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Abstract: Identifying and promoting students’ social-emotional strengths is essential in building their mental health. Covitality, representing the co-occurrence of psychological strengths, is a helpful framework for characterizing students’ well-being. This study used latent profile analysis to identify adolescents’ (n = 11,217; 50.3% female, 37.8% male; grades 9 [33.7%], 10 [21.0%], 11 [28.9%], and 12 [16.5%]) covitality patterns across 12 social-emotional health domains. We investigated whether student demographic characteristics (i.e., sex, parent educational attainment, ethnic identification) were related to profile membership. We further examined profiles’ relations to students’ proximal academic and mental health outcomes, including self-reported grades, school connectedness, life satisfaction, and psychological distress. Four covitality profiles were identified—High, Moderate-High, Moderate-Low, and Low. Profile membership was statistically significantly related to students’ sex and socioeconomic circumstances but with small effect sizes. We identified consistent differences across covitality profiles on student self-reported proximal outcomes. Overall, students in profiles with higher covitality levels (High and Moderate-High) reported (a) higher grades, school connectedness, and life satisfaction and (b) less psychological distress, with students in the High profile reporting the most favorable outcomes. Assessing students’ strengths and providing interventions focused on building strengths across domains are recommended.

Abstract: Managing the COVID-19 pandemic involved implementing public health policies that disrupted students’ lives, creating conditions that substantially influenced their mental health and well-being. Subsequently, research focused on the mental health sequelae of increased depression and anxiety, but the possible impacts on adolescents’ social well-being have been largely unexamined. Social well-being is essential to youth’s overall mental health and can be diminished even without symptoms of depression and anxiety. This report explored heterogeneities in changes in adolescents’ social well-being from pre-COVID-19 to post-restrictions using longitudinal data from adolescents attending middle and high schools in California (N = 1,299; 49.9% female). Data collection involved four observations. Participants completed a school-based mental health wellness survey annually from 2019 to 2022. A latent profile analysis identified five profiles demonstrating distinctive social well-being trajectories. Two ordered profiles included Stable-High (28%) and Stable-Low (26%) patterns. Three groups represented nonordered profiles labeled as Succumbing (20%), Languishing (14%), and Recovering (12%). Pervasive decreases in social well-being were observed, and a significant portion of the adolescents did not recover to their pre-COVID-19 level by 2022. Adolescents in the Stable-High and Recovering profiles showed better psychological well-being, optimism, and school connectedness and less distress than their counterparts in the other three profiles. Mental health professionals should be aware of the pandemic’s effects on adolescents’ social well-being. Lower levels of social well-being may be a risk factor for adolescents developing generally jaded attitudes about their social networks and diminishing their potential engagement with sources of social support.

There is a growing body of research on the importance of students engaging and learning by interacting with racially/ethnically diverse people, less is known about the effects of student interactions with others across other various aspects of difference (e.g., religion, political beliefs, gender, sexual orientation), and how this may impact on their awareness and understanding of various aspects and issues of difference. We used latent class analysis (LCA) to illustrate how college students can be classified into groups based on their openness to learning from diverse others. The LCA revealed four latent classes: global openness (14%), openness to visible diversity (12%), openness to less visible diversity (8%), and low openness (66%). The findings suggest that approximately two thirds of students perceive their interactions with diverse others as having little to no effect on their understanding of others' perspectives. However, students who were open to some type of diversity (regardless of that diversity) reported an increase in their awareness and understanding of various aspects and issues of difference. We conclude with implications of the findings for institutions. [ABSTRACT FROM AUTHOR]

Undocumented college students face systemic oppression, which they challenge through advocacy. Often, research focuses on one type of advocacy, but Advocacy Communication Theory (ACT) conceptualizes advocacy as multidimensional – minoritized people can engage in communicative strategies at the interpersonal, mediated, community, organizational, and policy levels to challenge oppression. Here, we used three waves of longitudinal survey data from 366 undocumented students, primarily of Latine origin, and conducted latent profile analyses. We found four advocacy communication profiles: Infrequent, Interpersonal, Organizational, and Frequent Advocators. The more students observed their family engage in undocumented advocacy, and the more students saw negative media depictions of undocumented immigrants, the more likely students were to be frequent advocators than infrequent advocators. Our findings support ACT's propositions. [ABSTRACT FROM AUTHOR]

Decades of disaster research support the influence parents have on their children's adaptation. Recently, research has shifted to focus on disasters as a whole family experience. Using the actor-partner interdependence model, this study examines maladaptive cognitive emotion regulation strategies in parents and children and how these strategies influence their own and one another's posttraumatic stress symptoms (PTSS). The present study includes 485 parent–child dyads who experienced the 2015–2016 Texas floods. The majority of parents identified as mothers (66.3%), with a male child (52.8%) whose average age was 13.75 years. Mplus was used to identify the models and evaluate differences between each cognitive emotion regulation strategy across parent–child dyads in the high disaster exposure group compared to all other levels of exposure (other-exposure). Odds ratios examined differences not captured by the actor-partner interdependence model. Support for interdependence was found for the other-exposure group, suggesting parents and children mutually influence each other's PTSS by their own cognitive emotion regulation. No interdependence was found in the high-exposure group. However, high-exposure child actor effects were found for self-blame and other-blame, and child partner effects were only found for self-blame. Parent actor effects were only significant for catastrophizing and parent partner effects for catastrophizing and rumination. Odds ratios for the high-exposure group found that only child self-blame influenced parent PTSS, and only parent rumination and catastrophizing influenced child PTSS. Implications for supporting families after disasters are discussed. [ABSTRACT FROM AUTHOR]

Emerging research suggests English and Spanish proficiencies of young Latine dual language learners (DLLs) are heterogeneous, including subgroups characterized by varying levels of English and Spanish dominance and proficiencies. However, there is limited understanding of contextual factors associated with the formation of DLL profiles. This study extends previous work by examining within-group variability in Spanish–English speaking DLLs' (n = 330) cognitive, linguistic, literacy, and math skills at the end of prekindergarten (M = 5.09 years old), their family (n = 313) characteristics, and their classrooms (n = 84). Using latent profile analysis, we identified four profiles of DLLs (English dominant, balanced average, Spanish dominant, emerging bilinguals), four profiles of parents (low parent education, high mother education, high parent education, high father education), and two profiles of classrooms (teachers with high education with high training and teachers with low education with low training). In general, the balanced average child profile outperformed the other child profiles in English and Spanish, and their norm-referenced standard scores provide additional evidence that bilingual development is not associated with educational risk. There was not a statistically significant correspondence between the parent and child profiles; however, the correspondence between the teacher and child profiles suggests that over half of the children taught by teachers with high education and training are in balanced average or Spanish-dominant profiles. A larger proportion of DLLs in the emerging-bilingual profile are in classrooms with teachers characterized by low education and little professional development as compared to the other three profiles. Educational Impact and Implications Statement: The results of this study highlight that preschool-aged Latine dual language learners (DLLs) are heterogeneous in terms of their cognition, language, literacy, and math skills. Four main profiles were identified (i.e., English dominant, balanced average, Spanish dominant, emerging bilingual). School personnel should consider these bilingual profiles when making decisions about assessment accommodations and individualized instructional models. Additional attention should be directed at identifying DLLs with low proficiencies in both English and Spanish. In the absence of early access to evidence-based intervention, these students will likely fall further and further behind their peers as they progress in school. The results also show the importance of teacher education and ongoing professional development. As the number of DLLs in U.S. schools increases, a larger investment must be made in preparing our teacher workforce to meet the instructional needs of DLL children. [ABSTRACT FROM AUTHOR]

Mixture modeling is a latent variable (i.e., a variable that cannot be measured directly) approach to quantitatively represent unobserved subpopulations within an overall population. It includes a range of cross-sectional (such as latent class [LCA] or latent profile analysis) and longitudinal (such as latent transition analysis) analyses and is often referred to as a "person-centered" approach to quantitative data. This research methods paper describes one type of mixture modeling, LCA, and provides examples of how this method can be applied to discipline-based education research in biology and other science, technology, engineering, and math (STEM) disciplines. This paper briefly introduces LCA, explores the affordances LCA provides for equity-focused STEM education research, highlights some of its limitations, and provides suggestions for researchers interested in exploring LCA as a method of analysis. We encourage discipline-based education researchers to consider how statistical analyses may conflict with their equity-minded research agendas while also introducing LCA as a method of leveraging the affordances of quantitative data to pursue research goals aligned with equity, inclusion, access, and justice agendas., Competing Interests: Conflicts of interest: The authors declare no conflicts of interest.