The Banksia plot: a method for visually comparing point estimates and confidence intervals across datasets.

Objectives: In research evaluating statistical analysis methods, a common aim is to compare point estimates and CIs calculated from different analyses. This can be challenging when the outcomes (and their scale ranges) differ across datasets. We therefore developed a graphical method, the "Banksia plot", to facilitate pairwise comparisons of different statistical analysis methods by plotting and comparing point estimates and CIs from each analysis method, both within and across datasets.

The association of adverse birth outcomes with flood exposure before and during pregnancy in Australia: a cohort study.

Background: Exposure to floods might increase the risks of adverse birth outcomes. However, the current evidence is scarce, inconsistent, and has knowledge gaps. This study aims to estimate the associations of flood exposure before and during pregnancy with adverse birth outcomes and to identify susceptible exposure windows and effect modifiers.

Identification of application and interpretation errors that can occur in pairwise meta-analyses in systematic reviews of interventions: a systematic review.

Objectives: To generate a bank of items describing application and interpretation errors that can arise in pairwise meta-analyses in systematic reviews of interventions.

Study Design And Setting: MEDLINE, Embase, and Scopus were searched to identify studies describing types of errors in meta-analyses. Descriptions of errors and supporting quotes were extracted by multiple authors.

Development of a search filter to retrieve reports of interrupted time series studies from MEDLINE and PubMed.

Background: Interrupted time series (ITS) studies contribute importantly to systematic reviews of population-level interventions. We aimed to develop and validate search filters to retrieve ITS studies in MEDLINE and PubMed.

Methods: A total of 1017 known ITS studies (published 2013-2017) were analysed using text mining to generate candidate terms.

A brief note on the common (fixed)-effect meta-analysis model.

Meta-analysis is a statistical method used to combine results from multiple studies, providing a quantitative summary of their findings. One of the fundamental decisions in conducting a meta-analysis is choosing an appropriate model to estimate the overall effect size and its CI. In this article, we focus on the common-effect (also referred to as the fixed-effect) model, and in a companion article, the random-effects model.

Comparison of statistical methods used to meta-analyse results from interrupted time series studies: an empirical study.

Background: The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data.

Investigation of bias due to selective inclusion of study effect estimates in meta-analyses of nutrition research.

We aimed to explore, in a sample of systematic reviews (SRs) with meta-analyses of the association between food/diet and health-related outcomes, whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available. We randomly selected SRs of food/diet and health-related outcomes published between January 2018 and June 2019. We selected the first presented meta-analysis in each review (index meta-analysis), and extracted from study reports all study effect estimates that were eligible for inclusion in the meta-analysis.

Variation observed in consensus judgments between pairs of reviewers when assessing the risk of bias due to missing evidence in a sample of published meta-analyses of nutrition research.

Objectives: To evaluate the risk of bias due to missing evidence in a sample of published meta-analyses of nutrition research using the Risk Of Bias due to Missing Evidence (ROB-ME) tool and determine inter-rater agreement in assessments.

Study Design And Setting: We assembled a random sample of 42 meta-analyses of nutrition research. Eight assessors were randomly assigned to one of four pairs.

The PRISMATIC project: protocol for a research programme on novel methods to improve reporting and peer review of systematic reviews of health evidence.

Background: Incomplete reporting about what systematic reviewers did and what they found prevents users of the report from being able to fully interpret the findings and understand the limitations of the underlying evidence. Reporting guidelines such as the PRISMA statement and its extensions are designed to improve reporting. However, there are important inconsistencies across the various PRISMA reporting guidelines, which causes confusion and misinterpretation.

Mortality risks associated with floods in 761 communities worldwide: time series study.

Objective: To evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.

Design: Time series study.

Setting: 761 communities in 35 countries or territories with at least one flood event during the study period.

Critical elements of synthesis questions are incompletely reported: survey of systematic reviews of intervention effects.

Objectives: To examine the characteristics of population, intervention and outcome groups and the extent to which they were completely reported for each synthesis in a sample of systematic reviews (SRs) of interventions.

Study Design And Setting: We coded groups that were intended (or used) for comparisons in 100 randomly sampled SRs of public health and health systems interventions published in 2018 from the Health Evidence and Health Systems Evidence databases.

Results: Authors commonly used population, intervention and outcome groups to structure comparisons, but these groups were often incompletely reported.

Evaluation of statistical methods used to meta-analyse results from interrupted time series studies: A simulation study.

Interrupted time series (ITS) are often meta-analysed to inform public health and policy decisions but examination of the statistical methods for ITS analysis and meta-analysis in this context is limited. We simulated meta-analyses of ITS studies with continuous outcome data, analysed the studies using segmented linear regression with two estimation methods [ordinary least squares (OLS) and restricted maximum likelihood (REML)], and meta-analysed the immediate level- and slope-change effect estimates using fixed-effect and (multiple) random-effects meta-analysis methods. Simulation design parameters included varying series length; magnitude of lag-1 autocorrelation; magnitude of level- and slope-changes; number of included studies; and, effect size heterogeneity.

Effect estimates can be accurately calculated with data digitally extracted from interrupted time series graphs.

Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis.

Interventions from pregnancy to two years after birth for parents experiencing complex post-traumatic stress disorder and/or with childhood experience of maltreatment.

Background: Acceptable, effective and feasible support strategies (interventions) for parents experiencing complex post-traumatic stress disorder (CPTSD) symptoms or with a history of childhood maltreatment may offer an opportunity to support parental recovery, reduce the risk of intergenerational transmission of trauma and improve life-course trajectories for children and future generations. However, evidence relating to the effect of interventions has not been synthesised to provide a comprehensive review of available support strategies. This evidence synthesis is critical to inform further research, practice and policy approaches in this emerging area.

Synthesis methods other than meta-analysis were commonly used but seldom specified: survey of systematic reviews.

Objectives: To examine the specification and use of summary and statistical synthesis methods, focusing on synthesis methods other than meta-analysis.

Study Design And Setting: We coded the specification and use of summary and synthesis methods in 100 randomly sampled systematic reviews (SRs) of public health and health systems interventions published in 2018 from the Health Evidence and Health Systems Evidence databases.

Results: Sixty of the 100 SRs used other synthesis methods for some (27/100) or all syntheses (33/100).

Conceptualizing the reporting of living systematic reviews.

Objectives: As part of an effort to develop an extension of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 statement for living systematic reviews (LSRs), we discuss conceptual issues relevant to the reporting of LSRs and highlight a few challenges.

Methods: Discussion of conceptual issues based on a scoping review of the literature and discussions among authors.

Results: We first briefly describe aspects of the LSR production process relevant to reporting.

[The PRISMA 2020 statement: an updated guideline for reporting systematic reviewsDeclaración PRISMA 2020: una guía actualizada para la publicación de revisiones sistemáticas].

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies.

Changing patterns in reporting and sharing of review data in systematic reviews with meta-analysis of the effects of interventions: cross sectional meta-research study.

Objectives: To examine changes in completeness of reporting and frequency of sharing data, analytical code, and other review materials in systematic reviews over time; and factors associated with these changes.

Design: Cross sectional meta-research study.

Population: Random sample of 300 systematic reviews with meta-analysis of aggregate data on the effects of a health, social, behavioural, or educational intervention.

Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement.

Objective: To develop a reporting guideline for overviews of reviews of healthcare interventions.

Design: Development of the preferred reporting items for overviews of reviews (PRIOR) statement.

Participants: Core team (seven individuals) led day-to-day operations, and an expert advisory group (three individuals) provided methodological advice.

Effectiveness of aromatherapy for prevention or treatment of disease, medical or preclinical conditions, and injury: protocol for a systematic review and meta-analysis.

Background: Aromatherapy - the therapeutic use of essential oils from plants (flowers, herbs or trees) to treat ill health and promote physical, emotional and spiritual well-being - is one of the most widely used natural therapies reported by consumers in Western countries. The Australian Government Department of Health (via the National Health and Medical Research Council) has commissioned a suite of independent evidence evaluations to inform the 2019-20 Review of the Australian Government Rebate on Private Health Insurance for Natural Therapies. This protocol is for one of the evaluations: a systematic review that aims to examine the effectiveness of aromatherapy in preventing and/or treating injury, disease, medical conditions or preclinical conditions.