5,494 research outputs found
Psychological adjustment in children with episodic migraine: a population-based study
We investigated psychological adjustment in a preadolescent pediatric population as a function of headache diagnosis. Children from a city public education system were enrolled in this study. Parents were interviewed using validated headache questionnaires and the Strengths and Difficulties Questionnaire (SDQ), which measures psychological adjustment. Crude and adjusted prevalence ratios were obtained using a binary regression model. The relative risk [RR] of SDQ items and scores were modeled as a function of headache diagnosis in adjusted analyses. Multivariate models estimated determinants of psychological adjustment characteristics in children with migraine. The sample consisted of 846 children (65.9% of the target sample) from 5 to 12 years old (50.5% girls). Relative to children without headache, children with episodic migraine (EM) were more likely to have abnormal scores on the following SDQ scales: emotional symptoms (RR = 3.43, 95% confidence interval [CI] = 2.51-4.69), conduct problems (RR = 1.96, 95% CI = 1.37-2.79), total difficulties (RR = 2.23, 95% CI = 1.59-3.13), and total impact (RR = 2.85, 95% CI = 1.15-7.11). The multivariate analysis showed that total difficulties in psychological adjustment in children with EM were significantly influenced by headache frequency (p < .05), analgesic intake (p < .001), and the occurrence of nausea (p < .01) and vomiting (p < .05) in headache attacks. To the best of our knowledge, this is the first study reported in the literature to identify determinants of the association between migraine and difficulties in psychological adjustment in preadolescent children. Providers and educators should be aware of this association, and studies that address causality should be conducted71334
A polynomial eigenvalue approach for multiplex networks
We explore the block nature of the matrix representation of multiplex
networks, introducing a new formalism to deal with its spectral properties as a
function of the inter-layer coupling parameter. This approach allows us to
derive interesting results based on an interpretation of the traditional
eigenvalue problem. More specifically, we reduce the dimensionality of our
matrices but increase the power of the characteristic polynomial, i.e, a
polynomial eigenvalue problem. Such an approach may sound counterintuitive at
first glance, but it allows us to relate the quadratic problem for a 2-Layer
multiplex system with the spectra of the aggregated network and to derive
bounds for the spectra, among many other interesting analytical insights.
Furthermore, it also permits to directly obtain analytical and numerical
insights on the eigenvalue behavior as a function of the coupling between
layers. Our study includes the supra-adjacency, supra-Laplacian, and the
probability transition matrices, which enable us to put our results under the
perspective of structural phases in multiplex networks. We believe that this
formalism and the results reported will make it possible to derive new results
for multiplex networks in the future.Comment: 15 pages including figures. Submitted for publicatio
On degree-degree correlations in multilayer networks
We propose a generalization of the concept of assortativity based on the
tensorial representation of multilayer networks, covering the definitions given
in terms of Pearson and Spearman coefficients. Our approach can also be applied
to weighted networks and provides information about correlations considering
pairs of layers. By analyzing the multilayer representation of the airport
transportation network, we show that contrasting results are obtained when the
layers are analyzed independently or as an interconnected system. Finally, we
study the impact of the level of assortativity and heterogeneity between layers
on the spreading of diseases. Our results highlight the need of studying
degree-degree correlations on multilayer systems, instead of on aggregated
networks.Comment: 8 pages, 3 figure
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