Description:

Co-Principal Investigators: Karen Nylund-Gibson, Erin Dowdy

Purpose: The project, a collaboration involving UC Santa Barbara, WestEd, and the California Department of Education, refined and validated the Social Emotional Health Survey-Secondary (now identified as SEHS-S-2020). This measure assesses students' essential social-emotional assets during the secondary school years (Grades 9–12), a developmental stage characterized by increasing academic demands, diverse and complex social interactions/relationships, and challenges associated with the crucial transition into adult life and its related responsibilities. During this developmental stage, efforts to foster students' life and social emotional dispositions require access to well-validated assessments.

Project Activities: The project team examined the SEHS-S-2020's psychometric characteristics drawing on subsets of data from the California Student Wellness Study (CSWS; see, www.covitalityucsb.info). The survey was part of the California State Department of Education's effort to support the systematic collection of information that local education agencies use to monitor school quality indicators. The responses of 123,508 California students comprised the cross-sectional data set, which was used with confirmatory factor analysis to evaluate structural validity and invariance. Structural equation modeling evaluated concurrent validity with school connectedness/belonging, recent emotional distress, past-year suicidal ideation, self-reported school grades, and behavioral risk (cigarette use, vaping, alcohol use, and marijuana use).

The team also collected longitudinal SEHS-S-2020 responses of 1,372 students attending four California partner high schools. Students had a unique identifier that allowed us to track students' responses over three years for two cohorts: Grades 9–11 and Grades 10–12. Latent transition analysis identified common social emotional assets profiles and their stability across the high school years.

Key Outcomes:

• The SEHS-S-2020 is a psychometric valid instrument for English (Furlong et al., 2021; Wagle et al., 2020) and Spanish language versions (Hinton et al., 2021). Analyses supported structural validity (Furlong et al., 2021), internal consistency (Table 3, Furlong et al., 2021), and measurement invariance for gender (Table 4, Furlong et al., 2021), grade level (Table 5, Furlong et al., 2021), and ethnic identification (Table 7, Furlong et al., 2021).
• The team developed and established the validity of the Social Emotional Distress Scale (SEDS), a brief (10-item) self-report of adolescent distress (Dowdy et al., 2018). The SEDS was co-administered with the SEHS-S-2020 and provided a practical way for schools to meaningfully implement the mental wellness screening Dual-Factor Model, as described in Furlong et al., 2022). Excellent short-term (4 month, Table 9, Furlong et al., 2020) and long-term (one year, Furlong et al., 2021) stability was documented (Furlong et al., 2021.)
• The SEHS-2020 also had wider impact as it was adopted and validated for use in China, Korea, Japan, Mexico, Chile, Spain, Turkey, Iran, Slovakia, Latvia, and the Netherlands. The Scottish government uses SEHS-S items in its TeenCovidLife longitudinal study.
• An unplanned positive grant outcome is that a number of schools in the cross-sectional sample were in unified school districts, which included Grades 7 and 8. As a result the cross-sectional sample included more 30,000 junior high school students. These responses were used to evaluate the SEHS-S-2020 validity and reliability for early adolescents (Furlong, et al., 2021, forthcoming ).

Products

• Comprehensive SEHS-S-2020 Manual: Modification and Standardization of Social Emotional Health Survey-Secondary—2020 Edition
• The SEHS-S-2020 and the SEDS are now included in the CHKS Core Module.
• Development of the Covitality social emotional wellness app for administration, scoring, reporting, and managing school-based screening and monitoring. https://covitality.com/

Structured Abstract

Setting: The project's main activities involved surveying secondary school students across California. Researchers collected self-reports from a cross-sectional sample from high schools using a stratified, two-stage cluster sampling design from three geographic regions of California. The cross-sectional sample included students from 19 of the state's 58 counties from urban, suburban, and rural communities. These schools were involved in the current study as part of their regularly scheduled biennial CHKS survey administration. Most of these schools were traditional public high schools (87.4%) or public charter schools (11.4%).

Sample:  Students (Grades 9-12) completed the CHKS Core Module (students report on substance use, school safety, school climate) and a second module that included the SEHS-S-2020 and the project-developed SEDS. These student responses were used for the structural validity (N = 72,740) and the criterion validity analyses (N = 11,217). Students completed the survey between September 2017 and May 2019. Seventy of the 113 cross-sectional sample schools surveyed only ninth (40.2% of the sample) and eleventh graders (33.9% of the sample), per standard CHKS administration procedures. The sample included 49.7% Latinx-identifying students, and 36.1% identified with two or more traditional census racial groups. Complete sample information is in Table 1, Furlong et al. (2021).

The research team examined response stability with a longitudinal sample drawn from four collaborating California high schools. As part of the stability investigation, 707 students completed the SEHS-S-2020 in the fall of 2017 and approximately one year later in 2018. See Table 1 (Furlong et al., 2021) for descriptive information.

The team examined short-term stability using a subsample of the September 2018 (T1) longitudinal sample. In January 2019 (T2), a random subsample of students (N = 200) equally divided among Grades 9–12 (n = 50 from each grade level), completed the SEHS-S-2020.

A longitudinal sample was created from students attending four California partner high schools. Students had a unique identifier that allowed us to track students' responses over three years for two cohorts:  Grades 9–11 and Grades 10–12. Latent transition analysis identified common social emotional assets profiles and their stability across the high school years. See p. 13–18 of the grants' final report and forthcoming article Moore, Carter, et al., in preparation.

Assessment: The SEHS-S-2020 conceptual framework posits that internal assets exert their primary effects by fostering an upward positive developmental spiral in the quality of youths' interpersonal transactions. Flourishing development occurs by nurturing various core dispositions (i.e., the sum is greater than its parts). The primary effects of these dispositions emerge via the day-to-day transactions a youth has with the adults, family, and peers in their immediate social ecosystems. Educators immersed intimately in youths' social circles play an essential role in fostering these psychological dispositions. Positive developmental outcomes increase when youth possess the internal dispositions and skillsets to influence the quality of their daily interpersonal interactions. This conceptualization draws upon the positive youth development perspective and as in self-determination theory by emphasizing the importance of creating conditions that empower youth to make things happen in their lives rather than passively letting them happen.

The SEHS-S-2020 itself has 36 items that assess secondary students' self-reports of social and emotional strengths. The hypothesized latent trait model has three-level, one general factor model with four domains and 12 subscales (three items per subscale) that load onto four domains: belief in self (self-awareness, persistence, self-efficacy), belief in others (school support, family coherence, peer support), emotional competence (empathy, self-control, behavioral self-control), and engaged living (gratitude, zest, and optimism). The four domains loaded onto one general factor called covitality (see Figure 2, Furlong et al., 2020; and Figure 1, Furlong et al., 2021).

Research Design and Methods: California students who completed the CHKS Core, SEHS-S, and SEDS items between September 2017 and May 2019 were considered for inclusion in the project sample. In year 1 (2016/17), the research team reviewed item content and response formats and administered the SEHS-S to a sample of 1889 students. The responses were used to select the optimal response format and to conduct a preliminary evaluation of the hypothesized factor model fit (Gordon Wolf et al., 2019). During 2017/18, 2018/19, and 2019/20, researchers  compiled cross-sectional and longitudinal data sets to investigate the criterion validity, response consistency, and stability of student responses to the SEHS-S. During 2020–21, they investigated strategies for evaluating the credibility of SEHS-S self-reports to facilitate interpretation and appropriate use by high schools and identified students' SEHS-S responses for the presence of empirically defined interpretation subtypes or classes.

Key Measures: The SEHS-S was the focal instrument that was developed by the researchers and was built upon a developmentally-grounded theoretical model. The 36-item SEHS-S edition assesses 12 psychosocial strengths derived from the social emotional learning (SEL) and positive youth development (PYD) literatures. The 12 (three items each) subscales are associated with four correlated general positive social emotional health domains that assess the higher-order covitality latent construct.

• The first domain, belief-in-self, consists of three subscales grounded in constructs from self-determination theory literature: self-efficacy, self-awareness, and persistence.
• The second domain, belief-in-others, comprises three subscales derived from constructs found chiefly in the childhood resilience literature: school support, peer support, and family support.
• The third domain, emotional competence, consists of three subscales based on constructs drawn from the SEL scholarship: emotion regulation, empathy, and behavioral self-control.
• The final domain engaged living, comprises three subscales grounded in constructs derived from the positive youth psychology literature: gratitude, zest, and optimism.

Other essential validation measures were the Social Emotional Distress Scale (SEDS), the Multidimensional Student Life Satisfaction Scale, and the Mental Health Continuum-Short Form. These measures helped assess if SEHS-S-2020 constructs related in excepted ways with other social/emotional factors that support or diminish learning (e.g., personal distress, school satisfaction, school connectedness, student learning strategies, subjective well-being).

Data Analytic Strategy: The primary data analytic methods to accomplish this study's psychometric, interpretation, and usability aims included exploratory and confirmatory factor analysis, measurement invariance analysis, internal consistency, correlational reliability and validity analyses, analysis of variance, and latent profile and latent transition analysis.

Project website:  http://covitalityucsb.info

Additional online resources and information:

• Monitoring Students' Social-Emotional Wellness (2-hour webinar)
• SHE-S-2020 Covitality Model Overview
• Dual Factor Model Complete Mental Health Screening Overview

Products and Publications

Carnazzo, K., Dowdy, E., Furlong, M. J., & Quirk, M. (2019). An evaluation of the Social Emotional Health Survey-Secondary for use with students with learning disabilities. Psychology in the Schools, 56, 433–446. https://doi.org/10.1002/pits.22199 EJ1204832

Chan, M., Dowdy, E., Nylund-Gibson, K., Carter, D., & Furlong, M. J. (2021). Heterogeneity Among Moderate Mental Health Students on the Mental Health Continuum-Short Form (MHC-SF). School Mental Health. Published online, 04 October 2021. https://doi.org/10.1007/s12310-021-09476-0 (submitted to ERIC)

Chan, M., Sharkey, J. D., Nylund-Gibson, K., Dowdy, E., & Furlong, M. J. (in press). Social support profiles associations with adolescents' psychological and academic functioning. Journal of School Psychology. (submitted to ERIC)

Chan, M., Yang, C., Furlong, J., Dowdy, E., & Xie, J-S. (2021). Association between social-emotional strengths and school membership: A cross-cultural comparison. International Journal of School & Educational Psychology, 9(2), 158–171. https://doi.org/10.1080/21683603.2019.1677539 EJ1303393

Dowdy, E., Furlong, M. J., Nylund-Gibson, K., Moore, S., & Moffa, K. (2018). Initial validation of the Social Emotional Distress Survey-Secondary to support complete mental health screening. Assessment for Effective Intervention. Intervention, 43, 241–248. https://doi.org/10.1177%2F153450841774987 EJ585101

Furlong, M. J. (2018). A comment on school safety and mental wellness, including covitality. In E. Gajdošová, M. Madro, & M. Valihorová (Eds.), Duševné zdravie a wellbeing virtuálnej generácie Zborník príspevkov z medzinárodnej vedeckej konferencie 21.11.2018. [Intellectual health and wellbeing of the virtual generation: Proceedings of the International Scientific Conference 21.11.2018.] (pp. 12–19). Bratislava, Slovakia. ED592263

Furlong, M. J., Dowdy, E., Moore, S., & Kim, E. (2022). Adapting the dual-factor model for universal school-based mental health screening: Bridging the research to practice divide. In K-A. Allen, M. J. Furlong, S. Suldo, & D. Vella-Brodrick (Eds.), Handbook of positive psychology in schools: In support of positive educational processes(3rd ed., Chap. 5).Routledge, Taylor and Francis.  https://www.routledge.com/Handbook-of- Positive-Psychology-in-Schools-Supporting-Process-and- Practice/Allen-Furlong-Vella-Brodrick-Suldo/p/book/9780367855864? gclid=Cj0KCQiA0eOPBhCGARIsAFIwTs6_ZpNoDloYvqzjxkip _Ul6nRk_Z2rhD2osh5N8hzG6g_GGNlpuDSAaAvAhEALw_wcB

Furlong, M. J., Dowdy, E., Nylund-Gibson, K., Wagle, R., Carter, D., & Hinton, T. (2021). Enhancement and standardization of a universal social-emotional health measure for students' psychological strengths. Journal of Well-Being Assessment, 4, 245–267.  https://doi.org/10.1007/s41543-020-00032-2. ED612144

Furlong, M. J., Paz, J. L., Carter, D., Dowdy, E., Nylund-Gibson, K. (2021). Extending validation of a covitality social emotional health measure to middle and junior high school students. In review.

Furlong, M. J., Smith, D. C., Springer, T., & Dowdy, E. (2021). Bored with school! Bored with life? Well-being characteristics associated with a school boredom mindset. Journal of Positive School Psychology, 5(1), 42–64. https://www.journalppw.com/ index.php/JPPW/article/view/261/95. ED612166

Hinton, T., Dowdy, E., Furlong, M. J., & Nylund-Gibson, K. (2021). Examination of the Social Emotional Distress Survey-Secondary for use across sociocultural groups. In review.

Hinton, T., Dowdy, E., Nylund-Gibson, K., Furlong, M. J., & Carter, D. (2021). Examining the Social Emotional Health Survey-Secondary for use with Latinx youth. Journal of Psychoeducational Assessment, 39, 242–246. https://doi.org/10.1177/0734282920953236 EJ1290904

Moore, S., Dowdy, E., Nylund-Gibson, K., & Furlong, M. J. (2019). A latent transition analysis of the longitudinal stability of dual-factor mental health in adolescence. Journal of School Psychology, 73, 56–73. https://doi.org/10.1016/j.jsp.2019.03.003 (submitted to ERIC)

Moore, S., Dowdy, E., Nylund-Gibson, K., & Furlong, M. J. (2019). An empirical approach to complete mental health classification in adolescents. School Mental Health, 11, 438–453. https://doi.org/10.1007/s12310-019-09311-7 EJ1229740

Moore, S., Carter, D., Kim, E.K., Dowdy, E., Nylund-Gibson, K., Furlong, M. J. (In press). Adolescents' covitality patterns: Relations with student demographic covariates and academic and mental health outcomes.

Wagle, R., Dowdy, E., Furlong, M. J., Nylund-Gibson K., Carter, D., & Hinton, T. (2020). Anonymous vs. self-identified response formats: Implications for mental health screening in schools. Assessment for Effective Intervention. First online 30 September, 2020. https://doi.org/10.1177/1534508420959439 EJ614477