Abstract Background Class size reductions in general education are some of the most researched educational interventions in social science, yet researchers have not reached any final conclusions regarding their effects. While research on the relationship between general education class size and student achievement is plentiful, research on class size in special education is scarce, even though class size issues must be considered particularly important to students with special educational needs. These students compose a highly diverse group in terms of diagnoses, functional levels, and support needs, but they share a common need for special educational accommodations, which often entails additional instructional support in smaller units than what is normally provided in general education. At this point, there is however a lack of clarity as to the effects of special education class sizes on student academic achievement and socioemotional development. Inevitably, such lack of clarity is an obstacle for special educators and policymakers trying to make informed decisions. This highlights the policy relevance of the current systematic review, in which we sought to examine the effects of small class sizes in special education on the academic achievement, socioemotional development, and well‐being of children with special educational needs. Objectives The objective of this systematic review was to uncover and synthesise data from studies to assess the impact of small class sizes on the academic achievement, socioemotional development, and well‐being of students with special educational needs. We also aimed to investigate the extent to which the effects differed among subgroups of students. Finally, we planned to perform a qualitative exploration of the experiences of children, teachers, and parents with class size issues in special education. Search Methods Relevant studies were identified through electronic searches in bibliographic databases, searches in grey literature resources, searches using Internet search engines, hand‐searches of specific targeted journals, and citation‐tracking. The following bibliographic databases were searched in April 2021: ERIC (EBSCO‐host), Academic Search Premier (EBSCO‐host), EconLit (EBSCO‐host), APA PsycINFO (EBSCO‐host), SocINDEX (EBSCO‐host), International Bibliography of the Social Sciences (ProQuest), Sociological Abstracts (ProQuest), and Web of Science (Clarivate, Science Citation Index Expanded & Social Sciences Citation Index). EBSCO OPEN Dissertations was also searched in April 2021, while the remaining searches for grey literature, hand‐searches in key journals, and citation‐tracking took place between January and May 2022. Selection Criteria The intervention in this review was a small special education class size. Eligible quantitative study designs were studies that used a well‐defined control or comparison group, that is, studies where there was a comparison between students in smaller classes and students in larger classes. Children with special educational needs in grades K‐12 (or the equivalent in European countries) in special education were eligible. In addition to exploring the effects of small class sizes in special education from a quantitative perspective, we aimed to gain insight into the lived experiences of children, teachers, and parents with class size issues in special education contexts, as they are presented in the qualitative research literature. The review therefore also included all types of empirical qualitative studies that collected primary data and provided descriptions of main methodological issues such as selection of informants, data collection procedures, and type of data analysis. Eligible qualitative study designs included but were not limited to studies using ethnographic observation or field work formats, or qualitative interview techniques applied to individual or focus group conversations. Data Collection and Analysis The literature search yielded a total of 26,141 records which were screened for eligibility based on title and abstract. From these, 262 potentially relevant records were retrieved and screened in full text, resulting in seven studies being included: three quantitative and five qualitative studies (one study contained both eligible quantitative and qualitative data). Two of the quantitative studies could not be used in the data synthesis as they were judged to have a critical risk of bias and, in accordance with the protocol, were excluded from the meta‐analysis on the basis that they would be more likely to mislead than inform. The third quantitative study did not provide enough information enabling us to calculate an effect size and standard error. Meta‐analysis was therefore not possible. Following quality appraisal of the qualitative studies, three qualitative studies were judged to be of sufficient methodological quality. It was not possible to perform a qualitative thematic synthesis since in two of these studies, findings particular to special education class size were scarce. Therefore, only descriptive data extraction could be performed. Main Results Despite the comprehensive searches, the present review only included seven studies published between 1926 and 2020. Two studies were purely quantitative (Forness, 1985; Metzner, 1926) and from the U.S. Four studies used qualitative methodology (Gottlieb, 1997; Huang, 2020; Keith, 1993; Prunty, 2012) and were from the US (2), China (1), and Ireland (1). One study, MAGI Educational Services (1995), contained both eligible quantitative and qualitative data and was from the U.S. Authors' Conclusions The major finding of the present review was that there were virtually no contemporary quantitative studies exploring the effects of small class sizes in special education, thus making it impossible to perform a meta‐analysis. More research is therefore thoroughly needed. Findings from the summary of included qualitative studies reflected that to the special education students and staff members participating in these studies, smaller class sizes were the preferred option because they allowed for more individualised instruction time and increased teacher attention to students' diverse needs. It should be noted that these studies were few in number and took place in very diverse contexts and across a large time span. There is a need for more qualitative research into the views and experiences of teachers, parents, and school administrators with special education class sizes in different local contexts and across various provision models. But most importantly, future research should strive to represent the voices of children and young people with special needs since they are the experts when it comes to matters concerning their own lives.

Abstract This is the protocol for a Campbell systematic review. The main objective of the review is to answer the following research question: What is the effect of performance pay on employee health?

This is the protocol for a Campbell review. Our primary research question is: What are the effects of different testing frequencies on student achievement? Our secondary research question is: What are the effects of different testing frequencies on measures of students' testing anxiety? Our third research question is: How are the effects of different testing frequencies on student achievement and testing anxiety moderated by subject, grade, type of test, duration of the intervention, and gender?

Abstract Background Adopted children and children placed in foster care are at increased risk of developing a range of mental health, behavioural, and psychosocial adjustment problems. Previous studies suggest that due to early experiences of separation and loss some children may have difficulties forming a secure attachment relationship with the adoptive/foster parents. Objectives The objectives of the present review were: (1) to assess the efficacy of attachment‐based interventions on measures of favourable parent/child outcomes (attachment security, dyadic interaction, parent/child psychosocial adjustment, behavioural and mental health problems, and placement breakdown) within foster and adoptive families with children aged between 0 and 17 years. (2) to identify factors that appear to be associated with more effective outcomes and factors that modify intervention effectiveness (e.g., age of the child at placement and at intervention start, programme duration, programme focus). Search Methods Relevant studies were identified through electronic searches of bibliographic databases, governmental and grey literature repositories, hand search in specific targeted journals, citation tracking, contact to international experts and Internet search engines. The database searches were carried out to October 2020. Selection Criteria The interventions of interest were parenting interventions aimed at helping the foster/adopted children and their parents to form or sustain a secure attachment relationship. The interventions had to be at least partly informed by attachment theory. Data Collection and Analysis The total number of potentially relevant studies constituted 17.822 hits after duplicates were removed. A total of 44 studies (27 different populations) met the inclusion criteria and were critically appraised by the review authors. Due to critical study quality, missing numeric data and re‐use of the same data, only 24 studies analysing 16 different populations could be used in the data synthesis (children, N = 1302; parents, N = 1344). Meta‐analysis using both child and parent outcomes were conducted on each metric separately. All analyses were inverse variance weighted using random effects statistical models. Random effects weighted mean effect sizes were calculated using 95% confidence intervals (CIs). When possible, we conducted moderator analysis using meta‐regression and single factor sub group moderator analysis. Sensitivity analysis were conducted across study design and domains of the risk of bias assessment. Main Results Ten studies analysed the effect of attachment‐based interventions on the overall psychosocial adjustment of foster or adopted children as reported by their caregivers post intervention. Measures used include the Child Behaviour Checklist, The Strengths and Difficulties Questionnaire, Brief Infant–Toddler Social and Emotional Assessment (BITSEA) and Eyberg Child Behaviour Inventory. The random effects weighted standardised mean difference (SMD) favouring the intervention group was 0.37 (95% CI, 0.10–0.65) and statistically significant. Three studies analysed the effects of attachment‐based interventions on the observed attachment security of foster and adopted children as measured by independent observation. Measures include the Strange Situation Procedure, Attachment Q‐Set, and The Emotional Availability Clinical Screener. The random effects weighted SMD was 0.59 (95% CI, −0.40–1.57) and not statistically significant. Four studies analysed the effect of attachment‐based interventions on positive child behaviour post intervention as measured by independent observation of video‐taped interaction between the child and caregivers. Measures include Disruptive Behaviour Diagnostic Observation Schedule (DB‐DOS) and Emotional Availability Scales). The random effects weighted SMD was 0.39 (95% CI, 0.14–0.64) and statistically significant. Ten studies analysed the effect of attachment‐based interventions on positive parenting behaviour post intervention as measured by independent observation of video‐taped interaction between the child and caregivers or coding of audio‐taped recordings of parental speech. Measures include Adapted Ainsworth Scales for sensitivity and noninterference, Measurement of Empathy in Adult–Child Interaction, The Dyadic Parent–Child Interaction Coding System, Reflective functioning scale, and Emotional Availability Scales. The random effects weighted SMD was 1.56 (95% CI, 0.81–2.31) and statistically significant. Nine studies analysed the effect of attachment‐based interventions on self‐reported post intervention parenting stress (Parenting Stress Index). The random effects weighted SMD was 0.24 (95% CI, 0.03–0.46.) and statistically significant. Three studies analysed the effect of attachment‐based interventions on parental post intervention self‐reported depressive symptoms (Beck Depression Inventory). The random effects weighted SMD was 0.59 (95% CI, −0.08–1.25.) and not statistically significant. Follow‐up analyses were carried out for the outcomes externalising behaviour, positive parenting, and parenting stress, but due to the low number of studies, results should be viewed with caution. Results of the single factor sub group moderator analysis suggest that it cannot be ruled out the effects differ depending on whether the interventions take place in the family home or in a clinical setting. However, it is unclear which location is associated with more positive effects as our findings differ between child and parent outcomes. Results of the sensitivity analysis showed no appreciable changes in the results following the removal of any of the studies in any of the analyses. Authors' Conclusions Parenting interventions based on attachment theory increase positive parent/child interactional behaviours, decrease parenting stress, and increase the overall psychosocial adjustment of children in foster and adoptive families postintervention. Due to the low number of studies evidence regarding the effects of attachment‐based parenting interventions on attachment security and disorganised attachment in foster and adopted children was inconclusive. Theoretically, it is possible that child attachment security and/or attachment disorganisation cannot change within the relatively short period of time that parenting interventions typically last. It is possible that if postintervention improvements in parenting behaviours are sustained over time, it may lead to possible improvement in child attachment security and a decrease in child disorganised attachment. Thus, more longitudinal research is needed. Furthermore, evidence regarding the long‐term effects of attachment‐based parenting interventions on any outcomes was inconclusive due to too few studies, but findings suggest that attachment‐based interventions increase positive parenting behaviour at follow‐up points 3–6 months after the intervention. No study included in the present review provided a measure of placement stability or breakdown as an outcome, which could be used in the meta‐analysis. This further emphasises the need for future longitudinal research in prevention of placement breakdown.

AbstractBackgroundWorldwide, a large number of infants, toddlers, and preschoolers are enroled in formal non‐parental early childhood education or care (ECEC). Theoretically, lower adult/child ratios (fewer children per adult) and smaller group sizes are hypothesised to be associated with positive child outcomes in ECEC. A lower adult/child ratio and a smaller group size may increase both the extent and quality of adult/child interactions during the day.ObjectivesThe objective of this review is to synthesise data from studies to assess the impact of adult/child ratio and group size in ECEC on measures of process characteristics of quality of care and on child outcomes.Search MethodsRelevant studies were identified through electronic searches of bibliographic databases, governmental and grey literature repositories, Internet search engines, hand search of specific targeted journals, citation tracking and contact to experts. The primary searches were carried out up to September 2020. Additional searches were carried out in February 2022.Selection CriteriaThe intervention was changes to adult/child ratio and group size in ECEC with children aged 0–5 years old. All study designs that used a well‐defined control group were eligible for inclusion.Data Collection and AnalysisThe total number of potential relevant studies constituted 14,060 hits. A total of 31 studies met the inclusion criteria and were critically appraised by the review authors. The 31 studies analysed 26 different populations. Only 12 studies analysing 8 different populations (N = 4300) could be used in the data synthesis. Included studies were published between 1968 and 2019, and the average publication year was 1992. We used random‐effects meta‐analysis, applying both robust‐variance estimation and restricted maximum likelihood procedures to synthesise effect sizes. We conducted separate analyses for process quality measures and language and literacy measures.Main ResultsThe meta‐analysis using measures of process quality as the outcome included 84 effect sizes, 5 studies, and 6256 observations. The weighted average effect size was positive but not statistically significant (effect size [ES] = 0.10, 95% confidence interval [CI] = [−0.07, 0.27]) using robust‐variance estimation. The adjusted degrees of freedom were below 4 (df = 1.5), meaning that the results were unreliable. Similarly, the low number of studies made the estimation of heterogeneity statistics difficult. The I2 and τ2 estimates were both 0, and the Q‐statistic 2.3 (p = 0.69). We found a similar, but statistically significant, weighted average effect size using a restricted maximum likelihood procedure (ES = 0.10, 95% CI = [0.004, 0.20]), and similar low levels of heterogeneity (Q = 0.7, I2 = 0%, τ2 = 0). The meta‐analysis of language and literacy outcomes is based on three studies exploring different changes to group size and/or adult/child ratio in ECEC. The meta‐analysis of language and literacy measures included 12 effect sizes, 3 studies, and 14,625 observations. The weighted average effect size was negative but not statistically significant (ES = −0.04, 95% CI = [−0.61, 0.53]) using the robust variance estimation procedure. The adjusted degrees of freedom were again below 4 (df = 1.9) and the results were unreliable. The heterogeneity statistics indicated substantial heterogeneity (Q = 9.3, I2 = 78.5%, τ2 = 0.07). The restricted maximum likelihood procedure yielded similar results (ES = −0.06, 95% CI = [−0.57, 0.46], Q = 6.1, I2 = 64.3%, τ2 = 0.03).Authors' ConclusionsThe main finding of the present review is that there are surprisingly few quantitative studies exploring the effects of changes to adult/child ratio and group size in ECEC on measures of process quality and on child outcomes. The overall quality of the included studies was low, and only two randomised studies were used in the meta‐analysis. The risk of bias in the majority of included studies was high, also in studies used in the meta‐analysis. Due to the limited number of studies that could be used in the data synthesis, we were unable to explore the effects of adult/child ratio and group size separately. No study that examined the effects of changes of the adult/child‐ratio and/or group size on socio‐emotional child outcomes could be included in the meta‐analysis. No high quality study examined the effects of large changes in adult/child ratio and group size on measures of process quality, or explored effects for children younger than 2 years. We included few studies (3) in the meta‐analysis that investigated measures of language and literacy and results for these outcomes were inconclusive. In one specification, we found a small statistically significant effect on process quality, suggesting that fewer children per adult and smaller group sizes do increase the process quality in ECEC. Caution regarding the interpretation must be exerted due to the heterogeneity of the study designs, the limited number of studies, and the generally high risk of bias within the included studies. Results of the present review have implications for both research and practice. First, findings from the present review tentatively support the theoretical hypothesis that lower adult/child ratios (fewer children per adult) and smaller group sizes beneficially influence process quality in ECEC. This hypothesis is reflected in the existence of standards and regulation on the minimum requirements regarding adult/child ratios and maximum group size in ECEC. However, the research literature to date provides little guidance on what the appropriate adult/child ratios and group sizes are. Second, findings from the present review may be seen as a testimony to the urgent need for more contemporary high‐quality research exploring the effects of changes in adult/child ratio and group size in ECEC on measures of process quality and child developmental and socio‐emotional outcomes.

This is the protocol for a Campbell systematic review. Our primary objective for this systematic review is to examine if preschool and school-based interventions aimed at improving language, literacy, and/or mathematical skills increase children's and adolescents' executive functions. As a secondary objective, we will examine how the effects of language, literacy, and mathematics interventions on executive functions are moderated by the subject of the intervention, child age or grade, the type of EF measured, and the at-risk status of participants. We will also explore how the effects are moderated by other study characteristics, and estimate the effects of the included interventions on language, literacy, and mathematical skills.

Abstract Background Low levels of numeracy and literacy skills are associated with a range of negative outcomes later in life, such as reduced earnings and health. Obtaining information about effective interventions for children with or at risk of academic difficulties is therefore important. Objectives The main objective was to assess the effectiveness of interventions targeting students with or at risk of academic difficulties in kindergarten to Grade 6. Search Methods We searched electronic databases from 1980 to July 2018. We searched multiple international electronic databases (in total 15), seven national repositories, and performed a search of the grey literature using governmental sites, academic clearinghouses and repositories for reports and working papers, and trial registries (10 sources). We hand searched recent volumes of six journals and contacted international experts. Lastly, we used included studies and 23 previously published reviews for citation tracking. Selection Criteria Studies had to meet the following criteria to be included: Population: The population eligible for the review included students attending regular schools in kindergarten to Grade 6, who were having academic difficulties, or were at risk of such difficulties. Intervention: We included interventions that sought to improve academic skills, were conducted in schools during the regular school year, and were targeted (selected or indicated). Comparison: Included studies used an intervention‐control group design or a comparison group design. We included randomised controlled trials (RCT); quasi‐randomised controlled trials (QRCT); and quasi‐experimental studies (QES). Outcomes: Included studies used standardised tests in reading or mathematics. Setting: Studies carried out in regular schools in an OECD country were included. Data Collection and Analysis Descriptive and numerical characteristics of included studies were coded by members of the review team. A review author independently checked coding. We used an extended version of the Cochrane Risk of Bias tool to assess risk of bias. We used random‐effects meta‐analysis and robust‐variance estimation procedures to synthesise effect sizes. We conducted separate meta‐analyses for tests performed within three months of the end of interventions (short‐term effects) and longer follow‐up periods. For short‐term effects, we performed subgroup and moderator analyses focused on instructional methods and content domains. We assessed sensitivity of the results to effect size measurement, outliers, clustered assignment of treatment, risk of bias, missing moderator information, control group progression, and publication bias. Results We found in total 24,414 potentially relevant records, screened 4247 of them in full text, and included 607 studies that met the inclusion criteria. We included 205 studies of a wide range of intervention types in at least one meta‐analysis (202 intervention‐control studies and 3 comparison designs). The reasons for excluding studies from the analysis were that they had too high risk of bias (257), compared two alternative interventions (104 studies), lacked necessary information (24 studies), or used overlapping samples (17 studies). The total number of student observations in the analysed studies was 226,745. There were 93% RCTs among the 327 interventions we included in the meta‐analysis of intervention‐control contrasts and 86% were from the United States. The target group consisted of, on average, 45% girls, 65% minority students, and 69% low‐income students. The mean Grade was 2.4. Most studies included in the meta‐analysis had a moderate to high risk of bias. The overall average effect sizes (ES) for short‐term and follow‐up outcomes were positive and statistically significant (ES = 0.30, 95% confidence interval [CI] = [0.25, 0.34] and ES = 0.27, 95% CI = [0.17, 0.36]), respectively). The effect sizes correspond to around one third to one half of the achievement gap between fourth Grade students with high and low socioeconomic status in the United States and to a 58% chance that a randomly selected score of an intervention group student is greater than the score of a randomly selected control group student. All measures indicated substantial heterogeneity across short‐term effect sizes. Follow‐up outcomes pertain almost exclusively to studies examining small‐group instruction by adults and effects on reading measures. The follow‐up effect sizes were considerably less heterogeneous than the short‐term effect sizes, although there was still statistically significant heterogeneity. Two instructional methods, peer‐assisted instruction and small‐group instruction by adults, had large and statistically significant average effect sizes that were robust across specifications in the subgroup analysis of short‐term effects (ES around 0.35–0.45). In meta‐regressions that adjusted for methods, content domains, and other study characteristics, they had significantly larger effect sizes than computer‐assisted instruction, coaching of personnel, incentives, and progress monitoring. Peer‐assisted instruction also had significantly larger effect sizes than medium‐group instruction. Besides peer‐assisted instruction and small‐group instruction, no other methods were consistently significant across the analyses that tried to isolate the association between a specific method and effect sizes. However, most analyses showed statistically significant heterogeneity also within categories of instructional methods. We found little evidence that effect sizes were larger in some content domains than others. Fractions had significantly higher associations with effect sizes than all other math domains, but there were only six studies of interventions targeting fractions. We found no evidence of adverse effects in the sense that no method or domain had robustly negative associations with effect sizes. The meta‐regressions revealed few other significant moderators. Interventions in higher Grades tend to have somewhat lower effect sizes, whereas there were no significant differences between QES and RCTs, general tests and tests of subdomains, and math tests and reading tests. Authors’ Conclusions Our results indicate that interventions targeting students with or at risk of academic difficulties from kindergarten to Grade 6 have on average positive and statistically significant short‐term and follow‐up effects on standardised tests in reading and mathematics. Peer‐assisted instruction and small‐group instruction are likely to be effective components of such interventions. We believe the relatively large effect sizes together with the substantial unexplained heterogeneity imply that schools can reduce the achievement gap between students with or at risk of academic difficulties and not‐at‐risk students by implementing targeted interventions, and that more research into the design of effective interventions is needed.

This is the protocol for a Campbell review. The aim of this study is to comprehensively assess the quality and nature of the search methods and reporting across Campbell systematic reviews. The search methods used in systematic reviews provide the foundation for establishing the body of literature from which conclusions are drawn and recommendations made. Searches should be comprehensive and reporting of search methods should be transparent and reproducible. Campbell Collaboration systematic reviews strive to adhere to the best methodological guidance available for this type of searching. The current work aims to provide a comprehensive assessment of the quality of the search methods and reporting in Campbell Collaboration systematic reviews. Our specific objectives include the following: To examine how searches are currently conducted in Campbell systematic reviews. To identify any machine learning or automation methods used, or emerging and less commonly used approaches to web searching. To examine how search strategies, search methods and search reporting adhere to the Methodological Expectations of Campbell Collaboration Intervention Reviews (MECCIR) and PRISMA guidelines. The findings will be used to identify opportunities for advancing current practices in Campbell reviews through updated guidance, peer review processes and author training and support.

Abstract Background Considering the rapid global movement towards inclusion for students with special educational needs (SEN), there is a surprising lack of pedagogical or didactic theories regarding the ways in which inclusive education may affect students with SEN. Group composition within the educational setting may play a role in determining the academic achievement, socio‐emotional development, and wellbeing of students with SEN. Proponents of inclusion propose that segregated educational placement causes stigmatisation and social isolation which may have detrimental effects on the self‐concept and self‐confidence of students with SEN. On the other hand, opponents of inclusion for all special needs students suggest that placement in general education classrooms may have adverse effects especially if the time and resources allocated for individualisation are not aligned with student needs. Since the 1980s, a number of reviews on the effects of inclusion have been published. Results are inconsistent, and several reviews point to a number of methodological challenges and weaknesses of the study designs within primary studies. In sum, the impact of inclusion on students with SEN may be hypothesised to be both positive and negative, and the current knowledge base is inconsistent. Objectives The objective was first: To uncover and synthesise data from contemporary studies to assess the effects of inclusion on measures of academic achievement, socio‐emotional development, and wellbeing of children with special needs when compared to children with special needs who receive special education in a segregated setting. A secondary objective was to explore how potential moderators (gender, age, type and severity of special need, part or full time inclusive education, and co‐teaching) relate to outcomes. Search Methods Relevant studies were identified through electronic searches in Academic Search Premier (EBSCO), APA PsycINFO (EBSCO), EconLit (EBSCO), ERIC (EBSCO), International Bibliography of the Social Sciences (ProQuest), Sociological Abstracts (ProQuest), Science Citation Index Expanded (Web Of Science), Social Sciences Citation Index (Web Of Science), and SocINDEX (EBSCO). The database searches were completed on 24 April 2021 and other resources: grey literature repositories, hand search in targeted journals and Internet search engines were searched in August/September 2021. The search was limited to studies reported after 2000. Selection Criteria The review included studies of children with special needs in grades K to 12 in the OECD countries. Children with all types of verifiable SEN were eligible. Inclusion refers to an educational setting with a mixture of children with and without SEN. Segregation refers to the separate education of children with SEN. All studies that compared inclusive versus segregated educational settings for children with SEN were eligible. Qualitative studies were not included. Data Collection and Analysis The total number of potentially relevant studies constituted 20,183 hits. A total of 94 studies met the inclusion criteria, all were non‐randomised studies. The 94 studies analysed data from 19 different countries. Only 15 studies could be used in the data synthesis. Seventy‐nine studies could not be used in the data synthesis as they were judged to be of critical risk of bias and, in accordance with the protocol, were excluded from the meta‐analysis on the basis that they would be more likely to mislead than inform. The 15 studies came from nine different countries. Separate meta‐analyses were conducted on conceptually distinct outcomes. All analyses were inverse variance weighted using random effects statistical models. Sensitivity analyses were performed to evaluate the robustness of pooled effect sizes across components of risk of bias. Main Results The average baseline year of the interventions analysed in the 15 studies used for meta‐analysis was 2006, ranging from 1998 to 2012. The average number of participants analysed in the interventions was 151, ranging from 10 to 1357, and the average number of controls was 261, ranging from 5 to 2752. The studies included children with multiple types of disabilities such as learning disorders/intellectual disabilities, autism spectrum disorders, ADHD, physical handicaps, visual impairments, and Down syndrome. At most, the results from eight studies could be pooled in any of the meta‐analyses. All the meta‐analyses showed a weighted average that favoured the intervention group. None of them were statistically significant. The random effects weighted standardised mean difference was 0.20 (95% confidence interval [CI]: −0.01 to 0.42) for overall psychosocial adjustment; 0.04 (95% CI: −0.27 to 0.35) for language and literacy learning outcomes, and 0.05 (95% CI: −0.16 to 0.26) for math learning outcomes. There were no appreciable changes in the results as indicated by the sensitivity analyses. There was some inconsistency in the direction and magnitude of the effect sizes between the primary studies in all analyses and a moderate amount of heterogeneity. We attempted to investigate the heterogeneity by single factor sub‐group analyses, but results were inconclusive. Authors' Conclusions The overall methodological quality of the included studies was low, and no experimental studies in which children were randomly assigned to intervention and control conditions were found. The 15 studies, which could be used in the data synthesis, were all, except for one, judged to be in serious risk of bias. Results of the meta‐analyses do not suggest on average any sizeable positive or negative effects of inclusion on children's academic achievement as measured by language, literacy, and math outcomes or on the overall psychosocial adjustment of children. The average point estimates favoured inclusion, though small and not statistically significant, heterogeneity was present in all analyses, and there was inconsistency in direction and magnitude of the effect sizes. This finding is similar to the results of previous meta‐analyses, which include studies published before 2000, and thus although the number of studies in the current meta‐analyses is limited, it can be concluded that it is very unlikely that inclusion in general increases or decreases learning and psychosocial adjustment in children with special needs. Future research should explore the effects of different kinds of inclusive education for children with different kinds of special needs, to expand the knowledge base on what works for whom.

This is the protocol for a Campbell review. The objective of this systematic review is to uncover and synthesise data from studies to assess the impact of small class sizes on the academic achievement, socioemotional development, and well-being of students with special educational needs. Where possible, we will also investigate the extent to which the effects differ among subgroups of students. Furthermore, we will perform a qualitative exploration of the experiences of children, teachers, and parents with special education class sizes.

Abstract Background School‐based service‐learning is a teaching strategy that explicitly links community service to academic instruction. It is distinctive from traditional voluntarism or community service in that it intentionally connects service activities with curriculum concepts and includes structured time for reflection. Service learning, by connecting education to real world issues and allowing students to address problems they identify, may be particularly efficacious as it increases engagement and motivates students, in particular students who might not respond well to more traditional teaching methods. Objectives The main objective was to answer the following research question: What are the effects of service learning on academic success, neither employed, nor in education or training (NEET) status post compulsory school, personal and social skills, and risk behaviour of students in primary and secondary education (grades kindergarten to 12)? Further, we wanted to investigate study‐level summaries of participant characteristics (e.g., gender, age or socioeconomic level) and quality of the service learning programme. Search Methods We identified relevant studies through electronic searches of bibliographic databases, governmental and grey literature repositories, hand search in specific targeted journals, citation tracking, and Internet search engines. The database searches were carried out in November 2019 and other resources were searched in October 2020. We searched to identify both published and unpublished literature, and reference lists of included studies and relevant reviews were searched. Selection Criteria The intervention was service learning which can be described as a curriculum‐based community service that integrates classroom instruction (such as classroom discussions, presentations, or directed writing) with community service activities. We included children in primary and secondary education (grades kindergarten to 12) in general education. Our primary focus was on measures of academic success and NEET status. A secondary focus was on measures of personal and social skills, and risk behaviour (such as drug and alcohol use, violent behaviour, sexual risk taking). All study designs that used a well‐defined control group were eligible for inclusion. Studies that utilised qualitative approaches were not included. Data Collection and Analysis The total number of potentially relevant studies constituted 13,719 hits. A total of 37 studies met the inclusion criteria. The 37 studies analysed 30 different populations. Only 10 studies (analysing nine different populations) could be used in the data synthesis. Eighteen studies could not be used in the data synthesis as they were judged to have critical risk of bias and, in accordance with the protocol, were excluded from the meta‐analysis on the basis that they would be more likely to mislead than inform. Five studies did not provide enough information enabling us to calculate an effects size and standard error, and one study did not provide enough information to assess risk of bias. Finally, two clusters of studies used the same data sets, resulting in an additional three studies we did not use in the data synthesis. Meta‐analysis of all outcomes were conducted on each conceptual outcome separately. All analyses were inverse variance weighted using random effects statistical models incorporating both the sampling variance and between study variance components into the study level weights. Random effects weighted mean effect sizes were calculated using 95% confidence intervals. We carried out a sensitivity analysis to examine the impact of correcting for clustered assignment of treatments. Main Results The 10 studies (analysing nine different populations) used for meta analysis were all from the United States. The timespan in which included studies were carried out was 33 years, from 1980 to 2013; on average the intervention year was 2007. The average number of participants in the analysed service learning interventions was 937, ranging from 18 to 3556 and the average number of controls was 927, ranging from 20 to 3395. At most, the results from three studies could be pooled in any of the meta‐analyses. All the meta‐analyses showed a weighted average that favoured the intervention group except the pregnancy outcome. None of them was statistically significant except the weighted average of the two studies reporting math test results. The random effects weighted standardised mean difference was 0.09 [95% confidence interval (CI): −0.02 to 0.21] for students' general grade point average; 0.04 (95% CI: −0.08 to 0.16) for reading; 0.21 (95% CI: 0.09 to 0.33) for math; 0.03 (95% CI: −0.10 to 0.16) for days absent from school; 0.13 (95% CI: −0.14 to 0.40) for self‐esteem; 0.07 (95% CI: −0.04 to 0.18) for locus of control. The random effects weighted odds ratio was 1.05 (95% CI: 0.63 to 1.74) for pregnancy and 0.96 (95% CI: 0.74 to 1.25) for sexual risk behaviour. In addition, a number of other outcomes were reported in a single study only. There were no appreciable changes in the results as indicated by the sensitivity analysis. We did not find any adverse effects. Authors' Conclusions In this review, we aimed to find evidence of the effectiveness of service learning on students' academic success, personal and social skills, and risk behaviour. However, the evidence was inconclusive. We found only few randomised controlled trials and the risk of bias in the included non‐randomised studies was very high. All available evidence used in the data synthesis was US‐based. The majority of studies available for meta‐analysis reported on a very limited number of outcomes; in particular few reported results on students' academic success even though the outcome was collected. Further, the majority of studies used in the meta‐analyses reported implementation problems. These considerations point to the need for more rigorously conducted studies performed outside the United States, reporting a larger number of outcomes. It would be natural to consider conducting a series of randomised controlled trial with specific allocation to implementation of high‐quality service learning as guided by the eight standards: (1) Meaningful service, (2) Link to curriculum, (3) Reflection, (4) Diversity, (5) Youth voice, (6) Community partnerships, (7) Progress monitoring and (8) Sufficient duration and intensity. Specific attention would also have to be paid to stringency in terms of conducting a well‐designed randomised trial with low risk of bias and ensuring that the sample sizes are large enough to enable sufficient power.

This is the protocol for a Campbell review. The objectives are as follows: 1.To assess the efficacy of attachment-based interventions on measures of favourable parent/child outcomes (attachment security, dyadic interaction, parent/child psychosocial adjustment, behavioural and mental health problems and placement breakdown) within foster and adoptive families with children aged between 0 and 17 years.2.To identify factors that appear to be associated with more effective outcomes and factors that modify intervention effectiveness (for example, age of the child at placement and at intervention start, programme duration, programme focus).

The Partners for Change Outcome System (PCOMS) is a feedback system that has been developed as part of psychotherapeutic treatment. The aim of this systematic review was to evaluate the effect of the PCOMS. We searched the literature and included studies that used a randomized controlled trial (RCT) design. We calculated a combined effect size across studies for outcomes related to the number of sessions attended. We also calculated a combined effect size for outcomes related to the participants' well-being. However, in the analysis of the effect on well-being, we excluded studies that included only the Outcome Rating Scale as a measure of effect because this scale is part of the PCOMS. In the calculation of the combined effect size, we used random effect models with inverse weighted variance. In the systematic literature search we identified 14 RCT studies that evaluated the effect of the PCOMS. Based on 12 studies, we found a rather small effect size for the number of sessions attended favoring the PCOMS intervention (Hedges's g = 0.13; 95% confidence interval [CI: 0.001, 0.26]). The effect size corresponded to a difference of less than 1 session. Six studies included a well-being scale that was independent of the PCOMS intervention as the outcome. The effect size for the 6 studies was insignificant (Hedges's g = 0.03; 95% Cl [-0.18, 0.23]). We found no evidence that the PCOMS feedback system has an effect on the number of sessions attended by clients or that the PCOMS improves the well-being of clients. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

This is the protocol for a Campbell review. The objectives are as follows: To synthesize data from studies to assess the impact of adult/child ratio and group size in ECEC on measures of process characteristics of quality of care and on child outcome measures.

Abstract Background At‐risk youth may be defined as a diverse group of young people in unstable life circumstances, who are currently experiencing or are at risk of developing one or more serious problems. At‐risk youth are often very unlikely to seek out help for themselves within the established venues, as their adverse developmental trajectories have installed a lack of trust in authorities such as child protection agencies and social workers. To help this population, a number of outreach programmes have been established seeking to help the young people on an ad hoc basis, meaning that the interventions are designed to fit the individual needs of each young person rather than as a one‐size‐fits‐all treatment model. The intervention in this review is targeted outreach work which may be (but does not have to be) multicomponent programmes in which outreach may be combined with other services. Objectives The main objective of this review was to answer the following research questions: What are the effects of outreach programmes on problem/high‐risk behaviour of young people between 8 and 25 years of age living in OECD countries? Are they less likely to experience an adverse outcome such as school failure or drop‐out, runaway and homelessness, substance and/or alcohol abuse, unemployment, long‐term poverty, delinquency and more serious criminal behaviour? Search Methods We identified relevant studies through electronic searches of bibliographic databases, governmental and grey literature repositories, hand search in specific targeted journals, citation tracking, and Internet search engines. The database searches were carried out in September 2020 and other resources were searched in October and November 2021. We searched to identify both published and unpublished literature, and reference lists of included studies and relevant reviews were searched. Selection Criteria The intervention was targeted outreach work which may have been combined with other services. Young people between 8 and 25 years of age living in OECD countries, who either have experienced or is at‐risk of experiencing an adverse outcome were eligible. Our primary focus was on measures of problem/high‐risk behaviour and a secondary focus was on social and emotional outcomes. All study designs that used a well‐defined control group were eligible for inclusion. Studies that utilised qualitative approaches were not included. Data Collection and Analysis The total number of potentially relevant studies constituted 17,659 hits. A total of 16 studies (17 different interventions) met the inclusion criteria. Only five studies could be used in the data synthesis. Eight studies could not be used in the data synthesis as they were judged to have critical risk of bias and, in accordance with the protocol, were excluded from the meta‐analysis on the basis that they would be more likely to mislead than inform. Two studies (three interventions) did not provide enough information enabling us to calculate an effect size and standard error, and one study did not provide enough information to assess risk of bias. Meta‐analysis of all outcomes were conducted on each conceptual outcome separately. All analyses were inverse variance weighted using random effects statistical models incorporating both the sampling variance and between study variance components into the study level weights. Random effects weighted mean effect sizes were calculated using 95% confidence intervals. Too few studies were included to carry out any sensitivity analyses. Main Results Four of the five studies used for meta analysis were from the USA and one was from Canada. The timespan in which included studies were carried out was 32 years, from 1985 to 2017; on average the intervention year was 2005. The average number of participants in the analysed interventions was 116, ranging from 30 to 346 and the average number of controls was 81, ranging from 32 to 321. At most, the results from two studies could be pooled in a single meta‐analysis. It was only possible to pool the outcomes drug (other than marijuana) use, marijuana use and alcohol use each at two different time points (one and 3 months follow up). At 1 month follow up the weighted averages varied between zero and 0.05 and at 3 months follow up between −0.17 and 0.07. None of them were statistically significant. In addition, a number of other outcomes were reported in a single study only. Authors' Conclusions Overall, there were too few studies included in any of the meta‐analyses in order for us to draw any conclusion concerning the effectiveness of outreach. The vast majority of studies were undertaken in the USA. The dominance of the USA as the main country in which outreach interventions meeting our inclusion criteria have been evaluated using rigorous methods and within our specific parameters clearly limits the generalisability of the findings. None of the studies, however, was considered to be of overall high quality in our risk of bias assessment and the process of excluding studies with critical risk of bias from the meta‐analysis applied in this review left us with only five of a total of 16 possible studies to synthesise. Further, because too few studies reported results on the same type of outcome at most two studies could be combined in a particular meta‐analysis. Given the limited number of rigorous studies available from countries other than the USA, it would be natural to consider conducting a series of randomised controlled trials evaluating the effectiveness of outreach for at‐risk youth in countries outside the USA. The trial(s) should be designed, conducted and reported according to methodological criteria for rigour in respect of internal and external validity to achieve robust results and preferably reporting a larger number of outcomes.

Campbell Systematic ReviewsVolume 16, Issue 2 e1081 SYSTEMATIC REVIEWOpen Access Targeted school-based interventions for improving reading and mathematics for students with, or at risk of, academic difficulties in Grades 7–12: A systematic review Jens Dietrichson, Corresponding Author Jens Dietrichson jsd@vive.dk VIVE—The Danish Center for Social Science Research, Copenhagen, Denmark Correspondence Jens Dietrichson, VIVE—The Danish Center for Social Science Research, Herluf Trollesgade 11, DK-1052 Copenhagen K, Denmark. Email: jsd@vive.dkSearch for more papers by this authorTrine Filges, Trine Filges VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorRasmus H. Klokker, Rasmus H. Klokker VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorBjørn C. A. Viinholt, Bjørn C. A. Viinholt VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorMartin Bøg, Martin Bøg Lundbeck A/S, Copenhagen, DenmarkSearch for more papers by this authorUlla H. Jensen, Ulla H. Jensen Professionshøjskolen Absalon, Roskilde, DenmarkSearch for more papers by this author Jens Dietrichson, Corresponding Author Jens Dietrichson jsd@vive.dk VIVE—The Danish Center for Social Science Research, Copenhagen, Denmark Correspondence Jens Dietrichson, VIVE—The Danish Center for Social Science Research, Herluf Trollesgade 11, DK-1052 Copenhagen K, Denmark. Email: jsd@vive.dkSearch for more papers by this authorTrine Filges, Trine Filges VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorRasmus H. Klokker, Rasmus H. Klokker VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorBjørn C. A. Viinholt, Bjørn C. A. Viinholt VIVE—The Danish Center for Social Science Research, Copenhagen, DenmarkSearch for more papers by this authorMartin Bøg, Martin Bøg Lundbeck A/S, Copenhagen, DenmarkSearch for more papers by this authorUlla H. Jensen, Ulla H. Jensen Professionshøjskolen Absalon, Roskilde, DenmarkSearch for more papers by this author First published: 01 April 2020 https://doi.org/10.1002/cl2.1081Citations: 4 Linked Article: Protocol Plain language summary on the Campbell website AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat 1 PLAIN LANGUAGE SUMMARY 1.1 Targeted school-based interventions improve achievement in reading and maths for at-risk students in Grades 7–12 School-based interventions targeting students with, or at risk of, academic difficulties in Grades 7–12 have on average positive effects on standardised tests in reading and maths. The most effective interventions have the potential to considerably decrease the gap between at-risk and not-at-risk students. Effects vary substantially between interventions, however, and the evidence for using certain instructional methods or targeting certain domains is weaker. 1.2 What is this review about? Low levels of literacy and numeracy skills are associated with a range of negative outcomes later in life, such as reduced employment, earnings and health. This review examines the effects of a broad range of school-based interventions targeting students with, or at risk of, academic difficulties on standardised tests in reading and maths. Included interventions changed instructional methods by, for example, using peer-assisted learning, introducing financial incentives, giving instruction in small groups, providing more progress monitoring, using computer-assisted instruction (CAI) and giving teachers access to subject-specific coaching. Some interventions targeted specific domains in reading and maths, such as reading comprehension, fluency and algebra, while others focused on building for example meta-cognitive and social-emotional skills. This Campbell systematic review examines the effects of targeted school-based interventions on standardised tests in reading and maths. The review analyses evidence from 71 studies, 52 of which are randomised controlled trials. 1.3 What studies are included? Included studies examine targeted school-based interventions that tested effects on standardised tests in reading and maths for students in Grades 7–12 in regular schools. The students either have academic difficulties, or are deemed at risk of such difficulties on the basis of their background. The interventions are targeted as they aim to improve achievement for these groups of students, and not all students. The review summarises findings from 71 studies. Of these, 59 are from the United States, four from Canada, three from the UK, two from Germany, two from the Netherlands and one from Australia. Fifty-two studies are randomised controlled trials (RCTs) and 19 are quasiexperimental studies (QESs). 1.4 What are the main findings of this review? The interventions studied have on average positive and statistically significant short-run effects on standardised tests in reading and maths. This effect size is of an educationally meaningful magnitude, for example, in relation to the gap between groups of at-risk and not-at-risk students. This means that the most effective interventions have the potential of making a considerable dent in this gap. Only seven included studies tested effects more than three months after the end of intervention, and there is, therefore, little evidence of longer-run effects. Effects are very similar across reading domains. Interventions have larger effects on standardised tests in maths than on reading tests. Small group instruction has significantly larger effect sizes than CAI and incentive components. 1.5 What do the findings of this review mean? The review provides support for school-based interventions for students with, or at risk of, academic difficulties in Grades 7–12. However, the results do not provide a strong basis for prioritising between earlier and later interventions. For that, estimates of the long-run cost-effectiveness of interventions would be needed. The lack of long-run evidence should not be confused with a lack of effectiveness. We simply do not know whether the short-run effects are lasting. More research about long-run effects would therefore be a welcome addition to the literature. More research is also needed from non-English speaking countries; a large share of the included studies is from the United States, Canada, or the UK. There are also more interventions that have been tested by reading tests than maths tests, and interventions targeting maths seem like a promising research agenda. Many studies are not included in the meta-analysis due to low methodological quality. The most important improvement to research designs would be to increase the number of units and students in intervention and control groups. Lastly, the instruction given to control groups is often not described in detail. Variation in control group instruction is therefore difficult to analyse and a likely source of the effect size variation. 1.6 How up-to-date is this review? The review authors searched for studies up to July 2018. 2 EXECUTIVE SUMMARY/ABSTRACT 2.1 Background Low levels of numeracy and literacy skills are associated with a range of negative outcomes later in life, such as reduced earnings and health. Obtaining information about effective interventions for educationally disadvantaged youth is therefore important. 2.2 Objectives The main objective was to assess the effectiveness of interventions targeting students with or at risk of academic difficulties in Grades 7–12. 2.3 Search methods We searched electronic databases from 1980 to July 2018. We searched multiple international electronic databases (in total 14), seven national repositories, and performed a search of the grey literature using governmental sites, academic clearinghouses, and repositories for reports and working papers, and trial registries (10 sources). We hand searched recent volumes of six journals and contacted international experts. Lastly, we used included studies and 23 previously published reviews for citation tracking. 2.4 Selection criteria Studies had to meet the following criteria to be included: Population: The population eligible for the review included students attending regular schools in Grades 7–12, who were having academic difficulties, or were at risk of such difficulties. Intervention: We included interventions that sought to improve academic skills, were performed in schools during the regular school year, and were targeted (selected/indicated). Comparison: Included studies used a treatment-control group design or a comparison group design. We included RCTs, quasirandomised controlled trials (QRCTs) and QESs. Outcomes: Included studies used standardised tests in reading or mathematics. Setting: Studies carried out in regular schools in an OECD country were included. 2.5 Data collection and analysis Descriptive and numerical characteristics of included studies were coded by members of the review team. A review author independently checked coding. We used an extended version of the Cochrane Risk of Bias tool to assess risk of bias. We used random-effects meta-analysis and robust-variance estimation procedures to synthesise effect sizes. We conducted separate meta-analyses for tests performed within three months of the end of interventions (short-run effects) and longer follow-up periods. For short-run effects, we performed subgroup and moderator analyses focused on instructional methods and content domains. Sensitivity of the results to effect size measurement, outliers, clustered assignment of treatment, missing values, risk of bias and publication bias was assessed. 2.6 Results We found 24,411 potentially relevant records and screened 4,244 in full text. In total 247 studies met our inclusion criteria and we included 71 studies in meta-analyses. The reasons for not including studies in the meta-analyses were that they had too high risk of bias (118), compared two alternative interventions (38 studies), lacked necessary information (13 studies), or used overlapping samples (7 studies). Of the 71 studies, 99 interventions, and 214 effect sizes included in the meta-analysis, 76% were RCTs, and the rest QESs. The total number of student observations in the analysed studies was around 105,700. The target group consisted of, on average, 47% girls, 73% minority students, and 62% low income students. The mean grade was 8.3. Most studies included in the meta-analysis had a moderate to high risk of bias. The average effect size for short-run outcomes was positive and statistically significant (weighted average effect size [ES] = 0.22, 95% confidence interval [CI] = [0.148, 0.284]). The effect size corresponds to a 56% chance that a randomly selected score of a student who received the intervention is greater than the score of a randomly selected student who did not. All measures indicated substantial heterogeneity across effect sizes. Seven studies included follow-up outcomes. The average effect size was small and not statistically significant (ES = 0.05, 95% CI = [−0.096, 0.192]), but there was substantial variation. We focused the analysis of comparative effectiveness on the short-run outcomes and two types of intervention components: instructional methods and content domains. Interventions that included small group instruction (ES = 0.38, 95% CI = [0.211, 0.547]), peer-assisted instruction (ES = 0.19, 95% CI = [0.061, 0.319]), progress monitoring (ES = 0.19, 95% CI = [0.086, 0.290]), CAI (ES = 0.17, 95% CI = [0.043, 0.309]) and coaching of personnel (ES = 0.10, 95% CI = [0.038, 0.166]) had positive and significant average effect sizes. Interventions that provided incentives for students did not have a significant average effect size (ES = 0.05, 95% CI = [−0.103, 0.194]). The average effect size of interventions that included none of the above components, but for example provided extra instructional time, instruction in groups smaller than whole class but larger than 5 students, or just changed the content had a relatively large, but statistically insignificant effect size (ES = 0.20, 95% CI = [−0.002, 0.394]). The differences between effect sizes from interventions targeting different content domains were mostly small. Interventions targeting fluency, vocabulary, multiple reading areas, meta-cognitive, social-emotional, or general academic skills, comprehension, spelling and writing, and decoding had average effect sizes ranging from 0.14 to 0.22, all of them statistically significant. Effect sizes based on mathematics tests had a relatively large effect size (ES = 0.34, CI = [0.169, 0.502]). Including all instructional methods and moderators without missing observations in meta-regressions revealed that effect sizes based on mathematics tests were significantly larger than effect sizes based on reading tests, and QES showed significantly larger effect sizes than RCTs. Small group instruction was associated with significantly larger effect sizes than CAI and incentive components. The unexplained heterogeneity remained substantial throughout the comparative effectiveness analysis. 2.7 Authors' conclusions We found evidence of positive and statistically significant average effects of educationally meaningful magnitudes (and no significant adverse effects). The most effective interventions in our sample have the potential of making a considerable dent in the achievement gap between at-risk and not-at-risk students. The results thus provide support for implementing school-based interventions for students with or at risk of academic difficulties in Grades 7–12. We want to stress that our results do not provide a strong basis for prioritising between earlier and later interventions. For that, we would need estimates of the long-run cost-effectiveness of interventions and evidence is lacking in this regard. Furthermore, there was substantial heterogeneity throughout the analyses that we were unable to explain by observable intervention characteristics. 3 BACKGROUND 3.1 The issue Across countries, a large proportion of students leave secondary school without the skills and qualifications needed to succeed in the labour market. In the member countries of the Organisation for Economic Co-operation and Development (OECD), 16% of all youth between 25 and 34 years of age have not earned the equivalent of an upper secondary education or high school degree (OECD, 2016a). According to the results from the Programme for International Student Achievement (PISA), on average around 20–25% of the participants are not proficient in reading and mathematics as 15 year olds (OECD, 2016b, 2019). Whilst the proportion of students that are not proficient in reading and mathematics is lower in some countries, it remains around 10% even in the best performing countries (OECD, 2016b, 2019). Thus, the share of students with academic difficulties is substantial in all OECD countries. Entering adulthood with a low level of educational attainment is not only associated with reduced employment and financial prospects (De Ridder et al. 2012; Johnson, Brett, & Deary, 2010; Scott & Bernhardt, 2000), it is also associated with numerous health problems and risk behaviours, such as drug use and crime, which have serious implications for the individual as well as for society (Berridge, Brodie, Pitts, Porteous, & Tarling, 2001; Brook, Stimmel, Zhang, & Brook, 2008; Feinstein, Sabates, Anderson, Sorhaindo, & Hammond, 2006; Horwood et al., 2010; Sabates, Feinstein, & Shingal, 2013). Improving the educational attainment and achievement for students with academic difficulties is therefore important. The group of students who experiences academic difficulties is diverse. It includes for instance students with learning disabilities, students who are struggling because they lack family support, because they have emotional or behavioural problems, or because they are learning the first language of the country they are living in. Some groups of students may not currently have academic difficulties but are "at risk" in the sense that they are in danger of ending up with difficulties in the future, at least in the absence of intervention (McWhirter, McWhirter, McWhirter, & McWhirter, 2004). Although being at risk points to a future negative situation, "at risk" is sometimes used to designate a current situation (McWhirter et al., 2004; Tidwell & Corona Garret, 1994), as current academic difficulties are a risk factor for future difficulties and having difficulties in one area may be a risk factor in other areas (McWhirter, McWhirter, McWhirter, & McWhirter, 1994). Separating students with and at risk of academic difficulties is therefore sometimes difficult. Test score achievement gaps are typically present well before secondary school (e.g., Heckman 2006; Lipsey et al., 2012; von Hippel, Workman, & Downey, 2018), and there are often large differences in risk factors for academic difficulties before children start primary school. For example, the gap between majority and minority ethnic children on cognitive skills tests is apparent when children are as young as 3–4 years old (e.g., Burchinal et al., 2011; Fryer & Levitt, 2013). Low-income preschool children can have more behaviour problems (e.g., Huaqing & Kaiser, 2003) and there is a strong continuity between emotional and behavioural problems in preschool and psychopathology in later childhood (Link Egger & Angold, 2006). Emotional and behavioural problems are in turn linked to lower academic achievement in school (e.g., Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011; Taylor, Oberle, Durlak, & Weissberg, 2017). Struggling readers tend to be persistently behind their peers from the early grades (e.g., Elbro & Petersen, 2004; Francis, Shaywitz, Stuebing, Shaywitz, & Fletcher, 1996) and early math and language abilities strongly predict later academic achievement (e.g., Duncan et al., 2007; Golinkoff, Hoff, Rowe, Tamis-Lemonda, & Hirsh-Pasek, 2018). The prenatal and early childhood environment appears to be an important factor that keeps students from realising their academic potential (e.g., Almond, Currie, & Duque, 2018).11 Hereditary factors do not seem like a major explanation for the achievement gap between at-risk and not-at risk groups, see e.g., Hackman and Farah (2009), Nisbett et al. (2012), and Tucker-Drob et al. (2013) for discussions. Currie (2009) furthermore documented that children from families with low socioeconomic status (SES) have worse health, including measures of foetal conditions, physical health at birth, incidence of chronic conditions and mental health problems. Immigrant and minority children are often overrepresented among low SES families and face similar risks (e.g., Bradley & Corwyn, 2002; Deater–Deckard, Dodge, Bates and Pettit, 1998; Morgan, Farkas, Hillemeier, & Maczuga, 2012). Family environments also differ in aspects thought to affect educational achievement. Low SES families are less likely to provide a rich language and literacy environment (Bus, Van IJzendoorn, & Pellegrini, 1995; Golinkoff et al., 2018; Hart & Risley, 2003). The parenting practices and access to resources such as early childhood education, health care, nutrition, and enriching spare-time activities also differ between high and low risk groups (e.g., Esping-Andersson et al., 2012; Morgan et al., 2012). Low SES parents also seem to have lower academic expectations for their children (Bradley & Corwyn, 2002; Slates, Alexander, Entwisle, & Olson, 2012), and teachers have lower expectations for low SES and minority students (e.g., Good, Aronson, & Inzlicht, 2003; Timperley & Phillips, 2003). Furthermore, low SES children are more likely to experience a decline in motivation during the course of primary, secondary, and upper secondary school (Archambault, Eccles, & Vida, 2010). The neighbourhoods students grow up in is another potential determinant of achievement (e.g., Campbell, Shaw, & Gilliom, 2000; Chetty, Friedman, Hendren, Jones, & Porter, 2018; Chetty, Hendren, & Katz, 2016). It seems likely that many students in high risk groups live in neighbourhoods that are less supportive of high educational achievement in terms of, for example, peer support and role models. To get by in a disadvantaged neighbourhood may also require a very different set of skills compared to what is needed to thrive in school, something which may increase the risk that pupils have trouble decoding the "correct" behaviour in educational environments (e.g., Heller et al., 2017). Regarding the relative importance of families and neighbourhoods, the review in Björklund & Salvanes (2011) indicates that family resources are the more important explanatory factor. After this review of risk factors for academic difficulties, it is worth noting that the life circumstances placing children and youth at risk are only partially predictive. That is, risk factors increase the probability of a having academic difficulties, but are not deterministic. As academic difficulties therefore cannot be perfectly predicted and may show up relatively late in a child's life, early interventions may not be enough and effective interventions in all grades may be needed to reduce the achievement gaps substantially. As the test score gaps between high and low risk groups remain relatively stable from the early grades, schools do not seem to be a major reason for the inequality in academic achievement (e.g., Heckman 2006; Lipsey et al., 2012; von Hippel et al. 2018). Further evidence is provided by the seasonality in achievement gaps. In the United States, the gap between high and low SES students tends to widen during summer breaks when schools are out of session (e.g., Alexander, Entwisle, & Olson, 2001; Gershenson, 2013; Kim & Quinn, 2013; although von Hippel et al., 2018, show that this pattern is not universal across risk groups, grades and cohorts). However, the stability of the test score gaps also implies that current school practice is not, in general, enough to decrease the achievement gaps. As schools are perhaps the societal arena where most children and youth can be reached, finding effective school-based interventions for students with or at risk of academic difficulties is a question of major importance. 3.2 The intervention This review focusses on interventions that are targeted at students with or at risk of academic difficulties and that aim to improve students' academic achievement. In line with the diversity of reasons for ending up with a low level of skills and educational attainment, we included interventions targeting students who for a broad range of reasons were having academic difficulties, or were at risk of such difficulties. We prioritised already having difficulties over belonging to an at risk group in the sense that if there was information about for example test scores, grade point averages, or low attendance, we did not require information about at risk status. Furthermore, we did not include interventions targeting high-performing students in groups that may otherwise be at risk. Interventions aimed at improving academic achievement are numerous and very diverse in terms of intervention focus, target group, and mode of delivery. This review focused on targeted interventions performed in schools and provided to students with or at risk of academic difficulties in Grades 7–12 (ages range from 12–14 to 17–19, depending on country/state), where academic skill building and learning were primary intervention aims. Many targeted interventions are delivered individually as a supplement to regular classes and school activities. However, targeted interventions can be delivered in various settings, including in class (e.g., paired reading interventions or the Xtreme Reading programme) or in group sessions (e.g., the READ 180 programme). This review restricts the settings to school-based interventions, by which we mean interventions delivered in school, during the regular school year, and where schools are a key stakeholder. This restriction excludes for example after-school programmes, summer camps and summer reading programmes, and interventions involving only parents and families (see, e.g., Zief, Lauver, & Maynard, 2006 for a review of after school-programmes, Kim & Quinn, 2013, for a review of summer reading programmes, and Jeynes, 2012, for a review of programmes that involve families or parents). We include a wide range of interventions that aim to improve the academic achievement of students by either changing the method of instruction—such as tutoring, peer-assisted learning or CAI interventions—or by changing the content of the instruction—for instance, interventions emphasising mathematical problem solving skills, reading comprehension or meta-cognitive and social-emotional skills. Many interventions involve changes to both teaching method and content of instruction, and very often consist of several major programmatic components. Thus, interventions were included in this review based on their aim to improve academic achievement of students with or at risk of academic under achievement and not on the type of components (or mechanisms) used in the intervention. For this reason, the review excludes interventions that may improve academic achievement as a side-effect, but do not state academic achievement as an explicit aim. For example, interventions where improvement in behavioural or social-emotional outcomes are the primary aim of the intervention, like Classroom Management or the SCARE programme, are not included. However, interventions with behavioural and social-emotional components may very well have academic achievement as one of their primary aims, and use standardised tests of reading and mathematics as one of their primary outcomes. If this is the case, and achievement is a primary outcome, such interventions are included. Thus, the content of the programme is less important than the primary outcome (academic achievement) and the target population (students with or at risk of academic difficulties). Universal interventions which aim to improve the quality of the common learning environment at school in order to raise academic performance of all students (including average and above average students) are excluded. Whole-school reform strategy concepts such as Success for All, curriculum-based programmes like Elements of Mathematics (EMP), as well as reduced class size interventions and general professional development interventions for principals and teachers that do not target at-risk students were also excluded. However, we do include interventions with a professional development component, for example, in the form of coaching of teachers during the implementation, as long as the intervention specifically targeted students with or at risk of academic difficulties. 3.3 How the intervention might work Given the spectrum of interventions that are included in this review, it is unsurprising that they represent a range of diverse strategies to achieve improvement in academic outcomes. This diversity reflects the varying reasons that might explain why students are struggling, or are at risk. In turn, the theoretical background for the interventions also vary. It is therefore not possible to specify one particular theory of change or one theoretical framework for this review. Instead, we briefly review three theoretical perspectives that characterise the majority of the included interventions. We also discuss and exemplify how targeted interventions may address some of the reasons for academic difficulties in light of the theoretical perspectives. 3.3.1 Theoretical perspectives The reasons why students may be struggling are multifaceted and the theoretical perspectives underlying interventions are therefore likely to be broad. Nevertheless, three superordinate components are characteristic for the majority of the included interventions. These components can be abridged to: Adaptation of behaviour (social learning theory). Individual cognitive learning (cognitive developmental theory). Alteration of the social learning environment (pedagogical theory). We emphasise that the following presentation of theoretical perspectives is not all-encompassing and although components are presented as demarcated, they contain some conceptual overlap. Social learning theory has its origins in social and personality psychology and was initially developed by psychologist Julian Rotter and further developed especially by Bandura (1977; 1986). From the perspective of social learning theory, behaviour and skills are primarily learned by observing and imitating the actions of others, and behaviour is in turn regulated by the recognition of those actions by others (reinforcement) or discouraged by a lack of recognition or sanctions (punishment). According to social learning theory, creating the right social context for the student can therefore stimulate more productive behaviour through social modelling and reinforcement of certain behaviours that can lead to higher achievement. Cognitive developmental theory is not one particular theory, but rather a myriad of theories about human development that focus on how cognitive functions such as language