What do meta-analysts need in primary studies? Guidelines and the SEMI checklist for facilitating cumulative knowledge.

Meta-analysis is often recognized as the highest level of evidence due to its notable advantages. Therefore, ensuring the precision of its findings is of utmost importance. Insufficient reporting in primary studies poses challenges for meta-analysts, hindering study identification, effect size estimation, and meta-regression analyses.

A meta-analysis of cognitive interventions for patients with recent onset psychosis: are they effective for improving functioning?

The increasing popularity of cognitive interventions for patients with psychosis calls for further exploration on how these interventions may benefit functional outcomes. We conducted a meta-analysis of randomized controlled trials (RCTs) to examine the effectiveness of cognitive interventions (i.e.

Efficacy of technology-based interventions in psychosis: a systematic review and network meta-analysis.

Background: Technology-based interventions (TBIs) are a useful approach when attempting to provide therapy to more patients with psychosis.

Methods: Randomized controlled trials of outcomes of TBIs face-to-face interventions in psychosis were identified in a systematic search conducted in PubMed/Ovid MEDLINE. Data were extracted independently by two researchers, and standardized mean changes were pooled using a three-level model and network meta-analysis.

Network meta-analysis in psychology and educational sciences: A systematic review of their characteristics.

Network meta-analysis (NMA) allows the combination of evidence on the effectiveness of several interventions. NMA has mainly been applied in the medical science field, whereas in the domain of psychology and educational sciences its use is less frequent. Consequently, systematic reviews that describe the characteristics of published NMAs are limited to the field of medicine, and nothing is known about the characteristics of NMAs published in the psychology and educational sciences field.

A proposal for the assessment of replication of effects in single-case experimental designs.

In science in general and in the context of single-case experimental designs, replication of the effects of the intervention within and/or across participants or experiments is crucial for establishing causality and for assessing the generality of the intervention effect. Specific developments and proposals for assessing whether an effect has been replicated or not (or to what extent) are scarce, in the general context of behavioral sciences, and practically null in the single-case experimental designs context. We propose an extension of the modified Brinley plot for assessing how many of the effects replicate.

Network Meta-Analysis for Single-Case Design Studies: An Illustration.

Single-case designs (SCDs) are used to evaluate the effects of interventions on individual participants. By repeatedly measuring participants under different conditions, SCD studies focus on individual effects rather than on group summaries. The main limitation of SCDs remains its generalisability to wider populations, reducing the relevance of their findings for practice and policy making.

Heart rate and skin conductance associations with physical aggression, psychopathy, antisocial personality disorder and conduct disorder: An updated meta-analysis.

The associations between physiological measures (i.e., heart rate and skin conductance) of autonomic nervous system (ANS) activity and severe antisocial spectrum behavior (AB) were meta-analyzed.

Moral foundations and political orientation: Systematic review and meta-analysis.

We investigate the relationship of morality and political orientation by focusing on the influential results showing that liberals and conservatives rely on different moral foundations. We conducted a comprehensive literature search from major databases and other sources for primary studies that used the Moral Foundations Questionnaire and a typical measure of political orientation, a political self-placement item. We used a predefined process for independent extraction of effect sizes by two authors and ran both study-level and individual-level analyses.

Multilevel Meta-Analysis of Individual Participant Data of Single-Case Experimental Designs: One-Stage versus Two-Stage Methods.

To conduct a multilevel meta-analysis of multiple single-case experimental design (SCED) studies, the individual participant data (IPD) can be analyzed in one or two stages. In the one-stage approach, a multilevel model is estimated based on the raw data. In the two-stage approach, an effect size is calculated for each participant and these effect sizes and their sampling variances are subsequently combined to estimate a meta-analytic multilevel model.

Estimating outcome-specific effects in meta-analyses of multiple outcomes: A simulation study.

In meta-analysis, primary studies often include multiple, dependent effect sizes. Several methods address this dependency, such as the multivariate approach, three-level models, and the robust variance estimation (RVE) method. As for today, most simulation studies that explore the performance of these methods have focused on the estimation of the overall effect size.

The application of meta-analytic (multi-level) models with multiple random effects: A systematic review.

In meta-analysis, study participants are nested within studies, leading to a multilevel data structure. The traditional random effects model can be considered as a model with a random study effect, but additional random effects can be added in order to account for dependent effects sizes within or across studies. The goal of this systematic review is three-fold.

Multilevel meta-analysis of multiple regression coefficients from single-case experimental studies.

The focus of the current study is on handling the dependence among multiple regression coefficients representing the treatment effects when meta-analyzing data from single-case experimental studies. We compare the results when applying three different multilevel meta-analytic models (i.e.

Cannabis use and nonuse in patients with first-episode psychosis: A systematic review and meta-analysis of studies comparing neurocognitive functioning.

Background: The implications of cannabis use in the onset of early psychosis and the severity of psychotic symptoms have resulted in a proliferation of studies on this issue. However, few have examined the effects of cannabis use on the cognitive symptoms of psychosis (i.e.

Loneliness and social anxiety across childhood and adolescence: Multilevel meta-analyses of cross-sectional and longitudinal associations.

Social relationships are of vital importance for children's and adolescents' development, and disruptions in these relationships can have serious implications. Such disruptions play a central role in both loneliness and social anxiety. Although both phenomena are closely related, they have largely been studied separately, and important questions have remained unanswered concerning how both go together within and across time.

Concealed correlations meta-analysis: A new method for synthesizing standardized regression coefficients.

The synthesis of standardized regression coefficients is still a controversial issue in the field of meta-analysis. The difficulty lies in the fact that the standardized regression coefficients belonging to regression models that include different sets of covariates do not represent the same parameter, and thus their direct combination is meaningless. In the present study, a new approach called concealed correlations meta-analysis is proposed that allows for using the common information that standardized regression coefficients from different regression models contain to improve the precision of a combined focal standardized regression coefficient estimate.

Analysis of single-case experimental count data using the linear mixed effects model: A simulation study.

When (meta-)analyzing single-case experimental design (SCED) studies by means of hierarchical or multilevel modeling, applied researchers almost exclusively rely on the linear mixed model (LMM). This type of model assumes that the residuals are normally distributed. However, very often SCED studies consider outcomes of a discrete rather than a continuous nature, like counts, percentages or rates.

A demonstration and evaluation of the use of cross-classified random-effects models for meta-analysis.

It is common for the primary studies in meta-analyses to report multiple effect sizes, generating dependence among them. Hierarchical three-level models have been proposed as a means to deal with this dependency. Sometimes, however, dependency may be due to multiple random factors, and random factors are not necessarily nested, but rather may be crossed.

Methodological quality of meta-analyses of single-case experimental studies.

Background: Methodological rigor is a fundamental factor in the validity and credibility of the results of a meta-analysis.

Aim: Following an increasing interest in single-case experimental design (SCED) meta-analyses, the current study investigates the methodological quality of SCED meta-analyses.

Methods And Procedures: We assessed the methodological quality of 178 SCED meta-analyses published between 1985 and 2015 through the modified Revised-Assessment of Multiple Systematic Reviews (R-AMSTAR) checklist.