Objectives: The aim of this study was to describe the relationship among abstract structure, readability, and completeness, and how these features may influence social media activity and bibliometric results, considering systematic reviews (SRs) about interventions in psoriasis classified by methodological quality.
Study Design And Setting: Systematic literature searches about psoriasis interventions were undertaken on relevant databases. For each review, methodological quality was evaluated using the assessing the methodological quality of systematic reviews tool.
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.
View Article and Find Full Text PDFBackground: 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.
View Article and Find Full Text PDFObjectives: No gold standard exists to assess methodological quality of systematic reviews (SRs). Although Assessing the Methodological Quality of Systematic Reviews (AMSTAR) is widely accepted for analyzing quality, the ROBIS instrument has recently been developed. This study aimed to compare the capacity of both instruments to capture the quality of SRs concerning psoriasis interventions.
View Article and Find Full Text PDFModerate-to-severe psoriasis is associated with significant comorbidity, an impaired quality of life, and increased medical costs, including those associated with treatments. Systematic reviews (SRs) and meta-analyses (MAs) of randomized clinical trials are considered two of the best approaches to the summarization of high-quality evidence. However, methodological bias can reduce the validity of conclusions from these types of studies and subsequently impair the quality of decision making.
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