Pub Date : 2025-03-28DOI: 10.1016/j.jsp.2025.101433
Sarah Fishstrom , Philip Capin , Bethany H. Bhat , Katlynn Dahl-Leonard , Blair Payne , Hsuan-Hui Wang , Jordan Dille , Sharon Vaughn
The purpose of this meta-analysis was to examine the effects of academic interventions on academic achievement and academic anxiety outcomes among secondary students. A systematic search yielded 19 studies comprising 2377 participants from research conducted between 1990 and 2020. Results revealed statistically significant differences favoring academic treatments over the control on academic outcomes (g = 0.66, SE = 0.17) but no statistically significant benefits for academic anxiety outcomes (g = −0.13, SE = 0.11). Moderator analysis revealed that the domain focus of the intervention (i.e., math, literacy, or science) did not explain the variance in student outcomes in either achievement or anxiety. The findings from this study corroborate previous research with elementary students, which found that academic interventions improve academic outcomes but do not substantially reduce academic anxiety. These findings suggested that academic anxiety may need to be addressed directly. However, the authors caution against drawing strong conclusions due to the limited research in this area.
本荟萃分析的目的是探讨学业干预对中学生学业成就和学业焦虑结果的影响。一项系统搜索产生了19项研究，包括1990年至2020年期间进行的2377名参与者。结果显示，学术治疗组在学业成绩上优于对照组，差异有统计学意义（g = 0.66, SE = 0.17），但在学业焦虑方面无统计学意义（g = - 0.13, SE = 0.11）。调节分析显示，干预的领域焦点（即数学、识字或科学）并不能解释学生在成就或焦虑方面的差异。本研究的结果证实了先前对小学生的研究，即学业干预改善了学业成绩，但并没有实质性地减少学业焦虑。这些发现表明，学业焦虑可能需要直接解决。然而，由于这一领域的研究有限，作者警告不要得出强有力的结论。
{"title":"A meta-analysis of the effects of academic interventions on academic and academic anxiety outcomes in secondary students","authors":"Sarah Fishstrom , Philip Capin , Bethany H. Bhat , Katlynn Dahl-Leonard , Blair Payne , Hsuan-Hui Wang , Jordan Dille , Sharon Vaughn","doi":"10.1016/j.jsp.2025.101433","DOIUrl":"10.1016/j.jsp.2025.101433","url":null,"abstract":"<div><div>The purpose of this meta-analysis was to examine the effects of academic interventions on academic achievement and academic anxiety outcomes among secondary students. A systematic search yielded 19 studies comprising 2377 participants from research conducted between 1990 and 2020. Results revealed statistically significant differences favoring academic treatments over the control on academic outcomes (<em>g</em> = 0.66, <em>SE</em> = 0.17) but no statistically significant benefits for academic anxiety outcomes (<em>g</em> = −0.13, <em>SE</em> = 0.11). Moderator analysis revealed that the domain focus of the intervention (i.e., math, literacy, or science) did not explain the variance in student outcomes in either achievement or anxiety. The findings from this study corroborate previous research with elementary students, which found that academic interventions improve academic outcomes but do not substantially reduce academic anxiety. These findings suggested that academic anxiety may need to be addressed directly. However, the authors caution against drawing strong conclusions due to the limited research in this area.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"110 ","pages":"Article 101433"},"PeriodicalIF":3.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-28DOI: 10.1016/j.jsp.2025.101429
Paulina Grekov, James E. Pustejovsky, David A. Klingbeil
There is growing interest in statistical modeling of data from single-case design (SCD) research. However, currently available methods such as hierarchical linear models and generalized linear mixed models have assumptions that may limit their utility for applied SCDs, such as those that use curriculum-based measures of academic performance as outcomes. In the present paper, we demonstrate use of a flexible class of distributional models, known as generalized additive models for location, scale, and shape (GAMLSS), to evaluate different distributional families and modeling specifications for reading curriculum-based measures of reading fluency data drawn from SCD studies of academic interventions. Using Bayesian methods and graphical posterior predictive checks, we evaluated GAMLSS based on normal (Gaussian), Poisson, and negative binomial distributional families. We also evaluated the extent to which the dispersion, or variability of outcomes, itself varied across studies and across participants within studies. We found that negative binomial models with heterogeneous dispersions fit better than other distributional families and closely reproduced features of the observed data. Findings highlight the need to consider a broader set of distributional families when developing meta-analytic models of SCD data as well as the need to consider how the degree of dispersion may vary from study to study. We discuss implications for future methodological research and for meta-analysis of SCDs.
{"title":"Flexible distributional models for meta-analysis of reading fluency outcomes from single-case designs: An examination using Bayesian methods","authors":"Paulina Grekov, James E. Pustejovsky, David A. Klingbeil","doi":"10.1016/j.jsp.2025.101429","DOIUrl":"10.1016/j.jsp.2025.101429","url":null,"abstract":"<div><div>There is growing interest in statistical modeling of data from single-case design (SCD) research. However, currently available methods such as hierarchical linear models and generalized linear mixed models have assumptions that may limit their utility for applied SCDs, such as those that use curriculum-based measures of academic performance as outcomes. In the present paper, we demonstrate use of a flexible class of distributional models, known as generalized additive models for location, scale, and shape (GAMLSS), to evaluate different distributional families and modeling specifications for reading curriculum-based measures of reading fluency data drawn from SCD studies of academic interventions. Using Bayesian methods and graphical posterior predictive checks, we evaluated GAMLSS based on normal (Gaussian), Poisson, and negative binomial distributional families. We also evaluated the extent to which the dispersion, or variability of outcomes, itself varied across studies and across participants within studies. We found that negative binomial models with heterogeneous dispersions fit better than other distributional families and closely reproduced features of the observed data. Findings highlight the need to consider a broader set of distributional families when developing meta-analytic models of SCD data as well as the need to consider how the degree of dispersion may vary from study to study. We discuss implications for future methodological research and for meta-analysis of SCDs.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"110 ","pages":"Article 101429"},"PeriodicalIF":3.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.jsp.2025.101430
Lisa N. Aguilar , Lora Henderson Smith , Anisa N. Goforth
Research involving Indigenous communities requires a nuanced approach that respects their communities' unique cultural contexts, knowledge systems, and values. This article presents the critical relationality in research framework conceptualized to facilitate respectful and collaborative engagement between researchers and Indigenous communities. Grounded in principles of decolonization, indigenization, critical theory, refusal, and survivance, this framework emphasizes the importance of visiting and visioning, sustaining relations and co-creation of knowledge, and sharing knowledge and embodying accountability. Drawing on lived experiences and best practices, the critical relationality in research framework provides practical guidance and critically reflexive questions for researchers seeking to conduct ethically sound and culturally sustaining research in partnership with Indigenous communities. Its implementation has the potential to foster meaningful relationships, promote Indigenous sovereignty, and generate knowledge that is beneficial for the survivance of Indigenous peoples and importantly, Indigenous youth.
{"title":"Critical relationality in research: A framework for engaging in research alongside Indigenous communities","authors":"Lisa N. Aguilar , Lora Henderson Smith , Anisa N. Goforth","doi":"10.1016/j.jsp.2025.101430","DOIUrl":"10.1016/j.jsp.2025.101430","url":null,"abstract":"<div><div>Research involving Indigenous communities requires a nuanced approach that respects their communities' unique cultural contexts, knowledge systems, and values. This article presents the critical relationality in research framework conceptualized to facilitate respectful and collaborative engagement between researchers and Indigenous communities. Grounded in principles of decolonization, indigenization, critical theory, refusal, and survivance, this framework emphasizes the importance of visiting and visioning, sustaining relations and co-creation of knowledge, and sharing knowledge and embodying accountability. Drawing on lived experiences and best practices, the critical relationality in research framework provides practical guidance and critically reflexive questions for researchers seeking to conduct ethically sound and culturally sustaining research in partnership with Indigenous communities. Its implementation has the potential to foster meaningful relationships, promote Indigenous sovereignty, and generate knowledge that is beneficial for the survivance of Indigenous peoples and importantly, Indigenous youth.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"110 ","pages":"Article 101430"},"PeriodicalIF":3.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143705182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
International literature indicates that adolescents' subjective well-being (SWB) is associated with their academic and social-emotional development. Teachers are a central source of social influence on adolescents' school-specific SWB. However, little is known about the multilevel associations between adolescents' and their teachers' school-specific SWB, especially in collectivist cultures. This international collaborative study examined the multilevel associations between adolescents' and their teachers' school-specific SWB. Using a stratified random sample from a public secondary school in China (nstudent = 1181, nteacher = 44), we surveyed teachers' and their students' school-specific SWB and general SWB (i.e., satisfaction with life and general self-efficacy). Random-intercept-only multilevel models were fitted to delineate the cross-level associations between teachers' (Level-2 predictors) and adolescents' overall and dimensional school-specific SWB (Level-1 outcomes) while partialing out adolescents' general SWB and demographics (e.g., student gender, age). Significant within-class similarities were found in adolescents' overall and dimensional school-specific SWB (i.e., joy of learning, student school connectedness, academic self-efficacy, and educational purpose). At the class level, teachers' school-specific SWB and teaching experience were positively associated with adolescents' school-specific SWB. At the individual level, adolescents' school-specific SWB was positively associated with their life satisfaction and general self-efficacy, but not with their demographics. Implications of findings and future directions are discussed to inform researchers, practitioners, and policymakers about the significance of multidimensional measures of SWB and a whole-school approach to promoting the SWB of an entire school population (e.g., students, teachers).
{"title":"Happy together: Multilevel associations between adolescents' and teachers' school-specific subjective wellbeing","authors":"Yanchen Zhang , Qiong Yu , Tyler Renshaw , Huijuan Li , Lindsay Fallon , Xu Jiang","doi":"10.1016/j.jsp.2025.101428","DOIUrl":"10.1016/j.jsp.2025.101428","url":null,"abstract":"<div><div>International literature indicates that adolescents' subjective well-being (SWB) is associated with their academic and social-emotional development. Teachers are a central source of social influence on adolescents' school-specific SWB. However, little is known about the multilevel associations between adolescents' and their teachers' school-specific SWB, especially in collectivist cultures. This international collaborative study examined the multilevel associations between adolescents' and their teachers' school-specific SWB. Using a stratified random sample from a public secondary school in China (<em>n</em><sub>student</sub> = 1181, <em>n</em><sub>teacher</sub> = 44), we surveyed teachers' and their students' school-specific SWB and general SWB (i.e., satisfaction with life and general self-efficacy). Random-intercept-only multilevel models were fitted to delineate the cross-level associations between teachers' (Level-2 predictors) and adolescents' overall and dimensional school-specific SWB (Level-1 outcomes) while partialing out adolescents' general SWB and demographics (e.g., student gender, age). Significant within-class similarities were found in adolescents' overall and dimensional school-specific SWB (i.e., joy of learning, student school connectedness, academic self-efficacy, and educational purpose). At the class level, teachers' school-specific SWB and teaching experience were positively associated with adolescents' school-specific SWB. At the individual level, adolescents' school-specific SWB was positively associated with their life satisfaction and general self-efficacy, but not with their demographics. Implications of findings and future directions are discussed to inform researchers, practitioners, and policymakers about the significance of multidimensional measures of SWB and a whole-school approach to promoting the SWB of an entire school population (e.g., students, teachers).</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"109 ","pages":"Article 101428"},"PeriodicalIF":3.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jsp.2024.101402
Lora Henderson Smith , Lisa N. Aguilar , Kate Joshua , Toshna Pandey , Dana M. Sox , Belinda E. Hernandez , Yufu Wang , Kaylin Yang , Jessika H. Bottiani
Implementing culturally appropriate school-based prevention programs with Indigenous students that leverage culture as a protective factor has the potential to revitalize and sustain cultural connections that have historically and systematically been destroyed in the United States. However, there is a dearth of literature synthesizing the effectiveness of school-based prevention programs that have been implemented with Indigenous students across contexts. As such, we conducted a mixed method systematic review to (a) evaluate school-based prevention programs with quantitative and/or qualitative data, (b) assess the use of Indigenous research methods, and (c) examine cultural and community validity. Studies were included if they were published between January 2010 and August 2022, reported quantitative and/or qualitative outcomes for a prevention program implemented in a K–12 school with Indigenous students, or examined an intervention that was designed for Indigenous students (even if there were non-Indigenous students in the study). We strategically included qualitative and mixed methods studies to ensure that cultural and community contexts were represented in this study and to contextualize quantitative findings. Our search resulted in the inclusion of 36 manuscripts describing 28 different interventions. There were 11 mixed methods, three qualitative, and 22 quantitative studies. Quality was assessed using the Mixed Methods Appraisal Tool (Hong et al., 2018) and a randomized controlled trials appraisal tool drawn from the Journal Article Reporting Standards (Appelbaum et al., 2018). Building on the work from Kūkea Shultz and Englert (2021), cultural validity was assessed by conceptualizing cultural validity into the two distinct domains of purposeful engagement and intentional privileging. Intervention effectiveness was evaluated and separated into three criteria (i.e., positive, null, and mixed) to determine if effectiveness varied based on intervention or study design. Most of the studies reported positive outcomes and effectiveness did not vary based on study design (i.e., quantitative, qualitative, and mixed methods) or intervention design (i.e., culturally grounded, culturally adapted or mainstream/no cultural adaptations). We discuss implications of systematic review findings as well as the importance of using mixed methods to understand and contextualize intervention effectiveness when conducting research that relates to identity and culture.
在原住民学生中实施文化上合适的学校预防项目，利用文化作为保护因素，有可能恢复和维持在美国历史上和系统地被破坏的文化联系。然而，缺乏文献综合了在不同背景下对土著学生实施的以学校为基础的预防方案的有效性。因此，我们进行了一项混合方法系统回顾，以(a)用定量和/或定性数据评估基于学校的预防计划，(b)评估土著研究方法的使用情况，以及(c)检查文化和社区有效性。如果研究发表于2010年1月至2022年8月之间，报告了在K-12学校实施的土著学生预防计划的定量和/或定性结果，或检查了为土著学生设计的干预措施（即使研究中有非土著学生），则纳入研究。我们战略性地纳入了定性和混合方法研究，以确保文化和社区背景在本研究中得到体现，并将定量研究结果置于背景中。我们的搜索结果纳入了36篇描述28种不同干预措施的手稿。共有11种混合方法，3种定性研究，22种定量研究。使用混合方法评估工具（Hong et al., 2018）和随机对照试验评估工具（Appelbaum et al., 2018）评估质量。在Kūkea Shultz和Englert（2021）的研究基础上，文化有效性通过将文化有效性概念化为有目的的参与和有意的特权两个不同的领域来评估。评估干预有效性并将其分为三个标准（即积极、无效和混合），以确定有效性是否因干预或研究设计而变化。大多数研究报告的积极结果和有效性没有因研究设计（即定量、定性和混合方法）或干预设计（即文化基础、文化适应或主流/无文化适应）而变化。我们讨论了系统评价结果的含义，以及在进行与身份和文化相关的研究时，使用混合方法来理解和背景化干预效果的重要性。
{"title":"Mixed methods systematic review: Using a cultural validity assessment to evaluate prevention programs for Indigenous students","authors":"Lora Henderson Smith , Lisa N. Aguilar , Kate Joshua , Toshna Pandey , Dana M. Sox , Belinda E. Hernandez , Yufu Wang , Kaylin Yang , Jessika H. Bottiani","doi":"10.1016/j.jsp.2024.101402","DOIUrl":"10.1016/j.jsp.2024.101402","url":null,"abstract":"<div><div>Implementing culturally appropriate school-based prevention programs with Indigenous students that leverage culture as a protective factor has the potential to revitalize and sustain cultural connections that have historically and systematically been destroyed in the United States. However, there is a dearth of literature synthesizing the effectiveness of school-based prevention programs that have been implemented with Indigenous students across contexts. As such, we conducted a mixed method systematic review to (a) evaluate school-based prevention programs with quantitative and/or qualitative data, (b) assess the use of Indigenous research methods, and (c) examine cultural and community validity. Studies were included if they were published between January 2010 and August 2022, reported quantitative and/or qualitative outcomes for a prevention program implemented in a K–12 school with Indigenous students, or examined an intervention that was designed for Indigenous students (even if there were non-Indigenous students in the study). We strategically included qualitative and mixed methods studies to ensure that cultural and community contexts were represented in this study and to contextualize quantitative findings. Our search resulted in the inclusion of 36 manuscripts describing 28 different interventions. There were 11 mixed methods, three qualitative, and 22 quantitative studies. Quality was assessed using the Mixed Methods Appraisal Tool (<span><span>Hong et al., 2018</span></span>) and a randomized controlled trials appraisal tool drawn from the Journal Article Reporting Standards (<span><span>Appelbaum et al., 2018</span></span>). Building on the work from <span><span>Kūkea Shultz and Englert (2021)</span></span>, cultural validity was assessed by conceptualizing cultural validity into the two distinct domains of purposeful engagement and intentional privileging. Intervention effectiveness was evaluated and separated into three criteria (i.e., positive, null, and mixed) to determine if effectiveness varied based on intervention or study design. Most of the studies reported positive outcomes and effectiveness did not vary based on study design (i.e., quantitative, qualitative, and mixed methods) or intervention design (i.e., culturally grounded, culturally adapted or mainstream/no cultural adaptations). We discuss implications of systematic review findings as well as the importance of using mixed methods to understand and contextualize intervention effectiveness when conducting research that relates to identity and culture.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"108 ","pages":"Article 101402"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jsp.2024.101397
Carly Oddleifson, Stephen Kilgus, David A. Klingbeil, Alexander D. Latham, Jessica S. Kim, Ishan N. Vengurlekar
The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance on a state end-of-year achievement test. Study data were collected in a large suburban school district in the Midwest across 2 school years and 19 elementary schools. Participants included 5753 students in Grades 3–5. Academic screening data included aimswebPlus reading and math composite scores. SEB screening data included Academic Behavior subscale scores from the Social, Academic, and Emotional Behavior Risk Screener. Criterion scores were derived from the Missouri Assessment Program (MAP) tests of English Language Arts and Mathematics. The performance of each individual screener was compared to the naive Bayesian approach that integrated pre-test probability information (i.e., district-wide base rates of risk derived from prior year MAP test scores), academic screening scores, and SEB screening scores. Post-test probability scores were then evaluated using a threshold model (VanDerHeyden, 2013) to determine the percentage of students within the sample that could be differentiated in terms of ruling in or ruling out intervention versus those who remained undifferentiated (as indicated by the need for additional assessment to determine risk status). Results indicated that the naive Bayesian approach tended to perform similarly to individual aimswebPlus measures, with all approaches yielding a large percentage (65%–87%) of undifferentiated students when predicting proficient performance. Overall, the results indicated that we likely failed to replicate the findings of the original study. Limitations and future directions for research are discussed.
{"title":"Using a naive Bayesian approach to identify academic risk based on multiple sources: A conceptual replication","authors":"Carly Oddleifson, Stephen Kilgus, David A. Klingbeil, Alexander D. Latham, Jessica S. Kim, Ishan N. Vengurlekar","doi":"10.1016/j.jsp.2024.101397","DOIUrl":"10.1016/j.jsp.2024.101397","url":null,"abstract":"<div><div>The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance on a state end-of-year achievement test. Study data were collected in a large suburban school district in the Midwest across 2 school years and 19 elementary schools. Participants included 5753 students in Grades 3–5. Academic screening data included <em>aimswebPlus</em> reading and math composite scores. SEB screening data included Academic Behavior subscale scores from the <em>Social, Academic, and Emotional Behavior Risk Screener</em>. Criterion scores were derived from the Missouri Assessment Program (MAP) tests of English Language Arts and Mathematics. The performance of each individual screener was compared to the naive Bayesian approach that integrated pre-test probability information (i.e., district-wide base rates of risk derived from prior year MAP test scores), academic screening scores, and SEB screening scores. Post-test probability scores were then evaluated using a threshold model (VanDerHeyden, 2013) to determine the percentage of students within the sample that could be differentiated in terms of ruling in or ruling out intervention versus those who remained undifferentiated (as indicated by the need for additional assessment to determine risk status). Results indicated that the naive Bayesian approach tended to perform similarly to individual aimswebPlus measures, with all approaches yielding a large percentage (65%–87%) of undifferentiated students when predicting proficient performance. Overall, the results indicated that we likely failed to replicate the findings of the original study. Limitations and future directions for research are discussed.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"108 ","pages":"Article 101397"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-25DOI: 10.1016/j.jsp.2024.101426
Garret J. Hall, Emma Doyle
We used Bayesian ordinal regression methods to examine reading and math screening predictive strength and accuracy before and after learning disruptions related to the Covid-19 pandemic. Using a Bayesian updating procedure in which model estimates from previous years were used as Bayesian priors in following years, we found that reading and math screening was similarly predictive before and after Covid-19 prolonged unplanned school closures (PUSCs) and subsequent learning disruptions (odds ratios range across years: 15–25). We additionally found that predictive strength and accuracy varied across grade levels, but this grade variation was insensitive to learning disruptions. These findings demonstrate the practical applicability of Bayesian updating to universal screening prediction, particularly in the context of PUSCs or other learning disruptions that may impact student academic needs. Limitations and future directions for Bayesian methods in screening are discussed.
{"title":"Learning from learning loss: Bayesian updating in academic universal screening during learning disruptions","authors":"Garret J. Hall, Emma Doyle","doi":"10.1016/j.jsp.2024.101426","DOIUrl":"10.1016/j.jsp.2024.101426","url":null,"abstract":"<div><div>We used Bayesian ordinal regression methods to examine reading and math screening predictive strength and accuracy before and after learning disruptions related to the Covid-19 pandemic. Using a Bayesian updating procedure in which model estimates from previous years were used as Bayesian priors in following years, we found that reading and math screening was similarly predictive before and after Covid-19 prolonged unplanned school closures (PUSCs) and subsequent learning disruptions (odds ratios range across years: 15–25). We additionally found that predictive strength and accuracy varied across grade levels, but this grade variation was insensitive to learning disruptions. These findings demonstrate the practical applicability of Bayesian updating to universal screening prediction, particularly in the context of PUSCs or other learning disruptions that may impact student academic needs. Limitations and future directions for Bayesian methods in screening are discussed.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"109 ","pages":"Article 101426"},"PeriodicalIF":3.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model-based recursive partitioning (MOB; Zeileis et al., 2008) is a flexible framework for detecting subgroups of persons showing different effects in a wide range of parametric models. It provides a versatile tool for detecting and explaining heterogeneity in, for example, intervention studies. In this tutorial article, we introduce the general MOB framework. In two specific case studies, we illustrate how MOB-based methods can be used to detect and explain heterogeneity in two widely used frameworks in educational studies: (a) The generalized linear mixed model (GLMM) and (b) item response theory (IRT). In the first case study, we show how GLMM trees (Fokkema et al., 2018) can be used to detect subgroups with different parameters in mixed-effects models. We apply GLMM trees to longitudinal data from a study on the effects of the Head Start pre-school program to identify subgroups of families where children show comparatively larger or smaller gains in performance. In a second case study, we show how Rasch trees (Strobl et al., 2015) can be used to detect subgroups with different item parameters in IRT models (i.e. differential item functioning [DIF]). DIF should be investigated before using test results for group comparisons. We show how a recently developed stopping criterion (Henninger et al., 2023) can be used to guide subgroup detection based on DIF effect sizes.
基于模型的递归分区；Zeileis et al., 2008)是一个灵活的框架，用于检测在广泛的参数模型中显示不同效果的人的子群体。它为检测和解释例如干预研究中的异质性提供了一个通用的工具。在这篇教程中，我们将介绍一般的MOB框架。在两个具体的案例研究中，我们说明了如何使用基于mobo的方法来检测和解释教育研究中两种广泛使用的框架中的异质性：(a)广义线性混合模型（GLMM）和(b)项目反应理论（IRT）。在第一个案例研究中，我们展示了如何使用GLMM树（Fokkema等人，2018）来检测混合效应模型中具有不同参数的子组。我们将GLMM树应用于一项关于学前教育项目效果研究的纵向数据，以确定儿童表现出相对较大或较小收益的家庭亚组。在第二个案例研究中，我们展示了如何使用Rasch树（strobel等人，2015）来检测IRT模型中具有不同项目参数的子组（即差异项目功能[DIF]）。在使用测试结果进行组比较之前，应调查DIF。我们展示了最近开发的停止标准（Henninger et al., 2023）如何用于指导基于DIF效应大小的子组检测。
{"title":"One model may not fit all: Subgroup detection using model-based recursive partitioning","authors":"Marjolein Fokkema , Mirka Henninger , Carolin Strobl","doi":"10.1016/j.jsp.2024.101394","DOIUrl":"10.1016/j.jsp.2024.101394","url":null,"abstract":"<div><div>Model-based recursive partitioning (MOB; Zeileis et al., 2008) is a flexible framework for detecting subgroups of persons showing different effects in a wide range of parametric models. It provides a versatile tool for detecting and explaining heterogeneity in, for example, intervention studies. In this tutorial article, we introduce the general MOB framework. In two specific case studies, we illustrate how MOB-based methods can be used to detect and explain heterogeneity in two widely used frameworks in educational studies: (a) The generalized linear mixed model (GLMM) and (b) item response theory (IRT). In the first case study, we show how GLMM trees (Fokkema et al., 2018) can be used to detect subgroups with different parameters in mixed-effects models. We apply GLMM trees to longitudinal data from a study on the effects of the Head Start pre-school program to identify subgroups of families where children show comparatively larger or smaller gains in performance. In a second case study, we show how Rasch trees (Strobl et al., 2015) can be used to detect subgroups with different item parameters in IRT models (i.e. differential item functioning [DIF]). DIF should be investigated before using test results for group comparisons. We show how a recently developed stopping criterion (Henninger et al., 2023) can be used to guide subgroup detection based on DIF effect sizes.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"109 ","pages":"Article 101394"},"PeriodicalIF":3.8,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-10DOI: 10.1016/j.jsp.2024.101427
Sonja D. Winter , Colleen L. Eddy , Wenxi Yang , Wes Bonifay
Item Response Theory (IRT) is commonly used in educational assessments to model the relationship between one or more latent traits and the observed responses. Traditional IRT methods often rely on frequentist approaches, which can be limited by assumptions and computational constraints. This article aims to introduce school psychology researchers to Bayesian methods for IRT analyses, highlighting their advantages over traditional approaches. We provide an overview of Bayesian IRT and discuss key concepts that make up the Bayesian workflow. This workflow includes model and prior specification, prior predictive checks, model estimation and comparison, posterior distribution interpretation, posterior predictive checks, and prior sensitivity analyses. To illustrate this workflow, we used a sample of 329 teachers who completed the 16-item Teacher Stress Inventory – Short Form (TSI-SF). Our Bayesian IRT analysis revealed that the TSI-SF is best represented by a three-correlated-traits model (measuring Discipline and Motivation, Professional Investment, and Work-Related Stress as sources of stress).
{"title":"A tutorial on Bayesian item response theory: An illustration using the Teacher Stress Inventory-Short Form","authors":"Sonja D. Winter , Colleen L. Eddy , Wenxi Yang , Wes Bonifay","doi":"10.1016/j.jsp.2024.101427","DOIUrl":"10.1016/j.jsp.2024.101427","url":null,"abstract":"<div><div>Item Response Theory (IRT) is commonly used in educational assessments to model the relationship between one or more latent traits and the observed responses. Traditional IRT methods often rely on frequentist approaches, which can be limited by assumptions and computational constraints. This article aims to introduce school psychology researchers to Bayesian methods for IRT analyses, highlighting their advantages over traditional approaches. We provide an overview of Bayesian IRT and discuss key concepts that make up the Bayesian workflow. This workflow includes model and prior specification, prior predictive checks, model estimation and comparison, posterior distribution interpretation, posterior predictive checks, and prior sensitivity analyses. To illustrate this workflow, we used a sample of 329 teachers who completed the 16-item Teacher Stress Inventory – Short Form (TSI-SF). Our Bayesian IRT analysis revealed that the TSI-SF is best represented by a three-correlated-traits model (measuring Discipline and Motivation, Professional Investment, and Work-Related Stress as sources of stress).</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"109 ","pages":"Article 101427"},"PeriodicalIF":3.8,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-07DOI: 10.1016/j.jsp.2024.101417
Kunyi Zhou , Jessica Olsen , Melynda D. Casement , Mark J. Van Ryzin
Peer relationships are a significant source of stress for adolescents that can negatively impact sleep quality. Cooperative learning can reduce adolescent stress by enhancing positive social interactions in school, which may improve adolescent sleep quality. This study evaluated (a) the effects of technology-assisted cooperative learning (i.e., PeerLearning.net) on adolescents' sleep quality, sleep duration, and sleep onset latency; (b) whether these effects were mediated by reductions in stress; and (c) whether effects were moderated by race and ethnicity, sex, grade level, and dosage. We conducted a cluster randomized trial with 12 middle and high schools in the Pacific Northwest (n = 6 intervention, n = 6 control) and collected two waves of data from a sample of 813 students (50.2% female, 70.7% White, US Grades 6–9, ages 12–16 years). Results indicated significantly reduced stress (R2 = 0.80) and increased perceived sleep quality (R2 = 0.47) among adolescents after implementing technology-assisted cooperative learning, including a significant effect for dosage, but no effects on sleep duration or sleep onset latency. Effects on perceived sleep quality were mediated by effects on stress. No moderation by sex, grade, or race/ethnicity was found. Our findings (and those from previous research) suggested that technology-assisted cooperative learning is a promising universal school-based prevention program that can impact a wide range of student (and teacher) outcomes.
{"title":"Supporting healthy development in adolescence: Technology-supported cooperative learning can reduce stress and increase sleep quality","authors":"Kunyi Zhou , Jessica Olsen , Melynda D. Casement , Mark J. Van Ryzin","doi":"10.1016/j.jsp.2024.101417","DOIUrl":"10.1016/j.jsp.2024.101417","url":null,"abstract":"<div><div>Peer relationships are a significant source of stress for adolescents that can negatively impact sleep quality. Cooperative learning can reduce adolescent stress by enhancing positive social interactions in school, which may improve adolescent sleep quality. This study evaluated (a) the effects of technology-assisted cooperative learning (i.e., <span><span>PeerLearning.net</span><svg><path></path></svg></span>) on adolescents' sleep quality, sleep duration, and sleep onset latency; (b) whether these effects were mediated by reductions in stress; and (c) whether effects were moderated by race and ethnicity, sex, grade level, and dosage. We conducted a cluster randomized trial with 12 middle and high schools in the Pacific Northwest (<em>n</em> = 6 intervention, <em>n</em> = 6 control) and collected two waves of data from a sample of 813 students (50.2% female, 70.7% White, US Grades 6–9, ages 12–16 years). Results indicated significantly reduced stress (<em>R</em><sup>2</sup> = 0.80) and increased perceived sleep quality (<em>R</em><sup>2</sup> = 0.47) among adolescents after implementing technology-assisted cooperative learning, including a significant effect for dosage, but no effects on sleep duration or sleep onset latency. Effects on perceived sleep quality were mediated by effects on stress. No moderation by sex, grade, or race/ethnicity was found. Our findings (and those from previous research) suggested that technology-assisted cooperative learning is a promising universal school-based prevention program that can impact a wide range of student (and teacher) outcomes.</div></div>","PeriodicalId":48232,"journal":{"name":"Journal of School Psychology","volume":"109 ","pages":"Article 101417"},"PeriodicalIF":3.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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