Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations between TSRs and, for example, academic achievement, a lack of disruptive behavior, school engagement, peer relationships, motivation, executive functions, and general well-being. However, these meta-analyses have differed substantially in TSR-outcome relationships, moderators, and quality, thus complicating the interpretation of these findings. In this preregistered systematic review of meta-analyses plus original second-order meta-analyses (SOMAs), we aimed to (a) synthesize the meta-analytic evidence on relationships between TSRs and student outcomes, (b) map influential moderators of these relationships, and (c) assess the methodological quality of the meta-analyses. We synthesized over 70 years of educational research in 24 meta-analyses encompassing a total of 116 effect sizes based on more than 2 million prekindergarten and K-12 students. We conducted several three-level SOMAs and found that TSRs had similar strong significant relationships with eight clusters of outcomes: academic achievement, academic emotions, appropriate student behavior, behavior problems, executive functions and self-control, motivation, school belonging and engagement, and student well-being. Age, gender, and informant (student-, peer-, or teacher-assessments) were the most frequently examined moderators in prior research, and our moderator analyses suggested student grade level and social minority status as moderators. We further found large differences in quality between the meta-analyses, and these differences were not associated with the TSR-outcome relationships. These results map the field of TSR research; present their relationships, moderators, and meta-analytic quality; and show how TSRs can contribute to improving outcomes in students via relationship building. Future research should follow meta-analytic open science procedures to improve quality and reproducibility.

Evaluating the quality of primary studies is a key step in meta-analyses in psychology. This step is aimed at reducing the risk of bias and establishing the validity of the inferences drawn from the meta-analytic findings. However, the extant body of research offers little guidance on how to represent and incorporate primary study quality (PSQ) in meta-analyses, and some common procedures, such as creating sum scores from a set of quality indicators, often lack the backing from measurement models. Addressing these issues, we present a tutorial that guides researchers in their analytic decisions and approaches to represent and incorporate PSQ in their meta-analyses. Specifically, we describe, review, and illustrate approaches to (a) represent PSQ by single or multiple quality indicators or aggregated scores; (b) examine the moderator effects of PSQ; and (c) test the sensitivity of moderator effects to PSQ. We illustrate these approaches and present a step-by-step tutorial with analytic code for researchers’ guidance. We also encourage meta-analysts to take a measurement perspective on representing PSQ if multiple quality indicators are aggregated into a quality score. Moreover, we argue for conducting moderator sensitivity analyses to obtain more evidence on the impact of PSQ in a meta-analysis.

Evaluating the quality of primary studies is a key step in meta-analyses in psychology. This step is aimed at reducing the risk of bias and establishing the validity of the inferences drawn from the meta-analytic findings. However, the extant body of research offers little guidance on how to represent and incorporate primary study quality (PSQ) in meta-analyses, and some common procedures, such as creating sum scores from a set of quality indicators, often lack the backing from measurement models. Addressing these issues, we present a tutorial that guides researchers in their analytic decisions and approaches to represent and incorporate PSQ in their meta-analyses. Specifically, we describe, review, and illustrate approaches to (a) represent PSQ by single or multiple quality indicators or aggregated scores; (b) examine the moderator effects of PSQ; and (c) test the sensitivity of moderator effects to PSQ. We illustrate these approaches and present a step-by-step tutorial with analytic code for researchers' guidance. We also encourage meta-analysts to take a measurement perspective on representing PSQ if multiple quality indicators are aggregated into a quality score. Moreover, we argue for conducting moderator sensitivity analyses to obtain more evidence on the impact of PSQ in a meta-analysis. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Lesbian, gay, and bisexual (LGB) students face victimization in multiple contexts, including the educational context. Here, teachers can serve as an important resource for LGB students. However, teachers who are prejudiced against students from sexual minorities might not be able to fulfill this role. Accordingly, it is important to find out more about teachers' attitudes and their correlates, as such information can provide starting points for sensitization interventions in teacher education programs, which have the potential to improve the situation of LGB students in the school setting. In the present preregistered questionnaire study, we investigated the attitudes of 138 preservice teachers from the University of Luxembourg toward LGB students and tried to identify predictors of teachers’ attitudes. Results suggested that Luxembourgish preservice teachers hold mostly positive attitudes toward LGB students. Using correlation and multiple regression analyses, we identified the frequency of participants’ contact with LGB people in family or friend networks, hypergendering tendencies, sexual orientation, and religiosity as reliable predictors of attitudes toward LGB students. Age, gender, and right-wing conservatism did not reliably predict preservice teachers’ attitudes in the regression models. Our findings thus offer support for intergroup contact theory and have implications for teacher education in Luxembourg.

Executive functions (EFs) are key skills underlying other cognitive skills that are relevant to learning and everyday life. Although a plethora of evidence suggests a positive relation between the three EF subdimensions, inhibition, shifting, and updating, and math skills for schoolchildren and adults, the findings on the magnitude of and possible variations in this relation are inconclusive for preschool children and several narrow math skills (i.e., math intelligence). Therefore, the present meta-analysis aimed to (a) synthesize the relation between EFs and math intelligence (an aggregate of math skills) in preschool children; (b) examine which study, sample, and measurement characteristics moderate this relation; and (c) test the joint effects of EFs on math intelligence. Utilizing data extracted from 47 studies (363 effect sizes, 30,481 participants) from 2000 to 2021, we found that, overall, EFs are significantly related to math intelligence ( r over bar = .34, 95% CI [.31, .37]), as are inhibition ( r over bar = .30, 95% CI [.25, .35]), shifting ( r over bar = .32, 95% CI [.25, .38]), and updating ( r over bar = .36, 95% CI [.31, .40]). Key measurement characteristics of EFs, but neither children's age nor gender, moderated this relation. These findings suggest a positive link between EFs and math intelligence in preschool children and emphasize the importance of measurement characteristics. We further examined the joint relations between EFs and math intelligence via meta-analytic structural equation modeling. Evaluating different models and representations of EFs, we did not find support for the expectation that the three EF subdimensions are differentially related to math intelligence. Public Significance Statement Executive functions (EFs) are key to learning, and children who score higher on EFs also show better scores in mathematics. This meta-analysis confirms that children who can better avoid (or inhibit) being distracted, shift easily between different tasks, or update the information they have just learned also score high on math intelligence tests. However, this link between EFs and math intelligence should always be interpreted in light of the measurement characteristics of EFs, as suggested by the moderator analyses. We found evidence to support the idea that the three EFs (inhibition, shifting, and updating) are equally important for math intelligence.

Value-added (VA) models are used for accountability purposes and quantify the value a teacher or a school adds to their students’ achievement. If VA scores lack stability over time and vary across outcome domains (e.g., mathematics and language learning), their use for high-stakes decision making is in question and could have detrimental real-life implications: teachers could lose their jobs, or a school might receive less funding. However, school-level stability over time and variation across domains have rarely been studied together. In the present study, we examined the stability of VA scores over time for mathematics and language learning, drawing on representative, large-scale, and longitudinal data from two cohorts of standardized achievement tests in Luxembourg (N = 7,016 students in 151 schools). We found that only 34-38% of the schools showed stable VA scores over time with moderate rank correlations of VA scores from 2017 to 2019 of r = .34 for mathematics and r = .37 for language learning. Although they showed insufficient stability over time for high-stakes decision making, school VA scores could be employed to identify teaching or school practices that are genuinely effective—especially in heterogeneous student populations.

BACKGROUND : Response inhibition, attention shifting, and working memory updating are the three core executive functions (EFs; Miyake et al., 2000) underlying other cognitive skills that are relevant for learning and everyday life. For example, they have shown to be differentially related to the mathematical component of intelligence (i.e., math intelligence) in school students and adults. While researchers suppose these three EFs to become more differentiated from early childhood to adulthood, neither the link of these constructs nor their structure has been conclusively established in preschool children yet. Primary studies on path models connecting EFs and math intelligence diverge in the exact relation of EFs and math intelligence. It remains unclear whether inhibition, shifting, and updating exhibit distinct but correlated constructs with respect to their relation to math intelligence. OBJECTIVES : With our meta-analysis, we aimed to (a) synthesize the relation between the three EFs and math intelligence in preschool children; and (b) compare plausible models of the effects of EFs on math intelligence. DISCUSSION Our findings corroborate the positive link between EFs and math intelligence in preschool children and are similar to other age groups. From the model testing, we learned that representing EFs by a latent variable, thus capturing the covariance among the three core EFs, explained substantially more variation in math intelligence than representing them as distinct constructs.

This research addresses the interplay between two implicit motives, that are power (nPow) and affiliation (nAff), and the cortisol reactivity (CR) to a psychosocial stressor (an adaption of the Trier Social Stress Test for Children; TSST-C; Buske-Kirschbaum a al., 1997) in 89 healthy children (45 female; M-age = 7.74, SDAge = 0.46). We assessed implicit motives by a 6-image Picture Story Exercise (PSE) and cortisol by 6 saliva samples. As hypothesized, the procedure triggered a significant cortisol reaction, F(1.44, 127.05(Greenhouse-Geisser)) = 8.22, p = .002, eta(2)(p)(art) = 0.09. Contrary to our hypothesis, children high in nPow showed no significant increase in CR (beta = 0.06, p = .60). However, our results were in line with the findings of Wegner, Schuler, and Budde (2014) that a high implicit affiliation motive is associated with an attenuated CR(beta = -0.21,p = .05). Perspectives for future research on implicit motives and children's CR to psychosocial stress are discussed.

The study compares empirical results on the coronavirus SARS‐CoV‐2 (causing COVID‐19) fatality risk perception of US adult residents stratified for age, gender, and race in mid‐March 2020 (N1 = 1,182) and mid‐April 2020 (N2 = 953). While the fatality risk perception has increased from March 2020 to April 2020, our findings suggest that many US adult residents severely underestimated their absolute and relative fatality risk (i.e., differentiated for subgroups defined by pre‐existing medical conditions and age) at both time points compared to current epidemiological figures. These results are worrying because risk perception, as our study indicates, relates to actual or intended health‐protective behaviour that can reduce SARS‐CoV‐2 transmission rates.