scholarly journals Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 407 ◽  
Author(s):  
Michael Duggan ◽  
Patrizio Tressoldi
Keyword(s):  
Confidence Intervals ◽  
Publication Bias ◽  
Effect Size ◽  
Statistical Estimation ◽  
Meta Analysis ◽  
Weighted Mean ◽  
Weighted Effect Size ◽  
Credible Intervals ◽  
Weighted Effect ◽  
Anticipatory Activity

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29 Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes. Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non-peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non-Peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41. The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias. Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.

scholarly journals Predictive physiological anticipation preceding seemingly unpredictable stimuli: an update of Mossbridge’s et al. meta-analysis

2018 ◽  
Author(s):  
Michael Duggan ◽  
Patrizio Tressoldi
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Bayesian Model ◽  
Statistical Estimation ◽  
Meta Analysis ◽  
Random Model ◽  
Weighted Mean ◽  
Weighted Effect Size ◽  
Credible Intervals ◽  
Weighted Effect

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes.Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41.The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias.Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.

scholarly journals Predictive physiological anticipation preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 407
Author(s):  
Michael Duggan ◽  
Patrizio Tressoldi
Keyword(s):  
Confidence Intervals ◽  
Publication Bias ◽  
Effect Size ◽  
Statistical Estimation ◽  
Meta Analysis ◽  
Random Model ◽  
Effect Sizes ◽  
Weighted Effect Size ◽  
Credible Intervals ◽  
Weighted Effect

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli. The overall effect size observed was 0.21; 95% Confidence Intervals: 0.13 - 0.29 Methods: Eighteen new peer and non-peer reviewed studies completed from January 2008 to October 2017 were retrieved describing a total of 26 experiments and 34 associated effect sizes. Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.29; 95% Confidence Intervals: 0.19-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.29; 95% Credible Intervals: 0.18-0.39. Effect sizes of peer reviewed studies were slightly higher: 0.38; Confidence Intervals: 0.27-0.48 than non-peer reviewed articles: 0.22; Confidence Intervals: 0.05-0.39. The statistical estimation of the publication bias by using the Copas model suggest that the main findings are not contaminated by publication bias. Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.

Promoting Treatment Credibility

2019 ◽  
pp. 495-521
Author(s):  
Michael J. Constantino ◽  
Alice E. Coyne ◽  
James F. Boswell ◽  
Brittany R. Iles ◽  
Andreea Vîslă
Keyword(s):  
Clinical Outcome ◽  
Systematic Reviews ◽  
Effect Size ◽  
Meta Analysis ◽  
Common Factor ◽  
Therapy Outcome ◽  
Patient Factors ◽  
Weighted Effect Size ◽  
Weighted Effect ◽  
Treatment Credibility

Patients’ perception of treatment credibility represents their belief about a treatment’s personal logicality, suitability, and efficaciousness. Although long considered an important common factor bearing on clinical outcome, there have been no systematic reviews of the credibility–outcome association. In this chapter, the authors first discuss the definitions of credibility and similar constructs, common measures of credibility, clinical examples of treatment credibility perception, and several landmark studies. The chapter then presents a meta-analysis of the association between patients’ credibility perception and their posttreatment outcomes. The meta-analysis was conducted on 24 independent samples with 1,504 patients. The overall weighted effect size was r = .12, or d = .24. Next, the authors present moderators and mediators of the treatment credibility–outcome link (the former in the context of the meta-analysis), evidence supporting causality in the association, patient factors contributing to their treatment credibility perception, and limitations of the research base. Finally, the chapter reviews diversity considerations, training implications, and therapeutic practices with regard to patient-perceived treatment credibility and its association with therapy outcome.

Cultivating Positive Outcome Expectation

2019 ◽  
pp. 461-494 ◽  
Author(s):  
Michael J. Constantino ◽  
Andreea Vîslă ◽  
Alice E. Coyne ◽  
James F. Boswell
Keyword(s):  
Mental Health ◽  
Effect Size ◽  
Meta Analysis ◽  
Positive Outcome ◽  
Outcome Expectation ◽  
Therapy Outcome ◽  
Health Consequences ◽  
Patient Factors ◽  
Weighted Effect Size ◽  
Weighted Effect

Patients’ outcome expectation (OE) represents their belief about the mental health consequences of participating in psychotherapy. In this chapter, the authors first discuss the definitions of OE and similar constructs, common OE measures, clinical examples of OE, several landmark studies, and results of a previous meta-analysis of the OE-outcome association. The chapter then presents an updated meta-analysis of 81 independent samples with 12,722 patients. The overall weighted effect size was r = .18, or d = .36. Next, the authors present moderators and mediators of the OE–outcome link (the former in the context of the meta-analysis), evidence supporting causality in the association, patient factors related to OE, and limitations of the research base. Finally, the chapter reviews diversity considerations, training implications, and therapeutic practices with regard to OE and its robust association with therapy outcome.

Appraising Research Reports

2016 ◽  
pp. 137-162
Author(s):  
John C. Norcross ◽  
Thomas P. Hogan ◽  
Gerald P. Koocher ◽  
Lauren A. Maggio
Keyword(s):  
Confidence Intervals ◽  
Publication Bias ◽  
Effect Size ◽  
Critical Appraisal ◽  
Meta Analysis ◽  
Flow Diagram ◽  
Careful Attention ◽  
Comparison Groups ◽  
Independent Variable ◽  
Meta Analyses

Assessing and interpreting research reports involves examination of individual studies as well as summaries of many studies. Summaries may be conveyed in narrative reviews or, more typically, in meta-analyses. This chapter reviews how researchers conduct a meta-analysis and report the results, especially by means of forest plots, which incorporate measures of effect size and their confidence intervals. A meta-analysis may also use moderator analyses or meta-regressions to identify important influences on the results. Critical appraisal of a study requires careful attention to the details of the sample used, the independent variable (treatment), dependent variable (outcome measure), the comparison groups, and the relation between the stated conclusions and the actual results. The CONSORT flow diagram provides a context for interpreting the sample and comparison groups. Finally, users must be alert to possible artifacts of publication bias.

The Relationship Between Immorality and Cleansing

2018 ◽  
Vol 49 (5) ◽  
pp. 303-309 ◽  
Author(s):  
Jedidiah Siev ◽  
Shelby E. Zuckerman ◽  
Joseph J. Siev
Keyword(s):  
Effect Size ◽  
Meta Analysis ◽  
Weighted Mean ◽  
The Relationship

Abstract. In a widely publicized set of studies, participants who were primed to consider unethical events preferred cleansing products more than did those primed with ethical events ( Zhong & Liljenquist, 2006 ). This tendency to respond to moral threat with physical cleansing is known as the Macbeth Effect. Several subsequent efforts, however, did not replicate this relationship. The present manuscript reports the results of a meta-analysis of 15 studies testing this relationship. The weighted mean effect size was small across all studies (g = 0.17, 95% CI [0.04, 0.31]), and nonsignificant across studies conducted in independent laboratories (g = 0.07, 95% CI [−0.04, 0.19]). We conclude that there is little evidence for an overall Macbeth Effect; however, there may be a Macbeth Effect under certain conditions.

Abstract 3789: Nessun Dorma : Have the Risks of Rosiglitazone been Exaggerated?

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
George A Diamond ◽  
Sanjay Kaul
Keyword(s):  
Confidence Intervals ◽  
Effect Size ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Cardiovascular Death ◽  
Sensitivity Analyses ◽  
Odds Ratios ◽  
True Effect Size ◽  
Index Study ◽  
The Stability

Background A highly publicized meta-analysis of 42 clinical trials comprising 27,844 diabetics ignited a firestorm of controversy by charging that treatment with rosiglitazone was associated with a “…worrisome…” 43% greater risk of myocardial infarction ( p =0.03) and a 64% greater risk of cardiovascular death ( p =0.06). Objective The investigators excluded 4 trials from the infarction analysis and 19 trials from the mortality analysis in which no events were observed. We sought to determine if these exclusions biased the results. Methods We compared the index study to a Bayesian meta-analysis of the entire 42 trials (using odds ratio as the measure of effect size) and to fixed-effects and random-effects analyses with and without a continuity correction that adjusts for values of zero. Results The odds ratios and confidence intervals for the analyses are summarized in the Table . Odds ratios for infarction ranged from 1.43 to 1.22 and for death from 1.64 to 1.13. Corrected models resulted in substantially smaller odds ratios and narrower confidence intervals than did uncorrected models. Although corrected risks remain elevated, none are statistically significant (*p<0.05). Conclusions Given the fragility of the effect sizes and confidence intervals, the charge that roziglitazone increases the risk of adverse events is not supported by these additional analyses. The exaggerated values observed in the index study are likely the result of excluding the zero-event trials from analysis. Continuity adjustments mitigate this error and provide more consistent and reliable assessments of true effect size. Transparent sensitivity analyses should therefore be performed over a realistic range of the operative assumptions to verify the stability of such assessments especially when outcome events are rare. Given the relatively wide confidence intervals, additional data will be required to adjudicate these inconclusive results.

scholarly journals A Statistical Method for Synthesizing Meta-Analyses

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman
Keyword(s):  
Statistical Method ◽  
Effect Size ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Weighted Mean ◽  
Summary Effect ◽  
Different Types ◽  
Meta Analyses ◽  
Size Estimates ◽  
Similar Search

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.

scholarly journals Influence of Mindfulness and Relaxation on Treatment of Essential Hypertension: Meta-Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Fushun Zhang ◽  
Yuanyuan Zhang ◽  
Nan Jiang ◽  
Qiao Zhai ◽  
Juanjuan Hu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Essential Hypertension ◽  
Systolic Blood Pressure ◽  
Publication Bias ◽  
Effect Size ◽  
Meta Analysis ◽  
Biomedical Literature ◽  
Cochrane Library ◽  
Control Group ◽  
Effect Model

Background. Some studies published previously have shown a strong correlation between hypertension and psychological nature including impulsion emotion or mindfulness and relaxation temperament, among which mindfulness and relaxation temperament might have a benign influence on blood pressure, ameliorating the hypertension. However, the conclusion was not confirmed. Objective. The meta-analysis was performed to investigate the influence of mindfulness and relaxation on essential hypertension interventions and confirm the effects. Methods. Systematic searches were conducted in common English and Chinese electronic databases (i.e., PubMed/MEDLINE, EMBASE, Web of Science, CINAHL, PsycINFO, Cochrane Library, and Chinese Biomedical Literature Database) from 1980 to 2020. A meta-analysis including 5 studies was performed using Rev Man 5.4.1 software to estimate the influence of mindfulness and relaxation on blood pressure, ameliorating the hypertension. Publication bias and heterogeneity of samples were tested using a funnel plot. Studies were analyzed using either a random-effect model or a fixed-effect model. Results. All the 5 studies investigated the influence of mindfulness and relaxation on diastolic and systolic blood pressure, with total 205 participants in the control group and 204 in the intervention group. The random-effects model (REM) was used to calculate the pooled effect for mindfulness and relaxation on diastolic blood pressure (I2 = 0%, t2 = 0.000, P = 0.41 ). The random pooled effect size (MD) was 0.30 (95% CI = −0.81–1.42, P = 0.59 ). REM was used to calculate the pooled effect for mindfulness and relaxation on systolic blood pressure (I2 = 49%, t2 = 3.05, P = 0.10 ). The random pooled effect size (MD) was −1.05 (95% CI = −3.29–1.18, P = 0.36 ). The results of this meta-analysis were influenced by publication bias to some degree. Conclusion. All the results showed less influence of mindfulness and relaxation might act on diastolic or systolic blood pressure, when mindfulness and relaxation are used to intervene in treating CVD and hypertension.

Stage 1 Registered Report: Stress regulation via being in nature and social support in adults - a meta-analysis

2021 ◽  
Author(s):  
Alessandro Sparacio ◽  
Ivan Ropovik ◽  
Gabriela M. Jiga-Boy ◽  
Hans IJzerman
Keyword(s):  
Social Support ◽  
Publication Bias ◽  
Effect Size ◽  
Meta Analysis ◽  
Multilevel Regression ◽  
Stress Regulation ◽  
Analysis Workflow ◽  
Affective Consequences ◽  
Emotional Social Support ◽  
Stage 1

This meta-analysis explored whether being in nature and emotional social support are effective in reducing levels of stress through a Registered Report. We retrieved all the relevant articles that investigated a connection between one of these two strategies and various components of stress (physiological, affective and cognitive) as well as affective consequences of stress. We followed a stringent analysis workflow (including permutation-based selection models and multilevel regression-based models) to provide publication bias-corrected estimates. We found [no evidence for the efficacy of either strategy/evidence for one of the two strategies/evidence for both strategies] with an estimated mean effect size of [xx/xx] and we recommend [recommendation will be provided if necessary].

Sign in / Sign up

Export Citation Format

Share Document