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Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of teachers in each grade. This limited teacher-level sample size may pose potential challenges for study design, analysis, and reporting. The current study aims to evaluate the impacts of small teacher-level sample sizes on study design, analysis, and reporting in cluster-randomized trials. Through a simulation study, we show that the intraclass correlation coefficients at the teacher and school levels are prone to biased estimates in many cases, especially when the student-level sample size is also small. One design strategy we recommend is to sample a large number of students per teacher as this will alleviate the impacts of small teacher-level sample sizes. We recommend that researchers use the total variance, if available, rather than school-level variance to report standardized treatment effects for a meta-analysis. When the total variance is not available for all studies, researchers should use a school-level variance in two-level models as the base for standardization to reduce biases. [ABSTRACT FROM AUTHOR]

Due to the adverse health effects of PM2.5 (particles with a diameter less than 2.5 μm), the national ambient air quality standards (NAAQS) for PM2.5 have been established in many countries. Ambient PM2.5 concentrations are monitored to determine compliance with the NAAQS, where beta attenuation monitors (BAMs) are widely used as a reference method. However, the high costs of installation and maintenance of BAMs result in difficulties in enhancing the spatial resolution of PM2.5 monitoring. In this context, low-cost PM2.5 sensors (LCSs) have been widely deployed for PM2.5 measurements. Despite their low cost and ease of installation, concerns regarding the data reliability of LCSs remain unresolved, necessitating further field research under various environmental conditions. In this study, we conducted a data comparability assessment between 125 LCSs and two BAMs over 12 months. Daily average PM2.5 concentrations measured by LCSs generally agreed with those from BAMs. However, when comparing hourly PM2.5 data, we found that the data comparability of LCSs against BAMs was lower than that of the daily average data, primarily influenced by ambient PM2.5 levels. Additionally, we found statistical differences in PM2.5 concentrations among six regions within the study area. This indicates that ambient PM2.5 levels can vary within a small area, supporting the necessity of monitoring PM2.5 on a small scale. Overall, the results of this study suggest that the sensors demonstrate both potential and limitations in PM2.5 monitoring. Therefore, to use LCSs for PM2.5 monitoring, it is necessary to appropriately select the averaging time and PM2.5 concentration ranges, considering local environmental conditions and the inherent characteristics of LCSs. [ABSTRACT FROM AUTHOR]

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test–retest reliability of these tasks in 262 PD participants and 50 controls by evaluating machine learning models based on wearable-sensor-derived measures and statistical metrics. This evaluation examines total duration, subtask duration, and other quantitative measures across two trials. We show that the diagnostic accuracy for distinguishing PD from controls decreases by a mean of 1.8% between the first and the second trial, suggesting that task repetition may not be necessary for accurate diagnosis. Although the total duration remains relatively consistent between trials (intraclass correlation coefficient (ICC) = 0.62 to 0.95), greater variability is seen in subtask duration and sensor-derived measures, reflected in machine learning performance and statistical differences. Our findings also show that this variability differs not only between controls and PD participants but also among groups with varying levels of PD severity, indicating the need to consider population characteristics. Relying solely on total task duration and conventional statistical metrics to gauge the reliability of mobility tasks may fail to reveal nuanced variations in movement. [ABSTRACT FROM AUTHOR]

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Heterogeneity of outcomes across different clinical trial study sites is often inevitable. Understanding how outcomes differ by site is important for planning future programs and studies. We examined the extent of heterogeneity of hepatitis C virus (HCV) treatment cascade outcomes among persons who inject drugs (PWIDs) across sixteen clinical sites utilized in the HERO Study—a pragmatic randomized trial of HCV treatment support. Treatment cascade outcomes included averages of overall treatment adherence and proportions of treatment initiation, treatment completion, sustained virologic response (SVR) test completion, and SVR achievement. The HERO study utilized 16 clinical sites across the United States (US): eight opioid treatment programs (OTPs) and eight community health centers (CHCs). Variability of the outcomes across the 16 clinical sites was assessed using ranges and intraclass correlation coefficients (ICC) estimated from mixed-effects linear or logistic regression models. Treatment initiation was analyzed in the intention-to-treat (ITT) sample (N = 755); treatment completion, adherence, and SVR test completion in the modified ITT (mITT) sample, which is the sample that initiated treatment (N = 623); and SVR achievement in the mITT and per-protocol (PP, N = 501) samples. Across the 16 clinical sites, the range observed in the averages of overall treatment adherence was from 68% to 81% [ICC = 0.026 (0.005, 0.054)], and the ranges of proportions observed were from 68% to 96% for treatment initiation [ICC (95% CI) = 0.086 (0.051, 0.155)], 60% to 100% for treatment completion [ICC = 0.049 (0.008, 0.215)], 54% to 95% for SVR test completion [ICC = 0.096 (0.006, 0.177)], 46% to 90% for SVR achievement in the mITT sample [ICC = 0.070 (0.014, 0.122)], and 76% to 100% for SVR achievement in the PP sample [ICC = 0.143 (0.021, 0.422)]. The variability of the outcomes across 16 US sites treating HCV among PWIDs appears to be substantial in view of the ranges and ICC values of the outcomes. It is imperative to develop tailored interventions to target the sources of variability and reduce barriers at the patient, provider, clinic, and state policy levels to facilitate more equitable access to HCV treatment and reduce heterogeneity in treatment outcomes. [ABSTRACT FROM AUTHOR]

Summary: For the first time, we determined whether actigraphic‐assessed sleep measures show inter‐individual differences and intra‐individual stability during baseline (BL) and recovery (REC) phases surrounding repeated total sleep deprivation (TSD). We conducted a 5‐day experiment at Months 2 and 4 in two separate studies (N = 11). During each experiment, sleep measures were collected via wrist actigraphy during two BL 8 h time‐in‐bed (TIB) nights (B1, B2) and during two REC 8–10 h TIB nights (R1, R2). Intraclass correlation coefficients (ICCs) assessed actigraphic measure long‐term stability between 2 and 4 months for (1) the pre‐experimental phase before BL; and (2) the BL (B1 + B2), REC (R1 + R2), and BL and REC average (BL + REC) phases; and short‐term stability at Month 2 and at Month 4; and (3) between B1 versus B2 and R1 versus R2 in each 5‐day experiment. Nearly all ICCs during the pre‐experimental, BL, REC, and BL + REC phases were moderate to almost perfect (0.446–0.970) between Months 2 and 4. B1 versus B2 ICCs were more stable (0.440–0.899) than almost all R1 versus R2 ICCs (−0.696 to 0.588) at Month 2 and 4. Actigraphic sleep measures show phenotypic long‐term stability during BL and REC surrounding repeated TSD between 2 and 4 months. Furthermore, within each 5‐day experiment at Month 2 and 4, the two BL nights before TSD were more stable than the two REC nights following TSD, likely due to increased R1 homeostatic pressure. Given the consistency of actigraphic measures across the short‐term and long‐term, they can serve as biomarkers to predict physiological and neurobehavioral responses to sleep loss. [ABSTRACT FROM AUTHOR]

Background: Hip-preserving surgery in young patients frequently reveals lesions of the ligamentum teres (LT). Histological and clinical evidence supports that those lesions could be source of intraarticular hip pain. It has been hypothesized that LT degeneration could be linked to the abnormal positioning of the fovea outside the lunate surface during various daily motions. We introduce the "fossa-foveolar mismatch" (FFM) by determining the trajectory of the fovea in the fossa during hip motions, enabling a comparison across diverse hip-pathomorphologies. Aims: to determine (1) intraobserver reliability and (2) interobserver reproducibility of our computer-assisted 3-dimensional (3D) model of the FFM. Materials and methods: All patients with joint preserving surgery for femoroacetabular impingement syndrome (FAIS) or developmental dysplasia of the hip (DDH) at our institution (11. 2015–08.2019)were initially eligible. We employed a simple random sampling technique to select 15 patients for analysis. Three-dimensional surface models based on preoperative computed tomography (CT) scans were built, the fossa virtually excised, the fovea capitis marked. Models were subjected to physiological range of motion with validated 3D collision detection software. Using a standardized medial view on the resected fossa and the transparent lunate surface, the FFM-index was calculated for 17 motions. It was obtained by dividing the surface occupied by the fovea outside of the fossa by the total foveolar tracking surface. Three observers independently performed all analyses twice. (1) Intraobserver reliability and (2) interobserver reproducibility were calculated using intraclass correlation coefficients (ICCs). Results: (1) We obtained excellent intraobserver ICCs for the FFM-index averaging 0.92 with 95% CI 0.77–0.9 among the three raters for all motions. (2) Interobserver reproducibility between raters was good to excellent, ranging from 0.76 to 0.98. Conclusions: The FFM-index showed excellent intraobserver reliability and interobserver reproducibility for all motions. This innovative approach deepens our understanding of biomechanical implications, providing valuable insights for identifying patient populations at risk. [ABSTRACT FROM AUTHOR]

The impact of text length on the estimation of lexical diversity has captured the attention of the scientific community for more than a century. Numerous indices have been proposed, and many studies have been conducted to evaluate them, but the problem remains. This methodological review provides a critical analysis not only of the most commonly used indices in language learning studies, but also of the length problem itself, as well as of the methodology for evaluating the proposed solutions. Analysis of three data sets of texts produced by English language learners revealed that indices that reduce all texts to the same length using a probabilistic or an algorithmic approach solve the length‐dependency problem; however, all these indices failed to address the second problem, which is their sensitivity to the parameter that determines the length to which the texts are reduced. The paper concludes with recommendations for optimizing lexical diversity analysis. A one‐page Accessible Summary of this article in nontechnical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

In this study, using data from evaluations of 20 companies by seven raters in a corporate award on the theme of human resource management, I examined the consistency of company evaluations by a small number of experts in different fields and the criterion-related validity of the mean evaluations per company. The evaluation was conducted in the order of documents and interviews, and each was rated on five items. The intraclass correlations showed that the evaluations of "philosophy," "innovation," "leadership," and "motivation" were consistent across raters and that the interview evaluations were more consistent than the document evaluations. Regarding "personnel" evaluations, significant consistency was found only for document evaluations. The correlations between the mean evaluations and indices of application documents showed that companies with more text in their application documents tended to be evaluated more highly. It was confirmed that the few experts' evaluations of the companies had a moderate degree of consistency and validity; however, it was also suggested that some combinations of evaluation items and evaluation materials may not have resulted in appropriate evaluations. [ABSTRACT FROM AUTHOR]

Aim: The objective of this study was to assess the validity, reliability, and reproducibility of dental arch measurements between conventional study models and digital study models. Materials and Methods: The study sample comprised 50 pretreatment diagnostic conventional study models. Six dental arch measurements were assessed. The conventional study model's measurements were done with digital vernier caliper (Precision, IP54). For three-dimensional (3D) model measurements, scanning of the conventional study models was done with the Maestro 3D dental scanner (Italy). Results: Measurement on conventional study models shows the mean value of the upper arch length was 72.33 and the mean value of the lower arch length was 64.68 for the conventional study model and the mean value of the upper arch length was 72.41 and the mean value of lower arch length was 63.11 for 3D model. There was a statistical difference between the measurements of overjet and overbite obtained between the study model and the 3D model. There was no statistical difference in intermolar width, intercanine width, and arch length of both the arches and curve of spee between conventional study models and 3D models. The Cronbach's alpha (internal consistency) ranged from 0.81 to 1, intraclass correlation ranged from 0.70 to 0.99, and the concordance correlation coefficient ranged from 0.81–1, respectively, for various arch parameters. Conclusion: Digital study models were accurate, efficient, and easy-to-use alternatives to conventional study models. Hence, dental arch measurements of digital study models were as valid, reliable, and reproducible compared to conventional study models for all arch parameters except nonvalidity was observed for overjet and overbite measurement in the study. [ABSTRACT FROM AUTHOR]

Abstract In this work, we present a novel preclinical device utilizing Torsional Wave Elastography (TWE). It comprises a rotational actuator element and a piezoceramic receiver ring circumferentially aligned. Both allow the transmission of shear waves that interact with the tissue before being received. Our main objective is to demonstrate and characterize the reliability, robustness, and accuracy of the device for characterizing the stiffness of elastic materials and soft tissues. Experimental tests are performed using two sets of tissue mimicking phantoms. The first set consists of calibrated CIRS gels with known stiffness value, while the second test uses non-calibrated manufactured phantoms. Our experimental observations show that the proposed device consistently and repeatably quantifies the stiffness of elastic materials with high accuracy. Furthermore, comparison with established techniques demonstrates a very high correlation (> 95%), supporting the potential medical application of this technology. The results obtained pave the way for a cross-sectional study aiming to investigate the correlation between gestational age and cervical elastic properties during pregnancy.

In this work, we present a novel preclinical device utilizing Torsional Wave Elastography (TWE). It comprises a rotational actuator element and a piezoceramic receiver ring circumferentially aligned. Both allow the transmission of shear waves that interact with the tissue before being received. Our main objective is to demonstrate and characterize the reliability, robustness, and accuracy of the device for characterizing the stiffness of elastic materials and soft tissues. Experimental tests are performed using two sets of tissue mimicking phantoms. The first set consists of calibrated CIRS gels with known stiffness value, while the second test uses non-calibrated manufactured phantoms. Our experimental observations show that the proposed device consistently and repeatably quantifies the stiffness of elastic materials with high accuracy. Furthermore, comparison with established techniques demonstrates a very high correlation (> 95%), supporting the potential medical application of this technology. The results obtained pave the way for a cross-sectional study aiming to investigate the correlation between gestational age and cervical elastic properties during pregnancy. [ABSTRACT FROM AUTHOR]

Objective: In this work, we propose a novel method for constructing wholebrain spatio-temporal multilayer functional connectivity networks (FCNs) and four innovative rich-club metrics. Methods: Spatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male-female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis. Results: The proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients. Conclusion: The proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNCPC) and conventional virtual non-contrast (VNCConv) algorithm were compared with true non-contrast (TNC) series. Methods: RFs of EAT from 52 patients who underwent PCCT were quantified using VNCPC, VNCConv, and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson's correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75. Results: the VNCPC and VNCConv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNCPC series showed higher correlation and agreement with TNC than VNCConv series. All types of RFs from VNCPC series showed greater reproducibility than VNCConv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters. Conclusion: The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNCPC series make it an excellent substitute for TNC series exceeding VNCConv series. [ABSTRACT FROM AUTHOR]

Degradation models based on heterogeneous Wiener processes are commonly used to assess information on the lifetime of highly reliable products. An optimal test plan given limited resources is generally obtained using numerical methods for heterogeneous Wiener processes. However, numerical searches for optimal test plans have the disadvantage of being time‐consuming and may provide unclear explanations for the findings. To overcome these difficulties, we derive an explicit expression for decision variables (such as the termination time, number of measurements, and sample size) of D$$ D $$‐ and V$$ V $$‐optimal test plans with cost constraints. The theoretical results not only ensure that the optimal test plan is found, but also provide clear insights into the decision variables affected by model parameters and experimental costs. Some numerical examples are presented to support the efficiency and applicability of the optimal test plans. [ABSTRACT FROM AUTHOR]

Even when raters demonstrate agreement in the use of a measure, limited score variability or violation of often-ignored statistical assumptions can result in lower reliability estimates than intuitively expected. This article uses data drawn from two randomized controlled trials of schema therapy and cognitive behavioral therapy for the treatment of major depression and binge eating disorder or bulimia nervosa (N = 212) to illustrate the limits of the intraclass coefficient. Randomly selected therapy sessions were rated for therapeutic alliance quality by independent observers using the well-validated Vanderbilt Psychotherapy Process Scale and Vanderbilt Therapeutic Alliance Scale. Scores on subscales related to therapist behavior were restricted, indicating consistent alliance-supportive actions. Inter-rater reliability estimates were low despite high agreement between raters, however. The use of Bland–Altman plots to visualize agreement and data spread is suggested as a useful tool for researchers, consistent with the ideal of exploring reliability from a number of perspectives. [ABSTRACT FROM AUTHOR]

The main aim of this study is to use comprehensive statistical analyses to evaluate measurement reliability of selected variables that characterize postural stability. The study examined twenty-nine healthy non-athlete students. The examinations were performed twice, with a one-week interval. The Microgate GYKO inertial sensor system was used to evaluate the reliability of variables that characterize postural stability. The relative reliability of the repeated test was evaluated using the intraclass correlation coefficient (ICC) with 95% confidence interval (95% CI). Next, the standard error of measurement (SEM) and minimal detectable change (MDC) were computed. Relative reliability of the repeated test for all analysed variables of ICC ranged from 0.31 to 0.75. For four variables, ICC values were ca. 0.7, i.e., they can be considered as good. For four other variables, ICC ranged from 0.41 to 0.54, with these values considered fair. Satisfactory reproducibility of postural stability measurements using the GYKO inertial sensor system demonstrates that it can offer an inexpensive and efficient alternative to measurements that use force balance platforms. [ABSTRACT FROM AUTHOR]

Stepped wedge design is a popular research design that enables a rigorous evaluation of candidate interventions by using a staggered cluster randomization strategy. While analytical methods were developed for designing stepped wedge trials, the prior focus has been solely on testing for the average treatment effect. With a growing interest on formal evaluation of the heterogeneity of treatment effects across patient subpopulations, trial planning efforts need appropriate methods to accurately identify sample sizes or design configurations that can generate evidence for both the average treatment effect and variations in subgroup treatment effects. To fill in that important gap, this article derives novel variance formulas for confirmatory analyses of treatment effect heterogeneity, that are applicable to both cross‐sectional and closed‐cohort stepped wedge designs. We additionally point out that the same framework can be used for more efficient average treatment effect analyses via covariate adjustment, and allows the use of familiar power formulas for average treatment effect analyses to proceed. Our results further sheds light on optimal design allocations of clusters to maximize the weighted precision for assessing both the average and heterogeneous treatment effects. We apply the new methods to the Lumbar Imaging with Reporting of Epidemiology Trial, and carry out a simulation study to validate our new methods. [ABSTRACT FROM AUTHOR]

Abstract Repeatability involves the assessment of the agreement among repeated measurements from the same cluster of subjects, and this concept has been widely used in different scientific fields when data is structured in clusters. In the context of spatial trajectories, a degree of repeatability implies that individual trips can be distinguished from those of other individuals. Repeatability is usually assessed by the intraclass correlation coefficient (ICC), which is defined as the proportion of the total variance accounted for by among‐subject variability. However, where data are spatial trajectories the common approach to estimate the ICC does not apply because data involves sets of ordered spatial locations rather than single values. In this work, a novel approach based on spatial distances is proposed to estimate the ICC to assess the repeatability of spatial trajectories. The methodology is illustrated with a real case example of the flight trajectories of 36 Audouin's gulls (Ichthyaetus audouinii) moving through a heterogeneous landscape over a period of 18 days. Additionally, simulations were used to evaluate the performance of the approach under various scenarios. I demonstrate that ICC can be estimated on complex, spatially ordered data such as spatial trajectories, when using the appropriate spatial distance.

Background: Surgeon visual estimation of shoulder range of motion (ROM) is commonplace in the outpatient office setting and routinely reported in clinical research, but the reliability and accuracy of this practice remain unclear. The purpose of this study is to establish the reliability and accuracy of remote visual estimation of shoulder ROM in healthy volunteers and symptomatic patients among a large group of shoulder surgeons. Our hypothesis is that remote visual estimation would be reliable and accurate compared with the digital goniometer method. Methods: Fifty shoulder surgeon members of the PacWest Shoulder and Elbow Society independently determined the active shoulder forward flexion (FF), internal rotation at 90° abduction (IR90), external rotation at 90° abduction, external rotation at the side , and maximal spinal level reached with internal rotation (IRspine) through visual estimation of video recordings taken from 10 healthy volunteers and 10 symptomatic patients. Variations in measurements were quantified using the interobserver reliability through calculation of the intraclass correlation coefficient. Accuracy was determined through comparison with digital goniometer measurements obtained with an on-screen protractor application using Bland–Altman mean differences and 95% limits of agreement. Results: The interobserver reliability among examiners showed moderate to excellent correlation, with intraclass correlation coefficient ranging from 0.768 to 0.928 for the healthy volunteers and 0.739 to 0.878 for the symptomatic patients. Accuracy was limited, with upper limits of agreement exceeding the established minimal clinically important differences (MCIDs) for FF (20° vs. MCID of 14°) and IR90 (25° vs. 18°) in the healthy volunteers and for FF (33° vs. 16°), external rotation at 90° abduction (21° vs. 18°), and IR90 (31° vs. 20°) in the symptomatic patients. Conclusion: Despite generally high intersurgeon reliability in the visual estimation of shoulder ROM, there was questionable accuracy when compared to digital goniometer measurements,with measurement errors often exceeding established MCID values. Given the potential implications for the clinical response to treatment and the significance of research findings, the adoption of validated instruments to measure ROM and the standardization of examination procedures should be considered.

The main aim of this study is to use comprehensive statistical analyses to evaluate measurement reliability of selected variables that characterize postural stability. The study examined twenty-nine healthy nonathlete students. The examinations were performed twice, with a one-week interval. The Microgate GYKO inertial sensor system was used to evaluate the reliability of variables that characterize postural stability. The relative reliability of the repeated test was evaluated using the intraclass correlation coefficient (ICC) with 95% confidence interval (95% CI). Next, the standard error of measurement (SEM) and minimal detectable change (MDC) were computed. Relative reliability of the repeated test for all analysed variables of ICC ranged from 0.31 to 0.75. For four variables, ICC values were ca. 0.7, i.e., they can be considered as good. For four other variables, ICC ranged from 0.41 to 0.54, with these values considered fair. Satisfactory reproducibility of postural stability measurements using the GYKO inertial sensor system demonstrates that it can offer an inexpensive and efficient alternative to measurements that use force balance platforms.

Modern medical devices are increasingly producing complex data that could offer deeper insights into physiological mechanisms of underlying diseases. One type of complex data that arises frequently in medical imaging studies is functional data, whose sampling unit is a smooth continuous function. In this work, with the goal of establishing the scientific validity of experiments involving modern medical imaging devices, we focus on the problem of evaluating reliability and reproducibility of multiple functional data that are measured on the same subjects by different methods (i.e. different technologies or raters). Specifically, we develop a series of intraclass correlation coefficient and concordance correlation coefficient indices that can assess intra-method, inter-method, and total (intra + inter) agreement based on multivariate multilevel functional data consisting of replicated functional data measurements produced by each of the different methods. For efficient estimation, the proposed indices are expressed using variance components of a multivariate multilevel functional mixed effect model, which can be smoothly estimated by functional principal component analysis. Extensive simulation studies are performed to assess the finite-sample properties of the estimators. The proposed method is applied to evaluate the reliability and reproducibility of renogram curves produced by a high-tech radionuclide image scan used to non-invasively detect kidney obstruction. [ABSTRACT FROM AUTHOR]

This study aimed to establish inter-rater reliability among three raters while training new driver rehabilitation specialists to correctly identify driving errors on a DriveSafety 250 driving simulator. Five participants completed adaptation, residential and suburban, and city and highway scenarios. Intraclass correlation coefficients indicated scores between.623–.877 (p =.003–.122) for the total driving errors recorded in the two scenario drives with rater agreement initially ranging between 7–8%. When analyzing the data for types of driving errors, the intraclass correlation coefficients ranged from.556–.973 (p <.05) and rater agreement between 15–100%. Through proper training and strategy development, raters reached 100% consensus on all aspects of inter-rater reliability while assessing driving errors. [ABSTRACT FROM AUTHOR]

In an individually randomized group treatment (IRGT) trial, participant outcomes can be positively correlated due to, for example, shared therapists in treatment delivery. Oftentimes, because of limited treatment resources or participants at one location, an IRGT trial can be carried out across multiple centers. This design can be subject to potential correlations in the participant outcomes between arms within the same center. While the design of a single‐center IRGT trial has been studied, little is known about the planning of a multicenter IRGT trial. To address this gap, this paper provides analytical sample size formulas for designing multicenter IRGT trials with a continuous endpoint under the linear mixed model framework. We found that accounting for the additional center‐level correlation at the design stage can lead to sample size reduction, and the magnitude of reduction depends on the amount of between‐therapist correlation. However, if the variance components of therapist‐level random effects are considered as input parameters in the design stage, accounting for the additional center‐level variance component has no impact on the sample size estimation. We presented our findings through numeric illustrations and performed simulation studies to validate our sample size procedures under different scenarios. Optimal design configurations under the multicenter IRGT trials have also been discussed, and two real‐world trial examples are drawn to illustrate the use of our method. [ABSTRACT FROM AUTHOR]

Repeatability involves the assessment of the agreement among repeated measurements from the same cluster of subjects, and this concept has been widely used in different scientific fields when data is structured in clusters. In the context of spatial trajectories, a degree of repeatability implies that individual trips can be distinguished from those of other individuals.Repeatability is usually assessed by the intraclass correlation coefficient (ICC), which is defined as the proportion of the total variance accounted for by among‐subject variability. However, where data are spatial trajectories the common approach to estimate the ICC does not apply because data involves sets of ordered spatial locations rather than single values.In this work, a novel approach based on spatial distances is proposed to estimate the ICC to assess the repeatability of spatial trajectories. The methodology is illustrated with a real case example of the flight trajectories of 36 Audouin's gulls (Ichthyaetus audouinii) moving through a heterogeneous landscape over a period of 18 days. Additionally, simulations were used to evaluate the performance of the approach under various scenarios.I demonstrate that ICC can be estimated on complex, spatially ordered data such as spatial trajectories, when using the appropriate spatial distance. [ABSTRACT FROM AUTHOR]

Phase-amplitude coupling (PAC) of theta and gamma rhythms of the brain has been observed in animals and humans, with evidence of its involvement in cognitive functions and brain disorders. This motivates finding individual frequencies of maximal theta-gamma coupling (TGC) and using them to adjust brain stimulation. This use implies the stability of the frequencies at least during the investigation, which has not been sufficiently studied. Meanwhile, there is a range of available algorithms for PAC estimation in the literature. We explored several options at different steps of the calculation, applying the resulting algorithms to the EEG data of 16 healthy subjects performing the n-back working memory task, as well as a benchmark recording with previously reported strong PAC. By comparing the results for the two halves of each session, we estimated reproducibility at a time scale of a few minutes. For the benchmark data, the results were largely similar between the algorithms and stable over time. However, for the EEG, the results depended substantially on the algorithm, while also showing poor reproducibility, challenging the validity of using them for personalizing brain stimulation. Further research is needed on the PAC estimation algorithms, cognitive tasks, and other aspects to reliably determine and effectively use TGC parameters in neuromodulation. [ABSTRACT FROM AUTHOR]

A large space still exists for improving the measurements used in orthopaedics and sports medicine, especially as we face rapid technological progress in devices used for diagnostic or patient monitoring purposes. For a specific measure to be valuable and applicable in clinical practice, its reliability must be established. Reliability refers to the extent to which measurements can be replicated, and three types of reliability can be distinguished: inter-rater, intra-rater, and test–retest. The present article aims to provide insights into reliability as one of the most important and relevant properties of measurement tools. It covers essential knowledge about the methods used in orthopaedics and sports medicine for reliability studies. From design to interpretation, this article guides readers through the reliability study process. It addresses crucial issues such as the number of raters needed, sample size calculation, and breaks between particular trials. Different statistical methods and tests are presented for determining reliability depending on the type of gathered data, with particular attention to the commonly used intraclass correlation coefficient. [ABSTRACT FROM AUTHOR]

Purpose: Mismatch between partial imported prostheses and Chinese anatomy affects the clinical outcome of the procedure. The purpose of this study was to measure the anatomical dimensions of Chinese distal femurs to provide guidance for the design of more compatible distal femoral prostheses. Methods: A total of 406 healthy distal femurs were reconstructed and measured. Consistency of these measurements and differences in sides, gender, and populations were examined. Parameter correlations were analyzed, and pairs with strong correlations underwent linear regression analysis. The design of distal femoral prostheses was referenced from the results of K-means and hierarchical clustering analysis. Results: Ten parameters were measured, including the trans-epicondylar axis, width of the distal femur (ML), anteroposterior diameter of the distal femur (AP), etc. The intra-class correlation coefficient ranged from 0.795 to 0.999 for intra-observer consistency, and from 0.796 to 0.998 for inter-observer consistency. Males exhibited significantly larger parameters than females, except for the posterior condylar angle (all P values < 0.05). Compared to other populations, substantial differences were observed for most parameters, such as ML, AP, width of lateral femoral condyle, etc. (all P values < 0.05). Clustering analysis suggested that distal femoral prostheses should include at least five sizes to adequately accommodate the sampled population. ML sizes for males were 68, 70, 83, 73, and 89 mm, and for females 64, 65, 71, 67, and 77 mm. AP sizes for males were 56, 60, 60, 64, and 64 mm, and for females 48, 52, 54, 57, and 58 mm. Conclusions: Chinese distal femur morphology, as analyzed using 3D techniques, varies significantly between genders and when compared with international data. For improved patient fit, the creation of five or more distal femur prostheses, diversified by gender and size and informed by the associated morphological parameters, is recommended. Level of evidence: IV. [ABSTRACT FROM AUTHOR]

Aim: To determine the test and retest reliability of the functional head impulse test (fHIT) in healthy young adults. Materials and methods: Thirty-three healthy participants (17 women, 16 men) aged 18–30 years were included in the study. Each participant underwent the fHIT twice, 1 week apart, by the same experienced clinician. Intraclass correlation coefficients (ICCs) were used to determine test–retest reliability. Results: There was no statistically significant difference between the results of total percentage of correct answer (CA%) of the fHIT obtained in session 1 and session 2 measurements in the lateral, anterior, and posterior semicircular canals (SCCs) (p > 0.05). ICC values for test–retest reliability were found to range from 0.619 to 0.665 for the three semicircular canals (SCCs). Conclusion: The test–retest reliability of the fHIT device was moderate. Attention, cognition, and fatigue may be the factors reducing reliability. In the diagnosis, follow-up, and rehabilitation processes of vestibular diseases in clinics, changes in the fHIT CA% can be used to assess vestibulo-ocular reflex (VOR) functionality. [ABSTRACT FROM AUTHOR]

The determinants of the temporal variability of indoor dust concentrations of semivolatile organic compounds (SVOCs) remain mostly unexplored. We examined temporal variability of dust concentrations and factors affecting dust concentrations for a wide range of SVOCs. We collected dust samples three times from 29 California homes during a period of 22 months and quantified concentrations of 47 SVOCs in 87 dust samples. We computed intraclass correlation coefficients (ICCs) using three samples collected within the same house. We calculated correlation coefficients (r) between two seasons with similar climate (spring and fall) and between two seasons with opposite climate (summer and winter). Among 26 compounds that were detected in more than 50% of the samples at all three visits, 20 compounds had ICCs above 0.50 and 6 compounds had ICCs below 0.50. For 19 out of 26 compounds, correlation coefficients between spring and fall (r = 0.48-0.98) were higher than those between summer and winter (r = 0.09-0.92), implying seasonal effects on dust concentrations. Our study showed that within-home temporal variability of dust concentrations was small (ICC > 0.50) for most SVOCs, but dust concentrations may vary over time for some SVOCs with seasonal variations in source rates, such as product use.

Lidwine B Mokkink,1,2 Iris Eekhout,1– 3 Maarten Boers,1,2 Cees PM van der Vleuten,4 Henrica CW de Vet1,2 1Amsterdam UMC, Vrije Universiteit Amsterdam, Epidemiology and Data Science, Amsterdam, the Netherlands; 2Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; 3Child Health, Netherlands Organisation for Applied Scientific Research, Leiden, the Netherlands; 4Department of Educational Development and Research, School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the NetherlandsCorrespondence: Lidwine B Mokkink, Amsterdam UMC, AMC, J1B -225, Meibergdreef 9, Amsterdam, 1105 AZ, the Netherlands, Tel +31 20 44 44474, Email w.mokkink@amsterdamumc.nlAbstract: Reliability and measurement error are measurement properties that quantify the influence of specific sources of variation, such as raters, type of machine, or time, on the score of the individual measurement. Several designs can be chosen to assess reliability and measurement error of a measurement. Differences in design are due to specific choices about which sources of variation are varied over the repeated measurements in stable patients, which potential sources of variation are kept stable (ie, restricted), and about whether or not the entire measurement instrument (or measurement protocol) was repeated or only part of it. We explain how these choices determine how intraclass correlation coefficients and standard errors of measurement formulas are built for different designs by using Venn diagrams. Strategies for improving the measurement are explained, and recommendations for reporting the essentials of these studies are described. We hope that this paper will facilitate the understanding and improve the design, analysis, and reporting of future studies on reliability and measurement error of measurements.Keywords: reliability, measurement error, classical test theory, generalizability theory, intraclass correlation coefficient, standard error of measurement

Cluster randomized trials often exhibit a three-level structure with participants nested in subclusters such as health care providers, and subclusters nested in clusters such as clinics. While the average treatment effect has been the primary focus in planning three-level randomized trials, interest is growing in understanding whether the treatment effect varies among prespecified patient subpopulations, such as those defined by demographics or baseline clinical characteristics. In this article, we derive novel analytical design formulas based on the asymptotic covariance matrix for powering confirmatory analyses of treatment effect heterogeneity in three-level trials, that are broadly applicable to the evaluation of cluster-level, subcluster-level, and participant-level effect modifiers and to designs where randomization can be carried out at any level. We characterize a nested exchangeable correlation structure for both the effect modifier and the outcome conditional on the effect modifier, and generate new insights from a study design perspective for conducting analyses of treatment effect heterogeneity based on a linear mixed analysis of covariance model. A simulation study is conducted to validate our new methods and two real-world trial examples are used for illustrations. [ABSTRACT FROM AUTHOR]

This study assessed the validity of the Entralpi force plate in the assessment of finger flexor performance in rock climbers. In addition to a static force evaluation, peak force, peak impulse, and total impulse were measured during 30 all-out performance trials by 15 participants, in which force during the trials was recorded simultaneously by the Entralpi and a Pasco force plate. Agreement between devices was assessed by a variety of statistical analyses, including intraclass correlation coefficient (ICC), coefficient of variation (CV), and Bland-Altman analyses. The static force evaluation showed a mean relative error of 0.41% and excellent day-to-day reliability (ICC = 1; CV = 0.03%). Peak force, peak impulse, and total impulse from the performance trials demonstrated strong agreement (ICC ≥ 0.991, CV ≤ 1.9%, Bland-Altman mean bias ≤ 0.5%). These results illustrate that the Entralpi force plate provides accurate and reliable data for rock climbing related tasks at an affordable cost. [ABSTRACT FROM AUTHOR]

Introduction: We determined whether cardiovascular (CV) measures show trait-like responses after repeated total sleep deprivation (TSD), baseline (BL) and recovery (REC) exposures in two long-duration studies (total N = 11 adults). Methods: A 5-day experiment was conducted twice at months 2 and 4 in a 4-month study (N = 6 healthy adults; 3 females; mean age ± SD, 34.3 ± 5.7 years; mean BMI ± SD, 22.5 ± 3.2 kg/m²), and three times at months 2, 4, and 8 in an 8-month study (N = 5 healthy adults; 2 females; mean age ± SD, 33.6 ± 5.17 years; mean BMI ± SD, 27.1 ± 4.9 kg/m²). Participants were not shift workers or exposed to TSD in their professions. During each experiment, various seated and standing CV measures were collected via echocardiography [stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI)] or blood pressure monitor [systolic blood pressure (SBP)] after (1) two BL 8h time in bed (TIB) nights; (2) an acute TSD night; and (3) two REC 8-10 h TIB nights. Intraclass correlation coefficients (ICCs) assessed CV measure stability during BL, TSD, and REC and for the BL and REC average (BL + REC) across months 2, 4, and 8; Spearman's rho assessed the relative rank of individuals' CV responses across measures. Results: Seated BL (0.693-0.944), TSD (0.643-0.962) and REC (0.735-0.960) CV ICCs showed substantial to almost perfect stability and seated BL + REC CV ICCs (0.552-0.965) showed moderate to almost perfect stability across months 2, 4, and 8. Individuals also exhibited significant, consistent responses within seated CV measures during BL, TSD, and REC. Standing CV measures showed similar ICCs for BL, TSD, and REC and similar response consistency. Discussion: This is the first demonstration of remarkably robust phenotypic stability of a number of CV measures in healthy adults during repeated TSD, BL and REC exposures across 2, 4, and 8 months, with significant consistency of responses within CV measures. The cardiovascular measures examined in our studies, including SV, HR, CI, LVET, SVRI, and SBP, are useful biomarkers that effectively track physiology consistently across long durations and repeated sleep deprivation and recovery. [ABSTRACT FROM AUTHOR]

Kraepelinian theory posits that schizophrenia (SZ) is a degenerative disorder that worsens throughout the lifespan. Behavioral studies of cognition have since challenged that viewpoint, particularly in the early phases of illness. Nonetheless, the extent to which cognition remains functionally stable during the early course of illness is unclear, particularly with regard to task-associated connectivity in cognition-related brain networks. In this study, we examined the 1-year stability of the frontoparietal control network during the AX-Continuous Performance Task (AX-CPT) from a new baseline sample of 153 participants scanned at 3T, of which 29 recent onset individuals with SZ and 42 healthy control (HC) participants had follow-up data available for analysis. Among individuals that had both baseline and follow-up data, reduced functional connectivity in SZ was observed between the dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex (SPC) during the high control (B cue) condition. Furthermore, this deficit was stable over time, as no significant time × diagnosis interaction or effects of time were observed and intraclass correlation coefficients were greater than 0.6 in HCs and SZ. Previous 1.5T findings showing stable deficits with no evidence of degeneration in performance or DLPFC activation in an independent SZ sample were replicated. Overall, these results suggest that the neuronal circuitry supporting cognitive control is stably impaired during the early course of illness in SZ across multiple levels of analysis with no evidence of functional decline.

Purpose Quantitative elastography methods, such as ultrasound two-dimensional shear-wave elastography (2D-SWE) and magnetic resonance elastography (MRE), are used to diagnose liver fibrosis. The present study compared liver stiffness determined by 2D-SWE and MRE within individuals and analyzed the degree of agreement between the two techniques. Methods In total, 888 patients who underwent 2D-SWE and MRE were analyzed. Bland-Altman analysis was performed after both types of measurements were log-transformed to a normal distribution and converted to a common set of units using linear regression analysis for differing scales. The expected limit of agreement (LoA) was defined as the square root of the sum of the squares of 2D-SWE and MRE precision. The percentage difference was expressed as (2D-SWEMRE)/ mean of the two methods×100. Results A Bland-Altman plot showed that the bias and upper and lower LoAs (ULoA and LLoA) were 0.0002 (95% confidence interval [CI], -0.0057 to 0.0061), 0.1747 (95% CI, 0.1646 to 0.1847), and -0.1743 (95% CI, -0.1843 to -0.1642), respectively. In terms of percentage difference, the mean, ULoA, and LLoA were -0.5944%, 19.8950%, and -21.0838%, respectively. The calculated expected LoA was 17.1178% (95% CI, 16.6353% to 17.6002%), and 789 of 888 patients (88.9%) had a percentage difference within the expected LoA. The intraclass correlation coefficient of the two methods indicated an almost perfect correlation (0.8231; 95% CI, 0.8006 to 0.8432; P

The climatic changes have important role which may lead to huge problems for the health of human and other organisms, therefore it is necessary to study and forecast this type of datasets to reduce . the damages through planning and controlling for these changes in the future. The main problem can be summarized in the nonlinearity of climatic dataset and its chaotic changes. The common approach is the integrated autoregressive and moving average model (ARIMA) as traditional univariate time series approach. Therefore, more appropriate model for studying the climatic data has been proposed for obtaining more accurate forecasting, it can be called random forest (RF) model.This model cannot deal with nonlinear data correctly and that may lead to inaccurate forecasting results. In this thesis, climatic datasets are studied represented by minimum air temperature and rational humidity for agricultural meteorological station in Nineveh. This thesis aims to satisfy data homogeneity through different seasons and find suitable model deal with nonlinear data correctly with minimal forecasting error comparing to ARIMA as traditional model. The research found the adequate of the model for this type of data, as it was found that there are some factors that contribute to the increase in the number of deaths in the epidemic, such as the advanced age of the patient, the length of stay in the hospital, the percentage of oxygen in the patient's blood, in addition to the incidence of some chronic diseases such as asthma. The study recommended a more in-depth study of other types of these models, and the use of other estimation methods, in addition to paying attention to the methods of data recording by the city health department.

This research deals with the study of the partial hierarchical Poisson regression model (with a random intercept), where this model is one of the most important models widely applied in analyzing data that is characterized by the fact that the observations take a hierarchical form. Where it the full maximum likelihood (FML) method is used to estimate the model parameters. The model was applied to the covid-9 deaths in Mosul city, were recorded during the period (1/1/202 - 1/9/2021), where four major hospitals in the city were selected to represent the group of second level of data (Ibn Sina Hospital, Al Salam Hospital, Shifa Hospital, General Mosul Hospital). *طالب دبلوم عالی/ قسم الاحصاء والمعلوماتیة/ کلیة علوم الحاسوب والریاضیات/ جامعة الموصل. **استاذ مساعد/ قسم الاحصاء والمعلوماتیة/ کلیة علوم الحاسوب والریاضیات/ جامعة الموصل. تاریخ استلام البحث: 4/3/2022 تاریخ القبول: 9/4/2022 تاریخ النشر: 1/12/2022 The research found the adequate of the model for this type of data, as it was found that there are some factors that contribute to the increase in the number of deaths in the epidemic, such as the advanced age of the patient, the length of stay in the hospital, the percentage of oxygen in the patient's blood, in addition to the incidence of some chronic diseases such as asthma. The study recommended a more in-depth study of other types of these models, and the use of other estimation methods, in addition to paying attention to the methods of data recording by the city health department.

Throwing Performance (TP) is important in throwing sports. Several tests have been designed to assess TP, and the reliability of these tests was examined in various studies. The aim of this systematic review was to critically appraise and synthesize the studies that examined the reliability of TP tests. A systematic search was conducted on PubMed, Scopus, CINAHL and SPORTDiscus to identify studies related to TP and reliability. The quality of the included studies was examined through the Quality Appraisal of Reliability Studies (QAREL) tool. Reliability was assessed using the intraclass correlation coefficient (ICC), while responsiveness was assessed using the minimal detectable change (MDC). Sensitivity analysis was conducted to identify whether low-quality studies may have biased the recommendations of this review. Seventeen studies were found eligible. The results showed a moderate level of evidence to suggest that TP tests have good reliability (ICC≥0.76). This recommendation was also applied separately when TP tests were used to measure throwing velocity, distance covered, endurance and throwing accuracy. Also, summated MDC scores were reported to assist coaches in decision-making when using TP tests to detect real performance changes. However, sensitivity analysis showed that there is a significant number of low-quality studies. This review revealed that the tests used for throwing performance assessment are reliable; however, due to a significant number of low-quality studies, these results should be used cautiously. Important recommendations of this review may be used in future studies to design high-quality studies. • A range of simple tests exist for the assessment of throwing performance. • Moderate level of evidence suggests that throwing performance tests have good reliability. • Tests that measure distance seem to be the most reliable for on-field measurements and in the clinical setting. • The majority of the studies demonstrated high external validity but low internal validity. • Future studies should address issues related to the blinding of the raters and the variation in the order of testing. [ABSTRACT FROM AUTHOR]

Bioelectrical impedance analysis (BIA) is gaining popularity as a tool for body composition assessment. Although BIA has been studied and validated in different populations, age groups, and clinical settings, including critically ill patients, there are concerns about BIA reproducibility and reliability for different device types and postures. This study aimed to evaluate the reliability of BIA using different devices, postures, and lead types. Cross-sectional observational data were collected from 74 healthy volunteers (32 women, 42 men). We used two types of devices, three types of postures (standing, sitting, and lying), and two lead types (clamp lead and adhesive lead) to measure the whole-body phase angle (phA) at a single frequency of 50 kHz. The measurements were validated using the intraclass correlation coefficient (ICC) and Bland–Altman plot analysis. All phA measurements recorded using the two types of devices, three different postures, and two types of leads were equivalent (mean ICC = 0.9932, 95% confidence interval (CI) 0.9905–0.0053, p < 0.001). The average mean difference in phA was 0.31 (95% CI 0.16–0.46). The largest phA value was measured using BWA with an adhesive-type lead in the supine position. There were no differences between the standing and sitting positions. We compared the consistency and reliability of phA using two devices, two lead types, and three postures. Seven different phA were interchangeable in healthy volunteers. [ABSTRACT FROM AUTHOR]

Intraclass correlation coefficients are estimated using appropriate analysis of variance models that are commonly used in behavioral measurement, biometric, and psychometric. The ICCs estimation accuracy is quantified by the degree of their sampling variability using the asymptotic standard errors or confidence intervals, which facilitates conducting hypothesis testing on ICCs. The article derived the asymptotic standard errors of absolute agreement ICC and relative consistency ICC for the two-way model. Monte Carlo simulations were performed for both normal data and nonnormal data under different conditions. Results supported that the proposed asymptotic standard errors for all ICCs were converging to the simulated true standard errors under different test conditions. [ABSTRACT FROM AUTHOR]

Accurate and reliable detection of the onset of gait initiation is essential for the correct assessment of gait. Thus, this study was aimed at evaluation of the reliability and accuracy of 3 different center of pressure--based gait onset detection algorithms: A displacement baseline--based algorithm (method 1), a velocity baseline--based algorithm (method 2), and a velocity extremabased algorithm(method 3). The center of pressure signal was obtained during 10 gait initiation trials from 16 healthy participants and 3 participants with Parkinson's disease. Intrasession and absolute reliability of each algorithm was assessed using the intraclass correlation coefficient and the coefficient of variation of center of pressure displacement during the postural phase of gait initiation. The accuracy was evaluated using the time error of the detected onset by each algorithm relative to that of visual inspection. The authors' results revealed that although all 3 algorithms had high to very high intrasession reliabilities in both healthy subjects and subjects with Parkinson's disease, methods 2 and 3 showed significantly better absolute reliability than method 1 in healthy controls (P = .001). Furthermore, method 2 outperformed the other 2 algorithms in both healthy subjects and subjects with Parkinson's disease with an overall accuracy of 0.80. Based on these results, the authors recommend using method 2 for accurate and reliable gait onset detection. [ABSTRACT FROM AUTHOR]

IntroductionWe determined whether cardiovascular (CV) measures show trait-like responses after repeated total sleep deprivation (TSD), baseline (BL) and recovery (REC) exposures in two long-duration studies (total N = 11 adults).MethodsA 5-day experiment was conducted twice at months 2 and 4 in a 4-month study (N = 6 healthy adults; 3 females; mean age ± SD, 34.3 ± 5.7 years; mean BMI ± SD, 22.5 ± 3.2 kg/m2), and three times at months 2, 4, and 8 in an 8-month study (N = 5 healthy adults; 2 females; mean age ± SD, 33.6 ± 5.17 years; mean BMI ± SD, 27.1 ± 4.9 kg/m2). Participants were not shift workers or exposed to TSD in their professions. During each experiment, various seated and standing CV measures were collected via echocardiography [stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI)] or blood pressure monitor [systolic blood pressure (SBP)] after (1) two BL 8h time in bed (TIB) nights; (2) an acute TSD night; and (3) two REC 8–10 h TIB nights. Intraclass correlation coefficients (ICCs) assessed CV measure stability during BL, TSD, and REC and for the BL and REC average (BL + REC) across months 2, 4, and 8; Spearman’s rho assessed the relative rank of individuals’ CV responses across measures.ResultsSeated BL (0.693–0.944), TSD (0.643–0.962) and REC (0.735–0.960) CV ICCs showed substantial to almost perfect stability and seated BL + REC CV ICCs (0.552–0.965) showed moderate to almost perfect stability across months 2, 4, and 8. Individuals also exhibited significant, consistent responses within seated CV measures during BL, TSD, and REC. Standing CV measures showed similar ICCs for BL, TSD, and REC and similar response consistency.DiscussionThis is the first demonstration of remarkably robust phenotypic stability of a number of CV measures in healthy adults during repeated TSD, BL and REC exposures across 2, 4, and 8 months, with significant consistency of responses within CV measures. The cardiovascular measures examined in our studies, including SV, HR, CI, LVET, SVRI, and SBP, are useful biomarkers that effectively track physiology consistently across long durations and repeated sleep deprivation and recovery.

Objectives: Artistic gymnastics is a sport where most athletes start at an early age and training volumes are high. Hence, overuse and acute injuries are frequent due to the load endured during landing tasks. During landing, the ground reaction force (GRF) is up to 15.8 times the body weight and therefore reliable GRF measurements are crucial. The gold standard for GRF measurements are force plates. As force plates are mostly used in a constrained laboratory environment, it is difficult to measure the GRF in representative training settings. Textile insoles (novel GmbH, Munich, Germany) exist, which can be used to measure dynamic GRF. Hence, the motivation of this study is to test the validity and reliability of these insoles during landing tasks. GRF was measured during four different exercises, in two test subjects and compared to concurrent force plate data. Results: Twelve out of 16 statistical parametric mapping plots showed no significant difference between the measured force curves of insoles and force plates. Across conditions, the root mean square error of the maximal vertical GRF was 21 N/kg and an impulse 0.4 Ns/kg. The intraclass correlation coefficient (ICC 2,1) ranged from 0.02 to 0.76 for maximal vertical GRF and from − 0.34 to 0.76 for impulse. The insoles are a valid measurement tool for GRF curve progression and impulse during landing but underestimate the maximal vertical GRF. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The Workplace Safety Culture Questionnaire (WSCQ) was developed to assess the level of knowledge, attitudes and practices on Workplace Safety Culture (WSC) among public sector office workers in Nigeria. The main objective of this study was to determine the validity and reliability of the new Workplace Safety Culture Questionnaire (WSCQ) using the Information Motivation and Behavior (IMB) model. MATERIALS AND METHODS: The WSCQ questionnaire was completed twice by the respondents themselves, with an interval of ten days between sessions, to assess the accuracy of the initial results with the retest. This study involved 44 participants. RESULTS: Cronbach's alpha showed significant item consistency for each construct in the second pilot study. The information construct (Cronbach's a=0.929 and minimum corrected item-total correlation (CITC)=0.399). The motivation construct (Cronbach's a=0.932 and minimum corrected item-total correlation (CITC)=0.450). The behavior construct (Cronbach's a=0.812 and minimum corrected item-total correlation (CITC)= 0.401). In test-retest reliability, Cohen's kappa coefficient for construct of information for all items was almost 70% between (kappa k=0.689-1000, p<0.001). The intraclass correlation coefficient (ICC) for the construct of motivation for all items is 90% between (ICC=0.810-1000, p<0.001) and (kappa k=0.944-1000, p<0.001) for the construct of behavior was 71% for all items. CONCLUSION: This study introduces the WSCQ using the IMB model among public sector office workers as the first official validation of the WSCQ. [ABSTRACT FROM AUTHOR]

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