Reciprocity explains food sharing in humans and other primates independent of kin selection and tolerated scrounging: a phylogenetic meta-analysis

Helping, i.e. behaviour increasing the fitness of others, can evolve when directed towards kin or reciprocating partners. These predictions have been tested in the context of food sharing both in human foragers and non-human primates. Here, we performed quantitative meta-analyses on 32 independent study populations to (i) test for overall effects of reciprocity on food sharing while controlling for alternative explanations, methodological biases, publication bias and phylogeny and (ii) compare the relative effects of reciprocity, kinship and tolerated scrounging, i.e. sharing owing to costs imposed by others. We found a significant overall weighted effect size for reciprocity of r = 0.20–0.48 for the most and least conservative measure, respectively. Effect sizes did not differ between humans and other primates, although there were species differences in in-kind reciprocity and trade. The relative effect of reciprocity in sharing was similar to those of kinship and tolerated scrounging. These results indicate a significant independent contribution of reciprocity to human and primate helping behaviour. Furthermore, similar effect sizes in humans and primates speak against cognitive constraints on reciprocity. This study is the first to use meta-analyses to quantify these effects on human helping and to directly compare humans and other primates.

Download Full-text

The relationship between intolerance of uncertainty and anxiety in autism: A systematic literature review and meta-analysis

Autism ◽

10.1177/1362361320932437 ◽

2020 ◽

Vol 24 (8) ◽

pp. 1933-1944 ◽

Cited By ~ 3

Author(s):

Richard Jenkinson ◽

Elizabeth Milne ◽

Andrew Thompson

Keyword(s):

Systematic Review ◽

Meta Analysis ◽

Intolerance Of Uncertainty ◽

Effective Interventions ◽

Limited Effectiveness ◽

Autistic People ◽

High Prevalence ◽

Weighted Effect Size ◽

Weighted Effect ◽

Meta Analyses

The association between intolerance of uncertainty and anxiety has proved robust in neurotypical populations and has led to effective interventions targeting intolerance of uncertainty. The aim of this systematic review and meta-analysis was to investigate this association in autistic people, given the high prevalence of anxiety in this population and the limited effectiveness of therapies used currently to treat anxiety in autism. A protocol was published on the Prospero database (CRD42019125315), and electronic databases were searched using terms related to intolerance of uncertainty, anxiety and autism. Included in the systematic review were 12 studies, of which 10 were included in a meta-analysis. Results showed that anxiety and intolerance of uncertainty were consistently elevated in autistic participants. Examining the correlation between these two constructs, the meta-analysis revealed a large sample-weighted effect size, r = 0.62, 95% confidence interval = [0.52, 0.71], p < 0.001. The strength of this association was comparable to meta-analyses conducted on neurotypical populations, and therefore, it was concluded intolerance of uncertainty may be an appropriate target for intervention for autistic individuals. However, conclusions were limited due to the small number of relevant studies that were available and due to issues with methodological quality. Lay abstract People who find it especially hard to cope with the unexpected or unknown are said to have an intolerance of uncertainty. Autistic individuals often report a preference for certainty and experience levels of anxiety that can interfere with their daily life. Understanding more about the link between the intolerance of uncertainty and anxiety in autistic people might lead to better treatments for anxiety being developed. Therefore, this work aimed to review previous research in order to explore this link. Twelve studies were found and their results were compared and contrasted. The autistic people who participated in the studies completed questionnaires that suggested a large number of them experienced very high levels of anxiety and intolerance of uncertainty. Of 10 studies that used relevant statistics, nine found a statistically significant link between anxiety and the intolerance of uncertainty. In general, the strength of the link was about the same as previous research found in people who did not have a diagnosis of autism. This might mean that interventions that aim to help people who are intolerant of uncertainty could be effective for autistic individuals.

Download Full-text

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

F1000Research ◽

10.12688/f1000research.14330.1 ◽

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.

Download Full-text

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

10.32942/osf.io/epqa7 ◽

2019 ◽

Author(s):

Shinichi Nakagawa ◽

Malgorzata Lagisz ◽

Rose E O'Dea ◽

Joanna Rutkowska ◽

Yefeng Yang ◽

...

Keyword(s):

Meta Analysis ◽

R Package ◽

Effect Sizes ◽

Forest Plot ◽

Point Estimates ◽

Aggregate Effect ◽

The Individual ◽

Meta Analyses ◽

Heterogeneous Effect ◽

Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

Download Full-text

Identification of and Correction for Publication Bias: Comment

10.31222/osf.io/dh87m ◽

2019 ◽

Author(s):

Amanda Kvarven ◽

Eirik Strømland ◽

Magnus Johannesson

Keyword(s):

Publication Bias ◽

False Positive ◽

Large Scale ◽

Meta Analysis ◽

False Positive Rate ◽

Effect Sizes ◽

Replication Studies ◽

Moderate Reduction ◽

Positive Rate ◽

Meta Analyses

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Download Full-text

A protocol for the systematic review and meta-analysis of thigmotactic behaviour in the open field test in rodent models associated with persistent pain

BMJ Open Science ◽

10.1136/bmjos-2020-100135 ◽

2021 ◽

Vol 5 (1) ◽

pp. e100135

Author(s):

Xue Ying Zhang ◽

Jan Vollert ◽

Emily S Sena ◽

Andrew SC Rice ◽

Nadia Soliman

Keyword(s):

Systematic Review ◽

Outcome Measure ◽

Meta Analysis ◽

Persistent Pain ◽

Effect Sizes ◽

Bias Assessment ◽

Animal Pain ◽

Trim And Fill ◽

Meta Analyses ◽

The Impact

ObjectiveThigmotaxis is an innate predator avoidance behaviour of rodents and is enhanced when animals are under stress. It is characterised by the preference of a rodent to seek shelter, rather than expose itself to the aversive open area. The behaviour has been proposed to be a measurable construct that can address the impact of pain on rodent behaviour. This systematic review will assess whether thigmotaxis can be influenced by experimental persistent pain and attenuated by pharmacological interventions in rodents.Search strategyWe will conduct search on three electronic databases to identify studies in which thigmotaxis was used as an outcome measure contextualised to a rodent model associated with persistent pain. All studies published until the date of the search will be considered.Screening and annotationTwo independent reviewers will screen studies based on the order of (1) titles and abstracts, and (2) full texts.Data management and reportingFor meta-analysis, we will extract thigmotactic behavioural data and calculate effect sizes. Effect sizes will be combined using a random-effects model. We will assess heterogeneity and identify sources of heterogeneity. A risk-of-bias assessment will be conducted to evaluate study quality. Publication bias will be assessed using funnel plots, Egger’s regression and trim-and-fill analysis. We will also extract stimulus-evoked limb withdrawal data to assess its correlation with thigmotaxis in the same animals. The evidence obtained will provide a comprehensive understanding of the strengths and limitations of using thigmotactic outcome measure in animal pain research so that future experimental designs can be optimised. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines and disseminate the review findings through publication and conference presentation.

Download Full-text

Pre-post effect sizes should be avoided in meta-analyses

Epidemiology and Psychiatric Sciences ◽

10.1017/s2045796016000809 ◽

2016 ◽

Vol 26 (4) ◽

pp. 364-368 ◽

Cited By ~ 72

Author(s):

P. Cuijpers ◽

E. Weitz ◽

I. A. Cristea ◽

J. Twisk

Keyword(s):

Comparison Group ◽

Meta Analysis ◽

Effect Sizes ◽

Behaviour Therapy ◽

Natural Processes ◽

Cognitive Behaviour ◽

Post Test ◽

The Difference ◽

Meta Analyses ◽

Highly Cited

AimsThe standardised mean difference (SMD) is one of the most used effect sizes to indicate the effects of treatments. It indicates the difference between a treatment and comparison group after treatment has ended, in terms of standard deviations. Some meta-analyses, including several highly cited and influential ones, use the pre-post SMD, indicating the difference between baseline and post-test within one (treatment group).MethodsIn this paper, we argue that these pre-post SMDs should be avoided in meta-analyses and we describe the arguments why pre-post SMDs can result in biased outcomes.ResultsOne important reason why pre-post SMDs should be avoided is that the scores on baseline and post-test are not independent of each other. The value for the correlation should be used in the calculation of the SMD, while this value is typically not known. We used data from an ‘individual patient data’ meta-analysis of trials comparing cognitive behaviour therapy and anti-depressive medication, to show that this problem can lead to considerable errors in the estimation of the SMDs. Another even more important reason why pre-post SMDs should be avoided in meta-analyses is that they are influenced by natural processes and characteristics of the patients and settings, and these cannot be discerned from the effects of the intervention. Between-group SMDs are much better because they control for such variables and these variables only affect the between group SMD when they are related to the effects of the intervention.ConclusionsWe conclude that pre-post SMDs should be avoided in meta-analyses as using them probably results in biased outcomes.

Download Full-text

Meta-analysis of effect sizes reported at multiple time points: A multivariate approach

Clinical Trials ◽

10.1177/1740774512453218 ◽

2012 ◽

Vol 9 (5) ◽

pp. 610-620 ◽

Cited By ~ 28

Author(s):

Thomas A Trikalinos ◽

Ingram Olkin

Keyword(s):

Random Effects ◽

Treatment Effects ◽

Multivariate Analyses ◽

Meta Analysis ◽

Effect Sizes ◽

Multiple Time ◽

Time Points ◽

Fixed And Random Effects ◽

Multiple Time Points ◽

Meta Analyses

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.

Download Full-text

A Statistical Method for Synthesizing Meta-Analyses

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/732989 ◽

2013 ◽

Vol 2013 ◽

pp. 1-9 ◽

Cited By ~ 4

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.

Download Full-text

Physical Abuse, Emotional Abuse, and Neglect and Childhood Behavior Problems: A Meta-Analysis of Studies in Mainland China

Trauma Violence & Abuse ◽

10.1177/1524838018757750 ◽

2018 ◽

Vol 21 (1) ◽

pp. 206-224 ◽

Cited By ~ 2

Author(s):

Naixue Cui ◽

Jianghong Liu

Keyword(s):

Child Maltreatment ◽

Behavior Problems ◽

Emotional Abuse ◽

Meta Analysis ◽

Mainland China ◽

Effect Sizes ◽

Childhood Behavior ◽

Abuse And Neglect ◽

Meta Analyses ◽

Childhood Behavior Problems

The relationship between three types of child maltreatment, including physical abuse, emotional abuse and neglect, and childhood behavior problems in Mainland China, has not been systematically examined. This meta-analysis reviewed findings from 42 studies conducted in 98,749 children in Mainland China and analyzed the pooled effect sizes of the associations between child maltreatment and childhood behavior problems, heterogeneity in study findings, and publication bias. In addition, this study explored cross-study similarities/differences by comparing the pooled estimates with findings from five existing meta-analyses. Equivalent small-to-moderate effect sizes emerged in the relationships between the three types of maltreatment and child externalizing and internalizing behaviors, except that emotional abuse related more to internalizing than externalizing behaviors. Considerable heterogeneity exists among the 42 studies. Weak evidence suggests that child gender and reporter of emotional abuse may moderate the strengths of the relationships between child maltreatment and behavior problems. No indication of publication bias emerged. Cross-study comparisons show that the pooled effect sizes in this meta-analysis are about equal to those reported in the five meta-analyses conducted in child and adult populations across the world. Findings urge relevant agencies in Mainland China to build an effective child protection system to prevent child maltreatment.

Download Full-text

A-027 Differentiating HIV-Associated Neurocognitive Disorder from Alzheimer’s Disease: A Neuropsychological Profile

Archives of Clinical Neuropsychology ◽

10.1093/arclin/acaa068.027 ◽

2020 ◽

Vol 35 (6) ◽

pp. 817-817

Author(s):

Eilenberger D

Keyword(s):

Alzheimer’S Disease ◽

Executive Function ◽

Episodic Memory ◽

Motor Function ◽

Effect Size ◽

Effect Sizes ◽

Neurocognitive Disorder ◽

Weighted Effect Size ◽

Weighted Effect ◽

Hiv Associated Neurocognitive Disorder

Abstract Objective This meta-analysis examined the potential for executive function, episodic memory, and motor function to differentiate HIV-associated neurocognitive disorder (HAND) from Alzheimer’s disease (AD), in an attempt to aid in accurate differential diagnosis. Data Selection The literature search identified records investigating neuropsychological test performance associated with HAND and AD. Databases used were: PsycINFO, Academic Search Complete, and Medline with Full Text. Eligibility was assessed using the following inclusion criteria: (a) study examines HAND or AD, (b) diagnosis is determined using standard diagnostic criteria, (c) study contains data regarding executive function, episodic memory, and/or motor function, (d) study published in English, (e) study is quantitative, and (f) study contains statistical information for effect size calculations. A total of 947 relevant studies were initially identified. Twenty studies were included. Data Synthesis Group difference effect sizes were converted/calculated using Cohen’s d and Cohen’s (1998) conventions. Three weighted effect sizes were calculated for constructs of interest for each disorder. Weighted effect size for executive function was large for each group (HAND d = 1.28; AD d = 1.57). A large weighted effect size for episodic memory in AD (AD d = −2.17) and a medium effect size for HAND (HAND d = −0.65) were calculated. A large weighted effect size was determined for motor function in AD (d = 3.60), while a small effect size was calculated for HAND (d = 0.27). Conclusions Level of impairment in episodic memory and motor function can be used to differentiate HAND from AD. Executive function lacked differences needed for diagnostic differentiation. Future research should be done directly comparing neuropsychological performance between HAND and AD.

Download Full-text