The differential impact of scientific quality, bibliometric factors, and social media activity on the influence of systematic reviews and meta-analyses about psoriasis.

Researchers are increasingly using on line social networks to promote their work. Some authors have suggested that measuring social media activity can predict the impact of a primary study (i.e., whether or not an article will be highly cited). However, the influence of variables such as scientific quality, research disclosures, and journal characteristics on systematic reviews and meta-analyses has not yet been assessed. The present study aims to describe the effect of complex interactions between bibliometric factors and social media activity on the impact of systematic reviews and meta-analyses about psoriasis (PROSPERO 2016: CRD42016053181). Methodological quality was assessed using the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool. Altmetrics, which consider Twitter, Facebook, and Google+ mention counts as well as Mendeley and SCOPUS readers, and corresponding article citation counts from Google Scholar were obtained for each article. Metadata and journal-related bibliometric indices were also obtained. One-hundred and sixty-four reviews with available altmetrics information were included in the final multifactorial analysis, which showed that social media and impact factor have less effect than Mendeley and SCOPUS readers on the number of cites that appear in Google Scholar. Although a journal's impact factor predicted the number of tweets (OR, 1.202; 95% CI, 1.087-1.049), the years of publication and the number of Mendeley readers predicted the number of citations in Google Scholar (OR, 1.033; 95% CI, 1.018-1.329). Finally, methodological quality was related neither with bibliometric influence nor social media activity for systematic reviews. In conclusion, there seems to be a lack of connectivity between scientific quality, social media activity, and article usage, thus predicting scientific success based on these variables may be inappropriate in the particular case of systematic reviews.

Abstract analysis method facilitates filtering low-methodological quality and high-bias risk systematic reviews on psoriasis interventions.

BACKGROUND: Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone. METHODS: Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company. RESULTS: This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score < 6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ≥ 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk. CONCLUSIONS: The methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.