Abstract:
This paper presents some of the data from a doctoral project about high school students’ well-being during the COVID-19 pandemic. Extant literature shows that the pandemic had a negative impact on both student learning (Fahle et al., 2023) and well-being (Ravens-Sieberer et al., 2022), and some research shows that the pandemic may have also exacerbated existing inequities in academic achievement for children and youth.
This paper presents a secondary analysis of a survey (n = 18,529) board-conducted survey from December 2020 where students were asked about their learning conditions at home (Which of the following are making it difficult to complete schoolwork at home?) and their emotional well-being (how often do you feel happy, hopeful, bored, nervous, stressed, lonely). I coded all outcomes as binary (1 = always/often; 0 = sometimes/rarely/never) and used logistic regression to analyze whether there were differences in well-being across school socio-economic status (low-SES, mid-SES, high-SES). Surprisingly, students from high-SES schools reported worse well-being than students from low-SES schools. At the same time, students from low-SES schools were more likely to face greater challenges (e.g., less likely to have a quiet workspace, reliable internet, their own device). These findings are understood through the lens of reference group effects. Reference group effects suggest that in an individuals’ evaluation of their emotional well-being, their comparison of their own well-being against their perceptions of their peers’ well-being is more important than the objective truth (Heine et al., 2002). The contrast between objective and subjective well-being findings within the same survey point to the importance of clearly defining and validating well-being metrics in research and policy evaluation.
Fahle, E., Kane, T. J., Reardon, S. F., Staiger, D. O., & Stuart, E. A. (2023). School district and community factors associated with learning loss during the COVID-19 pandemic (Education Recovery Scorecard). Center for Education Policy Research, Harvard University and The Educational Opportunity Project at Stanford University. https://cepr.harvard.edu/sites/hwpi.harvard.edu/files/cepr/files/explaining_covid_losses_5.23.pdf?m=1683748707
Heine, S. J., Lehman, D. R., Peng, K., & Greenholtz, J. (2002). What’s wrong with cross-cultural comparisons of subjective Likert scales?: The reference-group effect. Journal of Personality and Social Psychology, 82(6), 903–918. https://doi.org/10.1037/0022-3514.82.6.903
Ravens-Sieberer, U., Kaman, A., Erhart, M., Devine, J., Schlack, R., & Otto, C. (2022). Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany. European Child & Adolescent Psychiatry, 31(6), 879–889. https://doi.org/10.1007/s00787-021-01726-5
This paper presents a secondary analysis of a survey (n = 18,529) board-conducted survey from December 2020 where students were asked about their learning conditions at home (Which of the following are making it difficult to complete schoolwork at home?) and their emotional well-being (how often do you feel happy, hopeful, bored, nervous, stressed, lonely). I coded all outcomes as binary (1 = always/often; 0 = sometimes/rarely/never) and used logistic regression to analyze whether there were differences in well-being across school socio-economic status (low-SES, mid-SES, high-SES). Surprisingly, students from high-SES schools reported worse well-being than students from low-SES schools. At the same time, students from low-SES schools were more likely to face greater challenges (e.g., less likely to have a quiet workspace, reliable internet, their own device). These findings are understood through the lens of reference group effects. Reference group effects suggest that in an individuals’ evaluation of their emotional well-being, their comparison of their own well-being against their perceptions of their peers’ well-being is more important than the objective truth (Heine et al., 2002). The contrast between objective and subjective well-being findings within the same survey point to the importance of clearly defining and validating well-being metrics in research and policy evaluation.
Fahle, E., Kane, T. J., Reardon, S. F., Staiger, D. O., & Stuart, E. A. (2023). School district and community factors associated with learning loss during the COVID-19 pandemic (Education Recovery Scorecard). Center for Education Policy Research, Harvard University and The Educational Opportunity Project at Stanford University. https://cepr.harvard.edu/sites/hwpi.harvard.edu/files/cepr/files/explaining_covid_losses_5.23.pdf?m=1683748707
Heine, S. J., Lehman, D. R., Peng, K., & Greenholtz, J. (2002). What’s wrong with cross-cultural comparisons of subjective Likert scales?: The reference-group effect. Journal of Personality and Social Psychology, 82(6), 903–918. https://doi.org/10.1037/0022-3514.82.6.903
Ravens-Sieberer, U., Kaman, A., Erhart, M., Devine, J., Schlack, R., & Otto, C. (2022). Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany. European Child & Adolescent Psychiatry, 31(6), 879–889. https://doi.org/10.1007/s00787-021-01726-5