ADHD-Related School Compositional Effects: An Exploration

Abstract

Background/ Context

Children with attention-deficit/hyperactivity disorder (ADHD) provide a test case through which to investigate psychosocial school compositional effects. Characterized by developmentally atypical levels of inattention, activity, and impulsivity, the condition often manifests itself, and is identified, in school settings and is associated with deficits in academic and social functioning. Research on school practices related to children with ADHD and regional variation in diagnosis and psychostimulant treatment rates supported the expectation that such compositional effects would be observed.

Purpose/Objective/Research Question/Focus of Study

This study examines variation in ADHD compositional effects as a function of key school factors derived from school effects research and the education production function literature, including student body and teacher characteristics, structural features, and specific school process and practices. It also tested for the presence of ADHD compositional effects on three key student-level outcomes: reading achievement, mathematics achievement, and teacher-reported levels of externalizing behavior. It was hypothesized that there would be negative effects on all three outcomes, such that children in schools with higher proportions of children with ADHD would show lower achievement in reading and math, and higher levels of externalizing symptoms (that is, aggressive and disruptive behaviors).

Population/Participants/Subjects

Approximately 14,000 students in more 1,000 schools participating in the Early Childhood Longitudinal Study–Kindergarten Cohort (ECLS-K) constituted the analytic samples. The ECLS-K collected a rich set of child background, mental health, and behavioral characteristics, as well as school achievement indicators. School administrators reported on school characteristics and practices.

Research Design

Because the ECLS-K follows groups of students nested within schools, it allowed for particularly robust tests for the presence and correlates of within-school aggregations of children with ADHD using student- and school-level fixed-effects models. In addition, several steps were taken to address the potential conflation of the ADHD compositional effect with ECLS-K sampling dynamics and methods.

Findings

Results generated from student-level fixed-effects regression models indicate that ADHD clustering effects predict lower reading achievement scores in schools as compared with schools without this characteristic, but comparable levels of mathematics achievement and externalizing symptoms. These ADHD-related school effects were larger in schools serving minority students, schools with higher retention rates, and schools with a strong emphasis on order. For both children and schools, the patterning of ADHD-related effects differed by region.

Conclusions

Findings are discussed in light of research criticizing the aggregation of children with disruptive behavioral characteristics and/or low academic performance within classrooms and schools, as well as larger school resegregation trends.>

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References

Agostin

T. M.

, & Bain

S. K.

(1997). Predicting early school success with developmental and social skills screeners. Psychology in the Schools, 34, 219–228.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

Angold

, Costello

E. J.

, Farmer

E. M. Z.

, Burns

B. J.

, & Erkanli

(1999). Impaired but undiagnosed. Journal of the American Academy of Child & Adolescent Psychiatry, 38, 129–137.

Barkley

R. A.

, Fischer

, Edelbrock

C. S.

, & Smallish

(1990). The adolescent outcome of hyperactive children diagnosed by research criteria: I. An 8-year prospective follow-up study. Journal of the American Academy of Child & Adolescent Psychiatry, 29, 546–557.

Bryk

A. S.

, Lee

V. E.

, & Holland

P. B.

(1993). Catholic schools and the common good. Cambridge, MA: Harvard University Press.

Bryk

A. S.

, & Thum

Y. M.

(1989). The effects of high school organization on dropping out: An exploratory study. American Education Research Journal, 26, 353–383.

Bussing

, Gary

F. A.

, Leon

C. E.

, Wilson Garvan

, & Reid

(2002). General classroom teachers’ information and perceptions of attention deficit hyperactivity disorder. Behavioral Disorders, 27, 327–339.

Cox

, Motheral

, Henderson

, & Mager

(2003) Geographic variation in the prevalence of stimulant medication use among children 5 to 14 years old: Results from a commercially insured sample. Journal of Pediatrics, 111, 237–243.

Currie

, & Stabile

(2006). Child mental health and human capital accumulation: The case of ADHD. Journal of Health Economics, 25, 1094–1118.

10.

Dodge

K. A.

, Dishion

T. J.

, & Lansford

J. E.

(2006). Deviant peer influences in intervention and public policy for youth. Social Policy Report of the Society for Research in Child Development, 20(1), 3–19.

11.

DuPaul

, & Stoner

(2004). ADHD in the schools: Assessment and intervention strategies (2nd ed.). New York: Guilford Press.

12.

Eccles

, & Roeser

(1999). School and community influences on human development. In Bornstein

& Lamb

(Eds.), Developmental psychology: An advanced textbook (pp. 503–554). Mahwah, NJ: Erlbaum.

13.

Fare

, Grosskopf

, & Weber

W. L.

(1989). Measuring school district performance. Public Finance Quarterly, 17, 409–428.

14.

Fine

(2001). New laws leave Ritalin decisions to parents and doctors. Education Week, 20 (43), 31.

15.

Fryer

R. G.

, & Levitt

S. D.

(2004). Understanding the Black-White test score gap in the first two years of school. Review of Economics and Statistics, 86, 447–464.

16.

Forness

S. M.

, & Kavale

K. A.

(2002). Impact of ADHD on School Systems. In Jensen

P. S.

& Cooper

J. R.

(Eds.), Attention-deficit hyperactivity disorder: State of the science, best practices (pp. 24-1–24-21). Kingston, NJ: Civic Research Institute.

17.

Greene

W. T.

(1990). Econometric analysis. New York: Macmillan.

18.

Gresham

F. M.

, & Elliot

S. N.

(1990). Social skills rating system manual. Circle Pines, MN: American Guidance Service.

19.

Hansen

, Weiss

, & Last

C. G.

(1999). ADHD boys in young adulthood: Psychosocial adjustment. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 165–171.

20.

Heubert

J. P.

, & Hauser

R. M.

(Eds.). (1999). High stakes: Testing for tracking, promotion and graduation. Washington, DC: National Academy Press.

21.

Hinshaw

S. P.

(1992a). Academic underachievement, attention deficits, and aggression: Comorbidity and implications for intervention. Journal of Consulting and Clinical Psychology, 60, 893–903.

22.

Hinshaw

S. P.

(1992b). Externalizing behavior problems and academic underachievement in childhood and adolescence: Causal relationships and underlying mechanisms. Psychological Bulletin, 111, 127–155.

23.

Hinshaw

S. P.

(2002). Is ADHD an impairing condition in childhood and adolescence? In Jensen

P.S.

& Cooper

J. R.

(Eds.), Attention-deficit hyperactivity disorder: State of the science, best practices (pp. 5-1–5-21). Kingston, NJ: Civic Research Institute.

24.

Hinshaw

S. P.

, Klein

, & Abikoff

(2007). Childhood attention-deficit hyperactivity disorder: Nonpharmacologic treatments and their combination with medication. In Nathan

P. E.

& Gorman

(Eds.), A guide to treatments that work (3rd ed., pp. 3–27). New York: Oxford University Press.

25.

Hunter

(2003). School psychology: A public health framework: III. Managing disruptive behavior in schools: The value of a public health and evidence-based perspective. Journal of School Psychology, 41, 39–59.

26.

Jensen

P. S.

, & Cooper

J. R.

(Eds.). (2002). Attention-deficit hyperactivity disorder: State of science, best practices. New York: Civic Research Institute.

27.

Jensen

P. S.

, Kettle

, Roper

M. T.

, Sloan

M. T.

, Dulcan

M. K.

, Hoven

. (1999). Are stimulants overprescribed? Treatment of ADHD in four U.S. communities. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 797–804.

28.

Lee

V. E.

, & Burkam

D. T.

(2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Washington, DC: Economic Policy Institute.

29.

Maughan

(1994) School influences. In Rutter

& Hay

D. F.

(Eds.), Development through life: A handbook for clinicians (pp. 134–158). Oxford, England: Blackwell.

30.

Monk

(1989). The education production function: Its evolving role in policy analysis Educational Evaluation and Policy Analysis, 11, 31–45.

31.

Mortimore

(1995). The positive effects of schooling. In Rutter

(Ed.), Psychosocial disturbance in young people: Challenges for prevention (pp. 333–363). New York: Cambridge University Press.

32.

MTA Cooperative Group. (1999). A 14-month randomized clinical trial of treatment strategies for attention-deficit/hyperactivity disorder. Archives of General Psychiatry, 56, 1073–1086.

33.

National Center for Education Statistics. (2003). User's manual for the ECLS-K third grade restricted-use data file and electronic code book. Washington, DC: United States Department of Education.

34.

Needham

B. L.

, Crosnoe

R. M.

, & Muller

(2004). Academic failure in secondary school: The inter-related role of health problems and educational context. Social Problems, 51, 569–586.

35.

Orfield

(2001). Schools more separate: Consequences of a decade of resegregation. Cambridge, MA: Harvard Civil Rights Project.

36.

Raudenbush

S. W.

, & Bryk

A. S.

(2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks, CA: Sage.

37.

Redden

S. C.

, Forness

S. R.

, Ramey

C. T.

, Ramey

S. L.

, Brezausek

C. M.

, & Kavale

K. A.

(2003). Head Start children with a putative diagnosis of ADHD: A four-year follow-up of special education placement. Education & Treatment of Children, 26, 208–223.

38.

Peterson

(2004). Analyzing panel data: Fixed- and random-effects models. In Hardy

& Bryman

(Eds.), Handbook of data analysis (pp. 341–346). Thousand Oaks, CA: Sage.

39.

Rosenbaum

P. R.

, & Rubin

D. B.

(1984). Reducing bias in observational studies using sub-classification on the propensity score. Journal of the American Statistical Association, 79, 516–524.

40.

Rumberger

R. W.

(2003). The causes and consequences of student mobility. Journal of Negro Education, 72, 6–21.

41.

Rumberger

R. W.

, & Palardy

G. J.

(2005). Test scores, dropout rates, and transfer rates as alternative indicators of high school performance. American Educational Research Journal, 41, 3–42.

42.

Rutter

, & Maughan

(2002). School effectiveness findings, 1979–2002. Journal of School Psychology, 40, 451–475.

43.

Rutter

, Maughan

, Mortimore

, & Ouston

(1979). Fifteen thousand hours: Secondary schools and their effects on children. London: Open Books.

44.

St. Sauver

J. L.

, Barbaresi

W. J.

, Katusic

S. K.

, Colligan

R. C.

, Weaver

A. L.

, & Jacobsen

S. J.

(2004). Early life risk factors for attention-deficit/hyperactivity disorder: A population-based cohort study. Mayo Clinic Proceedings, 79, 1124–1131.

45.

Sax

, & Kautz

K. J.

(2003). Who first suggests the diagnosis of attention deficit/ hyperactivity disorder? Annals of Family Medicine, 1, 171–174.

46.

Schneider

, & Eisenberg

(2006). Who receives a diagnosis of attention-deficit/ hyper-activity disorder in the Unites States elementary school population? Pediatrics, 117, 601–609.

47.

Sebring

P. A.

, Allensworth

E. A.

, Bryk

A. S.

, Easton

J. Q.

, & Luppescu

(2006). The essential supports for student learning. Chicago: Consortium on Chicago School Research.

48.

Snider

V. E.

, Frankenberger

, & Aspensen

M. R.

(2000). The relationship between learning disabilities and attention deficit hyperactivity disorder: A national survey. Developmental Disabilities Bulletin, 28 (1), 18–38.