Person-Specific Methods for Characterizing the Course and Temporal Dynamics of Concussion Symptomatology: A Pilot Study.

Better characterization of acute concussion symptomatology is needed in order to advance clinical and scientific understanding of persistent concussion symptoms. This paper aims to illustrate a novel framework for conceptualizing, collecting, and analyzing concussion symptom data. To that end, we describe the temporal and structural dynamics of acute concussion symptoms at the individual-patient level. Ten recently concussion adolescents and young adults completed 20 days of ecological momentary assessment (EMA) of post-concussion symptoms. Follow-up assessments were completed at 3 months post-injury. Network modeling revealed marked heterogeneity across participants. In the overall sample, temporal patterns explained the most variance in light sensitivity (48%) and the least variance in vomiting (5%). About half of the participants had symptom networks that were sparse after controlling for temporal variation. The other individualized symptom networks were densely interconnected clusters of symptoms. Networks were highly idiosyncratic in nature, yet emotional symptoms (nervousness, emotional, sadness), cognitive symptoms (mental fogginess, slowness), and symptoms of hyperacusis (sensitivity to light, sensitivity to noise) tended to cluster together across participants. Person-specific analytic techniques revealed a number of idiosyncratic features of post-concussion symptomatology. We propose applying this framework to future research to better understand individual differences in concussion recovery

Statistical inferences of Rs;k = Pr(Xk-s+1:k \u3e Y ) for general class of exponentiated inverted exponential distribution with progressively type-II censored samples with uniformly distributed random removal

The problem of statistical inference of the reliability parameter Pr(Xk-s+1:k \u3e Y ) of an s-out-of-k : G system with strength components X1,X2,…,Xk subjected to a common stress Y when X and Y are independent two-parameter general class of exponentiated inverted exponential (GCEIE) progressively type-II right censored data with uniformly random removal random variables, are discussed. We use p-value as a basis for hypothesis testing. There are no exact or approximate inferential procedures for reliability of a multicomponent stress-strength model from the GCEIE based on the progressively type-II right censored data with random or fixed removals available in the literature. Simulation studies and real-world data analyses are given to illustrate the proposed procedures. The size of the test, adjusted and unadjusted power of the test, coverage probability and expected confidence lengths of the confidence interval, and biases of the estimator are also discussed

Using network analysis for the prediction of treatment dropout in patients with mood and anxiety disorders: a methodological proof-of-concept study

There are large health, societal, and economic costs associated with attrition from psychological services. The recently emerged, innovative statistical tool of complex network analysis was used in the present proof-of-concept study to improve the prediction of attrition. Fifty-eight patients undergoing psychological treatment for mood or anxiety disorders were assessed using Ecological Momentary Assessments four times a day for two weeks before treatment (3,248 measurements). Multilevel vector autoregressive models were employed to compute dynamic symptom networks. Intake variables and network parameters (centrality measures) were used as predictors for dropout using machine-learning algorithms. Networks for patients differed significantly between completers and dropouts. Among intake variables, initial impairment and sex predicted dropout explaining 6% of the variance. The network analysis identified four additional predictors: Expected force of being excited, outstrength of experiencing social support, betweenness of feeling nervous, and instrength of being active. The final model with the two intake and four network variables explained 32% of variance in dropout and identified 47 out of 58 patients correctly. The findings indicate that patients’ dynamic network structures may improve the prediction of dropout. When implemented in routine care, such prediction models could identify patients at risk for attrition and inform personalized treatment recommendations.This work was supported by the German Research Foundation National Institute (DFG, Grant nos. LU 660/8-1 and LU 660/10-1 to W. Lutz). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript. The corresponding author had access to all data in the study and had final responsibility for the decision to submit for publication. Dr. Hofmann receives financial support from the Alexander von Humboldt Foundation (as part of the Humboldt Prize), NIH/NCCIH (R01AT007257), NIH/NIMH (R01MH099021, U01MH108168), and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative. (LU 660/8-1 - German Research Foundation National Institute (DFG); LU 660/10-1 - German Research Foundation National Institute (DFG); Alexander von Humboldt Foundation; R01AT007257 - NIH/NCCIH; R01MH099021 - NIH/NIMH; U01MH108168 - NIH/NIMH; James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition - Special Initiative)Accepted manuscrip

A new method reveals microtubule minus ends throughout the meiotic spindle

Anastral meiotic spindles are thought to be organized differently from astral mitotic spindles, but the field lacks the basic structural information required to describe and model them, including the location of microtubule-nucleating sites and minus ends. We measured the distributions of oriented microtubules in metaphase anastral spindles in Xenopus laevis extracts by fluorescence speckle microscopy and cross-correlation analysis. We localized plus ends by tubulin incorporation and combined this with the orientation data to infer the localization of minus ends. We found that minus ends are localized throughout the spindle, sparsely at the equator and at higher concentrations near the poles. Based on these data, we propose a model for maintenance of the metaphase steady-state that depends on continuous nucleation of microtubules near chromatin, followed by sorting and outward transport of stabilized minus ends, and, eventually, their loss near poles

The Hierarchical Taxonomy of Psychopathology (HiTOP) Is Not an Improvement Over the DSM

DeYoung and colleagues did not sufficiently address three fundamental flaws with HiTOP. First, HiTOP was created using a simple structure factor analytic approach, which does not adequately represent the dimensional space of the symptoms of psychopathology. Consequently, HiTOP is not the empirical structure of psychopathology. Second, factor analysis and dimensional ratings do not fix the problems inherent to descriptive (folk) classification; self-reported symptoms are still the basis upon which clinical judgments about people are made. Finally, HiTOP is not ready to use in real-world clinical settings. There is currently no empirical evidence demonstrating that clinicians who use HiTOP have better clinical outcomes than those who use the DSM. In sum, HiTOP is a factor analytic variation of the DSM that does not get us closer to a more valid and useful taxonomy

Crossâ Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in diseaseâ specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and selfâ efficacy (i.e., control). The 2015â 2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved crossâ sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (Marchâ May 2016) and one just after the first cases of local transmission (Julyâ August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and selfâ efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153206/1/risa13369_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153206/2/risa13369.pd

Drought drove forest decline and dune building in eastern upper Michigan, USA, as the upper Great Lakes became closed basins

Current models of landscape response to Holocene climate change in midcontinent North America largely reconcile Earth orbital and atmospheric climate forcing with pollen-based forest histories on the east and eolian chronologies in Great Plains grasslands on the west. However, thousands of sand dunes spread across 12,000 km2 in eastern upper Michigan (EUM), more than 500 km east of the present forest-prairie ecotone, present a challenge to such models. We use 65 optically stimulated luminescence (OSL) ages on quartz sand deposited in silt caps (n = 8) and dunes (n = 57) to document eolian activity in EUM. Dune building was widespread ca. 10–8 ka, indicating a sharp, sustained decline in forest cover during that period. This decline was roughly coincident with hydrologic closure of the upper Great Lakes, but temporally inconsistent with most pollen-based models that imply canopy closure throughout the Holocene. Early Holocene forest openings are rarely recognized in pollen sums from EUM because faint signatures of non-arboreal pollen are largely obscured by abundant and highly mobile pine pollen. Early Holocene spikes in nonarboreal pollen are recorded in cores from small ponds, but suggest only a modest extent of forest openings. OSL dating of dune emplacement provides a direct, spatially explicit archive of greatly diminished forest cover during a very dry climate in eastern midcontinent North America ca. 10–8 ka