The TDAI and IDAI groups differed on several aspects. Following the ADHD informational session, consultants in the TDAI group scheduled two meetings to interview teachers, with the design of academic interventions based on teacher choice. It should be noted that the content of the interviews was typical of what occurs in the school setting. The initial interview served to identify academic are as of concern, discuss current performance, and set goals. At this time, no observations or data collection procedures were conducted. The second interview was used to provide a menu of intervention options appropriate for teacher identified academic concerns, with the teacher choosing the intervention(s). In contrast, the IDAI consultant scheduled three meetings to interview teachers, with the design of academic interventions based on assessment data using a consultative problem-solving model (Bergan & Kratochwill, 1990).

In addition to identifying academic areas of concern and setting goals, the initial interview (problem identification, PI) was used to discuss antecedent and consequent conditions, identify patterns to academic behavior problems, and determine additional observation and data collection procedures. Following PI, IDAI consultants conducted functional academic assessments (e.g., Daly, Witt, Martens, & Dool, 1997) of the classroom (e.g., teacher routines, behaviors, procedures; student and peer behaviors), compared target students' and their peers' work products, and students completed curriculum-based reading and math tests. The second interview (problem analysis, PA) focused on reviewing functional assessment data, providing teachers with a menu of intervention options based on teacher concerns, direct observations, and assessment data, with the teacher choosing the intervention(s). In addition, the consultant established a progress-monitoring plan at this time.

Another critical difference between the two consultation groups is that after teachers chose the intervention(s), IDAI consultants trained teachers, as needed,on implementing the intervention and established weekly contact via phone calls, emails, or face-to-face meetings. In contrast, contact with teachers in the TDAI group was minimal and included occasional phone calls or emails to provide updates and address questions or concerns. Further, either the teacher or the consultant in the IDAI group collected weekly progress-monitoring data using procedures such as curriculum-based probes in beginning reading skills, oral reading fluency, and/or math fluency, as well as comprehension and problem-solving skills, when appropriate. In the TDAI group, data on student progress were not collected, and any changes in intervention were based solely on teacher report of student progress.

With regard to intervention integrity, only teachers in the IDAI group were provided with feedback that was linked to the intervention plan.Finally,only the IDAI consultant conducted a treatment evaluation interview (TEI) with the teacher approximately 4 weeks into the intervention. Using visual analysis of the graphed progress monitoring data, consultants in the IDAI group provided feedback to teachers regarding treatment integrity and student progress (e.g., mastered, no progress, adequate progress, inadequate progress) of skills and outcomes (Browder, Demchak, Heller, & King, 1989). This information was used to determine the appropriatness of the intervention plan.On the basis of the data, decisions included maintaining the intervention, intensifying or simplifying the intervention, providing for improved antecedents, changing the intervention, redefining the goals,or retraining the teacher and/or students in the use of the intervention procedures.

OUR MEASURES
Academic achievement data in the study were collected using curriculum-based measurement (CBM) in reading and math, individualized academic goal attainment or progress of target behavior (POTB) scores, and report card grades. We collected CBM measures and report card grades on four occasions (baseline, 3-months, 12-months, 15-months) across two school years. For POTB, we collected teacher ratings of student performance on nine occasions during the study to provide pre-, mid- and post-intervention assessments between baseline and 3-months (Phase1), 3-and 12-months (Phase 2), and 12- and 15-months (Phase 3). Indicators of academic achievement in this study included words correct per minute and total number of digits correct from the CBM reading and math assessments. Student progress in reading was examined by having children read for 1 minute an excerpt of connected text taken from passages developed by the Children's Educational Services, Inc. (CES; Deno, Deno, & Marston,1987). Student progress in mathematics computation was evaluated by having students complete 25-item computation tests taken from the basic math computation probes, which represented a sample of items found in a specific grade-level curriculum (Fuchs, Hamlett, & Fuchs, 1998).

To evaluate POTB, teachers completed ratings of their perceptions of a student's progress toward academic goals.In this study,consultants worked with teachers to develop academic goals (e.g.,number of words read correctly in a minute) that were objective, measurable, and stated in a positive fashion, which were used as the basis for evaluating the frequency of student demonstration of the specific academic goal using a four-point rating scale that ranged from 0 (never) to +3 (very often). To evaluate student performance and progress in the classroom, report card grades in reading and math were used. To standardize grades across different report card systems, all grades were entered on a 1 ("F") to 5 ("A") basis.

OUR ANALYSES
Separate hierarchical linear modeling (HLM) analyses were conducted for each of the measures to assess possible differences in intercept (baseline value) and slope (academic growth) between the two consultation groups. For all analyses, individual trajectories (i.e., intercept [baseline value] and slope) were calculated for each participant followed by analyses at the group level to determine potential initial group differences, mean growth rate across time, and difference in mean growth rate between TDAI and IDAI. It should be noted that age in months and paternal occupation were used as level 2 covariates for math analyses and reading analyses of POTB data, respectively given the initial differences between the groups at pretreatment.

OUR RESULTS
For 6 of the10 measures, there were no significant group differences in initial performance, indicating group equivalency at pretreatment. However, results revealed group differences at intercept for POTB in both math and reading (Phases 1 and 2), with IDAI group scores being greater than TDAI scores. With the exception of math report card scores, results indicated significant growth on 9 of the10 dependent measures. However, a comparison of the two groups' performance showed that they did not differ in rate of growth for any measure after 15-months of intervention, with similar increasing slopes observed for both groups. Within-group effect sizes were calculated to estimate the magnitude of change from baseline to15 months. Small effect sizes (ES ≤ .50) were found for report card grade in math (both groups) and reading (IDAI only). Alternatively, changes in report card grade in reading(TDAI only)were of moderate magnitude (.50 < ES < .80). Finally, the magnitude of within-subject change was large (ES ≥ .80) for CBM instructional level in both math and reading, as well as all POTB scores for both groups.

CONCLUSIONS
The finding that the two consultation groups did not differ with respect to growth on any of the academic measures is counter intuitive to our hypothesis that children in the IDAI group receiving individualized academic interventions would exhibit greater growth in academic achievement than would children in the TDAI group, whose interventions were selected in the context of atypical school-based consultation model. Although the positive growth trajectories for both groups are encouraging, we cannot attribute the outcomes to either treatment group given the lack of a control group int his study. However, to answer the question as to whether these slopes are educationally significant, we can only speculate from prior research at this time. That is, the less than ideal academic performance (i.e., the typical maintenance and/or worsening of achievement difficulties through the school years) of children with ADHD (Barkley et al., 1990; Lambert, 1988; Latimer et al., 2003; Mannuzza et al.,1993) considered in conjunction with finding simplying the relative intractability of academic problems in response to treatment among children with both ADHD symptoms and academic difficulties (MTA Cooperative Group,1999, 2004; Rabiner, Malone, & the Conduct Problems Prevention Research Group, 2004) underscore our positive findings for both consultation groups. Further, the large effect sizes (mean changes of .80 to 1.49 SD) representing change over a 15-month period across both groups for CBM math and reading tests and POTB add to the practical significance of the findings.The lack of trajectory differences between groups could also reflect the fact that the TDAI group was similar to the IDAI condition in most aspects and differed primarily with regard to intensity of data utilization and feedback to teachers.

The finding that both consultative group scan successfully improve academic outcomes for children with ADHD has direct implications for educators and clinicians working with individuals with ADHD. Consistent with the goals of the response to intervention (RTI) approaches, primary prevention efforts require investment inefficient, evidence-based practices of instruction employed in both consultation groups to address the academic difficulties of children with ADHD (Fuchs & Fuchs, 2006). As such, it may be the case that only a select group of children with ADHD may need the more intensive consultation support services offered by the IDAI.

A second implication is the need to consider cost effectiveness and teacher preference when selecting either type of consultation. Given the challenges of working with inadequate school resources, it may be imperative to consider the use of the less intensive TDAI approach than the comprehensive, data-based model employed in the IDAI condition because both approaches led to effective growth in academic skills.

In sum, our results suggest that both consultation approaches, TDAI and IDAI, hold promise in improving academic outcomes for children with ADHD and, consequently, closing the achievement gap. Future research must be conducted with a larger sample size and over longer periods of time to increase the confidence in the effectiveness of either or both treatment approaches. In addition, future research should explore the conditions under which the TDAI consultation approach is sufficient and when an intensive which the TDAI consultation approach is sufficient and when an intensive IDAI consultation approach is necessary.

Dr. Jitendra is the Rodney Wallace Professor for the Advancement of Teaching and Learning, Department of Educational Psychology, University of Minnesota. Dr. DuPaul is a Professor in the Department of Counseling Psychology, School Psychology, and Special Education at Lehigh University, Bethlehem, PA 18015. Dr. DuPaul is also on the Editorial Board of the ADHD Report and can be contacted via email at gjd3@lehigh.edu.

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This article was reprinted with permission from The ADHD Report, Vol. 15(6), 2007.published by The Guilford Press.