Search

Abstract 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 ( $${\tau }^{2}$$ τ 2 ) 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 $${\tau }^{2}$$ τ 2 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 $${\tau }^{2}$$ τ 2 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.

This study conducted a meta-analysis to identify the primary risk and protective factors associated with the revictimization in intimate partner violence against women (IPVAW). Out of 2382 studies initially identified in eight databases, 22 studies met the inclusion criteria and provided the necessary data for calculating pooled effect sizes. The analysis focused on non-manipulative quantitative studies examining revictimization in heterosexual women of legal age. Separate statistical analyses were performed for prospective and retrospective studies, resulting in findings related to 14 variables. The Metafor package in RStudio was used with a random-effects model. The meta-analysis revealed that childhood abuse was the most strongly associated risk factor for revictimization, while belonging to a white ethnicity was the most prominent protective factor. Other significant risk factors included alcohol and drug use, recent physical violence, severity of violence, and PTSD symptomatology. The study also found that older age was a protective factor in prospective studies. The consistency of results across different study designs and sensitivity analyses further supported the robustness of the findings. It is important to note that the existing literature on revictimization in women facing intimate partner violence is limited and exhibits significant heterogeneity in terms of methodology and conceptual frameworks.

The aim of the study is to determine the association between Behavioral Lifestyles (regular physical activity, healthy diet, sleeping, and weight control) and longevity in the elderly. A search strategy was conducted in the PsycInfo, Medline, PubMed, Web of Science (WoS), and Scopus databases. The primary outcome was mortality/survival. Four variables (mean of participant's age at the baseline of the study, follow-up years of the study, gender, and year of publication) were analyzed to evaluate the role of potential moderators. Ninety-three articles, totaling more than 2,800,000 people, were included in the meta-analysis. We found that the lifestyles analyzed predict greater survival. Specifically, doing regular physical activity, engaging in leisure activities, sleeping 7–8 h a day, and staying outside the BMI ranges considered as underweight or obesity are habits that each separately has a greater probability associated with survival after a period of several years.

Copyright of Ayer: Revista de Historia Contemporánea is the property of Asociacion de Historia Contemporanea and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Signal detection theory (SDT) and two-high threshold models (2HT) are often used to analyze accuracy data in recognition memory paradigms. However, when reaction times (RTs) and/or confidence levels (CLs) are also measured, they usually are analyzed separately or not at all as dependent variables (DVs). We propose a new approach to include these variables based on multinomial processing tree models for discrete and continuous variables (MPT-DC) with the aim to compare fits of SDT and 2HT models. Using Juola et al.'s (2019, Memory & Cognition, 47[4], 855–876) data we have found that including CLs and RTs reduces the standard errors of parameter estimates and accounts for interactions among accuracy, CLs, and RTs that classical versions of SDT and 2HT models do not. In addition, according to the simulations, there is an increase in the proportion of correct model selections when relevant DV are included. We highlight the methodological and substantive advantages of MPT-DC in the disentanglement of contributing processes in recognition memory. [ABSTRACT FROM AUTHOR]

Copyright of Anales de Psicología is the property of Servicio de Publicaciones de la Universidad de Murcia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study conducted a meta-analysis to identify the primary risk and protective factors associated with the revictimization in intimate partner violence against women (IPVAW). Out of 2382 studies initially identified in eight databases, 22 studies met the inclusion criteria and provided the necessary data for calculating pooled effect sizes. The analysis focused on non-manipulative quantitative studies examining revictimization in heterosexual women of legal age. Separate statistical analyses were performed for prospective and retrospective studies, resulting in findings related to 14 variables. The Metafor package in RStudio was used with a random-effects model. The meta-analysis revealed that childhood abuse was the most strongly associated risk factor for revictimization, while belonging to a white ethnicity was the most prominent protective factor. Other significant risk factors included alcohol and drug use, recent physical violence, severity of violence, and PTSD symptomatology. The study also found that older age was a protective factor in prospective studies. The consistency of results across different study designs and sensitivity analyses further supported the robustness of the findings. It is important to note that the existing literature on revictimization in women facing intimate partner violence is limited and exhibits significant heterogeneity in terms of methodology and conceptual frameworks. [ABSTRACT FROM AUTHOR]

This article traces the presence of the concept digital semiotics in scientific literature with the aim of constituting a corpus of study that would allow to identify its goals and fields of interest. We undertook a systematic review of the term in the most important academic databases. We obtained 389 records and analyzed each of them in terms of publication date, type, content, and synthesis of contributions that develop distinct lines of investigation in digital semiotics. The results show a reduced number of first level publications that approach in detail this object of inquiry while establishing multimodal semiotics and social semiotics as the most consolidated branches. However, we found an increasing amount of gray literature that paves the way towards a deeper semiotic research tradition in the 21st century. We conclude by calling for a revision of semiotics, understood as a field of study that brings together interdisciplinary relationships and methodological solutions that interrogate the digital culture. [ABSTRACT FROM AUTHOR]

Despite the growing literature that examines the determinants of turnover intention in the public sector, little effort has been made to systematize the findings from this scholarship. To address this research gap, this study conducts the first meta‐analysis of the literature on turnover intention among public sector employees. The meta‐analysis includes 249 effect sizes from 59 studies concerning the relationship between individual demographic variables, work environment characteristics, job characteristics, HRM practices, work motivation and work attitudes, and factors related to the external environment and turnover intention. It finds that predictors related to public employees' job involvement, job exhaustion, job satisfaction, role ambiguity, affective organizational commitment, and participation in decision making are among the strongest predictors of turnover intention. In contrast, individual demographic predictors show small or negligible effects on turnover intention. [ABSTRACT FROM AUTHOR]

This is the protocol for a Campbell systematic review. The objectives are as follows: The purpose of this review is to synthesize the evidence about the efficacy of problem solving before instruction (PS‐I) to promote learning and motivation in students. Specifically, this review is designed to answer the following questions: To what degree does PS‐I affect learning and motivation, relative to alternative learning approaches? To what extent is the efficacy of PS‐I associated with the use of different design features within it, including the use of group work, contrasting cases, and metacognitive guidance in the initial problem‐solving activity, and the use of explanations that build upon students' solutions in the explicit instruction phase? To what extent is the relative efficacy of PS‐I associated with the contextual factors of activities used as control, age of students, duration of the interventions, and learning domain? What is the quality of the existent evidence to evaluate these questions in terms of number of studies included and potential biases derived from publication and methodological restrictions? [ABSTRACT FROM AUTHOR]

In many mechanical engineering undergraduate curriculums, there are topics that are vital to the students' future careers in the manufacturing and design workforce that are not taught in-depth. As one of those topics, Geometric Dimensioning and Tolerancing, or GD&T, is vital to companies who develop and manufacture products because it allows one to communicate with other team members in order to produce and inspect manufactured parts. GD&T is filled with intricate concepts that are hard to grasp without repetition and practice. An active learning intervention was developed and deployed in a mechanical engineering undergraduate class at the Georgia Institute of Technology. The active learning interventions were developed to assist students in learning basic manual inspection methods and communicating through a part drawing. The goal was for the students to obtain a foundational, hands-on understanding of GD&T and implement their learnings onto a part drawing and inspection plan. The results of this intervention were based on a Knowledge Assessment, self-reported Self-Efficacy Survey, and an Exit Survey. These assessments revealed that the GD&T intervention had a significant impact on the students' knowledgebase of the topic and their ability to perform identification and inspection tasks used in the workforce. This paper discusses the intervention structure and its potential applications for engineering education in the workforce. [ABSTRACT FROM AUTHOR]

Museums must assess visitors' experience to understand them and their needs. TripAdvisor provides an accessible source of user-generated data about the visit experience, but there is limited empirical evidence on the value of automated elaboration of this data for museum management. This paper uses topic modeling to identify the latent dimensions of the visit experience for the 30 most-visited Italian museums in 2019 using online reviews. Differences in the latent dimensions are assessed between visitors with different cultural backgrounds, as identified by whether they write in the local or non-local language. The results show that while all visitors share three cross-cultural dimensions of experience (museum cultural heritage, personal experience, and museum services), specific latent dimensions are emphasized by local (i.e., 'wow effect' and hospitality) and non-local visitors (i.e., time management and unfavorable experiences). [ABSTRACT FROM AUTHOR]

The concept of intelligence has been extensively studied, undergoing an evolution from a unitary concept to a more elaborate and complex multidimensional one. In addition, several research studies have focused their efforts for decades on the study of intelligence as a predictor of academic performance of students at different educational stages, being a stable and highly relevant predictor along with other variables such as executive functions, social context, culture or parental guardianship. Thus, the present study, based on a systematic review and meta-analysis, includes 27 studies with a total sample of 42,061 individuals. The main objective was to analyse the relationship between intelligence and academic performance using different predictive models that include moderating variables such as country of origin, type of intelligence, gender and age. The findings of this research highlight the significant, positive and moderate relationship between intelligence and academic performance (r = 0.367; p < 0.001), highlighting the predictive capacity on school performance when the type of intelligence (general and implicit; 35%) or the country of origin (45%) is taken as a moderating variable, with the explanatory models on age or sex not being significant. Therefore, it can be concluded that intelligence, in addition to being a good predictor of academic performance, is influenced depending on the type of intelligence or theoretical model taken as a reference, and also depending on the country or culture of origin. [ABSTRACT FROM AUTHOR]

Copyright of Theological Review / Bogoslovska Smotra is the property of University of Zagreb, Catholic Faculty of Theology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

The aim of the study is to determine the association between Behavioral Lifestyles (regular physical activity, healthy diet, sleeping, and weight control) and longevity in the elderly. A search strategy was conducted in the PsycInfo, Medline, PubMed, Web of Science (WoS), and Scopus databases. The primary outcome was mortality/survival. Four variables (mean of participant's age at the baseline of the study, follow-up years of the study, gender, and year of publication) were analyzed to evaluate the role of potential moderators. Ninety-three articles, totaling more than 2,800,000 people, were included in the meta-analysis. We found that the lifestyles analyzed predict greater survival. Specifically, doing regular physical activity, engaging in leisure activities, sleeping 7–8 h a day, and staying outside the BMI ranges considered as underweight or obesity are habits that each separately has a greater probability associated with survival after a period of several years. [ABSTRACT FROM AUTHOR]