Exploring multicultural classroom dynamics: A network analysis

Revisiting the effects of maternal education on adolescents' academic performance: Doubly robust estimation in a network-based observational study

In many contexts, particularly when study subjects are adolescents, peer effects can invalidate typical statistical requirements in the data. For instance, it is plausible that a student's academic performance is influenced both by their own mother's educational level as well as that of their peers. Since the underlying social network is measured, the Add Health study provides a unique opportunity to examine the impact of maternal college education on adolescent school performance, both direct and indirect. However, causal inference on populations embedded in social networks poses technical challenges, since the typical no interference assumption no longer holds. While inverse probability-of-treatment weighted (IPW) estimators have been developed for this setting, they are often highly unstable. Motivated by the question of maternal education, we propose doubly robust (DR) estimators combining models for treatment and outcome that are consistent and asymptotically normal if either model is correctly specified. We present empirical results that illustrate the DR property and the efficiency gain of DR over IPW estimators even when the treatment model is misspecified. Contrary to previous studies, our robust analysis does not provide evidence of an indirect effect of maternal education on academic performance within adolescents' social circles in Add Health.

Ukrainian-Russian bilingualism in the war-affected migrant and refugee communities in Austria and Germany: a survey-based study on language attitudes

Introduction

This paper provides an initial exploration of Ukrainian-Russian bilingualism in the context of the war-affected migration from Ukraine to Austria and Germany. While extensive research exists on various aspects of Ukrainian- Russian bilingualism in relation to Ukraine itself, thus far no studies have been conducted on this bilingualism in the diasporic context, i.e., as a language of the first and subsequential generations with a migrant background in Austria and Germany.

Methods

To address this research gap, our paper examines the language attitudes of two respondent groups with a Ukrainian background in the two countries: migrants and refugees who left Ukraine after 2014 and those who left after Russia's invasion in February 2022. In the framework of a sociolinguistic survey, we describe their current attitudes regarding the use of Ukrainian and Russian, among others, in relation to the actual and intended use of the language(s) in the multilingual context of migration. The survey eliciting information on demographic information, language proficiency, language attitudes and language use was conducted on 406 Ukrainians in two host countries (Austria: n = 103; Germany: n = 306). First, we compared self-rated proficiency in Ukrainian and Russian as well as attitudes and use of these languages. Second, we applied a network modelling analysis to determine the nature of relationships between these variables.

Results and discussion

The results indicated that proficiency in Ukrainian and in Russian were the strongest nodes in the model affecting language use and language attitudes toward the respective languages. Our data analysis focused on the pragmatic and symbolic value of Russian and Ukrainian playing a crucial role in the language vitality in multilingual settings. The paper discusses the imbalanced correlation of the symbolic and pragmatic value of Ukrainian and Russian in the diasporic Ukrainian communities. While Ukrainian has gained a higher symbolic status, Russian maintains a better pragmatic one, despite its negative symbolic status. However, we anticipate that the increasing symbolic value of Ukrainian and the diminishing value of Russian will lead to an increase in the use of Ukrainian also in Russian-dominant bilingual groups of Ukrainian migrants and refugees, even as an insider-code in hermetic minority groups.

Modeling lexical abilities of heritage language and L2 speakers of Hebrew and English in Israel and the United States: a network approach

Introduction

This paper examines the productive vocabulary skills of five groups of English-Hebrew bilinguals in Israel and the United States. The juxtaposition of these five groups allows us to simultaneously compare performance across dominance profiles, acquisition contexts (L2 learned in school, HL maintained at home, immigration and immersion), and countries (Israel and the USA).

Methods

A total of 185 participants took part in study: Hebrew-dominant heritage English speakers, Hebrew-dominant L2-English speakers, English-dominant heritage Hebrew speakers, and English-dominant L2-Hebrew speakers in the US and in Israel. They were all administered the MINT assessment in both languages, as well as background questionnaires. We then employ network modeling based on a secondary data analysis of background questionnaires to consider how each group's lexical proficiency ties in to reported input factors.

Results and discussion

The MINT results indicate clear language dominance in all the groups except Hebrew-dominant heritage English speakers, who show balanced proficiency in both their languages. The network models indicate key distinctions between the groups as a function of linguistic context, and we assess our findings in the context of recent work on quantifying the bilingual experience.

The relations of psychotic-like experiences (PLEs) and depressive symptoms and the bias of depressive symptoms during the clustering among Chinese adolescents: Findings from the network perspective

BACKGROUND

There are rare studies about the network structure of psychotic-like experiences (PLEs) and depressive symptoms among adolescents. Studies have widely acknowledged that PLEs in adolescents confer a higher risk of depressive symptoms, but the complex interactions remain inadequately understood. Our study aimed to examine the hierarchy and inter-associations of PLEs and depressive symptoms in a large adolescent sample from the network analysis perspective.

METHODS

A total of 5008 Chinese adolescents were enrolled in our sample. Community Assessment of Psychic Experiences-42 (CAPE-42) was applied to build the network. Centrality indexes were calculated to represent the significance of nodes in the network. Community detection was conducted to figure out the specific clustering of nodes. Demographic information was collected for the sub-network comparisons. Accuracy and stability of the network were also tested.

RESULTS

"Failure", "External control", and "Lack of activity" were the most central nodes. The main bridge nodes linking PLEs and depressive symptoms were "Failure", "Guilty", and "No future". Positive PLE "Odd looks" and negative PLE "Unable to terminate" are the two PLEs that were most relevant to depressive nodes. Community detection further demonstrated the bias of depressive nodes in the data-driven clustering. Comparative sub-network analysis suggested that age was the only demographic factor related to the current network.

CONCLUSION

In this study of a large adolescent sample, we first demonstrated the network structure and specific clustering preference of PLEs and depressive symptoms. Our findings may enhance the understanding of the relationship between PLE and depressive symptoms.

Prevalence, correlates, and network analysis of depression and its association with quality of life in survivors with myocardial infarction during the COVID-19 pandemic

BACKGROUND

Depression is common among myocardial infarction (MI) survivors and is strongly associated with poor quality of life (QOL). The aim of this study was to examine the prevalence, correlates and the network structure of depression, and its association with QOL in MI survivors during the COVID-19 pandemic.

METHODS

This cross-sectional study evaluated depression and QOL in MI survivors with the Chinese version of the nine-item Patient Health Questionnaire (PHQ-9) and World Health Organization Quality of Life-BREF (WHOQOL-BREF) respectively. Univariable analyses, multivariable analyses, and network analyses were performed.

RESULTS

The prevalence of depression (PHQ-9 total score ≥ 5) among 565 MI survivors during the COVID-19 pandemic was 38.1 % (95 % CI: 34.1-42.1 %), which was significantly associated with poor QOL. Patients with depression were less likely to consult a doctor regularly after discharge, and more likely to experience more severe anxiety symptoms and fatigue. Item PHQ4 "Fatigue" was the most central symptom in the network, followed by PHQ6 "Guilt" and PHQ2 "Sad mood". The flow network showed that PHQ4 "Fatigue" had the highest negative association with QOL.

CONCLUSION

Depression was prevalent among MI survivors during the COVID-19 pandemic and was significantly associated with poor QOL. Those who failed to consult a doctor regularly after discharge or reported severe anxiety symptoms and fatigue should be screened for depression. Effective interventions for MI survivors targeting central symptoms, especially fatigue, are needed to reduce the negative impact of depression and improve QOL.

Fear network and pain extent: Interplays among psychological constructs related to the fear-avoidance model

OBJECTIVE

Psychological constructs related to the fear-avoidance model such as fear of movement, pain catastrophizing, and affective distress have been found to be inter-related among patients with chronic pain. However, relationships of these constructs have mostly been examined using regression-based analyses. This cross-sectional study employs a novel analytical approach, network analysis, to illustrate the complex interplays among these variables as well as pain intensity and pain interference.

METHODS

This study utilized the Swedish Quality Registry for Pain Rehabilitation, including data from 10,436 participants (76.0% women; M_age = 45.0 years). Networks were analyzed separately for patients with different pain extents (i.e., numbers of pain locations) as the interplays may differ qualitatively depending on pain extent.

RESULTS

We found that patients with a larger pain extent showed a worse clinical presentation (i.e., more depression and anxiety, increased fear of movement and pain interference), and their network differed from the patients with a smaller number of pain extent in terms of how strongly key variables were interconnected. In all network models, pain interference and catastrophizing showed consistently influential roles.

CONCLUSION

Our findings highlight the interactive nature of psychological aspects of pain and how interrelated associations differ depending on pain extent. Findings are discussed based on ideas on how both fear and pain become overgeneralized.

Emotion Regulation in the Classroom: A Network Approach to Model Relations among Emotion Regulation Difficulties, Engagement to Learn, and Relationships with Peers and Teachers

Emotion regulation is theorized to shape students' engagement in learning activities, but the specific pathways via which this occurs remain unclear. This study examined how emotion regulation mechanisms are related to behavioral and emotional engagement as well as relations with peers and teachers. The sample included 136 secondary school students (59,7% girls; M_age = 14.93, SD_age = 1.02, range: 13-18 years). Psychometric network models revealed that difficulties in emotional awareness, emotional clarity, and access to emotion regulation strategies were differentially related to behavioral and emotional engagement, establishing an indirect link with teacher and/or peer relations. Nonacceptance of emotional responses, emotional awareness, and impulse control difficulties were uniquely related to teacher and/or peer relations, establishing an indirect link with student engagement. Causal discovery analysis suggested that student emotional engagement is an empirically-plausible direct cause of increased access to emotion regulation strategies. These findings uncover potential pathways through which emotion regulation hampers or facilitates learning at school, providing information useful for the design of school curricula and teacher training programs.

Internet addiction and its association with quality of life in patients with major depressive disorder: a network perspective

Depressive disorders and internet addiction (IA) are often comorbid. The aims of this study were to examine the network structure of IA in patients with major depressive disorders (MDD) and explore the association between IA and quality of life (QoL) in this population. This was a multicenter, cross-sectional survey. IA and QoL were assessed with the Internet Addiction Test (IAT) and the World Health Organization Quality of Life-brief version, respectively. Node expected influence (EI) was used to identify central symptoms in the network model, while the flow network of QoL was generated to examine its association with IA. A total of 1,657 patients with MDD was included. "Preoccupation with the Internet," "Job performance or productivity suffer because of the Internet," and "Neglect chores to spend more time online" were central symptoms. The symptom "Form new relationships with online users" had the strongest direct positive relation with QoL, while "Spend more time online over going out with others" and "Job performance or productivity suffer because of the Internet" had the strongest direct negative relations with QoL. Neglecting work caused by IA correlated with QoL, while making friends online appropriately was related to better QoL among MDD patients. Appropriate interventions targeting the central symptoms may potentially prevent or reduce the risk of IA in MDD patients.

Autistic Symptoms and Social Functioning in Psychosis: A Network Approach

Psychotic and autistic symptoms are related to social functioning in individuals with psychotic disorders (PD). The present study used a network approach to (1) evaluate the interactions between autistic symptoms, psychotic symptoms, and social functioning, and (2) investigate whether relations are similar in individuals with and without PD. We estimated an undirected network model in a sample of 504 PD, 572 familial risk for psychosis (FR), and 337 typical comparisons (TC), with a mean age of 34.9 years. Symptoms were assessed with the Autism Spectrum Quotient (AQ; 5 nodes) and the Community Assessment of Psychic Experiences (CAPE; 9 nodes). Social functioning was measured with the Social Functioning Scale (SFS; 7 nodes). We identified statistically significant differences between the FR and PD samples in global strength (P < .001) and network structure (P < .001). Our results show autistic symptoms (social interaction nodes) are negatively and more closely related to social functioning (withdrawal, interpersonal behavior) than psychotic symptoms. More and stronger connections between nodes were observed for the PD network than for FR and TC networks, while the latter 2 were similar in density (P = .11) and network structure (P = .19). The most central items in strength for PD were bizarre experiences, social skills, and paranoia. In conclusion, specific autistic symptoms are negatively associated with social functioning across the psychosis spectrum, but in the PD network symptoms may reinforce each other more easily. These findings emphasize the need for increased clinical awareness of comorbid autistic symptoms in psychotic individuals.

Exploring inclusiveness towards immigrants as related to basic values: A network approach

Using the 9th round of European Social Survey (ESS), we explored the relationship between Europeans' basic values and their attitudes towards immigrants. Employing a latent class analysis (LCA), we classified the respondents based on three items capturing the extent to which participants would support allowing three groups of immigrants to enter and live in their countries: immigrants of same ethnic groups, immigrants of different ethnic groups, and immigrants from poorer countries outside Europe. Four classes of Europeans with mutually exclusive response patterns with respect to their inclusive attitudes towards immigrants were found. The classes were named Inclusive (highly inclusive), Some (selective), Few (highly selective), and Exclusive (highly exclusive). Next, using a network technique, a partial correlation network of 10 basic human values was estimated for each class of participants. The four networks were compared to each other based on three network properties namely: global connectivity, community detection, and assortativity coefficient. The global connectivity (the overall level of interconnections) between the 10 basic values was found to be mostly invariant across the four networks. However, results of the community detection analysis revealed a more complex value structure among the most inclusive class of Europeans. Further, according to the assortativity analysis, as expected, for the most inclusive Europeans, values with similar motivational backgrounds were found to be interconnected most strongly to one another. We further discussed the theoretical and practical implications of our findings.

The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: a randomized clinical trial

BACKGROUND

Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment.

METHODS

In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy.

RESULTS

At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar.

CONCLUSION

Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.

Predicting Student Well-Being: Network Analysis Based on PISA 2018

The latest trends in research extend the focus of school effectiveness beyond students’ acquisition of knowledge and skills, looking at aspects such as well-being in the academic context. Although the concept of well-being itself has been defined and measured in various ways, neither its dimensions nor the relationships between the components have been clearly described. The aim of the present study was to analyse how the elements of well-being interact and determine how they are influenced by school factors. To do that, we conducted a network analysis based on data from the Programme for International Student Assessment (PISA) 2018 international assessment. Our results demonstrated that cognitive, psychological, and social well-being variables form a solid welfare construct in the educational context, where students’ resilience and fear of failure, along with their sense of belonging, play central roles. Although the influence of school factors on student well-being is generally low, teaching enthusiasm and support promote positive school climates which are, in turn, crucial in reducing bullying.

Engagement SPIRALS in Elementary Students: A School-Based Self-Regulated Learning Approach

SPIRALS program was designed in accordance with the inclusive Universal Design for Learning approach and the social cognitive model of self-regulated learning. This project aims to promote cognitive, emotional, and behavioral engagement among elementary students, and especially those at high risk of dropping out (such as Roma students). To test the efficacy of the program, an intervention study was performed for four months within a truly inclusive learning environment, involving the whole classes. A quasi-experimental pre-test/post-test design with a control group (n = 63) and an experimental group (n = 57) was used. The dependent variables were student engagement (cognitive, emotional, and behavioral), academic self-concept, perceived climate of support, reading comprehension, and academic performance. Students in the experimental group exhibited statistically significant improvements compared to the control group in six of the seven dependent variables analyzed (behavioral and emotional engagement, academic self-concept, perceived climate of support, reading comprehension, and academic performance). Further, the magnitude of differences tended to be larger in student engagement, perceived climate of support, and reading comprehension than in academic self-concept or academic performance. These results provide evidence supporting the usefulness of intervention programs aimed at promoting student engagement, specifically among students at higher risk of failure or dropout.