find that 62% of the change‐points are attributed to GNSS, 19% to the reanalysis, and 10% are due to coincident detections. [ABSTRACT FROM AUTHOR]

The cognitive advantage (CA) hypothesis claims that multilingualism promotes the development of several basic cognitive capacities. A large number of empirical findings support this hypothesis, but recently there have also been numerous contradictory findings and methodological objections. The present paper extends the investigation of possible cognitive advantages from basic cognitive (executive) functions to broader cognitive competencies such as cognitive flexibility. A promising candidate for this is 'flexibility of goal adjustment' (FGA), a capacity of developmental regulation that solves problems through flexible adaptation processes. In a study with N = 119 monolingual and multilingual adults we found the predicted positive correlation between multilingualism and FGA. However, the mediator function of executive capacities entailed in the CA hypothesis operationalised as Stroop and flanker tasks could not be demonstrated. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing (HF) is commonly used to enhance onshore recovery of oil and gas during production. This process involves the use of a variety of chemicals to support the physical extraction of oil and gas, maintain appropriate conditions downhole (e.g., redox conditions, pH), and limit microbial growth. The diversity of chemicals used in HF presents a significant challenge for risk assessment. The objective of the present study is to establish a transparent, reproducible procedure for estimating 5th percentile acute aquatic hazard concentrations (e.g., acute hazard concentration 5th percentiles [HC5s]) for these substances and validating against existing toxicity data. A simplified, grouped target site model (gTSM) was developed using a database (n = 1696) of diverse compounds with known mode of action (MoA) information. Statistical significance testing was employed to reduce model complexity by combining 11 discrete MoAs into three general hazard groups. The new model was trained and validated using an 80:20 allocation of the experimental database. The gTSM predicts toxicity using a combination of target site water partition coefficients and hazard group‐based critical target site concentrations. Model performance was comparable to the original TSM using 40% fewer parameters. Model predictions were judged to be sufficiently reliable and the gTSM was further used to prioritize a subset of reported Permian Basin HF substances for risk evaluation. The gTSM was applied to predict hazard groups, species acute toxicity, and acute HC5s for 186 organic compounds (neutral and ionic). Toxicity predictions and acute HC5 estimates were validated against measured acute toxicity data compiled for HF substances. This case study supports the gTSM as an efficient, cost‐effective computational tool for rapid aquatic hazard assessment of diverse organic chemicals. Environ Toxicol Chem 2024;43:1161–1172. © 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

Air pollution is a growing concern in today's urbanized world, necessitating efficient and accurate methods for air quality monitoring. The proliferation of IoT devices has led to a surge in the generation of time-series data. With its high volume and complexity, this surge in time-series data necessitates cloud-based solutions for handling and analyzing this data effectively. However, existing methods for air quality monitoring face challenges in capturing the complex patterns and dynamics of air pollution, which often exhibit both linear and nonlinear characteristics. Air pollution data often exhibit both linear and nonlinear characteristics. Linearity and nonlinearity refer to the nature of the relationships within the data. Some aspects of air quality, such as pollutant concentrations, may follow linear patterns, while other factors, like the interaction of multiple pollutants and environmental conditions, exhibit nonlinear relationships. This complexity arises from the multifaceted nature of air quality dynamics, which various factors and interactions can influence. To address these challenges, this study introduces a novel hybrid time-series approach that combines the proven strengths of two well-established techniques: traditional time-series autoregressive integrated moving average (ARIMA) and soft computing adaptive neuro-fuzzy inference system (ANFIS). The hybrid model is designed to provide a comprehensive solution that accommodates the diverse characteristics of air quality time-series data. To assess the efficacy of our proposed model, we conducted extensive experiments using real-world air pollution datasets obtained from the Ministry of Environment, Forest and Climate Change of India, covering the period from January 2015 to July 2020. Our evaluation includes a range of performance metrics such as root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean squared logarithmic error (MSLE). Specifically, our model demonstrates exceptional accuracy, with notably low error values for key metrics such as air quality index (AQI) and PM2.5. Furthermore, we subjected our innovative hybrid model to rigorous statistical testing using the Diebold-Mariano test, establishing the significance and superiority of our approach. This research advances our understanding of air quality prediction and offers a valuable solution for mitigating the detrimental effects of air pollution on public health and the environment. [ABSTRACT FROM AUTHOR]

The aim is to pilot a low-touch program for reducing benzodiazepine receptor agonist (BZRA; benzodiazepines, z-drugs) prescriptions among older veterans. Pilot randomized controlled trial consists of 2,009 veterans aged ≥ 65 years who received BZRA prescriptions from a Veterans Health Administration pharmacy (Colorado or Montana) during the prior 18 months. Active: Arm 1 was a mailed brochure about BZRA risks that also included information about a free, online cognitive behavioral therapy for the insomnia (CBTI) program. Arm 2 was a mailed brochure (same as arm 1) and telephone reinforcement call. Control: Arm 3 was a mailed brochure without insomnia treatment information. Active BZRA prescriptions at follow-up (6 and 12 months) were measured. In logistic regression analyses, the odds of BZRA prescription at 6- and 12-month follow-ups were not significantly different for arm 1 or 2 (active) versus arm 3 (control), including models adjusted for demographics and prescription characteristics (p-values >0.36). Although we observed no differences in active BZRA prescriptions, this pilot study provides guidance for conducting a future study, indicating a need for a more potent intervention. A full-scale trial testing an optimized program would provide conclusive results. Mailing information about BZRA risks and CBTI did not affect BZRA prescriptions. [ABSTRACT FROM AUTHOR]

Granger causality is a classical and important technique for measuring predictability from one group of time series to another by incorporating information of the variables described by a full vector autoregressive (VAR) process. However, in some applications economic forecasts need to be made based on information provided merely by a portion of variates (e.g., removal of a listed stock due to halting, suspension or delisting). This requires a new formulation of forecast based on an embedded subprocess of VAR, whose theoretical properties are often difficult to obtain. To avoid the issue of identifying the VAR subprocess, we propose a computation‐based approach so that sophisticated predictions can be made by utilizing a reduced variable information set estimated from sampled data. Such estimated information set allows us to develop a suitable statistical hypothesis testing procedure for characterizing all designated Granger causal relationships, as well as a useful graphical tool for presenting the causal structure over the prediction horizon. Finally, simulated data and a real example from the stock markets are used to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

Because Null Hypothesis Significance Tests (NHST) can be misleading particularly when sample sizes are large, reporting effect sizes is recommended. Effect sizes such as Cohen's d, however, are abstract statistics and not relevant to decision-making. This article introduced an alternative formulation of Cohen's d based on a "minimal important percent difference" (MIPD) between groups that has an intuitive, practical meaning. Cohen's d was calculated based on detecting MIPDs of 5% and 10% differences in means. Power analyses were used to determine the number of responses needed to detect differences in means. Power-probability sample size requirements were examined for an 80% and a 50% chance of accepting a difference of MIPD at p <.05. We proposed a four-step process to show how both effect size and NHST jointly contribute to decision-making. To demonstrate the process, data were obtained for 6 years of annual waterfowl surveys in Illinois (N = 17,265, average response rate = 41%). [ABSTRACT FROM AUTHOR]

The escalating process of urbanization has raised concerns about incidents arising from overcrowding, necessitating a deep understanding of large human crowd behavior and the development of effective crowd management strategies. This study employs computational methods to analyze real-world crowd behaviors, emphasizing self-organizing patterns. Notably, the intersection of two streams of individuals triggers the spontaneous emergence of striped patterns, validated through both simulations and live human experiments. Addressing a gap in computational methods for studying these patterns, previous research utilized the pattern-matching technique, employing the Nelder-Mead Simplex algorithm for fitting a two-dimensional sinusoidal function to pedestrian coordinates. This paper advances the pattern-matching procedure by introducing Simulated Annealing as the optimization algorithm and employing a two-dimensional square wave for data fitting. The amalgamation of Simulated Annealing and the square wave significantly enhances pattern fitting quality, validated through statistical hypothesis tests. The study concludes by outlining potential applications of this method across diverse scenarios. [ABSTRACT FROM AUTHOR]

Background: Misconceptions about male nurses not only exacerbate the gender imbalance in the nursing profession but also negatively impact male nurses embarking on their careers. Currently, no tool exists to measure the gender biases toward males in nursing among nursing students in China. Consequently, the primary objective of this study is to assess the validity and reliability of the Chinese translation of the Gender Misconceptions of Men in Nursing (GEMINI) scale among nursing students. Methods: This cross-sectional study involved 1,102 nursing students from China who participated online. We utilized the Brislin translation technique with a forward-backward approach. To determine the factor structure within the Men in Nursing Gender Misconceptions Scale's Chinese version, both exploratory (EFA) and confirmatory factor analysis (CFA) were applied. The scale's internal consistency was measured through the Cronbach's alpha coefficient, corrected item-total correlation, and a retest reliability assessment. Results: The scale showed a content validity index of 0.938 and a retest reliability of 0.844. EFA indicated a two-factor structure for the translated instrument. CFA revealed a chi-square/degree of freedom of 3.837, an incremental fit index (IFI) of 0.952, a goodness-of-fit index (GFI) of 0.910, a comparative fit index (CFI) of 0.952, and an RMSEA of 0.073, all of which were within acceptable limits. The scale's Cronbach's α was 0.953, and the corrected item-total correlations ranged between 0.539 and 0.838. Gender-based misconceptions about men in nursing among students appeared to be influenced by their gender and whether they considered a nursing program as their first choice when applying for a major. Misconceptions about male nurses are greater among men and those who do not consider nursing programs as their first choice when applying for a major. Conclusions: The Chinese adaptation of the GEMINI scale showcased high reliability and validity. It stands as a potential instrument to gauge gender misconceptions concerning male nurses among Chinese nursing students. [ABSTRACT FROM AUTHOR]

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1, a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments. [ABSTRACT FROM AUTHOR]

To describe physical functioning after severe COVID-19-infection. An explanatory sequential mixed method design was used. Thirty-nine participants performed tests and answered questionnaires measuring physical functioning six months after hospitalisation due to COVID-19. Thirty of these participants participated in semi-structured interviews with questions regarding how they perceived their physical functioning and recovery from COVID-19 at 12 months post-hospitalisation. At six months, physical functioning measured via chair stand test and hip-worn accelerometers was lower than normal reference values. There was a reduction in breathing muscle strength. Participants estimated their functional status during different activities as lower compared to those before COVID-19-infection, measured with a patient-specific functional scale. At one year after infection, there were descriptions of a rough recovery process and remaining symptoms. Patients recovering from severe COVID-19 seem to have reduced physical functioning and activity levels, and they perceive their recovery to be slow and difficult. They experienced a lack of clinical support and contradictory advice regarding rehabilitation. Coaching in returning to physical functioning after the infection needs to be better co-ordinated and there is a need for guidelines for health professionals to avoid patients receiving contradictory advice. Coronavirus infection disease-19 (COVID-19) can have a great impact on a person's physical functioning. In the early course of the COVID-19 pandemic there were not any clear guidelines regarding rehabilitation for this group of patients. As some people with COVID-19 may have impairments in their physical functioning up to one year after leaving hospital there is a need to provide rehabilitation. [ABSTRACT FROM AUTHOR]

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language model embeddings are evaluated. We show that topics derived by the pipeline are consistent with legal doctrines in both areas and can be useful in other related legal analysis tasks. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

Objective The objective of this study was to describe the utilization of physical therapist and occupational therapist services after rotator cuff repair (RCR) and examine variation in rehabilitation characteristics by profession. Methods This retrospective cohort study used the IBM MarketScan Commercial Claims and Encounters database. Eligible patients were 18 to 64 years old and had undergone outpatient RCR between 2017 and 2020. Physical therapist and occupational therapist services were identified using evaluation and treatment codes with profession-specific modifiers ("GP" or "GO"). Factors predicting utilization of formal rehabilitation and physical therapist versus occupational therapist services were examined; and univariable and multivariable analyses of days to initiate therapy, number of visits, and episode length by profession were completed. Results Among 53,497 patients with an RCR, 81.2% initiated formal rehabilitation (93.8% physical therapist, 5.2% occupational therapist, 1.0% both services). Patients in the Northeast and West (vs the South) were less likely to receive rehabilitation (odds ratio [OR] = 0.67 to 0.70) and less likely to receive occupational therapist services (OR = 0.39). Patients living in the Midwest (versus the South) were less likely to receive rehabilitation (OR = 0.79) but more likely to receive occupational therapist services (OR = 1.51). Similarly, those living in a rural (versus urban) area were less likely to utilize rehabilitation (OR = 0.89) but more likely to receive occupational therapist services (OR = 2.21). Additionally, receiving occupational therapist instead of physical therapist services was associated with decreased therapist visits (−16.89%), days to initiate therapy (−13.43%), and episode length (−13.78%). Conclusion Most patients in our commercially insured cohort utilized rehabilitation services, with a small percentage receiving occupational therapist services. We identified profession-specific variation in utilization characteristics that warrants further examination to understand predictors and associated outcomes. Impact Variation in rehabilitation utilization after RCR, including profession-specific and regional differences, may indicate opportunities to improve standardization and quality of care. [ABSTRACT FROM AUTHOR]

Romans 8:20-22 is the prooftext par excellence for the hypothesis that the natural world is fallen. The basis for that hypothesis is challenged as follows: "subjected to futility" refers principally to Gen 1:26-28, not Gen 3:17-18, and must be interpreted as such; "bondage to decay" is best understood through the OT's naturalistic view of environmental phenomena; "groaning in labor pains" is not a periphrasis for animal suffering, but a personification of the creation-sin antipathy. While Paul assumes that sin can have extrinsic effects on creation, Rom 8:20-22 does not imply that creation was vitiated intrinsically by the fall, and thus the passage is fully compatible with the notion that the natural world retains the full extent of its prelapsarian integrity. [ABSTRACT FROM AUTHOR]

BACKGROUND: Behavioral health disorders (BHDs) can often be exacerbated in the setting of cancer. We sought to define the prevalence of BHD among cancer patients and characterize the association of BHD with surgical outcomes. STUDY DESIGN: Patients diagnosed with lung, esophageal, gastric, liver, pancreatic, and colorectal cancer between 2018 and 2021 were identified within Medicare Standard Analytic Files. Data on BHD defined as substance abuse, eating disorder, or sleep disorder were obtained. Postoperative textbook outcomes (ie no complications, prolonged length of stay, 90-day readmission, or 90-day mortality), as well as in-hospital expenditures and overall survival were assessed. RESULTS: Among 694,836 cancer patients, 46,719 (6.7%) patients had at least 1 BHD. Patients with BHD were less likely to undergo resection (no BHD: 23.4% vs BHD: 20.3%; p < 0.001). Among surgical patients, individuals with BHD had higher odds of a complication (odds ratio [OR] 1.32 [1.26 to 1.39]), prolonged length of stay (OR 1.36 [1.29 to 1.43]), and 90-day readmission (OR 1.57 [1.50 to 1.65]) independent of social vulnerability or hospital-volume status resulting in lower odds to achieve a TO (OR 0.66 [0.63 to 0.69]). Surgical patients with BHD also had higher in-hospital expenditures (no BHD: $16,159 vs BHD: $17,432; p < 0.001). Of note, patients with BHD had worse long-term postoperative survival (median, no BHD: 46.6 [45.9 to 46.7] vs BHD: 37.1 [35.6 to 38.7] months) even after controlling for other clinical factors (hazard ratio 1.26 [1.22 to 1.31], p < 0.001). CONCLUSIONS: BHD was associated with lower likelihood to achieve a postoperative textbook outcome, higher expenditures, as well as worse prognosis. Initiatives to target BHD are needed to improve outcomes of cancer patients undergoing surgery. [ABSTRACT FROM AUTHOR]

Introduction: Urolithiasis is one of the most common urological problems worldwide. The fastest treatment modality to achieve stone clearance of ureteral stones is Ureteroscopic Lithotripsy (URSL). However, it is negated by both the cost burden and potential risk to the patient. Medical Expulsive Therapy (MET) is a treatment option for upto 10 mm stones but has failure rates of 40-60% in the literature. Aim: To analyse the various indications for surgery, whether MET was used or not, if used-its details, operative findings at ureteroscopy including the reason for the failure of MET. Materials and Methods: A cross-sectional study consisting of 72 patients with ureteric calculi undergoing URSL was analysed from June 2017 to December 2018 at Mazumdar Shaw Medical Centre, Bangalore, Karnataka, India. Indications were assessed at the time of admission. During ureteroscopy, factors like impaction, distal obstruction, and unusual findings were studied, which could have contributed to the failure of MET. The Chi-square test was used as a test of significance for categorical data. The Analysis of Variance (ANOVA) test was used as a test of significance to identify the mean difference between continuous variables. The p-value of <0.05 was considered statistically significant. Results: The mean age in the study was 41.65±13.4 years (range 20-69 years), and the mean stone size was 10.03±3.34 mm. Large stone was the most common indication (41, 56.9%, p=0.004), followed by failed MET (35, 48.6%). Even though MET could have been continued for four weeks in 17 patients (23.6%), they were taken up for surgery. The impaction rate was 70.8% (51), with 48.6% (35) being large impacted stones and 22.2% (16) being small impacted stones. The overall stone clearance rate was 68 out of 72 (94.4%). Conclusion: Large stone size (=10 mm) and failed MET were the main indications for surgery. One reason for the failure of MET was not waiting for a duration of four weeks. During ureteroscopy, impaction of the stone, irrespective of size, was the most common finding and was the reason for the failure of MET. Ureteric stones on MET should not be neglected as there are reasons for the failure of MET, and they will require URSL after four weeks. [ABSTRACT FROM AUTHOR]

Parkinsonism‐dystonia‐2 PKDYS2 is an autosomal‐recessive disorder, caused by pathogenic biallelic variants in SLC18A2 which encodes the vesicular monoamine transporter (VMAT2) protein. PKDYS2 is a treatable neurotransmitter disease, and the rate of diagnosis of this disorder has increased significantly with the advance of genomic technologies. Our report highlights a novel pathologic variant in one case and a novel finding on MRI Brain, consisting of a normal symmetrical signal intensity in the dorsal brainstem and pons, and it substantiates the significance of genetic testing in the evaluation of children with developmental delays, which influences clinical decisions to enhance patient outcomes. [ABSTRACT FROM AUTHOR]

The present in vitro study aimed to evaluate the influence of various surface treatments on the micro-shear bond strength (μSBS) of calcium silicate–based materials (CSMs) to resin composite. Two hundred and forty cylindrical acrylic molds were filled with Biodentine, NeoMTA Plus, NeoPUTTY MTA, TheraCal LC, and Well-Root PT. The specimens were divided into four groups: control with no surface treatment, acid-etching, tribochemical silica coating (TSC), sandblasting with aluminum oxide (AL). Resin composite was applied and photo-polymerized. The μSBS was measured and surface alterations were evaluated using a SEM. Data were examined using two-way ANOVA and Tukey tests at a significance level of 5%. The lowest bond strength values were detected in the controls. Moreover, the lowest μSBS was demonstrated in the untreated NeoMTA Plus group, whereas the aluminum oxide–treated TheraCal LC group exhibited the highest bond strength (p < 0.05). Cohesive failures were observed dominantly for Biodentine and TheraCal LC, adhesive failures in Well-Root PT, and mixed failures for NeoPUTTY MTA. Surface treatments increased the μSBS values of CSMs and affected the micromorphology of the sample surfaces. The study suggests that surface treatments would be advantageous on CSMs. [ABSTRACT FROM AUTHOR]

Background: Endoscopic submucosal dissection (ESD) was widely used for the removal of esophageal tumors, and post-endoscopic submucosal dissection electrocoagulation syndrome (PEECS) was one of the postoperative adverse events. The aim of this research was to develop and validate a model to predict electrocoagulation syndrome after endoscopic submucosal dissection of esophageal tumors. Materials and methods: Patients who underwent esophageal ESD in our hospital were retrospectively included. A predictive nomogram was established based on the results of multivariate logistic regression analysis, and bootstrapping resampling was used for internal validation. Besides, the clinical usefulness of the nomogram was evaluated using decision curve analysis (DCA) and clinical impact curve. Results: A total of 552 patients who underwent esophageal ESD were included in the study, and the incidence of PPECS was 12.5% (69/552). Risk factors associated with PEECS (p < 0.1) were analyzed by multivariate logistic regression analysis, and the final model included four variables, namely gender, diabetes, tumor size and operation time. The predictive nomogram was constructed based on the above four variables, and the area under the ROC curve (AUC) was 0.811 (95% CI 0.767–0.855). The calibration curve of the nomogram presented good agreement between the predicted and actual probabilities. DCA showed that the model improved patient outcomes by helping to assess the risk of PEECS in patients compared to an all-or-no treatment strategy. In addition, the clinical impact curve of the model also indicates that the nomogram has a high clinical net benefit. Conclusion: In conclusion, we have developed a predictive nomogram for PEECS after ESD for esophageal tumors with good predictive accuracy and discrimination. This predictive nomogram can be effectively used to identify high-risk patients with PEECS, which will help clinicians in clinical decision-making and early intervention. [ABSTRACT FROM AUTHOR]

Background: Psychological Clearance level (PCL) for patients undergoing metabolic and bariatric surgery (MBS) is a critical step for successful postoperative outcomes. This study aims to assess the relationship between the level of psychologic fitness and postoperative outcomes in patients undergoing MBS. Methods: We retrospectively analyzed the data of patients who underwent MBS (laparoscopic sleeve gastrectomy [LSG] and laparoscopic Roux-en-Y Gastric Bypass [LRYGB]) and completed two years follow-up, between 2012 and 2019, in a single medical center. The patients were divided into four groups based on PCL, suggesting level of readiness for surgery: Group A (PCL-0: guarded), group B (PCL-1: Fair/reasonable), group C (PCL-2: Good/appropriate), and group D (PCL-3: Strong/excellent). Primary outcome was the percent of total body weight loss (%TWL), and the absolute change in BMI units. Secondary outcomes were missed postoperative visits and patient compliance. Differences between the groups were analyzed using a generalized linear model (GLM), chi-squared and exact Fisher tests, as appropriate. Results: Of 1411 total patients, 607 (43.20%) had complete data at two years follow-up. 512 (84.34%) were females. LSG was performed in 361 (59.5%). No difference was found in %TWL between the four groups (22.14% vs. 28.0% vs. 26.0% vs. 24.8%, p = 0.118). We found a small difference in the mean (SD) of absolute change in BMI between the groups, and on post-hoc analysis it was found between groups B (PCL-1) and D (PCL-3). Overall, no difference between the groups in number of follow-up visits, or compliance issues. However, patients who attended more follow-up visits had less compliance issues (p < 0.001). PCL is inversely correlated with number of psychologic diagnoses (r = − 0.41, p < 0.001) and medical comorbidities (r = − 0.20, p < 0.001). Conclusion: We found no difference in the percent of TWL in patients who underwent MBS based on PCL at two -years follow-up. Medical comorbidities and psychiatric diagnoses impact the PCL. [ABSTRACT FROM AUTHOR]

To longitudinally investigate speech production (consonant proficiency, consonant errors and perceived velopharyngeal competence) in 17 internationally adopted (IA) children with unilateral cleft lip and palate (UCLP) at three time points. Consonant proficiency (percent consonants correct, consonant inventory) and number and type of consonant errors were calculated based on blind phonetic transcriptions of words from the Swedish Test of Articulation and Nasality (SVANTE). Velopharyngeal competence was perceptually rated by three blinded experienced speech-language pathologists at the ages of 3, 5 and 7–8 years. A significant positive development of speech production was found, although most children still scored very low for consonant proficiency at the age of 7–8 compared with normative values: the median for percent consonants correct was 79.7 and many children still had persisting cleft-related and developmental consonant errors. At the age of 7–8, almost half of the children were rated as having a competent velopharyngeal function and only three as having an incompetent velopharyngeal function. Persisting speech difficulties at school age in IA children with UCLP were found in the present study, which is one of the very few longitudinal studies. Our results highlight the need for detailed follow-up of speech production in clinical settings. Speech disorders may have a severe impact on a child's intelligibility and participation with peers, and there is a need for more studies investigating the actual everyday effect of the difficulties found. [ABSTRACT FROM AUTHOR]

Objectives: More than half of women do not achieve appropriate gestational weight gain. Maternal body image may be an important factor associated with gestational weight gain. However, this association has not been thoroughly evaluated. We aimed to elucidate whether body image parameters before and during pregnancy are associated with gestational weight gain in Japanese women. Methods: This prospective cohort study was conducted at a hospital in Osaka, Japan from March 2020 to March 2021. We recruited women with singleton pregnancies in their second and third trimesters. Body image was assessed using the Pregnancy and Weight Gain Attitude Scale and additional questions. Gestational weight gain was classified as insufficient, appropriate, or excessive based on recommended ranges in Japan. One-way analysis of variance, chi-square tests, and multinomial logistic regression analyses were performed to identify factors associated with insufficient or excessive weight gain. Results: Of 266 enrolled women, 47 had insufficient weight gain and 100 had excessive weight gain during pregnancy. Risk factors for excessive gestational weight gain included a history of dietary restriction before pregnancy, negative attitudes toward gestational weight gain, and perception of body shape as fat and body shape dissatisfaction during pregnancy. Perception of body shape as thin during pregnancy was identified as a risk factor for insufficient gestational weight gain. Conclusions: Body image before and during pregnancy may be an important factor in preventing insufficient or excessive gestational weight gain in Japanese women. Healthcare professionals should consider body image when providing health guidance on weight management to pregnant women. Significance: What is Already Known? Body image is a possible factor in gestational weight gain. Compared to women in other countries, Japanese women of reproductive age tend to have a negative body image. What this Study adds? A history of dietary restriction before pregnancy and negative body image during pregnancy were associated with excessive gestational weight gain among Japanese women. Perception of body shape during pregnancy as thin was associated with insufficient gestational weight gain. Thus, even in a Japanese population, characterized by a majority of women with pre-pregnancy underweight or normal body mass index status, associations between negative body image and gestational weight gain were similar to those in other countries. [ABSTRACT FROM AUTHOR]

The objective was to determine reliability of sagittal plane range of motion (ROM) assessment in a healthy population and in people with cervicogenic headache (CGH). Upper cervical flexion/extension ROM was measured using an iPhone magnetometer sensor and retraction/protraction ROM measured by linear displacement. Two independent raters evaluated these movements in 33 subjects with CGH and 33 age and gender matched asymptomatic healthy controls on two occasions. Measurement procedures were standardized; and the order of testing randomized. Reliability, standard error of measurement (SEM) and minimum detectable change (MDC) were calculated. Subjects comprised 30 females and 36 males. The iPhone method demonstrated high reliability (ICC >0.82) with SEM values ranging from 0.62 to 1.0 and MDC values ranging from 1.70 to 4.81 respectively. Evaluation of linear displacement demonstrated moderate reliability (ICC >64). with SEM values ranging from 0.38 to 1.91 and MDC values ranging from 1.05 to 1.63 respectively. Compared to healthy controls, upper cervical flexion, retraction and protraction ROM was significantly less in the CGH group with mean difference of 6.50°, 1.52 cm and 2.34 cm respectively. Upper cervical spine sagittal plane ROM can be measured with moderate to high reliability and was found to be more restricted in people with CGH. [ABSTRACT FROM AUTHOR]

On-farm research (OFR) has become popular as a result of precision agriculture technology simplifying the process and farm software capabilities to summarize results collected through the technology. Different OFR designs exists with strip-trials being a simple approach to evaluate different treatments. Common in OFR is the use of yield monitors to collect crop performance data since yield represents a primary response variable in these type studies. The objective was to investigate the ability of grain yield monitoring technologies to accurately inform strip trials when frequent yield variability exists within an experimental unit. A combination of six sub-plot treatment resolutions (TR) that differed in length of imposed yield variation (7.6, 15.2, 30.5, 61.0, 121.9, and 243.8 m) were harvested at combine ground speeds of 3.2, 6.4, 7.2, and 8.1 kph, depending on study site (three study sites total). Intentional yield differences in maize (Zea mays L.) were created for each sub-plot by alternating the amount nitrogen (N) applied: 0 or 202 kg N/ha. Yield was measured by four commercially available yield monitoring (YM) technologies and a weigh wagon. Comparisons were made between the accumulated mass of the YM technology and weigh wagon through percent differences along with testing the significance of the plotted relationship between YM and weigh wagon. Results indicated that yield monitoring technology can be used to evaluate strip trial performance regardless of yield frequency and variability (error < 3%) within an experimental unit when operating within the calibrated range of the mass flow sensor. Operating outside of the calibrated range of the mass flow sensor resulted in > 15% error in estimating accumulated weight and overestimation of yield by 23%. Finally, no significant differences existed in estimating accumulated weight values between grain yield monitor technologies (all p-values ≥ 0.54). [ABSTRACT FROM AUTHOR]

Human anterior gradient‐2 (AGR2) has been implicated in carcinogenesis of various solid tumours, but the expression data in prostate cancer are contradictory regarding its prognostic value. The objective of this study is to evaluate the expression of AGR2 in a large prostate cancer cohort and to correlate it with clinicopathological data. AGR2 protein expression was analysed immunohistochemically in 1023 well‐characterized prostate cancer samples with a validated antibody. AGR2 expression levels in carcinomas were compared with matched tissue samples of adjacent normal glands. AGR2 expression levels were dichotomized and tested for statistical significance. Increased AGR2 expression was found in 93.5% of prostate cancer cases. AGR2 levels were significantly higher in prostate cancer compared with normal prostate tissue. A gradual loss of AGR2 expression was associated with increasing tumour grade (ISUP), and AGR2 expression is inversely related to patient survival, however, multivariable significance is not achieved. AGR2 is clearly upregulated in the majority of prostate cancer cases, yet a true diagnostic value appears unlikely. In spite of the negative correlation of AGR2 expression with increasing tumour grade, no independent prognostic significance was found in this large‐scale study. [ABSTRACT FROM AUTHOR]

An adequate foot clearance height while stepping over an obstacle is important for safety in daily life. In the present study, we examined whether visual illusions affect foot clearance during a stepping-over action, and whether this is further influenced by gaze behavior. Twelve participants stepped over an obstacle placed four meters away under conditions of three different obstacle characteristics: white, horizontal, or vertical lines. We measured the participants' foot clearances during the step-over action and their gaze behavior during the approaching phase. Participants stepped significantly higher over the obstacles in the vertical lines (illusion) condition. The duration of gaze fixation on the obstacle positively correlated with increased foot clearance in the vertical condition, suggesting that the effect of the visual illusion on foot clearance was enhanced by prolonged gaze fixation. Conversely, prolonged fixation negatively correlated with foot clearance in the white (control) condition, implying that a cautious perception of an obstacle may contribute to efficient stepping-over action. [ABSTRACT FROM AUTHOR]

This paper aims to interpret the connotation of high-quality development of tourism economy (HQTE) from the perspective of the new development concepts of innovation, coordination, green, openness and sharing, and then to evaluate the spatial differentiation of China's HQTE based on provincial panel data from 2009 to 2018. Specifically, we employ the spatial convergence model to explore the absolute and conditional β convergence trends of HQTE in the whole country and the eastern, central and western regions of China. Our empirical results reveal that: 1) within the decade, from 2009 to 2018, regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region, but the fastest growing one is the western region of China followed by the central region and then the eastern region. 2) Whether or not the spatial effect is included, there are absolute and conditional β convergence in HQTE in the whole country and aforementioned three regions. 3) The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions. The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions. The above conclusions could deepen the understanding of the regional imbalance and spatial convergence characteristics of HQTE, clarify the primary development objects, and accomplish the goal of China's HQTE. [ABSTRACT FROM AUTHOR]

This paper focuses on the likelihood ratio test (LRT) statistics for different hypothesis tests. Assuming that a random sample is from a normal population, we make the sample size n and the dimension p close to infinity and satisfy p < n − c for some 1 ≤ c ≤ 4. Based on this assumption, the moderate deviation principle (MDP) for the LRT will be given under the null hypothesis. The corresponding numerical simulation results are shown at the end of the paper. [ABSTRACT FROM AUTHOR]

Qualitative interactions occur when a treatment effect or measure of association varies in sign by sub‐population. Of particular interest in many biomedical settings are absence/presence qualitative interactions, which occur when an effect is present in one sub‐population but absent in another. Absence/presence interactions arise in emerging applications in precision medicine, where the objective is to identify a set of predictive biomarkers that have prognostic value for clinical outcomes in some sub‐population but not others. They also arise naturally in gene regulatory network inference, where the goal is to identify differences in networks corresponding to diseased and healthy individuals, or to different subtypes of disease; such differences lead to identification of network‐based biomarkers for diseases. In this paper, we argue that while the absence/presence hypothesis is important, developing a statistical test for this hypothesis is an intractable problem. To overcome this challenge, we approximate the problem in a novel inference framework. In particular, we propose to make inferences about absence/presence interactions by quantifying the relative difference in effect size, reasoning that when the relative difference is large, an absence/presence interaction occurs. The proposed methodology is illustrated through a simulation study as well as an analysis of breast cancer data from the Cancer Genome Atlas. [ABSTRACT FROM AUTHOR]

Background: Cancer, a disease with high morbidity and mortality rates, poses a significant threat to human health. Driver genes, which harbor mutations accountable for the initiation and progression of tumors, play a crucial role in cancer development. Identifying driver genes stands as a paramount objective in cancer research and precision medicine. Results: In the present work, we propose a method for identifying driver genes using a Generalized Linear Regression Model (GLM) with Shrinkage and double-Weighted strategies based on Functional Impact, which is named GSW-FI. Firstly, an estimating model is proposed for assessing the background functional impacts of genes based on GLM, utilizing gene features as predictors. Secondly, the shrinkage and double-weighted strategies as two revising approaches are integrated to ensure the rationality of the identified driver genes. Lastly, a statistical method of hypothesis testing is designed to identify driver genes by leveraging the estimated background function impacts. Experimental results conducted on 31 The Cancer Genome Altas datasets demonstrate that GSW-FI outperforms ten other prediction methods in terms of the overlap fraction with well-known databases and consensus predictions among different methods. Conclusions: GSW-FI presents a novel approach that efficiently identifies driver genes with functional impact mutations using computational methods, thereby advancing the development of precision medicine for cancer. [ABSTRACT FROM AUTHOR]

Aim. To develop a scale for measuring nurse's perceived work environment during the public health emergencies (PHEs) and assess its reliability and validity. Background. Although there is extensive research on instruments for measuring nursing work environments in regular healthcare settings, there is a lack of specific scales tailored to address the unique work conditions experienced by nurses during PHEs. Design. This study employed a cross-sectional design for psychometric evaluation and adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement. Methods. A self-report scale, the Chinese Nursing Work Environment Scale for Public Health Emergencies (C-NWE-PHE), was developed, integrating situational characteristics. Data on demographics, adapted scale scores, and subjective evaluations of nursing management performance were collected from 1156 nurses through online surveys conducted between January 2023 and March 2023. Confirmatory factor analysis, Pearson correlations, and Cronbach's alpha analyses were conducted to evaluate the psychometric properties of the scale. Results. The adapted C-NWE-PHE scale comprised 28 items organized into five subscales: Workforce and Deployment Support, Leadership and Emergency Management, Autonomy and Empowerment, Teamwork and Collaboration, and Logistics and Humanistic Care. Structural equation modelling showed satisfactory factor loadings for each subscale and a good model fit, confirming construct validity. The content validity and reliability of the total scale were confirmed. Conclusion. This study provides empirical evidence for understanding and assessing the nursing work environment during PHEs with a psychometrically sound scale. Implications for Nursing Management. The C-NWE-PHE scale, along with its five identified constructs, provides a nuanced comprehension of working conditions amid PHEs. Implementing this scale could foster specific enhancements, support nurse retention efforts, and enhance the effectiveness of responses during challenging emergency situations. [ABSTRACT FROM AUTHOR]

Cronbach's alpha, widely used for measuring reliability, often operates within studies with sample information, suffering insufficient sample sizes to have sufficient statistical power or precise estimation. To address this challenge and incorporate considerations of both confidence intervals and cost-effectiveness into statistical inferences, our study introduces a novel framework. This framework aims to determine the optimal configuration of measurements and subjects for Cronbach's alpha by integrating hypothesis testing and confidence intervals. We have developed two R Shiny apps capable of considering up to nine probabilities, which encompass width, validity, and/or rejection events. These apps facilitate obtaining the required number of measurements/subjects, either by minimizing overall cost for a desired probability or by maximizing probability for a predefined cost. [ABSTRACT FROM AUTHOR]

This study examines the relationships between state-provided paid-leave availability and enrollment in public health and nutrition programs (SNAP, Medicaid, WIC) among single low-income women following a birth in the U.S. We hypothesize that women in paid leave states will be less likely to participate in publicly available health and nutrition programs. Data are from the Survey of Income and Program Participation (SIPP), a nationally representative panel survey data set (N = 1168). Descriptive tests of significance and probit regression models are used to examine the relationship between paid-leave availability and participation in SNAP, Medicaid, and WIC following a birth. A descriptive analysis suggests significantly lower enrollment in SNAP but not Medicaid or WIC for single low-income women in paid-leave states compared to those in non-paid-leave states. The finding of significantly lower post-birth SNAP participation in paid-leave states holds in probit models that include potentially relevant mother, household, and state controls. [ABSTRACT FROM AUTHOR]

Z-numbers contain fuzzy restrictions, credibility measures, and probability distributions to effectively represent uncertain information. Converting Z-numbers to fuzzy numbers facilitates extensive applications (such as multi-attribute decision-making (MADM)), thus becoming valuable for research purposes. Regarding Z-number conversions, the original method never considers the association probability, while probabilistic strategies offer better informatization. Recently, a probability-driven conversion starts with a linear transformation of the centroid difference between the fuzzy restriction and probabilistic distribution. However, it has the invalidation weakness of edge information due to underlying non-normalization. To improve this probability-linear conversion, a Z-number conversion is proposed by using underlying probability-exponential descriptions, and this new method is further applied to MADM. At first, the current probability-linear conversion is analyzed based on the initial non-probabilistic conversion, and its intrinsic weakness and correctional improvement are revealed. Then, the novel probability-exponential conversion resorts to an exponential characterization of centroid difference between the restriction and distribution, and it gains information enrichment due to underlying normalization. The refined method preserves the inherent characteristics of Z-numbers more effectively, facilitating their application in subsequent engineering practices. This is especially pertinent in decision-making systems based on expert input and initial value problems. The proposed method for converting Z-numbers aims to minimize information loss in transitions between Z-numbers and classical fuzzy numbers. This approach will be further explored in future research. Furthermore, the probability-exponential conversion induces an ExpTODIM algorithm for MADM, called PE-ExpTODIM. Three Z-number conversions (i.e., the non-probabilistic, probability-linear, and probability-exponential types) and three decision algorithms (i.e., ExpTODIM, EDAS, MOORA) are combined to establish a 3 × 3 framework of Z-number-driven MADM. Finally, the systematical 9 algorithms are applied to the problem of site selection of carbon storage. They are validated by criss-cross contrast analyses and statistical significance tests. Thus, PE-ExpTODIM exhibits the desired optimization. The last technology of statistical testing is original, ingenious, and valuable for MADM. [ABSTRACT FROM AUTHOR]

The ability to remember our past and to imagine the future are critical to our sense of self. Previous research has indicated that they are disrupted in schizophrenia. However, it is unclear (i) whether this is found when examining experimenter-scored indices of content and/or participants' self-report of phenomenological characteristics, and (ii) how these abilities might be related to symptoms. This study sought to address these questions by taking a dimensional approach and measuring positive and negative schizotypal experiences in healthy people (n = 90). Participants were given cue words. For some, they remembered an event from the past and for others they generated an event in the future. No significant relationships were found with any aspect of schizotypy when participants' descriptions were scored by the experimenter according to a standardised episodic content measure. In contrast, several significant positive correlations were observed for past memory and future thinking when examining the positive dimension of schizotypy and participants' ratings, particularly to sensory characteristics of the experience and mental pre- or reliving. These results indicate enhanced subjective experiences of autobiographical memory and future thinking in those who report delusional and hallucinatory-like occurrences, which might be linked to mental imagery or metacognitive alterations. [ABSTRACT FROM AUTHOR]

The Omicron variants BA.1, BA.2, and BA.5 caused several waves of SARS-CoV-2 in Germany in 2022. In this comparative study, public health data on SARS-CoV-2 infections from Mecklenburg-Western Pomerania, Germany, between January and October 2022 were examined retrospectively using Pearson's chi-squared tests and Fisher's exact tests for testing for statistical significance. Compared to BA.5 infections, BA.1 and BA.2 infections affected younger individuals aged up to 19 years significantly more often, whereas BA.5 infections occurred significantly more frequently in patients between 40 and 59 years of age when compared to BA.1 and BA.2. Infections with all three variants predominantly caused flu-like symptoms; nevertheless, there were significant differences between the reported symptoms of BA.1, BA.2, and BA.5 infections. Especially, the symptoms of 'fever', 'severe feeling of sickness', 'loss of taste', and 'loss of smell' were significantly more often present in patients with BA.5 infections compared to BA.1 and BA.2 cases. Additionally, BA.2 and BA.5 cases reported significantly more often the symptoms of 'runny nose' and 'cough' than BA.1-infected cases. Our findings indicate remarkable differences in the clinical presentations among the sub-lineages, especially in BA.5 infections. Furthermore, the study demonstrates a powerful tool to link epidemiological data with genetic data in order to investigate their potential impact on public health. [ABSTRACT FROM AUTHOR]

Previous studies on Bayesian situations, in which probabilistic information is used to update the probability of a hypothesis, have often focused on the calculation of a posterior probability. We argue that for an in-depth understanding of Bayesian situations, it is (apart from mere calculation) also necessary to be able to evaluate the effect of changes of parameters in the Bayesian situation and the consequences, e.g., for the posterior probability. Thus, by understanding Bayes' formula as a function, the concept of covariation is introduced as an extension of conventional Bayesian reasoning, and covariational reasoning in Bayesian situations is studied. Prospective teachers (N=173) for primary (N=112) and secondary (N=61) school from two German universities participated in the study and reasoned about covariation in Bayesian situations. In a mixed-methods approach, firstly, the elaborateness of prospective teachers' covariational reasoning is assessed by analysing the arguments qualitatively, using an adaption of the Structure of Observed Learning Outcome (SOLO) taxonomy. Secondly, the influence of possibly supportive variables on covariational reasoning is analysed quantitatively by checking whether (i) the changed parameter in the Bayesian situation (false-positive rate, true-positive rate or base rate), (ii) the visualisation depicting the Bayesian situation (double-tree vs. unit square) or (iii) the calculation (correct or incorrect) influences the SOLO level. The results show that among these three variables, only the changed parameter seems to influence the covariational reasoning. Implications are discussed. [ABSTRACT FROM AUTHOR]

Background: Dysarthria, aphasia and executive processes have been examined for their role in producing impaired communicative competence post traumatic brain injury (TBI). Less understood is the role of emotional dysregulation, that is, apathy and disinhibition, and social cognition, that is, reading and interpreting social cues. Methods & Procedures: In this study, we examined 49 adults with moderate to severe TBI and 18 neurologically healthy adults. We hypothesised that apathy and disinhibition would predict communication outcomes as would social cognition. We also predicted that apathy and disinhibition would influence social cognition. Communication outcomes were measured by the La Trobe Communication Questionnaire (LCQ) and the Social Skills Questionnaire‐TBI (SSQ‐TBI). Apathy and disinhibition were measured by the Frontal Systems Behavior Scale (FrSBe). We measured four aspects of social cognition: emotion perception and theory of mind using The Awareness of Social Inference Test (TASIT) and the Complex Audio‐Visual Evaluation of Affect Test (CAVEAT), empathy using the Questionnaire of Cognitive and Affective Empathy (QCAE) and the Balanced Emotional Empathy Scale (BEES), and alexithymia using the Toronto Alexithymia Scale (TAS‐20) and the Bermond–Vorst Alexithymia Questionnaire. Outcomes & Results: Consistent with predictions, the LCQ and SSQ‐TBI were associated with disinhibition and the LCQ was also associated with apathy. The LCQ was associated with the full range of social cognition constructs although the SSQ‐TBI was not. Finally, apathy and disinhibition predicted a number of social cognition measures. Conclusions and Implications: These results are discussed in relation to understanding the nature of communication disorders following TBI and how they are measured, as well as the interrelation between emotion dysregulation and social cognition. What this study adds: What is already known on this subject: The role of emotional dysregulation and social cognition in producing impaired communicative competence post traumatic brain injury (TBI) is not well understood. Although most adults with severe TBI have minimal or possibly no language impairment, they often struggle with functional communication in everyday situations. Many have been reported to be overtalkative, insensitive, childish and self‐centred, displaying an inappropriate level of self‐disclosure and making tangential and irrelevant comments. Conversely, some speakers with TBI have been noted to have impoverished communication, producing little language either spontaneously or in response to the speaker's questions and prompts. What this paper adds to existing knowledge: We found that both apathy and disinhibition were strongly associated with the Latrobe Communication Questionnaire both empirically and conceptually, despite the LCQ being developed from a different, pragmatic orientation. Disinhibition was also associated with the Social Skills Questionnaire for TBI. We also found that poor social cognition scores predicted communication difficulties. Finally, we found that behavioural dysregulation itself, i.e., both apathy and disinhibition, predicted poor social cognition. What are the potential or actual clinical implications of this work?: Our findings highlight the central role that apathy and disinhibition play in both communication and social cognition. These insights point to the importance of remediation to target behavioural and autonomic dysregulation as a means to improve everyday social function. [ABSTRACT FROM AUTHOR]

Payment cards offer a simple and convenient method for making purchases. Owing to the increase in the usage of payment cards, especially in online purchases, fraud cases are on the rise. The rise creates financial risk and uncertainty, as in the commercial sector, it incurs billions of losses each year. However, real transaction records that can facilitate the development of effective predictive models for fraud detection are difficult to obtain, mainly because of issues related to confidentially of customer information. In this paper, we apply a total of 13 statistical and machine learning models for payment card fraud detection using both publicly available and real transaction records. The results from both original features and aggregated features are analyzed and compared. A statistical hypothesis test is conducted to evaluate whether the aggregated features identified by a genetic algorithm can offer a better discriminative power, as compared with the original features, in fraud detection. The outcomes positively ascertain the effectiveness of using aggregated features for undertaking real-world payment card fraud detection problems. [ABSTRACT FROM AUTHOR]

Objective There are well-described impacts of biological rhythms on human physiology. With the increasing push for routine blood tests for preventative medical care and clinical and physiological research, optimizing effectiveness is paramount. This study aimed to determine whether it is feasible to assess diurnal variations of peripheral lymphocyte prevalence using finger prick blood in a small sample size. Methods Using polychromatic flow cytometry, the prevalence of lymphocytes was assessed using 25 µL fingertip blood samples at 8 AM and 5 PM from 8 participants. Results TH cells and B cells showed significantly higher percentages in the 5 PM samples, whereas NK cells demonstrated a significantly higher morning percentage. T cells, leukocytes, and cytotoxic T cells showed no significant changes. Conclusion The detection of diurnal variations demonstrates that small blood volumes can be used to detect lymphocyte variations. The lower blood volume required provides a new testing method for clinical and research settings. [ABSTRACT FROM AUTHOR]

Although log‐likelihood is widely used in model selection, the log‐likelihood ratio has had few applications in this area. We develop a log‐likelihood ratio based method for selecting regression models by focusing on the set of models deemed plausible by the likelihood ratio test. We show that when the sample size is large and the significance level of the test is small, there is a high probability that the smallest model in this set is the true model; thus, we select this smallest model. The significance level of the test serves as a tuning parameter of this method. We consider three levels of this parameter in a simulation study and compare this method with the Akaike information criterion (AIC) and Bayesian information criterion (BIC) to demonstrate its excellent accuracy and adaptability to different sample sizes. This method is a frequentist alternative and a strong competitor to AIC and BIC for selecting regression models. [ABSTRACT FROM AUTHOR]

Introduction: During the Coronavirus (COVID-19) pandemic, healthcare providers have overcome difficult experiences such as workplace violence. Nurses are particularly vulnerable to workplace violence. The objective of this study was to characterize violence and aggression against nurses during the COVID-19 pandemic in Latin America. Methods: An electronic cross-sectional survey was conducted in 19 Latin American countries to characterize the frequency and type of violent actions against front-line healthcare providers. Results: Of the original 3544 respondents, 16% were nurses (n = 567). The mean age was 39.7 ± 9.0 years and 79.6% (n = 2821) were women. In total, 69.8% (n = 2474) worked in public hospitals and 81.1% (n = 2874) reported working regularly with COVID-19 patients. Overall, about 68.6% (n = 2431) of nurses experienced at least one episode of workplace aggression during the pandemic. Nurses experienced weekly aggressions more frequently than other healthcare providers (45.5% versus 38.1%, p < .007). Nurses showed a trend of lower reporting rates against the acts of aggression suffered (p = .076). In addition, nurses were more likely to experience negative cognitive symptoms after aggressive acts (33.4% versus 27.8%, p = .028). However, nurses reported considering changing their work tasks less frequently compared to other healthcare providers after an assault event (p = .005). Conclusion: Workplace violence has been a frequent problem for all healthcare providers during COVID-19 pandemic in Latin America. Nurses were a particularly vulnerable subgroup, with higher rates of aggressions and cognitive symptoms and lower rate of complaints than other healthcare providers who suffered from workplace violence. It is imperative to develop strategies to protect this vulnerable group from aggressions during their tasks. [ABSTRACT FROM AUTHOR]

Introduction Alcohol use can be significantly associated with negative social, professional, and health outcomes. Even more so, alcohol use disorder (AUD) is a critical public health issue and major avoidable risk factor. This study aimed to examine the effect of a naturalistic psychedelic experience on alcohol use and related measures. Methods A retrospective online survey was conducted on 160 individuals who reported a psychedelic experience and a concomitant drinking habit but did not necessarily have an AUD. Demographic data, characteristics of the psychedelic experience, and changes in alcohol consumption and psychological flexibility were surveyed. Results: The mean number of drinking days per week and AUDIT scores significantly decreased after the psychedelic experience (P  < .001). Subjects who quit or reduced drinking had a more severe AUD (P  < .01) and lower psychological flexibility (P  = .003) before the psychedelic session. Alcohol use reduction was significantly associated with the intensity of the mystical experience (P  = .03). Psychological flexibility increased more in participants who reduced their alcohol use (P  < .001), and the change in psychological flexibility was one of the predictors of alcohol use improvement (P  = .003). Conclusion: Our findings suggest that a naturalistic psychedelic experience could be associated with a reduction in alcohol use and dependency. Such positive health outcomes can be associated with the intensity of the mystical experience as well as an increase in psychological flexibility. [ABSTRACT FROM AUTHOR]