Mental Health and Educational Experiences Among Black Youth: A Latent Class Analysis
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Disproportionately lower educational achievement, coupled with higher grade retention, suspensions, expulsions, and lower school bonding make educational success among Black adolescents a major public health concern. Mental health is a key developmental factor related to educational outcomes among adolescents; however, traditional models of mental health focus on absence of dysfunction as a way to conceptualize mental health. The dual-factor model of mental health incorporates indicators of both subjective wellbeing and psychopathology, supporting more recent research that both are needed to comprehensively assess mental health. This study applied the dual-factor model to measure mental health using the National Survey of American Life—Adolescent Supplement (NSAL-A), a representative cross-sectional survey. The sample included 1170 Black adolescents (52% female; mean age 15). Latent class analysis was conducted with positive indicators of subjective wellbeing (emotional, psychological, and social) as well as measures of psychopathology. Four mental health groups were identified, based on having high or low subjective wellbeing and high or low psychopathology. Accordingly, associations between mental health groups and educational outcomes were investigated. Significant associations were observed in school bonding, suspensions, and grade retention, with the positive mental health group (high subjective wellbeing, low psychopathology) experiencing more beneficial outcomes. The results support a strong association between school bonding and better mental health and have implications for a more comprehensive view of mental health in interventions targeting improved educational experiences and mental health among Black adolescents.
KeywordsDual-factor model of mental health Educational experiences School bonding Black adolescents
The NSAL is supported by the National Institute of Mental Health (NIMH; U01-MH57716) with supplemental support from the OBSSR Office of Behavioral and Social Science Research and the National Institute on Drug Abuse at the National Institutes of Health (NIH) and the University of Michigan to Dr. James S. Jackson.
T.R. conceived of the study, conducted the statistical analysis, led interpretation of data, drafted the background and discussion sections of manuscript, formatted the manuscript including references, and edited throughout; M.L. participated in data interpretation, helped to draft the background and discussion sections of the manuscript, and provided additional edits throughout; Y.X. helped conduct the statistical analysis, wrote up results, edited the method section, worked on the discussion section of the manuscript, and provided additional edits throughout; N.F.C. participated in data interpretation, drafted the method section of the manuscript, and provided additional edits throughout; S.J. provided critical feedback on data analysis and interpretation and participated in editing the manuscript. All authors read and approved the final manuscript.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no competing interests.
The NSAL is an IRB approved nationally representative household survey thus all procedures performed were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
This study is a secondary analysis of the 2001–2003 National Survey of American Life (NSAL) adolescent sample, originally collected by researchers at the Program for Research on Black Americans (PRBA) through the University of Michigan’s Institute for Social Research. Informed consent and assent were obtained from the adolescent’s legal guardian and adolescent prior to the study participation.
- Ashley, K. M., Ennis, L. S., & Owusu-Ansah, A. (2012). An exploration of middle school students’ perceptions of personal adolescent wellness and their connectedness to school. International Journal of Social Sciences and Education, 2(1), 74–89.Google Scholar
- Asparouhov, T., & Muthén, B. O. (2013). Auxiliary variables in mixture modeling: 3-step approaches using Mplus. Mplus Web Notes: No. 15. https://www.statmodel.com/download/webnotes/webnote15.pdf.
- Balfanz, R., & Legters, N. (2004). Locating the dropout crisis. Which high schools produce the nation’s dropouts? Where are they located? Who attends them? (Report 70). http://files.eric.ed.gov/fulltext/ED484525.pdf.
- Bond, L., Butler, H., Thomas, L., Carlin, J., Glover, S., Bowes, G., et al. (2007). Social and school connectedness in early secondary school as predictors of late teenage substance use, mental health, and academic outcomes. Journal of Adolescent Health, 40(4), 357.e359–357.e318.CrossRefGoogle Scholar
- Braun, H., Chapman, L., & Vezzu, S. (2010). The Black-White achievement gap revisited (21). http://epaa.asu.edu/ojs/article/view/772/.
- Bray, B. C. (2015). The good, the bad, and the ugly: What we know today about latent class analysis with distal outcomes. Paper presented at the Methodology, Analytics, & Psychometrics (MAP) Academy Emerging Scholar Series, University of Nebraska—Lincoln. Lincoln, NE.Google Scholar
- Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis for the social, behavioral, and health sciences. New York: Wiley.Google Scholar
- Demyttenaere, K., Bruffaerts, R., Posada-Villa, J., Gasquet, I., Kovess, V., Lepine, J., et al. (2004). Prevalence, severity, and unmet need for treatment of mental disorders in the World health organization world mental health surveys. JAMA : the journal of the American Medical Association, 291(21), 2581–2590.PubMedCrossRefGoogle Scholar
- Finch, H., & Bolin, J. (2017). Multilevel Modeling Using Mplus. Boca Raton, FL: CRC Press, Taylor and Francis Group.Google Scholar
- Finlayson, T. L., Williams, D. R., Siefert, K., Jackson, J. S., & Nowjack-Raymer, R. (2010). Oral health disparities and psychosocial correlates of self-rated oral health in the National Survey of American Life. American Journal of Public Health, 100(S1), S246–S255.PubMedPubMedCentralCrossRefGoogle Scholar
- Greene, J. P., & Winters, M. A. (2006). Leaving Boys behind: Public High School Graduation Rates (Civic Report No. 48). http://files.eric.ed.gov/fulltext/ED491633.pdf.
- Harris, K. M. (2013). The Add Health Study: Design and Accomplishments. http://www.cpc.unc.edu/projects/addhealth/documentation/guides/DesignPaperWIIV.pdf.
- Harris, K. M., Halpern, C. T., Whitsel, E., Hussey, J., Tabor, J., Entzel, P., et al. (2009). National Longitudinal Study of Adolescent to Adult Health: Research Design. http://www.cpc.unc.edu/projects/addhealth/design.
- Jackson, J. S., & Neighbors, H. W. (1997). National survey of black Americans, waves 1- 4, 1979-1980, 1987-1988, 1988-1989, 1992. Ann Arbor, MI: Inter-university Consortium for Political and Social Research.Google Scholar
- Jackson, J. S., Torres, M., Caldwell, C. H., Neighbors, H. W., Nesse, R. M., Taylor, R. J., et al. (2004). The National Survey of American Life: A study of racial, ethnic and cultural influences on mental disorders and mental health. International Journal of Methods in Psychiatric Research, 13(4), 196–207.PubMedCrossRefGoogle Scholar
- Jimerson, S. R. (2001). Meta-analysis of grade retention research: Implications for practice in the 21st century. School Psychology Review, 30(3), 420–437.Google Scholar
- Joe, S., Baser, R. S., Neighbors, H. W., Caldwell, C. H., & Jackson, J. S. (2009a). 12-month and lifetime prevalence of suicide attempts among black adolescents in the National Survey of American Life. Journal of the American Academy of Child & Adolescent Psychiatry, 48(3), 271–283.CrossRefGoogle Scholar
- Kessler, R. C. National Comorbidity Survey: Adolescent Supplement (NCS-A). 2001–2004. ICPSR28581-v5. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2013-08-28. doi: 10.3886/ICPSR28581.v5.
- Kessler, R. C., Avenevoli, S., Costello, E. J., Georgiades, K., Green, J. G., Gruber, M. J., et al. (2012). Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National comorbidity survey replication adolescent supplement. Archives of General Psychiatry, 69(4), 372–380.PubMedCrossRefGoogle Scholar
- McLaughlin, K. A., Breslau, J., Green, J. G., Lakoma, M. D., Sampson, N. A., Zaslavsky, A. M., et al. (2011). Childhood socio-economic status and the onset, persistence, and severity of DSM-IV mental disorders in a US national sample. Social Science and Medicine, 73(7), 1088–1096.PubMedPubMedCentralCrossRefGoogle Scholar
- Morse, A. B., Anderson, A., Christenson, S. L., & Lehr, C. A. (2004). Promoting school completion. Principal Leadership, 4(6), 9–13.Google Scholar
- Musu-Gillette, L., Robinson, J., McFarland, J., KewalRamani, A., Zhang, A., & Wilkinson-Flicker, S. (2016). Status and Trends in the Education of Racial and Ethnic Groups 2016 (NCES 2016-007). Washington, DC: U.S. Department of Education, National Center for Education Statistics. http://nces.ed.gov/pubsearch.Google Scholar
- Muthén, L. K, & Muthén, B. O. (1998-2015). Mplus User’s Guide. Seventh Edition, Los Angeles, CA: Muthén & Muthén. .Google Scholar
- Orfield, G., & Lee, C. (2005). Why Segregation Matters: Poverty and Educational Inequality. UCLA: The Civil Rights Project/Proyecto Derechos Civiles. http://www.escholarship.org/uc/item/4xr8z4wb.
- Orfield, G., Losen, D., Wald, J., & Swanson, C. B. (2004). Losing Our Future: How Minority Youth are Being Left Behind by the Graduation Rate Crisis. UCLA: The Civil Rights Project / Proyecto Derechos Civiles. http://escholarship.org/uc/item/4x44w1qh.
- Poulin, C., Hand, D., & Boudreau, B. (2005). Validity of a 12-item version of the CES-D [Centre for epidemiological studies depression scale] used in the National longitudinal study of children and youth. Chronic Diseases and Injuries in Canada, 26(2-3), 65–72.Google Scholar
- Richman, J. M, Bowen, G. L, & Woolley, M. E. (2004). School failure: An eco-interactional developmental perspective. In M. W. Fraser (ed.) Risk and resilience in childhood. 2 ed. (pp. 133–160). Washington, DC: NASW Press.Google Scholar
- Rose, T., Finigan-Carr, N., & Joe, S. (2017). Lifetime mental disorders and education experiences among Black adolescents. In N. Finigan-Carr (Ed.), Linking health and education for African-American students’ success. New York, NY: Routledge.Google Scholar
- Seaton, E. K., Caldwell, C. H., Sellers, R. M., & Jackson, J. S. (2010). An intersectional approach for understanding perceived discrimination and psychological well-being among African American and Caribbean Black youth. Developmental Psychology, 46(5), 1372–1379.PubMedPubMedCentralCrossRefGoogle Scholar
- Serbin, L. A., Temcheff, C. E., Cooperman, J. M., Stack, D. M., Ledingham, J., & Schwartzman, A. E. (2011). Predicting family poverty and other disadvantaged conditions for child rearing from childhood aggression and social withdrawal: A 30-year longitudinal study. International Journal of Behavioral Development, 35(2), 97–106.CrossRefGoogle Scholar
- Smith, C. (2003). Theorizing religious effects among American adolescents. Journal for the Scientific Study, 42(1), 17–30.Google Scholar
- StataCorp. (2015). Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.Google Scholar
- Steele, C. M. (1992). Race and the schooling of Black Americans. The Atlantic Monthly, 269, 67–78.Google Scholar
- Stewart-Brown, S. (2016). Population level: Wellbeing in the general population. M. Slade, L. Oades, A. Jarden (Eds.), Wellbeing, Recovery, and Mental Health. (Chapter 18).Google Scholar
- Suldo, S. M., Hearon, B. V., Bander, B., McCullough, M., Garofano, J., Roth, R. A., et al. (2015). Increasing elementary school students’ subjective well-being through a classwide positive psychology intervention: Results of a pilot study. Contemporary School Psychology, 19(4), 300–311.CrossRefGoogle Scholar
- Suldo, S. M., & Shaffer, E. J. (2008). Looking beyond psychopathology: The dual-factor model of mental health in youth. School Psychology Review, 37(1), 52–68.Google Scholar
- UNICEF (2012). The state of the world’s children 2012: Children in an urban world. https://www.unicef.org/sowc2012/pdfs/SOWC%202012-Main%20Report_EN_13Mar2012.pdf.
- U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP). (2016) Mathematics and Reading Assessments. https://nces.ed.gov/nationsreportcard/subjectareas.aspx.
- World Health Organization (2016). Mental health: Strengthening our response (Fact Sheet). http://www.who.int/mediacentre/factsheets/fs220/en/.
- Zimmerman, M. A., & Arunkumar, R. (1994). Resiliency research: Implications for schools and policy. Social Policy Report, 8(4), 1–18.Google Scholar