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During the early stages of the pandemic, computed tomography (CT) of the chest, along with serological and clinical data, was frequently utilized in diagnosing COVID-19, particularly in regions facing challenges such as shortages of PCR kits. In these circumstances, CT scans played a crucial role in diagnosing COVID-19 and guiding patient management. The COVID-19 Reporting and Data System (CO-RADS) was established as a standardized reporting system for cases of COVID-19 pneumonia. Its implementation necessitates a high level of agreement among observers to prevent any potential confusion. This study aimed to assess the inter-observer agreement between physicians from different specialties with variable levels of experience in their CO-RADS scoring of CT chests for confirmed COVID-19 patients, and to assess the feasibility of applying this reporting system to those having little experience with it. All chest CT images of patients with positive RT-PCR tests for COVID-19 were retrospectively reviewed by seven observers. The observers were divided into three groups according to their type of specialty (three radiologists, three house officers, and one pulmonologist). The observers assessed each image and categorized the patients into five CO-RADS groups. A total of 630 participants were included in this study. The inter-observer agreement was almost perfect among the radiologists, substantial among a pulmonologist and the house officers, and moderate-to-substantial among the radiologists, the pulmonologist, and the house officers. There was substantial to almost perfect inter-observer agreement when reporting using the CO-RADS among observers with different experience levels. Although the inter-observer variability among the radiologists was high, it decreased compared to the pulmonologist and house officers. Radiologists, house officers, and pulmonologists applying the CO-RADS can accurately and promptly identify typical CT imaging features of lung involvement in COVID-19.

Neuronal responses to identically presented stimuli are extremely variable. This variability has in the past often been regarded as “noise.” At the single neuron level, interspike interval (ISI) histograms constructed during either spontaneous or stimulus-evoked activity reveal a Poisson type distribution. These observations have been taken as evidence that neurons are intrinsically “noisy” in their firing properties. More recent attempts to measure the information content of single neuron spike trains have revealed that a surprising amount of information can be coded in spike trains even in the presence of trial-to-trial variability. Multiple single unit recording experiments have suggested that variability formerly attributed to noise in single cell recordings may instead simply reflect system-wide changes in cellular response properties. These observations raise the possibility that, at least at the level of neuronal coding, the variability seen in single neuron responses may not simply reflect an underlying noisy process. They further raise the very distinct possibility that noise may in fact contain real, meaningful information which is available for the nervous system in information processing. To understand how neurons work in concert to bring about coherent behavior and its breakdown in disease, neuroscientists now routinely record simultaneously from hundreds of different neurons and from different brain areas, and then attempt to evaluate the network activities by computing various interdependence measures including cross correlation, phase synchronization, and spectral coherence. This book examines neuronal variability from theoretical, experimental, and clinical perspectives.

Encoding-variability theory presumes that there is greater encoding variability when repetitions are spaced than when they are massed and that encoding variability is positively related to both recall and apparent frequency. The first presumption was tested by assessing variability in associations to items that were repeated under conditions of either massed or spaced repetition. The validity of the presumption was called into question by a finding of more associations to massed than to spaced repetitions. Findings for recall and apparent-frequency measures administered after the word-association cover task were congruent with findings from prior studies of spacing effects. Hence, there is no reason to think that memory processes accompanying the word-association task differ from memory processes occurring with cover tasks typically used in studies of spacing effects.

Objective:Research evaluating mindfulness and cognition has produced mixed results. However, variability in mindfulness has not been previously evaluated as a predictor of cognitive ability. This study evaluated the relation between intra-individual variability (IIV) in mindfulness and cognitive performance.Participants and Methods:274 university participants (M=19 years old, SD=1.5; 72.6% female, 67.2% White, 25.6% African American, 3.3% Asian American, 1.1% Hispanic American) completed the Five Facet Mindfulness Questionnaire (FFMQ) and the CNS Vital Signs computerized test battery. IIV was computed from the FFMQ facet T-scores. Additionally, high and low cognitive performance groups were formed from the top and bottom 16% of the sample using the neurocognition index (NCI) score from CNS Vital Signs (N=52 high NCI performance and N=46 low NCI performance).Results:Pearson r correlations were used to evaluate the relation between mindfulness IIV and CNS Vital Signs domains. Mindfulness IIV was negatively associated with performance on the domains of psychomotor speed [r=-.18; p=.003], composite memory [r=-.14; p=.023] and verbal memory [r=-.15; p=.015]. For the high NCI group, IIV mindfulness was positively associated with cognitive flexibility [r=.31; p=.024], executive functioning [r=.33; p=.016] and was negatively related to visual memory [r=-.28; p=.043]. For the low NCI group, IIV mindfulness was negatively related to psychomotor speed [r=-.49; p<.001], composite memory [r=-.32; p=.033] and verbal memory [r=-.31; p=.038]. There was no relation found for individual FFMQ facet scores and CNS Vital Sign domains.Conclusions:Increased consistency in self-reported mindfulness (lower IIV) was associated with greater processing speed and memory performance in the overall sample. However, the relation been mindfulness IIV and cognitive performance changed greatly in high NCI performers compared to low NCI performers. The low NCI group may be a proxy for poor effort which would explain why more variable self-reported mindfulness was associated with worse performance for processing speed and memory and this could be driving the results for the overall sample. However, our findings for the high NCI performance group are unique and suggest an association between increased variability in mindfulness facets and improved cognitive flexibility and executive functioning. Further study of mindfulness variability and aspects of executive functioning is warranted.

Measuring the variability in persons’ behaviors and experiences using ecological momentary assessment is time-consuming and costly. We investigate whether interval responses provided through a dual-range slider (DRS) response format can be used as a simple and efficient alternative: Respondents indicate variability in their behavior in a retrospective rating by choosing a lower and an upper bound on a continuous, bounded scale. We investigate the psychometric properties of this response format as a prerequisite for further validation. First, we assess the test–retest reliability of factor-score estimates for the width of DRS intervals. Second, we test whether factor-score estimates of the visual analog scale (VAS) and the location of DRS intervals show convergent validity. Third, we investigate whether factor-score estimates for the DRS are uncorrelated between different personality scales. We present a longitudinal multitrait-multimethod study using two personality scales (Extraversion, Conscientiousness) and two response formats (VAS, DRS) at two measurement occasions (6–8 weeks apart) for which we estimate factor-score correlations in a joint item response theory model. The test–retest reliability of the width of DRS intervals was high ( ρ ^ ≥ . 73 ). Also, convergent validity between location scores of VAS and DRS was high ( ρ ^ ≥ . 88 ). Conversely, discriminant validity of the width of DRS intervals between Extraversion and Conscientiousness was poor ( ρ ^ ≥ . 94 ). In conclusion, the DRS seems to be a reliable response format that could be used to measure the central tendency of a trait equivalently to the VAS. However, it might not be well suited for measuring intra-individual variability in personality traits.

In this paper, we propose a model-based method to study conditional dependence between response accuracy and response time (RT) with the diffusion IRT model (Tuerlinckx and De Boeck in Psychometrika 70(4):629–650, 2005, https://doi.org/10.1007/s11336-000-0810-3 ; van der Maas et al. in Psychol Rev 118(2):339–356, 2011, https://doi.org/10.1080/20445911.2011.454498 ). We extend the earlier diffusion IRT model by introducing variability across persons and items in cognitive capacity (drift rate in the evidence accumulation process) and variability in the starting point of the decision processes. We show that the extended model can explain the behavioral patterns of conditional dependency found in the previous studies in psychometrics. Variability in cognitive capacity can predict positive and negative conditional dependency and their interaction with the item difficulty. Variability in starting point can account for the early changes in the response accuracy as a function of RT given the person and item effects. By the combination of the two variability components, the extended model can produce the curvilinear conditional accuracy functions that have been observed in psychometric data. We also provide a simulation study to validate the parameter recovery of the proposed model and present two empirical applications to show how to implement the model to study conditional dependency underlying data response accuracy and RTs.

Standard response formats such as rating or visual analogue scales require respondents to condense distributions of latent states or behaviors into a single value. Whereas this is suitable to measure central tendency, it neglects the variance of distributions. As a remedy, variability may be measured using interval-response formats, more specifically the dual-range slider (RS2). Given the lack of an appropriate item response model for the RS2, we develop the Dirichlet dual response model (DDRM), an extension of the beta response model (BRM; Noel & Dauvier in Appl Psychol Meas, 31:47–73, 2007). We evaluate the DDRM’s performance by assessing parameter recovery in a simulation study. Results indicate overall good parameter recovery, although parameters concerning interval width (which reflect variability in behavior or states) perform worse than parameters concerning central tendency. We also test the model empirically by jointly fitting the BRM and the DDRM to single-range slider (RS1) and RS2 responses for two Extraversion scales. While the DDRM has an acceptable fit, it shows some misfit regarding the RS2 interval widths. Nonetheless, the model indicates substantial differences between respondents concerning variability in behavior. High correlations between person parameters of the BRM and DDRM suggest convergent validity between the RS1 and the RS2 interval location. Both the simulation and the empirical study demonstrate that the latent parameter space of the DDRM addresses an important issue of the RS2 response format, namely, the scale-inherent interdependence of interval location and interval width (i.e., intervals at the boundaries are necessarily smaller).