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Out-of-School Activities on Weekdays and Adolescent Adjustment in China: a Person-Centered Approach

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The present study used a person-centered approach to identify adolescent out-of-school activity profiles and to examine whether academic achievement, cognitive ability and negative emotion vary across different profiles. Data were collected from 9312 adolescents, and four profiles were identified: the “academic tutoring profile”, the “moderate time-consuming profile”, the “screen profile” and the “low time-consuming profile”. These four profiles differed in academic achievement, cognitive ability and negative emotion. The students in the low time-consuming profile had the best performance on all indicators. Those in the academic tutoring profile had high academic achievement but a low level of cognitive ability and a high level of negative emotion. This result indicates that for some students, long-term academic tutoring can improve their academic achievement through emotional costs and that academic tutoring cannot improve their cognitive ability. The students in the screen profile had the worst performance on both academic achievement and cognitive ability, and the large amount of screen time did not even make them happy.

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References

  • Aishworiya, R., Cai, S. R., Chen, H. Y., Phua, D. Y., Broekman, B. F. P., Daniel, L. M., et al. (2019). Television viewing and child cognition in a longitudinal birth cohort in Singapore: The role of maternal factors. BMC Pediatrics, 19(1), 1–8.

    Google Scholar 

  • Allahverdipour, H., Bazargan, M., Farhadinasab, A., & Moeini, B. (2010). Correlates of video games playing among adolescents in an Islamic country. BMC Public Health, 10(286), 1–7.

    Google Scholar 

  • Anand, V. (2007). A study of time management: The correlation between video game usage and academic performance markers. Cyber Psychology & Behavior, 10(4), 552–559.

    Google Scholar 

  • Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78(4), 772–790.

    Google Scholar 

  • Ang, R. P., & Huan, V. S. (2006). Relationship between academic stress and suicidal ideation: Testing for depression as a mediator using multiple regression. Child Psychiatry & Human Development, 37(2), 133–143.

    Google Scholar 

  • Asparouhov, T., & Muthén, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using mplus. Structural Equation Modeling, 21, 329–341.

    Google Scholar 

  • Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling, 23, 20–31.

    Google Scholar 

  • Baron, I. (1985). What kind of intelligence components are fundamental? In J. W. Segal, S. F. Chipman, & R. Glaser (Eds.), Thinking and learning skills (Vol. 2, pp. 365–390). Hillsdale: Erlbaum Press.

    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(4), 233–241.

    Google Scholar 

  • Bolck, A., Croon, M. A., & Hagenaars, J. A. (2004). Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political Analysis, 12, 3–27.

    Google Scholar 

  • Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. British Journal of Developmental Psychology, 23(1), 143–151.

    Google Scholar 

  • Byun, S. Y., & Park, H. (2012). The academic success of east Asian American youth: The role of shadow education. Sociology of Education, 85(1), 40–60.

    Google Scholar 

  • Cheung, C. S. S., & Pomerantz, E. M. (2011). Parents’ involvement in children’s learning in the United States and China: Implications for children’s academic and emotional adjustment. Child Development, 82(3), 932–950.

    Google Scholar 

  • Christakis, D. A., Zimmerman, F. J., DiGiuseppe, D. L., & McCarty, C. A. (2004). Early television exposure and subsequent attentional problems in children. Pediatrics, 113(4), 708–713.

    Google Scholar 

  • Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis. With applications in the social, behavioral, and health sciences. Hoboken: John Wiley & Sons Press.

    Google Scholar 

  • Cooper, H. (1989). Homework. White Plains: Longman.

    Google Scholar 

  • Cooper, A., Putnam, D. E., Planchon, L. A., & Boies, S. C. (1999a). Online sexual compulsivity: Getting tangled in the net. Sexual Addiction & Compulsivity: The Journal of Treatment and Prevention, 6(2), 79–104.

    Google Scholar 

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

    Google Scholar 

  • Cooper, H., Robinson, J. C., & Patall, E. A. (2006). Does homework improve academic achievement? A synthesis of research, 1987-2003. Review of Educational Research, 76, 1–62.

    Google Scholar 

  • Du, F. (2018). Where did the time go?: China time use survey report. Beijing: China Social Science Press.

    Google Scholar 

  • Eccles, J. S., & Templeton, J. (2002). Extracurricular and other after-school activities for youth. Review of Research in Education, 26(1), 113–180.

    Google Scholar 

  • Flaherty, B. P., & Kiff, C. J. (2012). Latent class and latent profilemodels. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology (Vol. 3: Data analysis and research publication) (pp. 391–404). Washington, DC: American Psychological Association.

    Google Scholar 

  • Gentile, D. A., Lynch, P. J., Linder, J. R., & Walsh, D. A. (2004). The effects of violent video game habits on adolescent hostility, aggressive behaviors, and school performance. Journal of Adolescence, 27(1), 5–22.

    Google Scholar 

  • Giammattei, J., Blix, G., Marshak, H. H., Wollitzer, A. O., & Pettitt, D. J. (2003). Television watching and soft drink consumption: Associations with obesity in 11-to 13-year-old schoolchildren. Archives of Pediatrics & Adolescent Medicine, 157(9), 882–886.

    Google Scholar 

  • Gidwani, P. P., Sobol, A., DeJong, W., Perrin, J. M., & Gortmaker, S. L. (2002). Television viewing and initiation of smoking among youth. Pediatrics, 110(3), 505–508.

    Google Scholar 

  • Guo, Q., Zhou, J., & Feng, L. (2018). Pro-social behavior is predictive of academic success via peer acceptance: A study of Chinese primary school children. Learning and Individual Differences, 65, 187–194.

    Google Scholar 

  • Hilsman, R., & Garber, J. (1995). A test of the cognitive diathesis-stress model of depression in children: Academic stressors, attributional style, perceived competence, and control. Journal of Personality & Social Psychology, 69(2), 370–380.

    Google Scholar 

  • Hu, H., & Yin, Y. (2015). The reflection and advance of reducing primary and secondary school academic burden in China. Global Education(in Chinese), 44(12), 48–95.

    Google Scholar 

  • Kitsantas, A., Cheema, J., & Ware, H. W. (2011). Mathematics achievement: The role of homework and self-efficacy beliefs. Journal of Advanced Academics, 22(2), 310–339.

    Google Scholar 

  • Lv, B., Lv, L., Yan, Z., & Luo, L. (2019). The relationship between parental involvement in education and children's academic/emotion profiles: A person-centered approach. Children and Youth Services Review, 100, 175–182.

    Google Scholar 

  • Marsh, H. W., Lüdtke, O., Trautwein, U., & Morin, A. J. S. (2009). Classical latent profile analysis of academic self-concept dimensions: Synergy of person- and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling, 16, 191–225.

    Google Scholar 

  • McNeish, D., Stapleton, L. M., & Silverman, R. D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods, 22(1), 114–140.

    Google Scholar 

  • Mischo, C., & Haag, L. (2002). Expansion and effectiveness of private tutoring. European Journal of Psychology of Education, 17(3), 263–273.

    Google Scholar 

  • Morris, P., & Kalil, A. (2006). Out-of-school time use during middle childhood in a low-income sample: Do combinations of activities affect achievement and behavior? New York: Cambridge University Press.

    Google Scholar 

  • Obradović, J., Burt, K. B., & Masten, A. S. (2009). Testing a dual cascade model linking competence and symptoms over 20 years from childhood to adulthood. Journal of Clinical Child & Adolescent Psychology, 39(1), 90–102.

    Google Scholar 

  • OECD. (2017). Are students happy? pisa 2015 results: students’ well-being. Pisa in Focus.

  • Paschal, R. A., Weinstein, T., & WAlberg, H. J. W. (1984). The effects of homework on learning: A quantitative synthesis. The Journal of Educational Research, 78(2), 97–104.

    Google Scholar 

  • Petras, H., & Masyn, K. (2010). General growth mixture analysis with antecedents and consequences of change. In Handbook of quantitative criminology (pp. 69–100). New York: Springer press.

    Google Scholar 

  • Razel, M. (2001). The complex model of television viewing and educational achievement. The Journal of Educational Research, 94(6), 371–379.

    Google Scholar 

  • Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177.

    Google Scholar 

  • Schreiber, J. B. (2000). Advanced mathematics achievement, unpublished doctoral dissertation. Bloomington: Indiana University.

    Google Scholar 

  • Shams, T. A., Foussias, G., Zawadzki, J. A., Marshe, V. S., Siddiqui, I., Muller, D. J., & Wong, A. H. C. (2015). The effects of video games on cognition and brain structure: Potential implications for neuropsychiatric disorders. Current Psychiatry Reports, 17(9), 1–15.

    Google Scholar 

  • Silbereisen, R. K., & Eyferth, K. (1986). Development as action in context. In R. K. Silbereisen, K. Eyferth, & G. Rudinger (Eds.), Development as action in context: Problem behavior and normal youth development (pp. 3–16). Berlin: Springer-Verlag.

    Google Scholar 

  • Smyth, E. (2008). The more, the better? Intensity of involvement in private tuition and examination performance. Educational Research and Evaluation, 14(5), 465–476.

    Google Scholar 

  • Sun, L., Shafiq, M. N., McClure, M., & Guo, S. (2020). Are there educational and psychological benefits from private supplementary tutoring in mainland China? Evidence from the China education panel survey, 2013-15. International Journal of Educational Development, 72. https://doi.org/10.1016/j.ijedudev.2019.102144.

  • Thibodeaux, J., Deutsch, A., Kitsantas, A., & Winsler, A. (2017). First-year college students’ time use: Relations with self-regulation and GPA. Journal of Advanced Academics, 28(1), 5–27.

    Google Scholar 

  • Tofighi, D., & Enders, C. K. (2008). Identifying the correct number of classes in a growth mixture model. In G. R. Hancock (Ed.), Mixture models in latent variable research (pp. 317–341). Greenwich: Information Age Press.

    Google Scholar 

  • Trautwein, U., Köller, O., Schmitz, B., & Baumert, J. (2002). Do homework assignments enhance achievement? A multilevel analysis in 7th-grade mathematics. Contemporary Educational Psychology, 27(1), 26–50.

    Google Scholar 

  • Walberg, H. J. (1984). Improving the productivity of America’s schools. Educational Leadership, 41(8), 19–27.

    Google Scholar 

  • Wang, W., & Li, P. (2015). Psychometric report on cognitive ability test in China education panel survey (CEPS) baseline survey (in Chinese). https://ceps.ruc.edu.cn/assets/admin/org/ueditor/php/upload/20151221/14506963789569.pdf.

  • Williams, P. A., Haertel, E. H., Haertel, G. D., & Walberg, H. J. (1982). The impact of leisure-time television on school learning: A research synthesis. American Educational Research Journal, 19(1), 19–50.

    Google Scholar 

  • Xue, H., & Ding, X. (2009). A study on additional instruction for students in cities and towns in China. Educational Research, 348, 39–46 (in Chinese).

    Google Scholar 

  • Zhang, Y. (2013). Does private tutoring improve students’ National College Entrance Exam performance?—A case study from Jinan, China. Economics of Education Review, 32, 1–28.

    Google Scholar 

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Funding

National Science Foundation for Young Scientists of China (71904026) and Youth Fund Projects of Northeast Normal University (1909209). Jilin Province Social Science Fund (2020C081).

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Correspondence to Lijie Lv.

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All procedures performed in studies involving human participants 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. All procedures in this study were approved by Institutional Review Board of Faculty of Education, Northeast Normal University.

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Informed consent was obtained from all individual participants included in the study.

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Author Bo Lv declares that he has no conflict of interest. Author Lijie Lv declares that she has no conflict of interest.

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Lv, B., Lv, L. Out-of-School Activities on Weekdays and Adolescent Adjustment in China: a Person-Centered Approach. Child Ind Res 14, 783–798 (2021). https://doi.org/10.1007/s12187-020-09778-w

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