Uniform Measure Research Articles

High throughput in-line content uniformity measurement of tablets based on real-time UV imaging.

This paper presents a precursor of a novel, high-throughput, in-line system, which utilizes ultraviolet (UV) imaging in order to predict the active pharmaceutical ingredient (API) content of tablets in real-time, non-destructive manner. Pimobendan, cardiovascular drug used in veterinary medicine was chosen as a fluorescent model API. Two experiments were carried out using different measurement setups, where the tablets were moving at different speeds. The blue colour components of the images were used to predict the pimobendan content of the tablets, and as a reference method, traditional UV spectroscopy was used to measure the API content of the dissolved tablets. In the case of the first, slower experiment (with a conveyor belt speed of 83 mm/s), a second order polynomial was fitted to the calibration tablets containing a nominal dose of 1.25, 5 and 10 mg of pimobendan and it was used to predict the API content. The RMSEP obtained was 0.428 mg for the validation tablets with a relative error as low as 7 % for the target level. For the second, faster experiment (1000 mm/s) the same polynomial was used to predict the pimobendan concentration of a different set of tablets, achieving a relative error of 2.03 %. Finally, the throughput of both systems was calculated to assess their applicability to meet the requirements of a pharmaceutical manufacturing line. The first system could inspect up to 93375 tablets per hour, while the second was able to process up to 360000 tablets in an hour, making it suitable for industrial application. By using these developed systems, the API content of all produced tablets could be determined non-destructively, which can greatly improve patient safety.

Effectiveness of Cognitive Remediation Interventions for Schizophrenia in Asian Population: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Background: Cognitive deficits are an integral part of schizophrenia, with negatively impacting functionality. Current treatments, primarily pharmacological, do not adequately address these cognitive impairments. Cognitive remediation (CR) interventions, designed to improve cognitive functions, have shown promising outcomes. However, most research has been conducted in western contexts, necessitating a review of CR effectiveness in the Asian populations. This systematic review aims to provide comprehensive update on the effectiveness of CR interventions in improving cognition among individuals with schizophrenia in Asian countries. The meta-analysis aims to synthesize and summarize the relevant CR studies to obtain a pooled estimate of effectiveness. Methods: A systematic search of three databases, PubMed, Ovid MEDLINE, and EMBASE, was conducted from the date of inception to March 19, 2024, for eligible records using prespecified search criteria. Primary studies with a randomized controlled trial (RCT) design, conducted on individuals aged 18–65 years, diagnosed with schizophrenia in Asian countries, comparing CR interventions with other non-pharmacological interventions or treatment as usual, reporting cognitive outcomes, using standardized tools, and published in English were included in the study. The review excluded unpublished RCTs, low-quality studies, open-label studies, cohort studies, studies focusing on noncognitive outcomes, and those lacking a clear comparison arm. The quality of the studies was assessed using the Cochrane risk of bias 2 (RoB2) tool by two independent reviewers. Meta-analyses were performed using R version 4.3.0 software using meta package to synthesize the overall impact of CR interventions on cognitive outcomes. Results and Discussion: This systematic review included 17 studies with 1272 participants, conducted in China, Japan, Hong Kong, Taiwan, Iran, Korea, and Singapore. The interventions varied in type and format. These were delivered through group and individual sessions, both in-person and computer-based, with varied duration. Quality assessment done with RoB2 tool indicated high-risk concerns in 14 of the studies. The meta-analysis of four studies on composite cognitive scores using the brief assessment of cognition in schizophrenia showed a significant positive effect of CR interventions (standardized mean difference [SMD] = 0.89, 95% confidence interval [CI]: 0.35 to 1.43). For executive functioning, the meta-analysis of three studies indicated no significant improvement (SMD = 0.75, 95% CI: −0.11 to 1.61). Conclusion: CR is an effective intervention for improving cognitive functions in individuals with schizophrenia in Asia based on the meta-analysis conducted, akin to evidence from western countries. However, quality concerns and high heterogeneity among the included studies underscore the need for standardized protocols and uniform outcome measures to enhance the reliability of future research.

Comparative Efficacy of Antipsychotic Medication for Stereotypic Behavior in Autism Spectrum Disorder: A Systematic Review and Meta-analysis

Background: Stereotypic movements in autism form core symptoms under the rubric of repetitive and restricted patterns of behavior. Aim: The systematic review was aimed to find which antipsychotic has better efficacy in treating stereotypic behavior in autism spectrum disorder. Methods: We searched for journal publications in the English from PubMed and Cochrane databases (CENTRAL), January 1992–June 2024, for randomized controlled trials that compared antipsychotics with a placebo of at least 6 weeks’ trial, with the outcome measure being a change in stereotypy score. Quality assessment of the included studies in the meta-analysis was done using Cochrane risk of bias tool version 2. We followed PRISMA guidelines for systematic review. The mean difference in change of stereotypy symptoms score was calculated between antipsychotic and placebo participants along with 95% confidence interval (CI) using the random-effects model. Results: 146 studies were screened, and 25 studies were deemed eligible to retrieve full-length articles for review. A total of nine studies were included in the systematic review that had used aripiprazole, risperidone, or lurasidone as an antipsychotic. Six studies (n = 726) that had all data on mean difference in stereotypy scores on the Aberrant Behavior Checklist (ABC)-Stereotypy subscale and four studies (n = 554) that reported stereotypy scores using Children’s Yale-Brown Obsessive Compulsive Scale (CY-BOCS)-Compulsions subscale were included in the meta-analysis. Antipsychotics showed a significant reduction in ABC-Stereotypy scores (−1.84 [−2.84, −0.85; 95% CI], Z = 3.83, P < 0.001) with moderate heterogeneity between the studies (I 2 = 53%). Whereas, antipsychotics did not show significant improvement in compulsions as measured on CY-BOCS (−0.87 [−1.89, 0.16; 95% CI], Z = 1.65, P = 0.10). Conclusion: Stereotypy in autism is difficult to measure, and no uniform measure exists. Trials are limited to short duration and limited to few antipsychotics. Among antipsychotics, risperidone has robust efficacy in reducing stereotypic behaviors.

Problem utożsamiania liczby porządkowej z rangą w polskich słownikach frekwencyjnych

THE PROBLEM OF IDENTIFYING AN ORDINAL NUMBER WITH A RANKING POLISH FREQUENCY DICTIONARIES The frequency dictionaries listed in the title contain three ranking lists based on the F index (absolute frequency), U index (relative frequency) and D index (measure of uniformity and distribution in styles). There are serious objections to the method used, according to which, when the F, U or D index values are equal, the entry rank (i.e. the number in the list) is decided by the alphabetical order. In case of words with high frequencies, each word is usually assigned a separate rank, because they differ in frequency. With increasingly lower frequencies, the same frequency is shared by a few, a dozen, a few hundred or even thousands of words (for example frequency 2 or 1). Words with the same frequency should have the same rank. In Polish frequency dictionaries, however, their rank differs depending on the alphabetical order. Hence, the ordinal number of a word is made equal to its rank. I believe that such method falls short of scholarly standards, because words with the same frequency differ considerably in rank. For example, in the Polish frequency dictionary (Słownik frekwencyjny polszczyzny współczesnej, Kraków 1990), words with frequency 4 are assigned ranks from 8739 (abstrahować) to 10355 (żywot) – a difference of 1616 places on the ranking list. For words with frequency 3, 2 and 1, the differences in the ranking list would be much greater. The ordinal number of words is not equated with their rank in, among others, frequency dictionaries of Slovak and Croatian as well as the Bulgarian dictionary of colloquial speech. Nevertheless, many frequency dictionaries of various languages do equate the number and the rank. Therefore, a discussion involving linguists interested in statistical linguistics is necessary.

A novel 3D uniformity measurement method in mechanical stirring systems

AbstractAccurate assessment of mixing uniformity is crucial in industrial mixing processes. This study proposes an evaluation method for three‐dimensional (3D) mixing processes that combines dual‐camera positioning and point pattern density fluctuation (PD) based on disordered hyperuniformity. This study employs a positioning method using dual‐camera to achieve precise capture and reconstruction of tracer particles in 3D space. The 3D reconstruction data is then evaluated for mixing performance using the PD method. A relationship model between |k| and time I values with mixing time was established for λ = 1. The results indicate that mixing time decreases with the increase of |k| and decreases with the decrease of I values. To ensure the accuracy of the PD method, feasibility analysis was conducted using conductometry. Additionally, the superiority of the PD method was validated by comparing it with the 3D‐Q method. The impact of bottom height of stirring paddle and motor speed on mixing effect were also investigated. This study establishes a fundamental groundwork and theoretical framework for optimizing parameters of stirring systems and assessing 3D mixing uniformity. It also offers important references and insights for engineering practices and theoretical research in related fields.

On the degree of uniformity measure for probability distributions

Abstract A key challenge in studying probability distributions is quantifying the inherent inequality within them. Certain parts of the distribution have higher probabilities than others, and our goal is to measure this inequality using the concept of mathematical diversity, a novel approach to examining inequality. We introduce a new measure m D (P), called the degree of uniformity measure on a given probability space that generalizes the idea of the slope of secant of the slope of diversity curve. This measure generalizes the idea of degree of uniformity of a contiguous part (P = {k 1, k 2} in the discrete case or P = (a, b) in the continuous case) in a probability space related to a random variable X, to an arbitrary measurable part P. We also demonstrate the truly scale free and self-contained nature of the concept of degree of uniformity by relating the measure of two parts P 1 and P 2 from completely unrelated distributions with random variables X 1 and X 2 that have completely different scales of variation.

Modeling wear of different surface layers of agricultural tools in soil abrasive mass

Uniform quantitative measures have not been developed to identify the areas with the greatest intensification of tool wear. Therefore, this paper developed original approach to assess the wear of cutting elements by identifying the intensity of local volumetric wear. A tribological test was conducted under natural operating conditions in two soil types: sandy loam and loam. The specimens were mounted on a 9-tined cultivator with spring tines aggregated with an agricultural tractor. A method was developed to discretise the local volume changes of a component using surface scanning models developed from 3D scanning. The notion of the rake angle has been defined, allowing the assessment of changes in the shape of the element during wear. The practical usefulness of the developed method was verified on three types of surface layers, i.e. 38GSA steel, ELHARD70 deposited on it, and a G10 layer of carbide. For each of the tested variants, local volumetric consumption was defined based on the identification of the wear grid. These should be the basis for developing the technology of surface strengthening of elements. The work confirmed the complexity of the process of wear of working elements in natural soil conditions, presented in many research works. A different course of wear of the 38GSA steel and the Elhard 70 weld layer was shown, depending on the type of treated soil. In the case of samples made of G10 cemented carbide, the largest volumetric wear for heavy soil occurred outside the place of reinforcement application. The highest volumetric wear in the front zone was recorded for 38GSA steel in heavy soil. Wear results from the modelling are similar to those obtained from the experiment under natural conditions in light soil using the nominal model (CAD) and the actual friction surface.

Uniform measure attractors for nonautonomous stochastic tamed 3D Navier–Stokes equations with almost periodic forcing

This article provides a characterization of uniform measure attractors for non-autonomous stochastic tamed 3D Navier–Stokes equations, specifically with a almost-periodic external force term. The existing literature has primarily focused on measure attractors within an autonomous framework; however, when the forcing function is almost periodic, the solution process generated by the corresponding equations behaves as a non-autonomous Markov process, rendering the existing framework inapplicable. Therefore, it is crucial to investigate this within a new framework, which is the motivation behind the study of uniform measure attractors in this paper.

Hybrid leader corona virus herd optimizer with multilevel thresholding techniques for foreground and background image segmentation

In computer vision and image processing, an important role is given to image segmentation. As it can accurately extract and identify specific regions within an image. One of the key challenges that remain in this is achieving precise recognition and extraction of segmented regions. This can be solved by multilevel optimization techniques and this offers an effective solution. Recently, multilevel thresholding has emerged as an important technique for image segmentation as the separation of image pixels into various classes by the selection of optimal threshold values. However, when the number of thresholds increases, the computational complexity of multilevel thresholding also increases. To address this issue, various optimization algorithms are employed by the researchers. Thus, the Hybrid optimization techniques are integrated to enhance the overall efficacy of image segmentation processes. Thus, this research devised a Multithreshold-Hybrid Leader Coronavirus Herd Optimizer+kernel based Bayesian fuzzy clustering (Multithreshold-HLCHO+kernel-BFC) for the segmentation of foreground and background images. Here, the noise from the input image is removed using the Non-Local Means (NLM) filter and also the region of interest (ROI) extraction is done. The foreground and background image segmentation is done using the multilevel thresholding techniques, wherein threshold values are optimally generated utilizing HLCHO with multiobjectives like Renyi, Masi and Tsallic. Moreover, the integration of Hybrid Leader Based Optimization (HLBO) with Coronavirus Herd Immunity Optimizer (CHIO) forms the HLCHO. Also, the kernel-based BFC is employed for the segmentation of background and foreground images. Finally, the segmented output is achieved by fusing these two outputs using a fusion process. Additionally, Multithreshold-HLCHO+kernel-BFC acquired a maximum value of 0.891 for dice coefficient, 37.174 dB for PSNR, 0.918 for uniformity measure, and 0.297 for Mean Squared error (MSE).

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

ABSTRACT High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. To elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

A-171 Novel Fluorometric Assay for Pediatric Anti-Factor Xa Testing: Minimizing Bilirubin and Hemolysis Interference in Whole Blood

Abstract Background High bilirubin levels are common in pediatric patients and are noted in patients undergoing extracorporeal membrane oxygenation (ECMO). Acute anticoagulation therapy necessitates frequent monitoring of anti-Factor Xa activity (aFXa), and high bilirubin levels cause interference in chromogenic assays. Moreover, large volumes of blood lead to iatrogenic anemia in pediatric and neonatal patients. We developed a fluorescence assay to measure aFXa activity on a near-patient digital microfluidic (DMF) platform using low volume whole blood samples (< 50 μL) and present the results of interference of bilirubin and hemolysis on aFXa activity. Methods aFXa assay was performed on a DMF cartridge wherein 50 μL whole blood was loaded into the cartridge which separates plasma droplets through agglutination within the cartridge followed by incubation with a droplet containing exogenous FXa and a fluorogenic substrate. The fluorescence is inversely proportional to the concentration of heparin in the sample. All required reagents for the aFXa assay are dried within the cartridge, allowing for integrated sample preparation and assay automation for point of care use. To test the interference of bilirubin, we spiked into whole blood different concentrations of unconjugated bilirubin, ranging from 0-40 mg/dL. We also tested hemoglobin interference by testing 4 different concentrations of hemolysate (0-1,000 mg/dL) on the aFXa assay. All experiments were performed with 6 replicates of each concentration. Results Across each bilirubin concentration, we saw uniform measurements of aFXa activity (see Table). We observed < 5% CV in aFXa activity with 0, 13.33 and 26.67 mg/dL bilirubin levels. All measured unfractionated heparin values for hemolysate interference were <5% CV. Conclusions Our interference results suggest that high bilirubin and hemolysate levels do not interfere with our novel aFXa fluorescence assay. Further clinical studies are underway to establish clinical performance.

Emaciated enigma: Decline in body conditions of common dolphins in the Celtic Seas ecoregion

AbstractMonitoring the nutritional health of cetaceans has become increasingly important in a changing environment, where multiple stressors impact animals. Particularly for those species that require consumption of energy‐dense prey, such as the common dolphin. Thus far, no uniform measure for monitoring body condition has been recommended across cetaceans, and species‐specific measures may need to be developed if employed as a population condition indicator under Descriptor 1 of the Marine Strategy Framework Directive. Here, nine morphometric body condition indices were applied to long‐term common dolphin stranding data sets originating from Ireland and the UK. We report a recent decline in the nutritional health of common dolphins in the Celtic Seas ecoregion comparing animals from 2017 to 2019 to animals from 1990 to 2006, with an increase in cases of animals dying due to starvation. Using ordinal regression trees, ventral blubber thickness (VBT) was identified as the most important index to predict nutritional status, defined at necropsy, followed by the scaled mass index (SMI). Using generalised linear models, both the VBT and SMI indices differentiated individuals that died from chronic and acute causes of death (i.e., bycatch), where animals in chronic conditions had significantly thinner VBT and lower SMI. Both significant temporal and seasonal patterns in VBT were identified, with poorer body conditions observed during the autumn and better body conditions observed during the spring, as well as an overall decline detected in VBT during the study period. While VBT was positively correlated with total body length, SMI showed the opposite trend. The VBT index is recommended for monitoring nutritional health within the species when total body length and season are considered. Further research is needed to understand the underlying causes for the observed decline, including shifts in prey availability and/or quality, to inform targeted conservation management strategies.

Integrated modelling of fertilizer and climate change scenario impacts on agricultural production and nitrogen losses in Austria

The European Commission's Farm to Fork strategy aims at reducing nutrient losses and fertilizer use, but has been criticized for its expected negative impacts on European economy, agriculture, and food supply. We apply an integrated modelling framework to analyze potential effects of fertilizer reductions on land use, nitrogen losses, and agricultural output of two fertilizer and four climate change scenarios. The fertilizer scenarios comprise a uniform 20 % reduction of mineral N fertilizer (f20) and a combination of several fertilizer restrictions (fcm). The model results indicate that the restrictions in fertilization lead to decreases in crop production of 6 to 9 %, whereas intensive and extensive grassland production increases. N losses to air, water, and soil are substantially reduced by 9 % (f20) and 20 % (fcm), yet fall short of the intended 50 % reduction. The regional heterogeneity of the model results shows that tailored measures need to be elaborated by taking climate change developments, the regional heterogeneity of prevalent farming systems, and bio-physical conditions into account. Uniform measures applied to the national policy context fall short to attain policy targets cost-effectively. N emission capping, taxes or managerial measures such as crop rotational N balancing are options to be explored in future research.

The Gromov–Wasserstein Distance Between Spheres

AbstractThe Gromov–Wasserstein distance—a generalization of the usual Wasserstein distance—permits comparing probability measures defined on possibly different metric spaces. Recently, this notion of distance has found several applications in Data Science and in Machine Learning. With the goal of aiding both the interpretability of dissimilarity measures computed through the Gromov–Wasserstein distance and the assessment of the approximation quality of computational techniques designed to estimate the Gromov–Wasserstein distance, we determine the precise value of a certain variant of the Gromov–Wasserstein distance between unit spheres of different dimensions. Indeed, we consider a two-parameter family $$\{d_{{{\text {GW}}}p,q}\}_{p,q=1}^{\infty }$$ { d GW p , q } p , q = 1 ∞ of Gromov–Wasserstein distances between metric measure spaces. By exploiting a suitable interaction between specific values of the parameters p and q and the metric of the underlying spaces, we are able to determine the exact value of the distance $$d_{{{\text {GW}}}4,2}$$ d GW 4 , 2 between all pairs of unit spheres of different dimensions endowed with their Euclidean distance and their uniform measure.

Development of a core outcome set of clinical research on the integration of traditional Chinese and Western medicine for spinal metastases: a study protocol

BackgroundIn recent years, the incidence of spinal metastasis (SM) has been increasing steadily. In response to this serious public health problem, researchers have made progress by using the integration of...

The Distribution of Planet Radius in Kepler Multiplanet Systems Depends on Gap Complexity

The distribution of small planet radius (<4 R ⊕) is an indicator of the underlying processes governing planet formation and evolution. We investigate the correlation between the radius distribution of exoplanets in Kepler multiplanet systems and the system-level complexity in orbital period spacing. Utilizing a sample of 234 planetary systems with three or more candidate planets orbiting FGK main-sequence stars, we measure the gap complexity (C) to characterize the regularity of planetary spacing and compare it with other measures of period spacing and spacing uniformity. We find that systems with higher gap complexity exhibit a distinct radius distribution compared to systems with lower gap complexity. Specifically, we find that the radius valley, which separates super-Earths and sub-Neptunes, is more pronounced in systems with lower gap complexity (C < 0.165). Planets in high-complexity systems (C > 0.35) exhibit a lower frequency of sub-Earths (2.5 times less) and sub-Neptunes (1.3 times less) and a higher frequency of super-Earths (1.4 times more) than planets in low-complexity systems. This may suggest that planetary systems with more irregular spacings are more likely to undergo dynamic interactions that influence planet scattering, composition, and atmospheric retention. The gap complexity metric proves to be a valuable tool in linking the orbital configurations of planets to their physical characteristics.

Circular-ESG Model for Regenerative Transition

This paper presents a novel circular-ESG framework integrating circular economy (CE) principles with environmental, social, and governance (ESG) criteria to address the lack of uniform sustainability measures. We introduce normalized sustainability coordinates (NSCs) as a comprehensive metric for sustainability performance, reconciling economic development with environmental balance. The circular-ESG model employs a four-quadrant Cartesian system to map business model impacts on natural and socio-economic systems, ranging from linear open-loop to circular closed-loop ESG models. This framework enables empirical analysis through data-driven NSCs (−1 to 1) and establishes temporal key performance indicators. By incorporating the Human Development Index within ecological limits, the model promotes regenerative development aligned with planetary boundaries. The circular-ESG approach offers a practical tool for businesses, households, organizations, and policymakers to navigate sustainable development complexities. This integrated framework fosters innovation and supports a just transition towards regenerative practices, providing a roadmap for high human development within ecological limits. The circular-ESG model advances sustainability science and management, contributing to the discourse on measuring and implementing sustainable practices across sectors and scales. The model is currently conceptual; we encourage empirical validation and further research to explore its practical applications and effectiveness in real-world scenarios. While the provided examples of use cases serve as conceptual demonstrations, future research could empirically apply the model to real-world data.

Unsupervised machine learning application in the selection of measurement strategy on Coordinate Measuring Machine

It is indisputable that some type of coordinate measurement system (CMS) is generally used to assess the quality of dimensional and geometric characteristics. Considering the required accuracy, flexibility, and speed of measurement, a CMM with a scanning sensor may offer the best performance. These measurement systems are very complex, and many factors affect the reliability of the measurement results. A Metrologist’s choice represents the greatest variability in the measurement strategy. Previous research has shown that the measurement results can be changed up to 100 % by choosing a different measurement strategy when evaluating the form error. This paper conducts a detailed study of the impact of the measurement strategy on the cylindricity error when measuring eleven workpieces with the same nominal characteristics, but different real characteristics described by roughness and the reference value of cylindricity. To examine the influence and importance of certain factors and their levels, design of experiment (DoE) and unsupervised machine learning techniques of PCA (Principal Component Analysis) and Multiple Correspondence Analysis (MCA), were used. The results suggest that depending on the real geometry of the workpiece, different factors with different percentages influence the output characteristic. The objective was to choose a uniform measurement strategy when measuring cylindricity on the CMM, while the prior information about the actual geometry of the workpiece is lacking.

Germany under the Tinfoil Hat? The associations of the big five personality traits and coronavirus conspiracy beliefs with the intention to get vaccinated

BackgroundThe governments of democracies worldwide are relying on the active cooperation of their populations to combat COVID-19. Simultaneously, beliefs in conspiracy theories surrounding the pandemic have flourished. The present article examines the effects of the big five personality traits and conspiracy beliefs on the intention to get vaccinated against COVID-19 in Germany. MethodsThis correlational, cross-sectional mediation analysis was conducted using data from a nationwide German household panel (N = 1390). ResultsOpenness to experience (β = −.082, p = .004) and neuroticism (β = .112, p < .001) showed direct effects on conspiracy beliefs, while conspiracy beliefs had the strongest effect on vaccination intention (β = −.424, p < .001). Indirect positive effects of openness (β = .035, p = .005) and negative effects of neuroticism (β = −.047, p < .001) on the intention to get vaccinated via conspiracy beliefs were identified, with a mediation in the strict sense only for openness. No direct or total effect of the big five on vaccination intention could be found. ConclusionsThe big five personality traits are associated, although indirectly, with the intention to be vaccinated. Compared with similar studies on the effects of the big five on COVID-19-related outcomes, we found slightly higher proportions of explained variance in conspiracy beliefs and significantly higher explained variance in vaccination intention. In order to increase the willingness to be vaccinated, targeted and nationwide uniform information measures should be provided addressing feelings of security, of not being excluded, and the activation of critical reasoning.

Palliative care outcome measures used in head and neck cancer: A scoping review.

The palliative care (PC) needs of patients with head and neck cancer (HNC) are complex, due to high and unique symptom burdens. Uniform outcome measures are critical to assessing the impact of PC interventions in HNC. A scoping review of outcome measures used in patients with HNC receiving PC was performed using PubMed, Embase, and Web of Science from 1980 to 2022. Of 20 eligible studies, 19 unique instruments were identified which assessed 22 physical, 5 mental, 4 social, 7 related quality of life, and 9 advanced care planning outcomes. Instruments were underutilized, with a larger number of outcomes measurable for instruments used than were reported. The average instrument assessed three domains whereas the average study only reported outcomes from two domains. Comparison across studies is limited due to heterogeneity in outcome measures. Future work is needed to develop core PC outcome measures for use in HNC care.