Psychometric Properties of the Social Emotional Health Survey-Primary: A Strengths-based Assessment of Student Covitality

In December 2024, we presented the results of a confirmatory factor analysis of the Social Emotional Health Survey-Primary (SEHS-P). Contributors included Kaitlynn M. Carter, Alexander M. Schoemann, Allison Dembowski (pictured above), Brandon K. Schultz, and Mark Weist (University of South Carolina).

Introduction

The Social Emotional Health Survey-Primary (SEHS-P) was based on the Positive Experiences at School Scale (PEAS; Furlong et al., 2013). The PEAS is designed to measure the overall construct of covitality or “the synergistic experience of well-being that results from the interactions of multiple school-grounded positive traits in youth” (p. 753). Covitality is measured through four subscales: gratitude (acknowledging transactions that benefit you), zest (having energy and excitement regarding life in general), optimism (having positive expectations and seeing failure/defeat in a positive light), and persistence (having passion/determination in pursuit of goals).

In the current study, we examined the performance of North Carolina and South Carolina elementary students on the SEHS-P’s four subscales related to covitality: (1) gratitude, (2) zest, (3) optimism, and (4) persistence.

Materials & Methods

Elementary students (n = 1,167) from eight NC schools and eight SC schools completed the SEHS-P via computer to measure their overall well-being and engagement in school. Demographic information, including gender, ethnicity, state, and grade level, were collected and analyzed.

Similarities across groups were investigated using measurement invariance testing via multiple-group categorical Confirmatory Factor Analysis (CFA). The measures of gratitude, zest, optimism, and persistence were compared across states, grade levels, gender, and ethnicity. Thresholds were constrained, and the following models were investigated: configural invariance, weak invariance, strong invariance, and mean invariance. Once invariance was established, the higher-order variable covitality was added to the model and configural invariance and metric invariance were investigated. All statistical analyses were conducted in R with the lavaan package used for to investigate multiple group CFA (R Core Team, 2022; Rosseel, 2012).

Results

Students’ performance on the four subscales of gratitude, zest, optimism, and persistence were compared across state (NC = 512; SC = 515), grade (3rd = 508; 4th = 519), gender (male = 521; female = 506), and ethnicity (black = 431; white = 365). Fit indices supported configural invariance for state, grade, gender, and ethnicity. We found weak, strong, and latent means invariance based on model comparisons for state, grade, and gender. Regarding ethnicity, latent means invariance did not hold when compared to the strong model. Covitality was then added to all comparisons due to finding strong invariance. After the addition, we found both higher order configural and higher order weak invariance for state, grade, gender, and ethnicity.

Figure 1. Path Diagram for SEHS-P Four Subscales with Higher Order Variable

Discussion

The current study found configural, weak, strong, and latent mean invariance across states, gender, and grade on the four subscales of gratitude, zest, optimism, and persistence. After adding covitality as a higher order variable, configural and weak invariance held when compared to strong invariance models.

The current study found configural, weak, and strong invariance across ethnicities on the four subscales of gratitude, zest, optimism, and persistence. After adding covitality as a higher order variable, configural and weak invariance held when compared to strong invariance models.

These results indicate the groups did not significantly differ in performance across the four subscales of gratitude, zest, optimism, and persistence as measured by the SEHS-P, which allowed for the addition of the higher order variable covitality to the overall model. These results add to the literature for SEHS-P’s generalizability across elementary student populations

References

Furlong, M. J., You, S., Renshaw, T. L., O’Malley, M. D., & Rebelez, J. (2013). Preliminary development of the positive experiences at school scale for elementary school children. Child Indicators Research, 6(4), 753–775. https://doi.org/10.1007/s12187-013-9193-7

R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

Rosseel, Y. (2012). lavaan: An r package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02

Acknowledgements

Research described in this presentation was supported, in part, by the Institute of Education Sciences, US Department of Education, through Grant R324A210179 to East Carolina University and the University of South Carolina. The opinions expressed are those of the presenters and do not represent the views of the Institute or the U.S. Department of Education.