A systematic review and network meta-analysis on the effectiveness of exercise-based interventions for reducing the injury incidence in youth team-sport players. Part 2: an analysis by movement patterns.

The objectives of this network meta-analysis were: (a) to estimate and compare the pooled effects of some injury prevention programs (IPPs) whose exercise-based components were categorized using a movement pattern-specific taxonomy on reducing overall and some specific body regions (lower extremity, thigh, knee, and ankle) injury incidences in youth team sport athletes and (b) to explore the individual effects of these components on the injury incidence rates (IIRs) previously mentioned. Searches were performed in PubMed, Web of Science, SPORTDiscus, and Cochrane Library. Eligible criteria were: exercise-based interventions comprised of exercises involving athletic motor skill competencies and evaluated against a control group, overall IIRs were reported, and youth (≤19 years old) team sport players. For the current analysis, a taxonomy based on movement patterns was employed for exercise component identification (upper body pushing and pulling; lower body concentric and eccentric; core; mechanics; acceleration; and lower body stability). Pooled effects were calculated by frequentist random effects pairwise and network meta-analyses. Nineteen studies were included. Most of the IPPs exhibit risk reduction when compared to their control groups on overall, lower extremity, and ankle injuries. Interventions comprised of lower body concentric and eccentric, core, mechanics, and lower body stability exercises were the most effective measures for reducing these injuries. None of the IPPs demonstrated to be effective for reducing thigh injuries, and contradictory results were found for knee injuries. Individual analysis at component level revealed that the lower body (bilateral and unilateral, concentric, and eccentric) component was the only one associated with a significant reduction on overall injuries. Indirect evidence suggests that interventions incorporating lower body concentric and eccentric, core, mechanics, and lower body stability exercises might be the most effective for reducing overall, lower extremity, and ankle injuries in youth team sports.

The categorization of exercise components based on the movement patterns might, a priori, be considered a criterion more closely associated with the injury phenomenon.Lower body concentric and eccentric, core, mechanics, and lower body stability exercises should be incorporated to any training program aimed at minimizing the risk of injury in youth.The ineffectiveness of interventions on the reduction of thigh injuries reveals the need for reconsideration of injury prevention strategies.

The Fear of COVID-19 Scale: A meta-analytic structural equation modeling approach.

The widespread administration and multiple validations of the Fear of COVID-19 Scale (FCV-19S) in different languages have highlighted the controversy over its underlying structure and the resulting reliability index. In the present study, a meta-analysis based on structural equation modeling (MASEM) was conducted to assess the internal structure of the seven-item, 5-point Likert-type FCV-19S version, estimate an overall reliability index from the underlying model that best reflected the internal structure (one τ-equivalent factor, one congeneric factor, or two-factor models), and perform moderator analyses for the model-implied interitem correlations and estimated factor loadings. A Pearson interitem correlation matrix was obtained for 48 independent studies, from which a pooled matrix was calculated following a random-effects multivariate meta-analysis. The results from the one-stage MASEM analysis showed that the two-factor model properly fitted the pooled matrix, while the τ-equivalent and congeneric one-factor models did not. Even though, the use of a bifactor model exhibited the predominance of the general factor over the domain-specific ones. High omega coefficients were obtained for the entire scale (.91) and the psychological (.83) and physiological (.83) symptoms subscales. Moderator analyses evidenced an increase in the estimated factor loadings, as well as in the reliability of the FCV-19S, when the standard deviation of the total scores increased and when the FCV-19S was administered to specific (vs. general) populations. The FCV-19S can be therefore considered as a highly related two-factor scale whose reliability makes it suitable for applied and research purposes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Heterogeneity estimation in meta-analysis of standardized mean differences when the distribution of random effects departs from normal: A Monte Carlo simulation study.

BACKGROUND: Advantages of meta-analysis depend on the assumptions underlying the statistical procedures used being met. One of the main assumptions that is usually taken for granted is the normality underlying the population of true effects in a random-effects model, even though the available evidence suggests that this assumption is often not met. This paper examines how 21 frequentist and 24 Bayesian methods, including several novel procedures, for computing a point estimate of the heterogeneity parameter ([Formula: see text]) perform when the distribution of random effects departs from normality compared to normal scenarios in meta-analysis of standardized mean differences. METHODS: A Monte Carlo simulation was carried out using the R software, generating data for meta-analyses using the standardized mean difference. The simulation factors were the number and average sample size of primary studies, the amount of heterogeneity, as well as the shape of the random-effects distribution. The point estimators were compared in terms of absolute bias and variance, although results regarding mean squared error were also discussed. RESULTS: Although not all the estimators were affected to the same extent, there was a general tendency to obtain lower and more variable [Formula: see text] estimates as the random-effects distribution departed from normality. However, the estimators ranking in terms of their absolute bias and variance did not change: Those estimators that obtained lower bias also showed greater variance. Finally, a large number and sample size of primary studies acted as a bias-protective factor against a lack of normality for several procedures, whereas only a high number of studies was a variance-protective factor for most of the estimators analyzed. CONCLUSIONS: Although the estimation and inference of the combined effect have proven to be sufficiently robust, our work highlights the role that the deviation from normality may be playing in the meta-analytic conclusions from the simulation results and the numerical examples included in this work. With the aim to exercise caution in the interpretation of the results obtained from random-effects models, the tau2() R function is made available for obtaining the range of [Formula: see text] values computed from the 45 estimators analyzed in this work, as well as to assess how the pooled effect, its confidence and prediction intervals vary according to the estimator chosen.

The Fear of COVID-19 Scale: A Reliability Generalization Meta-Analysis.

A reliability generalization meta-analysis was carried out to estimate the average reliability of the seven-item, 5-point Likert-type Fear of COVID-19 Scale (FCV-19S), one of the most widespread scales developed around the COVID-19 pandemic. Different reliability coefficients from classical test theory and the Rasch Measurement Model were meta-analyzed, heterogeneity among the most reported reliability estimates was examined by searching for moderators, and a predictive model to estimate the expected reliability was proposed. At least one reliability estimate was available for a total of 44 independent samples out of 42 studies, being that Cronbach's alpha was most frequently reported. The coefficients exhibited pooled estimates ranging from .85 to .90. The moderator analyses led to a predictive model in which the standard deviation of scores explained 36.7% of the total variability among alpha coefficients. The FCV-19S has been shown to be consistently reliable regardless of the moderator variables examined.

Age and Moral Foundations: A Meta-Analytic Approach.

Several meta-analytic analyses are carried out to analyzed the relationship between age and different moral constructs based on the Moral Foundations Theory (MFT) framework. Pearson's correlation estimates between age and any of the moral construcs were available for a total of 239 independent samples out of 122 studies. Correlation coefficients were meta-analyzed, heterogeneity was examined by searching for moderators when there were more than 30 estimates available, and a predictive model to estimate the expected correlation was proposed when several moderators showed a significant effect. The correlation between age and all the moral constructs analyzed exhibited pooled estimates of null or not relevant magnitude, ranging from -.02 to .08. The moderator analyses led to a predictive model in which participant's mean age and ideology explained 40.80% of the total variability among the correlation between age and the Loyalty/Betrayal foundation, whereas participant's mean age explained a significant percentage of variability (8.85 - 25.12%) for the correlations between age and the rest of moral foundations and the Individualizing group. Results show a quite stable moral matrix over the lifespan, but future research is needed for examine a possible non-linear relationship between age and moral foundations.

Improving the reporting quality of reliability generalization meta-analyses: The REGEMA checklist.

Reliability generalization (RG) is a meta-analytic approach that aims to characterize how reliability estimates from the same test vary across different applications of the instrument. With this purpose RG meta-analyses typically focus on a particular test and intend to obtain an overall reliability of test scores and to investigate how the composition and variability of the samples affect reliability. Although several guidelines have been proposed in the meta-analytic literature to help authors improve the reporting quality of meta-analyses, none of them were devised for RG meta-analyses. The purpose of this investigation was to develop REGEMA (REliability GEneralization Meta-Analysis), a 30-item checklist (plus a flow chart) adapted to the specific issues that the reporting of an RG meta-analysis must take into account. Based on previous checklists and guidelines proposed in the meta-analytic arena, a first version was elaborated by applying the nominal group methodology. The resulting instrument was submitted to a list of independent meta-analysis experts and, after discussion, the final version of the REGEMA checklist was reached. In a pilot study, four pairs of coders applied REGEMA to a random sample of 40 RG meta-analyses in Psychology, and results showed satisfactory inter-coder reliability. REGEMA can be used by: (a) meta-analysts conducting or reporting an RG meta-analysis and aiming to improve its reporting quality; (b) consumers of RG meta-analyses who want to make informed critical appraisals of their reporting quality, and (c) reviewers and editors of journals who are considering submissions where an RG meta-analysis was reported for potential publication.