Research Synthesis Methods

Quality and clarity in systematic review abstracts: an empirical study

Journal Article


Systematic review (SR) abstracts are important for disseminating evidence syntheses to inform medical decision making. We assess reporting quality in SR abstracts using PRISMA for Abstracts (PRISMA‐A), Cochrane Handbook, and Agency for Healthcare Research & Quality guidance.


We evaluated a random sample of 200 SR abstracts (from 2014) comparing interventions in the general medical literature. We assessed adherence to PRISMA‐A criteria, problematic wording in conclusions, and whether “positive” studies described clinical significance.


On average, abstracts reported 60% of PRISMA‐A checklist items (mean 8.9 ± 1.7, range 4 to 12). Eighty percent of meta‐analyses reported quantitative measures with a confidence interval. Only 49% described effects in terms meaningful to patients and clinicians (e.g., absolute measures), and only 43% mentioned strengths/limitations of the evidence base. Average abstract word count was 274 (SD 89). Word count explained only 13% of score variability. PRISMA‐A scores did not differ between Cochrane and non‐Cochrane abstracts (mean difference 0.08, 95% confidence interval −1.16 to 1.00).

Of 275 primary outcomes, 48% were statistically significant, 32% were not statistically significant, and 19% did not report significance or results. Only one abstract described clinical significance for positive findings. For “negative” outcomes, we identified problematic simple restatements (20%), vague “no evidence of effect” wording (9%), and wishful wording (8%).


Improved SR abstract reporting is needed, particularly reporting of quantitative measures (for meta‐analysis), easily interpretable units, strengths/limitations of evidence, clinical significance, and clarifying whether negative results reflect true equivalence between treatments. Copyright © 2016 John Wiley & Sons, Ltd.

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Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.