Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg March 7, 2018

Does Compressing High School Duration Affect Students’ Stress and Mental Health? Evidence from the National Educational Panel Study

  • Johanna Sophie Quis EMAIL logo

Abstract

Starting in 2004/2005, the German state Baden-Wurttemberg reduced academic track duration from nine to eight years, leaving cumulative instruction time mostly unchanged. I use this change in schooling policy to identify the effect of increased schooling intensity on students’ internalizing mental health problems and perceived stress. Using data on 2306 students from the Additional Study Baden-Wurttemberg of the National Educational Panel Study (NEPS), estimates show strong negative effects on internalizing mental health problems for girls and an increase in stress for both genders.

JEL Classification: I12; I28; I21; J24

Funding statement: This work was supported by the Bamberg Graduate School of Social Sciences which is funded by the German Research Foundation (DFG) under the German Excellence Initiative (GSC1024).

Acknowledgements

I am grateful to two anonymous referees, as well as to the editors, for helpful insights and comments on an earlier draft of this paper. Furthermore, I would like to thank Silke Anger, Guido Heineck, Stefanie Herber, and Jana Jarecki, seminar participants at the University of Bamberg, the participants of the Third Lisbon Research Workshop on Economics, Statistics and Econometrics of Education, the Sixth International Workshop on Applied Economics of Education, the 29th Annual Conference of the European Society for Population Economics, and the Workshop Consequences of the G8 Reform for useful comments and fruitful discussions.

References

Altner, Helmuth (2007), Naturwissenschaften im achtjährigen Gymnasium G8. Der mathematische und naturwissenschaftliche Unterricht 60 (8): 493–497.Search in Google Scholar

Andersen, Simon Calmar, Humlum Maria Knoth, Nandrup Anne Brink (2016), Increasing Instruction Time in School Learning Does Increase. Proceedings of the National Academy of Sciences 113 (27): 7481–7484. http://www.pnas.org/content/113/27/7481.abstract, DOI: http://dx.doi.org/10.1073/pnas.1516686113.Search in Google Scholar

Autorengruppe Bildungsberichterstattung (2010), Bildung in Deutschland 2010. Ein indikatorengestützter Bericht mit einer Analyse zu Perspektiven des Bildungswesens im demografischen Wandel. W. Bertelsmann, Bielefeld.Search in Google Scholar

Bergmüller, Silvia (2007), Schulstress unter Jugendlichen: Entstehungsbedingungen, vermittelnde Prozesse und Folgen; eine empirische Studie im Rahmen von PISA 2003, Bd. 24, Schriftenreihe Studien zur Streßforschung. Kovač, Hamburg.Search in Google Scholar

Bilz, Ludwig (2008), Schule und psychische Gesundheit: Risikobedingungen für emotionale Auffälligkeiten von Schülerinnen und Schülern. VS Verlag für Sozialwissenschaften, Wiesbaden.Search in Google Scholar

Bilz, Ludwig, Cornelia Hähne, Melzer Wolfgang (2003), Die Lebenswelt Schule und ihre Auswirkungen auf die Gesundheit von Jugendlichen. 243–299 in: Hurrelmann Klaus, Klocke Andreas, Wolfgang Melzer, U. Ravens-Sieberer (eds.), Jugendgesundheitssurvey. Juventa, Weinheim.Search in Google Scholar

Blossfeld, Hans-Peter, Hans-Günther Roßbach, von Maurice Jutta (eds.) (2011), Education as a Lifelong Process: The German National Educational Panel Study (NEPS) Zeitschrift für Erziehungswissenschaft, 14. VS Verlag für Sozialwissen\-schaften, Wiesbaden.Search in Google Scholar

Böhm-Kasper, Oliver, Horst Weishaupt (2002), Belastung und Beanspruchung von Lehrern und Schülern am Gymnasium. Zeitschrift für Erziehungswissenschaft 5 (3): 472–499, DOI: http://dx.doi.org/10.1007/s11618-002-0062-2.Search in Google Scholar

Brütting, Rolf (2007), Drastische Kürzung des Geschichtsunterrichts im achtjährigen Gymnasium. Geschichte, Politik und ihre Didaktik 35 (3–4): 179–182.Search in Google Scholar

Büttner, Bettina, Thomsen Stephan L. (2015), Are We Spending Too Many Years in School? Causal Evidence of the Impact of Shortening Secondary School Duration. German Economic Review 16 (1): 65–86, DOI: http://dx.doi.org/10.1111/geer.12038.Search in Google Scholar

Carneiro, Pedro, Crawford Claire, Goodman Alissa (2007), The Impact of Early Cognitive and Non-Cognitive Skills on Later Outcomes. CEE Discussion Papers. http://EconPapers.repec.org/RePEc:cep:ceedps:0092.Search in Google Scholar

Compas, Bruce, Wagner Barry (1991), Psychosocial Stress During Adolescence: Intrapersonal and Interpersonal Processes. 67–85 in: Colten M. E., Gore S. (eds.), Adolescent Stress: Causes and Consequences. Aldine de Gruyter, Hawthorne, NY, US.Search in Google Scholar

Costello, E. Jane, Copeland William, Angold Adrian (2011), Trends in psychopathology across the adolescent years: what changes when children become adolescents, and when adolescents become adults? Journal of Child Psychology and Psychiatry, and Allied Disciplines 52 (10): 1015–1025. DOI: http://dx.doi.org/10.1111/j.1469-7610.2011.02446.x.Search in Google Scholar

Crystal, David, Chen Chuansheng, Fuligni Andrew, Stevenson Harold, Chen-Chin Hsu, Huei-Jen Ko, Kitamura Seiro, Kimura Susumu (1994), Psychological Maladjustment and Academic Achievement: A Cross-Cultural Study of Japanese, Chinese, and American High School Students. Child Development 65 (3): 738–753. http://www.jstor.org/stable/1131415.10.2307/1131415Search in Google Scholar

Dahmann, Sarah, Anger Silke (2014), The Impact of Education on Personality: Evidence from a German High School Reform, IZA Discussion Paper No. 8139.10.2139/ssrn.2432423Search in Google Scholar

Dahmann, Sarah C. (in press), How Does Education Improve Cognitive Skills? Instructional Time versus Timing of Instruction. Labour Economics. DOI: http://dx.doi.org/10.1016/j.labeco.2017.04.008.Search in Google Scholar

Dam, Harmjan (2005), Der neue Lehrplan für das verkürzte Gymnasium. Schönberger Hefte 35 (4): 14–17.Search in Google Scholar

Dornbusch, Sanford, Mont-Reynaud Randy, Ritter Philip, Chen Zeng-Yin, Steinberg Laurence (1991), Stressful Events and Their Correlates Among Adolescents of Diverse Backgrounds. 111–130 in: Social Institutions and Social Change. Aldine de Gruyter, Hawthorne, NY, US.Search in Google Scholar

Dörsam, Michael, Verena Lauber (2015), The Effect of a Compressed High School Curriculum on University Performance.Search in Google Scholar

Eide, Eric, Showalter Mark H. (1998). The Effect of School Quality on Student Performance: A Quantile Regression Approach. Economics Letters 58 (3): 345–350. DOI: http://dx.doi.org/10.1016/S0165-1765(97)00286-3.Search in Google Scholar

Forehand, Rex, Neighbors Bryan, Wierson Michelle (1991), The Transition to Adolescence: The Role of Gender and Stress in Problem Behavior and Competence. Journal of Child Psychology and Psychiatry 32 (6): 929–937. DOI: http://dx.doi.org/10.1111/j.1469-7610.1991.tb01920.x.Search in Google Scholar

Garrison, C. Z., Schluchter M. D., Schoenbach V. J., Kaplan B. K. (1989), Epidemiology of Depressive Symptoms in Young Adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 28 (3): 343–351. DOI: http://dx.doi.org/10.1097/00004583-198905000-00007.Search in Google Scholar

Gneezy, U., Niederle M., Rustichini A. (2003), Performance in Competitive Environments: Gender Differences. The Quarterly Journal of Economics 118 (3): 1049–1074. DOI: 10.1162/00335530360698496.Search in Google Scholar

Gneezy, Uri, Rustichini Aldo (2004), Gender and Competition at a Young Age. The American Economic Review 94 (2): 377–381. DOI: 10.2307/3592914.Search in Google Scholar

Grant, Kathryn, Compas Bruce, Stuhlmacher Alice, Thurm Audrey, McMahon Susan, Halpert Jane (2003), Stressors and Child and Adolescent Psychopathology: Moving from Markers to Mechanisms of Risk. Psychological Bulletin} 129 (3): 447–466. DOI: http://dx.doi.org/10.1037/0033-2909.129.3.447.Search in Google Scholar

Heller, Kurt (2002), Begabtenförderung im Gymnasium: Ergebnisse einer zehnjährigen Längs\-schnitt\-stu\-die. Leske und Budrich, Opladen.10.1007/978-3-322-92212-0Search in Google Scholar

Homuth, Christoph (2017), Die G8-Reform in Deutschland: Auswirkungen auf Schülerleistungen und Bildungsungleichheit. Springer VS, Wiesbaden.10.1007/978-3-658-15378-6Search in Google Scholar

Hübner, Nicolas, Wolfgang Wagner, Jochen Kramer, Benjamin Nagengast, Ulrich Trautwein (2017), Die G8-Reform in Baden-Württemberg: Kompetenzen, Wohlbefinden und Freizeitverhalten vor und nach der Reform. Zeitschrift für Erziehungswissenschaft 1 (2): 1. DOI: http://dx.doi.org/10.1007/s11618-017-0737-3.Search in Google Scholar

Huebener, Mathias, Susanne Kuger, Jan Marcus (in press). Increased Instruction Hours and the Widening gap in Performance Student. Labour Economics. DOI: http://dx.doi.org/10.1016/j.labeco.2017.04.007.Search in Google Scholar

Huebener, Mathias, Marcus Jan (2015). Moving up a Gear: The Impact of Compressing Instructional Time into Fewer Years of Schooling. DIW Discussion Papers (1450). http://ideas.repec.org/p/diw/diwwpp/dp1450.html.Search in Google Scholar

Huebener, Mathias, Marcus Jan (2017), Compressing Instruction Time into Fewer Years of Schooling and the Impact on Student Performance. Special Issue: Economic Returns to Education 58: 1–14. DOI: http://dx.doi.org/10.1016/j.econedurev.2017.03.003.Search in Google Scholar

Kaiser, Arnim, Kaiser Ruth (1998). Entwicklung und Erprobung von Modellen der Begabtenförderung am Gymnasium mit Verkürzung der Schulzeit: Abschlussuntersuchung in der Gymnasialen Oberstufe (MSS), Schulversuche und Bildungsforschung. V. Hase und Koehler, Mainz.Search in Google Scholar

Karakurt, Yakamoz (2011), Mein Kopf ist voll! Selbst gute Schüler wollen lieber länger lernen, Die Zeit 34.Search in Google Scholar

Krashinsky, Harry (2014). How Would One Extra Year of High School Affect Academic Performance in University? Evidence from an Educational Policy Change, Canadian Journal of Economics/Revue canadienne d’économique, 47 (1), pp. 70–97, DOI: http://dx.doi.org/10.1111/caje.12066.Search in Google Scholar

Kühn, Svenja, Isabell Ackeren, Gabriele Bellenberg, Christian Reintjes, Grit Brahm (2013), Wie viele Schuljahre bis zum Abitur? Zeitschrift für Erziehungswissenschaft 16 (1): 115–136. DOI: http://dx.doi.org/10.1007/s11618-013-0339-7.Search in Google Scholar

Kühn, Svenja Mareike (2014), Sind 12 Schuljahre ausreichend für den Zugang zur Hochschule? Der doppelte Abiturjahrgang aus empirischer Perspektive. Bayerisches Staatsinst. für Hochschulforschung und Hochschulplanung, München.Search in Google Scholar

Kultusministerkonferenz (2013), Vereinbarung zur Gestaltung der gymnasialen Oberstufe in der Sekundarstufe II: Sekretariat der Ständigen Konferenz der Kultusminister der Länder in der Deutschland Bundesrepublik. Original July 7, 1972, revised June 6, 2013. http://www.kmk.org/fileadmin/veroeffentlichungen_beschluesse/1972/1972_07_07-Vereinbarung-Gestaltung-Sek2.pdf.Search in Google Scholar

Lavy, Victor (2015), Do Differences in Schools’ Instruction Time Explain International Achievement Gaps? Evidence from Developed and Developing Countries. The Economic Journal 125 (588): F397–F424. DOI: http://dx.doi.org/10.1111/ecoj.12233.Search in Google Scholar

Lee, Jong-Wha, Barro Robert J. (2001), Schooling Quality in a Cross-Section of Countries. Economica 68 (272): 465–488. DOI: http://dx.doi.org/10.1111/1468-0335.d01-12.Search in Google Scholar

Lewinsohn, Peter M., Rohde Paul, John R. Seeley (1998), Major Depressive Disorder in Older Adolescents: Prevalence, Risk Factors, and Implications Clinical. Clinical Psychology Review 18 (7): 765–794. DOI: http://dx.doi.org/10.1016/S0272-7358(98)00010-5.Search in Google Scholar

Lohmar, Brigitte, Eckhardt Thomas (2013), The Education System in the Federal Republic of Germany 2011/2012: A Description of the Responsibilities, Structures and Developments in Education Policy for the Exchange of Information in Europe: Sekretariat der Ständigen Konferenz der Kultusminister der Länder in der Deutschland Bundesrepublik .Search in Google Scholar

Lundborg, Petter, Nilsson Anton, Rooth Dan-Olof (2014), Adolescent Health and Adult Labor Market Outcomes. Journal of Health Economics 37: 25 – 40. DOI: http://dx.doi.org/10.1016/j.jhealeco.2014.05.003.Search in Google Scholar

Marcus, Jan, Zambre Vaishali (2016), The Effect of Increasing Education Efficiency on University Enrollment: Evidence from Administrative Data and an Unusual Schooling Reform in Germany.10.2139/ssrn.2866330Search in Google Scholar

Merikangas, Kathleen Ries, Jian-Ping He, Burstein Marcy, Sonja A. Swanson, Avenevoli Shelli, Cui Lihong, Benjet Corina, Georgiades Katholiki, Swendsen Joel (2010), Lifetime Prevalence of Mental Disorders in Adolescents: U.S. Results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry 49 (10): 980–989. DOI: http://dx.doi.org/10.1016/j.jaac.2010.05.017.Search in Google Scholar

Merikangas, Kathleen Ries, Nakamura Erin F., Ronald C. Kessler (2009), Epidemiology of Mental Disorders in Children and Adolescents. Dialogues in Clinical Neuroscience 11 (1): 7–20.10.31887/DCNS.2009.11.1/krmerikangasSearch in Google Scholar

Meyer, Tobias, Thomsen Stephan L. (2015), Schneller fertig, aber weniger Freizeit? Eine Evaluation der Wirkungen der verkürzten Gymnasialschulzeit auf die außerschulischen Aktivitäten der Schülerinnen und Schüler. Schmollers Jahrbuch 135 (3): 249–277. DOI: http://dx.doi.org/10.3790/schm.135.3.249.Search in Google Scholar

Meyer, Tobias, Thomsen Stephan L. (2016), How Important Is Secondary School Duration for Postsecondary Education Decisions? Evidence from a Natural Experiment. Journal of Human Capital 10 (1): 67–108. DOI: http://dx.doi.org/10.1086/684017.Search in Google Scholar

Meyer, Tobias, Thomsen Stephan L. (2017), The Role of High-school Duration for University Students’ Motivation, Abilities and Achievements. Education Economics 4 (2): 1–22. DOI: http://dx.doi.org/10.1080/09645292.2017.1351525.Search in Google Scholar

Meyer, Tobias, Thomsen Stephan L., Schneider Heidrun (2016), New Evidence on the Effects of the Shortened School Duration in the German States: An Evaluation of Post-School Education Decisions. IZA Discussion Paper (9507).10.2139/ssrn.2696305Search in Google Scholar

Milde-Busch, Astrid, A. Borggräfe Blaschek, I., von Kries R., Straube A., Heinen F. (2010), Besteht ein Zusammenhang zwischen der verkürzten Gymnasialzeit und Kopfschmerzen und gesundheitlichen Belastungen bei Schülern im Jugendalter? Klinische Pädiatrie 222 (04): 255–260. DOI: http://dx.doi.org/10.1055/s-0030-1252012.Search in Google Scholar

Ministerium für Bildung Kultur und Wissenschaft, Saarland (2000), Das achtjährige Gymnasium im Saarland Kürzere Schulzeit - bessere Chancen}. www.saarland.de/dokumente/thema_bildung/brosch_g8.PDF.Search in Google Scholar

Morin, Louis-Philippe (2015), Do Men and Women Respond Differently to Competition? Evidence from a Major Education Reform. Journal of Labor Economics 33 (2): 443–491. DOI: http://dx.doi.org/10.1086/678519.Search in Google Scholar

Nolen-Hoeksema, S., Girgus J. S. (1994), The Emergence of Gender Differences in Depression During Adolescence. Psychological Bulletin 115 (3): 424–443. DOI: http://dx.doi.org/10.1037/0033-2909.115.3.424.Search in Google Scholar

OECD (2000), Education at a Glance 2000: OECD Publishing. DOI: http://dx.doi.org/10.1787/eag-2000-en.Search in Google Scholar

OECD (2013), Education at a Glance 2013: OECD Publishing. DOI: http://dx.doi.org/10.1787/eag-2013-en.Search in Google Scholar

Patel, Vikram, Flisher Alan J., Hetrick Sarah, McGorry Patrick (2007), Mental Health of Young People: A Global Public-health Challenge. The Lancet 369 (9569): 1302–1313. DOI: http://dx.doi.org/10.1016/S0140-6736(07)60368-7.Search in Google Scholar

Quis, Johanna Sophie (2015). Does Higher Learning Intensity Affect Student Well-being? Evidence from the National Educational Panel Study. http://hdl.handle.net/10419/106468.Search in Google Scholar

Reivich, Karen, Gillham Jane, Chaplin Tara, Seligman Martin (2013), From Helplessness to Optimism: The Role of Resilience in Treating and Preventing Depression in Youth. 201–214 in: Sam Goldstein, Robert B. Brooks (eds.), Handbook of Resilience in Children: Springer US. DOI: http://dx.doi.org/10.1007/978-1-4614-3661-4_12.Search in Google Scholar

Rushton, Jerry L., Michelle Forcier, Robin M. Schectman (2002), Epidemiology of Depressive Symptoms in the National Longitudinal Study of Adolescent Health. Journal of the American Academy of Child and Psychiatry Adolescent 41 (2): 199–205. DOI: http://dx.doi.org/10.1097/00004583-200202000-00014.Search in Google Scholar

Schavan, Anette, Ahnen Doris (2001), Abitur nach 12 Schuljahren? Pro und Contra. Forschung und Lehre 8 (9): 472–473.Search in Google Scholar

Schönberger, Benno, Christian Aßmann (2014), Weighting the Additional Study in Baden-Wuerttemberg of the National Study Educational Panel. https://www.neps-data.de/Portals/0/NEPS/Datenzentrum/Forschungsdaten/BW/2-0-0/BW_ 2-0-0_Weighting.pdf.Search in Google Scholar

Seiffge-Krenke, Inge (2000), Causal Links between Stressful Events, Coping Style, and Adolescent Symptomatology. Journal of Adolescence 23 (6): 675 – 691. DOI: http://dx.doi.org/10.1006/jado.2000.0352.Search in Google Scholar

Seiffge-Krenke, Inge (2007), Depression bei Kindern und Jugendlichen: Prävalenz, Diagnostik, ätiologische Faktoren, Geschlechtsunterschiede, therapeutische Ansätze. Praxis der Kinderpsychologie und Kinderpsychiatrie 56: 185–205. DOI: http://dx.doi.org/10.13109/prkk.2007.56.3.185.Search in Google Scholar

Skirbekk, Vergard (2006), Does School Duration Affect Student Performance? Findings from Canton-based Variation in Length Swiss Educational. Schweizerische Zeitschrift für Volkswirtschaft und Statistik 142 (I): 115–145.Search in Google Scholar

Smith, James Patrick, Gillian C. Smith (2010), Long-term Economic Costs of Psychological Problems During Childhood. Social Science & Medicine 71 (1): 110–115. http://www.sciencedirect.com/science/article/pii/S0277953610002686, DOI: http://dx.doi.org/10.1016/j.socscimed.2010.02.046.Search in Google Scholar

Bundesamt Statistisches (2013), Fachserie 11/Reihe 1, Bildung und Kultur. Allgemeinbildende Schulen., Wiesbaden. www.destatis.de/DE/Publikationen/Thematisch/BildungForschungKultur/Schulen/AllgemeinbildendeSchulen2110100137004.pdf?__blob=publicationFile.Search in Google Scholar

Sussebach, Henning (2011), Liebe Marie. Die Zeit 22: 15–18.Search in Google Scholar

Thapar, Anita, Stephan Collishaw, Daniel S. Pine, Ajay K. Thapar (2012), Depression in Adolescence. The Lancet 379 (9820): 1056–1067. DOI: http://dx.doi.org/10.1016/S0140-6736(11)60871-4.Search in Google Scholar

Thiel, Hendrik, Thomsen Stephan, Büttner Bettina (2014), Variation of Learning Intensity in Late Adolescence and the Effect on Personality Traits. Journal of the Royal Statistical Society: Series A (Statistics in Society). 177 (4): 861–892. DOI: http://dx.doi.org/10.1111/rssa.12079.Search in Google Scholar

Thomsen, Stephan (2015), The Impacts of Shortening Secondary School Duration. IZA World of Labor. 166. DOI: http://dx.doi.org/10.15185/izawol.166.Search in Google Scholar

Wagner, Wolfgang, Kramer Jochen, Trautwein Ulrich, Lüdtke Oliver, Nagy Gabriel, Jonkmann Kathrin, Maaz Kai, Meixner Sonja, Schilling Julia (2011), Upper Secondary Education in Academic School Tracks and the Transition from School to Postsecondary Education and the Job Market. Zeitschrift für Erziehungswissenschaft 14 (2): 233–249. DOI: http://dx.doi.org/10.1007/s11618-011-0196-1.Search in Google Scholar

Westermaier, Franz (2016), The Impact of Lengthening the School Day on Substance Abuse and Crime: Evidence from a German High School Reform.10.2139/ssrn.2867922Search in Google Scholar

Wiater, Werner (1996), Zwölf Jahre bis zum Abitur? Positionen im Streit um die Verkürzung der gymnasialen Schulzeit. 121–139 in: Melzer Wolfgang, Sandfuchs Uwe (eds.), Schulreform in der Mitte der 90er Jahre, 8. VS Verlag für Sozialwissenschaften, Reihe Schule und Gesellschaft. DOI: http://dx.doi.org/10.1007/978-3-322-95751-1_8.Search in Google Scholar

Wiater, Werner (1997), Abitur nach 12 oder 13 Jahren? Die Diskussion um die Schulzeitverkürzung und ihre Folgen. Praxis Schule 8 (3): 5–10.Search in Google Scholar

Zydatiß, Wolfgang (1999), Förderung über Akzeleration: Gymnasiale Express-und Regelklassen im Vergleich. Schulverwaltung MO 7: 255–260.Search in Google Scholar


Correction note

This article is part of the special issue “Empirical Health Economics” published in the Journal of Economics and Statistics. Access to further articles of this special issue can be obtained at https://www.degruyter.com/view/j/jbnst.



Code and Datasets

The author(s) published code and data associated with this article in the ZBW Journal Data Archive, a storage platform for datasets. See: https://doi.org/10.15456/jbnst.2018302.100223.


Appendix

Table 6:

Description of variables.

VariableDescription
StressStandardized index of perceived stress constructed from 15 items,
mean 0 and standard deviation 1 (for contained items see Table 7)
Mental health problemsStandardized index of internalizing mental health problems
constructed from 15 items, mean 0 and standard deviation 1
(for contained items see Table 8)
Reform (G8)Dummy indicating whether student was affected by the reform
FemaleDummy indicating whether student is female
Age (years)Student age in years
Age - medianStudent age in months minus median age of respondents in
own cohort
RepeatedDummy indicating whether student ever repeated a grade
Migration backgroundDummy indicating whether student has a migration background,
i. e. at least one parent was not born in Germany
Books at homeNumber of Books at home, categories: 0-100, 101-200, 201-500, more
than 500 books
SportsDummy indicating whether student does sports on more than one day per week
Table 7:

Perceived stress.

How much do you agree with the following statements?
1I am tense when I get home from school.
2Sometimes I have trouble falling asleep because problems from school are on my mind.
3It happens that I react irritably when others start talking to me about school.
4I feel that school is overwhelming me.
5Even during my free time I think about troubles at school.
6I consider the requirements at school in general as stressful.
7After school I am often exhausted.
8Thinking of school makes me feel uncomfortable.
9Pressure at school is too high.
10School is eating me up.
11It is hard for me to conciliate school with other obligations.
12School often makes me feel tired and exhausted.
13It is easy for me to recover from school during my free time. (reversed)
14I can relax well during my free time. (reversed)
15Apart from school, I do not have time for anything else.
Response format: 1 = not at all true; 2 = hardly true; 3 = moderately true; 4 = exactly true
  1. Notes: NEPS BW D_3-0-0 wave 2011/12. Translation by NEPS.

Table 8:

Symptoms of internalizing mental health problems.

How often have you had the following problems in the last 6 weeks?
1Nervousness, inner anxiety
2Headaches
3Strong heart palpitations
4Fear that it’s all getting too much
5Difficulty concentrating
6Sleep disturbances
7Bad dreams
8Excessive sweating
9Vomiting
10Easily irritable
11Feelings of dizziness
12Tiredness, fatigue
13Incapable of relaxing
14Severe forgetfulness, distraction
15Angry at everything
16Feeling of being worthless
17Fear of going to school
18Shakiness, weakness
19Nausea
20Loss of appetite
21Backache
22Sadness
23Feeling that excessive demands are being made of me
24Eating binges
25Feeling of inner emptiness
26Stomach ache
Response format: 1 = never; 2 = 1-2 times; 3 = 3-6 times; 4 = more than 6 times
  1. Notes: NEPS BW D_3-0-0 wave 2011/12. Translation by NEPS.

Table 9:

Gender differences in (non-standardized) dependent variables.

MeanEquality of means
MaleFemaleDifferencet-stat
Pooled
Stress (std)–0.2520.188–0.441–10.73***
Mental health (std)–0.3370.252–0.589–14.62***
Observations98613202306
Control Group
Stress (std)–0.3510.003–0.354–6.2***
Mental health (std)–0.3380.178–0.516–9.03***
Observations4946531147
MeanEquality of means
MaleFemaleDifferencet-stat
Treatment Group
Stress (std)–0.1530.370–0.524–8.91***
Mental health (std)–0.3360.324–0.660–11.66***
Observations4926671159
  1. Notes: NEPS BW D_3-0-0 wave 2011/12.

Table 10:

Regressions on stress and internalizing mental health problems.

StressMental health problems
PooledMaleFemalePooledMaleFemale
Reform (G8)0.314***0.214***0.392***0.111**0.0100.186***
(0.049)(0.065)(0.063)(0.048)(0.061)(0.063)
Age - median0.015***0.026***0.0060.0030.0040.001
(0.005)(0.007)(0.006)(0.005)(0.007)(0.006)
Repeated a grade0.167-0.0540.3650.334***0.1130.537***
(0.127)(0.168)(0.220)(0.123)(0.150)(0.172)
Female0.424***0.580***
(0.045)(0.044)
Sports-0.234***-0.199**-0.257***-0.128**-0.161*-0.110
(0.051)(0.087)(0.057)(0.049)(0.082)(0.068)
Migration backgr.0.209***0.242**0.191**0.241***0.247***0.241***
(0.057)(0.092)(0.080)(0.054)(0.090)(0.079)
Books at home:
0–100 books0.268***0.294***0.232***0.123*0.177**0.068
(0.055)(0.079)(0.085)(0.064)(0.085)(0.090)
101–200 books0.0730.0950.055-0.067-0.034-0.101
(0.053)(0.072)(0.067)(0.062)(0.072)(0.083)
201–500 books0.0090.057-0.026-0.0370.045-0.100
(0.046)(0.056)(0.072)(0.052)(0.059)(0.073)
Constant-0.345***-0.349***0.074-0.360***-0.311***0.197**
(0.059)(0.083)(0.075)(0.065)(0.091)(0.074)
Observations2306986132023069861320
R20.1140.06950.07880.1140.03170.0384
  1. Notes: NEPS BW D_3-0-0 wave 2011/12. OLS regressions. The dependent variables are standardized to a mean of zero and a standard deviation of one. Age - median = age in months - median(age of students in own cohort). Books at home: reference category: ’more than 500’. A two-sided test for equality of the reform effect for the male and female subsamples yields a p-value of 0.05 for stress and of 0.04 for internalizing mental health problems. Equality of the reform effect of males vs. females can therefore be rejected at the 5%-level. p< 0.1, p< 0.05, p< 0.01. Standard errors, clustered at school level, in parentheses.

Table 11:

Effect heterogeneity.

StressMental health problems
PooledMaleFemalePooledMaleFemale
Age higher than median
Reform (G8)0.278***0.165**0.359***0.056-0.0360.121
(0.054)(0.074)(0.075)(0.055)(0.073)(0.076)
Interaction0.0750.0960.0720.1130.0900.141
(0.062)(0.095)(0.093)(0.068)(0.101)(0.093)
Wald test p-valuea0.000***0.003***0.000***0.009***0.5230.002***
Math competence above medianb
Reform (G8)0.373***0.245**0.441***0.151**-0.0540.248***
(0.050)(0.101)(0.055)(0.067)(0.110)(0.071)
Interaction-0.118-0.027-0.139-0.0750.114-0.160
(0.075)(0.117)(0.111)(0.085)(0.126)(0.117)
Wald test p-valuea0.001***0.006***0.009***0.2250.3810.397
More than 200 books at home (higher SES)
Reform (G8)0.265***0.169*0.352***0.072-0.0670.180*
(0.064)(0.092)(0.083)(0.079)(0.089)(0.105)
Interaction0.0750.0700.0610.0610.1210.008
(0.076)(0.118)(0.099)(0.091)(0.118)(0.116)
Wald test p-valuea0.000***0.006***0.000***0.022**0.5070.009***
Students with migration background
Reform (G8)0.341***0.251***0.415***0.137***0.0480.208***
(0.057)(0.079)(0.070)(0.048)(0.063)(0.063)
Interaction-0.127-0.185-0.103-0.124-0.188-0.100
(0.102)(0.162)(0.143)(0.095)(0.141)(0.135)
Wald test p-valuea0.016**0.6070.019**0.8900.2970.424
Observations2306986132023069861320
  1. Notes: NEPS BW D_3-0-0 wave 2011/12. OLS regressions. The dependent variables are standardized to a mean of zero and a standard deviation of one. All models contain a constant and control additionally for age deviation from cohort median, previous grade repetition, sports participation, migration background, books at home, gender (only pooled models), and a dummy indicating whether the student’s mathematical competence is above the median in her cohort (only mathematical competence part). The interaction term displays the interaction of the reform with being older than the median student, with above median mathematical competence, with having more than 200 books at home or with having a migration background. aTest of the hypothesis H0 Reform (G8) + Interaction = 0. bDue to missing data, 3 observations are missing in the mathematical competence part. p< 0.1, p< 0.05, p< 0.01. Standard errors, clustered at school level, in parentheses.

Table 12:

Robustness checks.

StressMental health problems
PooledMaleFemalePooledMaleFemale
Panel A: Robustness checks using analysis sample
Control for relative age over both cohorts
Reform (G8)0.526***0.573***0.474***0.152**0.0840.190*
(0.076)(0.115)(0.093)(0.073)(0.098)(0.095)
Omit sports participation from controls
Reform (G8)0.317***0.218***0.395***0.113**0.0130.187***
(0.049)(0.064)(0.065)(0.048)(0.060)(0.063)
No controls
Reform (G8)0.298***0.198***0.368***0.088*0.0020.146**
(0.052)(0.061)(0.065)(0.047)(0.056)(0.061)
Separate standardization by gender
Reform (G8)0.319***0.226***0.394***0.110**0.0110.183***
(0.050)(0.069)(0.063)(0.050)(0.070)(0.061)
Using weights
Reform (G8)0.272***0.190**0.339***0.088*–0.0030.154**
(0.053)(0.074)(0.068)(0.052)(0.066)(0.072)
Observations2306986132023069861320
Panel B: Robustness checks with additional sample restrictions
Exclude grade repeaters
Reform (G8)0.316***0.225***0.388***0.114**0.0060.198***
(0.051)(0.068)(0.065)(0.049)(0.063)(0.062)
Observations2192932126021929321260
Exclude old G8
Reform (G8)0.311***0.207***0.393***0.106**0.0020.183***
(0.049)(0.063)(0.062)(0.048)(0.058)(0.063)
Observations2282978130422829781304
Panel C: Using wave 2010/11 as control and wave 2012/13 as treatment
Reform (G8)0.436***0.403***0.464***0.282***0.254***0.306***
(0.049)(0.050)(0.067)(0.045)(0.043)(0.064)
Observations241910551364241910551364
  1. Notes: NEPS BW D_3-0-0, wave 2011/12 (panel A and B) and waves 2010/11 and 2012/13 (Panel C). OLS regressions. The dependent variables are standardized to a mean of zero and a standard deviation of one. All models contain a constant and control additionally for age deviation from cohort median, previous grade repetition, sports participation, migration background, books at home and gender (only pooled models). p< 0.1, p< 0.05, p< 0.01. Standard errors, clustered at school level, in parentheses.

Table 13:

Different calculations for dependent variables.

StressMental health problems
PooledMaleFemalePooledMaleFemale
Separate standardization by gendera
Reform (G8)0.319***0.226***0.394***0.110**0.0110.183***
(0.050)(0.069)(0.063)(0.050)(0.070)(0.061)
Observations2306986132023069861320
Allow for no missing valuesb
Reform (G8)0.314***0.198***0.402***0.122**-0.0060.213***
(0.053)(0.068)(0.066)(0.050)(0.064)(0.065)
Observations2154918123621549181236
No restriction for missingsc
Reform (G8)0.316***0.217***0.393***0.111**0.0130.182***
(0.049)(0.065)(0.062)(0.047)(0.061)(0.062)
Observations2316988132823169881328
Count all occurrences of largest and second largest valued
Reform (G8)0.302***0.199***0.383***0.115**0.0150.188***
(0.050)(0.067)(0.064)(0.046)(0.059)(0.061)
Observations2322992133023229921330
Count all occurrences of largest valuee
Reform (G8)0.258***0.0960.377***0.094*-0.0290.184***
(0.053)(0.066)(0.062)(0.047)(0.060)(0.062)
Observations2322992133023229921330
Using factor loadsf
Reform (G8)0.318***0.216***0.397***0.097**-0.0490.205***
(0.052)(0.069)(0.064)(0.047)(0.058)(0.066)
Observations2240958128222279471280
  1. Notes: NEPS BW D_3-0-0 wave 2011/12. OLS regressions. The dependent variables are standardized to a mean of zero and a standard deviation of one. All models contain a constant and control additionally for age deviation from cohort median, previous grade repetition, sports participation, migration background, books at home, gender (only pooled models). a Since there are severe differences between male and female students in the outcomes, in addition to the normal standardization over the entire sample, the outcomes were standardized separately for males and females. bIn this specification, indexes for stress and mental health are only calculated if there is no missing value in any of the respective items. c In this specification, indexes for stress and mental health are calculated as long as there is at least one nonmissing value in among the respective items. d In this specification all occurrences of the highest and second highest answer category are counted. The number of occurrences is then standardized, in order to allow comparison of the results to the other specifications e This specification is similar to the previous specification, except that it only counts occurrences of the highest possible answer category f In this specification, before the standardization takes place, the items in each score are weighted by their predicted rotated factor loadings, which result from factor analysis. p< 0.1, p< 0.05, p< 0.01. Standard errors, clustered at school level, in parentheses.

Table 14:

Differences in variables between G9-students in wave 2010/11 and 2011/12.

MeanEquality of means
Wave 2010/11Wave 2011/12Differencet-stat
Stress score1.9292.015-0.0859-3.851***
Mental health problem score1.8001.869-0.0693-3.227**
Female0.5560.568-0.0122-0.596
Age (years)18.4718.400.07693.272**
Repeated a grade0.1040.08530.01901.573
Sports0.7900.7780.01210.711
Migration backgr.0.2350.2220.01380.800
0-100 books at home %0.1890.1790.01020.636
101-200 books at home %0.1630.1620.0007020.0462
201-500 books at home %0.3160.3110.005150.270
500 + books at home %0.3280.346-0.0176-0.906
Observations11981160
  1. Notes: NEPS BW D_3-0-0 wave 2010/11 and 2011/12.

Table 15:

Differences in variables between G8-students in wave 2011/12 and 2012/13.

MeanEquality of means
Wave 2011/12Wave 2012/13Differencet-stat
Stress score2.1932.201-0.008-0.317
Mental health problem score1.9201.972-0.052-2.259*
Female0.5770.5680.009260.453
Age (years)17.3317.45-0.118-5.499***
Repeated a grade0.0150.110-0.095-9.732***
Sports0.7630.7360.02621.465
Migration backgr.0.2090.240-0.031-1.775
0-100 books at home %0.1910.1790.0120.740
101-200 books at home %0.1720.1510.0211.393
201-500 books at home %0.3070.311-0.004-0.199
500 + books at home %0.3280.358-0.030-1.534
Observations12061208
  1. Notes: NEPS BW D_3-0-0 wave 2011/12 and 2012/13.

Table 16:

Differences in variables between G9-students in wave 2010/11 and G8-students in wave 2012/13.

MeanEquality of means
Wave 2010/11Wave 2012/13Differencet-stat
Stress score1.9292.201-0.272-11.84***
Mental health problem score1.8001.972-0.172-7.875***
Female0.5560.568-0.0121-0.594
MeanEquality of means
Wave 2010/11Wave 2012/13Differencet-stat
Age (years)18.4717.451.02139.30***
Repeated a grade0.1040.110-0.00535-0.422
Sports0.7900.7360.05333.057**
Migration backgr.0.2350.240-0.00440-0.252
0-100 books at home %0.1890.1790.01010.632
101-200 books at home %0.1630.1510.01230.821
201-500 books at home %0.3160.3110.005140.270
500 + books at home %0.3280.358-0.0299-1.537
Observations11981176
  1. Notes: NEPS BW D_3-0-0 wave 2010/11 and 2012/13.

Received: 2016-10-25
Revised: 2017-10-21
Accepted: 2018-01-05
Published Online: 2018-03-07
Published in Print: 2018-09-25

© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston

Downloaded on 23.3.2023 from https://www.degruyter.com/document/doi/10.1515/jbnst-2018-0004/html
Scroll Up Arrow