IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i3p2120-d1045594.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/3/2120/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/3/2120/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlos Hervás-Gómez & María Dolores Díaz-Noguera & Ángela Martín-Gutiérrez & Gloria Luisa Morales-Pérez, 2023. "Validation of the Attitude Scale on Prospective Teachers’ Perceptions of the Consequences on Their Psychological State: Well-Being and Cognition," IJERPH, MDPI, vol. 20(8), pages 1-14, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mengya Xia & Caitlin M. Hudac, 2023. "Social Connection Constellations and Individual Well-Being Typologies: Using the Loglinear Modeling Approach with Latent Variables," Journal of Happiness Studies, Springer, vol. 24(6), pages 1991-2012, August.
    2. Laura Dal Corso & Alessandro De Carlo & Francesca Carluccio & Daiana Colledani & Alessandra Falco, 2020. "Employee burnout and positive dimensions of well-being: A latent workplace spirituality profile analysis," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-17, November.
    3. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
    4. Nicolas Depraetere & Martina Vandebroek, 2014. "Order selection in finite mixtures of linear regressions," Statistical Papers, Springer, vol. 55(3), pages 871-911, August.
    5. Michael T. Baglivio & Kevin T. Wolff, 2021. "Adverse Childhood Experiences Distinguish Violent Juvenile Sexual Offenders’ Victim Typologies," IJERPH, MDPI, vol. 18(21), pages 1-14, October.
    6. Marianna Virtanen & Jussi Vahtera & Jenny Head & Rosemary Dray-Spira & Annaleena Okuloff & Adam G Tabak & Marcel Goldberg & Jenni Ervasti & Markus Jokela & Archana Singh-Manoux & Jaana Pentti & Marie , 2015. "Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    7. Danks, Nicholas P. & Sharma, Pratyush N. & Sarstedt, Marko, 2020. "Model selection uncertainty and multimodel inference in partial least squares structural equation modeling (PLS-SEM)," Journal of Business Research, Elsevier, vol. 113(C), pages 13-24.
    8. Morgan, Grant B. & Hodge, Kari J. & Baggett, Aaron R., 2016. "Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 146-161.
    9. Xiaotong Wen & Yixiang Lin & Yuchen Liu & Katie Starcevich & Fang Yuan & Xiuzhu Wang & Xiaoxu Xie & Zhaokang Yuan, 2020. "A Latent Profile Analysis of Anxiety among Junior High School Students in Less Developed Rural Regions of China," IJERPH, MDPI, vol. 17(11), pages 1-14, June.
    10. Scott, Carol F. & Bay-Cheng, Laina Y. & Nochajski, Thomas H. & Lorraine Collins, R., 2024. "Emerging adults’ social media engagement & alcohol misuse: A multidimensional, person-centered analysis of risk," Children and Youth Services Review, Elsevier, vol. 159(C).
    11. Julian Aichholzer & Sylvia Kritzinger & Carolina Plescia, 2021. "National identity profiles and support for the European Union," European Union Politics, , vol. 22(2), pages 293-315, June.
    12. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.
    13. Palma, Marco A. & Ness, Meghan L. & Anderson, David P., 2015. "Buying More than Taste? A Latent Class Analysis of Health and Prestige Determinants of Healthy Food," 2015 Conference (59th), February 10-13, 2015, Rotorua, New Zealand 202566, Australian Agricultural and Resource Economics Society.
    14. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    15. van Hoorn, André, 2018. "Is the happiness approach to measuring preferences valid?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 73(C), pages 53-65.
    16. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    17. Nicoleta Serban & Huijing Jiang, 2012. "Multilevel Functional Clustering Analysis," Biometrics, The International Biometric Society, vol. 68(3), pages 805-814, September.
    18. Jacky C. K. Ng & Joanne Y. H. Chong & Hilary K. Y. Ng, 2023. "The way I see the world, the way I envy others: a person-centered investigation of worldviews and the malicious and benign forms of envy among adolescents and adults," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    19. Gillian C. Williams & Karen A. Patte & Mark A. Ferro & Scott T. Leatherdale, 2021. "Associations between Longitudinal Patterns of Substance Use and Anxiety and Depression Symptoms among a Sample of Canadian Secondary School Students," IJERPH, MDPI, vol. 18(19), pages 1-14, October.
    20. Violeta Misheva, 2016. "What Determines Emotional Well-Being? The Role of Adverse Experiences: Evidence Using Twin Data," Journal of Happiness Studies, Springer, vol. 17(5), pages 1921-1937, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2120-:d:1045594. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.