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Long-Term Trends in Socially Maladjusted Behavior of Students with and without Emotional and Behavioral Disorders: A 22-Year Repeated Cross-Sectional Study

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Title: Long-Term Trends in Socially Maladjusted Behavior of Students with and without Emotional and Behavioral Disorders: A 22-Year Repeated Cross-Sectional Study
Language: English
Authors: Matthew C. Lambert (ORCID 0000-0002-7387-3780), Antonis Katsiyannis, John W. Maag, W. Alex Mason, Michael H. Epstein
Source: Behavioral Disorders. 2025 50(2):63-75.
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: 13
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Secondary Education
Descriptors: Elementary School Students, Secondary School Students, Antisocial Behavior, Emotional Disturbances, Student Behavior, Trend Analysis
DOI: 10.1177/01987429241269464
ISSN: 0198-7429
2163-5307
Abstract: Although the construct of social maladjustment has been used for the last six decades, relatively little research has addressed secular trends in socially maladjusted behaviors over time, and even fewer studies have addressed trends for students identified with emotional disturbance (ED). The purpose of this study was to use two U.S. nationally representative cross-sectional cohorts, one sampled in 1998 (n = 1,509) and one sampled in 2020 (n = 1,513), to examine long-term trends in the socially maladjusted behaviors of students with ED and their peers without disabilities. Results indicated that (a) socially maladjusted behaviors were significantly lower for the 2020 cohort compared with 1998 cohort, (b) the decrease from 1998 to 2020 was significantly more pronounced for students with ED compared with peers without disabilities, and (c) only adolescent students demonstrated significant decreases in socially maladjusted behaviors. Potential explanations, limitations of the study, and implications for schools are discussed.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1456572
Database: ERIC
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  Value: <anid>AN0182120033;bhd01feb.25;2025Jan10.01:47;v2.2.500</anid> <title id="AN0182120033-1">Long-Term Trends in Socially Maladjusted Behavior of Students With and Without Emotional and Behavioral Disorders: A 22-Year Repeated Cross-Sectional Study </title> <p>Although the construct of social maladjustment has been used for the last six decades, relatively little research has addressed secular trends in socially maladjusted behaviors over time, and even fewer studies have addressed trends for students identified with emotional disturbance (ED). The purpose of this study was to use two U.S. nationally representative cross-sectional cohorts, one sampled in 1998 (n = 1,509) and one sampled in 2020 (n = 1,513), to examine long-term trends in the socially maladjusted behaviors of students with ED and their peers without disabilities. Results indicated that (a) socially maladjusted behaviors were significantly lower for the 2020 cohort compared with 1998 cohort, (b) the decrease from 1998 to 2020 was significantly more pronounced for students with ED compared with peers without disabilities, and (c) only adolescent students demonstrated significant decreases in socially maladjusted behaviors. Potential explanations, limitations of the study, and implications for schools are discussed.</p> <p>Keywords: social maladjustment; child behavior; emotional disturbance; cross-sectional cohort design; secular trends</p> <p>Severe conduct or delinquent behaviors in the school context disrupt academic achievement and, when persistent, result in serious school disciplinary actions that can limit students' subsequent educational attainment, occupational success, and well-being ([<reflink idref="bib28" id="ref1">28</reflink>]). In the context of the Education for All Handicapped Children Act (later renamed the [<reflink idref="bib24" id="ref2">24</reflink>]), such behaviors—which include vandalism, stealing, substance misuse, and related activities—have been termed <emph>social maladjustment</emph>. National and regional surveillance studies conducted with cross-sectional cohorts of students indicated that socially maladjusted behaviors are prevalent in school settings (see [<reflink idref="bib53" id="ref3">53</reflink>]) and are particularly elevated for students with emotional disturbance (ED) compared with peers without ED (see [<reflink idref="bib52" id="ref4">52</reflink>]). Although the "snapshots" that these types of studies provide are informative, most are short-term and are unable to determine the degree to which there are secular (long-term) trends in socially maladjusted behaviors that reflect either an increase or decrease in problem behavior over an extended period of time (cf. [<reflink idref="bib8" id="ref5">8</reflink>]). The current study addresses this gap by comparing the socially maladjusted behaviors of students in two matched, nationally representative cohorts separated by a 22-year period and examining moderation of these trends by disability status as well as by gender, school level, and race/ethnicity (including potential higher-order interactions).</p> <hd id="AN0182120033-2">Secular Trends in Emotional and Behavioral Functioning</hd> <p>In the past few decades, several large, nationally representative studies have assessed the emotional and behavioral functioning of different cohorts of children across time periods spanning multiple decades. An important line of cross-sectional research used the Achenbach System of Empirically Based Assessment (ASEBA; [<reflink idref="bib3" id="ref6">3</reflink>]), an assessment battery used to measure children's emotional and behavioral problems. In the ASEBA system, parent-, teacher-, and/or child ratings are used to measure a child's standing on eight "narrow-band" emotional and behavior problems. Achenbach and colleagues (e.g., [<reflink idref="bib1" id="ref7">1</reflink>], [<reflink idref="bib2" id="ref8">2</reflink>]) collected parent completed ASEBA ratings of different cohorts of children and adolescents in 1976, 1989, and 1999. The researchers reported that, on average, children's problem behavior worsened from 1976 to 1989 and then improved from 1989 to 1999. Similarly, Dutch researchers, using parent and teacher completed ASEBA rating forms completed in 1983 and 1993, reported similar results ([<reflink idref="bib51" id="ref9">51</reflink>]). In both sets of research studies, differences across time were small in magnitude.</p> <p>Several more recent studies have examined secular trends in problem behaviors in the general population of children and adolescents in the 21st century. Most of these studies used parent- and/or self-report of such behaviors, although a few studies incorporated teacher reports in school contexts (e.g., [<reflink idref="bib2" id="ref10">2</reflink>]). Regardless of respondent, results have generally indicated that problem behaviors have declined in recent decades. In a systematic review of 19 studies conducted in the United States and internationally, [<reflink idref="bib8" id="ref11">8</reflink>] reported that while externalizing types of problems remained relatively stable, most studies found increases in internalizing behaviors, particularly for girls. Clearly, such findings are informative and suggest research and development efforts focus on the screening, identification, prevention, and treatment for children and adolescents with or at risk of internalizing problems. These cross-sectional studies underscore the value of using repeated measurement over extended period of time to monitor the prevalence and magnitude of the emotional and behavioral problems of children and adolescents.</p> <hd id="AN0182120033-3">Secular Trends in Socially Maladjusted Behaviors</hd> <p>Unfortunately, there is limited school-based research examining trends of socially maladjusted behaviors over the last 20 years. Such information is critical because it may suggest possible causes, identify vulnerable populations, and inform practitioners in designing service delivery systems as well as influence policy makers as they allocate funds to address behavioral functioning among students. However, several nationally representative cross-sectional studies have used self-report data to assess changes of social maladjustment behaviors among adolescents. Using data from the National Survey on Drug Use and Health, [<reflink idref="bib22" id="ref12">22</reflink>] measured the prevalence of substance use and delinquent behaviors among 12- to 17-year-olds. The data indicated a significant decline between 2003 and 2014, leading the researchers to interpret these declines as reflecting a general trend in externalizing, conduct, and delinquent behaviors rather than a localized trend in the specific behaviors measured in the study. In another noteworthy study, [<reflink idref="bib9" id="ref13">9</reflink>] analyzed data from the Youth Risk Behavior Survey spanning the years 1999–2017. The Survey consists of several nationally representative cross-sectional cohorts with data collected via self-report. The researchers focused on trends in substance abuse, delinquency, and sexual activity among boys and girls in high school. The data indicated a decline across the group of socially maladjusted behaviors and suggested a generalized reduction in the underlying tendency to engage in such behaviors.</p> <p>There also are available data, which have been collected over the past two decades, focused on criminal behaviors in educational settings. In 1998, schools reported 2.7 million nonfatal crimes (theft plus violent crime) at school and 2.5 million away from school; prevalence rates were 101 crimes per 1,000 students at school and 95 crimes per 1,000 outside the school among students ages 12 to 18 ([<reflink idref="bib29" id="ref14">29</reflink>]). In contrast, data from 2018 showed substantially lower incidents with 836,000 nonfatal incidents at school and 410,000 away from school, with prevalence rates being 33 crimes per 1,000 students at school and 16 crimes per 1,000 outside the school ([<reflink idref="bib53" id="ref15">53</reflink>]). Similarly, in 1998, there were more than 2.6 million juvenile arrests ([<reflink idref="bib46" id="ref16">46</reflink>]), whereas in 2018 only 728,280 arrests were made ([<reflink idref="bib41" id="ref17">41</reflink>]). Collectively, these data suggest substantial decreases in criminal behavior in and outside of educational settings from 1998 to 2018.</p> <hd id="AN0182120033-4">Need for Ongoing Rigorous Cohort Comparisons of Socially Maladjusted Behavior</hd> <p>Informative as those findings have been, there is an ongoing need for more rigorous studies that evaluate comparable (e.g., probabilistic, or systematically matched) cohorts of students over an extended period of time using identical measures of socially maladjusted behaviors. Such studies are rare, and those that have been conducted demonstrate varying patterns of results. For example, the previously mentioned work by [<reflink idref="bib2" id="ref18">2</reflink>] reported that AESBA ratings completed by parents of 7- to 16-year-olds in 1976, 1989, and 1999 indicated that problem scores increased from 1976 to 1989 and then decreased from 1989 to 1999, but still remained higher than in 1976. In addition, rates of service utilization for children with "deviant total problems" were 30.5% in 1989 and 26.6% in 1999 reflecting statistically insignificant differences suggesting that service utilization may not be a significant mechanism underlying the observed decreases in emotional and behavioral problems.</p> <p>More recently, [<reflink idref="bib19" id="ref19">19</reflink>] analyzed teacher ratings on the Scales for Assessing Emotional Disturbance (SAED; [<reflink idref="bib19" id="ref20">19</reflink>]) for students with school identified ED between 1998 and 2020 and found that in 1998, students with ED exhibited significantly more problems than a matched group of peers in 2020 on approximately 30% of the assessment items. Specifically, students in the 1998 cohort demonstrated significantly more problems in the areas of inappropriate behaviors (e.g., disrespectful, disruptive, destroys things) and relationship problems compared with peers in the 2020 cohort. Because of the high-risk status of students with ED, these findings were unlikely to generalize to the majority of students in the general population. In a follow-up study, [<reflink idref="bib37" id="ref21">37</reflink>] extended the research by replicating these comparisons among students without disabilities. The researchers found that students in the 2020 cohort had more problems related to learning and somatic issues compared with students in the 1998 cohort. Interaction tests further indicated that the cohort differences in these two factors were comparable across gender groups. There were no statistically significant cohort differences on the remaining SAED factors, including relationship problems, inappropriate behavior, and unhappiness/depression, for either girls or boys.</p> <hd id="AN0182120033-5">Purpose of the Current Study</hd> <p>The current study capitalizes on the unique availability of SAED teacher ratings for students with ED and students without disabilities across decades, which allows for direct comparisons of the socially maladjusted behaviors exhibited by these two groups of students over a 22-year period. The SAED assesses the severity of six socially maladjusted behaviors, including vandalizing property, engaging in illegal or gang activity, abusing drugs or alcohol, engaging in sexual behavior, running away, and stealing. In addition, these ratings were examined in the context of how trends may differ due to potential moderating factors such as disability status, school level, gender, and race/ethnicity. This nuanced approach is particularly important for three reasons: (a) there are disparities between racially minoritized and non-minoritized children reflecting disproportionate identification of African American children compared with White peers (see [<reflink idref="bib48" id="ref22">48</reflink>]), (b) ED is more common in males but still prevalent in females (e.g., 28% of students with ED in 2017 were females), and gender differences are apparent in patterns of externalizing behaviors (see [<reflink idref="bib23" id="ref23">23</reflink>]; [<reflink idref="bib43" id="ref24">43</reflink>]), and (c) differences in several problematic behaviors between younger and older students have been documented in large population studies ([<reflink idref="bib10" id="ref25">10</reflink>]).</p> <p>Consequently, the purpose of the present study was to examine whether (a) there was a significant difference (increase or decrease) in teacher-reported socially maladjusted behaviors between 1998 and 2020; (b) the trends across time differed between students with ED and their peers without disabilities; (c) the trends across time differed by gender, school level, or race/ethnicity; and (d) the interaction between Cohort × ED was moderated by gender, school level, or race/ethnicity. Two specific hypotheses were supported by the existing literature. First, there would be a significant overall decrease in socially maladjusted behaviors between 1998 and 2020. Multiple studies have documented decreasing trends in problem and delinquency behaviors of children and adolescents in the general population (e.g., [<reflink idref="bib2" id="ref26">2</reflink>]; [<reflink idref="bib8" id="ref27">8</reflink>]; [<reflink idref="bib9" id="ref28">9</reflink>]; [<reflink idref="bib22" id="ref29">22</reflink>]). Second, and related to the first, the reduction in socially maladjusted behaviors would be more pronounced for students with ED compared with peers without disabilities. While few studies have focused on long-term secular trends for children with ED (or clinical emotional and behavior disorders), the cumulative evidence suggests that the emotional and behavioral functioning of children with emotional and behavioral disorders (including those with clinical <emph>Diagnostic and Statistical Manual of Mental Disorders</emph> [<emph>DSM</emph>] diagnoses) has improved over the last several decades at a more substantial rate than children in the general population ([<reflink idref="bib1" id="ref30">1</reflink>]; [<reflink idref="bib19" id="ref31">19</reflink>]; [<reflink idref="bib37" id="ref32">37</reflink>]). No a priori hypotheses were generated regarding moderation by gender, school level, or race/ethnicity, nor about any of the higher-order (i.e., three-way) interactions because there is no extant research on which to base such hypotheses.</p> <hd id="AN0182120033-6">Method</hd> <p></p> <hd id="AN0182120033-7">Data Source</hd> <p>Participants were drawn from the 1998 and 2020 norming data collection samples for the Scales for Assessing Emotional Disturbance–Rating Scale (SAED-RS; [<reflink idref="bib18" id="ref33">18</reflink>]; [<reflink idref="bib19" id="ref34">19</reflink>]). The 1998 cohort included 2,480 students 5 through 18 years of age who were sampled from 34 U.S. states and the District of Columbia, representing all four census regions of the United States: Northeast, Midwest, South, and West. Slightly over 52% of the 1998 cohort were students school-identified with ED (<emph>n</emph> = 1,291). The 2020 cohort included 2,399 students 5 through 18 years of age who were sampled from 16 U.S. states and the District of Columbia, again representing all four census regions. Just over 20% of the 2020 cohort were students school-identified with ED (<emph>n</emph> = 491). Because the two cohorts differed in terms of the proportion of students with ED as well as other demographic characteristics, a case-control matching approach was used to randomly select a subset of students who were <emph>exact matches</emph> on disability status, gender, school level, and race/ethnicity.</p> <hd id="AN0182120033-8">Participants</hd> <p>Participants were 3,022 students 5 through 18 years of age, with a fraction under 50% of the sample representing the 1998 cohort (<emph>n</emph> = 1,509) and just over 50% representing the 2020 cohort (<emph>n</emph> = 1,513). This minor imbalance was due to missing item-level data for four students in the 1998 cohort. For the overall sample, slightly more than 57% of the sample were male (<emph>n</emph> = 1,726), and 70.8% were White/Non-Hispanic (<emph>n</emph> = 2,138), 20.8% were African American/Non-Hispanic (<emph>n</emph> = 630), and 8.4% were Hispanic (<emph>n</emph> = 254). Students who identified as Asian, Native American, or another race or ethnicity were excluded from this study due to very small sample sizes. Just under 55% of participants were elementary school students (<emph>n</emph> = 1,657), 22.7% were middle school students (<emph>n</emph> = 685), and 22.5% were high school students (<emph>n</emph> = 680).</p> <p>Twenty-nine percent of the sample (<emph>n</emph> = 877) were students with school-identified ED and had an active IEP at the time of data collection. Students with ED were not identified with any other disability at the time of data collection (students with concomitant disabilities were excluded from the study). Of the students identified with ED, 69.0% were male (<emph>n</emph> = 605), and 61.8% were White/Non-Hispanic (<emph>n</emph> = 542), 31.4% were African American/Non-Hispanic (<emph>n</emph> = 275), and 6.8% were Hispanic (<emph>n</emph> = 60). Nearly 33% were elementary school students (<emph>n</emph> = 289), 22.4% were middle school students (<emph>n</emph> = 196), and 44.7% were high school students (<emph>n</emph> = 392). Demographic characteristics for the overall sample and subsample of students with ED were virtually identical between the 1998 and 2020 cohorts due to the matching procedure; however, trivial differences did arise due to missing data for four students in the 1998 cohort.</p> <hd id="AN0182120033-9">Procedures</hd> <p>The sample recruitment procedures were consistent for the 1998 and 2020 normative data collection efforts (note that data collection for the 2020 cohort was completed just before the COVID-19 pandemic). The test authors recruited educators from across the United States, contacting them by mail, email, or telephone and asking them to participate in the SAED norming process. Teachers who agreed to participate were asked to either complete the SAED-RS on all students on their class roster(s) or select an unbiased sample of their students using the following readily applied procedure:</p> <p>First, decide how many students you wish to rate. Then, start at either the top or bottom of your class roster and rate every student. Do not skip any student unless you have known this student for less than two months. Stop selecting and rating students when you have reached the number of students you decided to rate.</p> <p>Each rater also provided demographic information for each rated student (e.g., age in years, grade, race, ethnicity) and for herself or himself (e.g., gender, race, ethnicity).</p> <p>For both the 1998 and 2020 cohorts, SAED-RS data were collected using a two-stage sampling process, where the teachers were selected first and then students. However, data on the nested structure of the assessment data were not collected (e.g., which students were rated by which teachers) and therefore the nested structure could not be accounted for or directly modeled in the analysis. This represents a limitation that relates to the interpretation of the data analysis results, primarily the statistical significance of the observed effects.</p> <hd id="AN0182120033-10">Measure</hd> <p>The SAED is a standardized, norm-referenced approach to identifying ED, was first normed in 1998 ([<reflink idref="bib18" id="ref35">18</reflink>]), and re-normed in 2020 ([<reflink idref="bib19" id="ref36">19</reflink>]). The SAED-3 system includes a teacher Rating Scale (SAED-RS), a Screener, a parent interview protocol (i.e., Developmental/Educational Questionnaire), and a direct classroom observation procedure (i.e., Observation Form). The SAED-RS is a teacher-completed rating scale consisting of 45 items for students ages 5 to 18 years. The SAED-RS used to collect the data in 1998 and 2020 was identical in terms of the 45 items, directions, and instructions to teachers. Teachers rate each item on a 4-point Likert-type scale (0 = <emph>not a problem</emph>, 1 = <emph>mild problem</emph>, 2 = <emph>considerable problem</emph>, and 3 = <emph>severe problem</emph>). The SAED-RS has six subscales: (<reflink idref="bib1" id="ref37">1</reflink>) Inability to Learn, (<reflink idref="bib2" id="ref38">2</reflink>) Relationship Problem, (<reflink idref="bib3" id="ref39">3</reflink>) Inappropriate Behavior, (<reflink idref="bib4" id="ref40">4</reflink>) Unhappiness or Depression, (<reflink idref="bib5" id="ref41">5</reflink>) Physical Symptoms or Fears, and (<reflink idref="bib6" id="ref42">6</reflink>) Socially Maladjusted. As stated earlier, the Socially Maladjusted subscale consists of six items (e.g., vandalizes property, takes part in gang activity, abuses drugs/alcohol, steals). A high score denotes a considerable problem involving the student's severe antisocial and delinquent activity. For this sample, coefficient alpha (internal consistency) of the Socially Maladjusted score was.85.</p> <p>Prior research has demonstrated that scores from the 1998 and 2020 SAED-RS assessments meet acceptable standards for reliability (i.e., test–retest, interrater) and validity evidence (e.g., content, construct, criterion, convergent; see, for example, [<reflink idref="bib18" id="ref43">18</reflink>]; [<reflink idref="bib19" id="ref44">19</reflink>]; [<reflink idref="bib30" id="ref45">30</reflink>]; [<reflink idref="bib32" id="ref46">32</reflink>]). Furthermore, the SAED-RS scores have demonstrated validity evidence based on internal structure including a well-defined confirmatory factor model ([<reflink idref="bib31" id="ref47">31</reflink>]) and measurement invariance; that is, the scores reflect the same underlying dimensions of emotional and behavioral problems across race ([<reflink idref="bib33" id="ref48">33</reflink>]), ethnicity ([<reflink idref="bib33" id="ref49">33</reflink>]), age, and gender ([<reflink idref="bib19" id="ref50">19</reflink>]). Measurement invariance has also been established across the 1998 and 2020 normative cohorts ([<reflink idref="bib19" id="ref51">19</reflink>]). Because measurement invariance has been established across these subgroups and across cohorts, SAED-RS scores are comparable across the students included in the study.</p> <hd id="AN0182120033-11">Data Analysis</hd> <p>Stata v17 was used to analyze data within a factorial analysis of variance (ANOVA) framework where the Socially Maladjusted raw score was the dependent variable and cohort, ED status, gender, school level, and race/ethnicity were the independent variables. All two-way interactions involving either cohort or ED status were included in the analysis as were the three-way interactions between Cohort × ED × Gender, Cohort × ED × School Level, and Cohort × ED × Race.</p> <p>While numerous effects were estimated in the ANOVA, the focus of the analysis was on the main effect of cohort and the interactions involving cohort.</p> <p>The main effect of cohort indicated whether, on average, the Socially Maladjusted scores differed between the two cohorts. The interaction between Cohort × ED indicated whether the effect of cohort differed across students with ED and students without disabilities. For example, a significant interaction might indicate that there was a moderate difference between cohorts for students with ED, but no difference between cohorts for students without disabilities. In other words, the trend across time was different for students with ED compared with students without disabilities. The interactions between Cohort × Gender, Cohort × School Level, and Cohort × Race indicated whether the effect of cohort differed across levels of gender, school level, or race, respectively.</p> <p>The three-way interactions between Cohort × ED × Gender, Cohort × ED × School Level, Cohort × ED × Race indicate whether the two-way interaction between Cohort × ED varied across levels of gender, school level, or race, respectively. For example, a significant three-way interaction could indicate that the two-way interaction Cohort × ED was present for elementary students, present for middle school students, but absent for high school students. In other words, the trends across time were different for elementary and middle school students with ED compared with peers without disabilities, but equivalent for high school students with ED and peers without disabilities.</p> <p>There were eight effects of interest estimated in the ANOVA—many other effects were estimated because they formed part of important interactions, but were not themselves of substantive interest in this study (e.g., main effect of gender, ED × Race, Race × Gender). In addition to the tests of main effects and interactions, there were a total of 10 simple effects tested in order to probe significant interactions. To account for multiple comparisons, we conservatively set the per-test significance level at.001, which resulted in a.018 probability of making a single Type I error and a.0002 probability of making two Type I errors across the collection of tests.</p> <p>Effect sizes were computed for <emph>significant</emph> main effects and interaction effects as well as for <emph>all</emph> simple effects. Partial eta-squared (η<subs>p</subs><sups>2</sups>) was computed for significant main effects. Partial eta-squared indicates the proportion of variance attributable to the effect after accounting for other effects in the model. For significant main effects (with 1 df) and all simple effects, Cohen's <emph>d</emph> was computed, which indicates the mean difference between the 1998 and 2020 cohorts scaled in standard deviation units. [<reflink idref="bib13" id="ref52">13</reflink>] suggested that <emph>d</emph> values ranging from 0.00 to 0.19 were trivial, 0.20 to 0.49 were small, 0.50 to 0.79 were medium, and ≥0.80 were large.</p> <p>In addition to Cohen's general guidelines, we also used findings from [<reflink idref="bib1" id="ref53">1</reflink>], [<reflink idref="bib8" id="ref54">8</reflink>], and [<reflink idref="bib9" id="ref55">9</reflink>] to inform the magnitude of effects within the specific context of long-term secular trends. Achenbach and colleagues analyzed teacher ratings of behavior and emotional functioning (using the ASEBA, 2009) for nationally representative cohorts sampled in 1989 and 1999. They found that Total Problems scores decreased by an average of 0.10 standard deviations over that time period. Bor and colleagues reviewed results of five studies on secular trends of behavioral and emotional functioning reported by either parents or teachers using the ASEBA or the Strengths and Difficulties Questionnaire ([<reflink idref="bib21" id="ref56">21</reflink>]). While the findings of these studies were mixed and many of the studies reported non-significant trends over time on individual subscales, the magnitude of the statistically significant effects ranged from <emph>d</emph> =|0.13 to 0.52|. [<reflink idref="bib9" id="ref57">9</reflink>] analyzed risk behaviors (e.g., drug use and delinquency) from 1999 to 2017 and found that those behaviors had decreased, on average, for high school students between 0.54 and 0.73 standard deviations over that period of time.</p> <p>The magnitude of an interaction is generally reported as a Cohen <emph>f</emph><sups>2</sups> effect size, which indicates the proportion of explained variance attributable to the interaction term. [<reflink idref="bib13" id="ref58">13</reflink>] suggested values of.02,.15, and.35 indicate small, medium, and large effects, respectively. However, these guidelines were primarily developed to interpret the magnitude of main effects rather than interactions. A comprehensive review of applied psychological research revealed that the mean interaction effect size was <emph>f</emph><sups>2</sups> =.009, the median effect size was <emph>f</emph><sups>2</sups> =.002, and that 75% of interactions were smaller than <emph>f</emph><sups>2</sups> =.005 ([<reflink idref="bib4" id="ref59">4</reflink>]), so we interpreted the interaction effect sizes within this context rather than Cohen's general guidelines. Therefore, we considered <emph>f</emph><sups>2</sups> values less than.002 as small, those ranging between.002 and.009 as medium, and ≥.009 as large.</p> <hd id="AN0182120033-12">Results</hd> <p></p> <hd id="AN0182120033-13">Main Effect of Cohort</hd> <p>The unconditional means and standard deviations for each subgroup are reported in Table 1. The results from the ANOVA model are reported in Table 2. The main effect of Cohort was statistically significant (<emph>F</emph><subs>1, 2998</subs> = 52.52, <emph>p</emph> <.0001, η<subs>p</subs><sups>2</sups> =.017, <emph>d</emph> = −0.26), indicating that the 2020 cohort, on average, had lower social maladjustment scores compared with the matched sample of peers in the 1998 cohort. The magnitude of this decrease was substantially larger than the effect observed by [<reflink idref="bib1" id="ref60">1</reflink>], consistent with effects reported in [<reflink idref="bib8" id="ref61">8</reflink>], but smaller than the effects reported in [<reflink idref="bib9" id="ref62">9</reflink>].</p> <p>Table 1. Unconditional Means and Standard Deviations for Student Participant Characteristics.</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="center">Student Characteristics</th><th align="center"><italic>n</italic></th><th align="center"><italic>M</italic></th><th align="center"><italic>SD</italic></th></tr></thead><tbody><tr><td><bold>Disability</bold></td><td /><td /><td /></tr><tr><td>Emotional disturbance</td><td>877</td><td>2.24</td><td>3.46</td></tr><tr><td>No disability</td><td>2,145</td><td>0.32</td><td>1.28</td></tr><tr><td><bold>Cohort</bold></td><td /><td /><td /></tr><tr><td>1998</td><td>1,509</td><td>1.11</td><td>2.57</td></tr><tr><td>2020</td><td>1,513</td><td>0.64</td><td>2.03</td></tr><tr><td><bold>Gender</bold></td><td /><td /><td /></tr><tr><td>Female</td><td>1,296</td><td>0.69</td><td>1.97</td></tr><tr><td>Male</td><td>1,726</td><td>1.01</td><td>2.55</td></tr><tr><td><bold>Race/ethnicity</bold></td><td /><td /><td /></tr><tr><td>White/Non-Hispanic</td><td>2,138</td><td>0.70</td><td>2.03</td></tr><tr><td>Black/Non-Hispanic</td><td>630</td><td>1.44</td><td>3.00</td></tr><tr><td>Hispanic</td><td>254</td><td>0.98</td><td>2.47</td></tr><tr><td><bold>School level</bold></td><td /><td /><td /></tr><tr><td>Elementary</td><td>1,657</td><td>0.30</td><td>0.99</td></tr><tr><td>Middle</td><td>685</td><td>1.04</td><td>2.59</td></tr><tr><td>High</td><td>680</td><td>2.13</td><td>3.53</td></tr></tbody></table> </ephtml> </p> <p>Table 2. ANOVA Results for Effects in Study on Socially Maladjusted Behaviors.</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="." /></colgroup><thead><tr><th align="center">Model Effect</th><th align="center">SS</th><th align="center">df</th><th align="center">MS</th><th align="center"><italic>F</italic></th><th align="center"><italic>p</italic>-value</th></tr></thead><tbody><tr><td>Cohort</td><td>217.70</td><td>1</td><td>217.70</td><td>52.52</td><td><.0001</td></tr><tr><td>Emotional disturbance (ED)</td><td>1,059.03</td><td>1</td><td>1,059.03</td><td>255.47</td><td><.0001</td></tr><tr><td>Gender</td><td>0.30</td><td>1</td><td>0.30</td><td>0.07</td><td>.7880</td></tr><tr><td>School level</td><td>842.05</td><td>2</td><td>421.02</td><td>101.57</td><td><.0001</td></tr><tr><td>Race/ethnicity</td><td>176.61</td><td>2</td><td>88.30</td><td>21.30</td><td><.0001</td></tr><tr><td>Cohort × ED</td><td>54.81</td><td>1</td><td>54.81</td><td>13.22</td><td>.0003</td></tr><tr><td>Cohort × Gender</td><td>6.28</td><td>1</td><td>6.28</td><td>1.52</td><td>.2182</td></tr><tr><td>Cohort × School Level</td><td>135.15</td><td>2</td><td>67.57</td><td>16.30</td><td><.0001</td></tr><tr><td>Cohort × Race</td><td>8.87</td><td>2</td><td>4.43</td><td>1.07</td><td>.3431</td></tr><tr><td>ED × Gender</td><td>13.46</td><td>1</td><td>13.46</td><td>3.25</td><td>.0716</td></tr><tr><td>ED × School Level</td><td>193.05</td><td>2</td><td>96.52</td><td>23.29</td><td><.0001</td></tr><tr><td>ED × Race</td><td>103.56</td><td>2</td><td>51.78</td><td>12.49</td><td><.0001</td></tr><tr><td>Cohort × ED × Gender</td><td>8.410</td><td>1</td><td>8.41</td><td>2.03</td><td>.1544</td></tr><tr><td>Cohort × ED × School</td><td>77.60</td><td>2</td><td>38.80</td><td>9.36</td><td>.0001</td></tr><tr><td>Cohort × ED × Race</td><td>10.46</td><td>2</td><td>5.23</td><td>1.26</td><td>.2831</td></tr><tr><td><bold>Cohort @ ED</bold></td><td /><td /><td /><td /><td /></tr><tr><td>ED</td><td>176.99</td><td>1</td><td>176.99</td><td>42.70</td><td><.0001</td></tr><tr><td>No disability</td><td>44.06</td><td>1</td><td>44.06</td><td>10.63</td><td>.0011</td></tr><tr><td><bold>Cohort @ School Level</bold></td><td /><td /><td /><td /><td /></tr><tr><td>Elementary</td><td>11.56</td><td>1</td><td>11.56</td><td>2.79</td><td>.0951</td></tr><tr><td>Middle</td><td>156.23</td><td>1</td><td>156.23</td><td>37.69</td><td><.0001</td></tr><tr><td>High</td><td>216.45</td><td>1</td><td>216.45</td><td>52.22</td><td><.0001</td></tr><tr><td><bold>Cohort</bold> × <bold>ED @ School Level</bold></td><td /><td /><td /><td /><td /></tr><tr><td>Elementary</td><td>11.85</td><td>1</td><td>11.85</td><td>2.86</td><td>.0912</td></tr><tr><td>Middle</td><td>116.23</td><td>1</td><td>116.23</td><td>28.04</td><td><.0001</td></tr><tr><td>High</td><td>0.99</td><td>1</td><td>0.99</td><td>0.24</td><td>.6216</td></tr><tr><td><bold>Cohort @ ED (School Level = Middle)</bold></td><td /><td /><td /><td /><td /></tr><tr><td>ED</td><td>189.30</td><td>1</td><td>189.30</td><td>45.67</td><td><.0001</td></tr><tr><td>No Disability</td><td>2.61</td><td>1</td><td>2.61</td><td>0.63</td><td>.4289</td></tr></tbody></table> </ephtml> </p> <p>At the item level, the main effect of cohort was statistically significant at the.001 level for five of the six socially maladjusted behaviors (except for <emph>vandalizes property</emph>). In each case, the significant main effects demonstrated a decrease in socially maladjusted behaviors from 1998 to 2020. The odds of students in the 1998 cohort demonstrating more serious problems across the five significant behavioral indicators were 1.82 to 2.77 times higher than students in the 2020 cohort. These odds ratios represent small to medium effects ([<reflink idref="bib12" id="ref63">12</reflink>]), which tended to be larger than the effects observed by [<reflink idref="bib1" id="ref64">1</reflink>], but consistent with effects reported in [<reflink idref="bib8" id="ref65">8</reflink>].</p> <hd id="AN0182120033-14">Two-Way Interactions Involving Cohort</hd> <p>The two-way interaction between Cohort × ED was statistically significant (<emph>F</emph><subs>1, 2998</subs> = 13.22, <emph>p</emph> =.0003, <emph>f</emph><sups>2</sups> =.004), indicating that the effect of Cohort differed between students with ED and students without disabilities. A comparison of the simple effects of Cohort revealed a statistically significant simple effect for students with ED (<emph>F</emph><subs>1, 2998</subs> = 42.70, <emph>p</emph> <.0001, <emph>d</emph> = −0.43), but a non-significant effect for students without disabilities (<emph>F</emph><subs>1, 2998</subs> = 10.63, <emph>p</emph> =.0011, <emph>d</emph> = −0.21) indicating that, on average, students with ED differed significantly across cohorts, but peers did not differ at the prespecified significance level. The effect size of the interaction was medium in magnitude, and the magnitude of the simple effect for students with ED was large compared with [<reflink idref="bib1" id="ref66">1</reflink>] and [<reflink idref="bib8" id="ref67">8</reflink>], and consistent with [<reflink idref="bib9" id="ref68">9</reflink>]. This interaction is plotted in Figure 1.</p> <p>Graph: Figure 1. Two-Way Interaction Between Cohort × Emotional Disturbance.</p> <p>The two-way interaction between Cohort × School Level was also statistically significant (<emph>F</emph><subs>1, 2998</subs> = 16.30, <emph>p</emph> <.0001, <emph>f</emph><sups>2</sups> =.011), indicating that the effect of Cohort differed between students in elementary, middle, and high school. A comparison of the simple effects of Cohort at each school level revealed a significant simple effect for middle school (<emph>F</emph><subs>1, 2998</subs> = 37.69, <emph>p</emph> <.0001, <emph>d</emph> = −0.40) and high school (<emph>F</emph><subs>1, 2998</subs> = 52.22, <emph>p</emph> <.0001, <emph>d</emph> = −0.47), but a non-significant simple effect for elementary school (<emph>F</emph><subs>1, 2998</subs> = 2.79, <emph>p</emph> =.0951, <emph>d</emph> = −0.09) indicating that only students in middle school and high school demonstrated meaningfully less socially maladjusted behaviors in 2020 compared with peers in 1998. The effect size of the interaction was large in magnitude indicating salient and relevant differences across school levels, and the magnitude for both significant simple effects were large compared with [<reflink idref="bib1" id="ref69">1</reflink>] and [<reflink idref="bib8" id="ref70">8</reflink>], and consistent with [<reflink idref="bib9" id="ref71">9</reflink>]. This interaction is plotted in Figure 2.</p> <p>Graph: Figure 2 Cohort × School Level Interaction.</p> <hd id="AN0182120033-15">Three-Way Interactions Involving Cohort</hd> <p>In terms of three-way interactions, the interaction between Cohort × ED × School Level was statistically significant (<emph>F</emph><subs>1, 2998</subs> = 77.60, <emph>p</emph> =.0001, <emph>f</emph><sups>2</sups> =.006) indicating that the two-way interaction between Cohort × ED varied across school levels (<emph>or</emph> that the two-way interaction between Cohort × School Level varied across ED). When evaluated at each school level, the two-way interaction between Cohort × ED was significant for students in middle school (<emph>F</emph><subs>1, 2998</subs> = 28.04, <emph>p</emph> <.0001, <emph>f</emph><sups>2</sups> =.009), but not significant for students in elementary school (<emph>F</emph><subs>1, 2998</subs> = 2.86, <emph>p</emph> =.0912, <emph>f</emph><sups>2</sups> =.001) or high school (<emph>F</emph><subs>1, 2998</subs> = 0.24, <emph>p</emph> =.6216, <emph>f</emph><sups>2</sups> <.001). The effect size for the three-way interaction and the significant two-way interaction (at middle school) were medium in magnitude. These findings indicate that a statistically significant interaction between Cohort × ED was only detectable for students in middle school. This three-way interaction is plotted in Figure 3, which depicts the two-way interaction between Cohort × ED separately at each school level. A comparison of the simple effects of Cohort for middle school students with ED and middle students without disabilities revealed a significant simple effect for students with ED (<emph>F</emph><subs>1, 2998</subs> = 45.67, <emph>p</emph> <.0001, <emph>d</emph> = −0.44), but a non-significant effect for students without ED (<emph>F</emph><subs>1, 2998</subs> = 61.10, <emph>p</emph> <.0001, <emph>d</emph> = −0.05). The magnitude of the simple effect for students with ED was large compared with [<reflink idref="bib1" id="ref72">1</reflink>] and [<reflink idref="bib8" id="ref73">8</reflink>], and consistent with [<reflink idref="bib9" id="ref74">9</reflink>].</p> <p>Graph: Figure 3. Cohort × Disability Interaction at Each School Level.</p> <hd id="AN0182120033-16">Discussion</hd> <p>The purpose of the present study was to examine whether (a) there was a significant difference (increase or decrease) in teacher-reported socially maladjusted behaviors between the 1998 and 2020 cohorts; (b) the difference between cohorts was moderated by disability status; (c) the difference between cohorts was moderated by gender, school level, or race/ethnicity; and (d) the interaction between Cohort × Disability was moderated by gender, school level, or race/ethnicity. Results are nuanced due to significant interactions and can be summarized as follows.</p> <p>First, the overall average teacher-reported social maladjustment score was significantly lower for the 2020 cohort compared with 1998 cohort, indicating that socially maladjusted behaviors have decreased over time for school-age children. The magnitude of the overall decrease was large compared with [<reflink idref="bib1" id="ref75">1</reflink>] and consistent with the findings of [<reflink idref="bib8" id="ref76">8</reflink>]; however, this decrease was substantially smaller than decreases reported for high school students in [<reflink idref="bib9" id="ref77">9</reflink>]. Second, the decrease in behaviors from 1998 to 2020 was significantly moderated by disability status wherein students with school-identified ED demonstrated significantly larger decreases across cohorts compared with peers without disabilities. Notably, students without disabilities did not demonstrate a statistically significant difference in socially maladjusted behaviors between cohorts; note that while this effect was not statistically significant (when adjusted for multiple comparisons), it was consistent with [<reflink idref="bib8" id="ref78">8</reflink>]. Third, the two-way interaction between Cohort × School Level indicated that only high school and middle school students demonstrated significant decreases in socially maladjusted behaviors between cohorts. Decreases for middle school (<emph>d</emph> = −0.40) and high school students (<emph>d</emph> = −0.47) were large compared with findings for students in the general population reported by [<reflink idref="bib1" id="ref79">1</reflink>] and [<reflink idref="bib8" id="ref80">8</reflink>], and comparable to the magnitude of decreases reported by [<reflink idref="bib9" id="ref81">9</reflink>]. Fourth, the three-way interaction between Cohort × ED × School Level revealed that the decrease from 1998 to 2020 was only <emph>differential</emph> between students with ED and peers without disabilities in middle school—the decrease in behavior was statistically equivalent between students with ED and peers without disabilities for students in elementary and high school. In the three-way interaction, middle school students with ED demonstrated significant decreases in socially maladjusted behaviors while their peers without disabilities did not differ from 1998 to 2020. Finally, gender and ethnicity did not significantly moderate changes in socially maladjusted behaviors over time.</p> <hd id="AN0182120033-17">Overall Decrease in Socially Maladjusted Behaviors</hd> <p>The overall trend in socially maladjusted behaviors among students over the 22-year time frame of this study is consistent in direction and magnitude with findings from prior research indicating that child and adolescent problem behaviors have declined in recent decades (for review, see [<reflink idref="bib8" id="ref82">8</reflink>]). Furthermore, the magnitude of decreases in socially maladjusted behaviors for adolescents (i.e., middle school and high school students) were consistent with findings from [<reflink idref="bib9" id="ref83">9</reflink>] who reported a decline from 1999 to 2017 in high school students' propensity to engage in problem behaviors, such as substance use and delinquency, that are consistent with our definition of socially maladjusted behaviors (see also [<reflink idref="bib22" id="ref84">22</reflink>]).</p> <p>There are several plausible explanations for the overall decline observed in this study and reported in prior research. Importantly, the rigor of this study, which collected data using the SAED in matched cohorts, rules out certain methodological explanations, such as limitations related to instrumentation (e.g., variation in the sensitivity of different measures or a lack of measurement invariance across time). It is possible that environmental changes over the past several decades have facilitated a decrease in socially maladjusted behaviors ([<reflink idref="bib6" id="ref85">6</reflink>]). For example, public policies have reduced children's exposure to known determinants of the development of social maladjustment, such as lead ([<reflink idref="bib5" id="ref86">5</reflink>]). Moreover, the proliferation in recent years of evidence-based school-focused interventions (https://ies.ed.gov/ncee/wwc/), such as Multitiered Systems of Support (MTSS; [<reflink idref="bib40" id="ref87">40</reflink>]) and Positive Behavioral Interventions and Supports (PBIS; [<reflink idref="bib20" id="ref88">20</reflink>]), may have bolstered key protective influences (e.g., effective classroom management practices) that reduce the likelihood of problem behaviors. Causal inferences are beyond the scope of this study and require further research; however, a clear implication concerns the need for routine surveillance, using measures such as the SAED, to monitor the ongoing trend in socially maladjusted behaviors among students.</p> <hd id="AN0182120033-18">Declining Socially Maladjusted Behaviors of Students with ED</hd> <p>Most prior research has examined students from the general population without consideration of disability status (e.g., [<reflink idref="bib8" id="ref89">8</reflink>]; [<reflink idref="bib9" id="ref90">9</reflink>]). A major strength of the current study was the inclusion of both students with school-identified ED and those without educational disabilities, and results from a two-way interaction test indicated that the cohort difference in socially maladjusted behaviors, reflecting a decrease over time, was significantly more pronounced for students with school-identified ED. This finding is encouraging, because it appears that vulnerable students with the greatest needs experienced the most improvement. The decrease in socially maladjusted behaviors among these students may reflect the effectiveness of evidence-based interventions, including school-based MTSS and PBIS that implement increasingly tailored and intensified practices with students as their needs increase. Alternative explanations must also be acknowledged, such as the possibility of changing perspectives on students with ED that might focus less attention over the last two decades on identifying their disruptive behaviors and more on characterizing their strengths, while seeking ways to promote positive youth development ([<reflink idref="bib26" id="ref91">26</reflink>]).</p> <p>Another possible explanation is related to changes in the population of students with ED, rather than the effectiveness of intervention or changes in teacher perspectives. Interestingly, the number of students served under the ED label also decreased during the last two decades. In 1998, 463,172 students with ED representing 0.74% of the school age population received services ([<reflink idref="bib49" id="ref92">49</reflink>]), whereas in 2020, 344,473 students representing 0.5% of the student population received services for ED ([<reflink idref="bib50" id="ref93">50</reflink>]). Perhaps the decline in the rate of students identified with ED has been accompanied by changes in the types of students identified as ED. It may be that schools have generally become less likely to identify those students who show a high level of socially maladjusted behaviors so that schools have more flexibility in suspending and expelling students who display disruptive antisocial behaviors (e.g., [<reflink idref="bib11" id="ref94">11</reflink>]; [<reflink idref="bib36" id="ref95">36</reflink>]). Such a change in the identification process might produce results similar to those of the present study. Further research and policy analysis is needed to identify other potential causes of declining socially maladjusted behaviors among students with ED.</p> <hd id="AN0182120033-19">Additional Moderators of the Trend in Socially Maladjusted Behaviors</hd> <p>Further moderation tests revealed increasingly nuanced patterns of cohort differences in social maladjustment, elucidating important subgroup differences in the overall trend. Decreases were more pronounced for middle school and high school students than for elementary school students. This trend may reflect the fact that certain socially maladjusted behaviors, such as substance use and delinquency, typically onset and progress during adolescence, and secular trends in many adolescent problem behaviors (e.g., substance use; [<reflink idref="bib9" id="ref96">9</reflink>]) have demonstrated steady declines over the past two decades. A statistically significant three-way interaction suggested that the decline in socially maladjusted behaviors over the time frame of this study was particularly evident for students with ED (compared with their peers without ED) in middle school. It may be difficult to contextually interpret this specific pattern, although it is noteworthy that the middle school years represent a critical period of development and an important window of opportunity for intervention during the transition to adolescence ([<reflink idref="bib39" id="ref97">39</reflink>]). Empirically, the data suggest that middle school students without disabilities engaged in very low levels of socially maladjusted behavior—levels similar to peers in elementary school—while middle school students with ED engaged in socially maladjusted behaviors similar to high school peers with ED. It may be that the onset of problem behaviors, such as drug use or delinquency, occurs earlier and more prevalently for middle school students with ED leading to trends that were more similar to high school students rather than same age peers without disabilities.</p> <p>Interestingly, neither gender nor race/ethnicity played a moderating role in the trends. [<reflink idref="bib47" id="ref98">47</reflink>] reported decreases from 1993 to 2003 in externalizing behaviors for boys, but not girls in cohorts of Dutch adolescents; however, additional studies of secular trends in such behaviors have documented similar patterns of change across gender groups, despite consistent evidence of higher overall levels of conduct problems in males than females (e.g., [<reflink idref="bib15" id="ref99">15</reflink>]; [<reflink idref="bib38" id="ref100">38</reflink>]). Other studies such as Duinhof and colleagues (2015) found similar patterns of change in conduct problems over a 10-year time frame in Dutch non-minoritized adolescents compared with their minoritized peers; however, there are few studies of racial/ethnic differences in secular trends over time making it difficult to contextualize the current findings.</p> <hd id="AN0182120033-20">School Factors</hd> <p>Returning to the schools and students with ED, special education programming may be a factor for some of the decreases in socially maladjusted behaviors. Although social maladjustment is excluded from the federal IDEA definition of ED, nonetheless most children being served under the ED category display socially maladjusted behaviors (e.g., [<reflink idref="bib16" id="ref101">16</reflink>]; [<reflink idref="bib35" id="ref102">35</reflink>]). Furthermore, most students who receive services under the ED category are usually identified in elementary school rather than middle or high school (e.g., [<reflink idref="bib27" id="ref103">27</reflink>]). Consequently, special education services may have an impact on reducing socially maladjusted behaviors.</p> <p>Although the prevalence of socially maladjusted behaviors has decreased over the past two decades for students in general, significant numbers of students with and without ED in middle and high schools engage in these problematic behaviors to the degree that their educational achievement is limited and may contribute to school dropout. For this reason, teachers and school administrators need to implement strategies directed at retaining students with and without ED who demonstrate significant socially maladjusted behaviors. School-based strategies with moderate to strong evidence for maintaining such students in school include (a) providing intensive, individualized support for students who have fallen off track; (b) engaging students by offering programs that link schoolwork and to career success, and (c) creating small, personalized learning communities to facilitate monitoring and support ([<reflink idref="bib42" id="ref104">42</reflink>]). These three strategies are congruent with the increasingly popular multi-tiered systems of support (MTSS) that schools are adopting.</p> <p>Multi-tiered systems of support approaches provide universal supports that address students' behavior and learning regardless of the presence or absence of a disability. In terms of behavior, it may be that young children exposed to tier 1 and tier 2 levels of PBIS may have a kind of "titration" effect in that it may take many years within this type of system before meaningful behavior change will occur. The use of response to intervention for academics has been posited to be one of the reasons the number of students identified as learning disabled has decreased within the last 20 years ([<reflink idref="bib48" id="ref105">48</reflink>]).</p> <p>Could MTSS be responsible for decreases in socially maladjusted behaviors for students with ED? These systems have existed in schools for the past 10 to 15 years. [<reflink idref="bib25" id="ref106">25</reflink>] found that implementation fidelity for PBIS has improved in the past 10 years and may be partially responsible for lower levels of out-of-school suspensions. The "titration" hypothesis put forth previously, however, is likely insufficient to explain the reductions in socially maladjusted behaviors. One reason is because socially maladjusted behaviors and activities occur both in and outside of the school, and therefore, other social-cultural variables likely contribute to the decreases observed in this study (e.g., [<reflink idref="bib7" id="ref107">7</reflink>]).</p> <hd id="AN0182120033-21">Limitations</hd> <p>Although this study represents one of the largest school-based cross-sectional cohort studies to examine long-term changes in socially maladjusted behaviors, it is not without limitations. First, the outcome for this study was ratings on a teacher-reported scale. While the ratings from the SAED have demonstrated strong psychometric properties across a large series of studies, it is possible that the outcomes of this study would have been different if a different rating scale was used or if an alternative data collection method was used. In future replications of this study, the socially maladjusted behaviors of students with and without ED should be measured via methods other than teacher rating scales. Moreover, similar data should be collected from parents and youth self-reports.</p> <p>Second, because data were collected as part of large-scale norming studies, relatively few demographic data were collected on students. One significant omission from the norming studies, and thus this study, was the collection of socioeconomic status (SES) or a proxy variable such as free and reduced lunch. Socioeconomic status is closely associated with ED and juvenile delinquency, so this factor may have been important to include in the analytic models to account for differences between students with ED and peers without disabilities. The omission of SES from the analytic model may have inflated the differences in changes over time between the two groups of students. This suggests that future investigations should collect SES data and evaluate whether trends in socially maladjusted behaviors are associated with SES.</p> <p>Third, only limited demographic data on teachers were collected as part of the SAED norming studies, so it is unknown what proportion of teachers were general educators and special educators, level of education (e.g., bachelor versus master's degree), years of teaching experience, and how the responding teachers differed for students with ED and peers without disabilities. Perhaps the most significant limitation with respect to teacher demographic data is the lack of information on teacher race and ethnicity as major questions have been raised about disproportional representation of racially minoritized students receiving services for ED (see [<reflink idref="bib45" id="ref108">45</reflink>]; [<reflink idref="bib54" id="ref109">54</reflink>]). Specifically, teacher bias has been found to be related to disciplinary actions and referral to special education (see [<reflink idref="bib14" id="ref110">14</reflink>]; [<reflink idref="bib44" id="ref111">44</reflink>]; [<reflink idref="bib54" id="ref112">54</reflink>]). Moreover, [<reflink idref="bib17" id="ref113">17</reflink>] have reported that White teachers are more likely to rate racially minoritized students as demonstrating higher rates of impulsive and inattentive behaviors than non-minoritized peers. For this reason, future researchers need to collect complete demographic data on the teachers and other school professionals providing the ratings and to assess the relationship between teacher demographic variables and student race/ethnicity on the ratings of students.</p> <p>Another limitation is that the data collected during the norming process in 1998 and 2020 did not include a process to take into account the nested structure of the ratings (i.e., multiple students rated by the same teacher). Raters were instructed to complete forms on all of their students or an unbiased subset of students as they were able to rate. This led to some teachers rating all their students, whereas other teachers rating a small subset of students. Relatedly, it was not possible to link teachers with students, so this inherent nested structure of the dataset (i.e., students nested within teachers) could not be accounted for in the analytic models. This unavoidable omission likely caused downwardly biased standard errors (and thus an inflated Type I error rate) because the non-independence of observations was violated to some extent. In order to address this limitation, future researchers need to be able to link teachers to students.</p> <p>Finally, because of the relatively low rates and severity of socially maladjusted behaviors, the distribution of scores (and model residuals) in the samples were non-normal and the variances between some groups in the analysis (e.g., elementary, middle, high school students) were unequal, which violate two assumptions underlying the analytic framework of this study. In light of the violations, readers should cautiously interpret the reported <emph>p</emph>-values; however, we used a conservative significance level to help guard against Type I errors caused by violations of the underlying assumptions and multiple comparisons.</p> <hd id="AN0182120033-22">Conclusion</hd> <p>Despite the limitations noted above, this study represents one of the most comprehensive evaluations of long-term trends of socially maladjusted behaviors, and the only evaluation of such trends for students identified with ED. While several other studies have documented decreasing trends of similar behaviors over extended periods of time, this study is the only school-based evaluation of these trends. The effects documented in this study were consistent with the extant literature, which underlines the robustness of the finding that socially maladjusted behaviors are decreasing. This observation appears to be independent of the informant providing the data (e.g., students, parents, teachers), the setting in which the data were collected (e.g., community and school), and the disability status of children. While this study does not provide a causal explanation for the decreasing trends, it highlights the need to continually monitor trends and begin to evaluate malleable factors that may contribute to long-term trends, which would have significant educational and social importance.</p> <ref id="AN0182120033-23"> <title> References </title> <blist> <bibl id="bib1" idref="ref7" type="bt">1</bibl> <bibtext> Achenbach T. M., Dumenci L., Rescorla L. A. (2002). Ten-year comparisons of problems and competencies for National samples of youth: Self, parent, and teacher reports. Journal of Emotional and Behavioral Disorders, 10(4), 194–203. https://doi.org/10.1177/10634266020100040101</bibtext> </blist> <blist> <bibl id="bib2" idref="ref8" type="bt">2</bibl> <bibtext> Achenbach T. M., Dumenci L., Rescorla L. A. (2003). Are American children's problems still getting worse? A 23-year comparison. Journal of Abnormal Child Psychology, 31(1), 1–11. https://doi.org/10.1023/A:1021700430364</bibtext> </blist> <blist> <bibl id="bib3" idref="ref6" type="bt">3</bibl> <bibtext> Achenbach T. M., Rescorla L. A. (2001). Manual for the ASEBA school-age forms & profiles: An integrated system of mult-informant assessment. University of Vermont.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref40" type="bt">4</bibl> <bibtext> Aguinis H., Beaty J. C., Boik R. J., Pierce C. A. (2005). Effect size and power in assessing moderating effects of categorical variables using multiple regression: A 30-year review. Journal of Applied Psychology, 90(1), 94–107. https://doi.org/10.1037/0021-9010.90.1.94</bibtext> </blist> <blist> <bibl id="bib5" idref="ref41" type="bt">5</bibl> <bibtext> Aizer A., Currie J. (2019). Lead and juvenile delinquency: New evidence from linked birth, school, and juvenile detention records. The Review of Economics and Statistics, 101(4), 575–587. https://doi.org/10.1162/rest_a_00814</bibtext> </blist> <blist> <bibl id="bib6" idref="ref42" type="bt">6</bibl> <bibtext> Arnett J. J. (2018). Getting better all the time: Trends in risk behavior among American adolescents since 1990. Archives of Scientific Psychology, 6(1), 87–95. <ulink href="http://dx.doi.org/10.1037/arc0000046">http://dx.doi.org/10.1037/arc0000046</ulink></bibtext> </blist> <blist> <bibl id="bib7" idref="ref107" type="bt">7</bibl> <bibtext> Barnert E. S., Perry R., Shetgiri R., Steers N., Dudovitz R., Heard-Garris N. J., Zima B., Chung P. J. (2021). Adolescent protective and risk factors for incarceration through early adulthood. Journal of Child and Family Studies, 30(6), 1428–1440. https://doi.org/10.1007/s10826-021-01954-y</bibtext> </blist> <blist> <bibl id="bib8" idref="ref5" type="bt">8</bibl> <bibtext> Bor W., Dean A. J., Najman J., Hayatbakhsh R. (2014). Are child and adolescent mental health problems increasing in the 21st century? A systematic review. The Australian and New Zealand Journal of Psychiatry, 48(7), 606–616. <ulink href="http://dx.doi.org/10.1177/0004867414533834">http://dx.doi.org/10.1177/0004867414533834</ulink></bibtext> </blist> <blist> <bibl id="bib9" idref="ref13" type="bt">9</bibl> <bibtext> Borodovsky J. T., Krueger R. F., Agrawal A., Grucza R. A. (2019). A decline in propensity toward risk behaviors among U.S. adolescents. Journal of Adolescent Health, 65(6), 745–751. https://doi.org/10.1016/j.jadohealth.2019.07.001</bibtext> </blist> <blist> <bibtext> Centers for Disease Control and Prevention. (2020). Data and statistics on children's mental health. https://<ulink href="http://www.cdc.gov/childrensmentalhealth/data.html">www.cdc.gov/childrensmentalhealth/data.html</ulink></bibtext> </blist> <blist> <bibtext> Chan P. E., Katsiyannis A., Yell M. L., Zimmerman J. (2021). Handcuffed in school: Legal and practice considerations. Advances in Neurodevelopmental Disorders, 5(3), 339–350. https://doi.org/10.1007/s41252-021-00213-x</bibtext> </blist> <blist> <bibtext> Chen H., Cohen P., Chen S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics—Simulation and Computation, 39, 860–864. https://doi.org/10.1080/03610911003650383</bibtext> </blist> <blist> <bibtext> Cohen J. (1988). Statistical power and analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.</bibtext> </blist> <blist> <bibtext> Devine P. G., Forscher P. S., Austin A. G., Cox W. T. (2012). Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 48(6), 1267–1278. https://doi.org/10.1016/j.jesp.2012.06.003</bibtext> </blist> <blist> <bibtext> Duinhof E. L., Stevens G. W. J. M., van Dorsselaer S., Monshouwer K., Vollebergh W. A. M. (2015). Ten-year trends in adolescents' self-reported emotional and behavioral problems in the Netherlands. European Child and Adolescent Psychiatry, 24, 1119–1128. https://doi.org/10.1007/s00787-014-0664-2</bibtext> </blist> <blist> <bibtext> Duncan B. B., Forness S. R., Hartsough C. (1995). Students identified as seriously emotionally disturbed in school-based day treatment: Cognitive, psychiatric, and special education characteristics. Behavioral Disorders, 20(4), 238–252. https://doi.org/10.1177/019874299502000403</bibtext> </blist> <blist> <bibtext> DuPaul G. J., Reid R., Anastopoulos A. D., Lambert M. C., Watkins M. W., Power T. J. (2016). Parent and teacher ratings of attention-deficit/hyperactivity disorder symptoms: Factor structure and normative data. Psychological Assessment, 28(2), 214–225. https://doi.org/10.1037/pas0000166</bibtext> </blist> <blist> <bibtext> Epstein M. H., Cullinan D. (1998). Scale for assessing emotional disturbance. PRO-ED.</bibtext> </blist> <blist> <bibtext> Epstein M. H., Cullinan D., Pierce C. D., Huscroft-D'Angelo J., Wery J. J. (2020). Scales for assessing emotional disturbance (3rd ed.). PRO-ED.</bibtext> </blist> <blist> <bibtext> George H. P. (2018). Introduction to the special issue of behavioral disorders: Positive behavior interventions and supports. Behavioral Disorders, 43(3), 340–343. https://doi.org/10.1177/0198742918763951</bibtext> </blist> <blist> <bibtext> Goodman A., Goodman R. (2009). Strengths and difficulties questionnaire as a dimensional measure of child mental health. Journal of the American Academy of Child and Adolescent Psychiatry, 48(4), 400–403. https://doi.org/10.1097/CHI.0b013e3181985068</bibtext> </blist> <blist> <bibtext> Grucza R. A., Krueger R. F., Agrawai A., Plunk A. D., Krauss M. J., Bongu J., Cavazos-Rehg P. A., Bierut L. J. (2018). Declines in prevalence of adolescent substance use disorders and delinquent behaviors in the United States: A unitary trend? Psychol Med, 48(9), 1494–1503. https://doi.org/10.1017/S0033291717002999</bibtext> </blist> <blist> <bibtext> Hartung C. M., Lefler E. K. (2019). Sex and gender in psychopathology: DSM–5 and beyond. Psychological Bulletin, 145(4), 390–409. https://doi.org/10.1037/bul0000183</bibtext> </blist> <blist> <bibtext> Individuals with Disabilities Education Improvement Act of 2004, Pub. L. No. 108-446, 20 U.S.C. §1400et seq. (2004).</bibtext> </blist> <blist> <bibtext> James A. G., Noltemeyer A., Ritchie R., Palmer K. (2019). Longitudinal disciplinary and achievement outcomes associated with school-wide PBIS implementation level. Psychology in the Schools, 56(9), 1512–1521. https://doi.org/10.1002/pits.22282</bibtext> </blist> <blist> <bibtext> Jimerson S. R., Sharkey J. D., Nyborg V., Furlong M. J. (2004). Strength-based assessment and school psychology: A summary and synthesis. The California School Psychologist, 9, 9–19. https://doi.org/10.1007/BF03340903</bibtext> </blist> <blist> <bibtext> Kauffman J. M., Landrum T. J. (2009). Characteristics of emotional and behavioral disorders of children and youth (9th ed.). Pearson.</bibtext> </blist> <blist> <bibtext> Kauffman J. M., Landrum T. J. (2018). Characteristics of emotional and behavioral disorders of children and youth (11th ed.). Pearson.</bibtext> </blist> <blist> <bibtext> Kaufman P., Chen X., Choy S. P., Ruddy S. A., Miller A. K., Fleury J. K., Chandler K. A., Rand M. R., Klaus P., Planty M. G. (2000). Indicators of school crime and safety, 2000. U.S. Departments of Education and Justice. NCES 2001–017/NCJ-184176</bibtext> </blist> <blist> <bibtext> Lambert M. C., Cullinan D., Epstein M. H., Martin J. (2022a). Differences between students with emotional disturbance, learning disabilities, and without disabilities on the five dimensions of emotional disturbance. Journal of Applied School Psychology, 38(1), 58–73. https://doi.org/10.1080/15377903.2021.1895399</bibtext> </blist> <blist> <bibtext> Lambert M. C., Cullinan D., Epstein M. H., Martin J. (2022b). Factor structure of the Scales for Assessing Emotional Disturbance–3 Rating Scale for students identified with emotional disturbance. Behavioral Disorders, 47(3), 187–195. https://doi.org/10.1177/01987429211012328</bibtext> </blist> <blist> <bibtext> Lambert M. C., Katsiyannis A., Epstein M. H., Cullinan D. (2022). An initial study of the emotional and behavioral characteristics of Black students school identified as emotionally disturbed. Behavioral Disorders, 47(2), 108–117. https://doi.org/10.1177/01987429211038022</bibtext> </blist> <blist> <bibtext> Lambert M. C., Martin J., Epstein M. H., Cullinan D. (2021). Differential item functioning of the Scales for Assessing Emotional Disturbance–3 for White and Hispanic students. Journal of Emotional and Behavioral Disorders, 29(4), 252–260. https://doi.org/10.1177/1063426620988658</bibtext> </blist> <blist> <bibtext> Lambert M. C., Martin J., Epstein M. H., Cullinan D., Katsiyannis A. (2021). Differential item functioning of the Scales for Assessing Emotional Disturbance–3 Rating Scale for White and African American students. Psychology in the Schools, 58(3), 553–568. https://doi.org/10.1002/pits.22463</bibtext> </blist> <blist> <bibtext> Liu J. (2004). Childhood externalizing behavior: Theory and implications. Journal of Child and Adolescent Psychiatric Nursing, 17(3), 93–103. https://doi.org/10.1111/j.1744-6171.2004.tb00003.x</bibtext> </blist> <blist> <bibtext> Losinski M., Katsiyannis A., Ryan J., Baughan C. (2014). Weapons in schools and zero-tolerance policies. NASSP Bulletin, 98(2), 126–141. https://doi.org/10.1177/0192636514528747</bibtext> </blist> <blist> <bibtext> Mason W. A., Lambert M. C., Epstein M. H. (2023). Differences in emotional and behavioral problems of students over time: A 22-year cross-sectional cohort study. Research on Child and Adolescent Psychopathology, 51, 557–569. https://doi.org/10.1007/s10802-022-01014-z</bibtext> </blist> <blist> <bibtext> Maughan B., Iervolino A. C., Collishaw S. (2005). Time trends in child and adolescent mental disorders. Current Opinion in Psychiatry, 18, 381–385. https://doi.org/10.1097/01.yco.0000172055.25284.f2</bibtext> </blist> <blist> <bibtext> National Academies of Sciences, Engineering, and Medicine. (2019). The promise of adolescence: Realizing opportunity for all youth. The National Academies Press. https://doi.org/10.17226/25388</bibtext> </blist> <blist> <bibtext> National Association of School Psychologists. (2016). Integrated model of academic and behavioral supports [Position statement].</bibtext> </blist> <blist> <bibtext> Puzzanchera C. (2020, June). Juvenile arrests, 2018. Juvenile Justice Statistics: National Report Series Bulletin. U.S. Department of Justice; Office of Justice Programs. https://ojjdp.ojp.gov/sites/g/files/xyckuh176/files/media/document/254499.pdf</bibtext> </blist> <blist> <bibtext> Rumberger R., Addis H., Allensworth E., Balfanz R., Bruch J., Dillon E., Duardo D., Dynarski M., Furgeson J., Jayanthi M., Newman-Gonchar R., Place K., Tuttle C. (2017). Preventing drop-out in secondary schools (NCEE 2017-4028). National Center for Education Evaluation and Regional Assistance; Institute of Education Sciences; U.S. Department of Education. <ulink href="http://ies.ed.gov/ncee/wwc/practiceguides">http://ies.ed.gov/ncee/wwc/practiceguides</ulink></bibtext> </blist> <blist> <bibtext> Salk R. H., Hyde J. S., Abramson L. Y. (2017). Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychology Bulletin, 143(8), 783–822. https://doi.org/10.1037/bul0000102</bibtext> </blist> <blist> <bibtext> Skiba R. J., Horner R. H., Chung C.-G., Rausch M. K., May S. L., Tobin T. (2011). Race is not neutral: A national investigation of Black and Latino disproportionality in school discipline. School Psychology Review, 40(1), 85–107. https://doi.org/10.1080/02796015.2011.12087730</bibtext> </blist> <blist> <bibtext> Skiba R. J., Simmons A. B., Ritter S., Gibb A. C., Rausch M. K., Cuadrado J., Chung C.-G. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74(3), 264–288. https://doi.org/10.1177/001440290807400301</bibtext> </blist> <blist> <bibtext> Snyder H. N. (2000, December). Juvenile arrests 1999. Juvenile Justice and Delinquency Prevention: Juvenile Justice Bulletin. U.S. Department of Justice; Office of Justice Programs. https://<ulink href="http://www.ojp.gov/pdffiles1/ojjdp/185236.pdf">www.ojp.gov/pdffiles1/ojjdp/185236.pdf</ulink></bibtext> </blist> <blist> <bibtext> Tick N., van der Ende J., Verhulst F. (2008). Ten-year trends in self-reported emotional and behavioral problems of Dutch adolescents. Social Psychiatry and Psychiatric Epidemiology, 43, 349–355. https://doi.org/10.1007/s00127-008-0315-3</bibtext> </blist> <blist> <bibtext> U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics. (2021). Table 204.30: Children 3 to 21 years old served under Individuals with Disabilities Education Act (IDEA), Part B, by type of disability: Selected years, 1976-77 through 2019-20. https://nces.ed.gov/programs/digest/d20/tables/dt20_204.30.asp</bibtext> </blist> <blist> <bibtext> U.S. Department of Education, Office of Special Education and Rehabilitative Services, Office of Special Education Programs. (2000). 22nd annual report to congress on the implementation of the individuals with Disabilities Education Act, 1999.</bibtext> </blist> <blist> <bibtext> U.S. Department of Education, Office of Special Education and Rehabilitative Services, Office of Special Education Programs. (2021). 42nd annual report to congress on the implementation of the individuals with Disabilities Education Act, 2020. https://sites.ed.gov/idea/files/42nd-arc-for-idea.pdf</bibtext> </blist> <blist> <bibtext> Verhulst F. C., van der Ende J., Rietbergen A. (1997). Ten-year time trends of psychopathology in Dutch children and adolescents: No evidence for strong trends. Acta Psychiatry Scandinavian, 96, 7–13. https://doi.org/10.1111/j.1600-0447.1997.tb09898.x</bibtext> </blist> <blist> <bibtext> Walker H. M., Nishioka V. M., Zeller R., Severson H. H., Feil E. G. (2000). Causal factors and potential solutions for the persistent underidentification of students having emotional or behavioral disorders in the context of schooling. Assessment for Effective Intervention, 26(1), 29–40. https://doi.org/10.1177/073724770002600105</bibtext> </blist> <blist> <bibtext> Wang K., Chen Y., Zhang J., Oudekerk B. A. (2020). Indicators of school crime and safety: 2019 (NCES 2020-063/NCJ 254485). National Center for Education Statistics; U.S. Department of Education, and Bureau of Justice Statistics; Office of Justice Programs; U.S. Department of Justice. https://nces.ed.gov/pubs2020/2020063.pdf</bibtext> </blist> <blist> <bibtext> Whitford D. K., Katsiyannis A., Counts J. (2016). Discriminatory discipline: Trends and issues. NASSP Bulletin, 100(2), 117–135. https://doi.org/10.1177/0192636516677340</bibtext> </blist> </ref> <ref id="AN0182120033-24"> <title> Footnotes </title> <blist> <bibtext> It may be important to note that the last author is one of the developers of the SAED, which was used in this research study. He receives royalties from sales of the assessment. None of the other co-authors have any direct or indirect competing interests related to this study.</bibtext> </blist> <blist> <bibtext> The author(s) received no financial support for the research, authorship, and/or publication of this article.</bibtext> </blist> <blist> <bibtext> The data used in this study are not currently available for open access.</bibtext> </blist> <blist> <bibtext> Matthew C. Lambert</bibtext> </blist> <blist> <bibtext>Graph https://orcid.org/0000-0002-7387-3780</bibtext> </blist> </ref> <aug> <p>By Matthew C. Lambert; Antonis Katsiyannis; John W. Maag; W. Alex Mason and Michael H. Epstein</p> <p>Reported by Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib28" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib24" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib53" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib52" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib51" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib22" firstref="ref12"></nolink> <nolink nlid="nl7" bibid="bib29" firstref="ref14"></nolink> <nolink nlid="nl8" bibid="bib46" firstref="ref16"></nolink> <nolink nlid="nl9" bibid="bib41" firstref="ref17"></nolink> <nolink nlid="nl10" bibid="bib19" firstref="ref19"></nolink> <nolink nlid="nl11" bibid="bib37" firstref="ref21"></nolink> <nolink nlid="nl12" bibid="bib48" firstref="ref22"></nolink> <nolink nlid="nl13" bibid="bib23" firstref="ref23"></nolink> <nolink nlid="nl14" bibid="bib43" firstref="ref24"></nolink> <nolink nlid="nl15" bibid="bib10" firstref="ref25"></nolink> <nolink nlid="nl16" bibid="bib18" firstref="ref33"></nolink> <nolink nlid="nl17" bibid="bib30" firstref="ref45"></nolink> <nolink nlid="nl18" bibid="bib32" firstref="ref46"></nolink> <nolink nlid="nl19" bibid="bib31" firstref="ref47"></nolink> <nolink nlid="nl20" bibid="bib33" firstref="ref48"></nolink> <nolink nlid="nl21" bibid="bib13" firstref="ref52"></nolink> <nolink nlid="nl22" bibid="bib21" firstref="ref56"></nolink> <nolink nlid="nl23" bibid="bib12" firstref="ref63"></nolink> <nolink nlid="nl24" bibid="bib40" firstref="ref87"></nolink> <nolink nlid="nl25" bibid="bib20" firstref="ref88"></nolink> <nolink nlid="nl26" bibid="bib26" firstref="ref91"></nolink> <nolink nlid="nl27" bibid="bib49" firstref="ref92"></nolink> <nolink nlid="nl28" bibid="bib50" firstref="ref93"></nolink> <nolink nlid="nl29" bibid="bib11" firstref="ref94"></nolink> <nolink nlid="nl30" bibid="bib36" firstref="ref95"></nolink> <nolink nlid="nl31" bibid="bib39" firstref="ref97"></nolink> <nolink nlid="nl32" bibid="bib47" firstref="ref98"></nolink> <nolink nlid="nl33" bibid="bib15" firstref="ref99"></nolink> <nolink nlid="nl34" bibid="bib38" firstref="ref100"></nolink> <nolink nlid="nl35" bibid="bib16" firstref="ref101"></nolink> <nolink nlid="nl36" bibid="bib35" firstref="ref102"></nolink> <nolink nlid="nl37" bibid="bib27" firstref="ref103"></nolink> <nolink nlid="nl38" bibid="bib42" firstref="ref104"></nolink> <nolink nlid="nl39" bibid="bib25" firstref="ref106"></nolink> <nolink nlid="nl40" bibid="bib45" firstref="ref108"></nolink> <nolink nlid="nl41" bibid="bib54" firstref="ref109"></nolink> <nolink nlid="nl42" bibid="bib14" firstref="ref110"></nolink> <nolink nlid="nl43" bibid="bib44" firstref="ref111"></nolink> <nolink nlid="nl44" bibid="bib17" firstref="ref113"></nolink>
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  Label: Abstract
  Group: Ab
  Data: Although the construct of social maladjustment has been used for the last six decades, relatively little research has addressed secular trends in socially maladjusted behaviors over time, and even fewer studies have addressed trends for students identified with emotional disturbance (ED). The purpose of this study was to use two U.S. nationally representative cross-sectional cohorts, one sampled in 1998 (n = 1,509) and one sampled in 2020 (n = 1,513), to examine long-term trends in the socially maladjusted behaviors of students with ED and their peers without disabilities. Results indicated that (a) socially maladjusted behaviors were significantly lower for the 2020 cohort compared with 1998 cohort, (b) the decrease from 1998 to 2020 was significantly more pronounced for students with ED compared with peers without disabilities, and (c) only adolescent students demonstrated significant decreases in socially maladjusted behaviors. Potential explanations, limitations of the study, and implications for schools are discussed.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1456572
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1456572
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/01987429241269464
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 63
    Subjects:
      – SubjectFull: Elementary School Students
        Type: general
      – SubjectFull: Secondary School Students
        Type: general
      – SubjectFull: Antisocial Behavior
        Type: general
      – SubjectFull: Emotional Disturbances
        Type: general
      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Trend Analysis
        Type: general
    Titles:
      – TitleFull: Long-Term Trends in Socially Maladjusted Behavior of Students with and without Emotional and Behavioral Disorders: A 22-Year Repeated Cross-Sectional Study
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Matthew C. Lambert
      – PersonEntity:
          Name:
            NameFull: Antonis Katsiyannis
      – PersonEntity:
          Name:
            NameFull: John W. Maag
      – PersonEntity:
          Name:
            NameFull: W. Alex Mason
      – PersonEntity:
          Name:
            NameFull: Michael H. Epstein
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0198-7429
            – Type: issn-electronic
              Value: 2163-5307
          Numbering:
            – Type: volume
              Value: 50
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Behavioral Disorders
              Type: main
ResultId 1