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Optimists and Realists: A Latent Class Analysis of Students Graduating from High School during COVID-19 and Impacts on Affect and Well-Being

Author

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  • Ana Zdravkovic

    (Applied Psychology and Human Development, Ontario Institute for Studies in Education, The University of Toronto, Toronto, ON M5S 1V6, Canada)

  • Abby L. Goldstein

    (Applied Psychology and Human Development, Ontario Institute for Studies in Education, The University of Toronto, Toronto, ON M5S 1V6, Canada)

Abstract

The Novel Coronavirus Disease (COVID-19) pandemic has had profound effects on physical and mental health worldwide. Students transitioning out of high school were uniquely impacted at the onset of the pandemic, having missed the opportunity to properly mark the end of their final year in the K-12 school system. The adverse effects of this loss on this population are still unknown. The purpose of the current study was to examine stress, wellbeing, and affect in a sample of 168 students ( N = 168; M age = 17.0, SD = 0.46; 60% female; 40% male) who were completing their final year of high school during the early stages of the pandemic when emergency stay-at-home orders were in place. Participants completed an online survey assessing the impact of COVID-19 on their life satisfaction (pre-COVID19, during COVID-19, and anticipated five years from now), stress, positive affect, and negative affect. Latent class analysis (LCA) was used to create classes of participants based on their responses to the pandemic. A two-subgroup solution provided the best model for the life satisfaction outcome variable. Subgroup 1, optimists , comprised 24% ( N = 40) of the sample and reported high life satisfaction ratings one year prior to COVID-19 and a slight decrease in life satisfaction during COVID-19, and they anticipated an increase in life satisfaction 5 years from now. This group was characterized by low stress, low negative affect, and high positive affect during the pandemic. Subgroup 2, realists , comprised 76% of the population ( N = 128) and experienced similarly high retrospective ratings of pre-COVID life satisfaction but a larger decrease in life satisfaction during the pandemic and a smaller increase in five years. The realist group was characterized by low positive affect, high stress, and high negative affect during the pandemic. The findings suggest that during the pandemic, certain subsamples of adolescents had greater difficulty in managing this transitional period and experienced changes in mood and well-being (i.e., affect, stress) as compared to other adolescents (i.e., optimists ). Future research should investigate the characteristics and coping mechanisms that are instrumental for increasing life satisfaction and positive affect while lowering stress in this population.

Suggested Citation

  • Ana Zdravkovic & Abby L. Goldstein, 2023. "Optimists and Realists: A Latent Class Analysis of Students Graduating from High School during COVID-19 and Impacts on Affect and Well-Being," IJERPH, MDPI, vol. 20(3), pages 1-13, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2120-:d:1045594
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    1. Ed Diener & Ed Sandvik & William Pavot & Dennis Gallagher, 1991. "Response artifacts in the measurement of subjective well-being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 24(1), pages 35-56, February.
    2. Gilles Celeux & Gilda Soromenho, 1996. "An entropy criterion for assessing the number of clusters in a mixture model," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 195-212, September.
    3. Stanley Sclove, 1987. "Application of model-selection criteria to some problems in multivariate analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 333-343, September.
    4. Silvia Guarnieri & Martina Smorti & Franca Tani, 2015. "Attachment Relationships and Life Satisfaction During Emerging Adulthood," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 121(3), pages 833-847, April.
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