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The objective of the study is to identify items and domains applicable for the quality assessment of prevalence studies. We searched databases and the gray literature to identify tools or guides about the quality assessment of prevalence studies. After study selection, we abstracted questions applicable for prevalence studies and classified into at least one of the following domains: ‘population and setting’, ‘condition measurement’, ‘statistics’, and ‘other’. PROSPERO registration:CRD42018088437. We included 30 tools: eight (26.7%) specifically designed to appraise prevalence studies and 22 (73.3%) adaptable for this purpose. We identified 12 unique items in the domain “population and setting”, 16 in the domain “condition measurement”, and 14 in the domain “statistics”. Of those, 25 (59.5%) were identified in the eight specific tools. Regarding the domain “other”, we identified 77 unique items, mainly related to manuscript writing and reporting (n = 48, 62.3%); of those, 24 (31.2%) were identified in the eight specific tools and 53 (68.8%) in the additional 22 nonspecific tools. We provide a comprehensive set of items classified by domains that can guide the appraisal of prevalence studies, conduction of primary prevalence studies, and update or development of tools to evaluate prevalence studies.

Background There is a notable lack of methodological and reporting guidance for systematic reviews of prevalence data. This information void has the potential to result in reviews that are inconsistent and inadequate to inform healthcare policy and decision making. The aim of this meta-epidemiological study is to describe the methodology of recently published prevalence systematic reviews. Methods We searched MEDLINE (via PubMed) from February 2017 to February 2018 for systematic reviews of prevalence studies. We included systematic reviews assessing the prevalence of any clinical condition using patients as the unit of measurement and we summarized data related to reporting and methodology of the reviews. Results A total of 235 systematic reviews of prevalence were analyzed. The median number of authors was 5 (interquartile range [IQR] 4–7), the median number of databases searched was 4 (3–6) and the median number of studies included in each review was 24 (IQR 15–41.5). Search strategies were presented for 68% of reviews. Forty five percent of reviews received external funding, and 24% did not provide funding information. Twenty three percent of included reviews had published or registered the systematic review protocol. Reporting guidelines were used in 72% of reviews. The quality of included studies was assessed in 80% of reviews. Nine reviews assessed the overall quality of evidence (4 using GRADE). Meta-analysis was conducted in 65% of reviews; 1% used Bayesian methods. Random effect meta-analysis was used in 94% of reviews; among them, 75% did not report the variance estimator used. Among the reviews with meta-analysis, 70% did not report how data was transformed; 59% percent conducted subgroup analysis, 38% conducted meta-regression and 2% estimated prediction interval; I 2 was estimated in 95% of analysis. Publication bias was examined in 48%. The most common software used was STATA (55%). Conclusions Our results indicate that there are significant inconsistencies regarding how these reviews are conducted. Many of these differences arose in the assessment of methodological quality and the formal synthesis of comparable data. This variability indicates the need for clearer reporting standards and consensus on methodological guidance for systematic reviews of prevalence data.

To investigate whether Appraisal of Guidelines for Research & Evaluation (AGREE) II users apply a cut-off based on standardized domain scores or overall guideline quality to distinguish between high- and low-quality guidelines, as well as to investigate which criteria they use to generate this cut-off and which type of cut-off they apply. We conducted a systematic search in MEDLINE, EMBASE, DARE, and the HTA-database for German- and English-language studies appraising guidelines with AGREE II. Information on cut-offs was extracted and analyzed descriptively. We identified 118 relevant publications. Thirty-nine (33%) used a cut-off, of which 24 (62%) used a 2-step and 13 (33%) used a 3-step approach. The cut-off for high quality lay between 50% and 70% (2-step) and 60% and 83% (3-step) of the highest possible rating. Twenty-four (62%) publications applied a cut-off based on standardized domain scores and 7 (18%) based on overall guideline quality. Eleven (28%) applied cut-offs to derive the recommendation for guideline use. A third of AGREE II users apply a cut-off to distinguish between high- and low-quality guidelines, often without clearly describing how the cut-off is generated. Many users might welcome a clear distinction between high- and low-quality guidelines; specifying a cut-off for this purpose might be useful. •In contrast to the specification of Appraisal of Guidelines for Research & Evaluation (AGREE)-II, a third of AGREE II users apply a cut-off to distinguish between high- and low-quality guidelines, often without clearly describing how the cut-off is generated.•Users in our analysis applied a 2- or 3-step cut-off.•Some of the AGREE II users who applied a cut-off mentioned the rationale for applying it.•In some cases, recommendation for use was derived from the cut-off based ratings of domains or overall guideline quality.•AGREE II users might welcome a clear distinction between high- and low-quality guidelines; specifying a cut-off for this purpose might be a useful approach.•Need of standardization of a procedure and its specification in AGREE II.

Background The AGREE II instrument is the most commonly used guideline appraisal tool. It includes 23 appraisal criteria (items) organized within six domains. AGREE II also includes two overall assessments (overall guideline quality, recommendation for use). Our aim was to investigate how strongly the 23 AGREE II items influence the two overall assessments. Methods An online survey of authors of publications on guideline appraisals with AGREE II and guideline users from a German scientific network was conducted between 10th February 2015 and 30th March 2015. Participants were asked to rate the influence of the AGREE II items on a Likert scale (0 = no influence to 5 = very strong influence). The frequencies of responses and their dispersion were presented descriptively. Results Fifty-eight of the 376 persons contacted (15.4%) participated in the survey and the data of the 51 respondents with prior knowledge of AGREE II were analysed. Items 7–12 of Domain 3 (rigour of development) and both items of Domain 6 (editorial independence) had the strongest influence on the two overall assessments. In addition, Items 15–17 (clarity of presentation) had a strong influence on the recommendation for use. Great variations were shown for the other items. The main limitation of the survey is the low response rate. Conclusions In guideline appraisals using AGREE II, items representing rigour of guideline development and editorial independence seem to have the strongest influence on the two overall assessments. In order to ensure a transparent approach to reaching the overall assessments, we suggest the inclusion of a recommendation in the AGREE II user manual on how to consider item and domain scores. For instance, the manual could include an a-priori weighting of those items and domains that should have the strongest influence on the two overall assessments. The relevance of these assessments within AGREE II could thereby be further specified.

To compare the methodological and reporting quality of systematic reviews by authors from China and those from the United States (USA). From systematic reviews of randomized trials published in 2014 in English, we randomly selected 100 from China and 100 from the USA. The methodological quality was assessed using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool, and reporting quality assessed using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) tool. Compared with systematic reviews from the USA, those from China were more likely to be a meta-analysis, published in low-impact journals, and a non-Cochrane review. The mean summary Assessing the Methodological Quality of Systematic Reviews score was 6.7 (95% confidence interval: 6.5, 7.0) for reviews from China and 6.6 (6.1, 7.1) for reviews from the USA, and the mean summary Preferred Reporting Items for Systematic Reviews and Meta-analyses score was 21.2 (20.7, 21.6) for reviews from China and 20.6 (19.9, 21.3) for reviews from the USA. The differences in summary quality scores between China and the USA were statistically nonsignificant after adjusting for multiple review factors. The overall methodological and reporting quality of systematic reviews by authors from China are similar to those from the USA, although the quality of systematic reviews from both countries could be further improved.

Background Systematic Reviews (SRs) of experimental animal studies are not yet common practice, but awareness of the merits of conducting such SRs is steadily increasing. As animal intervention studies differ from randomized clinical trials (RCT) in many aspects, the methodology for SRs of clinical trials needs to be adapted and optimized for animal intervention studies. The Cochrane Collaboration developed a Risk of Bias (RoB) tool to establish consistency and avoid discrepancies in assessing the methodological quality of RCTs. A similar initiative is warranted in the field of animal experimentation. Methods We provide an RoB tool for animal intervention studies (SYRCLE’s RoB tool). This tool is based on the Cochrane RoB tool and has been adjusted for aspects of bias that play a specific role in animal intervention studies. To enhance transparency and applicability, we formulated signalling questions to facilitate judgment. Results The resulting RoB tool for animal studies contains 10 entries. These entries are related to selection bias, performance bias, detection bias, attrition bias, reporting bias and other biases. Half these items are in agreement with the items in the Cochrane RoB tool. Most of the variations between the two tools are due to differences in design between RCTs and animal studies. Shortcomings in, or unfamiliarity with, specific aspects of experimental design of animal studies compared to clinical studies also play a role. Conclusions SYRCLE’s RoB tool is an adapted version of the Cochrane RoB tool. Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies. This may subsequently enhance the efficiency of translating animal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies.

The objectives of this study were to determine the interrater reliability (IRR) of assessment of multiple systematic reviews (AMSTAR) 2 for reviews of pharmacological or psychological interventions for the treatment of major depression, to compare it to that of AMSTAR and risk of bias in systematic reviews (ROBIS), and to assess the convergent validity between the appraisal tools. Two groups of four raters were each assigned one of two samples of 30 systematic reviews. All eight raters applied AMSTAR 2 to their sample. Each group also applied either AMSTAR or ROBIS. Fleiss' kappa and Gwet's AC1 were calculated, and agreement between the tools was assessed. The median kappa values as a measure of IRR indicated a moderate agreement for AMSTAR 2 (median = 0.51), a substantial agreement for AMSTAR (median = 0.62), and a fair agreement for ROBIS (median = 0.27). Validity results showed a positive association for AMSTAR and AMSTAR 2 (r = 0.91) as well as ROBIS and AMSTAR 2 (r = 0.84). For the overall rating, AMSTAR 2 showed a high concordance with ROBIS and a lower concordance with AMSTAR. The IRR of AMSTAR 2 was found to be slightly lower than the IRR of AMSTAR and higher than the IRR of ROBIS. Validity measurements indicate that AMSTAR 2 is closely related to both ROBIS and AMSTAR.

Data continue to accumulate indicating that many systematic reviews are methodologically flawed, biased, redundant, or uninformative. Some improvements have occurred in recent years based on empirical methods research and standardization of appraisal tools; however, many authors do not routinely or consistently apply these updated methods. In addition, guideline developers, peer reviewers, and journal editors often disregard current methodological standards. Although extensively acknowledged and explored in the methodological literature, most clinicians seem unaware of these issues and may automatically accept evidence syntheses (and clinical practice guidelines based on their conclusions) as trustworthy. A plethora of methods and tools are recommended for the development and evaluation of evidence syntheses. It is important to understand what these are intended to do (and cannot do) and how they can be utilized. Our objective is to distill this sprawling information into a format that is understandable and readily accessible to authors, peer reviewers, and editors. In doing so, we aim to promote appreciation and understanding of the demanding science of evidence synthesis among stakeholders. We focus on well-documented deficiencies in key components of evidence syntheses to elucidate the rationale for current standards. The constructs underlying the tools developed to assess reporting, risk of bias, and methodological quality of evidence syntheses are distinguished from those involved in determining overall certainty of a body of evidence. Another important distinction is made between those tools used by authors to develop their syntheses as opposed to those used to ultimately judge their work. Exemplar methods and research practices are described, complemented by novel pragmatic strategies to improve evidence syntheses. The latter include preferred terminology and a scheme to characterize types of research evidence. We organize best practice resources in a Concise Guide that can be widely adopted and adapted for routine implementation by authors and journals. Appropriate, informed use of these is encouraged, but we caution against their superficial application and emphasize their endorsement does not substitute for in-depth methodological training. By highlighting best practices with their rationale, we hope this guidance will inspire further evolution of methods and tools that can advance the field.

To evaluate reporting of abstracts of systematic reviews according to the preferred reporting items for systematic reviews and meta-analyses for abstracts (PRISMA-A) 2013 checklist. A random sample of 534 systematic reviews on effectiveness indexed in PubMed between 2000 and 2019 was assessed. Adherence of abstracts to PRISMA-A was analysed using descriptive statistics. Results were stratified by number of words, structure, and year of publication. The mean score of fully reported PRISMA-A items was 5.4 of 12, with adherence varying widely between items (0% to 98.8%). Cochrane reviews received higher mean total scores than non-Cochrane reviews (6.3 vs. 5.2). Adherence to PRISMA-A increased linearly with increasing word count. In non-Cochrane reviews, authors of structured abstracts more often adhered to PRISMA-A than those of unstructured abstracts. No improvements in reporting of abstracts were found after the implementation of PRISMA-A in 2013. Adherence to PRISMA-A shows great potential for improvement. Therefore, authors, editors, and reviewers should be made aware of PRISMA-A by referring to it in the journal submission guidelines. As adherence to PRISMA-A increases with the number of words, journals should consider to increase the word limit to 250–300 words.

The number of published meta‐analyses in plant ecology has increased greatly over the last two decades. Meta‐analysis has made a significant contribution to the field, allowing review of evidence for various ecological hypotheses and theories, estimation of effects of major environmental drivers (climate change, habitat fragmentation, invasive species, air pollution), assessment of management and conservation strategies, and comparison of effects across different temporal and spatial scales, taxa and ecosystems, as well as research gap identification. We identified 322 meta‐analyses published in the field of plant ecology between 1996 and 2013 in 95 different journals and assessed their methodological and reporting quality according to standard criteria. Despite significant recent developments in the methodology of meta‐analysis, the quality of published meta‐analyses was uneven and showed little improvement over time. We found many cases of imprecise and inaccurate usage of the term ‘meta‐analysis’ in plant ecology, particularly confusion between meta‐analysis and vote counting and incorrect application of statistical techniques designed for primary studies to meta‐analytical data, without recognition of the violation of statistical assumptions of the analyses. Methodological issues for meta‐analyses in plant ecology include incomplete reporting of search strategy used to retrieve primary studies, failure to test for possible publication bias and to conduct sensitivity analysis to test the robustness of the results, as well as lack of availability of the data set used for the analyses. The use of meta‐analysis is particularly common in community ecology, ecophysiology and ecosystem ecology, but meta‐analyses in ecophysiology are more likely not to meet standard quality criteria than papers in other subdisciplines. Fewer meta‐analyses have been conducted in plant population ecology. Synthesis. Over the past two decades, plant ecologists have embraced meta‐analysis as a statistical tool to combine results across studies, and much has been learned as a result. However, as the popularity and usage of meta‐analysis in the field of plant ecology has grown, establishment of quality standards, as has been done in other disciplines, becomes increasingly important. In order to improve the quality of future meta‐analyses in plant ecology, we suggest adoption of a checklist of quality criteria for meta‐analysis for use by research synthesists, peer reviewers and journal editors.