Meta-analysis Method Research Articles

Analyzing Treatment Effect by Integrating Existing Propensity Score and Outcome Regressions with Heterogeneous Covariate Sets

Analyzing treatment or exposure effect is a major research theme in scientific studies. In the current big-data era where multiple sources of data are available, it is of interest to perform a synthesized analysis of treatment effects by integrating information from different data sources or studies. However, studies may contain heterogeneous and incomplete covariate sets, and individual data therein may not be accessible. We apply and extend the generalized meta-analysis method to integrate summary results (e.g., regression coefficients) of outcome and treatment (propensity score, PS) regression analyses across different datasets that may contain heterogeneous covariate sets. The proposed integrated analysis utilizes a reference dataset, which contains data on the complete set of covariates. The asymptotic distribution for the proposed integrated estimator is established. Simulations reveal that the proposed estimator performs well. We apply the proposed method to obtain the causal effect of waist circumference on hypertension by integrating two existing outcomes and PS regression analyses with different sets of covariates.

Methods for multiancestry genome-wide association study meta-analysis.

Genome-wide association studies (GWAS) have significantly enhanced our understanding of the genetic basis of complex diseases. Despite the technological advancements, gaps in our understanding remain, partly due to small effect sizes and inadequate coverage of genetic variation. Multiancestry GWAS meta-analysis (MAGMA) addresses these challenges by integrating genetic data from diverse populations, thereby increasing power to detect loci and improving fine-mapping resolution to identify causal variants across different ancestry groups. This review provides an overview of the protocols, statistical methods, and software of MAGMA, as well as highlighting some challenges associated with this approach.

Meta-Analysis Study: Expectations of 21st Century Teaching from Pre-Service Teacher Education Programs

This study aims to investigate the expectations of 21st-century teaching from pre-service teacher education programs and to analyze the contemporary status of pre-service teacher education programs in developing 21st-century teaching skills among prospective teachers. The meta-analysis method was used to analyze previously conducted studies in the context of 21st-century teaching. The findings reveal that, to some extent, pre-service teacher education programs contribute to developing the 21st-century teaching skills by imparting theoretical knowledge, but there is a gap in the application of theory and pedagogical practices. Consequently, there is a pressing need to reconsider the pre-service teacher education programs to inculcate the essential teaching skills for 21st-century, such as collaborative learning, reflective thinking, social and emotional competencies, adaptive skills, communication skills, creativity and entrepreneurship skills, critical thinking, problem-solving skills, and ICT skills for teaching and social networking.

Short-term pain for long-term gain? A longitudinal meta-analysis of downsizing-financial performance relationships

IntroductionDownsizing, and the mass layoff upheavals that ensue, has been euphemistically referred to as a short-term pain, long-term gain strategy. But is that so? Do its financial outcomes over time justify the short-run harm? And, to what extent has its adoption been driven by economic or social rationales over time?MethodsTo examine these questions, we conducted the most comprehensive meta-analysis on downsizing-financial performance relationships to date, summarizing a total of 905 effect sizes. Using a new meta-analytic method multi-level longitudinal meta-analysis (MLLMA) we analyze temporal dimensions of these relationships.ResultsResults for downsizing adoption suggest shifting rationales over time, from a defensive response to decline in the 1980s, to a socially legitimate management convention in the 1990s, and back to a defensive response in the 2000s. Short-run market outcomes mirror these shifting rationales, with more negative reactions to defensive downsizing. Across a diverse range of lead/lag times and moderators, we find many negative and heterogeneous performance outcomes. Most importantly, little long-term gain is found.DiscussionOur MLLMA helps to address prior criticisms on the lack of temporality in extant downsizing research, while many equivocal relationships, despite almost 40 years of downsizing research, illustrate that considerable avenues for future research remain.

The effectiveness of faculty development programs for training university professors in the health area: a systematic review and meta-analysis

SummaryBackgroundThe growing discussion on teacher development focuses on diversified educational skills that promote knowledge and innovation in the teaching, learning and assessment process. With the Covid-19 scenario, this picture of necessary changes has become more evident, demonstrating the need for professional preparation to work in teacher development. The aim of the study was to analyze the effectiveness of teacher development programs for the training of university teachers in the health area, through a systematic review and meta-analysis.MethodsThe systematic review and meta-analysis were carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and involved searching five databases - PubMed-Medline, Education Resource Information Center (ERIC), SCOPUS, Embase and Web of Science. The review included randomized clinical trials and cohort studies that addressed the effectiveness of teaching professionalization in the health area for university professors. The quality of the selected studies was assessed based on the evaluation criteria of the Joanna Briggs Institute tool. The random effects meta-analysis method was used to explain the distribution of effects between the studies, using Stata® software (version 11.0) and publication bias was examined by visual inspection of the graphs and Egger's test.ResultsWe included 12 studies in the systematic review and 8 in the meta-analysis. These studies were published between 1984 and 2022 in 14 countries. Significant changes were reported in teachers' behavior to stimulate and encourage students, improvement in the quality of teaching and teaching staff, as well as improvement in skills such as leadership and self-evaluation. Furthermore, the result of the meta-analysis showed that there is evidence of the effectiveness of the positive effects of teacher development programs after their implementation, with this effect being 1.70% and an increase of 4.75 in the effect of these teacher development programs.ConclusionOur study shows that development programs have been implemented in different countries and contexts, all of which have proven to be effective in the short, medium and long term. We recommend that future research focus specifically on the different competencies that have been acquired following the implementation of these programs.

Estimating Effect Sizes, Heterogeneity Parameters and Weighted Standard Deviation (WSD) of Postgraduate Theses using Meta-Analytic and Systematic Review Methods

Estimating Effect Sizes, Heterogeneity Parameters and Weighted Standard Deviation (WSD) of Postgraduate Theses using Meta-Analytic and Systematic Review Methods

Multicenter proteome-wide Mendelian randomization study identifies causal plasma proteins in melanoma and non-melanoma skin cancers

This study addresses the diagnostic and therapeutic challenges in malignant melanoma (MM) and non-melanoma skin cancers (NMSC). We aim to identify circulating proteins causally linked to MM and NMSC traits using a multicenter Mendelian randomization (MR) framework. We utilized large-scale cis-MR to estimate the impact of numerous plasma proteins on MM, NMSC, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC). To ensure robustness, additional analyses like MR Steiger and Bayesian colocalization are conducted, followed by replication through meta-analytical methods. The associations between identified proteins and outcomes are also validated at the tissue level using Transcriptome-Wide Association Study methods. Furthermore, a protein-protein interaction analysis is conducted to explore the relationship between identified proteins and existing cancer medication targets. The MR analysis has identified associations of 13 plasma proteins with BCC, 2 with SCC, and 1 with MM. Specifically, ASIP and KRT5 are associated with BCC, with ASIP also potentially targeting MM. CTSS and TNFSF8 are identified as promising druggability candidates for BCC. This multidimensional approach nominates ASIP, KRT5, CTSS, and TNFSF8 as potential diagnostic and therapeutic targets for skin cancers.

Gender effects and firm financial performance: A SUMAD meta-analysis of social responsibility and family-to-work conflict

The current study uses SUMAD meta-analytic methods (Oh, 2020) to examine gender differences in social responsibility and family-to-work conflict. Synthesizing evidence from across social science literature, the results of this study provide an evidence-based foundation to support more theorizing and practical discourse regarding gender effects in entrepreneurship. As explained by theories of socialization and social roles, gender differences in (a) socially responsible attitudes and behaviors and (b) the balance between family and work responsibilities, are likely two of the more pervasive gender effects that influence entrepreneurial careers. The goal of this study is to motivate more research and practical discussion on these and related gender effects to improve our understanding of entrepreneurship phenomena. Using firm performance as an example, the results of the SUMAD meta-analysis suggest that gender effects related to social responsibility and family-to-work conflict have significant consequences for entrepreneurship outcomes. Based on the evidence and theory rooted in socialization and social roles, the current study calls for more theorizing and primary-level studies on these and related gender effects in entrepreneurship research.Comment to Readers:Does gender matter? Of course it does (depending on the issue). A simple search of “does gender matter” reveals ample discussion on this topic across a variety of gender issues. In this article I highlight gender regarding differences between women and men in social responsibility and family-to-work conflict. As the evidence suggests, gender does indeed matter as women – on average – are more socially responsible and have more family-to-work conflict than their men counterparts. The results of this study show that greater social responsibility is tied to better business performance whereas greater family-to-work conflict is tied to worse business performance. So, what should we do? First, acknowledge the fact that women and men are different in the contexts of social issues and family matters to clear the way for constructive discourse about these gender differences. Second, embrace that women are higher than men in socially responsible attitudes and behaviors, and that more women in business could inherently result in more socially responsible business practices. Moreover, while this is a societal win in and of itself, the results suggest it could also carry over to improved financial and economic performance. Lastly, focus more on “why” there are differences between women and men regarding family-to-work conflict. Specifically, emphasize both societal-driven influences (e.g., stereotypes; biases) and individual-driven influences (e.g., individual differences; personal preferences). Understanding these influences, which are not mutually exclusive, is key for maximizing the personal and professional well-being of both women and men.

Importance of Competitive Dynamics of Strategic Groups: Opportunities and Challenges

The competitive dynamics of strategic groups perform a major role in shaping the competitive background of industries. Strategic groups are sets of companies within an industry that follow related strategies or have comparable characteristics, such as product offerings, target markets, or geographic scale. Understanding these dynamics is central for firms to spot opportunities and cope with challenges effectively. This paper reviews the literature on the competitive dynamics of strategic groups. It analyses the theoretical underpinnings of competitive dynamics of strategic groups and discusses the central dimensions of the concept, underscoring the importance of competitive dynamics for strategic groups. Our aim is to sum up these perspectives while providing a clear and integrated overview through a systematic literature review. Such systematic literature review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. PRISMA is a framework with evidence-based data designed to help authors carry out a systematic literature review. This systematic literature review sought to consolidate knowledge on this topic. A discussion on the theme is carried out, an ensuing conclusion came up and, finally, avenues for further research are recommended.

The effect of psychotherapeutic interventions on posttraumatic stress disorder symptoms, depression and self-esteem in women exposed to violence: a systematic review and meta-analysis

This study aimed to reveal the level of effect of psychotherapeutic interventions on post-traumatic stress disorder symptoms, depression, and self-esteem in women who had been exposed to violence. For this systematic review and meta-analysis study, PubMed, Web of Science, EBSCOhost, Google Scholar, and YÖK Thesis Center databases were searched without any year limitation in August-December 2022, and 28 studies were included. The data were synthesized using meta-analysis and narrative methods. This systematic review and meta-analysis found that psychotherapeutic interventions for women exposed to violence were effective on post-traumatic stress disorder symptoms in individuals (SMD: -0,590, %95 CI: -0,893- 0.196; Z= -2,937, p = 0.003, I2= %93,59). Psychotherapeutic interventions had a significant effect on women’s depression levels in favor of the intervention group, and there was high heterogeneity between the studies (SMD: -0,475, %95 CI: -0,838- 0.113; Z= -2,569, p = 0.010, I2= %90,68). Subgroup analyses showed that cognitive behavioral therapy was effective in the treatment of intimate partner violence. It was also found that psychotherapeutic interventions did not affect women’s self-esteem levels. Psychotherapeutic therapies for women who have experienced violence have a favorable impact on them and improve their mental health.

Meta-analysis of the Turkish energy and climate pathways to achieve the net-zero emission target

The national energy and climate pathways are gaining importance to achieve the global net-zero emissions target. We surveyed the literature on energy and climate pathways for Turkey, with a 1 % share in global emissions with a historical increase of 118 % from 1990 to 2015. We used the meta-analysis method to compare the national and inter-regional energy and climate pathways. The finding reveals that the CO2 emissions are higher in national energy and climate pathways for 2050. The national energy and climate pathways are medium-sighted, with only three scenarios for having a time horizon of 2050. We recommend further research by considering the small study effect and the interoperability of the meta-analysis tools.

What factors affect teacher professional learning: a qualitative meta-analysis based on the Onion model

Purpose Current academic research on teacher learning is increasing in number and deepening in quality, but at the same time, the heterogeneity is growing significantly. Similar work is challenging to cross-check regarding conclusions due to the different research foci. This paper aims to provide a reliable theoretical framework and offers solid insights based on the existing research. Design/methodology/approach Based on the Onion model, 67 core literature in English and Chinese were coded through qualitative meta-analysis methods to explore environmental, behavioral, competence, belief, identity, mission and other factors that may impact teacher learning. Findings It was found that the quantitative structure of the current relevant studies was in an inverted triangular shape with three levels of steps, respectively, which can be summarized as structural environment, core behaviors and dominant mission. The heterogeneity between the findings mainly originated from two situations, oppositional and complementary and some structural adjustments were made to the Onion model according to the coding results to better represent the interaction of influences between the levels. It also analyzes current research trends and the centrality of learned behaviors based on the coding results. Social implications The design of teacher learning activities should combine theoretical, practical and inquiry learning to ensure that teachers are kept fresh and motivated by sustained and varied stimuli. Originality/value To the best of the authors’ knowledge, this study is the first to analyze teacher learning influences through qualitative meta-analysis and create node saturation to analyze the results, resulting in highly credible and valuable research findings.

A Proposed Concept for Developing School Administration in Light of Edward Deming's Quality Standards

The aim of this study was to present a proposed framework for the development and improvement of educational administration in light of the quality standards set by Edward Deming as a measure of quality. This is intended to enhance the educational level and work towards performance improvement by providing a set of strategies related to processes and organizational structures that lead to continuous improvement within educational institutions. This study relied on a descriptive approach through the presentation and analysis of concepts and key elements addressed in the analytical meta-analysis method. Finally, the researcher recommends the adoption of total quality management by educational institutions and emphasizes the support of administrative leadership for this philosophy, in order to create a new organizational culture based on standards that measure educational quality in various domains.

Effect of Wearable Technology on Metabolic Control and the Quality of Life in Children and Adolescents with Type 1 Diabetes: A Systematic Review and Meta-Analysis

Type 1 diabetes is one of the most common chronic diseases in children. Wearable technology (insulin pumps and continuous glucose monitoring devices) that makes diabetes management relatively simple, in addition to education and follow-ups, enhances the quality of life and health of individuals with diabetes. To evaluate the impact of wearable technology on metabolic management and the quality of life in children and adolescents with type 1 diabetes. Systematic review and meta-analysis. The Preferred Reporting System for Systematic Reviews and Meta-Analyses was used to conduct a systematic review and meta-analysis. PubMed, Web of Science, MEDLINE, Cochrane Library, EBSCO, Ulakbim and Google Scholar were searched in July 2022 and July 2023 using predetermined keywords. The methodological quality of the studies was evaluated using the Joanna Briggs Institute’s Critical Appraisal Checklists for randomized controlled experimental and cross-sectional studies. The meta-analysis method was used to pool the data. Eleven studies published between 2011 and 2022 were included. The total sample size of the included studies was 1,853. The meta-analysis revealed that the decrease in hemoglobin A1C (HbA1c) level in those using wearable technology was statistically significant [mean difference (MD): -0.33, Z = 2.54, p = 0.01]. However, the technology had no effect on the quality of life [standardized mean difference (SMD): 0.44, Z = 1.72, p = 0.09]. The subgroup analyses revealed that the decrease in the HbA1c level occurred in the cross-sectional studies (MD: -0.49, Z = 2.54, p = 0.01) and the 12-19 (MD = 0.59, Z = 4.40, p < 0.001) and 4-18 age groups (MD: -0.31, Z = 2.56, p = 0.01). The subgroup analyses regarding the quality of life revealed that there was no difference according to the research design. However, the quality of life was higher in the wearable technology group than in the control group in the 8-12 and 4-18 age groups (SMD: 1.32, Z = 2.31, p = 0.02 and SMD: 1.00, Z = 5.76, p < 0.001, respectively). Wearable technology effectively reduces the HbA1c levels in children and adolescents with type 1 diabetes in some age groups. However, it does not affect the quality of life.

Methods of diagnostic meta-analysis: comparing the generalized linear mixed model and the split component synthesis model

Purpose of review Diagnostic meta-analyses combine data from several diagnostic test accuracy (DTA) studies to provide an in-depth assessment of a specific diagnostic test's performance across diverse populations and settings. Additionally, knowledge on common methods of diagnostic meta-analyses is crucial for researchers to make informed decisions on best practice for reporting analyses and results. This article provides an overview of commonly used methods of diagnostic meta-analyses using real-life and simulation data. Recent findings Advances in methods of diagnostic meta-analyses in recent years have increased uncertainty among researchers in relation to the most suitable method to be used. Currently, the most popular approaches for diagnostic evidence synthesis include hierarchical summary operating characteristic (HSROC) and bivariate random effects models though other methods such as the split component synthesis method have been proposed. In addition, different software modules exist for DTA meta-analyses. Summary This article presents a thorough evaluation of current frequentist DTA meta-analysis methods implementing both simulated and real-world data. By understanding the recent methods of diagnostic meta-analyses and their limitations, clinicians may better be equipped in selecting the optimum approach to improve clinical judgement and consequently better patient outcomes.

MetaHD: A multivariate meta-analysis model for metabolomics data.

Meta-analysis methods widely-used for combining metabolomics data do not account for correlation between metabolites or missing values. Within- and between-study variability are also often overlooked. These can give results with inferior statistical properties, leading to misidentification of biomarkers. We propose a multivariate meta-analysis model for high-dimensional metabolomics data (MetaHD), which accommodates the correlation between metabolites, within- and between-study variances, and missing values. MetaHD can be used for integrating and collectively analysing individual-level metabolomics data generated from multiple studies as well as for combining summary estimates. We show that MetaHD leads to lower root mean square error compared to the existing approaches. Furthermore, we demonstrate that MetaHD, which exploits the borrowing strength between metabolites, could be particularly useful in the presence of missing data compared to univariate meta-analysis methods, which can return biased estimates in the presence of data missing at random. The MetaHD R package can be downloaded through Comprehensive R Archive Network (CRAN) repository. A detailed vignette with example datasets and code to prepare data and analyses are available on https://bookdown.org/a2delivera/MetaHD/. Supplementary data are available at Bioinformatics online.

Transdisciplinary method for exploration and visualization of neuroimaging papers and databases: Application to PTSD

A major improvement in MRI techniques has led to an exponential increase in data acquisition and, consequently, in the number of published articles reporting brain impairments and cognitive deficits underlying a disorder. Meta-analysis offers a means of synthesizing the available literature, testing existing models in the light of scientific advances, and revealing unexpected information. However, article selection, author specialization and top-down hypotheses can mask some results and introduce bias into interpretations. LinkRdata is a platform for automated, data-driven, meta-analytical methods suitable for processing large numbers of MRI articles, that can reduce selection and interpretation biases, thereby allowing scientists to review neurocognitive correlates of disorders in relation to their own corpus of articles. To validate our method, we applied it to fMRI studies of post-traumatic stress disorder. Results confirmed LinkRdata's power to uncover findings hidden by the top-down hypothesis approach.

Macronutrient Intake and Obesity In Adolescents: A Meta-Analysis Study

Obesity is a condition with excess body fat due to an imbalance in energy intake consumed more than the physical activity expended. Adolescents who are obese can increase the risk of degenerative diseases. This study aimed to determine the relationship between macronutrients, including carbohydrate, protein, and fat intake, and obesity in adolescents. This study uses a meta-analysis method. Articles were taken from Google Scholar, PubMed, and Science Direct databases. The articles analyzed were articles published from 2000 – 2022, full text; the keywords used for the search were "carbohydrate”, "protein”, "fat”, "obesity, and "adolescents”. The articles were collected using PRISMA diagram and analyzed by Review Manager Application 5.4. With the fixed effect model and random effect model. From the results of this study, seven articles were identified. The results of the forest plot show the relationship between carbohydrate intake and obesity in adolescents, p-value &lt; 0.001; OR = 2.58, protein intake with obesity in adolescents obtained p-value = 0.02; OR = 2.92, and fat intake with obesity in adolescents obtained p-value &lt; 0.001; OR = 6.20. The conclusion of this study shows that the variables of carbohydrate, protein, and fat intake have a significant relationship with obesity in adolescents.

EFEKTIVITAS MODEL EDUKASI DAN DUKUNGAN MENYUSUI UNTUK MENINGKATKAN BREASTFEEDING SELF-EFFICACY DAN PEMBERIAN ASI EKSKLUSIF: SCOPING REVIEW

WHO and UNICEF data state that the level of exclusive breastfeeding in the world is below the target of 40%. Breastfeeding self-efficacy was identified as one of the strongest modifiable predictors. This scoping review aimed to analyze the effectiveness of breastfeeding education models to increase breastfeeding self-efficacy and exclusive breastfeeding. The design of this article is a systematic review using the Preferred Reporting Items for Literature Review and Meta-Analyses (PRISMA) method. Article searches used electronic databases from Scopus, Science Direct, PubMed and Sage. The keywords in the article search are "Exclusive Breastfeeding", "Breastfeeding Education", and "Self-Efficacy". The inclusion criteria in this literature review were studies that have samples of pregnant women ≥ 30 weeks, normal pregnancies without complications. Criteria for babies to be born at term and have normal weight. The results of the scoping review show that the most effective breastfeeding education and support models are prenatal counselling, integrated breastfeeding education program and breastfeeding education with grandmothers' attention. The main characteristic is education carried out from antenatal to breastfeeding. Education is provided involving family members. Education is carried out in a multicomponent manner through breastfeeding training, home visits and post-natal telephone follow-up. The theoretical framework uses self-efficacy theory. The minimum educational frequency consists of 2-4 sessions with a minimum length of 40 minutes. It is hoped that the results of this review will serve as a guide for designing an effective exclusive breastfeeding education model by applying the five main characteristics to increase breastfeeding self-efficacy and exclusive breastfeeding.

Meta-analysis: Ethnomathematics approaches in mathematical learning in Indonesia

An introduction to ethnomathematics defines it as mathematics practiced among identified cultural groups. Ethnomathematics has a positive impact on the learning process, both as a moderate approach and as an approach to enhance numeracy literacy skills, for example. Previous researchers have conducted several studies on the ethnomathematics approach to mathematics education. However, the analysis presented has been highly varied. This study aims to determine the correlation between the ethnomathematics approach to mathematics education and students' mathematical abilities. This research utilizes a meta-analysis method, which combines multiple experimental studies that gather the effectiveness of ethnomathematics-based learning and regular learning in improving students' mathematical abilities. Relevant studies were searched through electronic resources from the National Library of Indonesia (Perpusnas) database using predetermined keywords. A total of 52 studies were obtained from the search, and eleven studies were selected based on inclusion and exclusion criteria. Meta-Mar was used to determine the combined effect size by analyzing the selected studies. This research indicates that the combined effect size of implementing ethnomathematics-based learning to enhance mathematical problem-solving abilities is 0.94, classified as a moderate effect. Therefore, it can be concluded that the ethnomathematics approach to mathematics education is related to students' mathematical abilities. Statistically, the implementation of the Ethnomathematics Approach in Mathematics Education is also influenced by study characteristics at the educational level.