Abstract
The long-term outcomes for adolescents who struggle in first-year university remain unexplored. This 7-year longitudinal study aimed to identify distinct groups of adolescents based on their characteristics/behaviors in first-year university, and then assess whether these groups differ in psychosocial adjustment trajectories (i.e., mental health, positive relationships) throughout the emerging adult period, as well as in graduation rates, employment characteristics, and reflections on time spent at university. Participants (N = 1017; 71% female; Year 1 Mage = 19 years) enrolled in a Canadian university completed a survey annually for 7 years. Four groups in Year 1 were identified: Good Students who exhibited no difficulties; Sensation-Seeking who prioritized social engagement and substance use over academic engagement but reported no psychological adjustment difficulties; Struggling Students who had the most difficulties; and Club Involved who exhibited high club involvement. The Struggling Students Group continued to have more psychosocial adjustment difficulties than the other groups during and after university, were more likely to drop out of university, and to later have less job satisfaction. This group requires the most support. Consideration also should be given to the Sensation-Seeking Group, as they reported a lack of academic motivation (and regret about that later) and also were more likely to drop out of university. At the same time, they may be more difficult to target given that they did not report psychosocial difficulties. Overall, the findings highlight the need for early support and discourage a ‘one-size fits all’ method for promoting psychosocial adjustment.
Similar content being viewed by others
References
Ando, M. (2011). An intervention program focused on self-understanding and interpersonal interactions to prevent psychosocial distress among Japanese university students. Journal of Adolescence, 34(5), 929–940. https://doi.org/10.1016/j.adolescence.2010.12.003.
Armsden, G. C., & Greenberg, M. T. (1987). The inventory of parent and peer attachment: Individual differences and their relationship to psychological well-being in adolescence. Journal of Youth and Adolescence, 5, 427–453. https://doi.org/10.1007/BF02202939.
Arnett, J. J. (2000). Emerging adulthood: a theory of development from the late teens through the twenties. American Psychologist, 55, 469–480. https://doi.org/10.1037/0003-066X.55.5.469.
Bachman, J. G., Schulenberg, J. E., Freedman-Doan, P., O'Malley, P. M., Johnston, L. D., & Messersmith, E. E. (2008). The education-drug use connection: How successes and failures in school relate to adolescent smoking, drinking, drug use, and delinquency. New York, NY: Psychology Press.
Baker, R. W., & Siryk, B. (1986). Student adaptation to college questionnaire (SACQ). Los Angeles, CA: Western Psychological Services.
Baltes, P. B., Lindenberger, U., & Staudinger, U. M. (1998). Life-span theory in developmental psychology. In W. Damon (Series Ed.) & R.M. Lerner (Vol. Ed.), Handbook of child psychology, Vol 1. Theoretical models of human development (5th edn., pp 1029–1144). New York: Wiley.
Bastien, C. H., Vallières, A., & Morin, C. M. (2001). Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Medicine, 2(4), 297–307. https://doi.org/10.1016/s1389-9457(00)00065-4.
Boehm, M. A., Lei, Q. M., Lloyd, R. M., & Prichard, J. R. (2016). Depression, anxiety, and tobacco use: overlapping impediments to sleep in a national sample of college students. Journal of American College Health, 64(7), 565–574. https://doi.org/10.1080/07448481.2016.1205073.
Bowling, N. A., Eschleman, K. J., & Wang, Q. (2010). A meta-analytic examination of the relationship between job satisfaction and subjective well-being. Journal of Occupational and Organizational Psychology, 83, 915–934. https://doi.org/10.1348/096317909X478557.
Buote, V. M., Pancer, S. M., Pratt, M. W., Adams, G., Birnie-Lefcovitch, S., Polivy, J., & Wintre, M. G. (2007). The importance of friends: friendship and adjustment among 1st-year university students. Journal of Adolescent Research, 22(6), 665–689. https://doi.org/10.1177/0743558407306344.
Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology, 67, 319–333. https://doi.org/10.1037/0022-3514.67.2.319.
Cawthon, S. W., & Cole, E. V. (2010). Postsecondary students who have a learning disability: student perspectives on accommodations access and obstacles. Journal of Postsecondary Education and Disability, 23(2), 112–128.
Chronis-Tuscano, A., Degnan, K. A., Pine, D. S., Perez-Edgar, K., Henderson, H. A., Diaz, Y., & Fox, N. A. (2009). Stable early maternal report of behavioral inhibition predicts lifetime social anxiety disorder in adolescence. Journal of the American Academy of Child & Adolescent Psychiatry, 48(9), 928–935. https://doi.org/10.1097/CHI.0b013e3181ae09dfS0890-8567(09)60148-9.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum..
Dahmus, S., Bernardin, H. J., & Bernardin, K. (1992). Student adaptation to college questionnaire. Measurement and Evaluation in Counseling and Development, 25, 139–142.
Deci, E. L., Ryan, R. M., Gagné, M., Leone, D. R., Usunov, J., & Kornazheva, B. P. (2001). Need satisfaction, motivation, and well-being in the work organizations of a former eastern bloc country: a cross-cultural study of self-determination. Personality and Social Psychology Bulletin, 27(8), 930–942. https://doi.org/10.1177/0146167201278002.
Erikson, E. H. (1968). Identity: Youth and crisis (No. 7). New York, NY: WW Norton & company.
Galambos, N. L., & Krahn, H. J. (2008). Depression and anger trajectories during the transition to adulthood. Journal of Marriage and Family, 70, 15–27. https://doi.org/10.1111/j.1741-3737.2007.00458.x.
Galambos, N. L., Lascano, D. I. V., Howard, A. L., & Maggs, J. L. (2013). Who sleeps best? Longitudinal patterns and covariates of change in sleep quantity, quality, and timing across four university years. Behavioral Sleep Medicine, 11, 8–22. https://doi.org/10.1080/15402002.2011.596234.
Guilmette, M., Mulvihill, K., Villemaire-Krajden, R., & Barker, E. T. (2019). Past and present participation in extracurricular activities is associated with adaptive self-regulation of goals, academic success, and emotional wellbeing among university students. Learning and Individual Differences, 73, 8–15. https://doi.org/10.1016/j.lindif.2019.04.006.
Hamza, C., & Willoughby, T. (2013). Longitudinal trajectories of nonsuicidal self-injury: a person centered analysis of risk factors among university students. Journal of Youth and Adolescence, 43, 671–685. https://doi.org/10.1007/s10964-013-9991-8.
Hu, L. T., & Bentler, P. M. (1995). Evaluating model fit. In R.H. Hoyle (Ed.), Structural equation modeling: concepts, issues, and applications (pp. 76–99). Thousand Oaks, CA: Sage Publications, Inc.
Johnston, L. D., O’Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2007). Monitoring the future national survey results on drug use, 1975-2006. Volume II: College students and adults ages 19-45 (NIH Publication No. 07-6206). National Institute on Drug Abuse. https://files.eric.ed.gov/fulltext/ED514367.pdf.
Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–317. https://doi.org/10.1111/j.1751-9004.2007.00054.x.
Lanza, S. T., Rhoades, B. L., Nix, R. L., & Greenberg, M. T., the Conduct Problems Prevention Research Group. (2010). Modeling the interplay of multilevel risk factors for future academic and behavior problems: a person-centred approach. Development and Psychopathology, 22, 313–335. https://doi.org/10.1017/S0954579410000088.
Lascano, D. I. V., Galambos, N. L., & Hoglund, W. L. (2013). Canadian youths’ trajectories of psychosocial competencies through university: academic and romantic affairs matter. International Journal of Behavioral Development, 38(1), 11–22. https://doi.org/10.1177/0165025413491372.
Mancini, M., & Roumeliotis, I. (2019, November 21). “It’s literally life or death’: Students say University of Toronto dragging feet on mental health services. CBC News. https://www.cbc.ca/news/canada/toronto/student-suicides-mental-health-support-1.5363242
Martin, A. J. (2010). Should students have a gap year? Motivation and performance factors relevant to time out after completing school. Journal of Educational Psychology, 102(3), 561–576. https://doi.org/10.1037/a0019321.
Martin, A. J., Wilson, R., Liem, G. A. D., & Ginns, P. (2013). Academic momentum at University/College: exploring the roles of prior learning, life experience, and ongoing performance in academic achievement across time. The Journal of Higher Education, 84(5), 640–674. https://doi.org/10.1080/00221546.2013.11777304.
Miller, K., Danner, F., & Staten, R. (2008). Relationship of work hours with selected health behaviors and academic progress among a college student cohort. Journal of American College Health, 56(6), 675–679. https://doi.org/10.3200/JACH.56.6.675-679.
Morin, C. M. (1993). Insomnia: Psychological assessment and management. New York, NY: Guilford Press.
Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus User’s Guide. 8th edn. Los Angeles, CA: Muthén & Muthén.
Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535–569. https://doi.org/10.1080/10705510701575396.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students. Vol 2. Indianapolis, IN: Jossey-Bass Publishers.
Perkins, H. W. (2002). Surveying the damage: a review of research on consequences of alcohol misuse in college populations. Journal of Studies in Alcohol and Drugs, 14, 91–100. https://doi.org/10.15288/jsas.2002.s14.91.
Preacher, K. J., Wichman, A. L., MacCallum, R. C., & Briggs, N. E. (2008). Latent growth curve modeling (No. 157). Thousand Oaks, CA: Sage Publications, Inc.
R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/.
Radloff, L. S. (1977). The CES-D Scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401. https://doi.org/10.1177/014662167700100306.
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288. https://doi.org/10.1037/0033-2909.130.2.261.
Rose Birch, E., & Miller, P. W. (2007). The characteristics of ‘Gap-Year’ students and their tertiary academic outcomes. The Economic Record, 83(262), 329–344. https://doi.org/10.1111/j.1475-4932.2007.00418.x.
Schafer, J. L., & Graham, J. W. (2002). Missing data: our view of the state of the art. Psychological Methods, 7, 147–177. https://doi.org/10.1037//1082-989X.7.2.147.
Schulenberg, J. E., Sameroff, A. J., & Cicchetti, D. (2004). The transition to adulthood as a critical juncture in the course of psychopathology and mental health. Development and Psychopathology, 16, 799–806. https://doi.org/10.1017/S0954579404040015.
Schulenberg, J. E., & Zarrett, N. R. (2006). Mental health during emerging adulthood: continuity and discontinuity in courses, causes, and functions. In J. J. Arnett & J. L. Tanner (Eds), Emerging adults in America: Coming of age in the 21st century (pp. 135–172). Washington, DC: American Psychological Association.
Sivertsen, B., Hysing, M., Knapstad, M., Harvey, A. G., Reneflot, A., Lønning, K. J., & O’Connor, R. C. (2019). Suicide attempts and non-suicidal self-harm among university students: prevalence study. BJPsych Open, 5(2). https://doi.org/10.1192/bjo.2019.4
Spera, C., Ghertner, R., Nerino, A., & DiTommasso, A. (2013). Volunteering as a pathway to employment: does volunteering increase odds of finding a job for the out of work? Corporation for National and Community Service, Office of Research and Evaluation. http://cte.sfasu.edu/wp-content/uploads/2014/10/Employment-Research-Report.pdf
Stephens, N. M., Hamedani, M. G., & Destin, M. (2014). Closing the social-class achievement gap: a difference-education intervention improves first-generation students’ academic performance and all students’ college transition. Psychological Science, 25, 943–953. https://doi.org/10.1177/0956797613518349.
Van Overwalle, F., & De Metsenaere, M. (1990). The effects of attribution‐based intervention and study strategy training on academic achievement in college freshmen. The British Journal of Educational Psychology, 60, 299–311. https://doi.org/10.1111/j.2044-8279.1990.tb00946.x.
Vaughan, E. L., Corbin, W. R., & Fromme, K. (2009). Academic and social motives and drinking behavior. Psychology of Addictive Behaviors, 23(4), 564–576. https://doi.org/10.1037/a0017331.
Weaver, B. E., & Nilson, L. B. (2005). Laptops in class: What are they good for? What can you do with them? New directions for teaching and learning, 2005(101), 3–13. https://doi.org/10.1002/tl.181.
Willoughby, T. (2008). A short-term longitudinal study of Internet and computer game use by adolescent boys and girls: prevalence, frequency of use, and psychosocial predictors. Developmental Psychology, 44(1), 195–204. https://doi.org/10.1037/0012-1649.44.1.195.
Wood, E., Zivcakova, L., Gentile, P., Archer, K., De Pasquale, D., & Nosko, A. (2012). Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Computers & Education, 58(1), 365–374. https://doi.org/10.1016/j.compedu.2011.08.029.
Author information
Authors and Affiliations
Contributions
T.W. conceived of the study, designed and performed the statistical analyses, and participated in the interpretation and drafting of the paper; T.H., V.W.D., H.S. and J.B. participated in the interpretation and drafting of the paper. All authors read and approved the final paper.
Funding
This study was supported by grants from the Social Sciences and Humanities Research Council of Canada to Teena Willoughby.
Data Sharing and Declaration
This manuscript’s data will not be deposited.
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Ethical Approval
This study has ethics approval from Brock University (REB 09-118 from 2009 to 2015, 16-324 from 2016 to present).
Informed Consent
All participants provided written consent.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Willoughby, T., Heffer, T., Dykstra, V.W. et al. A Latent Class Analysis of Adolescents in First-Year University: Associations with Psychosocial Adjustment Throughout the Emerging Adult Period and Post-University Outcomes. J Youth Adolescence 49, 2459–2475 (2020). https://doi.org/10.1007/s10964-020-01318-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10964-020-01318-7