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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.

Schools are an essential setting for mental health supports and services for students. To support student well-being, schools engage in universal mental health screening to identify students in need of support and to provide surveillance data for district-wide or state-wide policy changes. Mental health data have been collected via anonymous and self-identified response formats depending on the purpose of the screening (i.e., surveillance and screening, respectively). However, most surveys do not provide psychometric evidence for use in both types of response formats. The current study examined whether responses to the Social Emotional Health Survey--Secondary (SEHS-S), a school mental health survey, are comparable when administered using anonymous versus self-identified response formats. The study participants were from one high school and completed the SEHS-S using self-identified (n = 1,700) and anonymous (n = 1,667) formats. Full measurement invariance was found across the two response formats. Both substantial and minimal latent mean differences were detected. Implications for the use and interpretation of the SEHS-S for schoolwide mental health are discussed.

Unprecedented financial and emotional stress, paired with measures to slow the spread of COVID-19 (e.g., school closures), place youth at risk for experiencing increased rates of abuse. We analyzed data from New York City's Administration for Children's Services to investigate the frequency of child maltreatment prevention service case openings during this time. Longitudinal counts of case openings were compiled for January through June of the years 2014-2020. An independent samples Kruskal-Wallis H-test suggested that pre-quarantine case openings were significantly larger than case openings during quarantine. To account for the possible influence of other historical events impacting data, a secondary Kruskal-Wallis H-test was conducted comparing only the 4 months of quarantine data available to the 4 months immediately preceding quarantine orders. The second independent samples Kruskal-Wallis H-test again suggested that pre-quarantine case openings were significantly larger than case openings during quarantine. A Poisson regression model further supported these findings, estimating that the odds of opening a new child maltreatment prevention case during quarantine declined by 49.17%. These findings highlight the severity of COVID-19 impacts on child maltreatment services and the gap between demand for services and service accessibility. We conclude with recommendations for local governments, community members, and practitioners.

The Social Emotional Health Survey-Secondary-2020 (SEHS-S-2020) is a well-studied option for assessing social emotional health to support students within a multitiered system of school support. While a growing body of literature supports the SEHS-S-2020 measure for assessing student covitality, there is less validation evidence specifically for middle-school-aged students. The present study aimed to fill this gap in the literature by examining its use for younger adolescents. Study participants were from two samples, including a cross-sectional sample with 9,426 students in Grades 7-8 from 32 counties in California and a longitudinal sample with 414 students in Grades 6-8 from two middle schools. Data analyses examined structural validity, internal consistency, measurement invariance, criterion validity, predictive validity, and response stability. Results indicate excellent fit indices for a four-level higher-order measurement model, with adequate concurrent and one-year predictive validity coefficients, supporting the use of the SEHS-S-2020 measure with young adolescents in middle school settings. The discussion focuses on implications for assessing students' psychosocial assets, universal school-based screening, and cultural and intersectionality considerations when interpreting SEHS-S-2020 responses.Supplementary informationThe online version contains supplementary material available at 10.1007/s40688-022-00411-x.

Culturally responsive assessment practices include validated measures appropriate for use with diverse populations. Considering the increasing population of Latinx students in US schools, measures need co-validated English and Spanish (Social and Emotional Health Survey (SEHS)) language forms. This study examined the SEHS-Secondary with Latinx students who completed a form in either Spanish or English. With a matched sample of 1404 Latinx students across 113 California schools, the analyses examined the factor structure, measurement invariance, and latent trait factor means of students who completed the SEHS in either Spanish or English. The factor structure was invariant across groups with some latent mean differences observed. Educational practice implications are considered.

Endeavors supporting college students' positive psychosocial development are gaining attention and investment in various countries and social contexts. Higher education experiences provide new academic, social, and vocational advancement opportunities at a critical developmental stage. However, higher education can also cause distress due to the challenges and stressors present during this new stage of increased independence. The Social Emotional Health Survey-Higher Education (SEHS-HE) assesses the core psychosocial strengths of individuals transitioning from secondary schools into institutions of higher education (IHE) to aid campus student support services. The present study sought to extend the SEHS-HE research by examining its application with college student samples from Mexico (n = 4,207), United States (n = 1,638), and Spain (n = 1,734). Confirmatory factor analyses investigated the hypothesized SEHS-HE higher-order factor model. The Mexico sample returned an acceptable model fit, but the USA and Spain samples had a suboptimal fit; hence, we explored alternative models. A two-level structure had full invariance for all three samples. This study extends the current scholarship on the conceptual model and psychometric properties of SEHS-HE. The discussion focuses on implications for future research to enhance SEHS-HE in national and cross-national research and practice.

Measures of positive well-being are needed to support the shift away from a deficit-based approach to mental health. This study examined one measure, the Mental Health Continuum-Short Form (MHC-SF), as a measure of positive well-being used in school-based mental health monitoring efforts. This study used latent profile analysis (LPA) to explore the mental health classifications of 10,880 California high school students' responses to MHC-SF emotional, psychological, and social well-being items. Five latent mental wellness profiles emerged, including two ordered profiles (i.e., High Well-Being and Low Well-Being) and three profiles spanning the two ordered profiles. The High Well-Being profile had the most favorable psychological adjustment, and the three moderate well-being range profiles had differentiated functioning. Informing the utility of the MHC-SF, this study also compared the MHC-SF categorical diagnostic criteria with the LPA's empirical classification approach and found the two classification approaches to be congruent. The findings provide an impetus for educators to attend to students in moderate well-being ranges and emphasize promoting positive mental well-being as an essential component of school-based mental health services.

AbstractRobust evidence links students’ positive mental health with academic achievement and provides a compelling rationale for developing and refining strength-based assessments. The Social Emotional Health Survey–Secondary (SEHS-S) assesses adolescents’ social and emotional skills and positive psychological dispositions. Previous studies provide reliability and validity evidence; nonetheless, there is a need for continued refinement and validation across diverse groups. The current study revised and standardized the updated SEHS-S-2020 to validate further its use in secondary schools (Grades 9–12) with a large, diverse adolescent sample. Study participants included 72,740 from 113 California schools (structural validation sample), 10,757 students from 15 randomly selected California schools (criterion validation sample), and 707 students from four additional California schools (test-retest sample). Data analyses examined structural validity, measurement invariance, criterion validity, internal consistency, and response stability. Results supported the SEHS-S-2020 validity across diverse groups of youth in various contexts. The discussion focuses on implications for assessing students’ psychosocial assets and universal school-based screening.

The Psychological Sense of School Membership (PSSM) scale has been used for more than 20 years to measure students' sense of school belonging, yet its psychometric properties have had limited examination with pre-adolescent children. This study investigated the utility and psychometrics of the PSSM in three primary school samples from the United States, China, and the United Kingdom. Exploratory factor analysis revealed good fit for a unidimensional factor structure in the US sample, which was subsequently confirmed in all three samples. Partial invariance across all three samples and full invariance across pairwise samples (United States and United Kingdom; United Kingdom and China) was found. Path analyses revealed significant positive relations of the PSSM total belonging score with gratitude and prosocial behavior, and significant negative relations with symptoms of distress. Future directions and implications are discussed. [For the corresponding grantee submission, see ED588824.]

Contemporary mental health assessment conceptualizations focus on both well-being and distress. This study presents initial validation information for the "Social Emotional Distress Survey--Secondary" (SEDS-S), which was designed for school-based complete mental health screening that employs brief self-report measures of well-being and distress. The SEDS-S structure was investigated using two independent samples of U.S. high school students (N = 3,780). Findings from exploratory and confirmatory factor analyses suggested a one-factor model of distress with good model fit. Path analyses revealed significant positive relations of the SEDS-S distress factor with symptoms of anxiety and depression, and a significant negative relation with life satisfaction and strengths scores. Future research directions and use in school-based screening applications are discussed. [For the corresponding grantee submission, see ED585101.]

AbstractRobust evidence links students’ positive mental health with academic achievement and provides a compelling rationale for developing and refining strength-based assessments. The Social Emotional Health Survey–Secondary (SEHS-S) assesses adolescents’ social and emotional skills and positive psychological dispositions. Previous studies provide reliability and validity evidence; nonetheless, there is a need for continued refinement and validation across diverse groups. The current study revised and standardized the updated SEHS-S-2020 to validate further its use in secondary schools (Grades 9–12) with a large, diverse adolescent sample. Study participants included 72,740 from 113 California schools (structural validation sample), 10,757 students from 15 randomly selected California schools (criterion validation sample), and 707 students from four additional California schools (test-retest sample). Data analyses examined structural validity, measurement invariance, criterion validity, internal consistency, and response stability. Results supported the SEHS-S-2020 validity across diverse groups of youth in various contexts. The discussion focuses on implications for assessing students’ psychosocial assets and universal school-based screening.

Background and objectivesProviding appropriate and culturally sensitive care to the rapidly growing number of U.S. Latinx older adults with psychiatric conditions presents a major public health challenge. We know little about older Latinx adults' perceived causes of mental health problems, offering clinicians limited insight to guide successful and culturally congruent treatment. Moreover, there is a paucity of mental health research examining heterogeneity in how Latinx individuals may attribute mental health symptoms. The present study sought to identify how Latinx and non-Latinx older adults attributed the sources of their mental health problems and how these types of attributions differ by ethnicity.Research design and methodsThis study analyzed data collected from a retrospective chart review and survey of 673 adults aged 55-95 years (430 Mexican origin and 244 non-Latinx) from a rural psychiatric outpatient clinic near the California-Mexico border. We conducted stratified latent class analysis (LCA) by race/ethnicity to explore the mental health attribution beliefs of Mexican-origin and non-Latinx clinic patients.ResultsDifferent LCA patterns for Mexican-origin Latinx versus non-Latinx groups were found. For non-Latinx adults, there was a class of individuals who attributed their mental health issues to social and financial problems. For Mexican-origin adults, there was a class of individuals who attributed their mental health issues to spiritual and/or supernatural factors, unaffected by acculturation level, depressive symptom severity, and time spent in the United States, but differing by gender. We found within-group heterogeneity: Not all Mexican-origin or non-Latinx older adults were alike in how they conceptualized their mental health.Discussion and implicationsMexican-origin Latinx and non-Latinx older adults attributed their mental health issues to different causes. More Mexican-origin older adults attributed their symptoms to spiritual causes, even after controlling for contextual factors. Further research is needed to determine whether attribution beliefs are affected by specific mental health diagnoses and other cultural factors not measured in this study.

Most disaster mental health research focuses on the relationship between disaster exposure and distress, often neglecting its influence on social-emotional health, despite implications for resilience and well-being after the disaster. Following multiple floods in Texas, a sample of 486 youth aged 10-19 years old (M = 13.74 years, SD = 2.57; 52.9% male) completed measures of disaster exposure, life stressors since the disaster, and social-emotional health. Using mixture regression modeling, we examined differences in the relationship between life stressors and social-emotional health across latent classes of disaster exposure (high, moderate, community, and low exposure). After accounting for mean levels of life stressors, the mean levels of social-emotional health did not differ across exposure classes; however, the strength of the relationship between life stressors and social-emotional health did. Youth in the high exposure group had the highest mean level of life stressors since the disaster. Thus, each additional life stressor did not result in changes in social-emotional health, suggesting saturated stress levels. For youth in the moderate and community exposure classes, increases in life stressors did lower social-emotional health, perhaps pushing them into stress overload. For the low exposure group, life stressors did not have an influence. This has implications for postdisaster mental health screening and support, tailored by levels of exposure and attuned to ongoing stressors that may impact long-term social-emotional health. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Using latent profile analysis (LPA), this study empirically identified dual-factor mental health subtypes, with a goal of examining structural stability of emerging latent classes over three high school years. Profiles relations with distal indicators of well-being, psychosocial distress, and self-reported grades were examined to explore the validity of emerging classes. A sample of 332 high school students reported on their social-emotional strengths and psychological distress during the fall term of their ninth-, tenth-, and eleventh-grade years. In Grade 12, students reported on measures assessing their grades and social-emotional experiences. Independent LPAs for each grade year yielded four mental health subtypes - complete mental health, moderately mentally healthy, symptomatic but content, and troubled - and provided evidence for the structural stability of the dual-factor mental health construct. Across high school years, most students were in the complete or moderately mentally healthy classes, with the troubled class consistently representing the smallest proportion of the sample. Students in classes with higher levels of strengths and lower levels of distress reported higher grades, prosocial contribution to community, and higher life satisfaction, and fewer symptoms of anxiety and depression. Implications and future directions for research and school-based practice are discussed.

Using latent profile analysis (LPA), this study empirically identified dual-factor mental health subtypes, with a goal of examining structural stability of emerging latent classes over three high school years. Profiles' relations with distal indicators of well-being, psychosocial distress, and self-reported grades were examined to explore the validity of emerging classes. A sample of 332 high school students reported on their social-emotional strengths and psychological distress during the fall term of their ninth-, tenth-, and eleventh-grade years. In Grade 12, students reported on measures assessing their grades and social-emotional experiences. Independent LPAs for each grade year yielded four mental health subtypes - complete mental health, moderately mentally healthy, symptomatic but content, and troubled - and provided evidence for the structural stability of the dual-factor mental health construct. Across high school years, most students were in the complete or moderately mentally healthy classes, with the troubled class consistently representing the smallest proportion of the sample. Students in classes with higher levels of strengths and lower levels of distress reported higher grades, prosocial contribution to community, and higher life satisfaction, and fewer symptoms of anxiety and depression. Implications and future directions for research and school-based practice are discussed.

Dual-factor models of mental health are increasingly supported but little is known about longitudinal trends in dual-factor mental health. The current study used latent profile analysis (LPA) to empirically identify dual-factor mental health classes at each of Grades 9 through 12 and latent transition analysis (LTA) to examine stability of classes over four academic years. A sample of 875 adolescents from two cohorts reported on their social-emotional strengths and psychological distress. Cross-sectional LPAs for each grade year resulted in four mental health classes: complete mental health, moderately mentally healthy, symptomatic but content, and troubled. An LTA model indicated that the complete mental health class exhibited the most stability, followed by moderately mentally healthy and symptomatic but content classes. The troubled class exhibited the least stability. Less than 24% of participants remained in the same mental health class across all years. Findings support regular monitoring of students dual-factor mental health to accurately inform mental health promotion, prevention, and intervention efforts.

Dual-factor models of mental health are increasingly supported but little is known about longitudinal trends in dual-factor mental health. The current study used latent profile analysis (LPA) to empirically identify dual-factor mental health classes at each of Grades 9 through 12 and latent transition analysis (LTA) to examine stability of classes over four academic years. A sample of 875 adolescents from two cohorts reported on their social-emotional strengths and psychological distress. Cross-sectional LPAs for each grade year resulted in four mental health classes: complete mental health, moderately mentally healthy, symptomatic but content, and troubled. An LTA model indicated that the complete mental health class exhibited the most stability, followed by moderately mentally healthy and symptomatic but content classes. The troubled class exhibited the least stability. Less than 24% of participants remained in the same mental health class across all years. Findings support regular monitoring of students' dual-factor mental health to accurately inform mental health promotion, prevention, and intervention efforts.

Disaster exposure can put survivors at greater risk for subsequent mental health (MH) problems. Within the field of disaster MH research, it is important to understand how the choice of analytic approaches and their implicit assumptions may affect results when using a disaster exposure measure. We compared different analytic strategies for quantifying disaster exposure and included a new analytic approach, latent class analysis (LCA), in a sample of parents and youth. Following exposure to multiple floods in Texas, a sample of 555 parents and 486 youth were recruited. Parents were predominantly female (70.9%) and White (60.8%). Parents were asked to have their oldest child between the ages of 10 and 19 years old participate (M = 13.74 years, SD = 2.57; 52.9% male). Participants completed measures on disaster exposure, posttraumatic stress, depression, and anxiety. The LCA revealed four patterns of exposure in both parents and youth: high exposure (15.5% parent, 9.5% child), moderate exposure (19.8% parent, 28.2% child), community exposure (45.9% parent, 34.4% child), and low exposure (18.8% parent, 27.8% child). In terms of MH, there were similarities across analytic approaches, but the LCA highlighted a threshold effect, with the high exposure class doing worse than all others, d = 1.12. These results have important implications in understanding the different exposure experiences of survivors and the linkage to MH outcomes. The findings are also informative in the development and use of screening tools used in postdisaster contexts in determining who may or may not need MH services.

Youth gang involvement is a serious public health challenge as adolescents involved in gangs are more likely than others to engage in violence and aggression. To better understand gang involvement, we examined the role of protective (empathy and parental support) and risk (peer deviance and lack of safety at school) factors, as well as their interactions, in predicting adolescent gang affiliation. The study involved a sample of 26,232 students (53.4% females; mean age = 14.62, SD = 1.69) participating in the California Healthy Kids Survey (CHKS), a survey investigating a wide range of youth health and risk behaviors administered in all California schools every 2 years. Using hierarchical linear modeling (HLM), findings indicated that high levels of empathy and parental support were associated with a lower likelihood of affiliating with a gang. Associating with deviant peers and perceiving the school as unsafe were positively correlated with gang membership. At the school level, lack of safety and type of school (special education, vocational, or alternative school vs. comprehensive schools) were associated with greater probability of gang membership. Empathy mitigated the association between deviant peers and gang membership.

This study extends current research by organizing information about students' expectancy-value achievement motivation, in a way that helps parents and teachers identify specific entry points to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task values and links these science-self-perceptions to interest in science. Findings suggest that there is a positive relationship between students' science self-perceptions and interest in science which is consistent with previous research (see for example, Aschbacher, Ing, & Tsai, 2014). The relationship between self-perceptions and interest in science was similar regardless of gender or ethnicity. Despite study limitations, self-perceptions should be considered valuable because teachers have influence on both learning activities and a students' sense of self as a science learner. These results underscore the importance of preparing teachers to foster student desire to learn more science in the future. In organizing the data using this particular methodology, information is provided in a potentially powerful way to target specific interventions or support.

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.