Sex-specific associations between sleep and mental health in university students: a large cross-sectional study

Abstract

Objective: To examine the associations between sleep problems and mental health dimensions in university students, and the effect of sex on these associations. Participants: Self-reported survey data from 3,483 students aged 18–30?years was drawn from a larger web-based study (i-Share) conducted in France in the years 2013–2017. Methods: We performed logistic regression analyses stratified by sex using insufficient sleep duration, poor sleep quality, difficulty initiating sleep and excessive daytime sleepiness, in relation with stress, self-esteem, depression and anxiety. Results: All sleep problems were strongly associated with all mental health dimensions, particularly anxiety, in female students. Sleep and mental health problems were also associated in male students, with the exception of low self-esteem, but odds ratios were lower than for female students. Conclusions: Present findings warrant attention to propose early interventions targeting sleep and mental health in the university setting taking sex into account.     

Colonial hangover? A case of multiple cross-cultural influences on Indian Railways

Employing a reflexive-ethnographic design involving past experiences and analysing qualitative data contained in 73 interviews with senior managers from the Indian Railways (IR), this study argues for the remnants of colonial influence on the management, governance aspects and culture in IR. Findings from the study further ratify and confirm aspects of our four scenarios and indicate that the interaction between colonial culture with both national and organisational culture collides to create a complex and conflicting culture in this extremely large and diverse organisation. Such organisational culture, despite the resilient presence of Indianness, paradoxically retains strong elements of the colonial influences as this is seen at times a legitimate and dominant way of governing the world’s largest commercial employer – The IR.     

A weakly informative prior for Bayesian dynamic model selection with applications in fMRI

In recent years, Bayesian statistics methods in neuroscience have been showing important advances. In particular, detection of brain signals for studying the complexity of the brain is an active area of research. Functional magnetic resonance imagining (fMRI) is an important tool to determine which parts of the brain are activated by different types of physical behavior. According to recent results, there is evidence that the values of the connectivity brain signal parameters are close to zero and due to the nature of time series fMRI data with high-frequency behavior, Bayesian dynamic models for identifying sparsity are indeed far-reaching. We propose a multivariate Bayesian dynamic approach for model selection and shrinkage estimation of the connectivity parameters. We describe the coupling or lead-lag between any pair of regions by using mixture priors for the connectivity parameters and propose a new weakly informative default prior for the state variances. This framework produces one-step-ahead proper posterior predictive results and induces shrinkage and robustness suitable for fMRI data in the presence of sparsity. To explore the performance of the proposed methodology, we present simulation studies and an application to functional magnetic resonance imaging data.     

Bayesian significance test for discriminating between survival distributions

An evaluation of FBST, Fully Bayesian Significance Test, restricted to survival models is the main objective of the present paper. A Survival distribution should be chosen among the tree celebrated ones, lognormal, gamma, and Weibull. For this discrimination, a linear mixture of the three distributions is an important tool: the FBST is used to test the hypotheses defined on the mixture weights space. Another feature of the paper is that all three distributions are reparametrized in that all the six parameters are written as functions of the mean and the variance of the population been studied. Some numerical results from simulations with some right-censored data are considered.     

I love chips and (h)ate them too: the role of ambivalence and contextual cues on attitudinally based eating behaviour / Me encantan las patatas fritas,las como y (también) las odio: el papel de la ambivalencia y de las claves contextuales en el comportamiento alimentario basado en la actitud

Although past work proposed ambivalence as moderating the consistency between attitudes and behaviours, empirical evidence is mixed. We address this matter by taking into account social influence processes and observing actual eating behaviour. We predicted that less ambivalent attitudes are more consistent with behaviours independently of context cues. In two studies, we first evaluated participants’ ambivalence towards the target food. A week later we observed their eating behaviour (Study 1), and analysed the influence of context cues on it (Study 2). Results showed that only less ambivalent attitudes are good predictors of actual behaviour. Importantly, context cues only influenced behaviour among individuals with ambivalent attitudes.     

A Model of Engagement Promotion in a Professionally Facilitated Online Intervention for Couples Affected by Breast Cancer

Professionally facilitated web‐based interventions for couples affected by an illness such as cancer are growing in popularity. Attrition rates for such online programs, however, are substantially higher than what is observed in face‐to‐face therapeutic contexts, and lower levels of participant engagement are associated with poorer outcomes. In the present investigation, a task analysis was employed to develop a model of engagement promotion in an online intervention for couples affected by breast cancer called “Couplelinks.” Results indicated that facilitators utilized a variety of meta‐processes, such as humanizing the technology, and associated “eBehaviors,” to maintain three relationships involved in promoting online engagement: (a) between the facilitator and couple; (b) between the intervention and couple; and (c) between the partners within the couple.     

A class of residuals for outlier identification in zero adjusted regression models

Zero adjusted regression models are used to fit variables that are discrete at zero and continuous at some interval of the positive real numbers. Diagnostic analysis in these models is usually performed using the randomized quantile residual, which is useful for checking the overall adequacy of a zero adjusted regression model. However, it may fail to identify some outliers. In this work, we introduce a class of residuals for outlier identification in zero adjusted regression models. Monte Carlo simulation studies and two applications suggest that one of the residuals of the class introduced here has good properties and detects outliers that are not identified by the randomized quantile residual.     

Special Education, Inclusion and Globalisation: a few considerations inspired in the Brazilian case

This article analyses contradictory aspects of globalisation in emergent countries and its reflections on special education taking the Brazilian context as reference. It argues that globalisation can only be positive if understood in its humanitarian sense which is in tune with the proposal of an inclusive education and the Education for All movement. The paper points out some key-terms used together with 'globalisation' and raises aspects related to the way(s) in which they affect the education of disabled people in Brazil. It suggests that understanding the new roles of education within the globalised world is imperative for inclusion to take place effectively.