A complex network approach to structural inequality of educational deprivation in a Latin American country

To guarantee the human right to education established by the fourth UNESCO’s Sustainable Development Goal, a deep understanding of a big set of non-linear relationships at different scales is need it, as well as to know how they impact on learning outcomes. In doing so, current methods do not provide enough evidence about interactions and, for this reason, some researchers have proposed to model education as a complex system for considering all interactions at individual level, as well as using computer simulation and network analysis to provide a comprehensive look at the educational processes, as well as to predict the outcomes of different public policies. The highlight of this paper is modeling the structure of the inequality of a national educational system as a complex network from learning outcomes and socio-economic, ethnicity, rurality and type of school funding, for providing a better understanding and measuring of the educational gaps. This new approach might help to integrate insights improving the theoretical framework, as well as to provide valuable information about non-trivial relationships between educational and non-educational variables in order to help policymakers to implement effective solutions for the educational challenge of ensuring inclusive and equitable education.info:eu-repo/semantics/acceptedVersio

Inequality in learning outcomes: Unveiling educational deprivation through complex network analysis

Understanding which factors are determinant to guarantee the human right to education entails the study of a large number of non-linear relationships among multiple agents and their impact on the properties of the entire system. Complex network analysis of large-scale assessment results provides a set of unique advantages over classical tools for facing the challenge of measuring inequality gaps in learning outcomes and recognizing those factors associated with educational deprivation, combining the richness of qualitative analysis with quantitative inferences. This study establishes two milestones in educational research using a census high-quality data from a Latin American country. The first one is to provide a direct method to recognize the structure of inequality and the relationship between social determinants as ethnicity, socioeconomic status of students, rurality of the area and type of school funding and educational deprivation. The second one focus in unveil and hierarchize educational and non-educational factors associated with the conditional distribution of learning outcomes. This contribution provides new tools to current theoretical framework for discovering non-trivial relationships in educational phenomena, helping policymakers to address the challenge of ensuring inclusive and equitable education for those historically marginalized population groups.info:eu-repo/semantics/acceptedVersio

Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder

ObjectivesNetwork analyses of psychopathology examine the relationships between individual symptoms in an attempt to establish the causal interactions between symptoms that may give rise to episodes of psychiatric disorders. We conducted a network analysis of mood symptoms in adolescents with or at risk for bipolar spectrum disorders.MethodsThe sample consisted of 272 treatment-seeking adolescents with or at high risk for bipolar disorder who had at least subsyndromal depressive or (hypo)manic symptoms. Based on symptom scores assessed via semi-structured interviews, we constructed the network of depressive and manic symptoms and identified the most central symptoms and symptom communities within the network. We used bootstrapping analyses to determine the reliability of network parameters.ResultsSymptoms within the depressive and manic mood poles were more related to each other than to symptoms of the opposing mood pole. Four communities were identified, including a depressive symptom community and three manic symptom communities. Fatigue and depressed mood were the strongest individual symptoms within the overall network (ie the most highly correlated with other symptoms), followed by motor hyperactivity. Mood lability and irritability were found to be "bridge" symptoms that connected the two mood poles.ConclusionsSymptoms of activity/energy (ie fatigue and hyperactivity) and depressed mood are the most prominent mood symptoms among youth with bipolar spectrum disorders. Mood lability and irritability represent potential warning signs of emergent episodes of either polarity. Targeting these central and bridge symptoms would lead to more efficient assessments and therapeutic interventions for bipolar disorder

A network analysis of female sexual function: comparing symptom networks in women with decreased, increased, and stable sexual desire

Problems related to low sexual desire in women are common clinical complaints, and the aetiology is poorly understood. We investigated predictors of change in levels of sexual desire using a novel network approach, which assumes that mental disorders arise from direct interactions between symptoms. Using population-based data from 1,449 Finnish women, we compared between-subject networks of women whose sexual desire decreased, increased, or remained stable over time. Networks were estimated and analyzed at T1 (2006) and replicated at T2 (2013) using R. Domains included were, among others, sexual functions, sexual distress, anxiety, depression, body dissatisfaction, and relationship status. Overall, networks were fairly similar across groups. Sexual arousal, satisfaction, and relationship status were the most central variables, implying that they might play prominent roles in female sexual function; sexual distress mediated between general distress and sexual function; and sexual desire and arousal showed different patterns of relationships, suggesting that they represent unique sexual function aspects. Potential group-differences suggested that sex-related pain and body dissatisfaction might play roles in precipitating decreases of sexual desire. The general network structure and similarities between groups replicated well; however, the potential group-differences did not replicate. Our study sets the stage for future clinical and longitudinal network modelling of female sexual function