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Academic and Behavioral Strategies in Inclusive Settings for Students with EBD: A Meta Analysis

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Title: Academic and Behavioral Strategies in Inclusive Settings for Students with EBD: A Meta Analysis
Language: English
Authors: Denise A. Soares, Judith R. Harrison, Corey Peltier (ORCID 0000-0003-3138-4126), Kathryn Press
Source: Behavioral Disorders. 2025 51(1):39-57.
Availability: SAGE Publications and Hammill Institute on Disabilities. 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: 2025
Document Type: Journal Articles
Information Analyses
Education Level: Elementary Secondary Education
Descriptors: Students with Disabilities, Emotional Disturbances, Behavior Disorders, Inclusion, Intervention, Elementary Secondary Education, Program Effectiveness, Classroom Techniques, Success, Educational Research, Positive Reinforcement, Self Determination, Self Management, Acoustics, Culturally Relevant Education, Reinforcement
DOI: 10.1177/01987429241261382
ISSN: 0198-7429
2163-5307
Abstract: More students with emotional and behavioral disorders (EBD) than ever before spend most of their time in general education. To increase their academic and behavioral success, students with EBD need access to empirically supported interventions and services. The purpose of this systematic review and meta-analysis was to evaluate strategy effectiveness for students with EBD in K-12 inclusive settings. Identified studies were assessed with two approaches for evaluating methodological quality and multiple methods for assessing intervention effects. Results indicated that there is a dearth of empirical support for strategies implemented in general education classrooms for students with EBD though most of the studied reviewed were of high quality with moderate-to-large effects. In addition to the practical findings, the research team compared review methods with findings indicating agreement between expert visual analysis and more structured approaches for visual analysis. For the quantitative metrics, results indicated variable agreement across methods. Implications for research and practice are discussed.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1487693
Database: ERIC
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  Value: <anid>AN0188856546;bhd01nov.25;2025Oct27.06:23;v2.2.500</anid> <title id="AN0188856546-1">Academic and Behavioral Strategies in Inclusive Settings for Students With EBD: A Meta Analysis </title> <p>More students with emotional and behavioral disorders (EBD) than ever before spend most of their time in general education. To increase their academic and behavioral success, students with EBD need access to empirically supported interventions and services. The purpose of this systematic review and meta-analysis was to evaluate strategy effectiveness for students with EBD in K–12 inclusive settings. Identified studies were assessed with two approaches for evaluating methodological quality and multiple methods for assessing intervention effects. Results indicated that there is a dearth of empirical support for strategies implemented in general education classrooms for students with EBD though most of the studied reviewed were of high quality with moderate-to-large effects. In addition to the practical findings, the research team compared review methods with findings indicating agreement between expert visual analysis and more structured approaches for visual analysis. For the quantitative metrics, results indicated variable agreement across methods. Implications for research and practice are discussed.</p> <p>Keywords: systematic review; emotional behavior disorder; EBD; classroom-based strategies; strategy effectiveness; effect size indices; research quality; single-case design</p> <p>The inclusion of students with disabilities in general education classrooms remains a polarizing issue with those supporting full inclusion and those in favor of using a continuum of placements claiming it as a moral imperative and essential for student success ([<reflink idref="bib6" id="ref1">6</reflink>]; [<reflink idref="bib13" id="ref2">13</reflink>]; [<reflink idref="bib37" id="ref3">37</reflink>]). Although research on the benefits of inclusion for students with disabilities is mixed ([<reflink idref="bib49" id="ref4">49</reflink>]), there is little doubt that students with disabilities spend more time in the least restrictive environment than at any other previous point. For instance, the National Center for Education Statistics (NCES, [<reflink idref="bib79" id="ref5">79</reflink>]) reported that approximately two-thirds of students with disabilities nationally spend at least 80% of their day in general education. Since the passage of the Individuals with Disabilities Education Improvement Act (IDEA) in 1997 and strengthened through its reauthorization in 2004, there have been consistent increases in the number of students with disabilities placed in general education classrooms.</p> <p>Given the prevalence of restrictive placements for students with emotional and behavioral disorders (EBD), it might come as a surprise that the trend toward more inclusion also holds for this population. Specifically, NCES reported that between 2012 and 2020 there was a nearly 10% increase in the proportion of students with EBD spending 80% or more of their day in the least restrictive environment. The increased inclusion of students with EBD in general education has made the need to provide practitioners with ecologically valid and empirically supported practices more urgent. Placing students with EBD in general education classrooms is a complex endeavor due to their high rates of maladaptive behavior, persistent academic needs, and difficulty building interpersonal relationships ([<reflink idref="bib52" id="ref6">52</reflink>]). Collectively, these challenges pose a threat to the school experiences of students with EBD who are more likely to fail classes, be retained in a grade, and drop out of school than students with other disabilities. As such teaching students with EBD often results in high levels of teacher stress ([<reflink idref="bib27" id="ref7">27</reflink>]), burnout ([<reflink idref="bib9" id="ref8">9</reflink>]), and attrition ([<reflink idref="bib56" id="ref9">56</reflink>]). Many general education teachers find including students with EBD challenging due, in part, to having less experience and knowledge of effective practices to address behavioral challenges ([<reflink idref="bib31" id="ref10">31</reflink>]). With the increase in the number of students with EBD receiving more of their education in general education classrooms, it is imperative that the field provide an overview of the academic and behavioral strategies with documented effectiveness in inclusive environments ([<reflink idref="bib50" id="ref11">50</reflink>]).</p> <hd id="AN0188856546-2">Prior Meta-Analyses and Systematic Reviews</hd> <p>Despite the increased inclusion of students with EBD, there remains a dearth of information available on effective practices to use with this population in general education classrooms. Among the reasons is that no prior systematic review or meta-analysis has examined the research on academic and behavioral strategies for students with EBD in general education settings specifically. Fortunately, there is research to draw on with systematic reviews and meta-analyses having explored (a) academic outcomes for students with EBD in general education settings with students with EBD; (b) academic, social, and behavioral outcomes for students with EBD in special education settings; and (c) academic, social, and behavioral outcomes for students with other disabilities in general education settings. Below, we review this literature with a goal to outline the scope of this study.</p> <hd id="AN0188856546-3">Academic Outcomes: Students With EBD in General Education Settings</hd> <p>[<reflink idref="bib51" id="ref12">51</reflink>] conducted a meta-analysis and systematic review that examined experimental research on academic interventions for students with EBD in general education classrooms. The authors found studies examining Time Warp Plus ([<reflink idref="bib65" id="ref13">65</reflink>]), Scotts Foresman Reading (SFR; [<reflink idref="bib84" id="ref14">84</reflink>]), self-monitoring ([<reflink idref="bib61" id="ref15">61</reflink>]), and class-wide peer tutoring ([<reflink idref="bib4" id="ref16">4</reflink>]). Based on this review, it was found that the intervention deployed by [<reflink idref="bib65" id="ref17">65</reflink>] led to improvements in reading fluency and on-task behavior. [<reflink idref="bib84" id="ref18">84</reflink>] found positive effects on letter naming with SFR; however, the intervention was conducted in a special education setting prior to measuring outcomes in a general education. [<reflink idref="bib61" id="ref19">61</reflink>] found an increase in the number of problems completed and math test scores for one student with EBD in an inclusive setting following the implementation of self-monitoring and [<reflink idref="bib4" id="ref20">4</reflink>] found improved history test scores for six students with EBD in an inclusive setting with class wide peer tutoring. Due to the small number of studies across meta-analyses and systematic reviews, McKenna et al. concluded that there was insufficient information supporting any intervention for increasing academic outcomes for students with EBD in inclusive settings.</p> <hd id="AN0188856546-4">Academic, Behavioral, and Social Outcomes: Students With EBD in Various Settings</hd> <p>Although [<reflink idref="bib51" id="ref21">51</reflink>] reviewed the existing research on academic outcomes, no prior reviews or meta-analyses have synthesized the effects of strategies on behavioral or social outcomes of students with EBD solely measured in general education settings. However, 14 literature reviews and meta-analyses have identified strategies with evidence of effectiveness with this population in special education settings. Across reviews and meta-analyses, results indicated that academic interventions (e.g., cover, copy, and compare; interest; choice; increasing opportunities to respond; mnemonics; pacing; previewing; peer tutoring; Self-Regulated Strategy Development [SRSD]; story mapping, task sequencing), behavioral interventions (e.g., Good Behavior Game; token economy), cognitive behavioral strategies (e.g., problem-solving training; self-management instruction), instructional strategies (e.g., small group instruction; one-on-one instruction), and studies of interventions selected through functional behavioral assessment (FBA) provided preliminary evidence of effectiveness with students with EBD in specialized settings. As such, [<reflink idref="bib51" id="ref22">51</reflink>] surmised that the practice might be beneficial when implemented in general education settings.</p> <hd id="AN0188856546-5">Academic, Social, and Behavioral Outcomes: Students With Disabilities in General Education Se...</hd> <p>In addition, there is a corpus of reviews examining strategies for students with disabilities other than EBD conducted in general education settings that have the potential to inform the development of strategies to support students with EBD succeed in the least restrictive environment. For example, several studies ([<reflink idref="bib1" id="ref23">1</reflink>]; [<reflink idref="bib69" id="ref24">69</reflink>]; [<reflink idref="bib86" id="ref25">86</reflink>]) evaluated the effects of the Self Determined Learning Model of Instruction (SDLMI; [<reflink idref="bib53" id="ref26">53</reflink>]) on the academic and behavioral progress of students with various disabilities including learning disabilities, autism spectrum disorder, and intellectual disabilities in general education settings. SDLMI is a model for teaching students to set goals, self-monitor progress, engage in a self-regulated problem solving, and utilize explicitly taught learning strategies ([<reflink idref="bib1" id="ref27">1</reflink>]). Results indicated that when exposed to the SDLMI, students were able to achieve their personalized goal and maintain mastery over time. Although students with EBD have unique characteristics in comparison to students with whom SDLMI was evaluated, the possibility exists that SDLMI might be used to teach students the skills needed to successfully navigate the academic expectations of the general education curriculum and setting.</p> <p>In summary, although no prior review has synthesized the literature on effective strategies for students with EBD in general education settings specifically, there appears ample research to examine based on previous systematic reviews and meta-analyses. As such, in addition to other search terms, we included each of these interventions as key search terms to ensure a comprehensive search process for this review.</p> <hd id="AN0188856546-6">Methodological Considerations for Reviewing Research on Students With EBD</hd> <p>SCD is a commonly used set of experimental research methods in special education that allows researchers to examine whether a practice is functionally related to a well-operationalized dependent variable ([<reflink idref="bib34" id="ref28">34</reflink>]). The premise of SCD is to examine within-participant responding both in the presence and absence of the intervention and to visually compare the responses using graphed data. Because of the low prevalence of students with EBD, SCDs provide researchers with a framework to test the effectiveness of a practices or strategy ([<reflink idref="bib25" id="ref29">25</reflink>]). However, the unique characteristics of SCDs require distinct procedures and methods to systematically review and meta-analyze the research. Given that these methods require continued development and refinement, we used this review to compare recommended review practices by (a) evaluating and comparing the methodological quality of the included literature as deemed by two sets of standards; (b) conducting and comparing findings from two unique approaches to visual analysis (VA); and (c) quantifying and comparing the magnitude of effect using five quantitative indices.</p> <hd id="AN0188856546-7">Methodological Quality Review</hd> <p>The development of standards to evaluate the internal validity of SCD research represents a major advance because it allows for a fulsome assessment of the presence of a functional relation ([<reflink idref="bib15" id="ref30">15</reflink>]). That is, the use of a research design that provides the opportunity to infer a causal relation between an intervention and dependent variable is insufficient, the researcher must also account for a variety of threats to internal validity within the research methods ([<reflink idref="bib34" id="ref31">34</reflink>]). For nearly 20 years, the field has developed and refined methods to assess the methodological quality of SCD research and establish benchmarks for determining a practice as evidence-based.</p> <p>While many strategies for evaluating evidential quality are available, the two sets of criteria for evaluating the methodological quality of SCDs within special education include the [<reflink idref="bib17" id="ref32">17</reflink>] evidence standards ([<reflink idref="bib15" id="ref33">15</reflink>]) and the [<reflink idref="bib87" id="ref34">87</reflink>] version 4.1. CEC includes eight categories that include 22 individual indicators designed to measure the methodological rigor and quality of SCDs. The CEC standards contain indicators related to external validity, such as reporting information about participants, setting, and intervention agent in addition to indicators related to internal validity of the design. In contrast, the WWC standards (4.1) focus on four stages of review, one being quality of evidence with within three categories coded dichotomously including systematic manipulation of the independent variable, measuring, and reporting inter-assessor agreement (IAA) across 20% of sessions in each phase with 80% simple agreement and a kappa of.60, and demonstrating a functional relation with three (meets standards with reservations) to five data points (meets standards) per phase. Due to the use of different criteria and methods, it's possible that these frameworks might produce different evidence classifications ([<reflink idref="bib12" id="ref35">12</reflink>]).</p> <p>To explore this hypothesis, prior reviews (e.g., [<reflink idref="bib31" id="ref36">31</reflink>]; [<reflink idref="bib58" id="ref37">58</reflink>]) have compared the two and described discordance between evidence classifications assigned to interventions using version 4.0 of the WWC standards. For example, [<reflink idref="bib31" id="ref38">31</reflink>] found that instructional and self-management interventions were considered evidence-based per WWC criteria, but potentially evidence-based via CEC indicators as classroom interventions for students with attention-deficit/hyperactivity disorder (ADHD). Similarly, [<reflink idref="bib58" id="ref39">58</reflink>] explored the evidence-based for functional communication training with Augmentative and Alternative Communication (AAC) for students with developmental disabilities and found that while four studies met all CEC indicators, 17 met the WWC standard with or without reservations. Ousley et al. reported that only three studies met the quality indicators for both methods, suggesting the need for further exploration of the concurrent validity of these methods and careful interpretation about their results. To our knowledge, no studies have compared outcomes with the application of the CEC and WWC (version 4.1) standards.</p> <hd id="AN0188856546-8">Visual Analysis</hd> <p>Historically, SCD data have been analyzed by visually inspecting graphed data. Two approaches to VA, expert analysis, and conservative dual criterion (CDC), have been frequently recommended in the literature ([<reflink idref="bib21" id="ref40">21</reflink>]). Expert analysis (see WWC version 4.1) involves professionals trained in VA inspecting the graphed data comparing the level, trend, and variability of data within and between phases. In addition, experts consider the immediacy of the effect and frequency of data that overlaps between phases. Details for conducting expert VA are outlined in version 4.1 of the What Works Clearinghouse Standards Handbook.</p> <p>The second approach, the CDC, was developed by [<reflink idref="bib23" id="ref41">23</reflink>]. Development of CDC, as an objective structured approach, was in response to questions being raised about the reliability of expert VA ([<reflink idref="bib23" id="ref42">23</reflink>]; [<reflink idref="bib88" id="ref43">88</reflink>]). CDC involves calculating the mean in each phase and the trend of the data beginning in baseline. The baseline mean and trend are compared to intervention phases to determine if the mean increased by 0.25 standard deviations (SD) or more in the direction of the desired behavior change. Recent investigations have found the outcomes of the CDC approach largely agree with expert VA ([<reflink idref="bib88" id="ref44">88</reflink>], 84% agreement).</p> <p>Both methods are plausible means of determining the existence, or not of a functional relation within meta-analysis. As such, the current meta-analysis provided the opportunity for comparison of these two methods. Prior studies (e.g., [<reflink idref="bib88" id="ref45">88</reflink>]) found strong agreement (83%) between expert VA and the CDC.</p> <hd id="AN0188856546-9">Quantitative Indices for Single-Case Experimental Designs</hd> <p>Researchers have developed effect size indices to address some of the statistical nuances of SCD research to summarize the magnitude of effect and supplement VA ([<reflink idref="bib8" id="ref46">8</reflink>]). Three categories of available indices are nonoverlap, within-case, and between-case ([<reflink idref="bib62" id="ref47">62</reflink>]). Nonoverlap indices are designed to explain the percent of data improved from baseline to intervention, thus quantifying the amount of nonoverlap between phases. Within-case indices provide an estimate of the magnitude of change between baseline and intervention within an individual case (e.g., AB phase within multiple-baseline design). Between-case indices provide an estimate of the intervention effects for the entire experiment by aggregating within-case estimates to produce an omnibus effect. Although an in-depth discussion of each is beyond the scope of this manuscript (see [<reflink idref="bib46" id="ref48">46</reflink>]; [<reflink idref="bib90" id="ref49">90</reflink>]), we must note that to date the field has yet to agree upon which best represents SCD findings ([<reflink idref="bib90" id="ref50">90</reflink>]). Therefore, for this study, we elected to calculate five commonly used effect size statistics ([<reflink idref="bib3" id="ref51">3</reflink>]), three nonoverlap indices, one within-case, and one between-case.</p> <p>Among our goals in calculating five effect sizes was to examine the concurrent validity of these metrics and determine the agreement across approaches and indices. Few prior studies have compared the association across different SCD effect sizes and VA. Examining the correlations of these measures will provide much needed information about their degree of association. Few prior studies have examined these correlations with those attempts indicating discrepant findings. Specifically, [<reflink idref="bib3" id="ref52">3</reflink>] found a strong correlation between LRR and Tau-U<subs>A v. B, Trend A</subs> (<emph>r</emph> =.801); however, the researchers found no correlation between LRR and Nonoverlap of All Pairs (NAP) (<emph>r</emph> =.036). Another study, [<reflink idref="bib12" id="ref53">12</reflink>] found strong intercorrelations in intervention studies between Tau<subs>nonoverlap</subs> and NAP (.9). More replication is needed for application in the field. With respect to SCD effect sizes and VA, our goal in this study was twofold. First, we proposed that the degree of agreement will speak to the strength of the findings. Second, as much more research is needed in this area, we aimed to provide information to the field to contribute to the discussion of effect size selection for SCD studies.</p> <hd id="AN0188856546-10">Purpose of this Study</hd> <p>In summary, several strategies have preliminary evidence of effectiveness for students with EBD in special education settings and with students with differing needs in general education settings. However, no prior review has systematically examined the literature on practices and strategies for students with EBD in general education settings. In addition, a secondary aim was to compare five effect size indices and two approaches to VA and to determine the agreement between quantitative labels of effects across indices and approaches. Finally, we aimed to compared ratings of study quality as designated by CEC and WWC indicators. As such, the following research questions guided this study:</p> <p></p> <ulist> <item> <bold> Research Question 1 (RQ1): </bold> What are the characteristics of the single-case research examining strategies implemented in general education classrooms for students with EBD?</item> <p></p> <item> <bold> Research Question 2 (RQ2): </bold> What is the methodological quality of the research for each strategy? What is the agreement between CEC and WWC ratings of scientific quality?</item> <p></p> <item> <bold> Research Question 3 (RQ3): </bold> What is the effectiveness of each strategy using both VA and five single-case effect size measures?</item> <p></p> <item> <bold> Research Question 4 (RQ4): </bold> What is the agreement and correlation between the effect sizes for VA and each of the five metrics?</item> </ulist> <hd id="AN0188856546-11">Method</hd> <p>We used a multiphase process to complete a systematic review and meta-analysis examining strategies used in general education settings with students with EBD. Methods are adapted from [<reflink idref="bib31" id="ref54">31</reflink>]. Procedures included three phases: (a) systematic literature review; (b) article coding; and (c) data analysis. Procedures for each phase are described in detail.</p> <hd id="AN0188856546-12">Phase 1: Systematic Literature Review</hd> <p>A systematic search was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) standards ([<reflink idref="bib43" id="ref55">43</reflink>]) to identify all relevant research studies. This study included six inclusion criteria. First, the research study was published between the years 1997 and 2020 in the United States. We elected to begin with the year 1997, due to the increased focus on inclusion in the reauthorization of the special education federal mandate, the Individuals with Disabilities Education Act (IDEA). Second, the study must be published because the peer review process serves to ensure research quality and maintain validity, scientific merit, and rigorous standards ([<reflink idref="bib83" id="ref56">83</reflink>]).</p> <p>Third, the study must have provided an evaluation of academic and behavioral effects of changes made through a "systematic process to develop or improve knowledge, skills, behaviors, cognitions, or emotions" ([<reflink idref="bib29" id="ref57">29</reflink>], p. 556). Fourth, the research study included K–12 students who were identified with EBD as defined by IDEA eligibility and reported by the source authors. Studies with students identified as "at-risk" for EBD were excluded as our goal was to explore research of interventions with students eligible for special education under the criteria of Emotional Disturbance implemented in inclusive settings. Fifth, the study used a Single Case Experiment Design. Sixth, the research study was conducted in K–12 general education settings in the United States. The intervention needed to be implemented in the general education environment, not just data collection. For example, we excluded studies that implemented the intervention in a separate environment, such as a special education resource setting, but then data were collected in the inclusive environment (e.g., [<reflink idref="bib84" id="ref58">84</reflink>]). We elected to exclude such articles as our goal was to evaluate strategies implemented in inclusive settings only. Seventh, the study provided quantitative data on student outcomes (i.e., academic, behavior, and social).</p> <p>The following multi-step process was used to identify peer reviewed published studies. First, we conducted an electronic search and an ancestral review of articles in literature reviews and meta-analyses through the following procedures. We performed a systematic electronic search of common education databases (Academic Search Premier, EBSCOhost, JSTOR Journals, Project MUSE, PsycINFO, and Education Resource Information Center [ERIC]). The limiters of date (1997 to 2020) and published documents were used as part of the search. The following key terms and Boolean strings were used ("<emph>EBD*" OR "ED*" OR "emotionally disturbed*" OR "emotional and behavioral disorder*s" OR "emotional disturbance*" OR "behavioral disorders*" OR "BD") AND ("classroom" OR "K-12*") AND ("interventions" OR "strategies*."</emph></p> <p>In addition, we specified that articles must be published between 1997 and 2021 in peer-reviewed, scholarly, academic journals and published in English. Next, we conducted an ancestral review of journal articles referenced in literature reviews and previous meta-analysis. Specifically, we reviewed 15 meta-analyses and literature reviews related to students with or at risk of EBD (i.e., [<reflink idref="bib5" id="ref59">5</reflink>]; [<reflink idref="bib7" id="ref60">7</reflink>]; [<reflink idref="bib11" id="ref61">11</reflink>]; [<reflink idref="bib24" id="ref62">24</reflink>]; [<reflink idref="bib30" id="ref63">30</reflink>]; [<reflink idref="bib31" id="ref64">31</reflink>]; [<reflink idref="bib33" id="ref65">33</reflink>]; [<reflink idref="bib42" id="ref66">42</reflink>]; [<reflink idref="bib44" id="ref67">44</reflink>]; [<reflink idref="bib51" id="ref68">51</reflink>]; [<reflink idref="bib55" id="ref69">55</reflink>]; [<reflink idref="bib60" id="ref70">60</reflink>]; [<reflink idref="bib68" id="ref71">68</reflink>]; [<reflink idref="bib82" id="ref72">82</reflink>], [<reflink idref="bib80" id="ref73">80</reflink>]). These reviews indicated that academic interventions (e.g., cover, copy, and compare; interest; choice; increasing opportunities to respond; mnemonics; pacing; previewing; peer tutoring; self-regulated strategy development [SRSD]; story mapping, task sequencing), behavioral interventions (e.g., Good Behavior Game; token economy), cognitive behavioral strategies (e.g., problem-solving training; self-management instruction), instructional strategies (e.g., small group instruction; one-on-one instruction) and studies of interventions selected through functional behavioral assessment (FBA) have been empirically evaluated and have preliminary evidence of effectiveness with students with EBD in specialized settings, as such might be beneficial when implemented in general education settings.</p> <p>A search of the references initially identified journal articles that were double checked against the initial pool of articles. Titles were reviewed for possible inclusion. These searches yielded 54 additional articles for screening. After screening titles and abstracts followed by full texts, we identified six articles that met inclusion criteria and were included in this review. See Figure 1 for a visual of this process.</p> <p>Graph: Figure 1. PRISMA Flow Diagram.</p> <hd id="AN0188856546-13">Phase 2: Coding</hd> <p>We developed a coding guide following the procedures of [<reflink idref="bib71" id="ref74">71</reflink>] that included codes for article characteristics and methodological quality standards. Each article was coded two times. Codes were developed specific to article characteristics, such as authors, name of strategy, definition of strategy, age of participants. Per article, using an excel spread sheet, members of the research team listed all author names, the name of the strategy given by the source authors, the definition provided by the source authors, and the age and grade of participants. Next, team members coded each indicator included in the CEC Standards and WWC Standards dichotomously (yes/no).</p> <p>Two research assistants coded all included studies for articles characteristics and across two sets of research standards, the CEC Standards for Evidence Based Practices in Special Education ([<reflink idref="bib15" id="ref75">15</reflink>]) and the WWC Design Standards (version 4.1). The second author trained the research team to code the source articles. First, the author reviewed the codes and provided examples/non-examples for each indicator. Second, the author and two research assistants coded one article together and discussed areas of disagreement or lack of understanding. If codes were not clearly written, the three deliberated until clarity was achieved with 100% agreement. Third, the three independently coded one article and discussed disagreements. This process continued until simple agreement was above 80% ([<reflink idref="bib32" id="ref76">32</reflink>]). Fourth, two raters independently coded the remaining four studies using the CEC standards and WWC standards. Interrater reliability was calculated as 91.4% across all variables and both sets of standards. When disagreements occurred, the first or second author met to determine discrepancies and resolve issues.</p> <hd id="AN0188856546-14">Phase 3: Data Analysis</hd> <p></p> <hd id="AN0188856546-15">Methodological Quality</hd> <p>The authors assigned CEC and WWC design ratings to each outcome from each study. For CEC evaluation, we determined a study to either be methodologically sound if they met all eight indicators. For WWC evaluation, we determined if a study met the standards, met the standards with reservations, or did not meet the standards. Studies met WWC criteria overall and based on standards per design. For all designs: (a) the independent variable must be systematically manipulated; (b) inter-assessor agreement (IAA) must be collected in at least 20% of the sessions in each condition and at least once in each condition per participation; (c) IAA must be reported at or above 80% agreement or Kappa must be.60 or above; and (d) study must include three opportunities to demonstrate effects at three different points in time.</p> <p>Specific to each design, reversal designs were coded as: (a) met standards without reservations (MS) if the study included at least four phases per case with at least five points in each phase; (b) met standards with reservations (MSR) if the study included four phases per case with three or four data points per phase; and (c) as did not meet standards if they did not meet these criteria. Multiple-baseline and multiple-probe were coded as: (a) met standards if they had at least six phases with five data points per phase, (b) met standards with reservations if they included six phases with three or four data points per phase, and (c) did not meet standards if they did not meet these criteria.</p> <p>Alternating treatments designs were coded as (a) met standards without reservations with five data points per condition with 2 points per phase; (b) to meet standards with reservations, studies must have four data points per condition with two points per phase; and (c) does not meet standards if the criteria are not established. To determine agreement between CEC and WWC criteria, we compared the overall outcomes of each. When different outcomes were found, we compared each code.</p> <hd id="AN0188856546-16">Visual Analysis</hd> <p>To determine the quality of the evidence of effectiveness for each study, the first and second author simultaneously visually analyzed the graphed data for each outcome and participate within the included studies following the stage three procedures of WWC (2020; version 4.1) and the CDC method. Specifically, we analyzed within phase data by visually inspecting the baseline data for demonstration of a problem behavior and pattern. Second, we compared the (a) level, (b) trend, and (c) variability of the adjacent phases. Third, we compared the (a) immediacy of the effect and (b) the overlap between phases. Fourth, we compared the consistency of the data patterns analyzing the level, trend, and variability within similar phases in the same condition. In addition, specific to multiple baseline and multiple probe designs, we vertically compared baseline phases with determine if they were independent of one another. Specifically, we determined if patterns in baseline data remained stable for cases not receiving the intervention, when the intervention was introduced in another series (e.g., student, setting). Based on these ratings, we characterized the evidence as strong, moderate, or none.</p> <p>We also used the CDC ([<reflink idref="bib23" id="ref77">23</reflink>]) for four studies that used a multiple baseline or multiple probe design. We were unable to use the CDC for one study that used a multiple-probe design because of insufficient baseline data (i.e., only two data points) and for one multielement design as CDC is not applicable to this design type. We followed the procedures for CDC outlined in a primer written by [<reflink idref="bib77" id="ref78">77</reflink>], using an Excel document, also created by the authors. We constructed mean and trend lines 0.25 standard deviations further in the direction of the desired behavior change on each study graph. Second, we compared the intervention data to the constructed mean and trend lines to determine if the intervention as effective. Treatment effect was verified if a specific number of data points, as established by Fisher et al., were above or below both lines depending on the direction of the predicted behavior change. To use the CDC method in this investigation, we used a programmed Excel document and followed the procedures in a primer provided by [<reflink idref="bib77" id="ref79">77</reflink>].</p> <hd id="AN0188856546-17">Quantitative Indices</hd> <p>To compute quantitative indices, we extracted the raw data plotted on time-series graphs from each participant that met the inclusion criteria in each article for each outcome. None of the studies provided this data as a supplemental file or linked to a repository, so we used Getdata Graph Digitizer ([<reflink idref="bib78" id="ref80">78</reflink>]). Procedurally, two doctoral level members of the research team scanned the published graphs and used the computer program to assign the values on the x- and y-axis and then captured each data point across all phases. This resulted in the exact reconstruction of the original graph with numeric raw data assigned to each data point needed to calculate the quantitative indices. Data were only digitized when collected in a general education setting. In one case ([<reflink idref="bib66" id="ref81">66</reflink>]), the intervention was conducted in a special education setting, but data were collected in both special and general education classrooms. We only included data collected in the general education classroom.</p> <p>After digitizing data points, we computed five quantitative indices: (a) NAP, (b) Tau<subs>nonoverlap</subs>, (c) Tau-U<subs>A v. B, Trend A</subs>, (d) LRR, and (e) BC-SMD. We elected to calculate the selected effect sizes because, as described in the background, there is no consensus for the "best" metric to use for single-case designs. The nonoverlap indices provided information about overlap between conditions (i.e., an important aspect of VA), but fail to capture magnitude of change, or level change, between conditions. The within-case effect size (LRR) is able to capture magnitude of change between conditions, but data patterns may not always fit necessary assumptions.</p> <p>To compute each quantitative index, we imported the digitized values to a pre-specified.csv template, which was then entered into a shinyapp developed by [<reflink idref="bib64" id="ref82">64</reflink>]. Each quantitative index was computed at the case level. Each estimate reflects AB phase comparisons consisting of baseline and intervention data unless otherwise specified. Finally, for purposes of this paper we qualified the effects as small, moderate, and large for ease of comparison between each. However, we must note that many have cautioned against the use of benchmarks as the true interpretation of the magnitude of effect is based on the wider context in which the study is set and the consistency of findings across studies ([<reflink idref="bib14" id="ref83">14</reflink>]; [<reflink idref="bib39" id="ref84">39</reflink>]; [<reflink idref="bib81" id="ref85">81</reflink>]).</p> <p>In this study, we used the following benchmarks. For Tau<subs>nonoverlap</subs>, effects between 0 and 0.29 were considered small, 0.30 and 0.84 were moderate, and 0.85 and 1.00 were large. For Tau-U<subs>A v. B, Trend A</subs> and NAP, effects between 0 and 0.65 were considered small, 0.66 and 0.92 were moderate, and 0.93 and 1.00 were large. Although no benchmarks have been established for LRR or BC-SMD to date, for our purposes we refer to [<reflink idref="bib14" id="ref86">14</reflink>] benchmarks, as the two are comparable ([<reflink idref="bib63" id="ref87">63</reflink>]). BC-SMD between 0.20 and 0.49 was considered small, 0.50 to 0.79 considered medium, and 0.80 and above considered large. Although, commonly used, we must note that using Cohen's <emph>d</emph> benchmarks for BC-SMD is considered inappropriate due to inflated effect size estimates for BC-SMD ([<reflink idref="bib72" id="ref88">72</reflink>]).</p> <p>To determine agreement between expert VA, CDC, Tau, Tau-U<subs>A v. B, Trend A</subs>, NAP, LRR, and BC-SMD, we divided the number of agreements by the sum of agreements and disagreements and multiplied by 100 for each possible combination. To determine the correlation between expert VA, CDC, Tau, Tau-U<subs>A v. B, Trend A</subs>, and LRR, we conducted a correlation analysis in IBM SPSS Statistic (version 28) at the study outcome level. As such, effect sizes were entered into the analyses for each outcome per study. The qualitative (i.e., no effect, small, moderate, large) codes for VA were coded as 0 for no effect, 1 for small effect, 2 for moderate effect, and 3 for large effect. In addition, we computed moment product correlations at the case level. We did not include VA in this correlation as the designation of effectiveness per VA required inspection across cases in each study and not at the case level. Furthermore, we did not include BC-SMD in either the analysis of study level or case level data due to insufficient results.</p> <hd id="AN0188856546-18">Results</hd> <p>In the following section, we describe the results in order of the research questions. We begin with a description of the findings from the systematic literature review and study selection. Next, we summarize the methodological quality across all studies followed by a discussion of the findings per each of six strategies. Specifically, we define the strategy and describe the: (a) study that evaluated the strategy; (b) quality of the study per CEC and WWC; (c) outcomes per expert VA and CDC; and (d) outcomes per effect size indices (i.e., NAP, Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, LLR, and BC-SMD).</p> <hd id="AN0188856546-19">Literature Review and Study Selection</hd> <p>As can be seen in Figure 1, the PRISMA flow diagram, we conducted the literature review in four phases: (a) identifying potential articles, (b) screening of article titles and abstracts for potential inclusion, (c) coding of full text articles, and (d) determining final articles based on the eligibility coding. The initial key term electronic database and ancestral search resulted in 8,933 articles. Next, we conducted backward snowballing ([<reflink idref="bib35" id="ref89">35</reflink>]) by examining reference lists in 15 literature reviews and meta-analyses to identify potentially relevant publications, which yielded an additional 54 articles for total of 8,987 documents. Next, we eliminated 1,318 duplicate articles, which led to 7,669. Within these articles, we further searched by applying additional criteria that resulted in the removal of 6,190 articles leaving 1,479 articles. Next four authors screened all abstracts and titles resulting in the removal of 901 articles leaving 578.</p> <p>Two authors independently screened full-text articles (<emph>k</emph> = 578) to determine if they met full inclusion criteria. Articles (<emph>k</emph> = 572) were excluded for the following reasons: (a) case study (<emph>k</emph> = 5); (b) class wide (<emph>k</emph> = 6); (c) date (<emph>k</emph> = 1); (d) design (<emph>k</emph> = 13); (e) not receiving special education services as a student with EBD (<emph>k</emph> = 57); (f) not an intervention study (<emph>k</emph> = 51); (g) not an experimental study (<emph>k</emph> = 8); (h) not in the United States (<emph>k</emph> = 10); (i) outcomes were not measured in general education settings (<emph>k</emph> = 376); (j) other (<emph>k</emph> = 39), and (k) no graph (<emph>k</emph> = 6). To evaluate interrater reliability, we calculated as simple agreement (total agreement/total articles × 100) at 95%. Authors reached consensus on disagreements resulting in 100% agreement. Retained articles (<emph>k</emph> = 6) were independently read in full by two authors and coded for the inclusion criteria (see section below) resulting in six articles retained for final review ([<reflink idref="bib2" id="ref90">2</reflink>]; [<reflink idref="bib41" id="ref91">41</reflink>]; [<reflink idref="bib45" id="ref92">45</reflink>]; [<reflink idref="bib48" id="ref93">48</reflink>]; [<reflink idref="bib66" id="ref94">66</reflink>]; [<reflink idref="bib70" id="ref95">70</reflink>]).</p> <p>A total of six studies (see Supplementary Appendix 1) of the effectiveness of strategies (behavior-specific praise [BSP], Self-Determined Learning Model of Instruction [SDLMI], sound field amplification, culturally responsive computer based social skills [CRCBSSI], choice of reinforcer, and Self-Regulated Strategy Development [SRSD]) that included quantitative data for 13 outcomes (i.e., on-task, off task, verbal interactions, goal attainment, quality, number of response parts, number of words, following adult directions, not following directions, seconds to engagement [latency], duration, correct, and incorrect) used in general education classrooms for students with EBD that met all inclusion criteria. Across all studies, there were 106 cases. The publication dates for the studies spanned from 2006 to 2016. A total of 22 students identified as EBD served as participants that met our inclusion criteria. Three studies took place in elementary, one in a middle school, and two in high school general education classrooms.</p> <p>Four studies employed a multiple-baseline design or a modified multiple-baseline design ([<reflink idref="bib2" id="ref96">2</reflink>]; [<reflink idref="bib41" id="ref97">41</reflink>]; [<reflink idref="bib45" id="ref98">45</reflink>]; [<reflink idref="bib48" id="ref99">48</reflink>]). Other designs included multiple probe (<emph>k</emph> = 1; [<reflink idref="bib66" id="ref100">66</reflink>]); multi-element (<emph>k</emph> = 1; [<reflink idref="bib70" id="ref101">70</reflink>]). Most studies, 67% (<emph>k</emph> = 5; [<reflink idref="bib41" id="ref102">41</reflink>]; [<reflink idref="bib48" id="ref103">48</reflink>]; [<reflink idref="bib66" id="ref104">66</reflink>]; [<reflink idref="bib70" id="ref105">70</reflink>]) reported fidelity/integrity and four studies (67%) reported social validity ([<reflink idref="bib2" id="ref106">2</reflink>]; [<reflink idref="bib41" id="ref107">41</reflink>]; [<reflink idref="bib66" id="ref108">66</reflink>]; [<reflink idref="bib70" id="ref109">70</reflink>]).</p> <hd id="AN0188856546-20">Summary of Methodological Quality</hd> <p>Ratings of the quality of the methodology of each study are illustrated in Table 1 and in the following section. One study ([<reflink idref="bib48" id="ref110">48</reflink>]) was both methodologically sound per CEC (i.e., met all eight quality indicators) and met the WWC standards. Three studies ([<reflink idref="bib41" id="ref111">41</reflink>]; [<reflink idref="bib66" id="ref112">66</reflink>]; [<reflink idref="bib70" id="ref113">70</reflink>]) were methodologically sound per CEC, but did not meet WWC standards. The three studies did not meet WWC standards, as the authors did not report IOA per all phases and all participants; although, all did report acceptable Inter Observer Agreement (IOA) on at least 20% of studies across all phases.</p> <p>Table 1. WWC and CEC Quality Rating per Study.</p> <p>Graph</p> <p> <ephtml> <table><colgroup><col align="left" /><col align="char" char="." /><col align="char" char="." /><col align="char" char="." /></colgroup><thead><tr><th align="left">Study</th><th align="center">WWC Quality of Evidence (Stage 2)</th><th align="center">WWC Evidence Visual Analysis (Stage 3)</th><th align="center">CEC Research Quality</th></tr></thead><tbody><tr><td><xref ref-type="bibr" rid="bibr2">Allday et al. (2012)</xref></td><td>DNMS</td><td>Moderate</td><td>No</td></tr><tr><td><xref ref-type="bibr" rid="bibr41">Kelly & Shogren (2014)</xref></td><td>DNMS</td><td>Strong</td><td>Yes</td></tr><tr><td><xref ref-type="bibr" rid="bibr45">Maag & Anderson (2006)</xref></td><td>MS</td><td>Strong</td><td>No</td></tr><tr><td><xref ref-type="bibr" rid="bibr48">Mason et al. (2013)</xref></td><td>MS</td><td>Strong</td><td>Yes</td></tr><tr><td><xref ref-type="bibr" rid="bibr66">Robinson-Ervin et al. (2016)</xref></td><td>DNMS</td><td>Strong</td><td>Yes</td></tr><tr><td><xref ref-type="bibr" rid="bibr70">Skerbetz & Kostewicz (2015)</xref></td><td>DNMS</td><td>No Evidence</td><td>Yes</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note.</emph> WWC = What Works Clearinghouse; CEC = Council for Exceptional Children; VA = Visual Analysis based on [<reflink idref="bib87" id="ref114">87</reflink>]; WWC Design Standards: MS = Meets Standards; DNMS = Does Not Meet Standards; Yes = Absolute Coding for all 8 quality indicators; No = at least 1 quality indicator is not met.</p> <hd id="AN0188856546-21">Findings per Intervention Type</hd> <p>Results per intervention type are described below. We begin with a description of the intervention followed by a description of the studies per that intervention. For each study, we provide results specific to effect size indices (see Appendix 2) and status of functional relation per expert VA and CDC (see Appendix 3).</p> <hd id="AN0188856546-22">Behavior Specific Praise (BSP)</hd> <p>BSP is verbal affirmation provided to students that includes an explicit description of the behavior ([<reflink idref="bib75" id="ref115">75</reflink>], [<reflink idref="bib76" id="ref116">76</reflink>]). One multiple baseline design study with three students ([<reflink idref="bib2" id="ref117">2</reflink>]) evaluated the effects of BSP given to an entire elementary general education class by the teacher (as opposed to the target student) on the on-task behavior of five students with EBD. The study did not meet the WWC quality standards as there was no evidence of measurement or reporting of interobserver agreement across phases and participants and authors did not respond to our query. In addition, the study did not meet CEC criteria, as the authors did not report fidelity of implementation or describe baseline sufficiently for replication.</p> <p>A functional relation was established through expert VA with moderate evidence and no intervention effect was established by CDC. The researchers found that the percentage of time on task increased with a small effect per Tau-U<subs>A v. B, Trend A</subs> and LRR (Tau-U<subs>A v. B, Trend A</subs> = 0.64; proportionate change per LRR = 30.4%; CI<subs>95%</subs> [14.12%, 48.17%]), moderate effect per Tau<subs>nonoverlap</subs> and NAP (Tau<subs>nonoverlap</subs> =.66, CI<subs>95%</subs> [0.30, 0.85]; NAP =.83 CI<subs>95%</subs> [0.65, 0.92]), a large effect per BC-SMD (1.34 CI<subs>95%</subs> [0.26, 2.42]).</p> <hd id="AN0188856546-23">Self-Determined Learning Model of Instruction (SDLMI)</hd> <p>The Self-Determined Learning Model of Instruction was developed by [<reflink idref="bib54" id="ref118">54</reflink>] and [<reflink idref="bib85" id="ref119">85</reflink>]. SDLMI is an intervention used to teach students self-determination skills (i.e., self-regulated self-directed learning). Specifically, students are taught to establish emotional, behavioral, and/or academic goals and evaluate their progress through self-monitoring strategies. One multiple baseline study with four students ([<reflink idref="bib41" id="ref120">41</reflink>]) evaluated the use of SDLMI in a special education class and implemented in a general education class to improve on and off task behavior. The study did not meet the WWC quality standards as there was no evidence of measurement or reporting of interobserver agreement across phases and participants and authors did not respond to our query.</p> <p>A functional relation was established through expert VA with strong effects and an intervention effect was established by CDC. The effect size for the change in on-task behavior between phases was large per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, NAP, BC-SMD (Tau<subs>nonoverlap</subs> =.96, CI<subs>95</subs> [0.82, 0.99]; Tau-U<subs>A v. B, Trend A</subs>=.87; NAP =.98, CI<subs>95</subs> [0.91, 1.00]; BC-SMD = 1.84, CI<subs>95</subs> [−0.41, 4.08]), the proportionate change per LRR was 226.13%, CI<subs>95</subs> [145.38%, 334.47%]. The researchers found that the percentage of time off task decreased with a large effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, NAP, and BC-SMD (Tau<subs>nonoverlap</subs> =.97, CI<subs>95</subs> [0.83, 0.99]; Tau-U<subs>A v. B, Trend A</subs> = 1.34; NAP =.98, CI<subs>95</subs> [0.92, 1.00], BD-SMD = 2.25 [−4.25, −0.26]), the proportionate change per LRR was −63.01%, CI<subs>95</subs> [−69.28%, −55.46%].</p> <hd id="AN0188856546-24">Sound Field Amplification</hd> <p>Sound field amplification is the use of a system that magnifies the teachers voice and spreads it evenly throughout the classroom with loudspeakers in the class and teacher use of an FM microphone. One multiple baseline design study ([<reflink idref="bib45" id="ref121">45</reflink>]) with six students evaluated the use of sound field amplification in a general education classroom on the speed in which students complied with task demands (i.e., tasks teachers perceived students would not enjoy) and high interest tasks (i.e., tasks teachers perceived students would enjoy). The study met the WWC quality standards; however, it did not meet CEC criteria as the authors did not report fidelity of implementation.</p> <p>A functional relation was established through VA with a strong effect for task demand and high interest directions and an intervention effect was established by CDC for both conditions. Overall, the researchers found that the use of sound field amplification on the speed in which students began either a low interest or high interest task following teacher directions was effective with a moderate omnibus effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau = 0.75, CI<subs>95</subs> [0.69, 0.80]; Tau-U<subs>A v. B, Trend A</subs>=.72; NAP =.88, CI<subs>95</subs> [0.85, 0.90]), and the proportionate change per LRR was −54.102%, CI<subs>95</subs> [−57.53%, −50.40%]).</p> <p>Results indicated that with directions to engage in a high interest (i.e., something students would most likely want to do) activities, time between the given direction and student beginning the task decreased with a moderate effect per Tau, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau<subs>nonoverlap</subs> =.84, CI<subs>95</subs> [0.70, 0.92]; Tau-U<subs>A v. B, Trend A</subs> =.79; NAP =.92, CI<subs>95</subs> [0.85, 0.96]), the proportionate change per LRR was −60.07%, CI<subs>95</subs> [−67.35%, −51.17%]. With directions to engage in activities that teachers perceived as something students probably would not want to do, and as such "demanding," time between the direction given and the beginning of the task decreased with small-to-moderate effects per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau = 0.58, CI<subs>95</subs> [0.39, 0.72]; Tau-U<subs>A v. B, Trend A</subs> =.46; NAP =.79, CI<subs>95</subs> [0.69, 0.86]), and the proportionate change per LRR was −39.03% CI<subs>95</subs> [−48.04%, −28.46%]. We were unable to calculate BC-SMD for this study as it is not an eligible design (i.e., multiple-baseline design across settings).</p> <hd id="AN0188856546-25">Self-Regulated Strategy Development for Quick Write</hd> <p>Self-Regulated Strategy Development (SRSD) for Quick Write is a involves applying SRSD to help students write paragraph responses to teacher developed questions related to content area (e.g., science, social studies) instruction to increase reflection and elaboration on the topic being studied ([<reflink idref="bib89" id="ref122">89</reflink>]). One multiple baseline design study with two students with EBD ([<reflink idref="bib48" id="ref123">48</reflink>]) evaluated the use of SRSD with a focus on quality of writing, parts of writing, and number of words in inclusive settings. The study met the WWC quality standards and CEC criteria.</p> <p>A functional relation was established through expert VA with strong effects and evidence of an intervention effect for quality and words, but not for parts. Overall, results for the study indicated that SRSD had a small-to-moderate omnibus effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau = 0.36 CI<subs>95</subs> [0.12, 0.55]; Tau-U<subs>A v. B, Trend A</subs> =.38; NAP =.68, CI<subs>95</subs> [0.56, 0.78]), the proportionate change per LRR was 55.81%, CI<subs>95</subs> [−9.96%, 169.60%]. BC-SMD was not calculated for this study as it did not meet the assumptions requiring at least three cases.</p> <p>The use of SRSD for Quick Writes resulted in increased quality of writing with a moderate-to-large effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau = 0.75, CI<subs>95</subs> [0.36, 0.91]; Tau-U<subs>A v. B, Trend A</subs> =.67; NAP =.88, CI<subs>95</subs> [0.68, 0.96]), and the proportionate change per LRR was 57.48%, CI<subs>95</subs> [22.66%, 102.19%]. The use of SRSD for Quick Writes resulted in increased writing parts with a small-to-moderate effect per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau = 0.59, CI<subs>95</subs> [0.19, 0.81]; Tau-U<subs>A v. B, Trend A</subs> =.48; NAP =.80, CI<subs>95</subs> [0.60, 0.91]) and the proportionate change per LRR was 46.19%, CI<subs>95</subs> [15.69%, 84.73%]. The use of SRSD for Quick Writes resulted in increased words with a moderate-to-large effect per TAU, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau = 0.77, CI<subs>95</subs> [0.38, 0.92]; Tau-U<subs>A v. B, Trend A</subs> =.83; NAP =.88, CI<subs>95</subs> [0.69, 0.96]), the proportionate change per LRR was 45.85%, CI<subs>95</subs> [18.34%, 79.77%].</p> <hd id="AN0188856546-26">Culturally Responsive Computer-Based Social Skills Instruction (CRCBSSI)</hd> <p>CRCBSSI involves the use of technology to proactively teach students appropriate social skills through their own unique identity (e.g., culture, beliefs, and experiences; [<reflink idref="bib26" id="ref124">26</reflink>]). One multiple probe study with five students ([<reflink idref="bib66" id="ref125">66</reflink>]) evaluated the use of CRCBSSI implemented in a special education class with generalization data taken in a general education classroom. Data included were the percentage of compliant behavior while in general education classrooms. The study did not meet the WWC quality standards as there was no evidence of measurement or reporting of interobserver agreement across phases and participants and authors did not respond to our query; however, the study did meet the CEC standards.</p> <p>A functional relation was established through expert VA. Overall, the researchers found that the use of CRCBSS was effective with a small-to-moderate omnibus effect per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> =.56, CI<subs>95</subs> [0.15, 0.80]; Tau-U<subs>A v. B, Trend A</subs> =.54; NAP =.78, CI<subs>95</subs> [0.58, 0.90]), and moderate per BC-SMD (0.60 CI<subs>95</subs> [−0.26, 1.46]), and the proportionate change per LRR was 73.94%, CI<subs>95</subs> [8.63%, 178.51%].</p> <hd id="AN0188856546-27">Choice</hd> <p>When using choice as a behavioral intervention, teachers provide students with two or more options following seven common implementation steps ([<reflink idref="bib28" id="ref126">28</reflink>]; [<reflink idref="bib36" id="ref127">36</reflink>]). [<reflink idref="bib70" id="ref128">70</reflink>] evaluated the use of choice in a general education classroom with students with EBD. The researchers compared the effects of no reinforcer, teacher-selected reinforcer, and student choice of reinforcer during math instruction for two students with EBD. Furthermore, the research team tested this across work identified as on students' independent and instructional math levels. The researchers measured the effects on the following dependent variables seconds of engagement, number of engagements, digits correct, and digits incorrect. BC-SMD was not calculated for this study as the number of participants was insufficient (i.e., 2 < 3).</p> <p>The study did not meet the WWC quality standards as there was no evidence of measurement or reporting of interobserver agreement across phases and participants and authors did not respond to our query. The study met the CEC standards. The study demonstrated no evidence of effects via expert VA.</p> <hd id="AN0188856546-28">No Choice of Reinforcer, Engagement</hd> <p>Results indicated that when students were not given a choice of reinforcers, seconds to engagement at the independent level as not impacted resulting in no effects per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> = −0.06, CI<subs>95</subs> [−0.36, 0.26]; Tau-U<subs>A v. B, Trend A</subs> = 0) and increased effect per NAP with a small effect (NAP =.47, CI<subs>95</subs> [0.32, 0.63]), and the proportionate change per LRR was only 0.58%, CI<subs>95</subs> [−40.28%, 69.38%]. Results indicated that when not given a choice of reinforcers, seconds to engagement at the instructional level had no impact per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> = −0.10, CI<subs>95</subs> [−0.38, 0.20; Tau-U<subs>A v. B, Trend A</subs> = −0.05]), a small effect per NAP (NAP =.45, CI<subs>95</subs> [0.31, 0.61]), and the proportionate change per LRR was only 1.40%, CI<subs>95</subs> [−37.52%, 64.55%]).</p> <hd id="AN0188856546-29">No Choice of Reinforcer, Academic Responding</hd> <p>Results indicated that when students were not given a choice of reinforcers, academic responding at the independent level was not impacted resulting in no effects per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau = −0.05, CI<subs>95</subs> [−0.34, 0.25]; Tau-U<subs>A v. B, Trend A</subs> = −0.05), and a small effect per NAP (NAP =.48, CI<subs>95</subs> [0.33, 0.63]), and the proportionate change per LRR was negligible (−1.70%, CI<subs>95</subs> [−35.01%, 48.66%]). Results indicated that when students were not given a choice of reinforcers, academic responding at the instructional level increased resulting in a small effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau<subs>nonoverlap</subs> =.08, CI<subs>95</subs> [−0.21, 0.36]; Tau-U<subs>A v. B, Trend A</subs> =.09; NAP =.54, CI<subs>95</subs> [0.40, 0.68]), and the proportionate change per LRR was 5.12%, CI<subs>95</subs> [−24.15%, 45.70%].</p> <hd id="AN0188856546-30">Choice of Reinforcer, Engagement</hd> <p>Results indicated that when students were given a choice of two preferred reinforcers at the independent level, the number of engagements were not impacted resulting in no effects per Tau<subs>nonoverlap</subs> (Tau<subs>nonoverlap</subs> = −0.03, CI<subs>95</subs> [−0.08, 0.32]), small effects per Tau-U<subs>A v. B, Trend A</subs> and NAP (Tau-U<subs>A v. B, Trend A</subs> =.05; NAP =.48, CI<subs>95</subs> [0.31, 0.66], and the proportionate change per LRR was negligible (−4.29%, CI<subs>95</subs> [−49.19%, 80.29%]). Results indicated that when students were given a choice of two preferred reinforcers at the instructional level, the number of engagements had no impact resulting in no effect per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> = −0.19, CI<subs>95</subs> [−0.45, 0.11]; Tau-U<subs>A v. B, Trend A</subs> = −0.14) a small effect per NAP (NAP =.41, CI<subs>95</subs> [0.27, 0.56]), and the proportionate change per LRR was −11.15%, CI<subs>95</subs> [−47.55%, 50.50%].</p> <hd id="AN0188856546-31">Choice of Reinforcer, Academic Responding</hd> <p>Results indicated that when given a choice of reinforcers, academic responding at the independent level was not impacted resulting in no effect per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> = −0.02, CI<subs>95</subs> [−0.36, 0.33]; Tau-U<subs>A v. B, Trend A</subs> = −0.01), a small effect per NAP (NAP =.49, CI<subs>95</subs> [0.32, 0.67]), and the proportionate change per LRR was negligible (0.78%, CI<subs>95</subs> [−37.10%, 61.48%]). Results indicated that when students were given a choice of reinforcers, academic responding at the instructional level increased with a small effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, and NAP (Tau<subs>nonoverlap</subs> =.13, CI<subs>95</subs> [−0.17, 0.41]; Tau-U<subs>A v. B, Trend A</subs> =.13; NAP =.57, CI<subs>95</subs> [0.41, 0.70], and the proportionate change per LRR was 5.37%, CI<subs>95</subs> [−23.129%, 44.75%].</p> <hd id="AN0188856546-32">No Choice Versus Choice of Reinforcer, Engagement</hd> <p>Results indicated that when comparing seconds of engagements when students were not given a choice to when they were given a choice of two reinforcers at the independent level, seconds to engagement were not impacted resulting in no effect per Tau<subs>nonoverlap</subs> (Tau<subs>nonoverlap</subs> = −0.04, CI<subs>95</subs> [−0.41, 0.35]; Tau-U<subs>A v. B, Trend A</subs> = −0.06), a small effect per NAP (NAP =.48, CI<subs>95</subs> [0.30, 0.67]), and the proportionate change per LRR was −9.33%, CI<subs>95</subs> [−54.00%, 78.75%].</p> <p>Results indicated that when comparing seconds of engagement when students were given no choice of reinforcer to choice of two preferred reinforcers, the seconds of engagement at the instructional level were not impacted resulting in with no effect per Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (Tau<subs>nonoverlap</subs> = −0.09, CI<subs>95</subs> [−0.38, 0.23]; Tau-U<subs>A v. B, Trend A</subs> = −0.14), a small effect per NAP (NAP =.46, CI<subs>95</subs> [0.31, 0.61]), and the proportionate of change per LRR was −12.38%, CI<subs>95</subs>% [−49.75%, 52.76%].</p> <hd id="AN0188856546-33">No Choice Versus Choice of Reinforcer, Academic Responding</hd> <p>Results indicated that when comparing seconds of engagement when students were not given a choice of reinforcer to when they were given a choice, academic responding at the independent level was slightly impacted with a small effect per Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs> and NAP (Tau<subs>nonoverlap</subs> =.06, CI<subs>95</subs> [−0.32, 0.41]; Tau-U<subs>A v. B, Trend A</subs> =.12; NAP =.53, CI<subs>95</subs> [0.34, 0.71]), and a proportionate change per LRR of 2.53%, CI<subs>95</subs> [−39.10%, 72.62%].</p> <p>Results indicated that comparing conditions when students were not given a choice of reinforcer to when they were given choice of two preferred reinforcers, academic responding at the instructional level did not change resulting in no effect per Tau<subs>nonoverlap</subs> (Tau<subs>nonoverlap</subs> = 0, CI<subs>95</subs> [−0.31, 0.30]), Tau-U<subs>A v. B, Trend A</subs> (Tau = −0.06) a small effect per NAP (NAP =.50, CI<subs>95</subs> [0.35, 0.65]), and the proportionate change per LRR was 0.24%, CI<subs>95</subs> [−25.16%, 34.26%].</p> <hd id="AN0188856546-34">Agreement Across Visual Analysis and Effect Sizes</hd> <p>When comparing each approach to VA and quantitative indices (per study outcome; see Table 2), large and statistically significant correlations were found between: (a) Tau<subs>nonoverlap</subs> and Tau-U<subs>A v. B, Trend A</subs> (<emph>r</emph> =.970, <emph>p</emph> <.01), NAP (<emph>r</emph> = 1.00), and LRR (<emph>r =</emph>.776); (b) Tau-U<subs>A v. B, Trend A</subs> and NAP (<emph>r</emph> =.968, <emph>p</emph> <.01) and LRR (<emph>r</emph> =.713, <emph>p</emph> <.01) and (c) NAP and LRR (<emph>r</emph> =.777. <emph>p</emph> <.01). At the case level (see Table 3), large and statistically significant correlations were found between: (a) CDC and Tau<subs>nonoverlap</subs> (<emph>r =</emph>.399), Tau-U<subs>A v. B, Trend A</subs>. (<emph>r =</emph>.354), and NAP (<emph>r =</emph>.400); between Tau<subs>nonoverlap</subs> and Tau U, NAP, LRR; Tau-U<subs>A v. B, Trend A</subs> and NAP and LRR, and NAP and LRR.</p> <p>Table 2. Correlation Matrix at the Study Outcome Level.</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">Variable</th><th align="center">k</th><th align="center">M</th><th align="center"><italic>SD</italic></th><th align="center">1</th><th align="center">2</th><th align="center">3</th><th align="center">4</th><th align="center">5</th></tr></thead><tbody><tr><td>1. VA<xref ref-type="table-fn" rid="tfn2">a</xref></td><td>9</td><td>2.89</td><td>.133</td><td /><td /><td /><td /><td /></tr><tr><td>2. CDC<xref ref-type="table-fn" rid="tfn2">a</xref></td><td>8</td><td>.75</td><td>.463</td><td>.655</td><td /><td /><td /><td /></tr><tr><td>3. Tau</td><td>9</td><td>.30</td><td>.407</td><td>.195</td><td>.568</td><td /><td /><td /></tr><tr><td>4. Tau_U</td><td>9</td><td>.31</td><td>.420</td><td>.131</td><td>.440</td><td>.970<xref ref-type="table-fn" rid="tfn3">**</xref></td><td /><td /></tr><tr><td>5. NAP</td><td>9</td><td>.65</td><td>.203</td><td>.199</td><td>.561</td><td>1.00<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.968<xref ref-type="table-fn" rid="tfn3">**</xref></td><td /></tr><tr><td>6. LRR</td><td>9</td><td>29.47</td><td>53.803</td><td>.260</td><td>.319</td><td>.776<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.713<xref ref-type="table-fn" rid="tfn3">**</xref></td><td>.777<xref ref-type="table-fn" rid="tfn3">**</xref></td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 VA on a scale of 0 = no effect, 1 = small effect, 2 = moderate effect, 3 = large effect; CDC = Conservative Dual Criterion and was coded as 0 for no effect and 1 for treatment effect.</item> <item>3 <emph>p</emph> <.001.</item> </ulist> <p>Table 3. Correlation Matrix at the Case Level.</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="." /></colgroup><thead><tr><th align="left">Variable</th><th align="center"><italic>n</italic></th><th align="center">M</th><th align="center"><italic>SD</italic></th><th align="center">Tau</th><th align="center">Tau-U</th><th align="center">NAP</th><th align="center">LRR</th></tr></thead><tbody><tr><td>1. CDC</td><td>53</td><td>0.89</td><td>0.32</td><td /><td /><td /><td /></tr><tr><td>2. Tau</td><td>106</td><td>0.51</td><td>0.54</td><td>.399<xref ref-type="table-fn" rid="tfn4">*</xref></td><td /><td /><td /></tr><tr><td>3. Tau_U</td><td>106</td><td>0.49</td><td>0.59</td><td>.354<xref ref-type="table-fn" rid="tfn4">*</xref></td><td>.944<xref ref-type="table-fn" rid="tfn4">**</xref></td><td /><td /></tr><tr><td>4. NAP</td><td>106</td><td>0.76</td><td>0.27</td><td>.400<xref ref-type="table-fn" rid="tfn4">*</xref></td><td>1.00<xref ref-type="table-fn" rid="tfn4">**</xref></td><td>.944<xref ref-type="table-fn" rid="tfn4">**</xref></td><td /></tr><tr><td>5. LRR</td><td>105</td><td>44.01</td><td>92.36</td><td>.114</td><td>.445<xref ref-type="table-fn" rid="tfn4">**</xref></td><td>.456<xref ref-type="table-fn" rid="tfn4">**</xref></td><td>.445<xref ref-type="table-fn" rid="tfn4">**</xref></td></tr></tbody></table> </ephtml> </p> <p>4 <emph>p</emph> <.05; **<emph>p</emph> <.001.</p> <p>When comparing outcomes per benchmarks for VA, Tau<subs>nonoverlap</subs>, Tau-U<subs>A v. B, Trend A</subs>, NAP, LRR, and BC-SMD per study outcome, the strongest agreements were between NAP and Tau<subs>nonoverlap</subs> (100%) and Tau-U<subs>A v. B, Trend A</subs> and CDC (88.00%). The lowest agreements were between VA and LRR (11.00%) and VA and Tau-U<subs>A v. B, Trend A</subs> (22.00%).</p> <hd id="AN0188856546-35">Summary of Study Level Effectiveness per VA and CDC</hd> <p>At the study outcome level, expert VA indicated that eight outcomes demonstrated strong evidence of effectiveness ([<reflink idref="bib41" id="ref129">41</reflink>] [on task, off task demand, high interest directions]; [<reflink idref="bib48" id="ref130">48</reflink>] [quality, parts, words]; [<reflink idref="bib66" id="ref131">66</reflink>] [compliance]). Expert VA indicated that one study, [<reflink idref="bib2" id="ref132">2</reflink>], found moderate evidence that providing behavior specific praise resulted in an increase in on-task behavior.</p> <p>Finally, no evidence was found in one study ([<reflink idref="bib70" id="ref133">70</reflink>]) of the effects of adding choice or no choice of reinforcer when comparing tasks at the student independent or instructional level. CDC indicated six intervention effects ([<reflink idref="bib41" id="ref134">41</reflink>]; [<reflink idref="bib45" id="ref135">45</reflink>]; [<reflink idref="bib48" id="ref136">48</reflink>] [quality, words]) and two non-effects ([<reflink idref="bib2" id="ref137">2</reflink>]; [<reflink idref="bib48" id="ref138">48</reflink>] [parts of writing]). As such, agreement between expert VA and CDC was 75%. Due to the limited sample size and heterogeneous grouping of studies, we opted to not report an omnibus effect size estimate across studies, but rather describe effectiveness of cases within each strategy. As such, in the section below, we provide a description of the intervention and study followed by the effects per effect size, VA and CDC, and quality of the design per WWC and CEC standards.</p> <hd id="AN0188856546-36">Discussion</hd> <p>The purpose of this review was to systematically review the research examining various intervention strategies for students with EBD in general education settings. Since [<reflink idref="bib65" id="ref139">65</reflink>], only six studies have been published with 106 total cases (i.e., AB phases) and 22 total participants. As such, we conclude that research has not kept pace with the current educational trend toward including students with EBD in general education classrooms. In the following sections, we discuss the characteristics of the literature base, describe interventions that hold promise for supporting students with EBD in general education classrooms, and unpack issues of research quality and the consistency across methods for reviewing and meta-analyzing single-case research.</p> <hd id="AN0188856546-37">Characteristics of the Literature</hd> <p>Perhaps the most significant finding of this review is the dearth of experimental research examining the inclusion of students with EBD in general education indicating a lack of empirically supported recommendations for teachers and students. It is essential that the field develops and evaluates strategies that are effective in general education settings due to the challenges, and result stress, that many teachers of students with EBD report ([<reflink idref="bib27" id="ref140">27</reflink>]). Because many assume that placement in the least restrictive environment would, by virtue of setting, lead to improved academic and behavioral outcomes for students with EBD ([<reflink idref="bib13" id="ref141">13</reflink>]), there is a need to determine those practices most likely to work in general education classrooms ([<reflink idref="bib50" id="ref142">50</reflink>]). Unfortunately, the research is not providing sufficient guidance indicating a need for a more concerted effort to develop and test strategies in general education classrooms specifically designed for students with EBD.</p> <hd id="AN0188856546-38">Methodological Quality</hd> <p>In addition to the lack of research available, overall quality of the existing studies is mixed. Based on WWC standards, quality appears less than acceptable with most studies not meeting evidence standards because of the methods used for interassessor agreement. In fact, only two studies met the WWC standards for interassessor agreement ([<reflink idref="bib45" id="ref143">45</reflink>]; [<reflink idref="bib48" id="ref144">48</reflink>]). The most common issue, which impacted approximately one-third of the studies, was that authors did not report interassessor agreement for each participant in each phase. Instead, the tendency was to report interassessor agreement for 80% or more opportunities throughout the entire study as has been the recommendation from experts in the field for several decades ([<reflink idref="bib32" id="ref145">32</reflink>]; [<reflink idref="bib38" id="ref146">38</reflink>], [<reflink idref="bib40" id="ref147">40</reflink>]). As the authors did not provide sufficient information within their studies, and did not respond to our queries for clarification, we deemed the study as not meeting the standard. This dimension of interassessor agreement resulted in the elimination of several studies and contributed to a change in the overall evidence classification. As such, it is important to consider the impact of such a narrow and specific criterion when summarizing the literature for practitioners in the field ([<reflink idref="bib73" id="ref148">73</reflink>]). As researchers, we might leave practitioners with choices of evidence-based interventions, which is unfortunate as this finding is based on strict rule interpretation that might eliminate helpful strategies.</p> <p>Contrarily, approximately two-thirds of the studies met CEC interassessor agreement standards because this method does not require authors to report a percentage of sessions in which interassessor agreement must be collected. As such, more studies met the interassessor agreement criteria according to the CEC standards than the WWC. However, the CEC standards do require authors to report intervention fidelity which led to low ratings for two articles ([<reflink idref="bib2" id="ref149">2</reflink>]; [<reflink idref="bib45" id="ref150">45</reflink>]). Many researchers consider fidelity an essential component of methodological rigor because the degree to which the intervention was implemented as designed has implications for determining the presence of a functional relation between the independent and dependent variables ([<reflink idref="bib74" id="ref151">74</reflink>]). That is, without providing a measure of intervention adherence, it is difficult to confidently assert that it was the intervention that produced changes in the dependent variable and not some other variable in the setting. The differences in the CEC and WWC standards suggest that users must be aware of the strengths and limitations of each method and interpret the results for consumers accordingly.</p> <hd id="AN0188856546-39">Intervention Effectiveness</hd> <p>In relation to findings regarding the effectiveness of interventions, the results of the current review suggest that three strategies hold promise for students with EBD in general education settings. First, research on SDLMI indicated that the intervention (a) produced large effects across all five effect sizes calculated for on-task behavior and across four effect sizes for off-task behavior; (b) produced strong effects via expert VA; and (c) resulted in an intervention effect per CDC. In addition, the quality of the study indicated that via CEC quality standards, the findings can be considered trustworthy. As such, it is possible that SDLMI would also be beneficial for students with EBD in similar settings. Although it is probable that the strategy would need to be taught in a class with a smaller teacher student ratio prior to implementation in a larger setting, as learning the component skills requires support and practice ([<reflink idref="bib10" id="ref152">10</reflink>]).</p> <p>Second, although only one study included in the current meta-analysis ([<reflink idref="bib2" id="ref153">2</reflink>]) evaluated BSP in a general education classroom, the outcomes were judged to be strong via expert VA and effect sizes and the methodological review indicated that the study met WWC standards. In addition, the use of BSP has been found to increase the appropriate behaviors and decrease inappropriate behaviors of students in varying settings in prior systematic reviews ([<reflink idref="bib67" id="ref154">67</reflink>]; [<reflink idref="bib75" id="ref155">75</reflink>]). When considered alongside prior research, it is likely that the use of BSP can be successful in general education settings with students with EBD. However, we caution that it may not be sufficient to result in substantial behaviors changes without evaluating the function of the behavior or without teaching additional skills.</p> <p>Third, we provide preliminary evidence that sound field amplification might be effective for students with EBD in general education settings. [<reflink idref="bib45" id="ref156">45</reflink>] evaluated the effects of sound field amplification with outcomes deemed to have moderate effects via all effect sizes calculated, determined to have an intervention effect via CDC, and strong effects via expert VA. In addition, the study could be considered methodologically sound as it was judged to meet WWC standards. Prior research has revealed mixed effects of sound field amplification. Several studies have revealed benefits of amplification for students without disabilities and those with learning disabilities in the areas of listening and attending ([<reflink idref="bib18" id="ref157">18</reflink>]; [<reflink idref="bib59" id="ref158">59</reflink>]). However, [<reflink idref="bib19" id="ref159">19</reflink>] reported mixed results based on outcome for sound field amplification. The researchers found larger gains in performance on non-verbal processing speed and listening comprehension for students in elementary classrooms with amplified sound as compared to those in classrooms without amplified sound. Despite these promising results, no group differences were found on academic attainment or performance measures of math, reading, or spelling. As such, findings for sound field amplification indicate a potential to provide benefit to students with EBD in general education settings and should be further evaluated.</p> <p>In addition, we were surprised by two findings. First, results of one source study indicated that providing students with a choice of reinforcers ([<reflink idref="bib70" id="ref160">70</reflink>]) provided no evidence of a functional relation between choice and the student outcomes except for one condition and one outcome. Following the procedures identified in the WWC for expert VA, we found no evidence of a functional relation due to the degree of overlapping data points and the within phase variability. In prior studies, providing students with a choice has been found to have large effects in special education settings with increases in appropriate behavior and decreases in problem behavior (see [<reflink idref="bib60" id="ref161">60</reflink>]). As such, research is needed to validate the effectiveness and determine the moderators of providing students with EBD a choice in all settings.</p> <p>Second, we found that many interventions with preliminary evidence of effectiveness in special education settings had not been explored in general education settings. [<reflink idref="bib80" id="ref162">80</reflink>] found that 16 types of interventions were promising with supporting evidence for students with EBD in special education settings, yet our results suggest researchers have yet to investigate these interventions in general education settings to evaluate their efficacy. We only found one article assessing the effects with students with EBD in general education settings. We recommend the exploration of generalizing the effects of those interventions.</p> <hd id="AN0188856546-40">Comparison Across Visual Analysis Approaches and Effect sizes</hd> <p>When determining the presence of a functional relation, we compared expert VA and the CDC method in eight eligible studies. We found agreement in three quarters of studies, which aligns closely with findings from [<reflink idref="bib88" id="ref163">88</reflink>] who reported 83% agreement between expert VA and the CDC. Both disagreements in this review had experts rating the study as demonstrating an effect, whereas the CDC decision rule suggested no effect was present. For instance, [<reflink idref="bib2" id="ref164">2</reflink>] provided a variable baseline for two cases which might have masked trend, leading to divergent conclusions between the two methods. [<reflink idref="bib48" id="ref165">48</reflink>] focused on number of strategy parts (e.g., topic sentence, explanation, counter-reason) written which led to one case with initial baseline performance that was high and with a contra-therapeutic trend and another case with a small immediate level change. These findings highlight the benefit of using a structured approach, such as the CDC to compliment expert VA and how the methods sometimes lead to divergent conclusions. Discrepant results between the CDC and VA may encourage researchers to conduct deeper analysis of the data series to determine why differing conclusions were reached.</p> <p>Complete agreement (100%) was found between expert VA, CDC, Tau, Tau-U, NAP, LRR, and BC-SMD on only one outcome (i.e., on-task) in the [<reflink idref="bib41" id="ref166">41</reflink>] study of BSP. However, in most of the experiments the quantitative indices appeared to align closely. For example, when evaluating total words written in [<reflink idref="bib48" id="ref167">48</reflink>], Tau, Tau-U, and NAP all indicated a moderate effect while the LRR suggested a small effect. As previously mentioned, placing strict cut points to place a qualitative label on the magnitude of the treatment effect can enhance the ability to communicate results to others but at the risk of losing valuable information. This is clear in the case of [<reflink idref="bib2" id="ref168">2</reflink>] where a 1-point difference would have changed the Tau-U<subs>A v. B, Trend A</subs> from small to moderate.</p> <p>The selection of an optimal approach for assessing the presence of a functional relation within single-case research remains an ongoing conversation. Historically, VA was considered the gold standard ([<reflink idref="bib34" id="ref169">34</reflink>]); however, concerns with the subjectivity, bias, and questions around reliability led researchers to find a more objective approach ([<reflink idref="bib57" id="ref170">57</reflink>]). For instance, [<reflink idref="bib22" id="ref171">22</reflink>] developed methods for conducting masked VA while [<reflink idref="bib20" id="ref172">20</reflink>] recommended the use of structured approaches to improving the reliability and validity of decisions. More recently, however, some have recommended that the field do away with VA all together in favor of effect size measures. Perhaps most prominently, the WWC Procedures Handbook, Version 4.1 (2020) removed VA all together when evaluating single-case research. Consensus from the field, however, is that researchers select metrics and analysis approaches that in relation to the question posed, the context of the research, understanding of the nature of the dependent variable, and the hypothesized characteristics of the data series ([<reflink idref="bib47" id="ref173">47</reflink>]). Theoretically, if parameters for inclusion in a systematic review or meta-analysis are broad and the included studies have substantial differences in research questions, data characteristics, and measurement procedures it might be difficult to identify the "best" quantitative approach that is suitable for all included experiments. Further work is needed to provide guidance for applied researchers on making these decisions.</p> <hd id="AN0188856546-41">Limitations</hd> <p>This study is not without limitations. First, we only included studies that had undergone the peer review process and were published. This likely introduces publication bias as unpublished studies, such as white papers and dissertations, were not included. Furthermore, it is possible that studies that found non-effects were not published and as such were not included here ([<reflink idref="bib16" id="ref174">16</reflink>]). Second, as there is no replication of any of the studies, all conclusions are preliminary. Third, we extracted data using a digital graph extractor and as such, it is possible that some data points were not exact. Finally, although the systematic review process was conducted with independent reviewers and reliability was calculated, it is possible that we did not locate all relevant studies.</p> <hd id="AN0188856546-42">Conclusion</hd> <p>In conclusion, with the trend toward inclusive education for students with EBD, the findings suggest the need for more research with this population in the least restrictive environment. The lack of information available to teachers in supporting students with EBD in inclusive settings runs counter to the increased emphasis on supporting students with disabilities alongside their peers. Even with the lack of research, the quality of the research and the positive results across studies is encouraging. Furthermore, we applaud the continued development and refinement of approaches for analyzing single-case research including particularly recent work on effect size indices and quality indicators. This work is advancing the field and combined with the results of the current review will provide valuable information to educators in the field teaching students with EBD in general education settings.</p> <hd id="AN0188856546-43">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-1-bhd-10.1177_01987429241261382 for Academic and Behavioral Strategies in Inclusive Settings for Students With EBD: A Meta Analysis by Denise A. Soares, Judith R. Harrison, Corey Peltier and Kathryn Press in Behavioral Disorders</p> <hd id="AN0188856546-44">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-2-bhd-10.1177_01987429241261382 for Academic and Behavioral Strategies in Inclusive Settings for Students With EBD: A Meta Analysis by Denise A. Soares, Judith R. Harrison, Corey Peltier and Kathryn Press in Behavioral Disorders</p> <hd id="AN0188856546-45">Supplemental Material</hd> <p>Graph: Supplemental material, sj-docx-3-bhd-10.1177_01987429241261382 for Academic and Behavioral Strategies in Inclusive Settings for Students With EBD: A Meta Analysis by Denise A. Soares, Judith R. Harrison, Corey Peltier and Kathryn Press in Behavioral Disorders</p> <p>The authors thank Paulomi Mehta and Nancy Colorado for their assistance with this manuscript.</p> <ref id="AN0188856546-46"> <title> References </title> <blist> <bibl id="bib1" idref="ref23" type="bt">1</bibl> <bibtext> Agran M., Cavin M., Wehmeyer M., Palmer S. (2006). 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  Label: Title
  Group: Ti
  Data: Academic and Behavioral Strategies in Inclusive Settings for Students with EBD: A Meta Analysis
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Denise+A%2E+Soares%22">Denise A. Soares</searchLink><br /><searchLink fieldCode="AR" term="%22Judith+R%2E+Harrison%22">Judith R. Harrison</searchLink><br /><searchLink fieldCode="AR" term="%22Corey+Peltier%22">Corey Peltier</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3138-4126">0000-0003-3138-4126</externalLink>)<br /><searchLink fieldCode="AR" term="%22Kathryn+Press%22">Kathryn Press</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Behavioral+Disorders%22"><i>Behavioral Disorders</i></searchLink>. 2025 51(1):39-57.
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  Label: Availability
  Group: Avail
  Data: SAGE Publications and Hammill Institute on Disabilities. 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
– Name: PeerReviewed
  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 19
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Information Analyses
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Students+with+Disabilities%22">Students with Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Emotional+Disturbances%22">Emotional Disturbances</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Disorders%22">Behavior Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Inclusion%22">Inclusion</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Effectiveness%22">Program Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Classroom+Techniques%22">Classroom Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Success%22">Success</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Positive+Reinforcement%22">Positive Reinforcement</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Determination%22">Self Determination</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Management%22">Self Management</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustics%22">Acoustics</searchLink><br /><searchLink fieldCode="DE" term="%22Culturally+Relevant+Education%22">Culturally Relevant Education</searchLink><br /><searchLink fieldCode="DE" term="%22Reinforcement%22">Reinforcement</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1177/01987429241261382
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0198-7429<br />2163-5307
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: More students with emotional and behavioral disorders (EBD) than ever before spend most of their time in general education. To increase their academic and behavioral success, students with EBD need access to empirically supported interventions and services. The purpose of this systematic review and meta-analysis was to evaluate strategy effectiveness for students with EBD in K-12 inclusive settings. Identified studies were assessed with two approaches for evaluating methodological quality and multiple methods for assessing intervention effects. Results indicated that there is a dearth of empirical support for strategies implemented in general education classrooms for students with EBD though most of the studied reviewed were of high quality with moderate-to-large effects. In addition to the practical findings, the research team compared review methods with findings indicating agreement between expert visual analysis and more structured approaches for visual analysis. For the quantitative metrics, results indicated variable agreement across methods. Implications for research and practice are discussed.
– Name: AbstractInfo
  Label: Abstractor
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  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1487693
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1487693
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/01987429241261382
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 39
    Subjects:
      – SubjectFull: Students with Disabilities
        Type: general
      – SubjectFull: Emotional Disturbances
        Type: general
      – SubjectFull: Behavior Disorders
        Type: general
      – SubjectFull: Inclusion
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Elementary Secondary Education
        Type: general
      – SubjectFull: Program Effectiveness
        Type: general
      – SubjectFull: Classroom Techniques
        Type: general
      – SubjectFull: Success
        Type: general
      – SubjectFull: Educational Research
        Type: general
      – SubjectFull: Positive Reinforcement
        Type: general
      – SubjectFull: Self Determination
        Type: general
      – SubjectFull: Self Management
        Type: general
      – SubjectFull: Acoustics
        Type: general
      – SubjectFull: Culturally Relevant Education
        Type: general
      – SubjectFull: Reinforcement
        Type: general
    Titles:
      – TitleFull: Academic and Behavioral Strategies in Inclusive Settings for Students with EBD: A Meta Analysis
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Denise A. Soares
      – PersonEntity:
          Name:
            NameFull: Judith R. Harrison
      – PersonEntity:
          Name:
            NameFull: Corey Peltier
      – PersonEntity:
          Name:
            NameFull: Kathryn Press
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0198-7429
            – Type: issn-electronic
              Value: 2163-5307
          Numbering:
            – Type: volume
              Value: 51
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Behavioral Disorders
              Type: main
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