Meta-analyses play an important role in cumulative science by combining information across multiple studies and attempting to provide effect size estimates corrected for publication bias. Research on the reproducibility of meta-analyses reveals that errors are common, and the percentage of effect size calculations that cannot be reproduced is much higher than is desirable. Furthermore, the flexibility in inclusion criteria when performing a meta-analysis, combined with the many conflicting conclusions drawn by meta-analyses of the same set of studies performed by different researchers, has led some people to doubt whether meta-analyses can provide objective conclusions. The present article highlights the need to improve the reproducibility of meta-analyses to facilitate the identification of errors, allow researchers to examine the impact of subjective choices such as inclusion criteria, and update the meta-analysis after several years. Reproducibility can be improved by applying standardized reporting guidelines and sharing all meta-analytic data underlying the meta-analysis, including quotes from articles to specify how effect sizes were calculated. Pre-registration of the research protocol (which can be peer-reviewed using novel ‘registered report’ formats) can be used to distinguish a-priori analysis plans from data-driven choices, and reduce the amount of criticism after the results are known. The recommendations put forward in this article aim to improve the reproducibility of meta-analyses. In addition, they have the benefit of “future-proofing” meta-analyses by allowing the shared data to be re-analyzed as new theoretical viewpoints emerge or as novel statistical techniques are developed. Adoption of these practices will lead to increased credibility of meta-analytic conclusions, and facilitate cumulative scientific knowledge.

Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

The worldwide number of dementia cases is increasing, and this is a trend that is expected to continue as a growing proportion of the population ages. However, conducting research with persons suffering from dementia can be fraught due to fears surrounding research risks in vulnerable populations. This can make seeking approval for studies difficult. As research directly involving persons with dementia is key for the development of evidence-based best practice, the development of a coherent ethical strategy to perform such research feasibly and effectively is of paramount importance. this paper aims to review and synthesise ethical challenges in performing research with persons who have dementia. in undertaking a systematic review of the current research literature, we will identify the central issues and arguments characterising research that concerns the ethical dimensions of research participation in the dementia population. Data were analysed using both inductive and deductive content analysis. Ethical considerations in research involving persons with dementia primarily concern the representation of the interests of the person with dementia and protection of their vulnerabilities and rights. a total of 2,894 results were returned from initial searches, following deduplication. In total, 2,458 were excluded at title review, and following abstract review 158 papers remained; 29 papers were included for analysis after full paper review and data extraction. Papers ranged between 1995 and 2013. this review has highlighted a lack of consensus in current research and guidelines addressing these concerns; a clear stance on ethical governance of studies is important for future research and best evidence-based practice in dementia.

Most of the commonly used and endorsed guidelines for systematic review protocols and reporting standards have been developed for intervention research. These excellent guidelines have been adopted as the gold-standard for systematic reviews as an evidence synthesis method. In the current paper, we highlight some issues that may arise from adopting these guidelines beyond intervention designs, including in basic behavioural, cognitive, experimental, and exploratory research. We have adapted and built upon the existing guidelines to establish a complementary, comprehensive, and accessible tool for designing, conducting, and reporting Non-Intervention, Reproducible, and Open Systematic Reviews (NIRO-SR). NIRO-SR is a checklist composed of two parts that provide itemised guidance on the preparation of a systematic review protocol for pre-registration (Part A) and reporting the review (Part B) in a reproducible and transparent manner. This paper, the tool, and an open repository (https://osf.io/f3brw) provide a comprehensive resource for those who aim to conduct a high quality, reproducible, and transparent systematic review of non-intervention studies.

Children with intellectual disabilities experience unique developmental, social, and environmental challenges that intersect with adverse childhood experiences (ACEs) and positive childhood experiences (PCEs), shaping their psychosocial outcomes. While prior research has mainly examined single adversities or protective elements, the frameworks of ACEs and PCEs provide a broader understanding of their cumulative and interactive effects. However, these constructs remain underexplored in children with intellectual disabilities. This scoping review maps the range, conceptualization, and impact of ACEs, PCEs, and related concepts on psychosocial outcomes. Following the Joanna Briggs Institute (JBI) methodology, a search of PsycInfo, MEDLINE, CINAHL, Web of Science, and Google Scholar identified studies until October 2024. Two reviewers screened and extracted data using standardized criteria. Findings reveal variability in how ACEs and PCEs are defined and measured. ACE exposure, particularly the cumulative impact of multiple ACEs (polyvictimization), links to adverse psychosocial outcomes, including emotional (e.g., anxiety, depression, Post-Traumatic Stress Disorder), behavioral (e.g., aggression, conduct problems), and developmental (e.g., social and adaptive skill deficits) difficulties. PCEs—such as positive parent–child relationships, teacher–student support, and peer acceptance—mitigate risks, though impact varies by context. Intellectual disabilities severity and socioeconomic adversity shape associations. Further research is needed to inform the adaptation of ACE–PCE frameworks for children with intellectual disabilities.