Objective: Youth mental health has become a global public health priority, with psychological distress, anxiety, and depressive symptoms increasing sharply over the last decade. Numerous interventions, ranging from mindfulness-based and cognitive behavioral programs to digital applications and peer-support initiatives, have been evaluated through meta-analytic reviews. However, the cumulative evidence remains heterogeneous and dispersed across intervention modalities. The present umbrella meta-analysis synthesized existing meta-analyses on psychological and digital interventions for adolescents and young adults, adopting a Bayesian random-effects framework to quantify the overall effectiveness and heterogeneity of outcomes. Method: Systematic searches were conducted in PubMed, PsycINFO, and Web of Science up to September 2025, using the following syntax: (“meta-analysis” OR “systematic review”) AND (adolescent* OR “youth” OR “young people”) AND (“mental health” OR “well-being” OR “psychological intervention”). Eligible reviews reported standardized mean differences (Hedges’ g) or convertible statistics and targeted mental health or well-being outcomes. Effect sizes were standardized using Hedges’ g and synthesized under a random-effects framework. They were then pooled using Bayesian random-effects modeling with a Normal (0, 0.52) prior on the grand mean μ and a half-Cauchy (0, 0.5) prior on the heterogeneity variance τ. Results: Nine eligible meta-analyses (k = 9 aggregated effects, ≈1150 primary studies) met the inclusion criteria. The posterior mean standardized effect was μ = 0.229 (95% CrI [0.157, 0.301]), indicating a small but credible positive impact of interventions on youth mental health and well-being indicators (μ = 0.19 for symptom reduction; μ = 0.28 for positive well-being). Between-study heterogeneity was non-negligible (τ2 = 0.003; posterior mean I2 = 23%, 95% CrI [0.04%, 74%]), reflecting uncertainty about the true degree of variability across modalities and settings. The posterior probability that μ > 0 was >0.999, providing strong Bayesian evidence for credible but heterogeneous effects. Conclusions: The findings suggest potentially credible but heterogeneous effects of psychological and digital interventions on youth mental health and well-being outcomes, although the magnitude and consistency of these effects remain constrained by substantial heterogeneity and the breadth of aggregated outcome constructs. Results should be interpreted with appropriate caution.

Differences in emotional intelligence (EI) between gifted and non-gifted peers are commonly proposed, yet available evidence remains equivocal, likely reflecting heterogeneity in EI conceptualization and assessment. We conducted a preregistered systematic review and meta-analysis of comparative observational studies conducted since 1990 and available in English, French, Italian, Turkish, Portuguese, or Spanish (OSF registration DOI: blinded). ERIC, MEDLINE, Open Access Theses and Dissertations, PsycInfo, ResearchGate, and TESEO were searched on 8 June 2023 and updated, plus Scopus and WoS, on 26 May 2025; additionally, specialist journals were hand-searched, and reference lists were screened. Two reviewers independently screened titles/abstracts and full texts, extracted data, and resolved disagreements by consensus (third-reviewer adjudication). Of 684 records screened, 61 full texts were assessed, and 29 studies met the inclusion criteria. We synthesized group differences using 28 dimension-specific random-effects meta-analyses, estimating standardized mean differences (SMDs) with 95% confidence intervals and prediction intervals to gauge expected effects in new samples. EI outcomes were classified by theoretical framework (ability vs. trait-mixed) and measurement modality (performance-based vs. self-report). Across dimensions, pooled effects provided no evidence of systematic EI differences between gifted and nongifted students. Adaptability was the sole dimension favoring gifted students; however, its prediction interval included negative values, indicating limited generalizability and context-dependent effects. Overall, the evidence does not support a generalized EI advantage associated with giftedness, underscoring the importance of dimension-level synthesis.

Las revisiones sistemáticas (RS) y los meta-análisis (MA) constituyen un tipo de investigación fundamental para una adecuada acumulación del conocimiento en cualquier ciencia empírica. Si bien los MA permiten alcanzar conclusiones más sólidas sobre la pregunta de interés, no siempre se dan las condiciones adecuadas para su aplicación. En su defecto, pueden aplicarse RS. Se presentan las diferencias y similitudes entre las RS y los MA. Se presentan las fases en las que se lleva a cabo una RS sin MA: planteamiento de la pregunta, definición de los criterios de selección de los estudios, búsqueda de los estudios, extracción de la información, valoración del riesgo de sesgo, medida del resultado de los estudios, métodos de síntesis y redacción del informe. Se ofrece un tratamiento detallado de las dos características principales que diferencian una RS de un MA: la medida del resultado de los estudios (tamaños del efecto, niveles de probabilidad, dirección del efecto) y los métodos de síntesis (cuantitativa) alternativos a los típicos de un MA. A lo largo del tutorial se utiliza un ejemplo para ilustrar las fases de una RS. Finalmente, se ofrecen reflexiones sobre las ventajas y limitaciones de las RS en relación con los MA.

The first aim of this study was to conduct a systematic review and meta-analysis of the effectiveness of interventions implemented to reduce multidimensional perfectionism in children and adolescents compared to the control group. The second aim was to examine potential moderators (i.e. country, treatment recipients, sample type, sample age, treatment goal, type of therapy, N of sessions, treatment modality, follow-up, scale) to determine whether these variables influenced the outcomes. A systematic search process was conducted using the Web of Science, Scopus, PsycINFO, and Psicodoc databases. Twenty studies were selected, four of which had two intervention groups, and one of which reported data by gender. Consequently, the meta-analytic dataset consisted of a total of 25 independent intervention-control comparisons. The interventions were clinically effective in reducing Overall Perfectionism (g = .32 and .36), Perfectionistic Concerns (g = .25 and .43), and Perfectionistic Strivings (g = .35 and .33) for both baseline-posttest and baseline-follow-up assessments, respectively. The only two significant moderators were the type of scale used and the sample's country, both of which influenced Perfectionistic Concerns and Perfectionistic Strivings, but not Overall Perfectionism. These findings highlight the interventions' effectiveness in reducing Overall Perfectionism and its two higher-order dimensions in children and adolescents.

Las revisiones sistemáticas y los meta-análisis son herramientas fundamentales para sintetizar de forma rigurosa la evidencia científica, también en el ámbito educativo. Para que sus resultados sean válidos y útiles, es esencial que se planifiquen, realicen y reporten con precisión metodológica. Este artículo ofrece una guía práctica para desarrollar revisiones sistemáticas y meta-análisis en educación, estructurada en torno a sus fases clave: formulación de la pregunta de investigación, registro del protocolo, búsqueda bibliográfica, selección de estudios, extracción de datos, evaluación de la calidad metodológica, análisis estadístico e interpretación de resultados. A lo largo del texto se presentan recomendaciones concretas y se ilustra el proceso con ejemplos de meta-análisis en el ámbito educativo. Asimismo, se abordan errores frecuentes y se proponen estrategias para prevenirlos. Este enfoque permite comprender tanto los fundamentos teóricos como las decisiones prácticas que requiere este tipo de investigación. En definitiva, las revisiones sistemáticas y los meta-análisis realizados correctamente permiten evaluar la efectividad de las intervenciones educativas, identificar lagunas de conocimiento y orientar la toma de decisiones basada en la mejor evidencia científica disponible. Abstract Systematic reviews and meta-analyses are essential tools for synthesizing scientific evidence, including the field of education. To ensure that their findings are valid, these studies must be carefully planned, rigorously conducted, and transparently reported. This article provides a practical guide to developing systematic reviews and meta-analyses in education, organized around their key phases: formulating the research question, protocol registration, literature search, study selection, data extraction, methodological quality assessment, statistical analyses, and interpretation of the results. Specific recommendations are provided and the process is illustrated with recent examples of meta-analyses in the educational field. Common errors are also addressed, along with strategies to avoid them. This approach enables understanding of both the theoretical foundations and the practical decisions involved in this type of research. Ultimately, well-conducted systematic reviews and meta-analyses enable researchers to evaluate the effectiveness of educational interventions, identify knowledge gaps, and guide decision-making based on the best available scientific evidence.

Meta-analyses play an influential role in synthesizing the existing evidence on a particular topic. Consequently, it is especially important that meta-analyses are conducted and reported to the highest standards and that the risk of bias is minimized. Preregistration can help detect and reduce bias arising from opportunistic use of “researcher degrees of freedom.” However, little is known about the prevalence and practice of the preregistration of meta-analyses in psychology. In this study, we first measured the prevalence of preregistration in all psychology meta-analyses published in 2021. Next, for 100 randomly selected preregistered meta-analyses, we evaluated the preregistration’s coverage of key meta-analytic decisions and the extent to which published meta-analyses deviated from their preregistered protocols. Of all 1,403 eligible psychology meta-analyses published in 2021, 382 (27%) were preregistered. In our random sample, we found that key PRISMA-P decision items were often omitted from preregistered protocols—out of the 23 decision items that were examined, the median number of items covered was 13 (interquartile range [IQR] = 11–14). We also found that all 100 preregistered meta-analyses contained at least one deviation from the preregistered protocol ( Mdn = 9, IQR = 6.75–11) and that most deviations were undisclosed ( Mdn = 8, IQR = 6–11). These findings suggest that the infrequent use and poor implementation of preregistration in psychology meta-analyses undermines its potential to reduce bias and increase transparency.

The School Attitude Assessment Survey-Revised (SAAS-R) is a popular scale for assessing attitudinal and motivational aspects of students’ academic achievement. However, evidence on key psychometric properties of the SAAS-R such as reliability remains limited. We conducted a reliability generalization study of the SAAS-R using meta-analytic structural equation modeling (MASEM). We included studies reporting an application of the SAAS-R and providing correlation coefficients between the SAAS-R subscales. We searched ERIC, PsycINFO, Academic Search Premier, Supplemental Index, and Web of Science from database inception to July 2023. Analyses were based on 18 independent matrices from 13 studies examining 8712 participants. Our main results, based on a one-stage, correlation-based MASEM approach and with omega total as the reliability measure, yielded an overall reliability estimate of 0.795 (95% CI 0.778–0.811). This suggests that the SAAS-R offers good score reliability for research and practice purposes. Applications using adapted versions obtained on average higher score reliabilities than the original ones. We discuss the implications of these results, which need to be interpreted with caution given the important reporting limitations of the primary studies included.

Psychological inflexibility (PI) and psychological flexibility (PF) are transdiagnostic mechanisms involved in the development, maintenance and treatment of SUDs. Evidence on the relationship between their components and substance abuse has not been investigated using a meta-analytic approach. The aim of this meta-analysis was to quantify the association between the dimensions of PF and PI, and substance abuse. A systematic literature review was conducted in four databases. A total of 24 studies were included. The associations were quantified using Pearson's r correlation coefficients, and two separate meta-analyses were conducted: one for the association between mindfulness and substance abuse, and one for the association between experiential avoidance and substance abuse. The meta-analyses showed a low and negative mindfulness-substance abuse relationship (r = -0.25), and a moderate and positive experiential avoidance-substance abuse relationship (r = 0.34). One study reported a correlation of r = -0.17 between defusion and substance abuse. The search for studies on the remaining components was unsuccessful. Substance type and target population moderated the relationship between mindfulness and substance abuse. Clinical and empirical implications of these results are discussed, and recommendations and future research directions are outlined.

Meta-analysis is one of the most useful research approaches, the relevance of which relies on its credibility. Reproducibility of scientific results could be considered as the minimal threshold of this credibility. We assessed the reproducibility of a sample of meta-analyses published between 2000 and 2020. From a random sample of 100 articles reporting results of meta-analyses of interventions in clinical psychology, 217 meta-analyses were selected. We first tried to retrieve the original data by recovering a data file, recoding the data from document files, or requesting it from original authors. Second, through a multistage workflow, we tried to reproduce the main results of each meta-analysis. The original data were retrieved for 67% (146/217) of meta-analyses. Although this rate showed an improvement over the years, in only 5% of these cases was it possible to retrieve a data file ready for reuse. Of these 146, 52 showed a discrepancy larger than 5% in the main results in the first stage. For 10 meta-analyses, this discrepancy was solved after fixing a coding error of our data-retrieval process, and for 15 of them, it was considered approximately reproduced in a qualitative assessment. In the remaining meta-analyses (18%, 27/146), different issues were identified in an in-depth review, such as reporting inconsistencies, lack of data, or transcription errors. Nevertheless, the numerical discrepancies were mostly minor and had little or no impact on the conclusions. Overall, one of the biggest threats to the reproducibility of meta-analysis is related to data availability and current data-sharing practices in meta-analysis.

Background Anxiety and depression symptomatology has increased in the child and adolescent population. Internet-delivered psychological treatments (IDPT) can help to reduce this symptomatology, attending to the largest possible population. Aim To conduct a systematic review and network meta-analysis of IDPT to reduce anxiety and depression symptoms in children and adolescents. Methods The search for studies was conducted in SCOPUS, PsycINFO, PSICODOC, PsycARTICLES and Medline, between 2000 and 2022, in December 2022. Studies were selected if they were conducted with a sample of children and/or adolescents with previous symptoms of anxiety and depression, had applied IDPT, and included at least two comparative groups with pretest-posttest measures. Network meta-analyses were separately performed for anxiety and depression outcomes. Publication bias was analyzed using Egger's test and funnel plots, and mixed-effects meta-regression models were applied to account for heterogeneity. Results 37 studies were included in the meta-analysis, providing a total of 74 comparative groups. IDPT exhibited low-to-moderate, statistically significant average effect sizes when compared to both inactive and active controls. No statistical significance was found when IDPT was compared with other types of interventions. Discussion IDPT is recommended to reduce anxiety and depression symptomatology in children and adolescents, but more studies are needed which compare treatments with other types of interventions, such as face-to-face therapy.

One of the biggest limitations of meta-analyses is that the information they provide can be affected by the biases of the included primary studies. To address this, evaluations of primary study risk of bias (RoB) can be performed and incorporated into the meta-analysis. However, research on this topic in clinical psychology is scarce. In this study, we examined this issue using a sample of clinical psychology meta-analyses that included RoB assessments. First, we evaluated meta-analysts’ assessment practices. Second, we summarized the RoB ratings of the primary studies included in the meta-analyses. Lastly, we examined the relationship between RoB ratings and effect sizes. We found some suboptimal practices in the assessment procedures, such as only half of the studies reporting that the assessment was conducted in duplicate. Regarding RoB ratings, the domains with the highest ratings were random sequence generation, blinding of outcome assessment, and incomplete outcome data, with about half of the primary studies rated as low RoB. The lowest ratings were found for allocation concealment and, especially, blinding of participants and personnel. Importantly, we found a positive association between the publication year of the primary studies and a lower RoB in most domains. Lastly, performing our own re-analysis, we found an association between RoB and effect sizes, which contrasts with the results of the analyses reported in the meta-analyses that combined those studies. We recommend caution when interpreting a lack of modulation of effect sizes in meta-analyses, as they may not have sufficient statistical power for moderator analyses.

Reliability generalization (RG) is a kind of meta-analysis that aims to characterize how reliability varies from one test application to the next. A wide variety of statistical methods have typically been applied in RG meta-analyses, regarding statistical model (ordinary least squares, fixed-effect, random effects, varying-coefficient models), weighting scheme (inverse variance, sample size, not weighting), and transformation method (raw, Fisher’s Z, Hakstian and Whalen’s and Bonett’s transformation) of reliability coefficients. This variety of methods compromise the comparability of RG meta-analyses results and their reproducibility. With the purpose of examining the influence of the different statistical methods applied, a methodological review was conducted on 138 published RG meta-analyses of psychological tests, amounting to a total of 4,350 internal consistency coefficients. Among all combinations of procedures that made theoretical sense, we compared thirteen strategies for calculating the average coefficient, eighteen for calculating the confidence intervals of the average coefficient and calculated the heterogeneity indices for the different transformations of the coefficients. Our findings showed that transformation methods of the reliability coefficients improved the normality adjustment of the coefficient distribution. Regarding the average reliability coefficient and the width of confidence intervals, clear differences among methods were found. The largest discrepancies were found between the different strategies for calculating confidence intervals. Our findings point towards the need for the meta-analyst to justify the statistical model assumed, as well as the transformation method of the reliability coefficients and the weighting scheme.

Several types of intervals are usually employed in meta-analysis, a fact that has generated some confusion when interpreting them. Confidence intervals reflect the uncertainty related to a single number, the parametric mean effect size. Prediction intervals reflect the probable parametric effect size in any study of the same class as those included in a meta-analysis. Its interpretation and applications are different. In this article we explain their different nature and how they can be used to answer specific questions. Numerical examples are included, as well as their computation with the metafor R package. En los informes meta-analíticos se suelen reportar varios tipos de intervalos, hecho que ha generado cierta confusión a la hora de interpretarlos. Los intervalos de confianza reflejan la incertidumbre relacionada con un número, el tamaño del efecto medio paramétrico. Los intervalos de predicción reflejan el tamaño paramétrico probable en cualquier estudio de la misma clase que los incluidos en un meta-análisis. Su interpretación y aplicaciones son diferentes. En este artículo explicamos su diferente naturaleza y cómo se pueden utilizar para responder preguntas específicas. Se incluyen ejemplos numéricos, así como su cálculo con el paquete metafor en R.

Meta-analyses often present flexibility regarding their inclusion criteria, outcomes of interest, statistical analyses, and assessments of the primary studies. For this reason, it is necessary to transparently report all the information that could impact the results. In this meta-review, we aimed to assess the transparency of meta-analyses that examined the benefits of cognitive training, given the ongoing controversy that exists in this field. Ninety-seven meta-analytic reviews were included, which examined a wide range of populations with different clinical conditions and ages. Regarding the reporting, information about the search of the studies, screening procedure, or data collection was detailed by most reviews. However, authors usually failed to report other aspects such as the specific meta-analytic parameters, the formula used to compute the effect sizes, or the data from primary studies that were used to compute the effect sizes. Although some of these practices have improved over the years, others remained the same. Moreover, examining the eligibility criteria of the reviews revealed a great heterogeneity in aspects such as the training duration, age cut-offs, or study designs that were considered. Preregistered meta-analyses often specified poorly how they would deal with the multiplicity of data or assess publication bias in their protocols, and some contained non-disclosed deviations in their eligibility criteria or outcomes of interests. The findings shown here, although they do not question the benefits of cognitive training, illustrate important aspects that future reviews must consider.