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Patterns of Time Use Among Low-Income Urban Minority Adolescents and Associations with Academic Outcomes and Problem Behaviors

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Abstract

Time budgets represent key opportunities for developmental support and contribute to an understanding of achievement gaps and adjustment across populations of youth. This study assessed the connection between out-of-school time use patterns and academic performance outcomes, academic motivations and goals, and problem behaviors for 504 low-income urban African American and Latino adolescents (54 % female; M = 16.6 years). Time use patterns were measured across eight activity types using cluster analysis. Four groups of adolescents were identified, based on their different profiles of time use: (1) Academic: those with most time in academic activities; (2) Social: those with most time in social activities; (3) Maintenance/work: those with most time in maintenance and work activities; and (4) TV/computer: those with most time in TV or computer activities. Time use patterns were meaningfully associated with variation in outcomes in this population. Adolescents in the Academic cluster had the highest levels of adjustment across all domains; adolescents in the Social cluster had the lowest academic performance and highest problem behaviors; and adolescents in the TV/computer cluster had the lowest levels of intrinsic motivation. Females were more likely to be in the Academic cluster, and less likely to be in the other three clusters compared to males. No differences by race or gender were found in assessing the relationship between time use and outcomes. The study’s results indicate that time use patterns are meaningfully associated with within-group variation in adjustment for low-income minority adolescents, and that shared contexts may shape time use more than individual differences in race/ethnicity for this population.

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References

  • Barnes, G. M., Hoffman, J. H., Welte, J. W., Farrell, M. P., & Dintcheff, B. A. (2007). Adolescents’ time use: Effects on substance use, delinquency and sexual activity. Journal of Youth and Adolescence, 36, 697.

    Article  Google Scholar 

  • Barnett, L. A. (2007). “Winners” and” Losers”: The effects of being allowed or denied entry into competitive extracurricular activities. Journal of Leisure Research, 39, 316.

    Google Scholar 

  • Bartko, W. T., & Eccles, J. S. (2003). Adolescent participation in structured and unstructured activities: A person-oriented analysis. Journal of Youth and Adolescence, 32, 233–241.

    Article  Google Scholar 

  • Bettinger, E. P. (2012). Paying to learn: The effect of financial incentives on elementary school test scores. Review of Economics and Statistics, 94, 686–698.

    Article  Google Scholar 

  • Blashfield, R. K. (1976). Mixture model tests of cluster analysis: Accuracy of four agglomerative hierarchical methods. Psychological Bulletin, 83, 377–388.

    Article  Google Scholar 

  • Bohnert, A. M., & Garber, J. (2007). Prospective relations between organized activity participation and psychopathology during adolescence. Journal of Abnormal Child Psychology, 35, 1021–1033.

    Article  PubMed  Google Scholar 

  • Bohnert, A. M., Richards, M., Kohl, K., & Randall, E. (2009). Relationships between discretionary time activities, emotional experiences, delinquency and depressive symptoms among urban African American adolescents. Journal of Youth and Adolescence, 38, 587–601.

    Article  PubMed  Google Scholar 

  • Bohnert, A. M., Richards, M., Kolomodin, K. E., & Lakin, B. L. (2008). Young urban African American adolescents’ experiences of discretionary time activities. Journal of Research on Adolescence, 18, 517.

    Article  Google Scholar 

  • Booth, M. L., Okely, A. D., Chey, T., & Bauman, A. (2002). The reliability and validity of the adolescent physical activity recall questionnaire. Medicine and Science in Sports and Exercise, 34, 1986–1995.

    Article  PubMed  Google Scholar 

  • Bouffard, S. M., Wimer, C., Caronongan, P., Little, P. M. D., Dearing, E., & Simpkins, S. D. (2006). Demographic differences in patterns of youth out-of-school time activity participation. Journal of Youth Development, 1, 24–39.

    Google Scholar 

  • Bronfenbrenner, U., & Morris, P.A. (2008). The bioecological model of human development. In R.M. Lerner (Ed.), Handbook of child psychology. Theoretical models of human development (6th ed., Vol. 1). Editors-in-chief: W. Damon & R. M. Lerner. Hoboken, NJ: Wiley.

  • Bryant, A. L., & Zimmerman, M. A. (2002). Examining the effects of academic beliefs and behaviors on changes in substance use among urban adolescents. Journal of Educational Psychology, 94, 621–637.

    Article  Google Scholar 

  • Center for Behavioral Health Statistics and Quality. (2012). Results from the 2011 national survey on drug use and health: Summary of national findings (NSDUH Series H-44, HHS Publication No. SMA 12-4713). Rockville, MD: Substance Abuse and Mental Health Services Administration.

  • Cooper, H., Valentine, J. C., Nye, B., & Lindsay, J. J. (1999). Relationships between five after-school activities and academic achievement. Journal of Educational Psychology, 91, 369–378.

    Article  Google Scholar 

  • Csikszentmihalyi, M., & Larson, R. (1984). Being adolescent: Conflict and growth in the teenage years. New York: Basic.

    Google Scholar 

  • Darling, N. (2005). Participation in extracurricular activities and adolescent adjustment: Cross-sectional and longitudinal findings. Journal of Youth and Adolescence, 34, 493–505.

    Article  Google Scholar 

  • Dishion, T. J., McCord, J., & Poulin, F. (1999). When interventions harm: Peer groups and problem behavior. American Psychologist, 54, 755–764.

    Article  PubMed  Google Scholar 

  • Dotterer, A. M., McHale, S. M., & Crouter, A. C. (2007). Implications of out-of-school activities for school engagement in African American adolescents. Journal of Youth and Adolescence, 36, 391.

    Article  Google Scholar 

  • Downey, D. B., & Vogt Yuan, A. S. (2005). Sex differences in school performance during high school: puzzling patterns and possible explanations. Sociological Quarterly, 46, 299–321.

    Article  Google Scholar 

  • Duckworth, A. L., & Seligman, M. P. (2006). Self-discipline gives girls the edge: Gender in self-discipline, grades, and achievement test scores. Journal of Educational Psychology, 98, 198.

    Article  Google Scholar 

  • Dumais, S. A. (2008). Adolescents’ time use and academic achievement: A test of the reproduction and mobility models. Social Science Quarterly, 89, 867–886.

    Article  Google Scholar 

  • Dumais, S. A. (2009). Cohort and gender differences in extracurricular participation: The relationship between activities, math achievement, and college expectations. Sociological Spectrum, 29, 72–100.

    Article  Google Scholar 

  • Ensminger, M. E., Lamkin, R. P., & Jacobson, N. (1996). School leaving: A longitudinal perspective including neighborhood effects. Child Development, 67, 2400–2416.

    Article  PubMed  Google Scholar 

  • Entwisle, D. R., Alexander, K. L., & Olson, L. S. (1994). The gender gap in math: Its possible origins in neighborhood effects. American Sociological Review, 59, 822–838.

    Article  Google Scholar 

  • Evans, G. W. (2004). The environment of childhood poverty. American Psychologist, 59, 77–92.

    Article  PubMed  Google Scholar 

  • Farb, A. F., & Matjasko, J. L. (2012). Recent advances in research on school-based extracurricular activities and adolescent development. Developmental Review, 32, 1–48.

    Article  Google Scholar 

  • Feldman, A. F., & Matjasko, J. L. (2005). The role of school-based extracurricular activities in adolescent development: A comprehensive review and future directions. Review of Educational Research, 75, 159.

    Article  Google Scholar 

  • Feldman, A. F., & Matjasko, J. L. (2007). Profiles and portfolios of adolescent school-based extracurricular activity participation. Journal of Adolescence, 30, 313–332.

    Article  PubMed  Google Scholar 

  • Ferrar, K., Chang, C., Li, M., & Olds, T. S. (2013). Adolescent time use clusters: A systematic review. Journal of Adolescent Health, 52, 259–270.

    Article  PubMed  Google Scholar 

  • Finn, J. D., & Rock, D. A. (1997). Academic success among students at risk for school failure. Journal of Applied Psychology, 8, 221–234.

    Article  Google Scholar 

  • Fredricks, J. A., & Eccles, J. S. (2006). Is extracurricular participation associated with beneficial outcomes? Concurrent and longitudinal relations. Developmental Psychology, 42, 698–713.

    Article  PubMed  Google Scholar 

  • Fredricks, J. A., & Eccles, J. S. (2008). Participation in extracurricular activities in the middle school years: Are there developmental benefits for African American and European American youth? Journal of Youth and Adolescence, 37, 1029–1043.

    Article  Google Scholar 

  • Fryer, R. G. (2011). Financial incentives and student achievement: Evidence from randomized trials. Quarterly Journal of Economics, 126, 1755–1798.

    Article  Google Scholar 

  • Fuligni, A. J., & Pedersen, S. (2002). Family obligation and the transition to young adulthood. Developmental Psychology, 38, 856–868.

    Article  PubMed  Google Scholar 

  • Fuligni, A. J., Tseng, V., & Lam, M. (1999). Attitudes toward family obligations among American adolescents with Asian, Latin American, and European backgrounds. Child Development, 70, 1030.

    Article  Google Scholar 

  • Furrer, C., & Skinner, E. (2003). Sense of relatedness as a factor in children’s academic engagement and performance. Journal of Educational Psychology, 95, 148–162.

    Article  Google Scholar 

  • García Coll, C. G., Crnic, K., Lamberty, G., Waskik, B. H., Jenkins, R., Garcia, H. V., et al. (1996). An integrative model for the study of developmental competencies in minority children. Child Development, 67, 1891–1914.

    Article  PubMed  Google Scholar 

  • Gaubert, J., Knox, V., Alderson, D. P., Dalton, C., Fletcher, K., & McCormick, M. (2010). Early lessons from the implementation of a relationship and marriage skills program. New York, NY: MDRC.

    Google Scholar 

  • Hill, N. E., & Craft, S. A. (2003). Parent-school involvement and school performance: Mediated pathways among socioeconomically comparable African American and Euro-American families. Journal of Educational Psychology, 95, 74–83.

    Article  Google Scholar 

  • Hirschi, T. (1969). Causes of delinquency. Berkeley, CA: University of California Press.

    Google Scholar 

  • Hoffman, J. (2006). Extracurricular activities, athletic participation, and adolescent alcohol use: Gender differentiated and school-contextual effects. Journal of Health and Social Behavior, 47, 275–290.

    Article  Google Scholar 

  • Husain, M., & Millimet, D. L. (2009). The mythical ‘boy crisis’? Economics of Education Review, 28, 38–48.

    Article  Google Scholar 

  • Hutcheson, G. D., & Moutinho, L. (2008). Statistical modeling for management. Thousand Oaks: Sage.

    Google Scholar 

  • Jago, R., Anderson, C. B., Baranowski, T., & Watson, K. (2005). Adolescent patterns of physical activity: Differences by gender, day, and time of day. American Journal of Preventive Medicine, 28, 447–452.

    Article  PubMed  Google Scholar 

  • Johnson, M. K., Crosnoe, R., & Elder, G. (2001). Students’ attachment and academic engagement: The role of race and ethnicity. Sociology of Education, 74, 318–340.

    Article  Google Scholar 

  • Juster, F. T. (1986). Response errors in the measurement of time use. Journal of the American Statistical Association, 81, 390–402.

    Article  Google Scholar 

  • Lareau, A. (2003). Unequal childhoods: Class, race, and family life. Berkley, CA: University of California.

    Google Scholar 

  • Larson, R. W. (2000). Toward a psychology of positive youth development. American Psychologist, 55, 170.

    Article  PubMed  Google Scholar 

  • Larson, R. W., Richards, M. H., Sims, B., & Dworkin, J. (2001). How urban African American young adolescents spend their time: Time budgets for locations, activities, and companionship. American Journal of Community Psychology, 29, 565–597.

    Article  PubMed  Google Scholar 

  • Larson, R. W., & Verma, S. (1999). How children and adolescents spend time across the world: Work, play and developmental opportunities. Psychological Bulletin, 125, 701–736.

    Article  PubMed  Google Scholar 

  • Leventhal, T., & Brooks-Gunn, J. (2000). The neighborhoods they live in: The effects of neighborhood residence on child and adolescent outcomes. Psychological Bulletin, 126, 309–337.

    Article  PubMed  Google Scholar 

  • Levine, T. R., & Hullett, C. R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research, 28, 612–625.

    Article  Google Scholar 

  • Linver, M. R., Roth, J. L., & Brooks-Gunn, J. (2009). Patterns of adolescents’ participation in organized activities: Are sports best when combined with other activities? Developmental Psychology, 45, 354.

    Article  PubMed  Google Scholar 

  • Lipsey, M. W. (1992). Juvenile delinquency treatment: A meta-analytic inquiry into the variability of effects. In T. D. Cook, et al. (Eds.), Meta-analysis for explanation: A casebook. NY: Russell Sage.

    Google Scholar 

  • Lleras, C. (2008). Do skills and behaviors in high school matter? The contribution of noncognitive factors in explaining differences in educational attainment and earnings. Social Science Research, 37, 888–902.

    Article  Google Scholar 

  • Loeber, R., & Dishion, T. J. (1983). Early predictors of male delinquency: A review. Psychological Bulletin, 94, 325–382.

    Article  Google Scholar 

  • Luke, D. A., Rappaport, J., & Seidman, E. (1991). Setting phenotypes in a mutual help organization: Expanding behavior setting theory. American Journal of Community Psychology, 19, 147.

    Article  PubMed  Google Scholar 

  • Magnusson, D. (1995). Individual development: A holistic integrated model. In P. Moen, G. H. Elder, & K. Luscher (Eds.), Linking lives and contexts: Perspectives on the ecology of human development (pp. 19–60). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  • Mahoney, J. L. (2000). School extracurricular activity participation as a moderator in the development of antisocial patterns. Child Development, 71, 502–516.

    Article  PubMed  Google Scholar 

  • Mahoney, J. L., & Cairns, R. B. (1997). Do extracurricular activities protect against early school dropout? Developmental Psychology, 33, 241–253.

    Article  PubMed  Google Scholar 

  • Mahoney, J. L., Larson, R. W., & Eccles, J. S. (Eds.). (2005). Organized activities as contexts of development: Extracurricular activities, after school and community programs. Malwah, NJ: Lawrence Erlbaum & Associates.

    Google Scholar 

  • Mahoney, J. L., Stattin, H., & Lord, H. (2004). Unstructured youth recreation centre participation and antisocial behavior development: Selection influences and the moderating role of antisocial peers. International Journal of Behavioral Development, 28, 553–560.

    Article  Google Scholar 

  • Mahoney, J. L., Stattin, H., & Magnusson, D. (2001). Youth recreation center participation and criminal offending: A 20-year longitudinal study of Swedish boys. International Journal of Behavioral Development, 25, 509–520.

    Article  Google Scholar 

  • Mahoney, J. L., Vandell, D. L., Simpkins, S., & Zarrett, N. (2009). Adolescent out-of-school activities. In R. M. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology. John Wiley: Hoboken, NJ.

    Google Scholar 

  • McHale, S. M., Kim, J., Whiteman, S. D., & Crouter, A. C. (2004). Links between sex-typed time use in middle childhood and gender development in early adolescence. Developmental Psychology, 40, 868.

    Article  PubMed  Google Scholar 

  • McHale, J. P., Vinden, P. G., Bush, L., Richer, D., Shaw, D., & Smith, B. (2005). Patterns of personal and social adjustment among sport-involved and noninvolved urban middle-school children. Sociology of Sport Journal, 22, 119–136.

    Google Scholar 

  • Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, L., Freeman, K., et al. (2000). Manual for the patterns of adaptive learning scales. Ann Arbor, MI: University of Michigan.

    Google Scholar 

  • Milligan, G. W. (1996). Clustering validation: Results and implications for applied analyses. In P. Arabie, L. J. Hubert, & G. De Soete (Eds.), Clustering and classification (pp. 341–375). Singapore: World Scientific.

    Chapter  Google Scholar 

  • Morris, P. A., Aber, J. L., Wolf, S., & Berg, J. (2012). Using incentives to change how teenagers spend their time the effects of New York city’s conditional cash transfer program. New York: MDRC.

    Google Scholar 

  • Nelson, I. A., & Gastic, B. (2009). Street ball, swim team and the sour cream machine: A cluster analysis of out of school time participation portfolios. Journal of Youth and Adolescence, 38, 1172–1186.

    Article  PubMed  Google Scholar 

  • Orpinas, P., & Frankowski, R. (2001). The aggression scale: A self-report measure of aggressive behavior for young adolescents. Journal of Early Adolescence, 21, 50–67.

    Article  Google Scholar 

  • Osgood, D. W., & Anderson, A. L. (2004). Unstructured socializing and rates of delinquency. Criminology, 42, 519–550.

    Article  Google Scholar 

  • Passmore, A., & French, D. (2001). Development and administration of a measure to assess adolescents’ participation in leisure activities. Adolescence, 36, 67–75.

    PubMed  Google Scholar 

  • Patterson, E. B. (1991). Poverty, income inequality, and community crime rates. Criminology, 29, 755–776.

    Article  Google Scholar 

  • Pederson, S., & Seidman, E. (2005). Contexts and correlates of out of school activity participation among low-income urban adolescents. In J. L. Mahoney, R. W. Larson, & J. S. Eccles (Eds.), Organized activities as contexts of development: Extracurricular activities, after-school and community programs (pp. 85–109). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement. Educational Psychologist, 37, 91–105.

    Article  Google Scholar 

  • Phipps, P. A., & Vernon, M. (2009). Twenty-four hours. In R. F. Belli, F. P. Stafford, & D. F. Alwin (Eds.), Calendar and time diary: Methods in life course research (pp. 109–128). Thousand Oaks: Sage.

    Google Scholar 

  • Raymore, L. A., Barber, B. L., Eccles, J. S., & Godbey, G. C. (1999). Leisure behavior pattern stability during the transition from adolescence to young adulthood. Journal of Youth and Adolescence, 28, 79–103.

    Article  Google Scholar 

  • Reardon, S. F., Robinson-Cimpian, J. P., & Weathers, E. S. (2014). Patterns and trends in racial/ethnic and socioeconomic academic achievement gaps. In H. A. Ladd & M. E. Goertz (Eds.), Handbook of research in education and finance policy. United Kingdom: Lawrence Erlbaum.

    Google Scholar 

  • Riccio, J., Dechausay, N., Greenberg, D., Miller, C., Rucks, Z., & Verma, N. (2010). Toward reduced poverty across generations. New York: MDRC.

    Google Scholar 

  • Rideout, V. J., Foehr, U. G., & Roberts, D. F. (2010). Generation M: Media in the lives of 8- to 18-year olds. 10. Menlo Park, CA: A Kaiser Family Foundation Study.

    Google Scholar 

  • Robinson, J. P. (1985). The validity and reliability of diaries versus alternative time use measures. In F. T. Juster & F. P. Stafford (Eds.), Time, goods, and wellbeing (pp. 33–62). Ann Arbor: University of Michigan, Institute for Social Research.

    Google Scholar 

  • Ryan, C. (2013). Language use in the United States: 2011. American community survey reports. U.S. census bureau. Retrieved from http://www.census.gov/prod/2013pubs/acs-22.pdf.

  • Ryan, R. M., & Connell, J. P. (1989). Perceived locus of causality and internalization: Examining reasons for acting in two domains. Journal of Personality and Social Psychology, 57, 749.

    Article  PubMed  Google Scholar 

  • Shanahan, M. J., & Flaherty, B. P. (2001). Dynamic patterns of time use in adolescence. Child Development, 72, 385–401.

    Article  PubMed  Google Scholar 

  • Sirin, S. R., & Sirin, L. (2004). Exploring school engagement of middle-class African American adolescents. Youth and Society, 35, 322–340.

    Article  Google Scholar 

  • Steinberg, L., & Cauffman, E. (1995). The impact of employment on adolescent development. Annals of Child Development, 11, 131–166.

    Google Scholar 

  • Theokas, C., & Bloch, M. (2006). Out-of-school time is critical for children: Who participates in programs?. Washington, DC: Child Trends.

    Google Scholar 

  • Umaña-Taylor, A. J. (2004). Ethnic identity and self-esteem: Examining the role of social context. Journal of Adolescence, 27, 139–146.

    Article  PubMed  Google Scholar 

  • Updegraff, K. A., McHale, S. M., Whiteman, S. D., Thayer, S. M., & Crouter, A. C. (2006). The nature and correlates of Mexican-American adolescents’ time with parents and peers. Child Development, 77, 1470.

    Article  PubMed Central  PubMed  Google Scholar 

  • Voelkl, K. E., & Frone, M. R. (2000). Predictors of substance use at school among high school students. Journal of Educational Psychology, 92, 583.

    Article  Google Scholar 

  • Wong, C. A., & Rowley, S. J. (2001). The schooling of ethnic minority children: Commentary. Educational Psychologist, 36, 57–66.

    Article  Google Scholar 

  • Zarrett, N., Fay, K., Li, Y. B., Carrano, J., Phelps, E., & Lerner, R. M. (2009). More than child’s play: Variable- and pattern centered approaches for examining effects of sports participation on youth development. Developmental Psychology, 45, 368–382.

    Article  PubMed  Google Scholar 

  • Zimmerman, B. J., & Schunk, D. H. (Eds.). (2013). Self-regulated learning and academic achievement: Theoretical perspectives. Washington, DC: Routledge.

    Google Scholar 

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Acknowledgments

This article summarizes some of the findings from an evaluation conducted by MDRC, with support from the William T. Grant Foundation, the New York City Center for Economic Opportunity (CEO), and the Smith Richardson Foundation. The authors give thanks to the many staff members at Seedco and the Neighborhood Partner Organizations who spent countless hours operating the program and collecting the essential data on families’ participation and experiences. We’d also like to thank the many people at MDRC who contributed to managing this study.

Author Contributions

J.A. conceived of the study and participated in the design and coordination of the study. P.M. conceived of the study and participated in the design of the survey instrument. S.W. conducted all statistical analyses and interpretation of the data, while all authors worked closely to interpret the results. S.W. drafted the manuscript with careful input from P.M. and J.A. All authors read and approved the final manuscript.

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The authors report no conflicts of interests.

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Wolf, S., Aber, J.L. & Morris, P.A. Patterns of Time Use Among Low-Income Urban Minority Adolescents and Associations with Academic Outcomes and Problem Behaviors. J Youth Adolescence 44, 1208–1225 (2015). https://doi.org/10.1007/s10964-015-0294-0

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