A 2004 study conducted by the U.S. Department of Education on the prevalence of sexual abuse in schools estimated that nearly 10 percent (4.5 million) of K–12 students in the United States reported being the victims of sexual abuse by a teacher (Shakeshaft, 2004).Although several subsequent studies have examined the phenomenon, no comprehensive study enumerating the prevalence of teacher-perpetrated sexual misconduct has been commissioned more recently by the department. However, whether the recent headlines are the result of heightened awareness, prevalence,or both, there is evidence that suggests the issue remains. A 2007 AP Wire Services report draws the obvious parallel between the occurrence of teacher-perpetrated child sexual abuse (CSA) and the clergy scandal that has rocked the Catholic Church (Irvine & Tanner, 2007). Their seven-month investigation covering the years 2001 to 2005 found 2,750 educators in the United States whose teaching credentials were surrendered, sanctioned, or revoked following charges of sexual misconduct. Young people were the victims in 1,801 of the cases, and 80 percent of those were students. A 2016 USA Today investigation compiled disciplinary records of certified teachers among all 50 states, using the open records laws (Reilly, 2016). The report found that states failed to report the names of at least 200 teachers whose license revocations were prompted by allegations of physical abuse or CSA to a centralized national database operated by the nonprofit National Association of State Directors of Teacher Education and Certification. The omissions allowed the teachers to obtain classroom jobs in other states.A 2017 study by the U.S. Department of Justice found 39 states out of compliance with 2015 federal legislation banning the practice known as “passing the trash”— school districts helping accused predators find other jobs to make them the new districts’ problem (Olson, 2019).
{"title":"Social Workers Have a Role in Curbing Sexual Grooming in Schools","authors":"D. Pollack, R. Reiser","doi":"10.1093/cs/cdaa004","DOIUrl":"https://doi.org/10.1093/cs/cdaa004","url":null,"abstract":"A 2004 study conducted by the U.S. Department of Education on the prevalence of sexual abuse in schools estimated that nearly 10 percent (4.5 million) of K–12 students in the United States reported being the victims of sexual abuse by a teacher (Shakeshaft, 2004).Although several subsequent studies have examined the phenomenon, no comprehensive study enumerating the prevalence of teacher-perpetrated sexual misconduct has been commissioned more recently by the department. However, whether the recent headlines are the result of heightened awareness, prevalence,or both, there is evidence that suggests the issue remains. A 2007 AP Wire Services report draws the obvious parallel between the occurrence of teacher-perpetrated child sexual abuse (CSA) and the clergy scandal that has rocked the Catholic Church (Irvine & Tanner, 2007). Their seven-month investigation covering the years 2001 to 2005 found 2,750 educators in the United States whose teaching credentials were surrendered, sanctioned, or revoked following charges of sexual misconduct. Young people were the victims in 1,801 of the cases, and 80 percent of those were students. A 2016 USA Today investigation compiled disciplinary records of certified teachers among all 50 states, using the open records laws (Reilly, 2016). The report found that states failed to report the names of at least 200 teachers whose license revocations were prompted by allegations of physical abuse or CSA to a centralized national database operated by the nonprofit National Association of State Directors of Teacher Education and Certification. The omissions allowed the teachers to obtain classroom jobs in other states.A 2017 study by the U.S. Department of Justice found 39 states out of compliance with 2015 federal legislation banning the practice known as “passing the trash”— school districts helping accused predators find other jobs to make them the new districts’ problem (Olson, 2019).","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"139-142"},"PeriodicalIF":2.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdaa004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41589588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sharon Young, Lori Connolly Sollose, Jennifer P Carey
{"title":"Addressing Chronic Absenteeism in Middle School: A Cost-Effective Approach","authors":"Sharon Young, Lori Connolly Sollose, Jennifer P Carey","doi":"10.1093/cs/cdaa009","DOIUrl":"https://doi.org/10.1093/cs/cdaa009","url":null,"abstract":"","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"131-138"},"PeriodicalIF":2.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdaa009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46261773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a growing need for valid measures that can be administered efficiently in school settings to assess the impact of school-based preventive interventions. The current article aimed to establish a balance among assessment efficiency, reliability, and the measurement properties of an instrument widely used to assess the impact of school-based programs, called the Teacher Observation of Classroom Adaptation-Checklist (TOCA-C). We leveraged item response theory (IRT) analyses to create a shortened, more focused checklist version of the TOCA-C that is both valid and efficient for large-scale use in schools to track students’ behavioral, social–emotional, and family factors over the course of elementary school. The sample included 17,456 children in kindergarten through grade 5 (47.7 percent female, 54.2 percent African American). IRT analyses resulted in the retention of 33 of the original 39 items comprising seven subscales: (1) Concentration Problems, (2) Aggressive/Disruptive Behavior, (3) Prosocial Behavior, (4) Emotion Regulation Problems, (5) Internalizing Problems, (6) Family Problems, and (7) Family Involvement. IRT, item difficulty estimates, and confirmatory factor analyses revealed limited evidence of bias based on gender, race, or grade; together, the findings suggested that the 33-item TOCA-C is a highly valid and reliable measure.
{"title":"Teacher Observation of Classroom Adaptation-Checklist: Measuring Children’s Social, Emotional, and Behavioral Functioning","authors":"Catherine P. Bradshaw, Joseph M. Kush","doi":"10.1093/cs/cdz022","DOIUrl":"https://doi.org/10.1093/cs/cdz022","url":null,"abstract":"\u0000 There is a growing need for valid measures that can be administered efficiently in school settings to assess the impact of school-based preventive interventions. The current article aimed to establish a balance among assessment efficiency, reliability, and the measurement properties of an instrument widely used to assess the impact of school-based programs, called the Teacher Observation of Classroom Adaptation-Checklist (TOCA-C). We leveraged item response theory (IRT) analyses to create a shortened, more focused checklist version of the TOCA-C that is both valid and efficient for large-scale use in schools to track students’ behavioral, social–emotional, and family factors over the course of elementary school. The sample included 17,456 children in kindergarten through grade 5 (47.7 percent female, 54.2 percent African American). IRT analyses resulted in the retention of 33 of the original 39 items comprising seven subscales: (1) Concentration Problems, (2) Aggressive/Disruptive Behavior, (3) Prosocial Behavior, (4) Emotion Regulation Problems, (5) Internalizing Problems, (6) Family Problems, and (7) Family Involvement. IRT, item difficulty estimates, and confirmatory factor analyses revealed limited evidence of bias based on gender, race, or grade; together, the findings suggested that the 33-item TOCA-C is a highly valid and reliable measure.","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"29-40"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44224056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Free and Valid Teacher Social Competence Scale for School Social Workers","authors":"A. Thompson, Russell Elmore, Lindsay Marie Oetker","doi":"10.1093/cs/cdz023","DOIUrl":"https://doi.org/10.1093/cs/cdz023","url":null,"abstract":"","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"63-66"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48757918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jack H. Andrews, E. Cho, S. Tugendrajch, Brigid R. Marriott, K. Hawley
Evidence-based assessment, which requires the use of reliable and valid measurement tools, is an essential component of many services that school social workers provide to promote the social, emotional, and behavioral health of students. A wide variety of psychometrically sound assessment tools exist to choose from, but it can be difficult for school personnel to identify and access the tools best suited to meet their needs. In an effort to reduce these barriers, the authors of this article provide a concise guide to free, validated measurement tools that are feasible for routine use in school settings for the most common youth mental health concerns (anxiety, depression, and disruptive behavior). The psychometric properties and other practical characteristics of 37 measurement tools are reviewed, accompanied by links to access each tool and suggestions to help social workers identify which may best fit any particular combination of the diverse goals, school settings, and student populations they serve.
{"title":"Evidence-Based Assessment Tools for Common Mental Health Problems: A Practical Guide for School Settings","authors":"Jack H. Andrews, E. Cho, S. Tugendrajch, Brigid R. Marriott, K. Hawley","doi":"10.1093/cs/cdz024","DOIUrl":"https://doi.org/10.1093/cs/cdz024","url":null,"abstract":"\u0000 Evidence-based assessment, which requires the use of reliable and valid measurement tools, is an essential component of many services that school social workers provide to promote the social, emotional, and behavioral health of students. A wide variety of psychometrically sound assessment tools exist to choose from, but it can be difficult for school personnel to identify and access the tools best suited to meet their needs. In an effort to reduce these barriers, the authors of this article provide a concise guide to free, validated measurement tools that are feasible for routine use in school settings for the most common youth mental health concerns (anxiety, depression, and disruptive behavior). The psychometric properties and other practical characteristics of 37 measurement tools are reviewed, accompanied by links to access each tool and suggestions to help social workers identify which may best fit any particular combination of the diverse goals, school settings, and student populations they serve.","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"41-52"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48329439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Free, Feasible, and Valid Measurement Tools for School Social Workers","authors":"A. Thompson, A. Frey","doi":"10.1093/cs/cdz030","DOIUrl":"https://doi.org/10.1093/cs/cdz030","url":null,"abstract":"","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"3-6"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41848058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Compendium of Assessment Tools for Measuring Bullying","authors":"Robyn B. Bratica","doi":"10.1093/cs/cdz027","DOIUrl":"https://doi.org/10.1093/cs/cdz027","url":null,"abstract":"","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"67-69"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45355219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Anderson-Butcher, A. Amorose, Samantha Bates, Aidyn L Iachini, Anna L. Ball, Tasha Henderson
The aim of this article is to describe the Community and Youth Collaborative Institute School Experience Surveys (CAYCI-SES). The CAYCI-SES measures are free and available to use with permission. The tools include valid and reliable surveys, assessments, and scales to help school stakeholders to identify and assess school climate and other conditions for learning. The CAYCI-SES gather data about the school environment across stakeholder groups and the broader school–family–community context known to influence student learning and youth development. For example, the measures include four survey versions: elementary school student, middle/high school student, parent/caregiver, and teacher/school staff. The CAYCI-SES also are valuable evaluation tools used to inform school planning and improvement efforts. This article describes each of the CAYCI-SES surveys and provides an overview of the process used for psychometric testing and instructions for implementation. Authors also discuss examples of schools and districts that have used the measures and implications for how school social workers may use the survey findings to address or identify needs, improve outcomes, and guide school improvement efforts.
{"title":"Driving School Improvement Planning with Community and Youth Collaborative Institute School Experience Surveys (CAYCI-SES)","authors":"D. Anderson-Butcher, A. Amorose, Samantha Bates, Aidyn L Iachini, Anna L. Ball, Tasha Henderson","doi":"10.1093/cs/cdz028","DOIUrl":"https://doi.org/10.1093/cs/cdz028","url":null,"abstract":"\u0000 The aim of this article is to describe the Community and Youth Collaborative Institute School Experience Surveys (CAYCI-SES). The CAYCI-SES measures are free and available to use with permission. The tools include valid and reliable surveys, assessments, and scales to help school stakeholders to identify and assess school climate and other conditions for learning. The CAYCI-SES gather data about the school environment across stakeholder groups and the broader school–family–community context known to influence student learning and youth development. For example, the measures include four survey versions: elementary school student, middle/high school student, parent/caregiver, and teacher/school staff. The CAYCI-SES also are valuable evaluation tools used to inform school planning and improvement efforts. This article describes each of the CAYCI-SES surveys and provides an overview of the process used for psychometric testing and instructions for implementation. Authors also discuss examples of schools and districts that have used the measures and implications for how school social workers may use the survey findings to address or identify needs, improve outcomes, and guide school improvement efforts.","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":"42 1","pages":"7-17"},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42149915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Waasdorp, S. L. Johnson, K. Shukla, Catherine P. Bradshaw
Positive school climate has been consistently associated with many desirable student outcomes in both middle and high schools. However, there has been little work comparing the perceptions across these two school settings. The U.S. Department of Education conceptualized a three-factor model for school climate consisting of safety, engagement, and environment. Drawing on data from 29,720 middle and 34,950 high school students, the fit of the three-factor model was examined for measurement invariance, to explore whether the measure functioned similarly across both middle and high schools. The results indicated measurement invariance, which suggests that practitioners and researchers can confidently compare findings across middle and high schools to inform local decision making related to school-based programming. A series of multilevel analyses also explored the extent to which perceptions of school climate differed for middle and high school students; these results generally indicated that middle school students perceived the school more favorably than high school students. Implications of these findings for social workers are considered.
{"title":"Measuring School Climate: Invariance across Middle and High School Students","authors":"T. Waasdorp, S. L. Johnson, K. Shukla, Catherine P. Bradshaw","doi":"10.1093/cs/cdz026","DOIUrl":"https://doi.org/10.1093/cs/cdz026","url":null,"abstract":"\u0000 Positive school climate has been consistently associated with many desirable student outcomes in both middle and high schools. However, there has been little work comparing the perceptions across these two school settings. The U.S. Department of Education conceptualized a three-factor model for school climate consisting of safety, engagement, and environment. Drawing on data from 29,720 middle and 34,950 high school students, the fit of the three-factor model was examined for measurement invariance, to explore whether the measure functioned similarly across both middle and high schools. The results indicated measurement invariance, which suggests that practitioners and researchers can confidently compare findings across middle and high schools to inform local decision making related to school-based programming. A series of multilevel analyses also explored the extent to which perceptions of school climate differed for middle and high school students; these results generally indicated that middle school students perceived the school more favorably than high school students. Implications of these findings for social workers are considered.","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44688654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Bowen, R. Lucio, Michele Patak-Pietrafesa, G. Bowen
To support student success effectively, school teams need information on known predictors of youth behavior and academic performance. In contrast to measures of behavioral and academic outcomes that are commonly relied on in schools, the School Success Profile (SSP) for middle and high school students provides comprehensive information on predictors of outcomes that reside in students’ neighborhoods, schools, peer systems, and families. This article presents the SSP 2020, a newly revised version of the SSP that is now freely available to schools and researchers. The online, self-report SSP 2020 retains the strengths of the SSP but is shorter and simpler. Revised group- and individual-level reports are automatically generated once SSP data are collected. The SSP 2020 dashboard allows users to request reports on numerous demographic subgroups. A comprehensive prevention road map walks teams through each step of an evidence-informed decision-making process based on SSP 2020 data. Resources embedded in the road map include information on evidence-informed prevention strategies for SSP dimensions with corresponding brief assessments and fidelity checklists. School social workers are encouraged to take the lead in bringing the SSP 2020 to school teams charged with promoting student behavioral and academic success.
{"title":"The SSP 2020: The Revised School Success Profile","authors":"N. Bowen, R. Lucio, Michele Patak-Pietrafesa, G. Bowen","doi":"10.1093/cs/cdz025","DOIUrl":"https://doi.org/10.1093/cs/cdz025","url":null,"abstract":"\u0000 To support student success effectively, school teams need information on known predictors of youth behavior and academic performance. In contrast to measures of behavioral and academic outcomes that are commonly relied on in schools, the School Success Profile (SSP) for middle and high school students provides comprehensive information on predictors of outcomes that reside in students’ neighborhoods, schools, peer systems, and families. This article presents the SSP 2020, a newly revised version of the SSP that is now freely available to schools and researchers. The online, self-report SSP 2020 retains the strengths of the SSP but is shorter and simpler. Revised group- and individual-level reports are automatically generated once SSP data are collected. The SSP 2020 dashboard allows users to request reports on numerous demographic subgroups. A comprehensive prevention road map walks teams through each step of an evidence-informed decision-making process based on SSP 2020 data. Resources embedded in the road map include information on evidence-informed prevention strategies for SSP dimensions with corresponding brief assessments and fidelity checklists. School social workers are encouraged to take the lead in bringing the SSP 2020 to school teams charged with promoting student behavioral and academic success.","PeriodicalId":35453,"journal":{"name":"Children & Schools","volume":" 19","pages":""},"PeriodicalIF":2.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/cs/cdz025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41331612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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