Meta-analysis shows environmental contaminants elevate cortisol levels in teleost fish – Effect sizes depend on contaminant class and duration of experimental exposure

Author(s):  
Jillian Rohonczy ◽  
Katie O'Dwyer ◽  
Alicia Rochette ◽  
Stacey A. Robinson ◽  
Mark R. Forbes
2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  

‘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.


2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson

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%.


2019 ◽  
Author(s):  
Bettina Moltrecht ◽  
Jessica Deighton ◽  
Praveetha Patalay ◽  
Julian Childs

Background: Research investigating the role of emotion regulation (ER) in the development and treatment of psychopathology has increased in recent years. Evidence suggests that an increased focus on ER in treatment can improve existing interventions. Most ER research has neglected young people, therefore the present meta-analysis summarizes the evidence for existing psychosocial intervention and their effectiveness to improve ER in youth. Methods: A systematic review and meta-analysis was conducted according to the PRISMA guidelines. Twenty-one randomized-control-trials (RCTs) assessed changes in ER following a psychological intervention in youth exhibiting various psychopathological symptoms.Results: We found moderate effect sizes for current interventions to decrease emotion dysregulation in youth (g=-.46) and small effect sizes to improve emotion regulation (g=0.36). Significant differences between studies including intervention components, ER measures and populations studied resulted in large heterogeneity. Conclusion: This is the first meta-analysis that summarizes the effectiveness for existing interventions to improve ER in youth. The results suggest that interventions can enhance ER in youth, and that these improvements correlate with improvements in psychopathology. More RCTs including larger sample sizes, different age groups and psychopathologies are needed to increase our understanding of what works for who and when.


2017 ◽  
Author(s):  
Nicholas Alvaro Coles ◽  
Jeff T. Larsen ◽  
Heather Lench

The facial feedback hypothesis suggests that an individual’s experience of emotion is influenced by feedback from their facial movements. To evaluate the cumulative evidence for this hypothesis, we conducted a meta-analysis on 286 effect sizes derived from 138 studies that manipulated facial feedback and collected emotion self-reports. Using random effects meta-regression with robust variance estimates, we found that the overall effect of facial feedback was significant, but small. Results also indicated that feedback effects are stronger in some circumstances than others. We examined 12 potential moderators, and three were associated with differences in effect sizes. 1. Type of emotional outcome: Facial feedback influenced emotional experience (e.g., reported amusement) and, to a greater degree, affective judgments of a stimulus (e.g., the objective funniness of a cartoon). Three publication bias detection methods did not reveal evidence of publication bias in studies examining the effects of facial feedback on emotional experience, but all three methods revealed evidence of publication bias in studies examining affective judgments. 2. Presence of emotional stimuli: Facial feedback effects on emotional experience were larger in the absence of emotionally evocative stimuli (e.g., cartoons). 3. Type of stimuli: When participants were presented with emotionally evocative stimuli, facial feedback effects were larger in the presence of some types of stimuli (e.g., emotional sentences) than others (e.g., pictures). The available evidence supports the facial feedback hypothesis’ central claim that facial feedback influences emotional experience, although these effects tend to be small and heterogeneous.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Adineh Jafarzadeh ◽  
Alireza Mahboub-Ahari ◽  
Moslem Najafi ◽  
Mahmood Yousefi ◽  
Koustuv Dalal

Abstract Background Irrational household storage of medicines is a world-wide problem, which triggers medicine wastage as well as its associated harms. This study aimed to include all available evidences from literature to perform a focused examination of the prevalence and factors associated with medicine storage and wastage among urban households. This systematic review and meta-analysis mapped the existing literature on the burden, outcomes, and affective socio-economic factors of medicine storage among urban households. In addition, this study estimated pooled effect sizes for storage and wastage rates. Methods Household surveys evaluating modality, size, costs, and affective factors of medicines storage at home were searched in PubMed, EMBASE, OVID, SCOPUS, ProQuest, and Google scholar databases in 2019. Random effect meta-analysis and subgroup analysis were used to pool effect sizes for medicine storage and wastage prevalence among different geographical regions. Results From the 2604 initial records, 20 studies were selected for systematic review and 16 articles were selected for meta-analysis. An overall pooled-prevalence of medicine storage and real wastage rate was 77 and 15%, respectively. In this regard, some significant differences were observed between geographical regions. Southwest Asia region had the highest storage and wastage rates. The most common classes of medicines found in households belonged to the Infective agents for systemic (17.4%) and the Nervous system (16.4%). Moreover, income, education, age, the presence of chronic illness, female gender, and insurance coverage were found to be associated with higher home storage. The most commonly used method of disposal was throwing them in the garbage. Conclusions Factors beyond medical needs were also found to be associated with medicine storage, which urges effective strategies in the supply and demand side of the medicine consumption chain. The first necessary step to mitigate home storage is establishing an adequate legislation and strict enforcement of regulations on dispensing, prescription, and marketing of medicines. Patient’s pressure on excessive prescription, irrational storage, and use of medicines deserve efficient community-centered programs, in order to increase awareness on these issues. So, hazardous consequences of inappropriate disposal should be mitigated by different take back programs, particularly in low and middle income countries.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lisa Holper

Abstract Background Conditional power of network meta-analysis (NMA) can support the planning of randomized controlled trials (RCTs) assessing medical interventions. Conditional power is the probability that updating existing inconclusive evidence in NMA with additional trial(s) will result in conclusive evidence, given assumptions regarding trial design, anticipated effect sizes, or event probabilities. Methods The present work aimed to estimate conditional power for potential future trials on antidepressant treatments. Existing evidence was based on a published network of 502 RCTs conducted between 1979-2018 assessing acute antidepressant treatment in major depressive disorder (MDD). Primary outcomes were efficacy in terms of the symptom change on the Hamilton Depression Scale (HAMD) and tolerability in terms of the dropout rate due to adverse events. The network compares 21 antidepressants consisting of 231 relative treatment comparisons, 164 (efficacy) and 127 (tolerability) of which are currently assumed to have inconclusive evidence. Results Required sample sizes to achieve new conclusive evidence with at least 80% conditional power were estimated to range between N = 894 - 4190 (efficacy) and N = 521 - 1246 (tolerability). Otherwise, sample sizes ranging between N = 49 - 485 (efficacy) and N = 40 - 320 (tolerability) may require stopping for futility based on a boundary at 20% conditional power. Optimizing trial designs by considering multiple trials that contribute both direct and indirect evidence, anticipating alternative effect sizes or alternative event probabilities, may increase conditional power but required sample sizes remain high. Antidepressants having the greatest conditional power associated with smallest required sample sizes were identified as those on which current evidence is low, i.e., clomipramine, levomilnacipran, milnacipran, nefazodone, and vilazodone, with respect to both outcomes. Conclusions The present results suggest that conditional power to achieve new conclusive evidence in ongoing or future trials on antidepressant treatments is low. Limiting the use of the presented conditional power analysis are primarily due to the estimated large sample sizes which would be required in future trials as well as due to the well-known small effect sizes in antidepressant treatments. These findings may inform researchers and decision-makers regarding the clinical relevance and justification of research in ongoing or future antidepressant RCTs in MDD.


2021 ◽  
pp. 1-11
Author(s):  
Maxi Weber ◽  
Sarah Schumacher ◽  
Wiebke Hannig ◽  
Jürgen Barth ◽  
Annett Lotzin ◽  
...  

Abstract Several types of psychological treatment for posttraumatic stress disorder (PTSD) are considered well established and effective, but evidence of their long-term efficacy is limited. This systematic review and meta-analysis aimed to investigate the long-term outcomes across psychological treatments for PTSD. MEDLINE, Cochrane Library, PTSDpubs, PsycINFO, PSYNDEX, and related articles were searched for randomized controlled trials with at least 12 months of follow-up. Twenty-two studies (N = 2638) met inclusion criteria, and 43 comparisons of cognitive behavioral therapy (CBT) were available at follow-up. Active treatments for PTSD yielded large effect sizes from pretest to follow-up and a small controlled effect size compared with non-directive control groups at follow-up. Trauma-focused treatment (TFT) and non-TFT showed large improvements from pretest to follow-up, and effect sizes did not significantly differ from each other. Active treatments for comorbid depressive symptoms revealed small to medium effect sizes at follow-up, and improved PTSD and depressive symptoms remained stable from treatment end to follow-up. Military personnel, low proportion of female patients, and self-rated PTSD measures were associated with decreased effect sizes for PTSD at follow-up. The findings suggest that CBT for PTSD is efficacious in the long term. Future studies are needed to determine the lasting efficacy of other psychological treatments and to confirm benefits beyond 12-month follow-up.


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