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The Efficacy of Integrating Engaged Learners into Small Group Reading Instruction on Reading and Attention Outcomes: A Randomized Controlled Trial

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Title: The Efficacy of Integrating Engaged Learners into Small Group Reading Instruction on Reading and Attention Outcomes: A Randomized Controlled Trial
Language: English
Authors: Garrett J. Roberts (ORCID 0000-0003-1128-5577), Greg Roberts, Philip Capin, Anna-Mari Fall, Brian B. Vedder, Anna Handy, Michelle Jestice
Source: Exceptional Children. 2026 92(4):483-501.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 19
Publication Date: 2026
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R324B190010
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Early Childhood Education
Grade 3
Primary Education
Grade 4
Intermediate Grades
Grade 5
Middle Schools
Descriptors: Reading Programs, Intervention, Elementary School Students, Grade 3, Grade 4, Grade 5, Student Behavior, Reading Difficulties, Attention Deficit Disorders, Small Group Instruction, Reading Tests, Rating Scales, Learner Engagement
Assessment and Survey Identifiers: Test of Word Reading Efficiency, Gates MacGinitie Reading Tests, Behavior Assessment System for Children
DOI: 10.1177/00144029251396747
ISSN: 0014-4029
2163-5560
Abstract: We investigate the efficacy of a reading intervention integrated with Engaged Learners, a program that applies behavioral and cognitive principles to increase student behavioral attention and reduce distractions during instruction. Using a three-arm randomized controlled trial, we randomized 159 Grade 3-5 students with co-occurring reading and behavioral attention challenges to a researcher-implemented small group reading intervention with Engaged Learners (READ + ENGAGE), an identical researcher-implemented reading intervention without Engaged Learners (READ), or a Business-as-Usual (BaU) condition. The READ + ENGAGE condition students demonstrated statistically significant greater behavioral attention according to direct observations and interventionist reports than READ condition students. The pattern of reading effect sizes contrasting the conditions suggests that the READ + ENGAGE and READ conditions were associated with higher performance on reading outcomes than the BaU condition and students in the READ condition significantly outperformed the BaU condition on measures of word reading, fluency and reading comprehension, and mid-transfer vocabulary and reading comprehension. We also explored whether integrating the Engaged Learners program in a reading intervention would be associated with improved reading outcomes by contrasting the READ + ENGAGE to the READ condition; however, the findings did not support this hypothesis. Future research could examine the effects of systematically fading the Engaged Learner supports over time and implementing the intervention over a longer duration. These findings demonstrate that an integrated intervention can be implemented with minimal training and coaching, increasing behavioral attention to reading instruction during small-group instruction for upper elementary students with co-occurring reading and behavioral attention challenges.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2026
Accession Number: EJ1508135
Database: ERIC
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  Value: <anid>AN0194392927;exc01jul.26;2026Jun10.02:32;v2.2.500</anid> <title id="AN0194392927-1">The Efficacy of Integrating Engaged Learners Into Small Group Reading Instruction on Reading and Attention Outcomes: A Randomized Controlled Trial </title> <p>We investigate the efficacy of a reading intervention integrated with Engaged Learners, a program that applies behavioral and cognitive principles to increase student behavioral attention and reduce distractions during instruction. Using a three-arm randomized controlled trial, we randomized 159 Grade 3–5 students with co-occurring reading and behavioral attention challenges to a researcher-implemented small group reading intervention with Engaged Learners (READ + ENGAGE), an identical researcher-implemented reading intervention without Engaged Learners (READ), or a Business-as-Usual (BaU) condition. The READ + ENGAGE condition students demonstrated statistically significant greater behavioral attention according to direct observations and interventionist reports than READ condition students. The pattern of reading effect sizes contrasting the conditions suggests that the READ + ENGAGE and READ conditions were associated with higher performance on reading outcomes than the BaU condition and students in the READ condition significantly outperformed the BaU condition on measures of word reading, fluency and reading comprehension, and mid-transfer vocabulary and reading comprehension. We also explored whether integrating the Engaged Learners program in a reading intervention would be associated with improved reading outcomes by contrasting the READ + ENGAGE to the READ condition; however, the findings did not support this hypothesis. Future research could examine the effects of systematically fading the Engaged Learner supports over time and implementing the intervention over a longer duration. These findings demonstrate that an integrated intervention can be implemented with minimal training and coaching, increasing behavioral attention to reading instruction during small-group instruction for upper elementary students with co-occurring reading and behavioral attention challenges.</p> <p>Keywords: reading; attention; behavioral; group experimental design</p> <p>Reading difficulties (RD) and clinical levels of survey measured inattention (henceforth behavioral inattention) co-occur at rates exceeding 25% ([<reflink idref="bib41" id="ref1">41</reflink>]; [<reflink idref="bib53" id="ref2">53</reflink>]) with even higher co-occurrence rates for students with elevated, although subclinical, levels of behavioral inattention ([<reflink idref="bib11" id="ref3">11</reflink>]; [<reflink idref="bib41" id="ref4">41</reflink>]; [<reflink idref="bib53" id="ref5">53</reflink>]). When students present co-occurring RD and clinical or elevated levels of behavioral inattention, they are less likely to adequately respond to evidence-based reading interventions than their peers without behavioral attention challenges ([<reflink idref="bib23" id="ref6">23</reflink>]; [<reflink idref="bib31" id="ref7">31</reflink>]). This difference in intervention response for students with co-occurring reading and behavioral attention challenges may be due to greater need for support than their peers in recalling spoken directions, prioritizing instructional tasks, ignoring irrelevant stimuli, and monitoring their own learning ([<reflink idref="bib29" id="ref8">29</reflink>]; [<reflink idref="bib31" id="ref9">31</reflink>]; [<reflink idref="bib40" id="ref10">40</reflink>]). According to cognitive load theory ([<reflink idref="bib44" id="ref11">44</reflink>]), such challenges may interfere with the ability to process and retain relevant information, while ignoring irrelevant information during reading instruction. As a result, cognitive demands of reading instruction may quickly exceed their working memory capacity. As such, interventions to support behavioral engagement during reading instruction may reduce extraneous cognitive load, enabling students to devote more cognitive resources to the core reading tasks.</p> <p>Researchers have advanced several hypotheses as to why some children experience both reading and attention challenges, simultaneously. The phenotype hypothesis suggests that children presenting both reading and behavioral attention challenges experience a primary area of concern (reading or behavioral attention; [<reflink idref="bib55" id="ref12">55</reflink>]). For example, when students struggle to sustain their behavioral attention to tasks, they may appear to experience reading challenges because behavioral inattention and disengagement can interfere with reading activities. If this were true, an intervention targeting the child's primary area of concern (reading or behavioral attention) would lead to improvements in both domains. In contrast, the multiple deficit model ([<reflink idref="bib33" id="ref13">33</reflink>]; [<reflink idref="bib37" id="ref14">37</reflink>]) suggests that reading and behavioral challenges arise from multiple shared risk factors (e.g., working memory, processing speed) that place children at risk for challenges in each area, resulting in true comorbidity. This model suggests that interventions targeting both domains may be necessary, as they would address the distinct yet interconnected challenges in reading and behavioral attention, potentially leading to greater improvements in both areas relative to an intervention focused on a single domain. Yet, few intervention studies have tested this supposition, and the limited available evidence indicates that instruction in both domains is not associated with improved reading outcomes beyond a reading-only condition (e.g., [<reflink idref="bib7" id="ref15">7</reflink>]; [<reflink idref="bib45" id="ref16">45</reflink>]; [<reflink idref="bib54" id="ref17">54</reflink>]).</p> <hd id="AN0194392927-2">Reading Interventions and Integrated Supports</hd> <p>Even though students with co-occurring reading and behavioral attention challenges are less likely to benefit from reading interventions (than those with only RD), few interventions have targeted both domains together ([<reflink idref="bib39" id="ref18">39</reflink>]). Furthermore, even fewer studies have systematically tested the impact of a reading intervention relative to a reading intervention with integrated supports for students with co-occurring reading and behavioral attention challenges. Recently, [<reflink idref="bib39" id="ref19">39</reflink>] conducted a meta-analysis to investigate the effects of reading interventions for students with co-occurring reading and broadly defined behavior challenges (e.g., inattention, attention-deficit/hyperactivity disorder [ADHD], emotional behavior disorder [EBD]). The authors found a statistically significant main effect of reading interventions on reading outcomes, yet reading interventions without a behavior support component were not associated with improvements in behavioral outcomes (e.g., behavioral attention, disruptive behavior). This finding aligns with previous research suggesting that reading-only interventions may be insufficient to address the dual needs of students with co-occurring reading and behavior challenges ([<reflink idref="bib31" id="ref20">31</reflink>]; [<reflink idref="bib45" id="ref21">45</reflink>]).</p> <p>[<reflink idref="bib39" id="ref22">39</reflink>] identified only three studies ([<reflink idref="bib3" id="ref23">3</reflink>]; Tamm et al., 2019; [<reflink idref="bib56" id="ref24">56</reflink>]) which systematically evaluated the added benefits of a reading intervention with student behavior supports relative to a reading intervention without such supports. [<reflink idref="bib3" id="ref25">3</reflink>] compared a reading intervention with and without a gamification strategy for Grade 6 students with co-occurring RD and ADHD (<emph>n</emph> = 6). According to [<reflink idref="bib3" id="ref26">3</reflink>], the gamification strategy was based on [<reflink idref="bib49" id="ref27">49</reflink>] view of cognitive development, and included teaching spelling through games (e.g., spelling is taught via engaging 1:1 and cooperative activities). Effect sizes on teacher surveys of student effort (ES = 1.86), initiative (ES = 2.96), disruptive behavior (ES = −0.42; less disruptive behavior), and inattentive behavior (ES = −1.85; less behavioral inattention) all favored the intervention condition. Reading outcomes for this study were mixed, as effect sizes varied, favoring both the treatment and comparison conditions. The authors did not test for statistical significance.</p> <p>[<reflink idref="bib56" id="ref28">56</reflink>] compared a reading intervention with and without social skill development (delivered outside the reading group) for Grade 4 students with RD and EBD (<emph>n</emph> = 92). The social skill component targeted social emotional learning (e.g., self-regulation, peer-interaction skills, conflict resolution) to support behaviors that could potentially allow students to more readily benefit from academic instruction ([<reflink idref="bib10" id="ref29">10</reflink>]). This study found a statistically significant effect size of 0.44 (<emph>p</emph> <.001), favoring the treatment condition, on a self-report measure composite score of emotional symptoms, conduct problems, hyperactivity, peer problems, and prosocial behavior. There was not a significant difference between conditions on reading fluency or reading comprehension (<emph>p</emph> >.05).</p> <p>Finally, [<reflink idref="bib45" id="ref30">45</reflink>] implemented a three-arm RCT with Grade 3–5 students with RD and ADHD. The Reading + ADHD intervention condition (<emph>n</emph> = 70) included a reading intervention with a behavioral- and pharmacological-based component (i.e., daily report cards, family training, and medication). The Reading-only intervention condition (<emph>n</emph> = 74) was an identical reading intervention without additional supports. The ADHD intervention condition (<emph>n</emph> = 78) included the behavioral- and pharmacological-based component without the reading intervention. Findings suggested the Reading + ADHD condition significantly outperformed the Reading-only condition with effect sizes of 0.44 (<emph>p</emph> <.05) and 0.41 (<emph>p</emph> <.01) on teacher surveys of behavioral inattention and hyperactivity, respectively. There were no statistically significant differences between these two conditions on the reading measures (i.e., word reading, phonemic decoding, reading fluency, and reading comprehension; findings are presented in both [<reflink idref="bib45" id="ref31">45</reflink>] and [<reflink idref="bib7" id="ref32">7</reflink>]).</p> <p>In summary, this literature base is limited and varies in terms of study design, sample size, and intervention characteristics. Results from these studies suggest that integrating a behavior support component is necessary to improve behavior outcomes. However, adding behavior supports to reading interventions has not yet proven beneficial in enhancing reading outcomes beyond what is achieved with reading-only interventions.</p> <hd id="AN0194392927-3">Engaged Learners: Theoretical and Empirical Underpinnings</hd> <p>Our team developed the Engaged Learners program in response to the need for programs that integrate support for behavioral attention with reading instruction (e.g., [<reflink idref="bib17" id="ref33">17</reflink>]; [<reflink idref="bib34" id="ref34">34</reflink>]; [<reflink idref="bib39" id="ref35">39</reflink>]). Engaged Learners is novel in that, to the best of our knowledge, it is the first fully manualized program designed to (a) be integrated into evidence-based small-group reading programs and (b) improve behavioral attention to academic instruction for students with reading and behavioral attention challenges. In this study, we chose to integrate Engaged Learners into the evidence-based reading curriculum <emph>Voyager Passport</emph> ([<reflink idref="bib48" id="ref36">48</reflink>]), although it was not designed for a specific curriculum.</p> <p>We developed Engaged Learners based on behavioral principles and cognitive training techniques to increase student behavioral attention to relevant information and tasks as well as reduce distractions during instruction ([<reflink idref="bib16" id="ref37">16</reflink>]; [<reflink idref="bib18" id="ref38">18</reflink>]), an approach supported by cognitive load theory ([<reflink idref="bib44" id="ref39">44</reflink>]). To increase student behavioral attention to academic tasks, the Engaged Learners program included empirically-supported behavioral interventions grounded in behavioral psychology ([<reflink idref="bib18" id="ref40">18</reflink>]) that train teachers to (a) explicitly teach adaptive behaviors and (b) manipulate or modify environmental antecedents and behavioral contingencies for students. More specifically, we included the following strategies due to their strong empirical support in school settings: (a) visual schedule to support classroom routines (e.g., [<reflink idref="bib13" id="ref41">13</reflink>]; [<reflink idref="bib42" id="ref42">42</reflink>]), (b) taught and practiced classroom expectations ([<reflink idref="bib14" id="ref43">14</reflink>]; [<reflink idref="bib42" id="ref44">42</reflink>]), and (c) high rates of behavior-specific praise paired with a token economy to reinforce positive behaviors ([<reflink idref="bib15" id="ref45">15</reflink>]).</p> <p>Additionally, the Engaged Learners program included instruction in the use of self-regulation strategies, based on strong empirical evidence suggesting that such strategies improve academic and behavioral outcomes ([<reflink idref="bib8" id="ref46">8</reflink>]; [<reflink idref="bib14" id="ref47">14</reflink>]). Self-regulation strategy instruction aims to develop students' self-regulatory behaviors by helping them establish, monitor, and reflect on academic and behavior-based goals throughout the reading lessons ([<reflink idref="bib9" id="ref48">9</reflink>]; [<reflink idref="bib14" id="ref49">14</reflink>]). This is accomplished through explicit instruction in self-regulation learning strategies and providing feedback at the end of every lesson, both of which have been shown to improve outcomes ([<reflink idref="bib9" id="ref50">9</reflink>]).</p> <hd id="AN0194392927-4">Study Purpose and Research Questions</hd> <p>Our aim was to address the need to support upper elementary students with reading and behavioral attention challenges during small-group reading instruction. Consistent with the multiple deficit model, which posits that these challenges often co-occur due to shared risk factors ([<reflink idref="bib33" id="ref51">33</reflink>]; [<reflink idref="bib37" id="ref52">37</reflink>]), we designed this intervention to simultaneously address both domains. Whereas the phenotype hypothesis would anticipate cross-domain improvements from targeting a single underlying deficit ([<reflink idref="bib55" id="ref53">55</reflink>]), the multiple deficit model predicts that targeting both reading and behavioral attention may be necessary to produce improvements across outcomes. In this context, we focused on behavioral attention rather than cognitive measures of attention (e.g., task-based measure of sustained attention) because our intervention is behavioral in nature and designed for classroom application. We included students with elevated levels of behavioral inattention, without requiring a diagnostic classification, given the strong association between behavioral inattention and RD as well as the dimensional nature of behavioral inattention. Additionally, our theory of change was influenced by cognitive load theory ([<reflink idref="bib44" id="ref54">44</reflink>]), which suggests that improving behavioral attention during instruction can free up limited cognitive resources for learning.</p> <p>To address our aim, we randomized Grade 3–5 students with reading and behavioral attention challenges to one of three conditions: a researcher-delivered reading intervention with Engaged Learners (READ + ENGAGE), a researcher-delivered reading intervention without Engaged Learners (READ), or a Business-as-Usual (BaU) condition. The BaU condition students received instruction as determined by their schools without input or support from the research team. This design allowed us to address the following research questions: (<reflink idref="bib1" id="ref55">1</reflink>) What were the effects of the READ + ENGAGE condition compared to the READ condition on behavioral attention as measured by interventionist surveys and direct observations? (<reflink idref="bib2" id="ref56">2</reflink>) What were the effects of the READ + ENGAGE and READ conditions compared to the BaU condition and READ + ENGAGE condition compared to the READ condition on behavioral attention as measured by English language arts (ELA) teachers? (<reflink idref="bib3" id="ref57">3</reflink>) What were the effects of the READ + ENGAGE and READ conditions compared to the BaU condition and the READ + ENGAGE condition compared to the READ condition on reading outcomes?</p> <p>Given the theoretical rationale and strong empirical evidence to support the impact of Engaged Learners on behavioral outcomes, we hypothesized that the READ + ENGAGE condition would significantly outperform the READ condition on an interventionist survey and direct observations of behavioral attention (e.g., [<reflink idref="bib7" id="ref58">7</reflink>]; [<reflink idref="bib45" id="ref59">45</reflink>]; [<reflink idref="bib54" id="ref60">54</reflink>]). As we did not provide behavioral attention supports outside the context of the reading intervention, we hypothesized that improvements in behavioral attention would not generalize to the ELA teacher reports of the general education setting. We also aimed to add to the limited intervention research investigating the theoretical implications of a combined reading and behavioral attention intervention (e.g., [<reflink idref="bib7" id="ref61">7</reflink>]; [<reflink idref="bib54" id="ref62">54</reflink>]) by exploring whether this approach (i.e., READ + ENGAGE) would outperform reading-only (i.e., READ) and BAU conditions on reading outcomes. Given the broader reading intervention literature indicates that interventions for upper elementary students with reading challenges have been associated with small, often non-statistically significant effects on reading measures ([<reflink idref="bib12" id="ref63">12</reflink>]), and considering our sample size, we did not expect to find statistically significant differences between conditions on reading outcomes. However, we anticipated a pattern of effect sizes favoring both the READ + ENGAGE and READ conditions over the BaU condition. Despite limited empirical support for combined interventions improving reading outcomes beyond reading-only interventions, we also hypothesized that effect sizes would favor the READ + ENGAGE condition relative to READ, as the integrated behavior supports were intended to free up cognitive resources for engagement with reading.</p> <hd id="AN0194392927-5">Method</hd> <p></p> <hd id="AN0194392927-6">Setting and Participants</hd> <p></p> <hd id="AN0194392927-7">Schools</hd> <p>Six urban schools from one school district within the Rocky Mountain region of the United States participated in this study. Across the six schools, the average number of students equaled 531 (<emph>SD</emph> = 145) with 55.7% (<emph>SD</emph> = 31) qualifying for free or reduced-price lunch, 12% (<emph>SD</emph> = 4.1) qualifying for special education services, and 22.1% (<emph>SD</emph> = 15) meeting the multilingual learner criteria. On average, the student population at each school equaled 37.6% (<emph>SD</emph> = 25.5) White, non-Hispanic; 35.7% (<emph>SD</emph> = 23.2) Hispanic; 16% (<emph>SD</emph> = 16.2) Black, non-Hispanic; 7.2% (<emph>SD</emph> = 3.4) multiple races; 2.6% (<emph>SD</emph> = 1.1) Asian; and 0.7% (<emph>SD</emph> = 0.6) American Indian or Alaskan.</p> <hd id="AN0194392927-8">Screening and randomization</hd> <p>To identify students with co-occurring reading and behavioral attention challenges, we first screened all Grade 3–5 students (<emph>n</emph> = 900) for RD with a 3-minute group-administered measure of reading fluency and comprehension, the Test of Silent Reading Efficiency and Comprehension (TOSREC; [<reflink idref="bib50" id="ref64">50</reflink>]). Two schools asked that we not include Grade 3 students in the study. Students who scored at or below a 90-standard score (25th percentile) qualified for a RD and proceeded to the second gate (<emph>n</emph> = 444). Next, we asked ELA teachers to respond to the nine behavioral inattention items of the Strength and Weaknesses of Attention-Deficit/Hyperactivity Symptoms and Normal Behaviors Scale (SWAN; [<reflink idref="bib43" id="ref65">43</reflink>]). Each school's ELA teachers sent home parent consent forms to the 12 students in each grade with the highest SWAN scores (i.e., elevated behavioral inattention). We did not screen for a formal ADHD diagnosis or medication. Schools could elect to send home additional parent consent forms (rank ordered from highest to lowest SWAN scores) if a parent or guardian did not respond or declined the intervention. This process resulted in 159 students randomized 1:1:1, blocked on school and grade.</p> <p>Our aim was to create three balanced treatment groups within each school/grade block and also allocate all consented and qualified students, requiring that we create three clusters of similar cases within each of 16 very small samples of differing sizes. For this, we employed a divisive hierarchical clustering technique to create three clusters of equal size within blocks, using the "diana" function in R's "clustering" package. We used "plot" to visualize the data structure as the total sample was divided into clusters. Divisive hierarchical clustering creates clusters in a top-down manner, dividing the overall sample into smaller clusters in a step-like manner according to locally optimal decisions. This may not always lead to the absolute best overall clustering solution; however, it provides a practical approach to identifying clusters within complex datasets. It makes "good enough" choices to efficiently partition the data rather than searching for the absolute best split in every iteration ([<reflink idref="bib20" id="ref66">20</reflink>]).</p> <hd id="AN0194392927-9">Participants</hd> <p>Table 1 provides the sample's demographic information by condition. There were no statistically significant associations between condition assignment and TOSREC scores: <emph>F</emph>(<reflink idref="bib2" id="ref67">2</reflink>, 127) =.295, <emph>p</emph> =.75; SWAN behavioral inattention scores: <emph>F</emph>(<reflink idref="bib2" id="ref68">2</reflink>, 127) = 0.403, <emph>p</emph> =.82; race/ethnicity: χ2 (<reflink idref="bib8" id="ref69">8</reflink>) = 9.405, <emph>p</emph> =.31; or special education status: χ2 (<reflink idref="bib2" id="ref70">2</reflink>) = 0.283, <emph>p</emph> =.87. The attrition rate for the READ + ENGAGE, READ, and BaU conditions equaled 17.85% (<emph>n</emph> = 10), 22.22% (<emph>n</emph> = 12), and 14.29% (<emph>n</emph> = 7), respectively. The overall attrition rate was 18.24% (<emph>n</emph> = 29). Student attrition was due to (a) scheduling conflicts (<emph>n</emph> = 23); (b) students moving to a different school (<emph>n</emph> = 3); (c) parent decision to remove their child from the study (<emph>n</emph> = 1); and (d) following randomization, the student was identified as having an intellectual disability (<emph>n</emph> = 2). Students who attrited were compared to students who remained to investigate the effects of attrition. The attrited students had mean TOSREC and SWAN screening scores of 76.03 and 11.69 respectively; the non-attrited students had mean TOSREC and SWAN screening scores of 74.04 and 10.18, respectively. There was no association between attrition TOSREC: <emph>F</emph> (<reflink idref="bib1" id="ref71">1</reflink>, 157) =.85, <emph>p</emph> =.36, or SWAN: <emph>F</emph>(<reflink idref="bib1" id="ref72">1</reflink>, 157) =.74, <emph>p</emph> =.39 screening scores.</p> <p>Table 1. Demographic Characteristics of the Analytic Sample</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left" /><th align="left" colspan="2">Overall Sample</th><th align="left" colspan="2">BaU</th><th align="left" colspan="2">READ</th><th align="left" colspan="2">READ + ENGAGE</th></tr><tr><th align="left">Variables</th><th align="left"><italic>n</italic></th><th align="left">%</th><th align="left"><italic>n</italic></th><th align="left">%</th><th align="left"><italic>n</italic></th><th align="left">%</th><th align="left"><italic>n</italic></th><th>%</th></tr></thead><tbody><tr><td>Grade</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3rd</td><td>37</td><td>28.5</td><td>12</td><td>28.6</td><td>13</td><td>31.0</td><td>12</td><td>26.1</td></tr><tr><td>4th</td><td>45</td><td>34.6</td><td>13</td><td>31.0</td><td>16</td><td>38.1</td><td>16</td><td>34.8</td></tr><tr><td>5th</td><td>48</td><td>36.9</td><td>17</td><td>40.5</td><td>13</td><td>31.0</td><td>18</td><td>39.1</td></tr><tr><td>Gender</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Male</td><td>71</td><td>54.6</td><td>22</td><td>52.4</td><td>26</td><td>61.9</td><td>23</td><td>50.0</td></tr><tr><td>Female</td><td>59</td><td>45.4</td><td>20</td><td>47.6</td><td>16</td><td>38.1</td><td>23</td><td>50.0</td></tr><tr><td>Race</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>White</td><td>35</td><td>26.9</td><td>10</td><td>23.8</td><td>14</td><td>33.3</td><td>11</td><td>23.9</td></tr><tr><td>Black</td><td>28</td><td>21.5</td><td>10</td><td>23.8</td><td>6</td><td>14.3</td><td>12</td><td>26.1</td></tr><tr><td>Hispanic</td><td>57</td><td>43.8</td><td>20</td><td>47.6</td><td>20</td><td>47.6</td><td>17</td><td>37.0</td></tr><tr><td>Two or More</td><td>9</td><td>6.9</td><td>2</td><td>4.8</td><td>1</td><td>2.4</td><td>6</td><td>13.0</td></tr><tr><td>Native American</td><td>1</td><td>0.8</td><td /><td /><td>1</td><td>2.4</td><td /><td /></tr><tr><td>ELL</td><td>19</td><td>14.6</td><td>9</td><td>21.4</td><td>6</td><td>14.3</td><td>4</td><td>8.7</td></tr><tr><td>Special Education</td><td>28</td><td>21.5</td><td>10</td><td>23.8</td><td>8</td><td>19.0</td><td>10</td><td>21.7</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note.</emph> BaU = Business-as-Usual; ELL = English language learner.</p> <hd id="AN0194392927-10">Measures</hd> <p>Assessment team members completed 90-minute and 30-minute trainings to deliver the individually- and group-administered reading assessments, respectively. All assessment team members demonstrated 100% administration and scoring reliability with the assessment director. We masked student condition from the research team during all test administration, scoring, and data entering. We coded student behavioral attention and fidelity using video-recorded sessions.</p> <hd id="AN0194392927-11">Word reading</hd> <p> <bold>Test of Word Reading Efficiency – Second Edition (TOWRE-2).</bold> The Test of Word Reading Efficiency–2 (TOWRE-2; [<reflink idref="bib46" id="ref73">46</reflink>]) sight word efficiency (SWE) and phonemic decoding efficiency (PDE) subtests measure a student's ability to accurately read real and decodable nonwords, respectively. Both subtests are individually administered with students reading aloud from a list of increasingly challenging words for 45 seconds. Results are reported in standard scores. The test-retest reliability coefficient is.87.</p> <hd id="AN0194392927-12">Mid transfer vocabulary and reading comprehension</hd> <p>We identified items from untaught adventure check points in the Voyager Passport curriculum to create grade-specific mid-transfer measures of vocabulary and reading comprehension questions. In total, there were three forms for vocabulary and reading comprehension (one form per Grade 3–5). Each form measured skills targeted in the curriculum and was presented in a similar format to previously taught lessons ([<reflink idref="bib19" id="ref74">19</reflink>]).</p> <p>The untimed reading comprehension measure had students read two novel grade-level passages and respond to five questions per passage. Questions asked students to identify the main idea, summarize, or make inferences. Response formats included multiple-choice, fill-in-the-blank, or short-answer items. The vocabulary measure included word banks with five sentences per word bank. Students filled in a missing word in each sentence with a word from the word bank. Each vocabulary measure had 20 items.</p> <hd id="AN0194392927-13">Reading comprehension</hd> <p> <bold>Test of Silent Reading Efficiency and Comprehension (TOSREC).</bold> The TOSREC ([<reflink idref="bib50" id="ref75">50</reflink>]) is a 3-minute group-administered test of reading fluency and comprehension. Students silently read as many sentences as possible and verify their accuracy (circling "yes" or "no"). Results are reported in standard scores. The alternate-form reliability coefficients exceed.85 across all grades and forms.</p> <p> <bold>Gates-MacGinitie Reading Test – Fourth Edition (GMRT).</bold> The GMRT Reading Comprehension subtest ([<reflink idref="bib32" id="ref76">32</reflink>]) is a 35-minute test with 11 narrative and expository passages ranging from three to 15 sentences. Each passage has three to six multiple-choice questions that test literal and inferential understanding. Internal consistency reliability ranges from.91 to.93, and the Kuder-Richardson reliability statistic ranges from.92 to.93.</p> <hd id="AN0194392927-14">Behavior</hd> <p> <bold>Strength and Weaknesses of Attention-Deficit/Hyperactivity Symptoms and Normal Behaviors Scale (SWAN).</bold> The SWAN ([<reflink idref="bib43" id="ref77">43</reflink>]) is a 30-item teacher survey measuring hyperactivity and inattentiveness on a 7-point scale. At screening and posttest, ELA teachers completed the nine behavioral inattention items on the SWAN. Each item is scored from +3 to −3 with higher scores representing higher levels of behavioral inattention. Results are presented in raw scores which were used for score-based groupings. The SWAN does not provide score thresholds for at-risk or diagnostic classification. The test-retest reliability and internal consistency coefficients are.76 and.95, respectively ([<reflink idref="bib26" id="ref78">26</reflink>]).</p> <p> <bold>The Behavior Assessment System for Children-3 (BASC-3) Teacher Rating Scale (TRS).</bold> The BASC-3 TRS ([<reflink idref="bib38" id="ref79">38</reflink>]) is a 156-question measure with a 4-point scale of adaptive and challenging behaviors in the school setting. At pre and posttest, interventionists in the READ + ENGAGE and READ conditions completed the survey. We present the Attention Problems Subscale with higher scores representing more attention challenges. Results are converted from raw scores to T-scores with Attention Problems scores of 60–69 and over 70 representing at-risk and clinically significant levels, respectively. The median reliability coefficients for the full scale range from.86 to.94.</p> <p> <bold>Direct Observation of Behavioral Attention.</bold> Graduate assistants (GA) masked to study purpose coded each student's behavioral attention from a randomly selected pretest (baseline) and posttest (last 2 weeks) video-recorded lesson. Coders used a duration recording system to record the start and end time of attentive behaviors. To calculate the percentage of attentive time, we divided the total time the student was attentive by the total session time and multiplied by 100. The definition of student behavioral attention is based on the SWAN inattention items and modified to be relevant to behaviors witnessed within small-group reading instruction: (a) having eyes oriented toward the speaker or assignment, (b) working on an assigned task, (c) using the materials appropriately, and/or (d) interacting with teachers or peers about relevant academic topics. GAs only coded behavioral attention during reading instruction and not during the Engaged Learners activities (e.g., review goals) to ensure consistency across conditions.</p> <hd id="AN0194392927-15">Procedures</hd> <p>After receiving Institutional Review Board approval from the university and the participating district, researcher-hired interventionists delivered 30–40-minute intervention lessons for 3–5 days per week from October to February. Intervention group sizes ranged from two to four students and took place outside of the core reading block. Both the READ + ENGAGE and READ conditions implemented the Voyager Passport reading intervention curriculum ([<reflink idref="bib48" id="ref80">48</reflink>]). The READ + ENGAGE condition was the only condition to integrate the Engaged Learners program into Voyager Passport.</p> <hd id="AN0194392927-16">Reading intervention curriculum</hd> <p>The Voyager Passport curriculum featured 12 adventures, each consisting of 10 lessons focused on a central theme (e.g., human anatomy and health, world travel). Each adventure began with a short <emph>Adventure Starter</emph> to introduce the unit topic. Lessons 1–4 and 6–9 included <emph>Word Work</emph> and <emph>Read to Understand</emph>. Word work included activities related to letter and sound identification, word reading, sight words, and spelling. Read to understand included a text-based lesson focused on fluency, vocabulary, and comprehension. Lessons 5 and 10 had <emph>Adventure Checkpoints</emph> to monitor student progress. A description of the Voyager Passport curriculum can be found at https://<ulink href="http://www.voyagersopris.com/products/reading/voyager-passport/overview">www.voyagersopris.com/products/reading/voyager-passport/overview</ulink>.</p> <hd id="AN0194392927-17">Engaged learners program</hd> <p>The READ + ENGAGE condition began with a 2-week baseline to collect pretest data, followed by two Engaged Learners training lessons, and then integrated daily lessons.</p> <p> <bold>Baseline</bold>. The 2-week baseline included the delivery of Voyager Passport without the Engaged Learners program (i.e., procedures were identical to the reading-only intervention condition) to allow our team to collect pretest behavioral attention data (i.e., surveys, observations) prior to the Engaged Learners program implementation.</p> <p> <bold>Overview of the Training Lessons</bold>. The Engaged Learners program had two training lessons for instructors to teach and practice the components with the students. The first training lesson introduced the (a) visual schedule to support routines, (b) group expectations, and (c) token economy to reinforce expected behaviors. The second training lesson reviewed the previous lesson's components and introduced the self-regulation component.</p> <p> <bold>Lesson 1.</bold> The first training lesson introduced the students to the visual schedule, token economy, and group expectations. This lesson began with the interventionist modeling the token economy by delivering individual points (independent group contingencies) paired with high rates of behavior-specific praise. Interventionists delivered points to the students by writing a tally mark on a sticky note placed in front of each student and pairing that point with behavior-specific praise (e.g., "That is a point for having your eyes are on the speaker."). The interventionist then introduced the visual schedule by pointing to the schedule and stating each activity for the lesson. Following each activity, the interventionist marked the activity on the schedule with a check mark. Next, the interventionist introduced the group expectations: (a) <emph>Follow Directions</emph>, (b) <emph>Work Hard</emph>, and (c) <emph>Be Nice</emph>. Then students identified positively phrased behavioral examples (e.g., keep eyes on the speaker) for each expectation and stated a reason why it is important to follow the group expectations. The expectations with student-created behavioral examples were posted. Students then completed a short reading lesson. During the last 3 minutes of the group, students counted their points. For every 10 points earned, students filled in one circle on a five-circle point chart. All students were able to trade in their completed point charts for a prize (e.g., fidget toy) by the end of Lesson 2.</p> <p> <bold>Lesson 2.</bold> The second training lesson began with a review of Lesson 1 components followed by an introduction to the self-regulation form. The self-regulation form (see Supplemental File Figure S1 in the online supplemental material) included (a) three goals that mirrored the class expectations, (b) a place for each student to write their own fourth goal, (c) a place to self-record their self-evaluation for each goal with a score of 0 (None of the time I meet my goal), 1 (Sometimes I met my goal), or 2 (Most of the time I met my goal), and (d) a place for a written reflection that will also be the goal for the next lesson (i.e., Next reading class, I will ___). The interventionist introduced the goals and explained that at the end of the lesson the students will (a) evaluate themselves on their four goals, (b) earn bonus points if the interventionist agreed with their evaluation partially (1 bonus point) or fully (2 bonus points), and (c) reflect on their behavior by writing what they will do next reading lesson to improve their behavior or reading outcomes.</p> <p>After the interventionist explained the self-regulation form, the students discussed and wrote their fourth goal on the self-regulation form. Next, groups completed a short reading lesson. With the final 10 minutes, the students completed the following steps (a) self-evaluated their performance on their self-regulation form, (b) reviewed their self-evaluation with the interventionist, (c) wrote a reflection on their self-regulation form, (d) summed the tally marks on their sticky note with the points from their self-regulation form, and (e) filled in circles on their prize chart. Completed point charts were exchanged for a prize (e.g., fidget toy).</p> <p> <bold>Daily Lessons.</bold> Following the two training lessons, interventionists embedded Engaged Learners into the daily Voyager Passport reading lesson. Engaged Learners included before- (2–3 min), during-, and after-reading lesson activities (2–3 min). Throughout the lesson, interventionists implemented the token economy with high rates of behavior-specific praise. In the before-reading activities, interventionist first pointed to the visual scheduled and stated the lesson's activities. Next, the interventionist stated the group expectations and students provided a behavioral example of each expectation. Finally, students read their individual goals. The during-reading activities were designed to be fully integrated into the reading lesson, thus taking minimal time away from reading instruction. These activities included the interventionist: (a) explicitly stating behavior expectations prior to tasks; (b) using high rates of behavior-specific praise (the delivery of explicit praise for appropriate behaviors immediately after a behavior occurs); and (c) implementing a token economy system. During the after-reading activities, (as described in the Lesson 2 description), students completed their self-evaluation, the interventionist gave bonus points based on the extent they agreed with the student's self-evaluation, and the student wrote their reflection. Students then added their points, filled in point charts, and traded in completed point charts for a prize.</p> <hd id="AN0194392927-18">Interventionists</hd> <p>Twelve interventionists delivered lessons. Each interventionist was responsible for one to four groups in either the READ + ENGAGE or READ condition. The six READ + ENGAGE condition interventionists included two GAs, two paraprofessionals, and two community members. Interventionists' highest degree earned included a high school diploma (<emph>n</emph> = 2), bachelor's degree (<emph>n</emph> = 3), and master's degree with teaching license (<emph>n</emph> = 1). Two interventionists identified as female, two identified as male, and two identified as nonbinary. Interventionist identified as White and Latinx (<emph>n</emph> = 1), Hispanic, American Indian, and White (<emph>n</emph> = 1), and White, non-Hispanic (<emph>n</emph> = 5).</p> <p>The six READ condition interventionists included one GA, two paraprofessionals, and three community members. Interventionists' highest degree earned included a high school diploma (<emph>n</emph> = 3), bachelor's degree (<emph>n</emph> = 1), and master's degree with teaching license (<emph>n</emph> = 1). Five interventionists identified as female, and one as male. Interventionists identified as White, non-Hispanic (<emph>n</emph> = 5) and White and American Indian (<emph>n</emph> = 1).</p> <hd id="AN0194392927-19">Interventionist Training and Coaching</hd> <p>All interventionists received a 5-hour reading instruction training. After 2 weeks of reading lessons (i.e., baseline), the READ + ENGAGE interventionists received an additional 5-hour Engaged Learners program training. All trainings followed the same sequential procedure for each component of the READ + ENGAGE and READ condition: (a) provide overview, (b) model (including sample videos), (c) guided practice, and (d) independently deliver components. Interventionist demonstrated a minimum of 90% proficiency in each component prior to independently delivering instruction. Bi-weekly—or as needed—coaching was provided in person or remotely (via recorded lessons) by doctoral students or the first author.</p> <hd id="AN0194392927-20">Intervention Fidelity</hd> <p>GAs coded video-record sessions for fidelity to Voyager Passport and Engaged Learners. We randomly selected 20% of sessions, blocked on school and month (i.e., a minimum of 20% of sessions delivered per group and month of intervention) to be coded. To establish reliability, we used the gold standard method ([<reflink idref="bib21" id="ref81">21</reflink>]), where coders independently reach 90% reliability with the lead coder. To prevent coder drift, we re-established reliability at the coding halfway point. Coders evaluated the implementation of the Voyager Passport lessons and the Engaged Learners program, as well as a lesson global quality ranking (e.g., [<reflink idref="bib47" id="ref82">47</reflink>]). Fidelity scores ranged from 1–4 (higher scores represented higher levels of fidelity). The global quality fidelity score was based on a holistic evaluation of adherence to principles of effective instruction (e.g., uses time efficiently, clearly explains concepts) and classroom management (e.g., quickly and efficiently redirects off-task behavior, engages all students in the lesson).</p> <p>For the READ + ENGAGE condition, the mean implementation score across components and interventionists for Voyager Passport was 3.94 (<emph>SD</emph> = 0.15, range: 3.43 to 4.00) with a global quality score of 3.56 (<emph>SD</emph> = 0.44, range: 2.60 to 4.00). Adherence to the Engaged Learners program equaled 3.90 (<emph>SD</emph> = 0.19, range: 3.38 to 4.00). For the READ condition, the mean Voyager Passport implementation score across components and interventionists equaled 3.98 (<emph>SD</emph> = 0.06, range: 3.83 to 4.00) with a mean global quality score of 2.79 (<emph>SD</emph> = 0.37, range: 2.42 to 3.83). We also evaluated the extent to which the READ condition interventionists implemented Engaged Learners components and found a mean score of 1.00 (<emph>SD</emph> = 0.00, range: 1.00 to 1.00). This suggests, as expected, that the READ condition interventionists rarely or never implemented components associated with the Engaged Learners program.</p> <hd id="AN0194392927-21">Inter-Observer Agreement (IOA) for Direct Observation of Behavioral Attention</hd> <p>The first author served as a lead trainer to the GAs for behavioral attention coding. The 2-hour training included defining relevant variables, identifying examples and nonexamples, and practice coding of a sample video. Each GA coder then completed additional independent practice assignments until reaching a minimum of 90% inter-observer agreement (IOA) with the lead trainer. All coders obtained the 90% IOA threshold by their second attempt. IOA was calculated using gross agreement for total duration recording, which equals the smaller measurement divided by the larger measurement multiplied by 100 ([<reflink idref="bib27" id="ref83">27</reflink>]). Blocking on school and condition, we randomly selected a minimum of 20% of pre and posttest READ + ENGAGE and READ observations for IOA double-coding. In total, we calculated IOA for 23.91% and 25.00% of the READ + ENGAGE and READ condition observations, respectively. IOA across all READ + ENGAGE and READ conditions averaged 93.56% (<emph>SD</emph> = 5.73, range: 79.43–99.09) and 86.57% (<emph>SD</emph> = 8.14, range: 74.42–98.32), respectively.</p> <hd id="AN0194392927-22">School-Provided Reading and Behavior Support Interventions</hd> <p>We collected data related to school-provided reading interventions delivered outside the core reading instruction and behavior support interventions delivered at any point throughout the school day. Data indicated that school personnel delivered at least one reading intervention to 59.52%, 56.52% and 57.14% of the BaU, READ + ENGAGE and READ condition students, respectively. On average, the BaU, READ + ENGAGE, and READ condition students received 142.02 (<emph>SD</emph> = 139.62), 97.28 (<emph>SD</emph> = 113.20) and 89.05 (<emph>SD</emph> = 106.35) weekly minutes of a school-provided reading intervention, respectively. Schools also provided at least one behavior-support intervention to 26.19%, 28.26%, and 11.90% of the BaU, READ + ENGAGE, and READ condition students, respectively. The types of school-delivered behavior interventions varied greatly and included variations of a check-in/check-out plan ([<reflink idref="bib24" id="ref84">24</reflink>]), teacher-created plans (e.g., walk in the hallway with a teacher aide), social skill lessons, and weekly check-ins (e.g., social worker, school counselor).</p> <hd id="AN0194392927-23">Preliminary Analyses</hd> <p>We fit several preliminary models. First, we estimated empty means models for all outcomes to estimate variances across levels of the data (i.e., interventionist, teacher, school) and to determine intraclass correlations (icc) across outcomes and levels (Supplemental File Table S1). Clustering at the interventionist level was nominal across all outcomes (icc <.03) except TOWRE-2 PDE (icc =.07). Intraclass correlations at the teacher level ranged from.00 (mid-transfer reading comprehension and SWAN) to.13 (TOWRE-2 PDE). School-level clustering was trivial apart from scores on the TOSREC (icc =.16) and the SWAN (icc =.08). We tailored our analytic models by outcome to reflect patterns of clustering.</p> <p>Rates of overall and differential attrition were very low (≈ 1%) across outcomes. With two exceptions, groups in the analytic sample were comparable based on guidelines of the What Works Clearinghouse (see Supplemental File Table S2 for further details). Groups in the READ + ENGAGE vs READ contrast on GMRT scores were not balanced. The effect size for the difference in Time 1 scores was.34, indicating that the READ group had higher GMRT pretest scores than the READ + ENGAGE group. Scores at pretest for groups in the READ + ENGAGE and READ groups were also not balanced on BASC-3 Attention Problems measure completed by the interventionists during the first 2 weeks of instruction. The effect size was.47, indicating that the READ + ENGAGE group scored higher (i.e., more behavioral attention challenges) at pretest than the READ group by almost one-half of a standard deviation. We included pretest covariates for all outcomes to address imbalance. For the two contrasts involving extreme Time 1 imbalances, results should be considered with caution.</p> <hd id="AN0194392927-24">Analysis</hd> <p>We addressed the research questions by fitting multilevel regression models. Nesting was determined by patterns of clustering, as described earlier. Final analytic models were constructed accordingly. A baseline three-level fully nested main effects model was estimated as</p> <p>Graph</p> <p> <ephtml> <math display="block" xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mrow><mi>i</mi><mi>j</mi><mi>k</mi></mrow></msub><mo>=</mo><msub><mi>Y</mi><mn>000</mn></msub><mo>+</mo><msub><mi>Y</mi><mn>100</mn></msub><mo stretchy="false">(</mo><mi>P</mi><mi>r</mi><mi>e</mi><mi>t</mi><mi>e</mi><mi>s</mi><mi>t</mi><msub><mo stretchy="false">)</mo><mrow><mi>i</mi><mi>j</mi><mi>k</mi></mrow></msub><mo>+</mo><mo>+</mo><mspace width="0.25em" /><msub><mi>Y</mi><mn>200</mn></msub><mo stretchy="false">(</mo><mi>R</mi><mi>E</mi><mi>A</mi><mi>D</mi><mo>+</mo><mi>E</mi><mi>N</mi><mi>G</mi><mi>A</mi><mi>G</mi><mi>E</mi><msub><mo stretchy="false">)</mo><mrow><mi>i</mi><mi>j</mi><mi>k</mi></mrow></msub><mo>+</mo><msub><mi>Y</mi><mn>300</mn></msub><mo stretchy="false">(</mo><mrow><mi>R</mi><mi>E</mi><mi>A</mi><mi>D</mi></mrow><msub><mo stretchy="false">)</mo><mrow><mi>i</mi><mi>j</mi><mi>k</mi></mrow></msub><mo>+</mo><msub><mi>e</mi><mrow><mi>i</mi><mi>j</mi><mi>k</mi></mrow></msub><mo>+</mo><msub><mi>r</mi><mrow><mn>0</mn><mi>j</mi><mi>k</mi></mrow></msub><mo>+</mo><msub><mi>u</mi><mrow><mn>00</mn><mi>k</mi></mrow></msub></math> </ephtml> where <emph>READ</emph><emph>+</emph><emph>ENGAGE<subs>ijk</subs></emph> and <emph>READ<subs>ijk</subs></emph> were student-level dummy-coded variables representing, respectively, READ + ENGAGE (coded 1) versus BaU (coded 0) and READ (coded 1) versus BaU (coded 0). <emph>Pretest<subs>ijk</subs></emph> was a mean-centered covariate (pretest measure of the outcome), and <emph>ε<subs>ijk,</subs> r</emph>0<emph>jk</emph>, <emph>μ<subs>00k</subs></emph> represent random effects at the student, teacher, and school levels. The average treatment effect (ATE) is indicated by <ephtml> <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mn>200</mn></msub></math> </ephtml> and <ephtml> <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mn>300</mn></msub></math> </ephtml> . All analyses were run with "lme4" ([<reflink idref="bib1" id="ref85">1</reflink>]) and "emmeans" packages ([<reflink idref="bib28" id="ref86">28</reflink>]) in R. We estimated effect sizes (Hedge's g) for the main effect of intervention as the ratio between the model-derived treatment coefficients and the unadjusted pooled within-group standard deviation across conditions at posttest ([<reflink idref="bib51" id="ref87">51</reflink>]). False discovery rates associated with multiple comparisons (i.e., Type 1 error) were controlled using the Benjamini-Hochberg correction ([<reflink idref="bib2" id="ref88">2</reflink>]). Adjusting <emph>p</emph> values for multiple group comparisons (READ vs BaU, READ + ENGAGE vs BaU, READ + ENGAGE vs READ) is necessary to control the risk of making Type I errors. Without this adjustment, the likelihood of incorrectly rejecting the null hypothesis (i.e., detecting a significant difference when none exists) increases with the number of comparisons, as each test carries a risk of error. Consequently, as the number of tests grows, so does the cumulative probability of making a Type I error. This study's design, hypotheses, and data analytic plan were not pre-registered.</p> <hd id="AN0194392927-25">Results</hd> <p>Descriptive statistics are presented in Supplemental File Table S3. Effect size estimates are in Table 2. Two behavioral attention outcomes involving the READ + ENGAGE and READ groups differed significantly from 0 and favored the READ + ENGAGE group. The READ + ENGAGE group outscored the READ condition by 3.98 points (T-Score) on the interventionist-completed BASC-3 Attention Problems survey at posttest (<emph>p</emph> =.03; <emph>g</emph> = -0.43 [-0.83, −0.03]), with a negative effect size indicating a reduction of attention challenges (i.e., more attentive). The READ + ENGAGE group also outscored the READ condition by 24.40 points (based on percentage of time) on the amount of time spent engaged during a reading lesson at posttest (<emph>p</emph> <.01; <emph>g</emph> = 1.14 [0.74, 1.55]), with a positive effect size indicating higher levels of behavioral attention.</p> <p>Table 2. Effect Size Estimates for the Main Effect of Intervention</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left" /><th align="left" colspan="3">READ vs. BaU</th><th align="left" colspan="3">READ + ENGAGE vs BaU</th><th align="left" colspan="3">READ + ENGAGE vs. READ</th></tr><tr><th align="left">Variables</th><th align="left">Impact</th><th align="left"><italic>P</italic> Value (fdr <italic>p</italic> value)</th><th align="left"><italic>g</italic> [95% CI]</th><th align="left">Impact</th><th align="left"><italic>P</italic> Value (fdr <italic>p</italic> value)</th><th align="left"><italic>g</italic> [95% CI]</th><th align="left">Impact</th><th align="left"><italic>P</italic> Value (fdr p-value)</th><th align="left"><italic>g</italic> [95% CI]</th></tr></thead><tbody><tr><td><bold>Reading Outcomes</bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>TOSREC</td><td>5.85</td><td>.01 (.03)</td><td>0.44 [.10,.78]</td><td>1.66</td><td>.46 (.46)</td><td>0.13 [−.21,.47]</td><td>−4.19</td><td>.08 (.11)</td><td>−0.33 [−.68,.03]</td></tr><tr><td>TOWRE PDE</td><td>4.66</td><td>.00 (.00)</td><td>0.33 [.14,.51]</td><td>−0.13</td><td>.92 (.92)</td><td>−0.01 [−.19,.17]</td><td>−4.78</td><td>.00 (.00)</td><td>−0.33 [−.51, −.15]</td></tr><tr><td>TOWRE SWE</td><td>2.99</td><td>.06 (.16)</td><td>0.30 [−.01,.42]</td><td>0.47</td><td>.77 (.77)</td><td>0.03 [−.17,.24]</td><td>−2.53</td><td>.11 (.16)</td><td>−0.17 [-.−.38,.04]</td></tr><tr><td>GMRT RC</td><td>0.90</td><td>.65 (.84)</td><td>0.09 [−.30,.48]</td><td>0.40</td><td>.84 (.84)</td><td>0.04 [−.34,.41]</td><td>−0.51</td><td>.80 (.84)</td><td>−0.05 [−.42,.33]</td></tr><tr><td>Mid-Transfer Vocab</td><td>3.13</td><td>.01 (.04)</td><td>0.53 [.11,.96]</td><td>1.94</td><td>.11 (.17)</td><td>0.32 [−.08,.71]</td><td>−1.20</td><td>.35 (.35)</td><td>−0.21 [−.63,.22]</td></tr><tr><td>Mid-Transfer RC</td><td>1.45</td><td>.01 (.02)</td><td>0.58 [.16,.99]</td><td>0.58</td><td>.26 (.26)</td><td>0.23 [−.17,.62]</td><td>−0.87</td><td>.10 (15)</td><td>−0.33 [−.73,.07]</td></tr><tr><td><bold>Attention Outcomes</bold></td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>SWAN Inattentionab</td><td>−1.19</td><td>.50 (.74)</td><td>−0.13 [−.53,.26]</td><td>−0.62</td><td>.72 (.75)</td><td>−0.07 [−.46,.32]</td><td>−0.57</td><td>.75 (.75)</td><td>−0.06 [−.30,.42]</td></tr><tr><td>BASC Attention Problemsac</td><td /><td /><td /><td /><td /><td /><td>−3.98</td><td>.03</td><td>−0.43 [−.83, −.03]</td></tr><tr><td>Attention Observationd</td><td /><td /><td /><td /><td /><td /><td>24.40</td><td>.00</td><td>1.14 [.74, 1.55]</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <emph>Note.</emph> fdr <emph>p</emph> value = <emph>p</emph> value adjusted for False Discovery Rate. TOSREC = Test of Silent Reading Efficiency and Comprehension ([<reflink idref="bib50" id="ref89">50</reflink>]); TOWRE-2 = The Test of Word Reading Efficiency – 2 ([<reflink idref="bib46" id="ref90">46</reflink>]); PDE = Phonemic Decoding Efficiency; SWE – Sight Word Efficiency; GMRT = Gates-MacGinitie Reading Test – 4th Edition ([<reflink idref="bib32" id="ref91">32</reflink>]); RC = reading comprehension; Vocab = vocabulary; SWAN = Strength and Weaknesses of Attention-Deficit/ Hyperactivity Symptoms and Normal Behaviors ([<reflink idref="bib43" id="ref92">43</reflink>]); BASC = Behavior Assessment System for Children-3 Teacher Rating Scale ([<reflink idref="bib38" id="ref93">38</reflink>]).</item> <item>3 negative effect size indicates more attention (i.e., less inattention). <sups>b</sups>raw score. <sups>c</sups>T-score. <sups>d</sups>Percentage of time.</item> </ulist> <p>Five reading main effect estimates differed from 0, four involving the READ versus BaU contrast, and one involving the READ and READ + ENGAGE groups. All contrasts favored the READ condition. The READ group outscored the BaU by almost 6 points on the TOSREC at posttest (<emph>p</emph> =.03; <emph>g</emph> = 0.44 [0.10, 0.78]). The posttest difference on the TOWRE-2 PDE was 4.66 (<emph>p</emph> <.01; <emph>g</emph> = 0.33 [0.14, 0.51]). Differences on the mid-transfer measures also differed from 0. On the vocabulary measure, the READ group outscored the BaU condition by 3.13 points (<emph>p</emph> =.04; <emph>g</emph> = 0.53 [0.11, 0.96]). The difference on the comprehension measure was 1.45 points (<emph>p</emph> =.02; <emph>g</emph> = 0.58 [0.16, 0.99]). Finally, the READ + ENGAGE and READ groups differed by 4.78 correct items at posttest on the TOWRE-2 PDE (<emph>p</emph> <.01; <emph>g</emph> = - 0.33 [-0.51, - 0.15]).</p> <hd id="AN0194392927-26">Discussion</hd> <p>In this study, we measured the effects of integrating a behavioral attention supports program into reading instruction for upper elementary students with co-occurring reading and teacher-identified behavioral attention challenges. In doing so, this study is the first three-arm RCT to integrate a fully manualized behavioral attention support intervention into an evidence-based reading intervention and compare the intervention's effects to reading-only and BaU conditions. This study is also the largest to date to integrate supports for student behavior (e.g., behavioral attention) into a small-group reading intervention.</p> <hd id="AN0194392927-27">Integrating Behavior Supports Positively Impacts Behavioral Attention</hd> <p>This study produced several meaningful outcomes. As hypothesized, READ + ENGAGE intervention produced statistically significant improvements on both an interventionist survey and direct observations of student behavioral attention compared to the READ condition. First, interventionists reported the students in the READ + ENGAGE condition demonstrated higher levels of behavioral attention (<emph>p</emph> =.03; <emph>g</emph> = -0.43; i.e., less behavioral inattention). The effect size was very similar to the one yielded in Tamm and colleagues' (2017) study examining the effects daily report cards, family training, and medication to support behavioral attention (<emph>p</emph> <.05; <emph>g</emph><emph>=</emph> 0.44).</p> <p>Additionally, the direct observations of student behavioral attention identified that the READ + ENGAGE students demonstrated higher levels of attentive behaviors (<emph>p</emph> <.01; <emph>g</emph> = 1.14). In practical terms, the effect size on the direct observation measure revealed that students in the READ + ENGAGE condition were attentive to the instruction on average 65% of the time, compared to 41% of the time by the READ condition. As hypothesized, the improvements in behavioral attention during small-group reading instruction did not generalize to the general education setting, as indicated by the ELA teacher's SWAN inattention survey (<emph>p</emph> >.05).</p> <hd id="AN0194392927-28">Benefits of Attention Supports Appear Limited to Behavioral Attention Outcomes</hd> <p>We also explored whether the addition of Engaged Learners program to an evidence-based reading intervention would lead to improved reading outcomes compared to a reading-only intervention. Given that our study found a pattern of reading effect sizes where the READ condition was associated with higher performance than the READ + ENGAGE condition (<emph>g</emph> = 0.05–0.33), the results did not support our a priori hypotheses. However, this finding is consistent with previous research (e.g., [<reflink idref="bib45" id="ref94">45</reflink>]; [<reflink idref="bib56" id="ref95">56</reflink>]).</p> <p>We also hypothesized that there would be non-statistically significant positive differences on reading outcomes comparing the READ + ENGAGE and READ conditions to the BaU condition. This hypothesis was supported as we observed a non-statistically significant positive direction of reading effects comparing the READ + ENGAGE to the BaU condition (<emph>g</emph> = -0.01–0.32). We also found statistically significant differences at posttest between students in the READ and BAU conditions (<emph>g</emph> = 0.09–0.58), including on standardized measures of reading such as the TOWRE-2 and TOSREC.</p> <p>There are a few potential explanations for this pattern, which are elaborated on in the limitations and future research section. An initial observation is that students in the READ condition spent more time on reading than students in the READ + ENGAGE condition. Interventionists providing READ + ENGAGE instruction spent 2–3 minutes at the beginning and end of each lesson (4–6 min total) implementing the Engaged Learning components, whereas interventionists in the READ condition spent the entire session focused on reading. While increased behavioral attention during reading in the READ + ENGAGE condition may have compensated for the reduced instructional time, it remains noteworthy that the READ condition offered more actual time focused on reading. Based on cognitive load theory, we developed Engaged Learners to increase behavioral attention and thus reduce extraneous cognitive load. However, the implementation may have inadvertently introduced competing cognitive demands (e.g., hearing frequent behavior-related positive feedback, monitoring behavioral engagement) that competed for students' working memory resources. For students with co-occurring reading and behavioral attention challenges, who are already at higher risk for executive functioning challenges (e.g., attentional control, working memory; [<reflink idref="bib54" id="ref96">54</reflink>]), managing both the cognitive demands of reading instruction and the behavioral attention routines may have exceeded their capacity to efficiently integrate and process instruction in both areas.</p> <p>Another potentially critical explanation relates to potential differences between experimental conditions at pretest. Even though we adjusted posttest scores for differences at pretest and used matched-pair randomization based on pretest performance on the TOSREC and SWAN, there were large pretest group differences on the GMRT between READ + ENGAGE and the READ (<emph>g</emph> = −0.41) and BaU (<emph>g</emph> = −0.29) conditions. There was also a statistically significant difference on the interventionist-completed BASC-3 Attention Problems survey between the READ + ENGAGE and the READ (<emph>g</emph> = 0.47) conditions. Given that students with lower pretest reading and behavioral attention outcomes tend to have more intractable reading challenges (e.g., [<reflink idref="bib31" id="ref97">31</reflink>]; [<reflink idref="bib40" id="ref98">40</reflink>]), these pretest differences may help to explain why the READ condition had a pattern of higher reading effects than the READ + ENGAGE condition.</p> <hd id="AN0194392927-29">Limitations and Future Research</hd> <p>This study presents several limitations and avenues for future research. First, it is possible that the time allocated to implementing Engaged Learners during the reading instruction time (and ultimately less reading instruction dosage) resulted in the READ condition having descriptively larger reading effect sizes than the READ + ENGAGE condition. In order to increase the impact of integrated support models without reducing instructional time, a key area of future research may be to reduce the instructional time spent on Engaged Learners during academic instruction. This could occur through systematically fading supports such as transitioning from individual points (independent group contingencies) to group points (interdependent group behavior) or transitioning from individual self-regulation goals to group goals. Systematically fading the Engaged Learners program after students demonstrate improved behavioral attention, particularly in conjunction with a longer duration study, may both improve behavioral attention and reduce cognitive load, ultimately leading to greater benefits on reading outcomes for a reading with Engaged Learners condition relative to reading-only instruction. Future observation studies could also play a key role in documenting instructional dosage of specific reading and behavioral attention components at a fine-grained level to better understand the association between dosage and reading and behavioral attention outcomes.</p> <p>Additionally, given the heterogeneity within comorbid groups ([<reflink idref="bib5" id="ref99">5</reflink>]; [<reflink idref="bib36" id="ref100">36</reflink>]), future research could include additional cognitive measures (e.g., processing speed, working memory), to provide more detailed participant profiles and increase the understanding of how underlying factors can influence intervention response. More specifically, including additional pretest measures would allow researchers to better understand how learner profiles influence the intervention's efficacy, potentially via an aptitude-by-treatment analysis (e.g., [<reflink idref="bib25" id="ref101">25</reflink>]), leading to more customized interventions.</p> <p>Furthermore, given the empirical evidence in support of interventions that target self-regulation (e.g., [<reflink idref="bib8" id="ref102">8</reflink>]; [<reflink idref="bib14" id="ref103">14</reflink>]), the Engaged Learners program included a self-regulation component. However, developing self-regulatory behaviors is complex, including motivational processes and cognitive and metacognitive activities ([<reflink idref="bib9" id="ref104">9</reflink>]). We acknowledge that some argue that providing external reinforcers (as we included as part of the token economy) could reduce student intrinsic motivation (e.g., [<reflink idref="bib22" id="ref105">22</reflink>]), potentially undermining the benefits of the self-regulation component. Conversely, others argue that for students with little prior success in reading, extrinsic rewards are a critical bridge to allow them to engage in the work, improve their reading, and eventually facilitate build more intrinsic motivation (e.g., [<reflink idref="bib4" id="ref106">4</reflink>]; [<reflink idref="bib6" id="ref107">6</reflink>]; [<reflink idref="bib52" id="ref108">52</reflink>]). To better understand the interplay between including both extrinsic rewards and a self-regulation component, future research could include measures of motivation and self-regulatory learning process as well as conduct observation studies to measure the extent to which teachers directly (e.g., explicit instruction in strategy use) and indirectly (e.g., create learning environment that require self-regulatory learning) support self-regulated learning ([<reflink idref="bib9" id="ref109">9</reflink>]). Future research may also consider monitoring the accuracy of student evaluations on their self-regulation forms relative to their actual performance or teacher evaluations. Such findings may support researchers to better understand the extent to which interventions are able to support students' ability to accurately monitor and evaluate their goals, thus supporting the development of academic instruction with self-regulation components.</p> <p>Finally, pretest groups were imbalanced on the GMRT and BASC-3 Attention Problems subscale. This means that the READ + ENGAGE and READ groups may have constituted different groups of students, with the READ + ENGAGE condition constituting a group with more reading comprehension and behavioral attention challenges than the READ condition. Matching designs for multiple treatments are limited in scope ([<reflink idref="bib30" id="ref110">30</reflink>]); available algorithms may not yield optimal solutions or solutions of unknown adequacy. The design used to create three balanced groups in the present study relies on a paired structure that does not allow for direct comparison of all groups. However, in a recent paper, [<reflink idref="bib35" id="ref111">35</reflink>] proposed a conditional three-way matching algorithm that forms matched sets consisting of one subject from each of three treatment groups. Replications of this study should consider its use.</p> <hd id="AN0194392927-30">Implications</hd> <p>Our findings align with previous intervention work where improvements in behavioral attention or reading require a specific intervention in the respective domain. In other words, an intervention that targets both reading and attention is needed to identify improvements in both areas. Our findings do not support the reading-as-a-cause phenotype hypothesis where reading challenges lead to behavioral attention challenges. If this hypothesis were true, improvements in reading (as witnessed by the reading-only condition) would have been associated with behavioral attention improvements. We explored whether integrating behavioral attention supports into reading instruction would lead to not only greater impact on behavior but also improved reading relative to a reading-only condition. However, consistent with previous research (e.g., [<reflink idref="bib7" id="ref112">7</reflink>]; [<reflink idref="bib45" id="ref113">45</reflink>]; [<reflink idref="bib54" id="ref114">54</reflink>]), our findings suggest that the positive effects were limited to behavioral attention. Finally, our findings leave open the possibility of a bi-directional relationship, where, over time, initial reading challenges lead to later behavioral attention challenges or early inattentive behaviors may contribute to later reading challenges.</p> <p>Previous studies have implemented many of the research-based practices (e.g., token economy, self-regulation) that are used within Engaged Learners; however, to the best of our knowledge, this is the first manualized program designed to support behavioral attention and be implemented within small-group reading instruction. By developing Engaged Learners as a fully-developed program, we sought to help educators (a) identify practices associated with improved student behavioral attention and (b) prepare and delivering professional development for school-based personnel. Study findings showed that after minimal training and coaching, interventionists were able to implement Engaged Learners with high fidelity and witness an increase in student behavioral attention.</p> <hd id="AN0194392927-31">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-1-ecx-10.1177_00144029251396747 for The Efficacy of Integrating Engaged Learners Into Small Group Reading Instruction on Reading and Attention Outcomes: A Randomized Controlled Trial by Garrett J. Roberts, Greg Roberts, Philip Capin, Anna-Mari Fall, Brian B. Vedder, Anna Handy and Michelle Jestice in Exceptional Children</p> <ref id="AN0194392927-32"> <title> References </title> <blist> <bibl id="bib1" idref="ref55" type="bt">1</bibl> <bibtext> Bates D., Mächler M., Bolker B., Walker S. (2014). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.48550/arXiv.1406.5823</bibtext> </blist> <blist> <bibl id="bib2" idref="ref56" type="bt">2</bibl> <bibtext> Benjamini Y., Hochberg Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x</bibtext> </blist> <blist> <bibl id="bib3" idref="ref23" type="bt">3</bibl> <bibtext> Cassar A. G., Jang E. E. (2010). Investigating the effects of a game-based approach in teaching word recognition and spelling to students with Reading disabilities and attention deficits. Australian Journal of Learning Difficulties, 15(2), 193–211. https://doi.org/10.1080/19404151003796516</bibtext> </blist> <blist> <bibl id="bib4" idref="ref106" type="bt">4</bibl> <bibtext> Cho E., Dahl-Leonard K., Kehoe K., Capin P., Hall C., Solari E. (2023). Motivational practices in reading interventions for students with or at risk for dyslexia: Literature synthesis and meta-analysis. Topics in Language Disorders, 43(2), 119–145.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref99" type="bt">5</bibl> <bibtext> Cirino P. T., Fuchs L. S., Elias J. T., Powell S. R., Schumacher R. F. (2015). Cognitive and mathematical profiles for different forms of learning difficulties. Journal of Learning Disabilities, 48(2), 156–175. https://doi.org/10.1177/0022219413494239</bibtext> </blist> <blist> <bibl id="bib6" idref="ref107" type="bt">6</bibl> <bibtext> Deci E. L., Ryan R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref15" type="bt">7</bibl> <bibtext> Denton C. A., Tamm L., Schatschneider C., Epstein J. N. (2020). The effects of ADHD treatment and Reading intervention on the fluency and comprehension of children with ADHD and word Reading difficulties: A randomized clinical trial. Scientific Studies of Reading, 24(1), 72–89. https://doi.org/10.1080/10888438.2019.1640704</bibtext> </blist> <blist> <bibl id="bib8" idref="ref46" type="bt">8</bibl> <bibtext> Dignath C., Buettner G., Langfeldt H. P. (2008). How can primary school students learn self-regulated learning strategies most effectively?: A meta-analysis on self-regulation training programmes. Educational Research Review, 3(2), 101–129. https://doi.org/10.1016/j.edurev.2008.02.003</bibtext> </blist> <blist> <bibl id="bib9" idref="ref48" type="bt">9</bibl> <bibtext> Dignath C., Veenman M. V. (2021). The role of direct strategy instruction and indirect activation of self-regulated learning—evidence from classroom observation studies. Educational Psychology Review, 33(2), 489–533. https://doi.org/10.1007/s10648-020-09534-0</bibtext> </blist> <blist> <bibtext> DiPerna J.C., Elliott S. N. (2002). Promoting academic enablers to improve student achievement: An introduction to the mini-series. School Psychology Review, 31(3), 293–297. https://doi.org/10.1080/02796015.2002.12086156</bibtext> </blist> <blist> <bibtext> Dittman C. K. (2016). Associations between inattention, hyperactivity and pre-reading skills before and after formal reading instruction begins. Reading and Writing, 29(9), 1771–1791. https://doi.org/10.1007/s11145-016-9652-x</bibtext> </blist> <blist> <bibtext> Donegan R. E., Wanzek J. (2021). Effects of Reading interventions implemented for upper elementary struggling readers: A look at recent research. Reading and Writing: An Interdisciplinary Journal, 34(8), 1943–1977. https://doi.org/10.1007/s11145-021-10123-y</bibtext> </blist> <blist> <bibtext> DuPaul G. J., Gormley M. J., Daffner-Deming M. (2022). School-based interventions for elementary school students with attention-deficit/hyperactivity disorder. Child and Adolescent Psychiatric Clinics, 31(1), 149–166. https://doi.org/10.1016/j.chc.2021.08.003</bibtext> </blist> <blist> <bibtext> DuPaul G. J., Weyandt L. L., Janusis G. M. (2011). ADHD In the classroom: Effective intervention strategies. Theory Into Practice, 50(1), 35–42. https://doi.org/10.1080/00405841.2011.534935</bibtext> </blist> <blist> <bibtext> Ennis R. P., Royer D. J., Lane K. L., Dunlap K. D. (2020). Behavior-specific praise in pre-K–12 settings: Mapping the 50-year knowledge base. Behavioral Disorders, 45(3), 131–147. https://doi.org/10.1177/0198742919843075</bibtext> </blist> <blist> <bibtext> Evans S. W., Owens J. S., Bunford N. (2014). Evidence-based psychosocial treatments for children and adolescents with attention-deficit/hyperactivity disorder. Journal of Clinical Child & Adolescent Psychology, 43(4), 527–551. https://doi-org.du.idm.oclc.org/10.1080/15374416.2013.850700.</bibtext> </blist> <blist> <bibtext> Fabiano G. A., Lupas K., Merrill B. M., Schatz N. K., Piscitello J., Robertson E. L., Pelham Jr W. E. (2024). Reconceptualizing the approach to supporting students with attention-deficit/hyperactivity disorder in school settings. Journal of School Psychology, 104, Article 101309. https://doi.org/10.1016/j.jsp.2024.101309</bibtext> </blist> <blist> <bibtext> Fabiano G. A., Schatz N. K., Aloe A. M., Pelham Jr W. E., Smyth A. C., Zhao X., Coxe S. (2021). Comprehensive meta-analysis of attention-deficit/hyperactivity disorder psychosocial treatments investigated within between group studies. Review of Educational Research, 91(5), 718–760. https://doi-org.du.idm.oclc.org/10.3102/00346543211025092</bibtext> </blist> <blist> <bibtext> Fuchs D., Hendricks E., Walsh M. E., Fuchs L. S., Gilbert J. K., Zhang Tracy W., Patton III S., Davis-Perkins N., Kim W., Elleman A. M., Peng P. (2018). Evaluating a multidimensional Reading comprehension program and reconsidering the lowly reputation of tests of near-transfer. Learning Disabilities Research & Practice, 33(1), 11–23. https://doi.org/10.1111/ldrp.12162</bibtext> </blist> <blist> <bibtext> Giordani P., Ferraro M. B., Martella F. (2020). Issues in gaussian model-based clustering. In An introduction to clustering with R (pp. 291–340). Springer Singapore.</bibtext> </blist> <blist> <bibtext> Gwet. (2001). Handbook of inter-rater reliability: How to estimate the level of agreement between two or multiple raters. STATAXIS Publishing Company.</bibtext> </blist> <blist> <bibtext> Hattie J., Timperley H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487</bibtext> </blist> <blist> <bibtext> Hendricks E. L., Fuchs D. (2020). Are individual differences in response to intervention influenced by the methods and measures used to define response? Implications for identifying children with learning disabilities. Journal of Learning Disabilities, 53(6), 428–443. https://doi-org.du.idm.oclc.org/10.1177/0022219420920379</bibtext> </blist> <blist> <bibtext> Kern L., Wehby J. H. (2014). Using data to intensify behavioral interventions for individual students. TEACHING Exceptional Children, 46(4), 45–53. https://doi.org/10.1177/0040059914522970</bibtext> </blist> <blist> <bibtext> Kulesz P., Roberts G. J., Francis J. D., Cirino P., Walczak M., Vaughn S. (2024). Latent profiles as a predictor of response to instruction for students with Reading difficulties. Journal of Educational Psychology, 116(3), 363–376. https://doi.org/10.1037/edu0000832</bibtext> </blist> <blist> <bibtext> Lakes K. D., Swanson J. M., Riggs M. (2012). The reliability and validity of the English and spanish strengths and weaknesses of ADHD and normal behavior rating scales in a preschool sample: Continuum measures of hyperactivity and inattention. Journal of Attention Disorders, 16(6), 510–516. https://doi-org.du.idm.oclc.org/10.1177/1087054711413550</bibtext> </blist> <blist> <bibtext> Ledford J. R., Gast D. L. (2018). Single case research methodology: Applications in special education and behavioral sciences. Routledge. https://doi.org/10.4324/9781315150666</bibtext> </blist> <blist> <bibtext> Lenth R. V., Buerkner P., Herve M., Love J., Riebl H., Singmann H. (2020). emmeans: Estimated Marginal Means, aka Least-Squares Means (Version 1.5.3). https://CRAN.R-project.org/package=emmeans.</bibtext> </blist> <blist> <bibtext> Lonergan A., Doyle C., Cassidy C., MacSweeney Mahon S., Roche R. A., Boran L., Bramham J. (2019). A meta-analysis of executive functioning in dyslexia with consideration of the impact of comorbid ADHD. Journal of Cognitive Psychology, 31(7), 725–749. <ulink href="http://doi.org/10.1080/20445911.2019.1669609">http://doi.org/10.1080/20445911.2019.1669609</ulink></bibtext> </blist> <blist> <bibtext> Lopez M. J., Gutman R. (2017). Estimation of causal effects with multiple treatments: A review and new ideas. Statistical Science, 32(3), 432–454. https://<ulink href="http://www.jstor.org/stable/26408300">www.jstor.org/stable/26408300</ulink></bibtext> </blist> <blist> <bibtext> Macdonald K. T., Barnes M. A., Miciak J., Roberts G., Halverson K. K., Vaughn S., Cirino P. T. (2021). Sustained attention and behavioral ratings of attention in struggling readers. Scientific Studies of Reading, 25(5), 436–451. https://doi.org/10.1080/10888438.2020.1826950</bibtext> </blist> <blist> <bibtext> MacGinitie W. H., MacGinitie R. K., Maria K., Dreyer L. G., Hughes K. E. (2000). Gates-MacGinitie Reading Tests (4th ed.). Riverside.</bibtext> </blist> <blist> <bibtext> McGrath L. M., Pennington B. F., Shanahan M. A., Santerre-Lemmon L. E., Barnard H. D., Willcutt E. G., DeFries J. C., Olson R. K. (2011). A multiple deficit model of Reading disability and attention-deficit/hyperactivity disorder: Searching for shared cognitive deficits. Journal of Child Psychology and Psychiatry, 52(5), 547–557. https://doi.org/10.1111/j.1469-7610.2010.02346.x</bibtext> </blist> <blist> <bibtext> Morgan P. L., Farkas G., Tufis P. A., Sperling R. A. (2008). Are Reading and behavior problems risk factors for each other? Journal of Learning Disabilities, 41(5), 417–436. https://doi.org/10.1177/0022219408321123</bibtext> </blist> <blist> <bibtext> Nattino G., Lu B., Shi J., Lemeshow S., Xiang H. (2021). Triplet matching for estimating causal effects with three treatment arms: A comparative study of mortality by trauma center level. Journal of the American Statistical Association, 116(533), 44–53. https://doi.org/10.1080/01621459.2020.1737078</bibtext> </blist> <blist> <bibtext> Peng P., Zhang Z., Wang W., Lee K., Wang T., Wang C., Luo J., Lin J. (2022). A meta-analytic review of cognition and Reading difficulties: Individual differences, moderation, and language mediation mechanisms. Psychological Bulletin, 148(3-4), 227–272. https://doi.org/10.1037/bul0000361</bibtext> </blist> <blist> <bibtext> Pennington B. F. (2006). From single to multiple deficit models of developmental disorders. Cognition, 101(2), 385–413. https://doi.org/10.1016/j.cognition.2006.04.008</bibtext> </blist> <blist> <bibtext> Reynolds C. R., Kamphaus R. W. (2015). Behavior assessment system for children–Third Edition (BASC-3). Pearson.</bibtext> </blist> <blist> <bibtext> Roberts G. J., Cho E., Garwood J. D., Goble G. H., Robertson T., Hodges A. (2020). Reading interventions for students with Reading and behavioral difficulties: A meta-analysis and evaluation of co-occurring difficulties. Educational Psychology Review, 32(1), 17–47. https://doi.org/10.1007/s10648-019-09485-1</bibtext> </blist> <blist> <bibtext> Sayal K., Washbrook E., Propper C. (2015). Childhood behavior problems and academic outcomes in adolescence: Longitudinal population-based study. Journal of the American Academy of Child & Adolescent Psychiatry, 54(5), 360–368. https://doi.org/10.1016/j.jaac.2015.02.007</bibtext> </blist> <blist> <bibtext> Sexton C. C., Gelhorn H. L., Bell J. A., Classi P. M. (2012). The co-occurrence of Reading disorder and ADHD: Epidemiology, treatment, psychosocial impact, and economic burden. Journal of Learning Disabilities, 45(6), 538–564. https://doi-org.du.idm.oclc.org/10.1177/0022219411407772</bibtext> </blist> <blist> <bibtext> Sutherland K. S., Conroy M. A., McLeod B. D., Kunemund R., McKnight K. (2019). Common practice elements for improving social, emotional, and behavioral outcomes of young elementary school students. Journal of Emotional and Behavioral Disorders, 27(2), 76–85. https://doi.org/10.1177/106342661878400</bibtext> </blist> <blist> <bibtext> Swanson J. M., Schuck S., Porter M. M., Carlson C., Hartman C. A., Sergeant J. A. Clevenger W. Wasdell M. McCleary R. Lakes K. Wigal T., Wigal T. (2012). Categorical and dimensional definitions and evaluations of symptoms of ADHD: History of the SNAP and the SWAN rating scales. The International Journal of Educational and Psychological Assessment, 10(1), 51–70. https://<ulink href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618695/">www.ncbi.nlm.nih.gov/pmc/articles/PMC4618695/</ulink></bibtext> </blist> <blist> <bibtext> Sweller J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/ 0364-0213(88)90023-7</bibtext> </blist> <blist> <bibtext> Tamm L., Denton C. A., Epstein J. N., Schatschneider C., Taylor H., Arnold L. E., et al. (2017). Comparing treatments for children with ADHD and word Reading difficulties: A randomized clinical trial. Journal of Consulting and Clinical Psychology, 85(5), 434–446. https://doi.org/10.1037/ccp0000170</bibtext> </blist> <blist> <bibtext> Torgesen J. K., Wagner R. K., Rashotte C. A. (2012). Test of word Reading efficiency. Pro-Ed.</bibtext> </blist> <blist> <bibtext> Vaughn S., Roberts G. J., Miciak J., Taylor P. M., Fletcher J. M. (2019). Efficacy of a word- and text-based intervention for students with significant Reading difficulties. Journal of Learning Disabilities, 52(1), 31–44. https://doi.org/10.1177/0022219418775113</bibtext> </blist> <blist> <bibtext> Voyager Sopris Learning. (2022). Passport. Voyager Sopris Learning.</bibtext> </blist> <blist> <bibtext> Vygotsky L S. (1978). Mind and society: The development of higher mental processes. Harvard University Press.</bibtext> </blist> <blist> <bibtext> Wagner R. K., Torgesen J. K., Rashotte C. A., Pearson N. A. (2010). TOSREC: Test of sentence Reading efficiency and comprehension. Pro-Ed.</bibtext> </blist> <blist> <bibtext> What Works Clearinghouse. (2022). What Works Clearinghouse procedures and standards handbook, Version 5.0. U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance (NCEE). This report is available on the What Works Clearinghouse website at https://ies.ed.gov/ncee/wwc/Handbooks.</bibtext> </blist> <blist> <bibtext> Wigfield A., Eccles J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015</bibtext> </blist> <blist> <bibtext> Willcutt E. G., Pennington F. B. (2000). Psychiatric comorbidity in children and adolescents with Reading disability. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 41(8), 1039–1048. https://doi.org/10.1111/1469-7610.00691</bibtext> </blist> <blist> <bibtext> Willcutt E. G., Petrill S. A. (2023). Comorbidity between Reading disability and ADHD in a community sample: Implications for academic, social, and neuropsychological functioning. Mind, Brain and Education: The Official Journal of the International Mind, Brain, and Education Society, 17(4), 338. https://doi.org/10.1111/mbe.12393</bibtext> </blist> <blist> <bibtext> Willcutt E. G., Petrill S. A., Wu S., Boada R., DeFries J. C., Olson R. K., Pennington B. F. (2013). Comorbidity between Reading disability and math disability: Concurrent psychopathology, functional impairment, and neuropsychological functioning. Journal of Learning Disabilities, 46(6), 500–516. https://doi.org/10.1177/0022219413477476</bibtext> </blist> <blist> <bibtext> Zeng S., Benner G. J., Silva R. M. (2016). Effects of a summer learning program for students at risk for emotional and behavioral disorders. Education and Treatment of Children, 39(4), 593–615. https://doi.org/10.1353/etc.2016.0026</bibtext> </blist> </ref> <ref id="AN0194392927-33"> <title> Footnotes </title> <blist> <bibtext> The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R324B190010 to the University of Denver. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education.</bibtext> </blist> <blist> <bibtext> Garrett J. Roberts https://orcid.org/0000-0003-1128-5577</bibtext> </blist> <blist> <bibtext> Supplemental material for this article is available online.</bibtext> </blist> </ref> <aug> <p>By Garrett J. Roberts; Greg Roberts; Philip Capin; Anna-Mari Fall; Brian B. Vedder; Anna Handy and Michelle Jestice</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib41" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib53" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib11" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib23" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib31" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib29" firstref="ref8"></nolink> <nolink nlid="nl7" bibid="bib40" firstref="ref10"></nolink> <nolink nlid="nl8" bibid="bib44" firstref="ref11"></nolink> <nolink nlid="nl9" bibid="bib55" firstref="ref12"></nolink> <nolink nlid="nl10" bibid="bib33" firstref="ref13"></nolink> <nolink nlid="nl11" bibid="bib37" firstref="ref14"></nolink> <nolink nlid="nl12" bibid="bib45" firstref="ref16"></nolink> <nolink nlid="nl13" bibid="bib54" firstref="ref17"></nolink> <nolink nlid="nl14" bibid="bib39" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib56" firstref="ref24"></nolink> <nolink nlid="nl16" bibid="bib49" firstref="ref27"></nolink> <nolink nlid="nl17" bibid="bib10" firstref="ref29"></nolink> <nolink nlid="nl18" bibid="bib17" firstref="ref33"></nolink> <nolink nlid="nl19" bibid="bib34" firstref="ref34"></nolink> <nolink nlid="nl20" bibid="bib48" firstref="ref36"></nolink> <nolink nlid="nl21" bibid="bib16" firstref="ref37"></nolink> <nolink nlid="nl22" bibid="bib18" firstref="ref38"></nolink> <nolink nlid="nl23" bibid="bib13" firstref="ref41"></nolink> <nolink nlid="nl24" bibid="bib42" firstref="ref42"></nolink> <nolink nlid="nl25" bibid="bib14" firstref="ref43"></nolink> <nolink nlid="nl26" bibid="bib15" firstref="ref45"></nolink> <nolink nlid="nl27" bibid="bib12" firstref="ref63"></nolink> <nolink nlid="nl28" bibid="bib50" firstref="ref64"></nolink> <nolink nlid="nl29" bibid="bib43" firstref="ref65"></nolink> <nolink nlid="nl30" bibid="bib20" firstref="ref66"></nolink> <nolink nlid="nl31" bibid="bib46" firstref="ref73"></nolink> <nolink nlid="nl32" bibid="bib19" firstref="ref74"></nolink> <nolink nlid="nl33" bibid="bib32" firstref="ref76"></nolink> <nolink nlid="nl34" bibid="bib26" firstref="ref78"></nolink> <nolink nlid="nl35" bibid="bib38" firstref="ref79"></nolink> <nolink nlid="nl36" bibid="bib21" firstref="ref81"></nolink> <nolink nlid="nl37" bibid="bib47" firstref="ref82"></nolink> <nolink nlid="nl38" bibid="bib27" firstref="ref83"></nolink> <nolink nlid="nl39" bibid="bib24" firstref="ref84"></nolink> <nolink nlid="nl40" bibid="bib28" firstref="ref86"></nolink> <nolink nlid="nl41" bibid="bib51" firstref="ref87"></nolink> <nolink nlid="nl42" bibid="bib36" firstref="ref100"></nolink> <nolink nlid="nl43" bibid="bib25" firstref="ref101"></nolink> <nolink nlid="nl44" bibid="bib22" firstref="ref105"></nolink> <nolink nlid="nl45" bibid="bib52" firstref="ref108"></nolink> <nolink nlid="nl46" bibid="bib30" firstref="ref110"></nolink> <nolink nlid="nl47" bibid="bib35" firstref="ref111"></nolink>
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  Data: The Efficacy of Integrating Engaged Learners into Small Group Reading Instruction on Reading and Attention Outcomes: A Randomized Controlled Trial
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  Data: <searchLink fieldCode="AR" term="%22Garrett+J%2E+Roberts%22">Garrett J. Roberts</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1128-5577">0000-0003-1128-5577</externalLink>)<br /><searchLink fieldCode="AR" term="%22Greg+Roberts%22">Greg Roberts</searchLink><br /><searchLink fieldCode="AR" term="%22Philip+Capin%22">Philip Capin</searchLink><br /><searchLink fieldCode="AR" term="%22Anna-Mari+Fall%22">Anna-Mari Fall</searchLink><br /><searchLink fieldCode="AR" term="%22Brian+B%2E+Vedder%22">Brian B. Vedder</searchLink><br /><searchLink fieldCode="AR" term="%22Anna+Handy%22">Anna Handy</searchLink><br /><searchLink fieldCode="AR" term="%22Michelle+Jestice%22">Michelle Jestice</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Exceptional+Children%22"><i>Exceptional Children</i></searchLink>. 2026 92(4):483-501.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 19
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  Data: 2026
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  Data: Institute of Education Sciences (ED)
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  Data: R324B190010
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+3%22">Grade 3</searchLink><br /><searchLink fieldCode="EL" term="%22Primary+Education%22">Primary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+4%22">Grade 4</searchLink><br /><searchLink fieldCode="EL" term="%22Intermediate+Grades%22">Intermediate Grades</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+5%22">Grade 5</searchLink><br /><searchLink fieldCode="EL" term="%22Middle+Schools%22">Middle Schools</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Reading+Programs%22">Reading Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+School+Students%22">Elementary School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+3%22">Grade 3</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+4%22">Grade 4</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+5%22">Grade 5</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Difficulties%22">Reading Difficulties</searchLink><br /><searchLink fieldCode="DE" term="%22Attention+Deficit+Disorders%22">Attention Deficit Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Small+Group+Instruction%22">Small Group Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Tests%22">Reading Tests</searchLink><br /><searchLink fieldCode="DE" term="%22Rating+Scales%22">Rating Scales</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Test+of+Word+Reading+Efficiency%22">Test of Word Reading Efficiency</searchLink><br /><searchLink fieldCode="SU" term="%22Gates+MacGinitie+Reading+Tests%22">Gates MacGinitie Reading Tests</searchLink><br /><searchLink fieldCode="SU" term="%22Behavior+Assessment+System+for+Children%22">Behavior Assessment System for Children</searchLink>
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  Data: 10.1177/00144029251396747
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  Label: ISSN
  Group: ISSN
  Data: 0014-4029<br />2163-5560
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  Label: Abstract
  Group: Ab
  Data: We investigate the efficacy of a reading intervention integrated with Engaged Learners, a program that applies behavioral and cognitive principles to increase student behavioral attention and reduce distractions during instruction. Using a three-arm randomized controlled trial, we randomized 159 Grade 3-5 students with co-occurring reading and behavioral attention challenges to a researcher-implemented small group reading intervention with Engaged Learners (READ + ENGAGE), an identical researcher-implemented reading intervention without Engaged Learners (READ), or a Business-as-Usual (BaU) condition. The READ + ENGAGE condition students demonstrated statistically significant greater behavioral attention according to direct observations and interventionist reports than READ condition students. The pattern of reading effect sizes contrasting the conditions suggests that the READ + ENGAGE and READ conditions were associated with higher performance on reading outcomes than the BaU condition and students in the READ condition significantly outperformed the BaU condition on measures of word reading, fluency and reading comprehension, and mid-transfer vocabulary and reading comprehension. We also explored whether integrating the Engaged Learners program in a reading intervention would be associated with improved reading outcomes by contrasting the READ + ENGAGE to the READ condition; however, the findings did not support this hypothesis. Future research could examine the effects of systematically fading the Engaged Learner supports over time and implementing the intervention over a longer duration. These findings demonstrate that an integrated intervention can be implemented with minimal training and coaching, increasing behavioral attention to reading instruction during small-group instruction for upper elementary students with co-occurring reading and behavioral attention challenges.
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  Data: 2026
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        Value: 10.1177/00144029251396747
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 483
    Subjects:
      – SubjectFull: Reading Programs
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Elementary School Students
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      – SubjectFull: Grade 3
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      – SubjectFull: Grade 4
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      – SubjectFull: Student Behavior
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      – SubjectFull: Reading Difficulties
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      – SubjectFull: Attention Deficit Disorders
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      – SubjectFull: Small Group Instruction
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      – SubjectFull: Behavior Assessment System for Children
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