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The MTA at 8 Years: Prospective Follow-Up of Children Treated for Combined Type ADHD in a Multisite Study



To determine any long-term effects, 6 and 8 years after childhood enrollment, of the randomly assigned 14-month treatments in the Multimodal Treatment Study of Children with ADHD (MTA; N=436); to test whether Attention-Deficit/Hyperactivity Disorder (ADHD) symptom trajectory through 3-years predicts outcome in subsequent years; to examine functioning level of the MTA adolescents relative to their non-ADHD peers (Local Normative Comparison Group or LNCG; N=261).


Mixed effects regression models with planned contrasts at 6- and 8-years tested a wide range of symptom and impairment variables assessed by parent, teacher, and youth report.


In nearly every analysis, the originally randomized treatment groups did not differ significantly on repeated measures or newly-analyzed variables (e.g., grades earned in school, arrests, psychiatric hospitalizations, or other clinically relevant outcomes). Medication use decreased by 62% after the 14-month controlled trial, but adjusting for this did not change the results. ADHD symptom trajectory in the first 3 years predicted 55% of the outcomes. MTA participants fared worse than LNCG on 91% of the variables tested.


Type or intensity of 14 months of treatment for ADHD in childhood (at age 7.0–9.9 years old) does not predict functioning six-to-eight years later. Rather, early ADHD symptom trajectory regardless of treatment type is prognostic. This finding implies that children with behavioral and sociodemographic advantage, with the best response to any treatment, will have the best longterm prognosis. As a group, however, despite initial symptom improvement during treatment that is largely maintained post-treatment, children with Combined-Type ADHD exhibit significant impairment in adolescence. Innovative treatment approaches targeting specific areas of adolescent impairment are needed.

Keywords: ADHD, adolescence, clinical trial, longitudinal

The Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (ADHD), abbreviated as MTA, compared four distinct treatment strategies during childhood for 579 children diagnosed with DSM-IV ADHD, Combined type. Children were randomly assigned to 14 months of (a) systematic medication management (MedMgt), which was initial placebo-controlled titration, thrice-daily dosing, seven days per week, and monthly 30-minute clinic visits, (b) multicomponent behavior therapy (Beh), which included 27-session group parent training supplemented with eight individual parent sessions, an 8-week summer treatment program, 12 weeks of classroom administered behavior therapy with a half-time aide and 10 teacher consultation sessions, (c) their combination (Comb), or (d) usual community care (CC). This randomized, 6-site, controlled clinical trial, conducted in parallel at 6 performance sites, featured rigorous diagnostic criteria at study entry (when the children were in first through fourth grade) and compared the relative effectiveness of treatments of well established efficacy. Characterization of the MTA children's functioning and services use through adolescence, including their continued use of prescribed psychoactive medication, should provide key insights into the long-term course of ADHD and whether time-limited intensive treatment in childhood influences later outcome. This article reports psychiatric, academic, and social functioning outcomes attained by adolescence.

The initial MTA findings were based on comparisons of the three MTA-treated groups with one another and with the CC at the end of the 14-month treatment period. At that time, all groups showed improvement over baseline, but Comb and MedMgt participants showed significantly greater improvements in ADHD and Oppositional Defiant Disorder (ODD) symptoms than did Beh or CC participants. Although Comb and MedMgt did not differ significantly in any direct comparisons, Comb but not MedMgt had significantly better outcomes than Beh and CC for internalizing symptoms, teacher-rated social skills, parent-child relations, and reading achievement. About half of the initial advantage of Comb and MegMgt had dissipated by the first follow-up evaluation, 10 months following the termination of treatment.

By the next follow up, three years after enrollment (22 months after the end of the randomly assigned treatment), there were no longer significant treatment group differences in ADHD/ODD symptoms or functioning. That is, although the improvements over baseline for children in all four groups were maintained, the relative advantage associated with the intensive 14-month medication management in the MedMgt and Comb groups had dissipated. Additional analyses failed to support the hypothesis that treatment-seeking biases accounted for these results. Also, through growth mixture modeling, we identified three subgroups (“latent classes”) of children with differing ADHD symptom trajectories between pre-treatment and the 36-month follow-up (see Fig. 1). “Class 1” (34% of the sample) showed a gradual improvement over time, with an increasing significant benefit from medication use at 36 months. In contrast, “Class 2” (52% of the sample) showed a larger initial improvement that was maintained over time, whereas “Class 3” (14% of the sample) returned to pre-treatment symptom levels following an initial positive response to treatment. The children in Class 2 began the study with relative sociodemographic and behavioral advantage compared to the children in Classes 1 and 3 (e.g., more married parents, higher IQ, lower behavior problem scores, better social functioning) and had originally been assigned disproportionately more to Comb or to MedMgt. A more detailed discussion of these and other findings from the MTA up to the 3-year follow-up may be found in Swanson and colleagues.,

Figure 1
Average ADHD Symptom Score Over Time by Latent Class. LNCG = Local Normative Comparison Group. Figure reproduced with Permission from Wolters Kluwer Health, August 14, 2008). Originally published in Swanson JM, Hinshaw SP, Arnold LE, et al. Secondary ...

The current study reports the next two follow-up assessments of the MTA sample, at 6 and 8 years after random assignment, when the sample ranged in age from 13–18 years. Our first aim was to determine the presence of any differential long-term effects of the randomized treatments on adolescent functioning. These analyses controlled for medication treatment during the follow-up period. Although continued merging of the treatment groups' average scores was highly likely given the trajectory of findings from the end of randomly assigned treatment through the 36-month findings, delayed “sleeper effects” were possible (i.e., an emergence of treatment group differences not previously observed). Importantly, we sought to characterize the functioning of the children along an expanded and developmentally informed continuum of variables. Our second aim was to determine whether 36-month latent class membership, reflecting differential ADHD symptom trajectories across the first 3 years, predicted adolescent outcome at 6 and 8 years. The third aim was to compare the level of functioning of the adolescents with ADHD with that of non-ADHD peers. Overall, we sought to provide insight into the long-term course of ADHD Combined Type following 14 months of intensive, high-quality treatment in childhood.



MTA participants were 579 children with DSM-IV ADHD-Combined Type. Each of six participating sites randomized 96 to 98 children to one of four treatment groups (MedMgt, Beh, Comb, CC). At baseline (pre-treatment), participants were 7.0 to 9.9 years of age (M = 8.5 yrs, S.D. = .8). The MTA recruitment strategy, procedures for diagnosing ADHD, treatment specifics, and sample demographics have been described elsewhere., ,

Participants were re-assessed at completion of the 14-month treatment phase, at 24- and 36-months, and again at 6 and 8 years post-randomization. Participation rates were 97%, 93%, 84%, 78%, and 75%, respectively. There was no significant difference in any baseline characteristic between participants and non-participants for the 36-month assessment. However, participants lost to the 8-year follow-up, compared to those retained, were more often male (87% vs. 78%), had younger mothers (M=25.9 yrs vs. 28.0 yrs at child's birth), had less educated parents (13.86 vs. 14.55 yrs of schooling for mothers, 13.51 vs. 14.35 yrs of schooling for fathers), had lower parent income (M=37.73 K vs. 43.24 K) and were more likely to have been on welfare (24% vs. 17%) at baseline, all p's < .05. The remaining socio-demographic/adversity variables (age, grade, ethnicity/race, parent marital status, stable residency, parent job loss, child health, birth weight) were not significantly different and may be seen in earlier reports by treatment group or by latent class. Furthermore, 8-year participants were not significantly different from non-participants on baseline measures of intellect and achievement, parent and teacher report of ADHD and ODD symptoms, parent reported aggression and conduct problems, or on randomized treatment group assignment (p's > .05). Mean ages at the 6-and 8-year assessments were 14.9, SD = 1.0, and 16.8, SD = 1.0., respectively.

A local normative comparison group (LNCG, N=289) was recruited at 24 months to reflect the local populations from which the MTA sample was drawn. LNCG children were randomly selected from the same schools and grades and in the same gender proportions as the MTA children. Children were not excluded due to ADHD (but see “Statistical Approach” section regarding exclusion of LNCG children with ADHD from main analyses comparing functioning between MTA and LNCG children). The assessment battery included the Diagnostic Interview Schedule for Children, 4th Edition (DISC-IV) and teacher-reported ratings of ADHD symptoms, which afforded examination of DSM-IV diagnoses and ADHD symptom severity. The LNCG had the same entry criteria as the MTA children except for ADHD diagnosis and age; they were matched to the MTA children's age at 24 months post-randomization. Thus, data for the LNCG are only available starting at the 24-month assessment. At that time, average age of the LNCG, Mage(SD)=10.4(1.08) yrs, did not differ from that of the MTA sample, t (df=811)=1.04, p=.36. Percent female was similar in the LNCG, 18.7% (n=54/289), and the MTA, 19.7% (n=114/579), X2(1) =.13, ns, samples. The percentage of retained LNCG participants by 6 and 8 years was 87% (252/289) and 90% (261/289), respectively. LNCG participants lost by the 8-year follow-up had less stable residency (29% vs. 69% owned their own home or were in the military at baseline), younger mothers (M=26.3 yrs vs. 29.0 yrs at child's birth), and higher reading achievement scores (M=110.3 vs 104.6) than those retained, but all other baseline variables were non-discriminating (p's > .05). Mean ages at the 6- and 8-year assessments were 14.5, SD = 1.2 and 16.6, SD = 1.2, respectively.


Outcome variables

Efforts were made to use the same child functioning variables analyzed in prior MTA reports and to expand outcomes into developmentally relevant domains. Measures included parent and teacher mean ratings of ADHD and ODD symptoms with the Swanson, Nolan, and Pelham Rating Scale (SNAP; adhd.net); parent and teacher mean ratings of aggression and conduct based on the DSM-IV symptoms of CD; severity of delinquent behavior coded on a 5-point ordinal scale using parent and youth report across several measures; parent report of number of contacts with police and arrests by 8-years [Services for Children and Adolescents-Parent Interview (SCAPI)]; parent-reported mean rating of overall functional impairment with the Columbia Impairment Rating Scale (CIS); self-reported mean rating of depression (Children's Depression Inventory; CDI) and anxiety symptoms (Multidimensional Anxiety Scale for Children; MASC); the Wechsler Individual Achievement Test (WIAT) reading and math standardized scores; teacher-rated academic performance relative to other students using the mean of the first 5 items (α = .91 at 8 years) of the Academic Competence subscale of the Social Skills Rating System (SSRS); grade point average (GPA) on a 4-point scale taken from the final report card closest in time to the 8-year assessment (coded with over 90% inter-rater agreement); parent-reported hours per week of special education (0=none, 1=up to one hour, 2=up to five hours, 3=more than five hours), counseling or therapy in school, or other school services such as help in the classroom to manage behavior or tutoring (SCAPI); post-treatment grade retention by 8-years (in lifetime for MTA vs. LNCG comparisons); parent- and teacher-rated total social skills mean rating from the SSRS; parent-reported psychiatric hospitalizations by 8-years (SCAPI); and parent- or youth-reported accidents or citations stemming from vehicular moving violations. (Driving accidents/citations were analyzed for participants who drove or were eligible to drive based on age.) The LNCG participants who were eligible by age were more likely to have a license, 116/203 = 57.14%, than the MTA participants, 152/376 = 40.43%, X2(1) = 14.82, p<.001).

Two teachers (English and Math) provided ratings, which were averaged for analysis. Psychiatric diagnoses were based on the DISC-IV, with ADHD diagnosis based on the same algorithm used to establish study entry (for details and exceptions, see MTA Cooperative Group). At the 8-year assessment, 55 MTA and 39 LNCG participants had turned 18 and were administered the Diagnostic Interview Schedule, Version IV (DIS-IV), the CIS worded for self-report, the Beck Depression Inventory (BDI), and the Beck Anxiety Inventory (BAI) instead of the parallel child measures. Results were not appreciably different when their data were excluded.

Medication usage

From the parent-reported SCAPI, prescription medication use was defined as the proportion of days that children received any medication for ADHD in the past year.

Statistical Approach

The main analytic approach was mixed-effects regression modeling with point-in-time contrasts. The mixed-effects regression is an extension of the ordinary linear regression (see Hedeker and Gibbons for a relevant overview, especially pp. 47–48). These analyses test whether groups differ as a function of time (i.e., randomly assigned treatment group; membership in 36-month latent class 1, 2, or 3; MTA vs. LNCG). In contrast to the traditional repeated measures analysis of variance, mixed-effects regression models allowed us to include subjects with incomplete data across time and account for within-subject correlations between observations. We included individual point-in-time contrasts, treating group and time as fixed effects and the intercept as a random effect, to test the significance of group differences at 6- and 8-years. Power was sufficient (.80 or higher) to detect small treatment group differences (effect size of .28 or larger at p<.05 or less). For five nominal (or categorical) variables analyzed at the 8-year endpoint only (police contact, arrested, grade retention, psychiatric hospitalizations, driving accidents/citations), we used a multinomial generalized linear model with a cumulative logit link function. GPA was analyzed as a continuous variable with a single 8-year endpoint comparison.

Three sets of analyses were conducted. (1) First, for the MTA participants, mixed-effects models with the planned point-in-time contrasts were tested for each outcome measure to establish any remaining differences of initial treatment assignments by the 6- and 8-year assessments. Following our procedures for ensuring a limited number of clinically relevant treatment group comparisons from previous papers, the effects of treatment were tested using three orthogonal contrasts following statistically significant treatment × time interactions (or for endpoint-only analyses, following statistically significant main effects of treatment): Comb+MedMgt vs Beh+CC, termed the MTA Medication Algorithm effect; Comb vs MedMgt, the Multimodality effect; and Beh vs CC, the Behavioral Substitution effect. We also tested an alternate set of planned contrasts distinguished by using behavioral treatment rather than medication algorithm as the primary divider (see Molina et al.): Comb+Beh vs MedMgt+CC, or the Intensive Behavioral effect; Comb vs Beh, the Medication Addition effect; and MedMgt vs CC, the Intensity of Medication effect. Site as a fixed effect and medication use (time-varying for repeated measures analyses) were covaried, and p-values > .025 are not reported as statistically significant to adjust for alpha inflation because of two sets of treatment group contrasts. (2) Comparisons among the three previously identified 36-month latent classes for the 6- and 8-year outcome measures were analyzed using mixed-effects regression models and point-in-time contrasts among the classes, controlling for site. (3) Finally, MTA subjects were compared to LNCG subjects with mixed-effects regression models with point-in-time contrasts. LNCG subjects who met diagnostic criteria for ADHD at recruitment, n=31, were removed; results were not appreciably different with these subjects included. To assist with interpretation, in addition to observed means and percentages in the tables by group, effect sizes are presented for statistically significant group comparisons using Cohen's d for means (SDs) and Cohen's h for proportions, where 0.2 is considered a small effect size, 0.5 is considered a medium effect size, and 0.8 is considered a large effect size. Because results were not affected by the inclusion of age as a covariate, we present findings without age covaried. IQ at study entry was controlled in the latent class and MTA vs. LNCG comparisons for academic outcomes (WIAT scores, teacher-rated academic performance, GPA, school services, grade retention). Data were from the 8-year dataset closed on 1/31/06.


Medication Use Over Time

We first examined medication use because of its importance as a covariate in determining long-term treatment effects. As previously reported, medication use varied at 14, 24, and 36 months according to initial random assignment: M(SD) = 0.71 (0.24), 0.67 (0.35), 0.66 (0.41) for MedMgt; 0.71 (0.22), 0.69 (0.35), 0.67 (0.39) for Comb; 0.16 (0.28), 0.35 (0.44), 0.43 (0.46) for Beh; 0.54 (0.41), 0.58 (0.42), 0.59 (0.43) for CC, respectively. By the 6- and 8-year assessments, however, these group differences in medication use were no longer significant, F (3, 457) = 1.11, ns, and F (3, 408) = 0.60, ns, respectively. For the MTA sample as a whole, M(SD) = 0.42 (0.43) at 6 years; M(SD) = 0.31 (0.42) at 8 years.

At 8 years, only 32.5% (132/406 with complete medication data) were medicated over 50% of days in the past year (versus 63.3% or 257/406 at 14 months). Treatment was still predominantly with stimulants (83%) or stimulants plus non-stimulant treatment (8%) with few reporting non-stimulant treatments alone (9%); average total daily dose of stimulant (in MPH equivalent units) was 44.93 mg, SD = 26.08. Most of the youths medicated at 8 years had also been medicated at 14 months (75.0% or 99/132). Average total daily dose of those taking stimulants at both assessments was 43.36 mg, SD = 24.33, at 8 years and 30.68 mg, SD = 13.94, at 14 months. Thus, stimulant medication at 8 years more often reflected continued treatment, with increased dosage, rather than newly initiated medication.

Across time, 17.2% (70/406) of children were medicated at every assessment beginning with 14 month reports, 20.4% (83/406) were not medicated at any of these assessments, and 62.3% (253/406) were medicated at least once but not every time. Of the total pool of children medicated at 14 months (n=257), 61.5% (158) had stopped medication some time after 14 months and were not medicated at the 8-year follow-up.

Effects of Randomized Treatment on 6- and 8-year Outcomes: Intent-to-Treat Analyses

Table 1 shows the results of the mixed-effects models at 8 years (if different, results of 6-year contrasts are discussed in text). There were no statistically significant effects of original randomized treatment group assignment on any of the 24 outcome variables tested. When treatment × time interactions were significant (eight variables), planned contrasts at 8-years were not. (As confirmed by additional contrasts, previously reported effects of randomized treatment group at 14 and 24 months accounted for the significant treatment × time interactions.) There were no statistically significant effects of randomized treatment group for the six variables analyzed only at the 8-year endpoint.

Table 1
8-Year Outcomes (M, SD or %) by Original Randomized Treatment Group

Two variables were statistically significant in the planned contrasts at 6-years only, and these effects were small. First, adolescents who received Comb had fewer school services at 6 years than adolescents who received Beh, p=.0204. Second, DISC diagnoses of anxiety or depression differed by group at 6-years. Children who received Beh had a lower rate of these diagnoses (4.3%) than children in the Comb (17.7%), MedMgt (19.1%), or CC (16.4%) groups. The difference was reflected in four statistically significant contrasts: Comb+MedMgt>Beh+CC, p=.0050; Beh<CC, p=.0064; Comb>Beh, p=.0027; Comb+Beh<MedMgt+CC, p=.0132.

Psychosis, mania, and hypomania occurred too infrequently for reliable statistical analysis, thereby failing to support the idea that prior stimulant medication may instigate appreciable increases in these disorders. Their prevalence (defined as presence of one or more of these three conditions) was 1.7% in Comb, 2.0% in MedMgt, 0.9% in Beh, and 2.9% in CC. Rates of tic disorder (new cases since enrollment, when tic disorder was among the exclusion criteria) were 5.2%, 5.0%, 3.6%, and 3.8%, and rates of elimination disorder were 0.9%, 1.0%, 0.9%, and 0%, for Comb, MedMgt, Beh, and CC, respectively.

Figure 2 illustrates the overall pattern of scores for six of the continuous variables. These graphs reveal convergence of treatment groups from 36 months to 8 years and maintenance of improved functioning overall relative to baseline. An exception appears for WIAT math achievement, for which no randomized treatment group-related gains were detected at any assessment point (see also,).

Figure 2
Selected outcome variables for MTA children, graphed by originally randomized treatment group assignment, and LNCG. CC = Community Care; MedMgt = Medication Management; Comb = Combined; Beh = Behavior Therapy; LNCG = Local Normative Comparison Group; ...

Medication use during the past year, measured at each assessment and treated as a time-varying covariate, was associated with outcome over time in a pattern consistent with prior reports., , It was generally associated with better functioning at 14 and 24 months, when medication use mostly reflected randomized treatment group assignment, but it was associated with worse functioning and more school services (or showed no association with other outcomes) at the later assessments. An exception occurred for WIAT math achievement, for which past-year medication and math test performance were positively associated at 36 months, p=.0011, at 6 years, p=.0002, and at 8 years, p<.0001 (but not at 14 or 24 months, p>.05). Because past-year medication use at the later assessments generally reflected continued rather than newly initiated medication, these findings may suggest a uniquely beneficial effect of continued medication treatment on math achievement. These associations were present whether or not initial randomized treatment group assignment was included in the model.

Prediction of 6- and 8-year Outcomes from 36-Month Latent Class

Table 2 shows the results for the 8-year outcomes when the independent variable is 36-month latent class membership (i.e., membership in one of the three ADHD symptom trajectories identified between baseline and 36-months; see Figure 1). Statistically significant effects of 36-month latent class were found for 12 of the 22 variables tested (54.5%), either as a significant effect of class with no class by time interaction (e.g., delinquency severity rating), or as a class by time interaction reflecting variation in the magnitude of class differences over time (e.g., SNAP inattention). The results of the associated statistically significant planned contrasts among the classes at 8 years revealed a consistent pattern across the variables. Children in Class 2 (the class comprising 52% of the sample with the best initial treatment response and most favorable clinical presentation at baseline) fared better over time than children in Classes 1 and 3. Effect sizes were small (mostly in the .2 to .3 range) when comparing Classes 1 and 2, but larger (in the .4 to .6 range, representing medium effects) when comparing Classes 2 and 3. Medium effect sizes were found for several statistically significant Class 1 versus Class 3 comparisons. Figure 3 illustrates for selected continuous variables the overall pattern of findings, namely that the differences in symptoms and functioning observed on the basis of latent classes established at the 36-month assessment generally maintain through high school age (although with some lessening in magnitude of difference by 8 years). All but one of the contrasts that were significantly different at 8 years was also significantly different at 6 years (ODD/CD diagnosis was not significantly different between Classes 1 and 2 at 6 years). A small number of contrasts were significant at 6 years but not at 8 years (Class 1 < Class 3 aggression/conduct score; Class 2 < Class 1 CIS impairment score; Class 2 < Class 1 proportion with ADHD diagnosis).

Figure 3
Selected outcome variables for MTA children, graphed by 36 month ADHD symptom latent class, and LNCG (Local Normative Comparison Group). SNAP = Swanson, Nolan, Pelham Rating Scale; CIS = Columbia Impairment Rating Scale; ODD = Oppositional Defiant Disorder. ...
Table 2
8-Year Outcomes (M, SD or %) by 36-Month Latent Class

Functioning Relative to the LNCG

Table 3 shows the results of comparisons between the MTA and LNCG youth at 8-years. Statistically significant effects of MTA vs. LNCG were found for 19 of the 21 variables tested (90.5%), either as a significant effect of group with no group × time interaction (e.g., delinquency severity rating), or as a group by time interaction reflecting variation in the magnitude of group differences over time (e.g., SNAP inattention. Two comparisons were not statistically significant (MASC anxiety and driving accidents/citations). Effect sizes in the far right column for statistically significant MTA vs. LNCG group differences generally ranged from 0.4 to 1.0 --medium to large effects, revealing worse outcome over time for the MTA children for each variable tested. All repeated measures comparisons that were statistically significant at 8 years were also statistically significant at 6 years.

Table 3
8-Year Outcomes (M, SD or %) for MTA and LNCG

Figures 2 and and33 show the LNCG mean scores for selected continuous variables, contrasted with the mean scores for the MTA youth by treatment group (Figure 2) or by 36-month latent class (Figure 3). These figures illustrate the relatively poorer behavioral (ADHD and ODD symptom ratings), academic (WIAT math achievement), and overall functioning (CIS impairment) of the MTA youth relative to the LNCG. For example, for ADHD and ODD symptom ratings, where the MTA average score is a full SD higher than the LNCG (even higher for inattention ratings), Figure 2 shows that treatment-related decreases in symptoms do not “normalize” the children as a group. Figure 3 shows that both childhood ADHD diagnosis and latent class membership predict long-term outcome, but original random assignment does not. The Table 2 statistics and Figures 23 show that these findings are steady over time, from 24 months post-baseline when the LNCG was recruited, through 8 years.

Rates of diagnosis of ADHD decreased from 43.0% at the 6-year assessment to 30.2% at the 8-year assessment for the MTA sample, versus 4.3% and 2.2% respectively, for the LNCG sample. (Recall that these results exclude 31 LNCG with ADHD at recruitment. Rates of ADHD diagnosis at 6- and 8-years for the full LNCG sample were 8.0% and 5.0%, respectively, also significantly different from the MTA sample at p<.0001.) As shown in Table 3, Inattentive subtype was the most common diagnosis, followed by Combined and Hyperactive-Impulsive subtypes (analyses using alternative diagnosing algorithms are in progress). About 25% to 30% of the MTA youth were in the spectrum of clinically significant antisocial behavior, with 25.1% meeting DSM-IV diagnostic criteria for ODD or CD, 26.8% arrested at least once by 8 years, and 30% earning a delinquency severity code of 3 or higher (moderately serious to serious behavior reported by the youth or parent). These percentages were each significantly higher for MTA than for LNCG youth. Group differences were not found for driving-related citations and accidents, perhaps due to the lag in time between the MTA and LNCG groups' obtaining of driver's licenses.

Academic performance indicators showed that on average, controlling for IQ, MTA youth were performing about half a SD less well than LNCG youth. The average teacher rating of academic performance was 3.08, corresponding to performance between the 30th and 70th percentiles compared to other students and grade-level expectations. This compares to an average rating of 3.54 for LNCG students (a rating of 4 corresponds to performance between the 70th and 90th percentiles). GPA was lower for the MTA than LNCG youth, revealing deficiency in the MTA student's permanent school record - an ecologically valid and salient indicator of academic performance.

Psychiatric hospitalizations occurred more often for MTA than for LNCG, but diagnoses of psychosis, mania, or hypomania by 8 years were uncommon for both groups. Eight MTA children had developed one of these disorders, versus only one LNCG child (1.8% vs. 0.4%). Tic (4.4% vs. 1.7%) and elimination disorders (0.7% and 0.0%) were also infrequent for MTA and LNCG, respectively, by 8 years.


Three sets of findings resulted from this prospective longitudinal study of the MTA children into adolescence. Intent-to-treat analyses revealed no appreciable differences among the children based on their randomized treatment group assignment at 7–9 years of age. ADHD symptom trajectory in childhood, however, was a strong predictor of outcome at both 6- and 8-years. Finally, despite overall maintenance of improvement in functioning relative to baseline (pre-treatment), the MTA group as a whole was functioning significantly less well than the non-ADHD classmate sample (LNCG) recruited at 24-months. These findings provide evidence that the differential effects of the ADHD treatments, evident when the interventions were delivered, attenuated when the intensity of treatment was relaxed. To our knowledge, these findings are the first in the ADHD treatment literature to document, for a wide range of symptom and functioning outcomes, the sustained absence of long-term effects of an initial period of randomly assigned treatment (separate analyses of long-term effects on substance use, growth, and heart rate are in progress).

Our results suggest that the initial clinical presentation in childhood, including severity of ADHD symptoms, conduct problems, intellect, and social advantage, and strength of ADHD symptom response to any treatment, are better predictors of later adolescent functioning than the type of treatment received in childhood for 14 months. This conclusion follows from our analyses comparing the children's 6- and 8-year functioning on the basis of their prior ADHD symptom “latent class” membership, when children in “Class 2” were characterized by the strongest and most enduring decrease in ADHD symptoms between baseline and 36 months. Compared to children in Classes 1 and 3, Class 2 children also had better scores at baseline on a range of variables that included symptom severity, conduct problems, learning problems and IQ, social skills, and family characteristics conferring socioeconomic advantage (fewer marital break-ups and better financial picture). These findings reflect, in a clinical sample, the moderate degree of stability in relative rank ordering of children's behavior or personality also seen in non-clinical samples. Yet for most of the MTA children (those in Classes 1 and 2), functioning was still substantially improved over baseline levels, suggesting that sustained improvement (not normalization) relative to the child's initial presentation for treatment is achievable. Gains may be greatest for children with the least severe initial presentation, although severity of initial presentation such as co-occurrence of conduct problems may not drive which treatment works best.

It is tempting to conclude that intensive medication management beyond 14-months could have resulted in continued differences between the randomly assigned treatment groups. This assumption is partially based on our prior report that the MTA medication algorithm resulted in a greater reduction of symptoms than the community-provided medication treatment, suggesting that aspects of the MTA pharmacologic protocol (e.g., initial titration, monthly monitoring including input from teacher, higher dosing, TID dosing) may improve results over those of community care. In addition, in a previous multimodal treatment study where medication was carefully titrated and monitored for two years, treatment gains were maintained for the entire period. However, after 14 months the MTA became an uncontrolled naturalistic follow-up study and inferences about potential advantages that might have occurred with continued long-term study-provided treatment are speculation. Moreover, with one exception (math achievement), children still taking medication by 6 and 8 years fared no better than their non-medicated counterparts despite a 41% increase in the average total daily dose, failing to support continued medication treatment as salutary (at least, continued medication treatment as monitored by community practitioners). Additionally, failure to find better outcomes associated with continued medication treatment occurred despite the arrival of improved long-acting stimulant medications that more effectively produce the 12-hour/day coverage of the MTA medication algorithm. Dramatic increases in prescriptions for these medications, beginning with OROS-MPH (Concerta®) in 2000 followed by Adderall XR®, showed widespread and immediate acceptance of their use during the MTA follow-up period. Finally, a previous analysis of the MTA data through 3 years did not provide evidence that subject selection biases towards medication use in the follow-up period accounted for the observed lack of differential treatment effects. Thus, although the MTA data provided strong support for the acute reduction of symptoms with intensive medication management, these long-term follow-up data fail to provide support for long-term advantage of medication treatment beyond two years for the majority of children—at least as medication is monitored in community settings. Decisions about starting, continuing, and stopping medication may have to be made on an individualized basis, avoiding untested assumptions about continuing benefit, and using periodic trial discontinuations to check for need and benefit.

Indeed, long-term monitoring of children with ADHD may be wise given the pervasive differences in symptoms, functioning, and apparent need for services found between the MTA and LNCG samples in adolescence. In an effort to fully appreciate the MTA children's functioning as adolescents, we expanded the range of variables studied. These results showed that, although symptoms and impairment remained appreciably improved over baseline levels, normalization was generally not achieved. We found poorer performance for the MTA children as a group versus LNCG children for 91% of the variables. For example, although we replicated an expected decrease in parent- and teacher-rated symptoms of hyperactivity and impulsivity, the MTA children's scores on all of the ADHD symptom measures were still substantially higher than those of their former classmates. Standardized achievement test scores, teacher ratings of academic performance, and even grades earned in high school, were lower for the ADHD than for the LNCG group. The MTA children also had a twofold higher rate of grade retention. Rates of delinquency and arrest were higher in the ADHD sample, and psychiatric hospitalizations were more common, occurring for 10% of the ADHD sample versus only 1% of the LNCG (although this difference did not appear to be a function of increased rates of psychosis, mania, or hypomania, dispelling concerns that CNS stimulant treatment triggers such disorders at high rates).

In contrast to this pattern of lower functioning on average in the MTA vs. LNCG samples, only 30% of the MTA children fulfilled DSM-IV criteria for ADHD by the 8-year follow-up. This figure is low compared to some prior estimates of ADHD persistence in adolescence, and may be an underestimate that fails to consider age-appropriate symptom cut-offs. Indeed, arguments have been put forth that the symptom count thresholds developed for the diagnosis of ADHD in children may be overly stringent for adolescents and adults. Moreover, there is some evidence that remission of symptoms does not equate with recovery of function. For example, only modest associations were found between ADHD symptom reports and various measures of impairment in daily functioning across four separate ADHD samples spanning the elementary to early adulthood years. A comparison of diagnostic algorithms in relation to indicators of impairment was beyond the scope of this paper but would be a fruitful analysis to aid future nosology decisions, particularly with regard to developmental changes in these associations. Our results also lend some support to the idea that indicators of functioning (beyond symptoms) may be crucial, if not more important than measurement of symptoms, in the design and study of treatments for ADHD., Direct measurements of academic performance in school (specifically, grades earned as a reflection of homework completion, quiz and test performance), behavioral transgressions including office referrals, disciplinary actions and conflict with parents, and social dysfunction ultimately drive treatment-seeking behavior and probably mediate long-term outcome. Given the wide-ranging differences between the MTA and LNCG samples in variables that transcend the symptoms of ADHD, and their potential importance as treatment targets, future clinical trials may be forced to broaden narrow definitions of primary outcome variables.

Taken together, these 8-year findings point to a crucial need for development of treatments that are efficacious, accessible, and lasting for high school-aged youth with ADHD and their parents. The available literature on this topic is quite small and in need of innovation. Unfortunately, teenagers with ADHD are not easy to treat. There is the temptation, despite our failure to find long-term advantage of medication treatment, to somehow improve adherence to medication treatment. However, an under-recognized problem in the treatment of adolescent ADHD is the dramatic decline in medication adherence with the onset of adolescence. In the current study, 62% of the MTA children taking medication at 14-months (post-treatment) had stopped by the 8-year follow-up despite the advances in long-acting stimulant medications. This decline is important in the larger context of studies finding poor adherence, more generally, with stimulant treatment regimens. Thus, treatments may need to target motivational variables to encourage adolescent participation in non-pharmacologic interventions (as well as pharmacologic interventions that may be acutely effective for a given individual), and that also address continued family and school involvement. There are also data to suggest that periodic psychosocial treatments for 10 years are effective, including for diagnosis of ADHD (for the children in the Fast Track study with high externalizing behaviors at baseline). Whether these strategies assist parents and adolescents with motivation to maintain treatment, and whether these results would apply to children diagnosed with ADHD Combined Type, is a subject of future study.

Overall, the findings of this 6- and 8-year follow-up of the children in the MTA indicate that 1) treatment-related improvements for the children in the MTA are generally maintained, but differential treatment efficacy continues to be lost at and beyond 36-months; 2) initial patient characteristics and demographics and improved ADHD symptom response to any of the MTA treatments or to community care predicts high-school-aged functioning for a range of outcomes; 3) on average, children with Combined Type ADHD, despite having received 14-months of intensive, state-of-the-art behavior therapy or medication management, are functioning less well than their nonADHD age-mates across most indices of functioning. Some children were lost to follow-up, and their families were demographically disadvantaged. Thus, the MTA versus LNCG group differences that we observed may be underestimates. Our findings suggest that community treatments can improve ADHD symptoms and associated impairment, but even when preceded by intensive medication management and/or behavioral therapy for 14 months, continuing community interventions are unable on average to “normalize” children with ADHD. These findings apply to a range of symptom and functioning indices including delinquency, arrests, grade retentions and letter grades earned in school, and psychiatric hospitalizations that occur for an important minority of the sample. Hence, there is a practical need to pursue further research to develop and deliver more effective sustainable interventions, and to shift the emphasis in the field from reliance on ADHD symptoms as the key outcome of treatment to include measurement of impairments that bring families in for treatment and that are likely to mediate adulthood functioning.


The work reported was supported by cooperative agreement grants and contracts from the National Institute of Mental Health to the following: University of California, Berkeley: U01 MH50461, N01MH12009, and HHSN271200800005-C; Duke University: U01 MH50477, N01MH12012, and HHSN271200800009-C; University of California, Irvine: U01 MH50440, N01MH 12011, and HHSN271200800006-C; Research Foundation for Mental Hygiene (New York State Psychiatric Institute/Columbia University): U01 MH50467, N01 MH12007, and HHSN271200800007-C; Long Island-Jewish Medical Center U01 MH50453; New York University: N01MH 12004, and HHSN271200800004-C; University of Pittsburgh: U01 MH50467, N01 MH 12010, and HHSN 271200800008C; and McGill University N01MH12008, and HHSN271200800003-C. The Office of Special Education Programs of the U.S. Department of Education, the Office of Juvenile Justice and Delinquency Prevention of the Justice Department, and the National Institute on Drug Abuse also participated in funding.

Disclosure: During the course of the MTA, since 1992: Dr. Jensen has received research funding from McNeil; has received unrestricted grants from Pfizer; has consulted to Best Practice, Inc., Shire, Janssen, Novartis, Otsuka, and UCB; and has participated in speaker's bureau for Janssen-Ortho, Alza, McNeil, UCB, CMED, CME Outfitters, and the Neuroscience Education Institute. Dr. Arnold has received research funding from Celgene, Shire, Noven, Eli Lilly, Targacept, Sigma Tau, Novartis, and Neuropharm; has consulted to Shire, Noven, Sigma Tau, Ross, Organon, and Neuropharm; and has been on speaker's bureau for Abbott, Shire, McNeil, and Novartis. Dr. Swanson has received research support from Alza, Richwood, Shire, Celgene, Novartis, Celltech, Gliatech, Cephalon, Watson, CIBA, Janssen, and McNeil; has been on the advisory board for Alza, Richwood, Shire, Celgene, Novartis, Celltech, UCB, Gliatech, Cephalon, McNeil, and Eli Lilly; has been on speaker's bureau for Alza, Shire, Novartis, Celltech, UCB, Cephalon, CIBA, Janssen, and McNeil; and has consulted to Alza, Richwood, Shire, Celgene, Novartis, Celltech, UCB, Gliatech, Cephalon, Watson, CIBA, Janssen, McNeil, and Eli Lilly. Dr. Abikoff has received research funding from McNeil, Shire, Eli Lilly and Bristol Myers-Squibb; has consulted to McNeil, Shire, Eli Lilly, Pfizer, Celltech, Cephalon, and Novartis; and has been on speaker's bureau for McNeil, Shire and Celltech. Dr. Greenhill has received research funding or has been a consultant for National Institute of Mental Health, Eli Lilly, Alza, Shire, Cephalon, McNeil, Noven, OrthoMcNeil, Celltech, Novartis, Sanofi Aventis, Otsuka, Pfizer, and Janssen. Dr. Hechtman has received research funding from National Institute of Mental Health, Eli Lilly, Glaxo Smith/Kline, Janssen-Ortho, Purdue Pharma, and Shire; has been on speaker's bureau for National Institute of Mental Health, Eli Lilly, Janssen-Ortho, Purdue Pharma, and Shire; and has been on the advisory board for Eli Lilly, Janssen-Ortho, Purdue Pharma, and Shire. Dr. Elliott has received research funding from Cephalon, McNeil, Shire, Sigma Tau, and Novartis; has consulted to Cephalon and McNeil; and has been on the Speakers' Bureau for Janssen, Eli Lilly, and McNeil. Dr. Epstein has received research funding from McNeil, Shire, Eli Lilly, and Novartis; has been on advisory board for Shire; and has been on speaker's bureau for Shire and McNeil. Dr. Hoza has received research funding from MediaBalance, Inc. and has received support for educational conferences from Abbott Laboratories. Dr. Newcorn has been an advisor/consultant to Eli Lilly, Alza, McNeil Pediatrics, Janssen, Shire, Novartis, Cephalon, Celltech, UCB, Sanofi-Aventis, Abbott, Pfizer, Cortex, Lupin, Sepracor and Bristol Myers-Squibb; received research funding from Eli Lilly, Shire, Alza, McNeil, Gliatech, Medeva, Novartis, and Smith Kline Beecham; and has been on a speaker's bureau for Alza, McNeil, Eli Lilly, Shire, Novartis, Celltech, and UCB. Dr. Wigal has received research funding from Eli Lilly, Shire, Novarits, and McNeil and has been on speaker's bureau for McNeil and Shire.


The opinions and assertions contained in this report are the private views of the authors and are not to be construed as official or as reflecting the views of the Department of Health and Human Services, the National Institutes of Health, or the National Institute of Mental Health.

Clinical Trials Registry: Multimodal Treatment Study of Children with Attention Deficit and Hyperactivity Disorder; http://www.ClinicalTrials.gov; NCT00000388.

The other authors report no conflicts of interest.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


1. The MTA Cooperative Group A 14-month randomized clinical trial of treatment strategies for attention-deficit/hyperactivity disorder. Arch Gen Psychiatry. 1999;56(12):1073–1086. [PubMed]
2. The MTA Cooperative Group Moderators and mediators of treatment response for children with attention-deficit/hyperactivity disorder. Arch Gen Psychiatry. 1999;56(12):1088–1096. [PubMed]
3. Richters JE, Arnold LE, Jensen PS, et al. The National Institute of Mental Health collaborative multisite Multimodal Treatment Study of Children with ADHD: I. background and rationale. J Am Acad Child Adolesc Psychiatry. 1995;34(8):987–1000. [PubMed]
4. The MTA Cooperative Group National Institute of Mental Health Multimodal Treatment Study of ADHD follow-up: 24-month outcomes of treatment strategies for attention-deficit/hyperactivity disorder. Pediatrics. 2004;113(4):754–761. [PubMed]
5. The MTA Cooperative Group National Institute of Mental Health Multimodal Treatment Study of ADHD follow-up: changes in effectiveness and growth after the end of treatment. Pediatrics. 2004;113(4):762–769. [PubMed]
6. Jensen PS, Arnold LE, Swanson JM, et al. 3-year follow-up of the NIMH MTA study. J Am Acad Child Adolesc Psychiatry. 2007;46(8):989–1002. [PubMed]
7. Swanson JM, Hinshaw SP, Arnold LE, et al. Secondary evaluations of MTA 36-month outcomes: propensity score and growth mixture model analyses. J Am Acad Child Adolesc Psychiatry. 2007;46(8):1003–1014. [PubMed]
8. Swanson J, Arnold LE, Kraemer H, Hechtman L, Molina B, Hinshaw S, Vitiello B, Jensen P, Steinhoff K, Lerner M, Greenhill L, Abikoff H, Wells K, Epstein J, Elliott G, Newcorn J, Hoza B, Wigal T, MTA Cooperative Group Evidence, interpretation, and qualification from multiple reports of long-term outcomes in the Multimodal Treatment Study of Children with ADHD (MTA): Part I: Executive summary. J Atten Disord. 2008;12:4–14. [PubMed]
9. Swanson J, Arnold LE, Kraemer H, Hechtman L, Molina B, Hinshaw S, Vitiello B, Jensen P, Steinhoff K, Lerner M, Greenhill L, Abikoff H, Wells K, Epstein J, Elliott G, Newcorn J, Hoza B, Wigal T, MTA Cooperative Group Evidence, interpretation, and qualification from multiple reports of long-term outcomes in the Multimodal Treatment Study of Children with ADHD (MTA): Part 2: Supporting details. J Atten Disord. 2008;12:15–43. [PubMed]
10. Arnold LE, Abikoff HB, Cantwell DP, Conners CK, Elliott GR, Greenhill LL. NIMH collaborative Multimodal Treatment Study of Children with ADHD (MTA): design challenges and choices. Arch Gen Psychiatry. 1997;54(9):865–870. [PubMed]
11. Greenhill LL, Abikoff HB, Arnold LE, Cantwell DP, Conners CK, Elliott GR. Medication treatment strategies in the MTA: relevance to clinicians and researchers. J Am Acad Child Adolesc Psychiatry. 1996;35(10):1304–1313. [PubMed]
12. Greenhill LL, Swanson JM, Vitiello B, Davies M, Clevenger W, Wu M. Impairment and deportment responses to different methylphenidate doses in children with ADHD: the MTA titration. J Am Acad Child Adolesc Psychiatry. 2001;40(2):180–187. [PubMed]
13. Hinshaw SP, March JS, Abikoff HB, et al. Comprehensive assessment of childhood attention-deficit hyperactivity disorder in the context of a multisite, multimodal clinical trial. J Atten Disord. 1997;1:217–234.
14. Wells KC, Pelham WE, Kotkin RA, et al. Psychosocial treatment strategies in the MTA study: rationale, methods, and critical issues in design and implementation. J Abnorm Child Psychol. 2000;28(6):483–505. [PubMed]
15. Shaffer D, Fisher P, Lucas CP, Dulcan MK, Schwab-Stone ME. NIMH diagnostic interview schedule for children version IV (NIMH DISC-IV): description, differences from previous versions, and reliability of some common diagnoses. J Am Acad Child Adolesc Psychiatry. 2000;39(1):28–38. [PubMed]
16. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 4th edition (DSM-IV) American Psychiatric Association; Washington, DC: 1994.
17. Molina BS, Flory K, Hinshaw SP, et al. Delinquent behavior and emerging substance use in the MTA at 36 months: prevalence, course, and treatment effects. J Am Acad Child Adolesc Psychiatry. 2007;46(8):1028–1040. [PubMed]
18. Jensen P, Hoagwood K, Roper M, et al. The services for children and adolescents parent interview (SCAPI): development and performance characteristics. J Am Acad Child Adolesc Psychiatry. 2004;43(11):1334–1344. [PubMed]
19. Hoagwood K, Jensen PS, Arnold LE, et al. Reliability of the services for children and adolescents parent interview (SCAPI) J Am Acad Child Adolesc Psychiatry. 2004;43(11):1345–1454. [PubMed]
20. Bird HR, Shaffer D, Fisher P, et al. The columbia impairment scale (CIS): pilot findings on a measure of global impairment for children and adolescents. Int J Methods Psychiatr Res. 1993;3:167–176.
21. Kovacs M. Manual: The Children's Depression Inventory. Multi-Health Systems; Toronto, Canada: 1995.
22. March J, Conners C, Arnold LE, et al. The multidimensional anxiety scale for children (MASC): confirmatory factor analysis in a pediatric ADHD sample. J Atten Disord. 1999;3(2):85–89.
23. Wechsler D. Wechsler Individual Achievement Test. Psychological Corporation; San Antonio, TX: 1992.
24. Gresham FM, Elliott SN. Social Skills Rating System--Parent, teacher, and child forms. American Guidance Systems; Circle Pines, MN: 1989.
25. Robins LN, Cottler LB, Bucholz KK, Compton WM, North CS, Rourke KM. Diagnostic Interview Schedule for the DSM-IV (DIS-IV) Washington University School of Medicine; St. Louis, MO: 2000.
26. Beck AT, Ward C, Mendelson N, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:53–63.
27. Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56:893–897. [PubMed]
28. Hedeker D, Gibbons RD. Longitudinal Data Analysis. John Wiley & Sons; New York: 2006.
29. Cohen J. A power primer. Psych Bull. 1992;112:155–159. [PubMed]
30. Roberts BW, DelVecchio WF. The rank-order consistency of personality traits from childhood to old age: A quantitative review of longitudinal studies. Psych Bull. 2000;126:3–25. [PubMed]
31. Owens EB, Hinshaw SP, Kraemer HC, Arnold LE, ABikoff HB, Cantwell DP, Conners CK, Elliott G, Greenhill LL, Hechtman L, Hoza B, Jensen PS, March JS, Newcorn JH, Pelham WE, Richters JE, Schiller EP, Severe JB, Swanson JM, Vereen D, Vitiello B, Wells KC, Wigal T. Which treatment for whom for ADHD? Moderators of treatment response in the MTA. J Consult Clin Psychol. 2003;71(3):540–552. [PubMed]
32. Abikoff H, Hechtman L, Kelin RG, et al. Symptomatic improvement in children with ADHD treated with long-term methylphenidate and multimodal psychosocial treatment. J Am Acad Child Adolesc Psychiatry. 2004;43(7):802–811. [PubMed]
33. Swanson JM, Volkow ND. Psychopharmacology: Concepts and opinions about the use of stimulant medications. J Child Psychol Psychiatry. In press. [PMC free article] [PubMed]
34. Hart EL, Lahey BB, Loeber R, Applegate B, Green SM, Frick PJ. Developmental change in attention-deficit hyperactivity disorder in boys: A four-year longitudinal study. J Abnorm Child Psychol. 1995;23:729–749. [PubMed]
35. Hinshaw SP, Owens EB, Sami N, Fargeon S. Prospective follow-up of girls with attention-deficit/hyperactivity disorder into adolescence: evidence for continuing cross-domain impairment. J Consult Clin Psychol. 2006;74(3):489–499. [PubMed]
36. Mick E, Faraone SV, Biederman J. Age-dependent expression of attention deficit/hyperactivity symptoms. Psychiatr Clin North Am. 2004;27(2):215–224. [PubMed]
37. Ross RG. Psychotic and manic-like symptoms during stimulant treatment of attention deficit hyperactivity disorder. Am J Psychiatry. 2006;163(7):1149–1152. [PubMed]
38. Barkley RA, Fischer M, Edelbrock CS, Smallish L. The adolescent outcome of hyperactive children diagnosed by research criteria: an 8-year prospective follow-up study. J Am Acad Child Adolesc Psychiatry. 1990;29(4):546–557. [PubMed]
39. Bagwell CL, Molina BSG, Pelham WE, Hoza B. Attention-deficit hyperactivity disorder and problems in peer relations: predictions from childhood to adolescence. J Am Acad Child Adolesc Psychiatry. 2001;40(11):1285–1292. [PubMed]
40. Barkley RA. Attention-Deficit Hyperactivity Disorder. A handbook for diagnosis and treatment. 3rd edition The Guilford Press; New York: 2006.
41. Gordon M, Antshel K, Faraone S, Barkley R, Lewandowski L, Hudziak JJ, Biederman J, Cunningham C. Symptoms versus impairment. The case for respecting DSM-IV's Criterion D. J Atten Disord. 2006;9(3):465–475. [PubMed]
42. Pelham WE, Fabiano GA, Massetti GM. Evidence-based assessment of attention deficit hyperactivity disorder in children and adolescents. J Clin Child Adolesc Psychol. 2005;34(3):449–476. [PubMed]
43. Smith BH, Barkley RA, Shapiro CJ. Attention-deficit/hyperactivity disorder. In: Mash EJ, Barkley RA, editors. Treatment of Childhood Disorders. Third Edition The Guilford Press; New York: 2006. pp. 65–136.
44. Barkley RA, Fischer M, Smallish L, Fletcher KE. Does the treatment of attention-deficit/hyperactivity disorder with stimulants contribute to drug use/abuse? A 13-year prospective study. Pediatrics. 2003;111(1):97–109. [PubMed]
45. Visser SN, Lesesne CA, Perou R. National estimates and factors associated with medication treatment for childhood attention-deficit/hyperactivity disorder. Pediatrics. 2007;119(Suppl 1):S99–106. [PubMed]
46. Leslie LK, Wolraich ML. ADHD service use patterns in youth. J Pediatr Psychol. 2007;32(6):695–710. [PubMed]
47. DuPaul G, Power TJ. Improving school outcomes for students with ADHD: Using the right strategies in the context of the right relationships. J Atten Disord. 2008;11(5):519–521. [PubMed]
48. Evans SW, White C, Sibley M, Barlow E. School-based mental health treatment of children and adolescents with Attention Deficit Hyperactivity Disorder. In: Evans SW, Weist MD, Serpell ZN, editors. Advances in school-based mental health interventions. Best practices and program models. Volume II. Civic Research Institute; Kingston, NJ: 2007. pp. 1–20.
49. Conduct Problems Prevention Research Group Fast track randomized controlled trial to prevent externalizing psychiatric disorders: findings from grades 3 to 9. J Am Acad Child Adolesc Psychiatry. 2007;2007;46(10):1250–62. [PMC free article] [PubMed]


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