Understanding of statistical terms routinely used in meta-analyses: an international survey among researchers.

Objective: Biomedical literature is increasingly enriched with literature reviews and meta-analyses. We sought to assess the understanding of statistical terms routinely used in such studies, among researchers.

Methods: An online survey posing 4 clinically-oriented multiple-choice questions was conducted in an international sample of randomly selected corresponding authors of articles indexed by PubMed.

Results: A total of 315 unique complete forms were analyzed (participation rate 39.4%), mostly from Europe (48%), North America (31%), and Asia/Pacific (17%). Only 10.5% of the participants answered correctly all 4 "interpretation" questions while 9.2% answered all questions incorrectly. Regarding each question, 51.1%, 71.4%, and 40.6% of the participants correctly interpreted statistical significance of a given odds ratio, risk ratio, and weighted mean difference with 95% confidence intervals respectively, while 43.5% correctly replied that no statistical model can adjust for clinical heterogeneity. Clinicians had more correct answers than non-clinicians (mean score ± standard deviation: 2.27±1.06 versus 1.83±1.14, p<0.001); among clinicians, there was a trend towards a higher score in medical specialists (2.37±1.07 versus 2.04±1.04, p = 0.06) and a lower score in clinical laboratory specialists (1.7±0.95 versus 2.3±1.06, p = 0.08). No association was observed between the respondents' region or questionnaire completion time and participants' score.

Conclusion: A considerable proportion of researchers, randomly selected from a diverse international sample of biomedical scientists, misinterpreted statistical terms commonly reported in meta-analyses. Authors could be prompted to explicitly interpret their findings to prevent misunderstandings and readers are encouraged to keep up with basic biostatistics.