The Correlation Between Academic Media Multitasking and Achievement-a Meta-Analysis

Since the early 1990s the number of systematic reviews (SR) of animal studies has steadily increased. There is, however, little guidance on when and how to conduct a meta‐analysis of human‐health‐related animal studies. To gain insight about the methods that are currently used we created an overview of the key characteristics of published meta‐analyses of animal studies, with a focus on the choice of effect size measures. An additional goal was to learn about the rationale behind the meta‐analysis methods used by the review authors. We show that important details of the meta‐analyses are not fully described, only a fraction of all human‐health‐related meta‐analyses provided rationales for their decision to use specific effect size measures. In addition, our data may suggest that authors make post‐hoc decisions to switch to another effect size measure during the course of their meta‐analysis, and possibly search for significant effects. Based on analyses in this paper we recommend that review teams: 1) publish a review protocol before starting the conduct of a SR, prespecifying all methodological details (providing special attention to the planned meta‐analysis including the effect size measure and the rational behind choosing a specific effect size, prespecifying subgroups and restricting the number of subgroup analyses), 2) always use the Preferred Reporting Items for Systematic Review and Meta‐Analyses (PRISMA) checklist to report your SR of animal studies, and 3) use the random effects model (REM) in human‐health‐related meta‐analysis of animal studies, unless the assumptions for using the fixed effect model (FEM) are all met.

Fixed-effect versus random-effects model in meta-regression analysis

ObjectiveThis study aimed to investigate the effects of curcumin on blood lipid levels and body mass index (BMI) in patients with metabolic diseases.MethodsA systematic database search identified 587 records, from which 11 randomized controlled trials (RCTs) involving 662 participants were included. The analysis evaluated changes in triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and BMI. Both fixed-effects models (FEM) and random-effects models (REM) were used for statistical analysis. Funnel plot asymmetry tests (Begg and Egger), Baujat, and Galbraith analyses assessed heterogeneity and potential publication bias. Cochrane RevMan (version 2.0) evaluated the risk of bias.ResultsCurcumin supplementation significantly reduced TG levels [mean difference (MD): −16.76 mg/dL, REM], TC levels (MD: −10.59 mg/dL, FEM), and BMI (MD: −0.94 kg/m2 in both models). However, no significant effect was found for HDL-C and LDL-C under the random-effects model, whereas fixed-effects models showed variable results, highlighting the inconsistency and the need for further investigation. For HDL-C, the random-effects model (REM), which accounts for high heterogeneity (I2 = 83%), showed no significant change (MD: −1.90 mg/dL, p = 0.11), while the fixed-effects model (FEM) indicated a modest increase. Due to substantial between-study variability, the REM results are more reliable and suggest no consistent effect of curcumin on HDL-C levels. For LDL-C, the random-effects model (REM), which accommodates high heterogeneity (I2 = 67%), showed no significant reduction (MD: 5.01 mg/dL, p = 0.12), whereas the fixed-effects model (FEM) suggested a significant effect. Given the heterogeneity, REM is more appropriate, and the results do not support a consistent LDL-lowering effect of curcumin. Subgroup analyses suggested that study quality, regional differences, and outlier studies contributed to high heterogeneity.ConclusionCurcumin effectively reduced levels of TG, TC, and BMI in patients with metabolic diseases. However, its effects on HDL-C and LDL-C were inconsistent and non-significant under random-effects models, indicating limited efficacy for these endpoints. Providing a more detailed context for the variability in lipid outcomes enhances understanding, especially for non-expert audiences.

Oral contraceptive pretreatment significantly reduces ongoing pregnancy likelihood in gonadotropin-releasing hormone antagonist cycles: an updated meta-analysis

Contrast-induced nephropathy is one of the common causes of acute renal insufficiency after cardiovascular procedures. The objective of this paper was to analyze the published data on the usefulness of N-acetylcysteine in the prevention of contrast-induced nephropathy after these procedures. Trials were selected if they were prospective, randomized, controlled, had selected patients with impaired renal function, used low-osmolality, nonionic contrast media intra-arterially, administered a total of four doses of N-acetylcysteine in addition to intravenous saline hydration, and had contrast-induced nephropathy as their primary outcome. Contrast-induced nephropathy was defined as an increase in serum creatinine concentration by >0.5 mg/dl or a 25% increase above baseline at or within 48 h post procedure. Meta-analysis was performed using the Fisher's Combined Test with a measure of effect size. The magnitude of the N-acetylcysteine effect was estimated using random-effects models. Homogeneity was evaluated using the chi-square test of homogeneity and standard Q statistic. Reporting bias was explored by the Rosenthal method. The Fisher's Combined Test was significant at p < 0.005 in favor of N-acetylcysteine. The size of the N-acetylcysteine effect was to reduce contrast-induced nephropathy by 20%. There was a 62% relative risk reduction in contrast-induced nephropathy with N-acetylcysteine using a fixed-effects model, and a 70% relative risk reduction using the random-effects model. In addition, we found that 27 unpublished trials showing no effects of N-acetylcysteine would exist to overturn the combined significance of p < 0.005 of the five trials in our meta-analysis. Oral administration of N-acetylcysteine in addition to intravenous saline hydration has a beneficial effect in the prevention of contrast-induced nephropathy after cardiovascular procedures in patients with impaired renal function.

The objective of this study was to analyze the scientific literature in public oral health regarding calculation, presentation, and discussion of the effect size in observational studies. The scientific literature (2015 to 2019) was analyzed regarding: a) general information (journal and guidelines to authors, number of variables and outcomes), b) objective and consistency with sample calculation presentation; c) effect size (presentation, measure used and consistency with data discussion and conclusion). A total of 123 articles from 66 journals were analyzed. Most articles analyzed presented a single outcome (74%) and did not mention sample size calculation (69.9%). Among those who did, 70.3% showed consistency between sample calculation used and the objective. Only 3.3% of articles mentioned the term effect size and 24.4% did not consider that in the discussion of results, despite showing effect size calculation. Logistic regression was the most commonly used statistical methodology (98.4%) and Odds Ratio was the most commonly used effect size measure (94.3%), although it was not cited and discussed as an effect size measure in most studies (96.7%). It could be concluded that most researchers restrict the discussion of their results only to the statistical significance found in associations under study.

The objective of this study was to analyze the scientific literature in public oral health regarding calculation, presentation, and discussion of the effect size in observational studies. The scientific literature (2015 to 2019) was analyzed regarding: a) general information (journal and guidelines to authors, number of variables and outcomes), b) objective and consistency with sample calculation presentation; c) effect size (presentation, measure used and consistency with data discussion and conclusion). A total of 123 articles from 66 journals were analyzed. Most articles analyzed presented a single outcome (74%) and did not mention sample size calculation (69.9%). Among those who did, 70.3% showed consistency between sample calculation used and the objective. Only 3.3% of articles mentioned the term effect size and 24.4% did not consider that in the discussion of results, despite showing effect size calculation. Logistic regression was the most commonly used statistical methodology (98.4%) and Odds Ratio was the most commonly used effect size measure (94.3%), although it was not cited and discussed as an effect size measure in most studies (96.7%). It could be concluded that most researchers restrict the discussion of their results only to the statistical significance found in associations under study.

People with Parkinson's disease (PD) develop postural imbalance and falls. Galvanic Vestibular Stimulation (GVS) may potentially improve postural balance in humans and hence reduce falls in PD. This systematic review and meta-analysis investigate the effects of GVS on postural balance in PD.Six separate databases and research registers were searched for cross-over design trials that evaluated the effects of GVS on postural balance in PD. We used standardized mean difference (Hedges' g) as a measure of effect size in all studies.We screened 223 studies, evaluated 14, of which five qualified for the meta-analysis. Among n = 40 patients in five studies (range n = 5 to 13), using a fixed effects model we found an effect size estimate of g = 0.43 (p < 0.001, 95% CI [0.29,0.57]). However, the test for residual heterogeneity was significant (p < 0.001), thus we used a random effects model and found a pooled effect size estimate of 0.62 (p > 0.05, 95% CI [− 0.17, 1.41], I2 = 96.21%). Egger's test was not significant and thus trim and funnel plot indicated no bias. To reduce heterogeneity, we performed sensitivity analysis and by removing one outlier study (n = 7 patients), we found an effect size estimate of 0.16 (p < 0.05, 95% CI [0.01, 0.31], I2 = 0%).Our meta-analysis found GVS has a favourable effect on postural balance in PD patients, but due to limited literature and inconsistent methodologies, this favourable effect must be interpreted with caution.

Consider a two-way ANOVA design. Generally, interactions are characterized by the difference between two measures of effect size. Typically the measure of effect size is based on the difference between measures of location, with the difference between means being the most common choice. This paper deals with extending extant results to two robust, heteroscedastic measures of effect size. The first is a robust, heteroscedastic analogue of Cohen's d. The second characterizes effect size in terms of the quantiles of the null distribution. Simulation results indicate that a percentile bootstrap method yields reasonably accurate confidence intervals. Data from an actual study are used to illustrate how these measures of effect size can add perspective when comparing groups.

It is shown how the difference between the success rates in two treatment groups is related to the treatment-outcome correlation and the overall success rate. A new measure of effect size is proposed, which is easily calculated and readily interpretable in terms of the ratio of success rates in the treatment groups.

This meta-analysis aimed to evaluate the inclusion of pellet binders on pellet quality and broiler performance, including growth metrics and organ development. A total of 130 data points acquired from 21 published articles were used as a database for determining the effectiveness of pellet binders on pellet quality, performance, and health of broilers. The Hedges’d value was employed as a measure of effect size (ES) in the present meta-analysis. The data were analyzed using a random effects model in OpenMEE software. The addition of pellet binders significantly increased the pellet durability index (PDI), pellet hardness, and moisture content (p&lt;0.05). However, the meta-analysis results suggest that broiler performance, including feed intake, body weight, and FCR, as well as broiler carcass yield, including total carcass, breast, and thighs, were not impacted (p&gt;0.05). In addition, pellet binders did not significantly affect (p&gt;0.05) the relative organ weights, including the gizzard, heart, duodenum, jejunum, and ileum. However, liver weight was significantly different (P&lt;0.01). The meta-analysis showed that pellet binders improved feed quality metrics such as pellet durability, hardness, and moisture, but did not impact broiler performance metrics, including feed intake, body weight, FCR, carcass yield, or other organ weights. Overall, pellet binders did not enhance efficiency in broiler production.

The relationship between students' smartphone addiction, social media use, video games play, and their academic performance has been widely studied, yet the existing literature presents inconsistent findings. This meta-analysis synthesizes current research to provide a comprehensive examination of the impact of these technologies on academic achievement. A total of 63 studies (yielding 64 effect sizes) were included, encompassing a sample of 124,166 students from 28 countries. The meta-analysis utilized correlation coefficients and sample sizes, reporting results based on the random effects model. Key statistics such as the Fisher's Z value, confidence intervals, and heterogeneity (Q) test results were considered, and publication bias was assessed using Begg and Mazumdar's rank correlation test, with the Kendall Tau coefficient determining bias significance. The meta-analysis revealed a small but statistically significant negative association between smartphone use, social media use, video game playing, and students' academic performance [Q(64) = 2501.93, p < 0.001, d = -0.085]. It is concluded that increased use of these technologies was associated with poorer academic outcomes, potentially impacting key cognitive skills essential for academic success. The implications for educational psychology research and future research directions are discussed.

Importance of Effect Sizes for the Accumulation of Knowledge

A recent trend in the psychological literature has been to include measures of effect size when reporting probability values. The several measures of effect size associated with the Student t test for two independent samples are appropriate only when the variances are homogeneous. In this paper, commonly used measures of effect size are considered and compared, using four data sets. A chance-corrected measure of effect size is provided for two or more treatment groups characterized by either homogeneous or heterogeneous variances.

PURPOSE: The decline of cardiovascular fitness (CRF) in adolescents has become a major concern. Efforts have been to improve adolescents’ CRF through exercise interventions, but the dose response of the interventions has not been summarized. This study was to determine the exercise dose response needed for increasing CRF in adolescents (12-19 yr. old). METHODS: Google scholar, Web of Science, PsycINFO, Scopus, SPORTDiscus, and Cochrane databases were searched. In addition, the listed studies’ methodological quality was assessed. The standardized mean differences and 95 % confidence intervals (95 % CIs) were calculated as the effect size measures (ES). RESULTS: The search yielded 50 studies, a total of 15 studies were included in the review. Most of the included studies employed a randomized control trial study design (12/15, 67%). Samples sizes ranged from 20 to 60. Intervention length ranged from 6-60 weeks. The major indicator of CRF was VO2max, measured by laps (20-m shuttle run) or minutes (1-mile run). Aerobic exercise was utilized in most of the interventions (73%), followed by resistance training (20%), and a combination of aerobic and resistance training (6.7%). Interventions with intensity of “>60% maximal heart rate (HRmax)” were found statistically significant for improving CRF (ES =0.87, 95% CI 0.23 to 1.11, p=0.04). Frequency of “3 times weekly” was found to be statistically significant for improving CRF (ES =1.07, 95% CI 0.37 to 1.77, p=0.003). Duration of an intervention that was “10-15 weeks” yielded statistically significance in improving CRF (ES =1.02, 95% CI 0.27 to 1.27, p=0.002). The effects of CRF interventions were moderate to significant (ES = 0.59, 95 % CI 0.55-0.88), with high heterogeneity (I 2 = 94 %). There was no sex difference (p=0.07) in terms of the interventions. CONCLUSIONS: Exercise interventions achieving at least 60% of HRmax, meeting 3 times weekly for 10-15 weeks seem to have a positive effect on CRF among adolescents, but there is a high heterogeneity among those studies.