Selective Classes and Early Health Inequalities in Comprehensive Schools in Finland.

adolescence comprehensive schooling health inequality selective class student grouping

Journal

The Journal of school health
ISSN: 1746-1561
Titre abrégé: J Sch Health
Pays: United States
ID NLM: 0376370

Informations de publication

Date de publication:
03 Jul 2024
Historique:
revised: 13 05 2024
received: 29 06 2023
accepted: 24 05 2024
medline: 4 7 2024
pubmed: 4 7 2024
entrez: 3 7 2024
Statut: aheadofprint

Résumé

The origin of inequalities in health outcomes has been explained by health selection and social causation models. Health selection processes operate particularly at school age. We study, if student allocation to teaching groups with aptitude tests (selective vs general class) differentiates adolescents by health behaviors and mental health. Finnish schoolchildren 12-13 years from 12 selective classes, n = 248; 41 general classes, n = 703 answered a questionnaire on addictive products (tobacco, snus, alcohol, and energy drinks), digital media use, and mental health (health complaints, anxiety, and depression). Structural equation modeling was conducted to identify structures between outcomes, SEP (socioeconomic position), class type, and academic performance. Students in the selective classes reported less addictive digital media and addictive products use than students in the general classes. Differences in academic performance or SEP between the class types did not solely explain these differences. Mental health was not related to the class type. SEP was indirectly associated with health behaviors via the class type and academic performance. Selecting students to permanent teaching groups with aptitude tests differentiates students according to risky health behaviors. The impact of education policies using student grouping should also be evaluated in terms of students' health.

Sections du résumé

BACKGROUND BACKGROUND
The origin of inequalities in health outcomes has been explained by health selection and social causation models. Health selection processes operate particularly at school age. We study, if student allocation to teaching groups with aptitude tests (selective vs general class) differentiates adolescents by health behaviors and mental health.
METHODS METHODS
Finnish schoolchildren 12-13 years from 12 selective classes, n = 248; 41 general classes, n = 703 answered a questionnaire on addictive products (tobacco, snus, alcohol, and energy drinks), digital media use, and mental health (health complaints, anxiety, and depression). Structural equation modeling was conducted to identify structures between outcomes, SEP (socioeconomic position), class type, and academic performance.
RESULTS RESULTS
Students in the selective classes reported less addictive digital media and addictive products use than students in the general classes. Differences in academic performance or SEP between the class types did not solely explain these differences. Mental health was not related to the class type. SEP was indirectly associated with health behaviors via the class type and academic performance.
CONCLUSIONS CONCLUSIONS
Selecting students to permanent teaching groups with aptitude tests differentiates students according to risky health behaviors. The impact of education policies using student grouping should also be evaluated in terms of students' health.

Identifiants

pubmed: 38961003
doi: 10.1111/josh.13488
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : The Turku Urban Research Programme
Organisme : Tampere University Hospital
ID : 9AB061
Organisme : Tampere University Hospital
ID : 9AC081
Organisme : Juho Vainio Foundation
Organisme : Nordforsk
ID : Project156778YoungEqual

Informations de copyright

© 2024 The Author(s). Journal of School Health published by Wiley Periodicals LLC on behalf of American School Health Association.

Références

Marmot M, Friel S, Bell R, Houweling TA, Taylor S. Closing the gap in a generation: health equity through action on the social determinants of health. Lancet. 2008;372(9650):1661‐1669.
Mackenbach JP, Valverde JR, Bopp M, et al. Progress against inequalities in mortality: register‐based study of 15 European countries between 1990 and 2015. Eur J Epidemiol. 2019;34(12):1131‐1142.
Macintyre S. The black report and beyond what are the issues? Soc Sci Med. 1997;44(6):723‐745.
Goldman N. Social factors and health: the causation‐selection issue revisited. Proc Natl Acad Sci USA. 1994;91(4):1251‐1255.
Hoffmann R, Kröger H, Geyer S. Social causation versus health selection in the life course: does their relative importance differ by dimension of SES? Soc Indic Res. 2019;141(3):1341‐1367.
Yang HK, Gustafsson J, Rosen M. School performance differences and policy variations in Finland, Norway and Sweden. In: Hansen KY, Gustafsson JE, Rosén M, Sulkunen S, Nissinen K, Kupari P, et al., eds. Northern Lights on TIMSS and PIRLS 2011: Differences and Similarities in the Nordic Countries. Norway: Nordisk Ministerråd; 2014:25‐48.
Seppänen P, Pasu T, Kosunen S. Pupil selection and enrolment in comprehensive schools in urban Finland. In: Thrupp M, Seppänen P, Kauko J, Kosunen S, eds. Finland's Famous Education System Unvarnished Insights into Finnish Schooling. Singapore: Springer Nature; 2023:193‐210.
Berisha AK, Seppänen P. Pupil selection segments urban comprehensive schooling in Finland: composition of school classes in pupils' school performance, gender, and ethnicity. Scand J Educ Res. 2017;61(2):240‐254.
Kosunen S, Bernelius V, Seppänen P, Porkka M. School choice to lower secondary schools and mechanisms of segregation in urban Finland. Urban Educ. 2020;55(10):1461‐1488.
Peetsma T, van der Veen I, Koopman P, van Schooten E. Class composition influences on pupils' cognitive development 1. Sch Eff Sch Improv. 2006;17(3):275‐302.
van Ewijk R, Sleegers P. The effect of peer socioeconomic status on student achievement: a meta‐analysis. Educ Res Rev. 2010;5(2):134‐150.
de Fraine B, Van Damme J, Van Landeghem G, Opdenakker MC, Onghena P. The effect of schools and classes on language achievement. Br Educ Res J. 2003;29(6):841‐859.
Hienonen N, Lintuvuori M, Jahnukainen M, Hotulainen R, Vainikainen MP. The effect of class composition on cross‐curricular competences – students with special educational needs in regular classes in lower secondary education. Learn Instr. 2018;58:80‐87.
Marsh HW, Seaton M. The big‐fish–little‐pond effect, competence self‐perceptions, and relativity: substantive advances and methodological innovation. In: Elliot AJ, ed. Advances in Motivation Science, Vol. 2. San Diego: Elsevier; 2015:127‐184. https://doi.org/10.1016/bs.adms.2015.05.002.
Koivuhovi S, Marsh HW, Dicke T, et al. Academic self‐concept formation and peer‐group contagion: development of the big‐fish‐little‐pond effect in primary‐school classrooms and peer groups. J Educ Psychol. 2022;114(1):198‐213.
Luukkonen J, Bernelius V, Palmqvist R, Raitasalo K. School segregation, selective education, and adolescents' alcohol use – is there a connection? Scand J Educ Res. 2023;68:702‐716. https://doi.org/10.1080/00313831.2023.2175251.
Moor I, Kuipers MAG, Lorant V, et al. Inequalities in adolescent self‐rated health and smoking in Europe: comparing different indicators of socioeconomic status. J Epidemiol Community Health. 2019;73(10):963‐970.
Latvala A, Rose RJ, Pulkkinen L, Dick DM, Korhonen T, Kaprio J. Drinking, smoking, and educational achievement: cross‐lagged associations from adolescence to adulthood. Drug Alcohol Depend. 2014;137(1):106‐113.
Koivusilta L, West P, Saaristo V, Nummi T, Rimpelä A. From childhood socio‐economic position to adult educational level – do health behaviours in adolescence matter? A longitudinal study. BMC Public Health. 2013;13(1):711.
Liu D, Kirschner PA, Karpinski AC. A meta‐analysis of the relationship of academic performance and social network site use among adolescents and young adults. Comput Hum Behav. 2017;77:148‐157.
Paakkari L, Tynjälä J, Lahti H, Ojala K, Lyyra N. Problematic social media use and health among adolescents. J Environ Public Health. 2021;18(4):1‐11.
Adelantado‐Renau M, Moliner‐Urdiales D, Cavero‐Redondo I, Beltran‐Valls MR, Martínez‐Vizcaíno V, Álvarez‐Bueno C. Association between screen media use and academic performance among children and adolescents: a systematic review and meta‐analysis. Arch Pediatr Adolesc Med. 2019;173(11):1058‐1067.
Fröjd SA, Nissinen ES, Pelkonen MU, Marttunen MJ, Koivisto AM, Kaltiala‐Heino R. Depression and school performance in middle adolescent boys and girls. J Adolesc. 2008;31(4):485‐498.
Agnafors S, Barmark M, Sydsjö G. Mental health and academic performance: a study on selection and causation effects from childhood to early adulthood. Soc Psychiatry Psychiatr Epidemiol. 2021;56(5):857‐866.
Rathmann K, Herke M, Bilz L, Rimpelä A, Hurrelmann K, Richter M. Class‐level school performance and life satisfaction: differential sensitivity for low‐and high‐performing school‐aged children. Int J Environ Res Public Health. 2018;15(12):2750. https://doi.org/10.3390/ijerph15122750.
Nordlander E, Stensöta HO. Grades – for better or worse? The interplay of school performance and subjective well‐being among boys and girls. Child Indic Res. 2014;7(4):861‐879.
OECD. Educational mobility and school‐to‐work transitions among disadvantaged students. In: Equity in Education: Breaking Down Barriers to Social Mobility. Paris: OECD Publishing; 2018. https://doi.org/10.1787/9789264073234‐8‐en.
Eriksson U, Sellström E. School demands and subjective health complaints among Swedish schoolchildren: a multilevel study. Scand J Public Health. 2010;38(4):344‐350.
Torsheim T, Wold B. School‐related stress, support, and subjective health complaints among early adolescents: a multilevel approach. J Adolesc. 2001;24(6):701‐713.
Minkkinen J, Lindfors P, Kinnunen J, et al. Health as a predictor of students' academic achievement: a 3‐level longitudinal study of Finnish adolescents. J Sch Health. 2017;87:902‐910.
Howe LD, Lawlor DA, Propper C. Trajectories of socioeconomic inequalities in health, behaviours and academic achievement across childhood and adolescence. J Community Health. 2013;67(4):358‐364.
Loft L, Waldfogel J. Socioeconomic status gradients in young children's well‐being at school. Child Dev. 2021;92(1):e91‐e105. https://doi.org/10.1111/cdev.13453.
Elgar FJ, Pförtner TK, Moor I, De Clercq B, Stevens GWJM, Currie C. Socioeconomic inequalities in adolescent health 2002–2010: a time‐series analysis of 34 countries participating in the Health Behaviour in School‐aged Children study. Lancet. 2015;385(9982):2088‐2095.
Gomes de Matos E, Kraus L, Hannemann T, Soellner R, Piontek D. Cross‐cultural variation in the association between family's socioeconomic status and adolescent alcohol use. Drug Alcohol Rev. 2017;36(6):797‐804.
Torikka A, Kaltiala‐Heino R, Luukkaala T, Rimpelä A. Trends in alcohol use among adolescents from 2000 to 2011: the role of socioeconomic status and depression. Alcohol Alcohol. 2017;52(1):95‐103.
Haugland S, Wold B. Subjective health complaints in adolescence—reliability and validity of survey methods. J Adolesc. 2001;24(5):611‐624.
Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD‐7. Arch Intern Med. 2006;166(10):1092‐1097.
Tiirikainen K, Haravuori H, Ranta K, Kaltiala‐Heino R, Marttunen M. Psychometric properties of the 7‐item Generalized Anxiety Disorder Scale (GAD‐7) in a large representative sample of Finnish adolescents. Psychiatry Res. 2019;272:30‐35.
Kroenke K, Spitzer RL, Williams JBW. The patient health questionnaire‐2: validity of a two‐item depression screener. Med Care. 2003;41(11):1284‐1292.
Richardson LP, Rockhill C, Russo JE, et al. Evaluation of the PHQ‐2 as a brief screen for detecting major depression among adolescents. J Pediatr. 2010;125(5):e1097‐e1103. https://doi.org/10.1542/peds.2009‐2712.
Andreassen CS, Billieux J, Griffiths MD, et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large‐scale cross‐sectional study. Psychol Addict Behav. 2016;30(2):252‐262.
Griffiths M. A “components” model of addiction within a biopsychosocial framework. J Subst Use. 2005;10(4):191‐197.
Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol. 2009;12(1):77‐95.
Vainikainen MP, Hautamäki J. Three studies on learning to learn in Finland: anti‐Flynn effects 2001‐2017. Scand J Educ Res. 2022;66(1):43‐58.
Kline RB. Principles and Practice of Structural Equation Modeling. 4th ed. New York: The Guilford Press; 2016.
Peugh JL. A practical guide to multilevel modeling. J Sch Psychol. 2010;48(1):85‐112.
Hayes AF. A primer on multilevel modeling. Hum Commun Res. 2006;32(4):385‐410.
Schermelleh‐Engel K, Moosbrugger H, Müller H. Evaluating the fit of structural equation models: tests of significance and descriptive goodness‐of‐fit measures. Methods Psychol Res. 2003;8:23‐74.
Tabachnick BG, Fidell LS. Using Multivariate Statistics. New York: Pearson; 1996.
Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull. 1980;88(3):588‐606.
Dishion TJ, Dodge KA. Peer contagion in interventions for children and adolescents: moving towards an understanding of the ecology and dynamics of change. J Abnorm Child Psychol. 2005;33(3):395‐400.
Mercken L, Steglich C, Knibbe CA, De Vries H. Dynamics of friendship networks and alcohol use in early and mid adolescence. J Stud Alcohol Drugs. 2012;73(1):99‐110.
Henneberger AK, Mushonga DR, Preston AM. Peer influence and adolescent substance use: a systematic review of dynamic social network research. Adolesc Res Rev. 2021;6(1):57‐73.
Huang GC, Unger JB, Soto D, et al. Peer influences: the impact of online and offline friendship networks on adolescent smoking and alcohol use. J Adolesc Health. 2014;54(5):508‐514.
Montgomery SC, Donnelly M, Bhatnagar P, Carlin A, Kee F, Hunter RF. Peer social network processes and adolescent health behaviors: a systematic review. Prev Med. 2020;130:105900. https://doi.org/10.1016/j.ypmed.2019.105900.
Robert PO, Kuipers M, Rathmann K, et al. Academic performance and adolescent smoking in 6 European cities: the role of friendship ties. Int J Adolesc Youth. 2019;24(1):125‐135.
Marsh HW, Kong CK, Hau KT. Longitudinal multilevel models of the big‐fish‐little‐pond effect on academic self‐concept: counterbalancing contrast and reflected‐glory effects in Hong Kong schools. J Pers Soc Psychol. 2000;78(2):337‐349.
Neal JW, Veenstra R. Network selection and influence effects on children's and adolescents' internalizing behaviors and peer victimization: a systematic review. Dev Rev. 2021;59:100944. https://doi.org/10.1016/j.dr.2020.100944.
Bernasco EL, van der Graaff J, Nelemans SA, Kaufman TML, Branje S. Depression socialization in early adolescent friendships: the role of baseline depressive symptoms and autonomous functioning. J Youth Adolesc. 2023;52(7):1417‐1432.
Cavallo F, Dalmasso P, Ottová‐Jordan V, et al. Trends in self‐rated health in European and north‐American adolescents from 2002 to 2010 in 32 countries. Eur J Public Health. 2015;25(2):13‐15.
Haugland S, Wold B, Stevenson J, Aaroe LE, Woynarowska B. Subjective health complaints in adolescence: a cross‐national comparison of prevalence and dimensionality. Eur J Public Health. 2001;11(1):4‐10.

Auteurs

Heidi Kesanto-Jokipolvi (H)

Faculty of Social Sciences, Unit of Health Sciences, Tampere University, Tampere, Finland.

Piia Seppänen (P)

Centre for Research on Lifelong Learning and Education CELE, University of Turku, Turku, Finland.

Satu Koivuhovi (S)

Inequalities, Interventions, and a New Welfare State INVEST, University of Turku, Turku, Finland.

Mari Siipola (M)

Centre for Research on Lifelong Learning and Education CELE, University of Turku, Turku, Finland.

Reija Autio (R)

Faculty of Social Sciences, Unit of Health Sciences, Tampere University, Tampere, Finland.

Arja Rimpelä (A)

Faculty of Social Sciences, Unit of Health Sciences, Tampere University; Department of Adolescent Psychiatry, Tampere University Hospital, Tampere, Finland.

Classifications MeSH