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

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

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